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212 publications mentioning hsa-mir-103b-1 (showing top 100)

Open access articles that are associated with the species Homo sapiens and mention the gene name mir-103b-1. Click the [+] symbols to view sentences that include the gene name, or the word cloud on the right for a summary.

1
[+] score: 472
Interestingly, we found that over -expression of miR-103 using Ad-miR-103 (adenovirus inserted with miR-103) down-regulates the expression of PANK3, whereas suppression of miR-103 leads to up-regulation of PANK3 (Figure 3B, C) by using miR-103-antisense -inhibitor, a small, chemically modified single-stranded RNA molecule designed to specifically bind to and inhibit endogenous miRNA molecules. [score:17]
Over -expression of miR-103 down-regulates the expression of PANK3 in GMEC, whereas suppression of miR-103 leads to up-regulation of PANK3. [score:13]
Based on the similar expression profiles of transcriptional factors and their downstream targets, we speculated that up-regulation of genes associated with the milk fat synthesis in miR-103 over -expression background may be due to the increased expression of PPARγ, SREBP-1c, and LXRα in GMEC. [score:12]
Goat specific miR-103 -inhibitor (antisense inhibitor for miR-103) (Anti-miR™ miRNA Inhibitor) and inhibitor negative control antisense oligonucleotide (Anti-miR™ miRNA Inhibitor Negative Control [#]1) were purchased from Invitrogen (USA). [score:11]
The levels of PDK4, glutamate dehydrogenase 1(GUD1, data not show), ACSL1 and ACOX1 were decreased as miR-103 over-expressed, and their expression were increased as miR-103 expression suppressed (data not show). [score:9]
The up-regulation of LPL and SLC27A6 are in accordance with the increased total fatty acid content (Figure 4D) and up-regulated C16:0 content (Figure 4F), suggesting that a higher level of fatty acid utilization is triggered by augmented miR-103 expression. [score:9]
For triglyceride synthesis, expression of DGA1 (1.21-fold, p<0.05) and S CD (2.87-fold, p<0.05) was up-regulated with elevated miR-103 expression, supporting our previous findings that triglyceride content and unsaturated fatty acids content were both increased in epithelial cells (Figure 4C, E). [score:8]
Through suppression of ACSL1 and ACOX1 expression, miR-103 may decrease the whole β-oxidation level and up-regulate acetyl-CoA amounts for fatty acid and triglyceride synthesis to meet the huge milk demands needed during mid-lactation. [score:8]
Over -expression or suppression of miR-103 was conducted by using Ad-miR-103 or miR-103 inhibitor as controls, respectively. [score:7]
Figure S3 MiR-103 expression in GMEC treated with Ad and inhibitor control (treatments are Ad-miR-103 and miR-103 inhibitor). [score:7]
Over -expression of miR-103 increases the mRNA expression level of LEP (A), whereas decreases the mRNA expression level of AMPKα (B). [score:7]
Relative mRNA expression in miR-103 over -expression or suppression background. [score:7]
In contrast, to the increased milk fat resulting from miR-103 over -expression, suppression of miR-103 expression had no effect on fat droplet accumulation (data not show). [score:7]
PPARγ, peroxisome proliferator-activated receptor γ; SREBP-1c, sterol regulatory element -binding protein-1c; LXRα,nuclear oxysterol receptorα;other gene symbols were listed in Table 1. Over -expression of miR-103 down-regulates the mRNA levels of HSL (A), ATGL (B), ACSL1(C), CPT1 (D), PPARα (E) and ACOX1 (F). [score:7]
QRT-PCR analysis (Figure S2) indicated that miR-103 over -expression significantly increased LEP mRNA expression relative to controls, while it decreased the expression of AMPKα, which is consistent with an increase in fatty acid content and a decrease in β-oxidation levels. [score:7]
Ectopic expression of miR-103 in preadipocyte 3T3-L1 cells up-regulated adipogenesis markers and increased triglyceride accumulation at an early stage of adipogenesis [47], while miR-103 silencing in OB/OB mice resulted in reduced levels of fat-pad weights [48]. [score:6]
Previous studies have shown that miR-103 is generally expressed in different tissues and cells [42], [43], [44], while differentially expressed during adipogenesis [45] and development [46]. [score:6]
*, p<0.05; C: Elevated miR-103 expression up-regulates triglyceride content. [score:6]
The entire gene network that controlls the milk fat synthesis, was up-regulated, supporting our previous findings that miR-103 over -expression increased the amount of fat droplets, as well as the contents of triglycerides and fatty acids. [score:6]
We compared miR-103 expression in mammary gland at two different physiological stages by quantitative Real-time PCR (qRT-PCR) and found the expression level of miR-103 was higher (4.3-fold, p<0.05) during the mid-lactation period than that in the dry period (Figure 2), suggesting that miR-103 may be involved in regulating lactation or development of the adult mammary gland. [score:6]
Fatty acids produced from lipolysis are transported by long-chain acyl-CoA synthetase 1 (ACSL1, a predicted target of miR-103 [Table S3]), enter into mitochondria by carnitine palmitoyltransferase (CPT1), and undergoes β-oxidation which is regulated by peroxisome proliferator-activated receptor α (PPARα) and acyl-CoA oxidase 1 (ACOX1, a predicted target of miR-103 [Table S3]) [41]. [score:6]
0079258.g006 Figure 6Over -expression of miR-103 down-regulates the mRNA levels of HSL (A), ATGL (B), ACSL1(C), CPT1 (D), PPARα (E) and ACOX1 (F). [score:6]
Furthermore, for fat droplet formation, the up-regulated expression of ADRP (18.02-fold, p<0.05) was consistent with the increased fat droplets in Ad-miR-103-infected cells (Figure 4B). [score:6]
Suppression of β-oxidation resulted in a down-regulation of energy supplies; however Ad-miR-103-infected cells still accumulated more triglycerides. [score:6]
And inhibitor-control doesn’t alter miR-103 expression by itself (Figure S3). [score:5]
MiR-103 was co-regulated with PANK and miR-103 also can regulate PANK expression though an unknown pathway. [score:5]
0079258.g005 Figure 5Elevated miR-103 expression promotes the expression levels of PPARγ (A), DGAT1(B), ABCA1(C), LXRα (D), ABCG1(E), SREBP-1c(F) FASN (G), and ACACA (H). [score:5]
The expression profiles of ACSL1, CPT1, PPARα, and ACOX1 were quite different; however their expression in Ad-miR-103-infected cells was lower than the Ad control (Figure 6C-F). [score:5]
MiR-103, one of the 30 most abundantly expressed miRNAs in the lactating mammary gland, controls gene expression (Figure 7), goat milk fat accumulation, as well as the ratio of unsaturated/saturated fatty acids. [score:5]
MiR-103 up-regulates gene expression associated with the milk fat synthesis process in GMEC. [score:5]
Over -expression of miR-103 transcriptionally hastens the expression of key transcription factors controlling the milk fat synthesis. [score:5]
We found that miR-103 had the lowest expression level with 60 nM inhibitor-control (Figure 3B). [score:5]
And the expression levels of miR-103 were determined at 48 h after transfecting GMEC with inhibitor-control. [score:5]
To validate miR-103 target genes, we measured the expression of miR-103 predicted targets (Table S3). [score:5]
SREBP-1c (Figure 5F) showed a different expression profile with FASN (Figure 5G) and ACACA (Figure 5H); however, the expression of these three genes in Ad-miR-103-infected cells was always greater than that of Ad-infected cells. [score:5]
Inhibitor control has no effect on miR-103 expression at any concentration. [score:5]
Elevated miR-103 expression decreases gene expression associated with lipolysis and β-oxidation. [score:5]
However, we have not yet obtained direct proof that one of these genes is a direct target of miR-103. [score:5]
Intensity scatter plot shows comparison of expression of miR-103 and PANK3; B: The optimal MOI (200) of Ad-miR-103 for infection and dose of miR-103 -inhibitor for transfection (60 nM). [score:5]
Elevated miR-103 expression promotes the expression levels of PPARγ (A), DGAT1(B), ABCA1(C), LXRα (D), ABCG1(E), SREBP-1c(F) FASN (G), and ACACA (H). [score:5]
Even so, we have used MFOLD software to analyze the ΔG of the 80 bp flanking sequence of a miR-103 binding site on these predicted targets, and have constructed miR-103 sensors using pGL3-control luciferase reporter vector inserted into the XbaI locus with 100-200 bp miRNA binding site of targets. [score:5]
One possible explanation for this is that other miRNAs in the miR-103 family (e. g., miR-107), or synergic miRNAs which target genes in conjunction with miR-103, could regulate fatty acid synthesis, compensating for miR-103 knockdown. [score:5]
However, miR-103 expression had little effect on the expression of JAK1 and other genes. [score:5]
Inhibitor-control was used as control for miR-103 -inhibitor-control. [score:5]
In the mammary glands of lactating goats, we found that miRNAs associated with cell proliferation (miR-26a, miR-21), conferring epithelial phenotype (miR-29a, miR-30a/d), immune response and development (miR-181, let-7a/b/f/g/i) were abundantly expressed, as well as miRNAs involved in lipid metabolism (miR-103, miR-23a, miR-27b, miR-200a/b/c). [score:4]
Gene expression in Ad(control)-infected, Ad-miR-103-infected, and uninfected cells was assessed at 0, 24, 48, and 72 h. qRT-PCR measurement of gene expression expressed as fold change compared to their respective level at 0 h, normalized to 1. Columns, average of 12 experiments; bars, SEM. [score:4]
Figure S2 MiR-103 increases LEP expression and decreases AMPKα expression. [score:4]
One possible explanation is that the suppression of miR-103 could be compensated by other redundant signaling pathways and thereby, knockdown of miR-103 alone does not affect fat droplet formation. [score:4]
Gene expression in Ad(control)-infected, Ad-miR-103-infected, and uninfected GMEC was assessed at 0, 24, 48, and 72 h. qRT-PCR measurement of gene expression expressed as fold change compared to their respective level at 0 h, normalized to 1. Columns, average of 12 experiments; bars, SEM. [score:4]
Genes associated with milk fat metabolism are shown to be positively (arrowheads) or negatively (end lines) regulated by miR-103 over-expressed. [score:4]
Gene expression in Ad-infected, Ad-miR-103-infected, and uninfected cells was assessed at 0, 24, 48, and 72 h. qRT-PCR measurement of gene expression expressed as fold change compared to their respective level at 0 h. Columns, average of 12 experiments; bars, SEM. [score:4]
0079258.g007 Figure 7 Genes associated with milk fat metabolism are shown to be positively (arrowheads) or negatively (end lines) regulated by miR-103 over-expressed. [score:4]
MOI of Ad-miR-103 and concentration of inhibitor is shown under X coordinate axis. [score:3]
The expression levels of miR-103 were determined at 72 h after infecting GMEC with Ad. [score:3]
To this end, we generated a recombinant adenovirus expressing miR-103 (Ad-miR-103), and investigated the effect of elevated expression of miR-103 on milk fat synthesis using goat mammary gland epithelial cells (GMEC). [score:3]
Additionally, no miR-103 binding sites were found in the 3′, 5′or the coding region of PANK3, indicating that this regulation is indirect. [score:3]
Over -expression of miR-103 can increase fat droplet, triglyceride, and fatty acid contents, which had been identified in the manuscript. [score:3]
We found that lipolysis in GMEC is not the main way to provide fatty acids for β-oxidation, for the mRNA expression of lipolysis-related genes (e. g., HSL and ATGL) are relatively low in normal and Ad-miR-103-infected cells (data not show). [score:3]
We presented novel data concerning miR-103 expression in lactating goats using a Solexa sequencing approach. [score:3]
Elevated miR-103 expression alters fatty acid composition in GMEC. [score:3]
MiR-103 expression was higher in Ad-miR-103-infected cells than that in Ad-infected cells, (2.42-fold, p<0.05, Figure 3B) at a MOI of 200. [score:3]
These transcription factors and their downstreams are not predicted targets of miR-103. [score:3]
Over -expression of miR-103 promotes milk fat droplet accumulation in GMEC. [score:3]
To investigate how miR-103 affects milk fat synthesis, we assessed the expression of key genes involved in these processes at 72 h in GMEC that over -expressing miR-103 (Table 1). [score:3]
A: Over -expression of miR-103 promotes fat accumulation. [score:3]
Ad can make a slight decrease in miR-103 expression at a MOI of ≥300. [score:3]
We compared the fat droplet formation between cells over -expressing miR-103 and controls that included cells infected by adenovirus (Ad) without any miRNA sequences and uninfected cells by using oil red O. With an optimal dose (multiplicity of infection: 200), we found that over -expression of miR-103 causes significantly increased fat droplet accumulation compared to Ad-control and uninfected cells (Figure 4A, B). [score:3]
In addition, some predicted targets of miR-103 (i. e., Long-chain acyl-CoA synthetase 1[ACSL1]) are involved in lactation [41]. [score:3]
*, p<0.05; E: Over -expression of miR-103 reduces total saturated fatty acids and promotes total unsaturated fatty acids. [score:3]
Transfection GMEC with antisense inhibitor of miR-103. [score:3]
For de novo fatty acid synthesis, expression levels of FASN and ACACA in Ad-miR-103-infected cells were significantly higher than in control groups (Ad-infected cells) (1.15-fold, p<0.05; 1.57-fold, p<0.05). [score:3]
*, p<0.05; F: Over -expression of miR-103 alters the composition of major types of fatty acids in GMEC. [score:3]
This correlation between miR-103-1 and PANK3 expression suggests that the function of miR-103-1 may be related to PANK3's; thereby miR-103 might modulate milk fat synthesis. [score:3]
Arrows indicate Ad- and Ad-miR-103-infected cells; B: Over -expression of miR-103 increases fat droplet content. [score:3]
We assessed the mRNA expression of these three transcription factors at 0, 24, 48, and 72 h in GMEC with Ad-miR-103 (Figure 5) (the data of Figure 5 (72 h) and Table 1 were generated from a same experiment). [score:3]
Then, an aliquot (500 µl) of medium in serum-and-antibiotic-free was added to 6-wells incubated with a complex compromising 20 µl transfection reagent, and 60 nM miR-103 -inhibitor or 60 nM negative control for 15 min according to procedure manual of Lipofectamine™ RNAiMAX (Invitrogen, USA). [score:3]
A possible explanation is that miR-103 may target other genes that can affect the transcriptional activity of PANK3. [score:3]
For fatty acid hydrolysis and uptake, expression of LPL and SLC27A6 in Ad-miR-103-infected cells was significantly greater than that of Ad-infected cells (20.48-fold, p<0.01; 1.40-fold, p<0.05). [score:3]
However, no significant differences were observed between the fat droplet accumulation in cells treated with the miR-103 -inhibitor and the negative control (data not show). [score:3]
In this study, we found ACSL1 and ACOX1, both involved in β-oxidation, to be predicted targets of miR-103 (Table S3). [score:3]
Table S3 Predicted targets of miR-103. [score:3]
0079258.g004 Figure 4A: Over -expression of miR-103 promotes fat accumulation. [score:3]
*, p<0.05; D: Over -expression of miR-103 increases total fatty acids content in GMEC. [score:3]
This result is consistent with previous studies done in the mouse 3T3-L1 cell line [47], suggesting that co-regulation of miRNA-103 and its host gene is highly conserved in mammals. [score:2]
The data (miR-103 levels) were expressed as fold change as compared to normal cells (MOI = 0 and 0 nM), normalized to 1. Columns, average of 3 experiments. [score:2]
Our data suggests that miR-103 plays an important role in regulating triglyceride synthesis. [score:2]
In summary, we have identified miR-103 as a new class of regulators of milk fat synthesis. [score:2]
The enrichment of miR-103 at the mid-lactation stage may be a reflection of its physiological role in the regulation of lactation. [score:2]
MiR-103 is differentially expressed in mid-lactation and dry period. [score:2]
From the top 30 miRNAs, we found six miRNAs (e. g., miR-23a, miR-27b, miR-103, miR-200a/b/c) to be related to lipid metabolism in human adipocyte cells: miR-23 enhances glutamine metabolism [38]; miR-27 decreases fat accumulation [27]; miR-103 regulates triglyceride content during cell differentiation [39]; and miR-200 affects insulin signaling [40]. [score:2]
MiR-103 is highly expressed in mid-lactation. [score:2]
The data (miR-103 levels) were expressed as fold change as compared to controls, normalized to 1. Columns, average of 12 experiments; bars, SEM. [score:2]
MiR-103 expression correlates with lactation stages. [score:2]
For the Ad control, miR-103 in Ad-infected cells (at a MOI of 200) did not change compared to uninfected cells (Figure S3), suggesting that Ad doesn’t alter miR-103 expression by itself at this MOI. [score:2]
Taken together, miR-103 plays a significant role in regulating fatty acid composition. [score:2]
Our results suggest that miR-103 may be an important regulator for fat composition and nutrient level of goat milk. [score:2]
MiR-103 may suppress β-oxidation to increase triglyceride content. [score:2]
Taken as a whole, miR-103 has an extensive role in regulating milk fat synthesis in goats. [score:2]
Our results indicate that miR-103 has a significant role in milk fat accumulation in goats. [score:1]
From abundantly expressed miRNAs, we chose miR-103, which has been reported to be involved in lipid metabolism in adipose tissue, to further investigate the correlation between this miRNA and lactation. [score:1]
Fat droplets were extracted using isopropanol in un-, Ad-control without any miRNA sequences and Ad-miR-103-infected cells at 72 h post infection. [score:1]
MiR-103 may decrease β-oxidation through regulating Leptin (LEP) and AMP-activated protein kinase subunit α (AMPKα) pathways. [score:1]
Specifically, triglyceride content of Ad-miR-103-infected cells was 33% higher (p<0.05) than that of Ad-infected cells. [score:1]
Ad-miR-103 generation and infection. [score:1]
Collectively, our data not only provides new insights regarding miRNAs participation in the gene network controlling milk fat synthesis, but also gives us important clues that miR-103 may be used as an index for a molecular breeding program in goats. [score:1]
The Ad-miR-103- and Ad-infected cells were harvested in lysis buffer (50 mmol/l Tris-HCL, pH 7.4, 150 mmol/NaCl, 1% Triton X-100) and sonicated to homogenize the cell suspension. [score:1]
The analysis of fatty acid contents showed that Ad-miR-103-infected cells accumulated more c9-C18:1 (1.35-fold, p<0.05), t11-C18:1 (1.17-fold) and c9,t11-C18:2 (2.16-fold, p<0.05) (Figure 3F). [score:1]
Of the six miRNAs evaluated, miR-103 is the most abundantly expressed miRNA (272,319) (Table S2). [score:1]
Gene networks modulated by miR-103. [score:1]
The MiR-103 family has three members, miR-103-1, miR-103-2 and miR-107, which reside in the sense oriented intron 5 of three members of the pantothenate kinase (PANK) gene family members across species: PANK3, PANK2, and PANK1, respectively. [score:1]
Triglyceride content was determined by using a Serum Triglyceride Determination Kit in un-, Ad-(control) and Ad-miR-103-infected cells. [score:1]
The Ad-miR-103- and Ad-infected cells were harvested and collected in sealable glass tubes. [score:1]
The Ad-miRNA-103- and Ad-infected cells cultured in wells (6 well plate) were rinsed three times in phosphate- buffered saline (PBS), fixed in 10% (v/v) paraformaldehyde for 40 min, and then rinsed again with PBS. [score:1]
For the first time we show that goat mammary gland-enriched miR-103 is linked to milk triglyceride accumulation and unsaturated fatty acids content, indicating that miRNAs may potentially play a role in milk production and the synthesis of beneficial milk components in dairy animal. [score:1]
Authentic miR-103 stem-loop and about 300 nucleotides flanking sequences on the 5′ and 3′ side of miR-103 were amplified from normal Xinong Saanen Dairy Goat genomic DNA. [score:1]
MiR-103 regulates milk fat synthesis. [score:1]
Thus, miR-103 was chosen for further functional studies. [score:1]
We harvested GMEC at 72h post-infection by Ad-(control) and Ad-miR-103, respectively. [score:1]
Therefore, miR-103 could be a candidate gene used for increasing milk yield or unsaturated fatty acid production in the goat milk industry, which is one of the main objectives of dairy goat breeding. [score:1]
GMEC was infected with Ad or Ad-miR-103 at multiplicities of infection MOI (MOI) of 50, 100, 150, 200 or 250. [score:1]
We used a triglyceride determination kit (Sigma-Aldrich) to determine the triglyceride content in GMEC at 72 h after infection with Ad-miR-103 virus. [score:1]
Ad(control)-infected cells were used as control for Ad-miR-103-infected cells. [score:1]
Triglyceride content of Ad-miR-103-infected cells was higher than that of uninfected and Ad-infected cells (Figure 4C). [score:1]
MiR-103 is differentially regulated at mid-lactation and dry period. [score:1]
The adenovirus vectors pAd-control(which dose not contain an inserted sequence) and pAd-miR-103 were constructed and packed in HEK 293 cells using a commercial system (AdEasy, Stratagene). [score:1]
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2
[+] score: 282
Other miRNAs from this paper: hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-103b-2
In conclusion, our results demonstrated that upregulation of miR-103 might contribute to gastric cancer progression by suppressing KLF4 expression and subsequently promoting the proliferation, migration, and invasion, and inhibiting apoptosis of gastric cancer cells. [score:10]
In our study, downregulation of miR-103 in SGC7901 and BGC823 cells showed a more epithelial-shaped phenotype, increased expression level of E-cadherin and decreased vimentin expression. [score:8]
2.7. miR-103 Directly Targets and Down-Regulates KLF4 in GC Cells. [score:7]
High miR-103 expression showed significantly shorter overall survival (OS) and disease free survival (DFS) of patients than that of patients with low miR-103 expression level (Figure 1E), indicating that miR-103 might serve as a promising candidate for the prognosis of GC patients. [score:7]
Kim et al found that the expression of miR-103 was upregulated in gastric cancer and associated with the more advanced tumor stages, especially the invasion and metastasis using qRT-PCR [9]. [score:6]
Downregulation of miR-103 increased the E-cadherin expression level and decreased the level of vimentin in GC cells (Figure 3B). [score:6]
Downregulation of miR-103 Inhibited GC Growth and Lung Metastasis In Vivo. [score:6]
EMT -associated genes tested, including Twist, Snail, Slug and Zeb2, were also downregulated by miR-103 knockdown. [score:5]
Relative miR-103 expression was significantly lower in SGC7901 and BGC823 cells transfected with miR-103 inhibitor than that in negative control (NC) groups (Figure 2A). [score:5]
miR-103 functions as an oncogene by inhibiting its target gene KLF4 in gastric cancer. [score:5]
The lung metastases of SGC7901 xenograft were also suppressed by downregulation of miR-103, and the number of lung metastatic nodules was decreased compared to the negative controls (Figure 4B). [score:5]
To further investigate the clinicopathologic significance of miR-103 levels in GC samples, 92 GC patients were divided into two groups based on miR-103 expression level including the low miR-103 expression group (below the median value) and the high miR-103 expression group (above the median value), for survival analysis. [score:5]
Overexpression of miR-103 has been found in several type human cancers and previous studies reported that miR-103 could enhance the proliferation, migration, and invasion of cancer cells by targeting anti-oncogenes DICER and PTEN [4], TIMP-3 [5], PDCD10 [6], KLF4 [11] respectively. [score:5]
To investigate a direct targeting mechanism, KLF4 was identified as a direct target of miR-103. [score:5]
These results clearly demonstrated that miR-103 promotes cell proliferation, migration, and invasion, and inhibits apoptosis in GC cells, at least in part by targeting KLF4. [score:5]
Meanwhile, RT-qPCR analysis showed that relative miR-103 expression of the tumor xenograft was lower in SGC7901 cells transfected with lentivirus miArrest™ miR-103 inhibitor than that in negative control groups (Figure 4C). [score:5]
Most of the EMT -associated genes tested were downregulated by miR-103 knockdown, with Snail being the most severely affected in SGC7901 and BGC823 cells (Figure 3C). [score:5]
To demonstrate the underlying mechanism of miR-103’s action in gastric cancer, we confirmed Krüppel-like Factor-4 (KLF4) as a direct target of miR-103. [score:4]
When miR-103 expression was knocked down, reduced cell migration and invasion capability were shown in SGC7901 and BGC823 cells (Figure 3A). [score:4]
Recently, miR-103 has been the focus of many studies and has been shown to function as a oncogen, and be upregulated in several types of cancer such as colorectal cancer [4], endometrial cancer [5], and prostate cancer [6]. [score:4]
As shown in Figure 5A, Western blot analysis showed that the expression of KLF4 protein was significantly increased in SGC7901 and BGC823 cells when miR-103 inhibitor was transfected compared with the negative control. [score:4]
The results showed that downregulation of miR-103 could result in decreased growth rate of SGC7901 and BGC823 cells (Figure 2B,C). [score:4]
These results demonstrated that upregulation of miR-103 might promote GC cell proliferation, migration and invasion through the KLF4 -mediated signal pathway. [score:4]
These results further confirmed that KLF4 expression was negatively regulated by miR-103 in GC. [score:4]
Upregulation of miR-103 in Gastric Cancer Tissues and Cell Lines. [score:4]
Downregulation of miR-103 increased luciferase activity in SGC7901 cells transfected with the wild-type 3′-UTR of KLF4 but not in SGC7901 cells with mutant 3′-UTR (Figure 5B). [score:4]
The results showed that KLF4 downregulation reversed the miR-103 -mediated oncogenic influence on cell proliferation, migration, apoptosis, migration and invasion in SGC-7901 cells (Figure 6B–E). [score:4]
Downregulation of miR-103 Impaired Proliferation and Induced Apoptosis of SGC7901 and BGC823 Cells. [score:4]
The growth of SGC7901 xenograft was significantly inhibited by knockdown of miR-103 (Figure 4A). [score:4]
To confirm that KLF4 is a direct target of miR-103, KLF4 3′-UTR and the mutant counterparts were introduced into pmirGLO luciferase reporter plasmid. [score:4]
This study identified KLF4 as a direct target of miR-103 in GC through dual-luciferase reporter and confirmed by western blot analysis. [score:4]
Downregulation of miR-103 attenuated the growth rate of gastric cancer cells significantly in vitro and in vivo. [score:4]
Taken together, these findings demonstrated that knockdown of miR-103 could inhibit EMT in GC cells. [score:4]
Knockdown of miR-103 Suppressed the Epithelial–Mesenchymal Transition (EMT) Process of GC Cells. [score:4]
These data suggested that KLF4 was a direct target of miR-103 in gastric cancer, and the position of 541-547 in the 3′-UTR of KLF4 is the miR-103 binding site (Figure 5C). [score:4]
Taken together, this study revealed that miR-103 was overexpressed in GC and associated with tumor size and lymph node metastasis. [score:3]
This result was confirmed in GC cell lines, miR-103 was over-expressed in gastric cancer cell line than nontumorous mucosa, especially in the metastatic SGC7901 gastric cancer cell line (Figure 1C). [score:3]
Previous study reports that miR-103 promotes endothelial maladaptation and atherosclerosis by mediating suppression of KLF4 [11]. [score:3]
The miR-103 inhibitor and the corresponding negative control (miR-NC) were purchased from GenePharma (Shanghai, China). [score:3]
Overexpression of KLF4 Could Rescue the Oncogenic Effects of miR-103 in GC. [score:3]
Clinicopathologic analysis showed that the overexpression of miR-103 was correlated with the tumor size, Lauren’s classification and lymph node metastasis (Table 1). [score:3]
SGC7901 cells were transfected with lentivirus miArrest™ miR-103 inhibitor (Genecopeia, Rockville, MD, USA). [score:3]
As shown in Figure 1C, SGC7901 and BGC823 showed relatively higher miR-103 expression. [score:3]
Spearman’s correlation test also confirmed that miR-103 expression was positively associated with tumor size. [score:3]
Based on these results, we hypothesized that KLF4 was a target of miR-103 in gastric cancer. [score:3]
At 48 h after transfection with miR-103 inhibitor or miR-NC, western blot analysis was done. [score:3]
In our study, we showed that miR-103 was overexpressed in primary GC tissues and cell lines. [score:3]
Furthermore, there was an inverse association between the miR-103 and KLF4 expression levels (r = −0.212, Figure 5F). [score:3]
These data suggested that the inhibitory effect of miR-103 on the KLF4 is clinically relevant in GC. [score:3]
miR-103 inhibitor transfection was performed in these two cell lines. [score:3]
The aberrant overexpression of miR-103 has been identified in gastric cancer by miRNA microarray and qRT-PCR [7, 8, 9, 10]. [score:3]
SYBR [®] Premix Ex Taq™ II kit (TaKaRa, Dalian, China) was used to quantify the expression levels of mature miR-103, EMT -associated genes and KLF4 according to the protocol provided. [score:3]
The miR-103 expression in tumor samples was significantly higher than that in adjacent nontumorous tissues (Figure 1A). [score:3]
However, the apoptosis ability was promoted after transfection of miR-103 inhibitor. [score:3]
To monitor transfection efficiency, qRT-PCR was performed to determine miR-103 expression at 48 h after transfection. [score:3]
Reduction of miR-103 Inhibited GC Cells Migration and Invasion. [score:3]
Hartmann P. Zhou Z. Natarelli L. Wei Y. Nazari-Jahantigh M. Zhu M. Grommes J. Steffens S. Weber C. Schober A. Endothelial Dicer promotes atherosclerosis and vascular inflammation by miRNA-103 -mediated suppression of KLF4Nat. [score:3]
miR-103 inhibitor and miR-NC and the report plasmid pmirGLO-KLF4 Wt/Mut were co -transfected into cells (SGC7901 and BGC823) using Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA). [score:3]
The expression of miR-103 in patients with lymph node metastasis was significantly higher than those without lymph node metastasis (Figure 1B). [score:3]
SGC-7901 cells were transfected with the miR-103 inhibitor or miR-NC and KLF4 siRNA. [score:3]
Furthermore, an inverse association between miR-103 and KLF4 expression in GC was observed. [score:3]
To elucidate the clinical relevance of miR-103 and KLF4 in GC, the KLF4 expression on mRNA level and protein level in T and ANT tissues were detected by western blot and qRT-PCR analysis, respectively. [score:3]
Overexpression of miR-103 Is Correlated with Poor Prognosis for Gastric Cancer. [score:3]
Later studies suggested that miR-103 was significantly overexpressed in sera of both early and advanced-stage DGC (Diffuse-type gastric cancer)-bearing mice compared with corresponding controls by miRNA microarray and qPCR analyses [10]. [score:2]
These results demonstrated that miR-103 might play an important role in regulating proliferation and metastasis of gastric cancer. [score:2]
Consistent with the Western blot results, it was found that when miR-103 inhibitor was transfected, the activity of a luciferase reporter gene fused to the KLF4 3′-UTR was increased by 36.02 ± 1.4% and 28.48 ± 1.8% in SGC7901 and BGC823 cells compared with negative control groups (Figure 5B). [score:2]
Additionally, it was found that miR-103 inhibitor, compared with the negative control, induced the apoptosis rate of SGC7901 and BGC823 cells (Figure 2D). [score:2]
However, the roles of miR-103 in the progression of GC and its underlying function to regulate tumor proliferation and metastasis are poorly understood, the clinical significance of miR-103 in the prognosis of patients with GC remains unclear. [score:2]
Despite the importance of miR-103 in development of cancer, the exact function of miR-103 in the progression of GC, especially with regard to migration and invasion, remained largely unknown, and its underlying molecular mechanisms have not been sufficiently elucidated. [score:2]
Therefore, miR-103 could be an important oncogene that promotes proliferation and metastasis in GC. [score:1]
2.8. miR-103 and KLF4 Are Clinically Relevant in Human GC Cell and Tissues. [score:1]
This study investigated the expression levels of miR-103 in GC tissues and cells and assessed the correlation between clinicopathologic characteristics and miR-103 expression. [score:1]
These results provide new proof that miR-103 promotes EMT of GC cells. [score:1]
Kaplan–Meier analysis and log-rank test were used to evaluate the prognostic significance of miR-103 expression in GC. [score:1]
The correlation between miR-103 level and tumor size or KLF4 level was analyzed by Spearman analysis. [score:1]
These results showed that miR-103 could facilitate cell proliferation, migration and invasion and reduce apoptosis. [score:1]
Moreover, spearman correlation test showed that miR-103 was positively related with tumor size (Figure 1D). [score:1]
These results suggest that miR-103 plays a crucial role in promoting GC progression. [score:1]
miR-103 was identified as one of the most important microRNAs associated with GC progression [7]. [score:1]
The effect of miR-103 on biological behaviors, including cells apoptosis, proliferation, migration and invasion of GC, was also detected. [score:1]
This study investigated miR-103 expression by qRT-PCR in gastric cancer and adjacent nontumorous tissues. [score:1]
Further analysis demonstrated that miR-103 levels were even higher in these patients with LNM and larger tumor size (≥5cm). [score:1]
To investigate whether miR-103 is involved in EMT process of GC cells, the expression of a variety of EMT markers was detected. [score:1]
[1 to 20 of 83 sentences]
3
[+] score: 115
As expected, in IEC-6 cells, miR-103 knock down by a LNA oligonucleotide resulted in marked up-regulation of the aformentioned gene products (Figure 6D) (1.43±0.13 vs 1.00±0.26 for CCNE1, P<0.05; 1.63±0.13 vs 1.00±0.13 for CDK2, P<0.01; 1.62±0.10 vs 1.00±0.25 for CREB1, P<0.05), presumably because of a decrease in miR-103 mediated mRNA inhibition or degradation. [score:7]
In immunoblotting analysis, the phosphorylated-CREB1 protein was also up-regulated, indicating functional activation during miR-103 inhibition. [score:6]
We performed real-time Q-PCR analysis to monitor the expression of some of these intestinal miRNAs, from which we confirmed two down-regulated miRNAs, miR-103 and miR-17. [score:6]
We retrieved the predicted 1040 target genes of miR-103 from the miRBase target database, and loaded them onto the Ingenuity Pathway Analysis software (IPA version 7.6). [score:5]
), which includes AP1, c-Myb, CREB (miRBase predicted miR-103 target), E2F-1, EGR, Ets, FKHR, Myc-Max, NE-E1 (YY1), NF-κB(miRBase predicted miR-103 target), OCT-1, p53, Pax-2, Pax-3, Pax-6, PPAR-γ, Smad SBE, Sp1, SRE, and Stat3. [score:5]
Furthermore, IGF-1 stimulated cell proliferation in IEC-6 cells was significantly inhibited by overexpression of miR-103 (211%±17% vs 140%±5%, P<0.05) (Figure 5). [score:5]
The miR-103 gene targets were predicted from the MicroCosm Targets Version 5 (http://www. [score:5]
CCNE1, CDK2, and CREB1 are direct targets of miR-103 in mouse small intestinal crypt cells during IGF-1 stimulation. [score:4]
miR-103 has also been shown to stimulate adipogenesis that accelerates fat cell proliferation, and is down-regulated in obesity [32]. [score:4]
Immunoblotting of IEC-6 cells demonstrated that CCNE1, CDK2, CREB1 are induced at the protein level upon miR-103 inhibition, further supporting an effect of miR-103 regulation on these genes. [score:4]
Arrow indicates miR-103 probe, which is 44.26% of relative control intensity over the course of 24 h. (B, C) real-time Q-PCR analysis of mature miR-103 (B) and pri-miR-103 expression (C) during 24 h in crypt cells. [score:3]
Among the mRNA targets of miR-103 was also the transcription factor CREB1 gene, which binds as a homodimer to cAMP responsive elements within the DNA sequence [39]. [score:3]
In this report, we examined whether miR-103 can bind and affect the predicted target mRNAs through mRNA 3′UTR interactions. [score:3]
miR-103 expression analysis in IGF-1 stimulated mouse small intestinal crypt cells. [score:3]
The present study determined the global microRNA expression in mouse crypt cells, and confirmed functional aspects of miR-103, which could be a suitable candidate for developing novel therapeutic interventions. [score:3]
Mature miR-103 then rebounded to 57% of the level prior to treatment (P<0.01), while pri-miR-103 expression was maintained at ∼25% of the level prior to treatment (P<0.01). [score:3]
For immunoblotting analysis, IEC-6 cells were seeded at 50% confluency per well in 6-well plate the day prior to transfection with 50 nM miR-103 inhibitor (Dharmacon). [score:3]
miR-103 mimic or LNA inhibitor transfection was performed as previousely described [18]. [score:3]
Kinetic analysis by real-time Q-PCR confirmed the presence of mature miR-103 (Figure 4B) and pri-miR-103 (Figure 4C) in small intestinal crypt cells, and also revealed that during the first 6 h of, expression of mature miR-103 and pri-miR-103 was rapidly reduced to 39% and 16% of initial levels, respectively (P<0.01). [score:3]
We explored whether miR-103 could affect the identified gene targets through interaction with the mRNA 3′UTR. [score:3]
Identification of miR-103 target genes in mouse small intestinal crypt cells. [score:3]
In this study, we successfully cultured mouse intestinal crypt cells during a 24 h period and confirmed targeting of the CREB1 transcription factor, and CCNE1/CDK2 by miR-103 during cell cycle progression, implicating a role for miRNAs in intestinal growth. [score:3]
To examine whether the miR-103 targets are involved in IGF-1 stimulated mouse intestinal cell proliferation, immunoblotting analyses were performed on the crypt cells before and after. [score:3]
miR-103 is directly involved in IGF-1 stimulated mouse intestinal cell proliferation. [score:2]
For luciferase assays, HEK293 cells were seeded at 70% confluency per well in 96-well plate 6 h prior to transfection with 4 ng/µl luciferase expression construct and 12.5–80 nM miR-103 mimic (Dharmacon). [score:2]
As seen in Figures 6B and Figure 6C, in HEK293 cells, all vectors containing the 3′UTRs of CCNE1, CDK2, and CREB1 displayed dose -dependent light emission reduction upon co-transfection with increasing miR-103 mimic, indicating the presence of a direct binding site for miR-103. [score:2]
In HEK293 cells, co-transfection with miR-103 mimic could repress the luciferase activity generated by luciferase vectors containing the mRNA 3′UTRs of CCNE1, CDK2, CREB1 of human (Figure 6B) and mouse (Figure 6C) origin in a dose dependent manner, clearly indicating direct binding between the miRNA sequence and the genes. [score:2]
miR-103 is directly involved in IGF-1 stimulated crypt cell proliferation. [score:2]
cel-miR-67 (Dharmacon) served as a negative control for miR-103 mimic. [score:1]
The CCNE1 vector displayed a more sensitive response to the miR-103 mimic, possibly because of higher percentage seed match to the human homologue. [score:1]
0012976.g006 Figure 6 (A) sequence alignment between miR-103 seed region and the seed matches on CCNE1, CDK2, and CREB1 mRNA 3′UTR region. [score:1]
pGL3-control luciferase vectors containing the mRNA 3′UTR of respective genes of human (B) or mouse (C) origin were co -transfected with the indicated amount of miR-103 mimic in HEK293 cells, and luciferase activity was analyzed 24 h post-transfection. [score:1]
org) was used to scan for seed matches between the miR-103 seed region and the predicted gene. [score:1]
Control group was set to 0. MA plot showed that miR-103 was the most substantially reduced miRNA during IGF-1 stimulated crypt cell proliferation (Mean log2 ratio of −1.176) (Figure 4A). [score:1]
Each sample was analyzed in triplicate and normalized to snoRNA202 for mature miR-103 and β-actin for pri-miR-103 using the following equation: ΔCt [GENE] = Ct [GENE]-Ct [snoRNA202/β-actin]. [score:1]
Data were normalized to snoRNA-202 levels for mature miR-103 and β-actin for pri-miR-103. [score:1]
We then manually aligned the mRNA 3′UTR and the miR-103 seed region (Figure 6A), which were found to be highly matched for both human and mouse genes. [score:1]
IEC-6 cells in 96-well plate were transfected with 50 nM miR-103 mimic before treated with 20 ng/ml IGF-1. The control group was cultured in growth media or treated with IGF-1 alone. [score:1]
The mature sequence of miR-103 (5′-AGCAGCAUUGUACAGGGCUAUGA-3′) was retrieved from the miRBase Sequence Database, release 14 (http://microrna. [score:1]
The human homologue of the mRNA 3′UTR was used, and computational approaches (Figure 6A) predicted that there is an 8-mer seed match between miR-103 and mouse CREB1/CDK2, while there is a 7-mer seed match between miR-103 and the human homologue; there is a 7-mer seed match between miR-103 and mouse CCNE1 mRNA 3′UTR, and an 8-mer seed match between miR-103 and the human homologue. [score:1]
uk/sequences/), and mRNA 3′UTRs of CCNE1, CDK2, and CREB1 from human and mouse were aligned with miR-103 sequence using the ClustalW program (http://www. [score:1]
The miR-103 family is found in 23 species, and comprised of 2 isoforms: miR-103-1 located on human chromosome 5q34 and miR-103-2 located on human chromosome 20p13 [29], [30], [31]. [score:1]
0012976.g005 Figure 5 IEC-6 cells in 96-well plate were transfected with 50 nM miR-103 mimic before treated with 20 ng/ml IGF-1. The control group was cultured in growth media or treated with IGF-1 alone. [score:1]
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4
[+] score: 106
MiR-107 and miR-103 are downregulated with age [35] as well as in AD gray matter [36] and repress the translation of cofilin. [score:6]
The downregulation of miR-103 and miR-107 with age could concern a protective effect against plaque formation because reduced levels of these miRNAs would lead to an increased level of the predicted target ADAM10 and its neuroprotective product sAPPα in brains of AD patients. [score:6]
After the analysis we got 156 and 157 target genes for miR-103 and miR-107, respectively, common in four out of six databases, and 890 target genes for miR-1306 of database PITA. [score:5]
Each set of target genes of miR-103 and miR-107 common in 4 out of 6 databases as well as the set of target genes of miR-1306 in the database PITA was explored for enrichment in Gene Ontology [32] by the software Pathway Studio 8.0 (Ariadne Genomics) based on database ResNet 8.0. [score:5]
Our observations of strong inhibition (> 40%) of ADAM10 expression in the reporter assay upon application of miR-103 and miR-107 would coincide with such a possible protective influence on amyloid pathology (see “Experimental validation of bioinformatically predicted miRNAs”). [score:4]
In our case Tarbase doesn’t contain target genes for the miRNAs: miR-103, miR-107 and miR-1306. [score:3]
Predicted target genes of miR-103 (p-value = 0.0065) and miR-107 (p-value = 0.0009) showed significant overlap with the AlzGene database except for miR-1306. [score:3]
The Venn diagram shows the significant overlap of the target genes of miR-103 and miR-107 common in four out of six databases as well as the genes of AlzGene database. [score:3]
Click here for file List of enriched target genes of miR-103 in Gene Ontology. [score:3]
The table shows a list of predicted target genes of miR-103, miR-107, miR-1306. [score:3]
In addition, the program TargetScan verifies the same binding site of miR-103 and miR-107 to human ADAM10. [score:3]
An additional evidence is given by the significant biological processes learning (miR-103: p-value = 0.0008; miR-107: p-value = 3.3 × 10 [−5]; miR-1306: p-value = 0.0003), brain development (miR-103: p-value = 0.0023; miR-107: p-value = 0.0004; miR-1306: p-value = 7.1 × 10 [−6]) and nervous system development (miR-103: p-value = 0.0004; miR-107: p-value = 0.0004; miR-1306: p-value = 6.9 × 10 [−8]) that the three miRNAs are involved in AD. [score:3]
The table shows the Gene Ontology entities with enrichment of predicted target genes of miR-103. [score:3]
The overlap between AlzGene database genes and the target genes of miR-103, miR-107 as well as miR-1306 are 12, 14 (Figure  5) and 24 genes, respectively (Additional file 1). [score:3]
We generated Venn diagrams to see the overlap between target genes of miR-103 and miR-107 common in 4 out of 6 databases as well as genes in the AlzGene database (http://www. [score:3]
MiR-103 and miR-107 have 130 target genes in common (Figure  5, Additional file 1). [score:3]
List of enriched target genes of miR-103 in Gene Ontology. [score:3]
According to the publication from Cogswell et al. [27] miR-103 is differentially expressed in hippocampus and cerebellum in AD. [score:3]
The combination of different and the restriction of the output to four out of six databases in the case of miR-103 and miR-107 are important to reduce the amount of false positive miRNA target sites in the end. [score:3]
Furthermore, target genes of miR-103, miR-107 and miR-1306 were derived from six publicly available. [score:3]
While miR-103 and miR-107 target the same DNA sequence within the ADAM10 3′UTR (see Figure  2), miR-1306 has a binding site in closer proximity to the Stop codon. [score:3]
The genes dicer 1, ribonuclease type III (Dicer) and TAR (HIV-1) RNA binding protein 2 (TARBP2) targeted by miRNA-103 and miRNA-107 are components of the miRNA-processing complex [46]. [score:3]
Applying a Fisher’s exact test we got a p-value of 0.0065, 0.0009 and 0.1904 for the overlap of miR-103, miR-107 and miR-1306, respectively, with the AlzGene database, which shows that 12 and 14 are significant high numbers of overlapping genes between the target genes and the AlzGene database. [score:3]
These findings of the literature and AlzGene database confirm the biological role of the target genes in neurodegenerative processes and hence the involvement of miR-103 and miR-107 in AD. [score:3]
These experimental results suggest an influence of miR-103 miR-107 and miR-1306 on ADAM10 expression. [score:3]
ADAM10 expression in the reporter assay was reduced by miR-1306 (28%), miR-103 (45%) and miR-107 (52%). [score:2]
Our results show that miR-103, miR-107 and miR-1306 influence the expression of ADAM10 at least in the reporter assay system. [score:2]
miR-103 directly binds and represses CDK2 and CREB1 through 3′UTR binding [51]. [score:2]
Only target genes predicted in at least four out of six databases in the case of miR-103 and miR-107 were compared to genes listed in the AlzGene database including genes possibly involved in AD. [score:2]
Furthermore, a network (Figure  6) containing already published interactions of miR-103 and miR-107 with genes involved in AD or included in the AlzGene database was established using the literature mining tool Pathway Studio. [score:1]
In brains of a transgenic mouse mo del of AD the level of miR-103 and miR-107 is decreased while the cofilin protein level is increased which results in the formation of rod-like structures [37]. [score:1]
We therefore combined miR-1306 and miR-103 or miR-107, respectively, but observed no distinct significant synergistic effect (miR-1306 vs. [score:1]
The figure shows the conservation of the miR-1306 (A), miR-103 (B) and miR-107 (C) binding region (light green) between different species. [score:1]
Three of them (miR-103, miR-107, miR-1306) were further analysed as they are linked to AD and most strictly conserved between different species. [score:1]
Figure 6 Interaction network of miR-103 and miR-107. [score:1]
Interactions between miR-103 and miR-107 to genes were revealed playing a role in processes leading to AD. [score:1]
This site is predicted by the two programs RNAhybrid and miRanda with binding energy −27.9 and −23.66 kcal/mol for miR-103, respectively, as well as −26.2 and −22.28 kcal/mol for miR-107, respectively. [score:1]
The three miRNAs identified by bioinformatical approaches and integration of literature mining all showed a significant decreasing effect on the ADAM10 3′UTR-reporter construct: miR-1306 lowered the luminescent signal to 72%, miR-103 to 55% and miR-107 to 48% of control. [score:1]
The second most interesting miRNAs possibly binding to human ADAM10 3′UTR are miR-103 as well as miR-107 both having the same binding site located on chromosome 15 positions 58889443–58889468. [score:1]
This result suggests that miR-103 and miR-107 might play a role in AD. [score:1]
The network (established by Pathway Studio) shows already published interactions between miR-103 as well as miR-107 and genes known to be involved in AD or neurodegenerative processes. [score:1]
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5
[+] score: 82
Although previous works have shown miR-103 to be down-regulated in several cancers [43], no previous investigation analyzing miRNA expression in MM reported a deregulation of miR-103 miRNA expression [13]– [18]. [score:7]
Only two of 49 miRNAs, miR-20a (p = 0.0101) and miR-103 (p = 0.0303), showed a significant down-regulation in MM. [score:4]
However, only miR-103 shows a significant down-regulation in MM. [score:4]
Scatter plot of relative expression of miR-103 in histological subtypes of malignant mesothelioma. [score:3]
This is in accordance with Duttagupta et al., showing no altered miR-103 expression between males and females [45]. [score:3]
Relative expression of miR-103 in the cellular fraction of human peripheral blood of malignant mesothelioma patients (blue), asbestos-exposed controls (yellow), and controls from the general population (orange) regarding (A) gender, (B) smoking status, and (C) age. [score:3]
The identified miR-103 is part of the miR-15/107 group commonly expressed in mammalian tissues [41]. [score:3]
Relative expression of miR-103 in the cellular fraction of human peripheral blood of malignant mesothelioma patients (blue), asbestos-exposed controls (yellow), and controls from the general population (orange). [score:3]
0030221.g003 Figure 3Relative expression of miR-103 in the cellular fraction of human peripheral blood of malignant mesothelioma patients (blue), asbestos-exposed controls (yellow), and controls from the general population (orange). [score:3]
Relative expression of miR-103 in the cellular fraction of human peripheral blood of patients with epithelioid and biphasic mesothelioma. [score:3]
0030221.g006 Figure 6Relative expression of miR-103 in the cellular fraction of human peripheral blood of malignant mesothelioma patients (blue), asbestos-exposed controls (yellow), and controls from the general population (orange) regarding (A) gender, (B) smoking status, and (C) age. [score:3]
A significant lower expression of miR-103 and other miRNAs was described in older individuals [46]. [score:3]
Using a threefold expression change in combination with a significance level of p<0.05, miR-103 was identified as a potential biomarker for malignant mesothelioma. [score:3]
Scatter plots of relative expression of miR-103. [score:3]
Box plots of relative expression of miR-103. [score:3]
0030221.g004 Figure 4Relative expression of miR-103 in the cellular fraction of human peripheral blood of patients with epithelioid and biphasic mesothelioma. [score:3]
In our study no gender-specific expression of miR-103 could be observed. [score:3]
To our knowledge, the present study is the first to show a significant deregulation of miR-103 in MM, including the two histological subtypes epithelioid and biphasic mesothelioma. [score:2]
The suitability of miR-103 alone and in combination with other biomarkers for early detection of mesothelioma needs to be further validated in a prospective study. [score:1]
In comparison to miR-126 (73% sensitivity and 74% specificity) [15], miR-103 shows a comparable specificity but slightly higher sensitivity. [score:1]
Median value of miR-103 was 0.611 (IQR 0.602–0.620) for epithelioid mesothelioma and 0.612 (IQR 0.610–0.614) for biphasic mesothelioma (Figure 4). [score:1]
Our study indicated also altered miR-103 levels, but the effect was marginal. [score:1]
For CGP median value of miR-103 was 0.630 (IQR 0.622–0.635) and differences were significant for MMP vs. [score:1]
Quantitative real-time PCR (qRT-PCR) was used for validation of miR-103 in 23 malignant mesothelioma patients, 17 asbestos-exposed controls, and 25 controls from the general population. [score:1]
Using normalized Ct values of miR-103, differences between histological subtypes were analyzed. [score:1]
A proper cut-off for miR-103 using a 2 [−Ratio] value of 0.621 was determined to discriminate MMP from AEC revealing a sensitivity of 83% and specificity of 71%. [score:1]
Subgroup comparisons regarding gender, smoking status, and age were performed using normalized Ct values of miR-103. [score:1]
0030221.g005 Figure 5 The area under curve (AUC) was determined for miR-103 in the cellular fraction of human peripheral blood of (A) malignant mesothelioma patients and asbestos-exposed controls and (B) malignant mesothelioma patients and controls from the general population. [score:1]
This is in accordance with Guled et al., showing several smoking-related miRNAs in a mesothelioma patients, but not miR-103 [14]. [score:1]
For male subjects the median value of miR-103 was 0.625 (IQR 0.612–0.636) and for female subjects 0.620 (IQR 0.614–0.629) (Figure 6 A). [score:1]
Therefore, the feasibility of miR-103 for detecting MM should also be validated in larger collectives in order to obtain more reliable values for sensitivity and specificity. [score:1]
Regarding the smoking status the median value of miR-103 was 0.629 (IQR 0.622–0.642) for smokers, 0.624 (IQR 0.612–0.635) for ex-smokers, and 0.621 (IQR 0.612–0.634) for non-smokers, (Figure 6 B). [score:1]
The results imply that miR-103 is a potential biomarker of MM. [score:1]
The area under curve (AUC) was determined for miR-103 in the cellular fraction of human peripheral blood of (A) malignant mesothelioma patients and asbestos-exposed controls and (B) malignant mesothelioma patients and controls from the general population. [score:1]
Median value of miR-103 for MMP was 0.612 (IQR 0.608–0.620) and for AEC 0.635 (IQR 0.615–0.648) and the difference was significant (p = 0.0062). [score:1]
However, for early detection of malignant mesothelioma the feasibility of miR-103 alone or in combination with other biomarkers needs to be analyzed in a prospective study. [score:1]
Thus, miR-125a was used as the reference to normalize the raw Ct values of miR-20a and miR-103 obtained in the qRT-PCR analysis. [score:1]
For example, miR-103 and miR-107 are described as possible prognostic markers in esophageal carcinoma [42]. [score:1]
miR-20a and miR-103 as potential biomarkers for MM. [score:1]
In our study miR-103 is not influenced by the smoking status. [score:1]
To discriminate MMP from AEC and CGP, respectively, a proper cut-off for miR-103 was determined utilizing ROC analysis. [score:1]
[1 to 20 of 41 sentences]
6
[+] score: 72
Ssc-miR-103 and ssc-miR-107 expression was slightly lower in premolars (Dpm) than in other types of teeth, ssc-miR-133a and ssc-miR-133b expression was much higher in Dpm than in other types of teeth, and ssc-miR-127 expression gradually increased from the incisor (Di) to the molar (Dm) In order to detect the oral developmental specificity of the five selected miRNAs, we further extracted kidney, liver and submandibular gland to contrast the five miRNAs expression (Fig.   5). [score:10]
Ssc-miR-103 and ssc-miR-107 expression was slightly lower in premolars (Dpm) than in other types of teeth, ssc-miR-133a and ssc-miR-133b expression was much higher in Dpm than in other types of teeth, and ssc-miR-127 expression gradually increased from the incisor (Di) to the molar (Dm)In order to detect the oral developmental specificity of the five selected miRNAs, we further extracted kidney, liver and submandibular gland to contrast the five miRNAs expression (Fig.   5). [score:10]
We also found that expression levels of ssc-miR-103 and ssc-miR-107 were slightly lower in Dpm than in other types of teeth, ssc-miR-133 a and ssc-miR-133b expression levels were much higher in Dpm than in other types of teeth, and ssc-miR-127 expression increased in Di, Dc, Dpm, and Dm, in that order. [score:7]
In our study, they were also broadly expressed in all types of teeth at nearly every stage, but the complete lack of expression of ssc-miR-103 and ssc-miR-107 in Dpm during E40 and E50 is worthy of attention, as this could indicate that they exist in bidirectional antagonism with ssc-miR-133a and ssc-miR-133b during premolar morphogenesis in large animal species. [score:6]
We could found that the expression levels of ssc-miR-103 were strongly lower in kidney, liver and submandibular gland, while the expression levels of ssc-miR-107 were strongly lower in kidney and liver but somehow relatively high in submandibular gland. [score:5]
At E50, miR-103 expression in all four types of teeth stayed the same for the most part, but the expression level was lower and more restricted in the inner enamel epithelium, which contains the most important structure of morphogenesis: the enamel knot in incisor and canine. [score:5]
Ssc-mir-107 expression was similar to that of ssc-miR-103 (Additional file 6A1–C4). [score:3]
Expression levels of five miRNAs (ssc-miR-103, ssc-miR-107, ssc-miR-127, ssc-miR-133a, and ssc-miR-133b) were detected by real-time RT-PCR and microarray chip. [score:3]
The present study indicated that these five miRNAs, including ssc-miR-103 and ssc-miR-107, ssc-miR-133a and ssc-miR-133b, and ssc-miR-127, may play key regulatory roles in different types of teeth during different stages and thus may play critical roles in tooth morphogenesis during early development in miniature pigs. [score:3]
In combination with our other results, this implies that ssc-miR-127, ssc-miR-103, and ssc-miR-107 may play a regulatory role in the morphogenesis of all kinds of teeth during different developmental stages. [score:3]
We then predicted that the miR-103, and miR-107, miR-133a, and miR-133b isomiRs would be differentially expressed miRNAs. [score:3]
At E60, mir-103 expression in the premolar increased substantially, while in the other three types of teeth, the location was restricted in the inner enamel epithelium (C1–C4). [score:3]
All the expression levels of five miRNAs were fairly high in tooth except ssc-miR-107, and relatively high in submandibular gland except ssc-miR-103, and lower in kidney and liver. [score:3]
Microarray, real-time RT-PCR, and in situ hybridization experiments revealed that ssc-miR-103 and ssc-miR-107, ssc-miR-133a and ssc-miR-133b, and ssc-miR-127 may play more important roles in Di and Dc, Dpm, and Dm, respectively, during different developmental stages. [score:2]
Previous studies have demonstrated that miR-103 and miR-107 may regulate human metabolic pathways that involve cellular acetyl-CoA and lipid levels [20]. [score:2]
For ssc-miR-103 and ssc-miR-107, we chose the first deciduous incisor to contrast with the three kinds of tissues. [score:1]
These results suggest that ssc-miR-103 and ssc-miR-107 may play important roles in the early morphogenesis of conoides teeth and in crosstalk between epithelial and mesenchymal tissue. [score:1]
By clustering analysis, we predicted 11 unique miRNA sequences that belong to mir-103 and mir-107, mir-133a and mir-133b, and mir-127 isomiR families. [score:1]
Ssc-mir-103 was located in the outer and inner enamel epithelium, dental mesenchyme, and stellate reticulum (Fig.   6A1–C4). [score:1]
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7
[+] score: 61
One particularly interesting finding is the upregulation of miR-103 and downregulation of its putative gene target Ptplb in brains. [score:9]
In the mature brain, however, upregulation of miR-103 may suppress BDNF synthesis in humans [65] and promote neuropathological processes in a mouse mo del of Alzheimer’s disease [66]. [score:8]
C, Prenatal stress elevated expression of miR-103, which coincides downregulation of its potential target Ptplb (mean ± SEM). [score:8]
Ptplb is a putative target for miR-103, which was upregulated by prenatal stress (Figure 4C). [score:6]
miR-103 is enriched in the cortex [61] and its expression increases during neurodevelopment, particularly cell differentiation [62], [63] and translation [64]. [score:6]
miR-103 -mediated inhibition of Ptplb translation may contribute to alterations in behavioural and neuronal plasticity in prenatally stressed offspring. [score:5]
The putative gene target of miR-103, Ptplb, is essential for biosynthesis of tyrosine phosphatase-like member b, which is involved in a wide range of neuronal functions, including synapse formation [70], disorders involving the frontal cortex such as Alzheimer’s disease [71], [72] and schizophrenia [73]. [score:5]
Altered miR-103 expression in the developing brain may therefore contribute to cognitive changes in adulthood. [score:3]
B, Table of putative target genes for modulated miRNAs (miR-103, miR-151, and miR-219-2-3p; p≤0.05) and their physiological functions. [score:3]
Moreover, significant changes in expression due to prenatal stress were found in miR-103 (down), miR-151 (down), and miR-219-2-3p (up). [score:3]
Ptplb and Dazap1 are targets for miR-103 and miR-219, respectively. [score:3]
The following miRNAs were analyzed (5′ to 3′): mirR-181 and miR-186 (dams); miR-103, miR-151, miR-323, miR-145, miR-425, miR-98 (newborns). [score:1]
Non-stress groups), as observed by microarray analyses, the following candidates were selected for verification by qRT-PCR analysis: miR-151, miR-145, miR-425 (all down) and miR-103, miR-323, miR-98 (up) (Figure 3C). [score:1]
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[+] score: 60
Twelve microRNAs were consistently up-regulated in metastasis (hsa-miR-103, -155, -16, -191, -200c, -21, -24, -26a, -26b, -29a, -31 and 93) and only two were down-regulated (hsa-miR-328 and -566) (Table 2). [score:7]
Recently, it has been demonstrated that hsa-miR-103/107 indirectly downregulates miR-200 family members, and that such pattern is associated with mesenchymal phenotype in breast cancer cell lines [24]. [score:5]
Particularly, hsa-miR-103 upregulation was detected in gastric cancer patients bearing positive lymph nodes. [score:4]
A Chi-squared test revealed a linear trend for both, hsa-miR-21 (P-value<0.0001) and hsa-miR-103 (P-value<0.0001): they were increasingly upregulated progressing from normal, to adenocarcinoma and to metastasis (Fig. 3, Fig 4). [score:4]
However, the only up-regulated validated microRNA identified in our signature that could discriminate between colonic hepatic metastasis and primary hepatocellular carcinoma was hsa-miR-103. [score:4]
Therefore, hsa-miR-103 and hsa-200c were not inversely correlated and do not regulate EMT in metastatic colon cancer in vivo, but were both overexpressed in adenocarcinomas and lymph nodes metastasis. [score:4]
High levels of hsa-miR-103 were correlated to poor survival in esophageal cancer and are associated to metastatic disease in breast and gastric cancer. [score:3]
0096670.g004 Figure 4 In normal colon the arrow is pointing at the lack of miR-103 expression in epithelial cells. [score:3]
Again, ISH gave us more specific cell-of-origin information: while, there were no significant differences between primary tumors and positive lymph nodes, liver metastasis showed the highest levels of hsa-miR-103 expression. [score:3]
In normal colon the arrow is pointing at the lack of miR-103 expression in epithelial cells. [score:3]
In the primary tumor the arrow is pointing at the increased expression of miR-103 in the invasive adenocarcinoma. [score:3]
The arrow in liver recurrence and the two arrows in the lymph node metastases are showing a dramatic increased expression of miR-103 in the metastatic adenocarcinoma epithelia. [score:3]
Similarly, in our study, qRT-PCR detected hsa-miR-103 over -expression in primary tumors as well as metastatic nodes and liver. [score:3]
However, while hsa-miR-103 was significantly overexpressed in liver metastasis when compared to adenocarcinomas and positive lymph nodes, hsa-miR-21 did not show any significant difference among the three classes. [score:2]
Recently, hsa-miR-103/107 levels were found inversely correlated to hsa-miR-200c in the regulation of Epithelial-to-Mesenchimal Transition in breast cancer [25]. [score:2]
with normal colon tissue (NORM), colon adenocarcinomas (ADENOCA), lymphonodal metastasis (POSLYM) and colon liver (LIVERMET) for miR-21 (A), miR-103(B), miR-93(C), miR-566(D) and miR-200c(E). [score:1]
This suggests that hsa-miR-103 and hsa-miR-200c do not control EMT in colon cancer, and that high levels of hsa-miR-200c are required for nodal invasion. [score:1]
A significant positive correlation between hsa-miR-103 and hsa-miR-200c was present in lymph node metastasis (P-value  = 0.0225), but not in adenocarcinomas or liver metastasis. [score:1]
0096670.g002 Figure 2with normal colon tissue (NORM), colon adenocarcinomas (ADENOCA), lymphonodal metastasis (POSLYM) and colon liver (LIVERMET) for miR-21 (A), miR-103(B), miR-93(C), miR-566(D) and miR-200c(E). [score:1]
Normal colon tissue (NORM), colon adenocarcinomas (ADENOCA), lymphonodal metastasis (POSLYM) and colon liver (LIVERMET) for miR-21(A), miR-31 (B), miR-93 (C), miR-103 (D) and miR-566 (E). [score:1]
miR-103 In Situ Hybridization of Normal Colon (5X), Primary Tumor (5X), Normal Liver (5X), Liver Metastasis (5X, 10X) and Metastatic Lymph node (5X). [score:1]
0096670.g001 Figure 1Normal colon tissue (NORM), colon adenocarcinomas (ADENOCA), lymphonodal metastasis (POSLYM) and colon liver (LIVERMET) for miR-21(A), miR-31 (B), miR-93 (C), miR-103 (D) and miR-566 (E). [score:1]
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[+] score: 51
n = 3. Treatment with trans-Pellitorine Decreases Expression and Protein Levels of PPARγThe online-tool TargetScanMouse by the Whitehead Institute for Biomedical Research [1] was used to select mRNA targets of the regulated miRNAs miR-let-7b and miR-103 which may be involved in adipogenesis, obesity and lipid metabolism. [score:8]
Furthermore, the present study shows that expression of the miRNAs mmu-miR-103 and mmu-miR-let-7b is upregulated after treatment with 1 μM trans-pellitorine. [score:6]
n = 3. The online-tool TargetScanMouse by the Whitehead Institute for Biomedical Research [1] was used to select mRNA targets of the regulated miRNAs miR-let-7b and miR-103 which may be involved in adipogenesis, obesity and lipid metabolism. [score:6]
Recently, we identified the miRNAs let-7a, let-7b, let-7d, miR-103, and miR-143 as potential targets of TRPV1 -dependent inhibition of adipogenesis by the pungent compound nonivamide using a customized miRNA-array (Rohm et al., 2015). [score:5]
Table 2 shows that, in comparison to undifferentiated control cells, expression levels of mmu-miR-let-7a, mmu-miR-let-7b, mmu-let-7d, mmu-miR-103, and mmu-miR-143 were largely increased in fully differentiated 3T3-L1 adipocytes and that addition of 0.1% ethanol during adipogenesis and maturation did not impact the expression of mmu-miR-let-7a, mmu-miR-let-7b, mmu-let-7d, mmu-miR-103, and mmu-miR-143. [score:5]
However, addition of 1 μM trans-pellitorine, which significantly decreased lipid accumulation when added to developing 3T3-L1 cells, increased expression of mmu-miR-let-7b to fold changes of 1.53 ± 0.31, and miR-103 to 1.50 ± 0.25 vs. [score:3]
N(𝜖) -carboxymethyllysine increases the expression of miR-103/143 and enhances lipid accumulation in 3T3-L1 cells. [score:3]
The results present evidence that expression levels of mmu-miR-let-7a, mmu-miR-let-7b, mmu-let-7d, mmu-miR-103, and mmu-miR-143 are increased during adipogenesis and maturation of 3T3-L1 cells, supporting an effect of the selected miRNAs on adipogenesis of 3T3-L1 cells. [score:3]
As target genes for mmu-miR-103, FAS and LPR2 were chosen, and for mmu-miR-let-7b, PPARG and IGF1R were selected. [score:3]
For example, several miRNAs like miR-103, miR-143, and members of the let-7 group have been shown to reduce adipogenesis by targeting the transcription factor PPARγ (Esau et al., 2004; Sun et al., 2009; Xie et al., 2009). [score:3]
As targets of mmu-miR-103, genes encoding for FAS and low density lipoprotein-related protein 2 (LPR2) were chosen. [score:3]
Energizing miRNA research: a review of the role of miRNAs in lipid metabolism, with a prediction that miR-103/107 regulates human metabolic pathways. [score:2]
In detail, we investigated expression of miR-let-7a, let-7b, let-7d, miR-103, and miR-143 after treatment with 1 μM trans-pellitorine. [score:1]
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[+] score: 46
Our results provide an extensive genome wide set of targets for miR-503, miR-103, and miR-494, and suggest that miR-503 may act as a tumor suppressor in breast cancer by its direct non-canonical targeting of DDHD2. [score:8]
There were no differences between compensatory target pairing sites and the intact 5′ seed alone for both miR-503 and miR-103, making it difficult to draw conclusions as to utilization of compensatory target pairing. [score:5]
There was enrichment for proliferation related genes in the targets identified for miR-503 and miR-494, but there were not enough target genes identified for miR-103 to produce meaningful results (Additional file 2) [38- 40]. [score:5]
Nelson et al. previously reported this same finding when they experimentally profiled the targets of miR-103, and concluded that miR-103 utilized miRNA 3′ pairing for targeting, although they did not further explore this observation experimentally [41]. [score:5]
The frequency of compensatory pairing sites in the target gene set for either miR-503 or miR-103 was not higher than the frequency of 5′ seed matches (Figure  4C & Additional file 3). [score:3]
In addition, mRNAs that were most repressed following miRNA transient overexpression showed the greatest enrichment for miR-103, and −494 seed matches, although not for miR-503 (Figure  3C). [score:3]
miR-503, miR-103, and miR-494 have previously been shown to act as either oncogenes or tumor suppressors in different cellular contexts [22- 29]. [score:3]
Using previously published data we identified numerous miRNAs induced in fibroblasts transitioning from quiescence to proliferation, and selected three, miR-503, miR-103, and miR-494, for further study that were consistently induced by serum stimulation and predicted to target proliferation and or cell cycle related genes [34]. [score:3]
Based on the enrichment for sequences pairing the miRNA 5′ seed and the miRNA 3′ end for miR-503 and miR-103, we hypothesized that miR-503 and −103 were using supplementary or compensatory pairing to target mRNAs (Figure  4B). [score:3]
Here we identified miR-503, miR-103, and miR-494 as negative regulators of proliferation in primary human cells. [score:2]
There were no significant differences in repression for miR-103 or in RISC association for either miR-503 or miR-103 that was dependent on pairing type (Figure  4E & Additional file 3). [score:1]
miR-503, miR-103, and miR-494 repress proliferation. [score:1]
The subsequences of miR-503 and miR-103 examined for pairing were selected based off the subsequence enrichment plots shown in Figure  4A. [score:1]
However, supplementary pairing sites were much more frequent than the 5′ seed matches and compensatory pairing sites for both miR-503 and miR-103 (Figure  4C & Additional file 3). [score:1]
miR-103 has been described to function as an oncomiR in colorectal cancer and breast cancer [22, 27]. [score:1]
For miR-103, the criteria used to search for compensatory sites (5′ mismatch + additional 3′ pairing) were: (1) a 6-mer pairing position 2–7 with 1 mismatch, (2) an 8-mer matching position 11–18 with 0 – 3 mismatches, and (3) a 1 base pair wobble allowed in the length of the sequence separating the 6-mer and 8-mer. [score:1]
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[+] score: 34
However, the importance of miR-103, miR-143 and miR-483-3p in human glucose and lipid metabolism, and the relative impact of genetic and environmental factors in the regulation of their expression, are undisclosed. [score:4]
Using murine mo dels of T2D, Trajkovski et al. demonstrated that miR-103 silencing improved glucose homeostasis, insulin sensitivity and decreased the amount of adipose tissue [4], while Takanabe et al. have found miR-143 levels associated with markers of adipocyte differentiation, and up-regulated in adipose tissue of high-fat diet -induced obese mice [5]. [score:4]
In conclusion, we have demonstrated that the expression levels of miR-483-3p, miR-103 and miR-143 in SAT are mainly influenced by age, obesity and birth weight in a non-genetic manner. [score:3]
Using SAT biopsies from a unique cohort of 244 elderly MZ and DZ twins, we estimated the genetic influence on the expression of miR-483-3p, miR-103 and miR-143, and found low heritability estimates. [score:3]
BMI: We found that an increase of 3.7 kg/m [2] in BMI was associated with a 34% increase in miR-103 expression (p = 0.05). [score:3]
Figure 1Multivariate analyses were performed to study the association between (A) age, birth weight, BMI and sex and miR-103, miR-143 and miR-483-3p expression in adipose tissue from elderly twins and the association between (B) miR-103, miR-143 and miR-483-3p and 2 h glucose values after an oral glucose tolerance test, hemoglobin A1c (HbA1c), homeostatic mo del assessment of insulin resistance (HOMA-IR) and triglycerides shown for all subjects (black), dizygotic (DZ) twins (blue) and monozygotic (MZ) twins (orange). [score:3]
Therefore, although our current cross-sectional association study cannot establish causality, we suggest that miR-103 is likely to be involved in the development of a dysfunctional metabolism and possibly T2D in humans. [score:2]
The results by Trajkovski et al. suggest that miR-103 repression of caveolin-1, through destabilization of the insulin receptor, leads to increased insulin resistance in the adipose tissue [4]. [score:1]
Importantly, using twins gives us a unique opportunity to explore the relative influence of genetic versus environmental factors on the levels of miR-483-3p, miR-103 and miR-143 in human SAT. [score:1]
We evaluated the associations between age, sex, birth weight and BMI; and the expression levels of miR-483-3p, miR-103 and miR-143 (Figure 1A). [score:1]
miR-103: A one SD (~10%) increase in miR-103 levels was associated with a ~8% increase in 2 h glucose levels (p < 0.001), a 2% increase in HbA1c (p = 0.001) and, additionally, we found a trend towards a 5% increase in triglycerides (p = 0.07). [score:1]
In the present study of 244 subjects, we found that miR-103 levels were positively and independently associated with BMI, 2 h glucose levels as well as HbA1c, and, in addition, we found a trend towards a positive association with plasma triglyceride levels. [score:1]
The interclass correlations for MZ and DZ twins were not significantly different for any of the miRNAs and all heritability estimates were low (0.21, 0.12 and ~0 for miR-483-3p, miR-143 and miR-103 respectively). [score:1]
We evaluated the associations between glucose metabolism (2-hour (2 h) glucose from an OGTT and hemoglobin A1c (HbA1c)), insulin resistance (HOMA-IR) and lipid metabolism (triglyceride levels); and miR-483-3p, miR-103 and miR-143 expression levels (Figure 1B). [score:1]
Considering the variation in human subjects, we expected that possible effects upon miR-103 expression might more readily be revealed through investigation of a larger cohort. [score:1]
miR-103 has also been investigated in two relatively small human studies, with no detected differences in the expression between non-obese and obese women with or without T2D (n = 6–13) [21], or between newly diagnosed T2D subjects and control subjects (n = 6–9) [22]. [score:1]
Trajkovski et al. demonstrated that miR-103 silencing improved glucose homeostasis and insulin sensitivity in mice and demonstrated an association between miR-103 and body weight [4]. [score:1]
While we did not see any association between miR-103 and insulin resistance as expressed by HOMA-IR, it should be noted that a more specific measure of insulin resistance, which can be obtained using the euglycemic hyperinsulinaemic clamp technique, was not available. [score:1]
miR-103 has previously been found to have a key role in murine insulin sensitivity, and our findings here suggest that miR-103 may have a similar importance in human adiposity and glucose metabolism. [score:1]
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[+] score: 29
[A] The expression of candidate biomarkers, miR-200a, miR-200b, miR-200c and miR-182 and [B] the expression of candidate normalizers, miR-103, miR-638, miR-92a and RNU48 in SEOC and OSE(tsT) cell lines by qRT-PCR normalized to Z30 and plotted as log [10] ratios. [score:5]
For the current study, miR-103, miR-92a, miR-638 and RNU48 were assessed as potential endogenous normalizers and miR-103 chosen as it had low differential expression between the SEOC and healthy cohorts (P = 0.768). [score:3]
miR-103, miR-92a and miR -638 had relatively invariant expression across all ovarian cell lines, and with small-nucleolar C/D box 48 (RNU48) were assessed in RNA extracted from serum as candidate endogenous normalizers. [score:3]
[B] Heatmap showing expression relative to OSE(tsT) cells (ie OSE(tsT) set to log [2]0) for candidate biomarkers in SEOC cell lines (miR-200a, b, c, and miR-182) and candidate endogenous controls for normalization (miR-638, miR-92a and miR-103). [score:3]
miR-103 had also been reported to have similar expression across ovarian cancer and normal tissues [29]. [score:3]
[A] Mean expression of miR-182, miR-200a, miR-200b and miR-200c in cancer and normal serum; volume adjusted values normalized to miR-103 (ΔΔC [T]/L [-1] of serum assayed) +/- SEM (N = 56). [score:2]
Individually, miR-200a, miR-200b and miR-200c normalized to serum volume and miR-103 were significantly higher in serum of the SEOC cohort (P < 0.05; 0.05; 0.0005 respectively) and in combination, miR-200b + miR-200c normalized to serum volume and miR-103 was the best predictive classifier of SEOC (ROC-AUC = 0.784). [score:1]
qRT-PCR assays were performed on RNA from the cell lines and confirmed that miR-92a and miR-103 were not differentially expressed in any of the SEOC cell lines compared to OSE(tsT) cells (P > 0.05; Figure 2B). [score:1]
No correlations were found between subject age and miR-103, miR-92a or miR-638 levels (Additional file 1: Figure S1), and no significant differences between the SEOC and healthy groups were observed for miR-103 (P = 0.768) or miR-92a (P = 0.367; Figure 3). [score:1]
miR-103 has previously been found to be highly invariant across a number of cancerous and adjacent normal tissues including ovarian tissue, and ranked in the top 3 of 16 candidates for use as a normalizer for tissue studies [29]. [score:1]
To determine the diagnostic potential of selected miRNAs, ROC-AUC curves were constructed for miR-200a, b and c. A multivariate mo del that combined miR-200b + c with normalization by serum volume and miR-103 gave the highest ROC-AUC for discriminating women with SEOC from healthy women (AUC = 0.784; Table 2, Figure 4B). [score:1]
We propose that specific miRNAs may have utility as serum biomarkers for SEOC and identified that a small marker panel combining miR-200b and c normalized to serum volume and miR-103, is a positive classifier of SEOC. [score:1]
We found no association between subject age and serum miRNA levels for miR-200a, b, c, (or miR-103, miR-92a, miR-182, miR-638 or RNU48). [score:1]
Volume adjusted C [T]s were normalized to miR-103. [score:1]
From this list, miRNA previously reported to be detected in serum or plasma were selected for further analysis, specifically, miR-92a, miR-103 [12, 14, 27] and miR-638 [28] (Figure 1B). [score:1]
From these results, miR-103 was chosen as the endogenous normalizer for serum miRNA. [score:1]
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[+] score: 28
We also found that treatment of mPGES-1 [+/+] cells with miR-15a, miR-103 or miR-186 mimics (50 nM), besides increasing the endogenous pool of their respective miRNAs (Supplementary Figure S4B), down-regulated VEGF expression/production (p < 0.001, Supplementary Figure S4C, S4D, S4E and Figure 4A). [score:6]
miRNA mimics and inhibitors target the following mature miRNA sequences: for miR-186-5p (5′-CAAAGAAUUCUCCUUUUGGGCU-3′), for miR-15a-5p (5′-UAGCAGCACAUAAUGGUUUGUG-3′) and for miR-103-3p (5′-AGCAGCAUUGUACAGGGCU AUGA-3′). [score:5]
Five miRNAs (miR-15b, miR-93 miR-15a, miR-186 and miR-103) have been predicted to target VEGF and HIF-1α on the basis of DianaMT, PICTAR5, miRanda, miRBASE, miRWALK and Target Scan analysis (Supplementary Table S2). [score:5]
analysis provided further evidence of down-regulation of miR-15a, miR-186 and miR-103 in mPGES-1 [+/+] cells (Supplementary Figure S4A). [score:4]
The miRNA mimics and inhibitors for miR-103, miR-186 and miR-15a were from Qiagen and transfection was performed with Lipofectamine 2000 (Life Technologies) following the manufacturer's protocol. [score:3]
3 × 10 [4] cells were exposed to 10% FBS or to PGE-2 (1 μM) for 48 h or siRNA -transfected for Dicer or transfected with mimics for miR-15a, miR-186, miR-103 or with miRNA inhibitors for miR-15a and miR-186. [score:3]
Figure 4(A) ELISA for VEGF in DU145 and PC3 mPGES-1 [+/+] cells (1% FBS, 48 h) transfected with miR-15a, miR-186 or miR-103 mimics (50 nM). [score:1]
The exception was miR-103, which failed to affect VEGF (Supplementary Figure S4C, S4D). [score:1]
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[+] score: 25
Several mRNAs targeted by neuronal miRNAs (i. e., miR-124, miR-9 and miR-96) were downregulated upon increased miRNA expression, consistent with expectations of the role of miRNAs in repressing downstream targets, whereas for the decreasing miR-302 cluster and miR-103, similar proportions of the targets were up- and downregulated. [score:15]
We initially analyzed the correlations between the expression levels of miR-302a-d, miR-124, miR-96, miR-9 and miR-103 and their experimentally validated (miRTarBase 4.4 (Hsu et al, 2011)) mRNA targets that are expressed in iNGN cells (Supplementary Fig S8). [score:7]
Validated miRNA targets (Hsu et al, 2011) were used for correlation analysis with miR-302a-d, miR-9, miR-96, and miR-103. [score:3]
[1 to 20 of 3 sentences]
15
[+] score: 25
Other miRNAs from this paper: hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7d, hsa-let-7e, hsa-let-7f-1, hsa-let-7f-2, hsa-mir-15a, hsa-mir-16-1, hsa-mir-18a, hsa-mir-19a, hsa-mir-19b-1, hsa-mir-19b-2, hsa-mir-20a, hsa-mir-21, hsa-mir-22, hsa-mir-24-1, hsa-mir-24-2, hsa-mir-25, hsa-mir-26a-1, hsa-mir-26b, hsa-mir-27a, hsa-mir-29a, hsa-mir-30a, hsa-mir-31, hsa-mir-33a, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-96, hsa-mir-101-1, hsa-mir-29b-1, hsa-mir-29b-2, hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-107, hsa-mir-16-2, hsa-mir-196a-1, hsa-mir-198, hsa-mir-129-1, hsa-mir-148a, hsa-mir-30c-2, hsa-mir-30d, hsa-mir-7-1, hsa-mir-7-2, hsa-mir-7-3, hsa-mir-10a, hsa-mir-10b, hsa-mir-34a, hsa-mir-181a-2, hsa-mir-181b-1, hsa-mir-181c, hsa-mir-182, hsa-mir-183, hsa-mir-196a-2, hsa-mir-199b, hsa-mir-203a, hsa-mir-204, hsa-mir-210, hsa-mir-211, hsa-mir-212, hsa-mir-181a-1, hsa-mir-214, hsa-mir-215, hsa-mir-216a, hsa-mir-217, hsa-mir-219a-1, hsa-mir-221, hsa-mir-222, hsa-mir-223, hsa-mir-224, hsa-mir-200b, hsa-let-7g, hsa-let-7i, hsa-mir-1-2, hsa-mir-15b, hsa-mir-23b, hsa-mir-30b, hsa-mir-122, hsa-mir-124-1, hsa-mir-124-2, hsa-mir-124-3, hsa-mir-125b-1, hsa-mir-128-1, hsa-mir-130a, hsa-mir-132, hsa-mir-133a-1, hsa-mir-133a-2, hsa-mir-137, hsa-mir-138-2, hsa-mir-140, hsa-mir-141, hsa-mir-142, hsa-mir-143, hsa-mir-145, hsa-mir-9-1, hsa-mir-9-2, hsa-mir-9-3, hsa-mir-125a, hsa-mir-125b-2, hsa-mir-126, hsa-mir-127, hsa-mir-129-2, hsa-mir-138-1, hsa-mir-146a, hsa-mir-150, hsa-mir-184, hsa-mir-185, hsa-mir-195, hsa-mir-206, hsa-mir-320a, hsa-mir-200c, hsa-mir-1-1, hsa-mir-155, hsa-mir-181b-2, hsa-mir-128-2, hsa-mir-29c, hsa-mir-30c-1, hsa-mir-200a, hsa-mir-101-2, hsa-mir-219a-2, hsa-mir-34b, hsa-mir-34c, hsa-mir-301a, hsa-mir-99b, hsa-mir-296, hsa-mir-130b, hsa-mir-30e, hsa-mir-26a-2, hsa-mir-365a, hsa-mir-365b, hsa-mir-375, hsa-mir-376a-1, hsa-mir-378a, hsa-mir-382, hsa-mir-383, hsa-mir-151a, hsa-mir-148b, hsa-mir-338, hsa-mir-133b, hsa-mir-325, hsa-mir-196b, hsa-mir-424, hsa-mir-20b, hsa-mir-429, hsa-mir-451a, hsa-mir-409, hsa-mir-412, hsa-mir-376b, hsa-mir-483, hsa-mir-146b, hsa-mir-202, hsa-mir-181d, hsa-mir-499a, hsa-mir-376a-2, hsa-mir-92b, hsa-mir-33b, hsa-mir-151b, hsa-mir-320b-1, hsa-mir-320c-1, hsa-mir-320b-2, hsa-mir-378d-2, hsa-mir-301b, hsa-mir-216b, hsa-mir-103b-2, hsa-mir-320d-1, hsa-mir-320c-2, hsa-mir-320d-2, hsa-mir-378b, hsa-mir-320e, hsa-mir-378c, hsa-mir-378d-1, hsa-mir-378e, hsa-mir-378f, hsa-mir-378g, hsa-mir-378h, hsa-mir-378i, hsa-mir-219b, hsa-mir-203b, hsa-mir-451b, hsa-mir-499b, hsa-mir-378j
Uptake of hyperosmotic 2% saline water resulted in upregulation of expression of miR-7b, miR-9, miR-29b, miR-137, and miR-451 and downregulation of miR-409, miR-107, miR-103, miR-185, and miR-320 in hypothalamus in mice (Lee et al. 2006). [score:9]
OsmoticUptake of hyperosmotic 2% saline water resulted in upregulation of expression of miR-7b, miR-9, miR-29b, miR-137, and miR-451 and downregulation of miR-409, miR-107, miR-103, miR-185, and miR-320 in hypothalamus in mice (Lee et al. 2006). [score:9]
Xia et al. (2011) Heart miR-218a-1/2 Zebrafish Knockdown, overexpression, ISH, luciferase reporter assay, qRT-PCR Heart field migration Fish et al. (2011) miR-138 Zebrafish Knockdown, antagomiR, ISH, luciferase reporter assay, qRT-PCR Cardiac patterning Morton et al. (2008) miR-21, miR-218a Zebrafish Knockdown, overexpression, ISH, qRT-PCR, luciferase reporter assay Heart valve formation Chiavacci et al. (2012) and Banjo et al. (2013) let-7e,f,g,h,i,j,k,l,m,n,o, miR-1a, miR-20, miR-21a,b,c, miR-29a,b, miR-103, miR-125, miR-126a,b, miR-128c, miR-145, and miR-199b Asian seabass qRT–PCR ? [score:5]
Soares et al. (2009) let-7a,b,c,f,i, miR-7b, miR-9-5p, miR-9-3p, miR-34b, miR-103, miR-107, miR-124a, miR-125a,b, miR-128, miR-129-3p, miR-132, miR-138, miR-181a,b, miR-216, miR-217, miR-219, and miR-375 Zebrafish Microarray, ISH ? [score:1]
Ma et al. (2012) let-7g, k, h, i, l, miR-29a, b, miR-103, miR-124a, b, c, d, and miR-125 Asian seabass qRT–PCR ? [score:1]
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[+] score: 24
To test this possibility, we considered a gene with a perfect 7-mer seed (nucleotides 2–8 from the 5’ end) match of miR-103-3p or moR-103a-2-3p in its 3’ UTR as a putative target of that small RNA and predicted the targets for these two in the three distinct gene sets: genes down-regulated by both mimics, genes down-regulated by only miR-103a-3p and genes down-regulated by moR-103a-2-3p (Table 7, S7 Table). [score:13]
Interestingly, many moRNA-deriving, cancer -associated hairpins are also expressed in oocytes such as mir-17-92 cluster, miR-20, miR-21, miR-15a/16 and miR-103 [50] whereas miR-421 from mir-374b-421 cluster has been reported to be up-regulated in ovarian teratomas [60]. [score:6]
Sixty nM of custom design moR-103-3p (AAGAACCAAGAAUGGGCUGC), miR-103-3p (4464066) or negative control #1 (neg#1, 4464058) was transfected twice at following days using 1.5 μl/ml RNAi max reagent (Life Technologies) starting from approximately 40% confluent HFF-1 cells in serum-free KnockOut DMEM. [score:2]
We observed that the sequences of moR-103a-2-3p and miR-103-3p are partly similar which could explain some of the common regulated genes (S2 Fig. ). [score:2]
Three independent biological samples were prepared for three conditions: moR-103-3p, miR-103-3p, neg#1. [score:1]
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[+] score: 24
Moreover, NF1 (a negative regulator of the ras signal transduction pathway) is also overtargeted by miR-103/107 and two other HNSCC upregulated. [score:7]
Other authors demonstrated that miR-103 is an oncomiR that promotes colorectal cancer proliferation and migration through down-regulation of the tumor suppressor genes DICER and PTEN [49]. [score:6]
Chen and colleagues showed that miR-103 and miR-107 target the metastasis suppressors DAPK and KLF4 [45]. [score:5]
Furthermore, high expression of miR-103/107 was found correlated with poor survival in human esophageal cancer [41]. [score:3]
Another in vitro study demonstrated the interaction of miR-103 with GPRC5A, a G-protein-coupled receptor that has been associated with a variety of cancers (reviewed in [48]). [score:1]
As evidenced in Figures 4 and 5, the interaction network approach underscores the key role of let-7a/f, miR-26a/b, miR-103, miR-107, miR-205, and miR-320a/b among others. [score:1]
Remarkably, circulating miRNA is miR-103-3p/107 was found significantly associated with the size and/or extent (reach) of the primary tumor (T). [score:1]
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[+] score: 23
In-vivo miR-103 was reported to be downregulated in mature adipocytes from obese mice [55], although studies in obese human adipose tissue show miR-103 is upregulated [9, 66]. [score:7]
TNF-α treatment of differentiated adipocytes downregulated miR-103 and miR-143 expression, although the mechanism responsible remains unknown [55]. [score:6]
When miR-103 is overexpressed in the presence of adipogenic stimuli, adipogenesis accelerates, as shown by increased triglyceride accumulation and adipogenic gene expression [55]. [score:5]
miR-103 is reported to be upregulated during differentiation of human pre-adipocytes [60]. [score:4]
It appears more experimental work is needed to establish the role of miR-103 in adipogenesis and obesity. [score:1]
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Expression of Large S–S (pCDH-Large S–S) reversed such suppression by inhibiting let-7 g function (left), but not in case of miR103 (right). [score:7]
When examining the effects of forced expression of miRNAs, 0.4 μg Let-7 g or miR103 precursor -expressing plasmids (pCDH-let-7 g or pCDH-miR103) were transfected simultaneously. [score:5]
The suppression of miRNA function by the Large S–S construct was not observed when using the miR103 reporter or precursor constructs (Fig. 2b), again suggesting specificity to let-7 g function. [score:3]
The firefly luciferase -based reporter carrying let-7 g- and miR103-responsive elements in its 3′ untranslated region, to examine corresponding miRNA function (pGL4-let-7 g and pGL4-miR103), and the internal control renilla luciferase -based plasmids (pGL4-TK) have been described previously 47. [score:3]
Let-7 g and miR103 precursor -expressing plasmids were constructed previously 48 49. [score:3]
Data are shown after normalizing the let-7 g levels to miR103 levels in the Ago2 -associated complexes. [score:1]
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[+] score: 22
Other miRNAs from this paper: hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7d, hsa-let-7e, hsa-let-7f-1, hsa-let-7f-2, hsa-mir-21, hsa-mir-22, hsa-mir-23a, hsa-mir-24-1, hsa-mir-24-2, hsa-mir-25, hsa-mir-26b, hsa-mir-27a, hsa-mir-31, hsa-mir-33a, hsa-mir-99a, hsa-mir-100, hsa-mir-29b-1, hsa-mir-29b-2, hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-199a-1, hsa-mir-148a, hsa-mir-147a, hsa-mir-34a, hsa-mir-182, hsa-mir-199a-2, hsa-mir-212, hsa-mir-221, hsa-mir-224, hsa-let-7g, hsa-let-7i, hsa-mir-27b, hsa-mir-30b, hsa-mir-125b-1, hsa-mir-130a, hsa-mir-132, hsa-mir-142, hsa-mir-145, hsa-mir-152, hsa-mir-153-1, hsa-mir-153-2, hsa-mir-125a, hsa-mir-125b-2, hsa-mir-127, hsa-mir-134, hsa-mir-200c, hsa-mir-106b, hsa-mir-361, hsa-mir-148b, hsa-mir-20b, hsa-mir-410, hsa-mir-202, hsa-mir-503, hsa-mir-33b, hsa-mir-643, hsa-mir-659, bta-let-7f-2, bta-mir-103-1, bta-mir-148a, bta-mir-21, bta-mir-221, bta-mir-26b, bta-mir-27a, bta-mir-99a, bta-mir-125a, bta-mir-125b-1, bta-mir-145, bta-mir-199a-1, bta-mir-27b, bta-mir-30b, bta-mir-31, bta-mir-127, bta-mir-142, bta-mir-20b, bta-let-7d, bta-mir-132, bta-mir-148b, bta-mir-200c, bta-mir-22, bta-mir-23a, bta-mir-29b-2, bta-mir-361, bta-let-7g, bta-mir-24-2, bta-let-7a-1, bta-let-7f-1, bta-let-7i, bta-mir-25, bta-let-7a-2, bta-let-7a-3, bta-let-7b, bta-let-7c, bta-let-7e, bta-mir-103-2, bta-mir-125b-2, bta-mir-34a, hsa-mir-708, hsa-mir-147b, hsa-mir-877, hsa-mir-940, hsa-mir-548j, hsa-mir-302e, hsa-mir-103b-2, bta-mir-100, bta-mir-106b, bta-mir-130a, bta-mir-134, bta-mir-147, bta-mir-152, bta-mir-153-1, bta-mir-153-2, bta-mir-182, bta-mir-24-1, bta-mir-199a-2, bta-mir-202, bta-mir-212, bta-mir-224, bta-mir-33a, bta-mir-33b, bta-mir-410, bta-mir-708, bta-mir-877, bta-mir-940, bta-mir-29b-1, bta-mir-148c, bta-mir-503, bta-mir-148d
Relative expression of candidate circulatory miRNAs in blood plasma of hypersitimulated heifers across different days during estrous (a- f) Expression of miR-221, miR-103, let-7g, miR-134, miR-147 and miR-127-3p was determined by RT-qPCR and each miRNA expression level was normalized using global normalization method. [score:7]
As shown in Fig.   4 expression analysis of candidate miRNAs (miR-221, miR-103, let-7 g, miR-134, miR-147 and miR-127-3p) using qRT-PCR revealed the presence of temporal changes in the pattern of expression depending on the time during the estrous cycle as shown in Fig.   4. While four of the candidates namely. [score:5]
For instance, miR-221, miR-103, miR-134 and miR-127-3p show significantly higher expression at day 7 of estrous cycle compared to day 0 or day 3. In contrast, miR-147 has significantly lower expression at day 7 of estrous. [score:4]
miR-221, miR-103, miR-134 and miR-127-3p showed a significant increase in abundance at day 7 of the estrous cycle compared to days 0 and 3, miR-147 showed a decreasing pattern from day 0 to day 7. No significant difference in the expression of let-7 g miRNA has been observed between the days during estrous cycle. [score:2]
Data are presented as raw Ct value and Ct value of more than 35 was considered as undetected Here we have tried to detect candidate miRNAs, which were enriched (miR-221, miR-103 & let-7 g) or suppressed (miR-134, miR-147 & miR-127-3p) in blood plasma samples of hyperstimulated animals compared to the unstimulated ones. [score:1]
Mir-103 and miR-127-3p were not detected in the Ago2 protein fraction of both treatment groups. [score:1]
Candidates including miR-182 from follicular fluid (Fig.   4) and miR-221, miR-103 and miR-127-3p from blood plasma (Fig.   5) were found to be detected only in exosomal fraction and completely undetected in the Ago2 fraction. [score:1]
As shown in Fig.   7, all candidate miRNAs, except miR-103 and miR-127-3p, were detected in both exosomal and Ago2 fraction of blood plasma of both hyperstimulated and unstimulated heifers. [score:1]
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[+] score: 21
Hence, upregulation of miR-103 and miR-107 as well as downregulation of miR-744 in asthmatic horses highlight a potential role of this miRNA network in chronic inflammatory conditions. [score:7]
This study reported a deregulation of the cell cycle characterized by an upregulation of various miR-15/16 members, including miR-103 and miR-107a, as well as a downregulation of miR-744. [score:6]
The closely related miRNAs miR-103 and miR-107a are known to pilot cell cycle arrest and their up-regulation in horses suffering from severe equine asthma support previous findings about cell cycle disturbances in equine asthma [33, 97, 98]. [score:4]
Xia W. Ni J. Zhuang J. Qian L. Wang P. Wang J. MiR-103 regulates hepatocellular carcinoma growth by targeting AKAP12Int. [score:3]
Using DESeq2, we identified 11 miRNAs as statistically significant DEmiRs after accounting for the level of hemolysis: eca-miR-128, eca-miR-744, eca-miR-197, eca-miR-103 and the closely related eca-miR-107a, eca-miR-30d, eca-miR-140-3p, eca-miR-7, eca-miR-361-3p, eca-miR-148b-3p and eca-miR-215. [score:1]
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[+] score: 18
miR-103 inhibits osteoblast proliferation through suppression of Cav1.2 expression under simulated microgravity condition in vitro (Sun et al., 2015). [score:7]
MiR-103 inhibits osteoblast proliferation mainly through suppressing Cav1.2 expression in simulated microgravity. [score:6]
In comparison with the BR-45d value, the levels of 3 miRNAs-miR-103, 130a, and 1234 were significantly higher in plasma of volunteers after 10 days of recovery. [score:1]
Next, we focused our studies on the 11 miRNAs: miR-103, 130a, 1234, 1290, 148a, 151-5p, 151-3p, 199a-3p, 20a, 363, and 451a which were verified by PCR on the basis of microarray results. [score:1]
Ten circulating miRNAs (miR-103, 130a, 1234, 1290, 151-5p, 151-3p, 199a-3p, 20a, 363, and 451a) have potential detective value for distinguishing the physiological changes after bed-rest, and miR-1234 might be the diagnostic biomarker of bone loss induced by bed rest or disuse. [score:1]
The AUC of remaining eight miRNAs was 0.8929 for miR-1290 (95% CI 0.7736–1.012, p = 0.00069), 0.8896 for miR-363 (95% CI 0.7514–1.028, p = 0.0010), 0.8799 for miR-20a (95% CI 0.7171–1.043, p = 0.0014), 0.8701 for miR-151-5p (95% CI 0.7223–1.018, p = 0.0018), 0.8571 for miR-151-3p (95% CI 0.6948–1.019, p = 0.0026), 0.8036 for miR-103 (95% CI 0.6089–0.9983, p = 0.0087), 0.7532 for miR-199a-3p (95% CI 0.5381–0.9684, p = 0.033), and 0.6788 for miR-148a (95% CI 0.4504–0.9067, p = 0. 12). [score:1]
Table 7 showed serum PICP at total time points were significantly associated with miR-363 (r = −0.3347 p < 0.05), miR-1290 (r = −0.2908, p < 0.05), miR-103 (r = −0.2739, p < 0.05), miR-451a (r = −0.3204, p < 0.05), miR-130a (r = −0.3402, p < 0.05), miR-1234 (r = −0.2396, p < 0.05), and miR-20a (r = −0.3148, p < 0.05), respectively. [score:1]
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[+] score: 17
Additionally, haploinsufficiency in Dicer, a protein responsible for miRNA biogenesis, can promote tumorigenesis (Kumar et al., 2009) and suppression of Dicer expression by miR-103/107 attenuates miRNA biogenesis and promotes metastasis (Martello et al., 2010). [score:5]
By comparing the downregulated miRNAs in metastatic sarcomas from human and mouse, we found six miRNAs common to both: miR-16, miR-103, miR-146a, miR-223, miR-342 and miR-511 (Fig.  1D,E). [score:4]
Interestingly, despite miR-103 being the most downregulated miRNA in both human and mouse metastatic sarcomas, restoration of miR-103 had no effect on either migration or invasion. [score:4]
Similar analysis in mouse metastatic sarcomas revealed overlap for several downregulated miRNAs including miR-16, miR-103, miR-146a, miR-223, miR-342 and miR-511. [score:4]
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[+] score: 17
Based on bioinformatics predictions, no miR-103 target site is present in the 3′UTR of hjurp (data not shown) that is downregulated in the hLRRK2-R1441G mice, suggesting that this gene is not directly regulated by this miRNA. [score:8]
However, since no complementary changes in mRNA expression were identified in the LRRK2 mutant mice, it is difficult to predict the role of miR-103 in this mouse mo del and in the context of PD. [score:3]
Our microarray analysis identified miR-103 to be specifically misregulated in hLRRK2-R1441G mice. [score:2]
It would thus be relevant to identify and validate proteins regulated by miR-103 in the mouse brain, in both normal and pathological conditions. [score:2]
Interestingly, miR-103 was specifically affected in hLRRK2-R1441G mice (Table S4). [score:1]
We validated changes in miR-103 levels by qRT-PCR (p = 0.055, 0.79 fold change) (Fig. 2E). [score:1]
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[+] score: 17
We suggest that some miRNAs targeting this machinery (e. g., let-7, miR-27, miR-29, and miR-103) are expressed fairly wi dely, while others (e. g., miR-138 and miR-25) have lower and more restricted expression. [score:7]
Many semaphorins and their receptors are predicted targets of brain-expressed miRNAs (e. g., let-7c, miR-125b, miR-153, miR-103, miR-323, miR-326, and miR-337). [score:5]
” Neuronal differentiation of embryonic carcinoma cells by retinoic acid in both mice and humans is coupled to induction of let-7b, miR-30, miR-98, miR-103, and miR-135 (Sempere et al. 2004), and their targets are enriched in “neurogenesis” (3.5-fold). [score:3]
Our data suggest that the RNAi–miRNA machinery itself is under miRNA regulation; for example Dicer appears to be controlled by let-7 and miR-15b; Ago-1 by let-7 and miR-29b/c; Ago-2 by miR-138; Ago-3 by miR-138, miR-25, and miR-103; and Ago-4 by miR-27a/b. [score:2]
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[+] score: 16
Other miRNAs from this paper: hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-mir-21, hsa-mir-26a-1, hsa-mir-27a, hsa-mir-28, hsa-mir-30a, hsa-mir-96, hsa-mir-98, hsa-mir-99a, hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-196a-1, hsa-mir-199a-1, hsa-mir-148a, hsa-mir-30d, hsa-mir-34a, hsa-mir-196a-2, hsa-mir-199a-2, hsa-mir-23b, hsa-mir-27b, hsa-mir-125b-1, hsa-mir-143, hsa-mir-145, hsa-mir-152, hsa-mir-125a, hsa-mir-125b-2, hsa-mir-194-1, hsa-mir-194-2, hsa-mir-200a, hsa-mir-99b, hsa-mir-26a-2, hsa-mir-378a, hsa-mir-342, hsa-mir-148b, hsa-mir-338, hsa-mir-335, hsa-mir-196b, hsa-mir-484, hsa-mir-486-1, hsa-mir-1271, hsa-mir-378d-2, bta-mir-26a-2, bta-mir-103-1, bta-mir-148a, bta-mir-21, bta-mir-27a, bta-mir-30d, bta-mir-484, bta-mir-99a, bta-mir-125a, bta-mir-125b-1, bta-mir-145, bta-mir-199a-1, bta-mir-27b, bta-mir-98, bta-mir-148b, bta-mir-200a, bta-mir-30a, bta-let-7a-1, bta-mir-342, bta-mir-23b, bta-let-7a-2, bta-let-7a-3, bta-mir-103-2, bta-mir-125b-2, bta-mir-34a, bta-mir-99b, hsa-mir-885, hsa-mir-103b-2, bta-mir-143, bta-mir-152, bta-mir-16a, bta-mir-194-2, bta-mir-196a-2, bta-mir-196a-1, bta-mir-196b, bta-mir-199a-2, bta-mir-26a-1, bta-mir-28, bta-mir-335, bta-mir-338, bta-mir-378-1, bta-mir-486, bta-mir-885, bta-mir-96, bta-mir-1271, bta-mir-2299, bta-mir-199c, bta-mir-1388, bta-mir-194-1, bta-mir-378-2, hsa-mir-378b, bta-mir-3431, hsa-mir-378c, hsa-mir-4286, hsa-mir-378d-1, hsa-mir-378e, hsa-mir-378f, hsa-mir-378g, hsa-mir-378h, hsa-mir-378i, bta-mir-4286-1, bta-mir-4286-2, hsa-mir-378j, bta-mir-378b, bta-mir-378c, hsa-mir-486-2, bta-mir-378d, bta-mir-194b, bta-mir-194b-2
The expression of miRNA in a sample was normalized to bta-miR-103 and calculated relative to day-14 as follows: ΔCt [target miRNA] = Ct [target miRNA]–Ct [bta-miR-103]; relative expression of target miRNA = 2-ΔΔCt, where ΔΔCt = ΔCt [target miRNA, day+28] - ΔCt [target miRNA, day-14]. [score:13]
In dairy goats, miR-27a and miR-103 have been found to function as regulators of milk fat metabolism and lactation cycle [26, 27]. [score:2]
Bta-miR-103 (product No. [score:1]
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27
[+] score: 15
S3 DatasetLog2-transformed miRNA expression ratios obtained from RT-qPCR analysis are plotted for the most reliable (RF ≥ 0.8) miRNAs from set A: (A) miR-100, (B) miR-146a, (C) miR-1274B and the most informative (MoR-value d≥0.57) miRNAs from set B: (D) miR-505*, (E) miR-375, and (F) miR-103. [score:3]
Most relevant gene targets identified by IPA were BACE1, REST for miR-103, MAPT for miR-219 and CDK5R1 for miR-375 (S4 Dataset). [score:3]
We also found significant correlations between miR-103 targeting BACE1 and both tau for the whole study sample (r = -0.4223, p = 0.045) and Aβ [1–42] (r = 0.5980, p = 0.024) for the control group. [score:3]
ROC curve analysis showed an AUC of 0.72 (miR-100), an AUC of 0.87 (miR-103) and an AUC of 0.99 (miR-375) for this combination (S5 Dataset). [score:1]
Another discriminant analysis performed on the most reliable biomarker miR-100 from set A (Fig 2B and 2C and S3 Dataset) and the most abundant miR-103 and miR-375 from set B (S2 Dataset and S3 Dataset) revealed for the two test groups a total correct classification rate of 96% after substitution of missing values, positively classifying controls and AD cases with 96.4% and 95.5% accuracy, respectively. [score:1]
The MoR plot illustrates the 9 most informative miRNAs, hsa-miR-505-5p, hsa-miR-4467, hsa-miR-766, hsa-miR-375, hsa-miR-708, hsa-miR-3622b-3p, hsa-miR-296, hsa-miR-219 and hsa-miR-103, each reaching a MoR value ≥ 0.57 (critical MoR value on the information chain). [score:1]
Moreover, we could also confirm the 9 informative miRNAs (miR-505-5p, miR-4467, miR-766, miR-375, miR-708, miR-3622b-3p, miR-296, miR-219 and miR-103) from set B as significant biomarkers by MANCOVA all reaching Bonferroni corrected significance. [score:1]
S5 Dataset ROC curves for the combination of (A) miR-146a and p-tau, and (B) miR-100, miR-103 and miR-375 to separate 28 control- from 22 AD cases. [score:1]
By performing discriminant analysis including candidate miRNAs of both subsets as well as in combination with CSF protein marker, we could, irrespective of FOC, demonstrate overall classification rates of 96% (miR-100, miR-375 and miR-103) and 86.4% (miR-146a and p-tau). [score:1]
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[+] score: 15
Decreased levels of miR-103/107 prevent the downregulation of FADD, thus allowing FADD to inhibit H [2]O [2] -induced necrotic cell death by its negative regulation on RIPK 1 and 3. Researchers have only just begun to learn the importance of the interaction of ncRNAs and its significance during pathogenesis of MI. [score:7]
H19 acts as an endogenous sponge of miR-103/107, which results in miR-103/107 downregulation (Table 2 and Figure 2). [score:4]
Wang J. X. Zhang X. J. Li Q. Wang K. Wang Y. Jiao J. Q. Feng C. Teng S. Zhou L. Y. Gong Y. MicroRNA-103/107 Regulate Programmed Necrosis and Myocardial Ischemia/Reperfusion Injury Through Targeting FADD Circ. [score:3]
Wang et al. also demonstrated the involvement of miR-103/107 and lncRNA H19 in myocardial necrosis through Fas -associated protein with death domain (FADD) [66]. [score:1]
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[+] score: 15
Western blotting results showed that overexpressing miR-9 and miR-137 significantly reduced CUL4A protein expression in HGC-27 cells; whereas, overexpressing miR-103 and miR-107 had no effect on CUL4A protein expression (Figure 5B). [score:9]
Four miRNAs, including miR-103, miR-107, miR-9, and miR-137 (Figure 5A), were predicted using two independent miRNA databases: TargetScan (http://www. [score:3]
B. Western blotting results showed that the overexpression of miR-9 and miR-137 significantly reduced CUL4A protein levels in HGC-27, SGC-7901 and BGC-823 cells; whereas, miR-103 and miR-107 had no effect on CUL4A protein levels. [score:3]
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[+] score: 15
Chen et al. showed that miR-103/107 directly targets MET inducer KLF4 and DAPK expression, leading to promoting metastasis [81]. [score:6]
One study showed that miR-103/107 induced EMT by targeting Dicer expression, leading to the decrease of miR-200 [78]. [score:5]
Moreover, miR-103/miR-107 up-regulated ZEB levels in a miR-200 -dependent manner [78]. [score:4]
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[+] score: 15
Relatively little is known about the functions in gene regulation of micro -RNAs (hsa-mir-214, hsa-mir-103, hsa-mir-107, & hsa-mir-98), although one member of this group, mir-214, has been implicated in cell survival in cancer [32] and another, mir-107, has been linked to Alzheimer’s disease pathogenesis [33]. [score:4]
Specifically, fetal sclera showed increased expression of mir-214, let-7c, let-7e, mir-103, mir-107, and mir-98 (1.5 to 4 fold changes, p<0.01). [score:3]
Figure 4 shows the results of comparisons of equivalent fetal and adult samples, expressed as relative fold differences for the selected micro -RNAs – hsa-let-7b, hsa-mir-214, hsa-let-7c, hsa-let-7e, hsa-mir-103, hsa-mir-107, and hsa-mir-98; microarray data are also shown for reference. [score:3]
Of the seven micro -RNAs selected for follow-up quantitative PCR analysis from the larger dataset generated from our microarray analyses (hsa-let-7b, hsa-mir-214, hsa-let-7c, hsa-let-7e, hsa-mir-103, hsa-mir-107, & hsa-mir-98), all but two of these micro -RNAs (hsa-let7b and hsa-let7c) showed significant up-regulation in fetal compared to adult sclera, irrespective of whether tissue samples were collected from the posterior pole or more peripherally. [score:3]
Subsequent validation experiments used TaqMan® micro -RNA assays on posterior and peripheral scleral samples from fetal and adult eyes (total of 4 groups; n=7 in each group) and targeted micro -RNAs showing collagen (Col1A1) specificity (i. e., hsa-let-7b, hsa-mir-214, hsa-let-7c, hsa-let-7e, hsa-mir-103, hsa-mir-107, and hsa-mir-98) and either highest significance, detection, or fold differences in comparisons of equivalent fetal and adult samples in microarray profiling. [score:2]
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32
[+] score: 14
The miR-15/107 family includes miR-15a-5p, miR-15b-5p, miR-16-5p, miR-103-3p, miR-107 (which are expressed in all vertebrates), miR-195-5p, miR-424-5p, miR-497-5p, miR-503-5p (which are expressed in mammals), and miR-646 (human specific) (Finnerty et al., 2010[53]). [score:5]
Although neither algorithm identified human endoglin mRNA MRE target sites for HITS-CLIP validated miRNAs (miR-20a-3p, miR-23b-5p, miR-29a-5p, miR-103-3p, miR-107, and miR-532-5p) (Table 7 (Tab. [score:3]
Again, it is not clear why the Diana-microT-CDS and TargetScan algorithms did not identify the miR-20a-3p, miR-23b-5p, miR-29a-5p, miR-103-3p, miR-107 and miR-532-5p MREs in human S-endoglin mRNA that were detected manually. [score:3]
It is now clear that miR-16-5p, miR-103-3p, and miR-107 belong to a group of paralogous, evolutionarily-conserved miRNAs termed the miR-15/107 family (Finnerty et al., 2010[53]). [score:1]
Importantly this group of miRNAs shares a sequence (5′ AGCAGC 3′) near the 5′ end that complements with the Diana-microT-CDS algorithm predicted miR-16-5p MREs (5′ GCUGCU 3′) and the manually identified miR-103-3p and miR-107 MREs within the human S-endoglin mRNA. [score:1]
Finally, sequence analysis detected three identical miR-103-3p and miR-107 MREs harbored in the human S-endoglin mRNA which overlaped with the three Diana-microT-CDS algorithm predicted miR-16-5p MREs above (3′-UTR MRE [5′ GCUGCU 3′, 6mer “seed” region] 842 nts downstream from the stop codon and two CDS MREs [5′ UGCUGCU 3′, 7mer “seed” region] 34 and 473 nts downstream from the start codon). [score:1]
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Targeting of miR-103/107 was demonstrated by Northern blot analysis, qRT-PCR and de-repression of the direct target Caveolin-1, whereas specificity was shown using mismatched and scrambled antagomirs. [score:6]
Furthermore, over -expression or antagomir mediated silencing of miR-103/107 in diet -induced obese mice lacking Caveolin-1 demonstrated a central role of Caveolin-1 in mediating the miR-103/107 effects on glucose tolerance and insulin sensitivity [128]. [score:3]
Recently, miR-103 and miR-107 were shown to directly regulate insulin sensitivity in vivo [128]. [score:3]
Silencing of miR-103/107 lowered plasma glucose levels in obese but not in wild-type mice, and improved glucose homeostasis and insulin sensitivity. [score:1]
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gov identifiers Mirna Therapeutics miR-34 Primary liver cancer or solid cancers with liver involvementMimicLNPs (Smarticles) Tumor regression, enhanced survival and inhibited the growth of non-hepatic tumors Phase 1, completed NCT01829971 Mirvirasen (Santaris Pharma A/S and Hoffmann-La Roche) miR-122 Hepatitis CAnti-miRLNA -modified antisense inhibitor delivery system Reduction in viral plasma RNA levels compared from baseline Phase 2a NCT02031133 MRG-201 (MiRagen Therapeutics) miR-29 SclerodermaMimicCholesterol-conjugated miRNA duplex Reduction in aberrant cell proliferation Phase 1 NCT02603224 RG-125/AZD4076 (Regulus Therapeutics) miR-103/107 Type 2 diabetes, non-alcoholic fatty liver diseasesAntimiRGalNAc-conjugated Phase I/IIa, ongoing NCT02826525 MRG-106 (miRagen Therapeutics) miR-155 Cutaneous T cell lymphoma and mycosis fungoidesAntimiRLNA -modified antisense inhibitor Phase 1 NCT02580552 miRagen Therapeutics miR-92 Pheripheral artery disease Improves recovery of damaged tissue, enhance blood vessel growth Pre-clinical – Another challenge in using miRNA -based therapeutics is their targeted delivery. [score:12]
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Free testosterone levels were positively associated with whole blood miRNA-21, miRNA-103, and miRNA-155, which were up-regulated in European women with PCOS [11]. [score:4]
Serum free testosterone levels were positively associated with the expression of whole blood miRNA-21, miRNA-103, and miRNA-155 [11]. [score:3]
Effects of polycystic ovary syndrome (PCOS), sex hormones, and obesity on circulating miRNA-21, miRNA-27b, miRNA-103, and miRNA-155 expression. [score:3]
The expression of whole blood miRNA-21, miRNA-27b, miRNA-103, and miRNA-155 was significantly increased in obese women with PCOS compared with lean women with PCOS. [score:2]
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Aside from the miRNAs that directly bind to IRS-1, a class of miRNAs indirectly inhibits the expression of IRS-1. For example, in livers and adipose tissues of diet -induced obesity mice, overexpression of miR-103/107 negatively regulates insulin signaling by targeting Cav-1, a caveolae protein that activates insulin signaling by stabilizing the interaction between caveolae and IRS-1. Thus, enhanced miR-103/107 levels are concomitant with a decreased stability of IRS-1 [45]. [score:12]
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For instance, miR-103 and miR-107, having very similar mature sequence and expression levels (Figure 6c), are two known miRNAs that have the same roles in regulating insulin sensitivity and promoting metastasis of colorectal cancer [20], [21]; miR-34b and miR-34c, having very similar mature sequence and expression levels (Figure 6c), are targets of p53 and cooperate in control of cell proliferation and adhesion-independent growth [22]; let-7a/b/c were also claimed to reduces tumor growth in mouse mo dels of lung cancer [23] and miR-29a/b/c reverts aberrant methylation in lung cancer by targeting DNA methyltransferases 3A and 3B [24] while these two miRNA clusters have very similar mature sequences and expression levels (Figure 6d). [score:12]
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92) 43 hsa-mir-302a dbDEMC 19 hsa-let-7g dbDEMC, miR2Disease 44 hsa-mir-212 literature 20 hsa-let-7b dbDEMC, HMDD, miR2Disease 45 hsa-mir-372 dbDEMC 21 hsa-mir-150 dbDEMC, literature 46 hsa-mir-197 dbDEMC 22 hsa-mir-338 dbDEMC 47 hsa-mir-124 literature 23 hsa-mir-103 dbDEMC, miR2Disease 48 hsa-mir-378 HMDD 24 hsa-mir-15b dbDEMC, HMDD 49 hsa-mir-26b dbDEMC, miR2Disease 25 hsa-mir-31 dbDEMC, HMDD, miR2Disease 50 hsa-mir-542 higher RWRMDA (No. [score:11]
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Two members of the miR-103 gene family, miR-103 and miR-107, are both downregulated with age. [score:4]
In addition to the miR-155 oncomir, we found that several other cancer -associated miRNAs are downregulated with age including miR-103, miR-107, miR-128 and miR-221 (see Fig. 3C for list of cancers associated with each miRNA). [score:4]
miR-103 and miR-107 only differ by one nucleotide and are predicted to target the same genes. [score:3]
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Other miRNAs from this paper: hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7d, hsa-let-7e, hsa-let-7f-1, hsa-let-7f-2, hsa-mir-17, hsa-mir-23a, hsa-mir-24-1, hsa-mir-24-2, hsa-mir-26a-1, hsa-mir-27a, hsa-mir-29a, hsa-mir-29b-1, hsa-mir-29b-2, hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-199a-1, hsa-mir-208a, hsa-mir-148a, hsa-mir-10a, hsa-mir-181a-2, hsa-mir-181c, hsa-mir-199a-2, hsa-mir-181a-1, hsa-mir-214, hsa-mir-221, hsa-let-7g, hsa-let-7i, hsa-mir-1-2, hsa-mir-23b, hsa-mir-27b, hsa-mir-125b-1, hsa-mir-128-1, hsa-mir-133a-1, hsa-mir-133a-2, hsa-mir-143, hsa-mir-125b-2, hsa-mir-126, hsa-mir-127, hsa-mir-206, hsa-mir-1-1, hsa-mir-128-2, hsa-mir-29c, hsa-mir-26a-2, hsa-mir-378a, hsa-mir-148b, hsa-mir-133b, hsa-mir-424, ssc-mir-125b-2, ssc-mir-148a, ssc-mir-23a, ssc-mir-24-1, ssc-mir-26a, ssc-mir-29b-1, ssc-mir-181c, ssc-mir-214, ssc-mir-27a, ssc-let-7c, ssc-let-7f-1, ssc-let-7i, ssc-mir-103-1, ssc-mir-128-1, ssc-mir-29c, hsa-mir-486-1, hsa-mir-499a, hsa-mir-503, hsa-mir-411, hsa-mir-378d-2, hsa-mir-208b, hsa-mir-103b-2, ssc-mir-17, ssc-mir-221, ssc-mir-133a-1, ssc-mir-1, ssc-mir-503, ssc-mir-181a-1, ssc-mir-206, ssc-let-7a-1, ssc-let-7e, ssc-let-7g, ssc-mir-378-1, ssc-mir-133b, ssc-mir-29a, ssc-mir-199a-2, ssc-mir-128-2, ssc-mir-499, ssc-mir-143, ssc-mir-10a, ssc-mir-486-1, ssc-mir-103-2, ssc-mir-181a-2, ssc-mir-27b, ssc-mir-24-2, ssc-mir-23b, ssc-mir-148b, ssc-mir-208b, ssc-mir-424, ssc-mir-127, ssc-mir-125b-1, hsa-mir-378b, hsa-mir-378c, ssc-mir-411, ssc-mir-133a-2, ssc-mir-126, ssc-mir-199a-1, ssc-mir-378-2, hsa-mir-378d-1, hsa-mir-378e, hsa-mir-378f, hsa-mir-378g, hsa-mir-378h, hsa-mir-378i, hsa-mir-499b, ssc-let-7a-2, ssc-mir-486-2, hsa-mir-378j, ssc-let-7d, ssc-let-7f-2, ssc-mir-29b-2, hsa-mir-486-2, ssc-mir-378b
MiR-103/107 family was validated to attenuate miRNA biosynthesis by targeting Dicer [59], regulate insulin sensitivity through down -regulating caveolin-1 [60] and affect cellular migration by modulating CDK5R1 expression [61], allowing us to hypothesize that these miRNA -mediated mechanism may affect myogenesis when the microRNA family, especially ssc-miR-103, down-regulated during both myofiber formation (at 35 to 77 dpc) and maturation (at 77 dpc to 180 dpn) (Figure 5F). [score:10]
Consequently, 18 candidate miRNAs were selected, including ssc-miR-378, -127, -128, -411, 23b, -27b, -10a, -140*, -9-1/-2, -148a/b, -126, 542-3p, 30a-5p/d/e-5p and miR-103 (Figure 5). [score:1]
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In this sense, by virtue of miRNAs known mechanism of action, reducing gene expression by binding to the 3'UTR of their targeted genes, a number of evidenced miRNA species (Mir-27a, Mir-103, Mir-17-5p and Mir-130a) might be involved in turning off the 'neuron projection morphogenesis' process in the SHVT group. [score:5]
Other deregulated biological processes included ‘blood vessel development’ (Mir-155, Mir-17-5p and Mir-130a) (FDR = 6x10 [-4]), 'lung development' (Mir-17-5p and Mir-27a) (FDR = 4x10 [-4]), and ‘cell motion’ (Mir-103) (FDR = 8x10 [-4]) (S3 Table). [score:3]
A heatmap built from nominally significant miRNAs between SHVT and NA detected by sRNA-seq are shown in S3 Fig. When comparing the direct sequencing of the samples with the bioinformatic prediction, 28 miRNA species overlapped, from which Mir-27a, Mir-103, Mir-17-5p, Mir-130a, and Mir-155 were nominally significant although the abundance of the latter was observed to be opposite to the one deduced by GSEA (Table 2). [score:2]
Interestingly, this process was the only one involving all four miRNA species with a consistent abundance among microarray -based predictions and sRNA-seq experiments (Mir-27a, Mir-103, Mir-17-5p and Mir-130a) (FDR<1x10 [-4]) (S3 Table). [score:1]
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Other miRNAs from this paper: hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7d, hsa-let-7e, hsa-let-7f-1, hsa-let-7f-2, hsa-mir-17, hsa-mir-18a, hsa-mir-19a, hsa-mir-19b-1, hsa-mir-19b-2, hsa-mir-20a, hsa-mir-21, hsa-mir-24-1, hsa-mir-24-2, hsa-mir-27a, hsa-mir-29a, hsa-mir-30a, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-93, hsa-mir-100, hsa-mir-29b-1, hsa-mir-29b-2, hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-107, mmu-let-7g, mmu-let-7i, mmu-mir-1a-1, mmu-mir-23b, mmu-mir-27b, mmu-mir-29b-1, mmu-mir-30a, mmu-mir-30b, mmu-mir-125a, mmu-mir-9-2, mmu-mir-133a-1, mmu-mir-136, mmu-mir-138-2, mmu-mir-181a-2, mmu-mir-24-1, mmu-mir-191, hsa-mir-196a-1, hsa-mir-148a, hsa-mir-30c-2, hsa-mir-30d, mmu-mir-122, mmu-mir-143, mmu-mir-30e, hsa-mir-34a, hsa-mir-181a-2, hsa-mir-196a-2, hsa-mir-181a-1, mmu-mir-296, mmu-mir-298, mmu-mir-34c, mmu-let-7d, mmu-mir-130b, hsa-let-7g, hsa-let-7i, hsa-mir-1-2, hsa-mir-23b, hsa-mir-27b, hsa-mir-30b, hsa-mir-122, hsa-mir-133a-1, hsa-mir-133a-2, hsa-mir-138-2, hsa-mir-143, hsa-mir-191, hsa-mir-9-1, hsa-mir-9-2, hsa-mir-9-3, hsa-mir-125a, hsa-mir-136, hsa-mir-138-1, mmu-mir-19b-2, mmu-mir-30c-1, mmu-mir-30c-2, mmu-mir-30d, mmu-mir-148a, mmu-mir-196a-1, mmu-mir-196a-2, mmu-let-7a-1, mmu-let-7a-2, mmu-let-7b, mmu-let-7c-1, mmu-let-7c-2, mmu-let-7e, mmu-let-7f-1, mmu-let-7f-2, mmu-mir-18a, mmu-mir-20a, mmu-mir-21a, mmu-mir-24-2, mmu-mir-29a, mmu-mir-29c, mmu-mir-27a, mmu-mir-92a-2, mmu-mir-93, mmu-mir-34a, mmu-mir-103-1, mmu-mir-103-2, mmu-mir-330, mmu-mir-346, hsa-mir-1-1, mmu-mir-1a-2, mmu-mir-107, mmu-mir-17, mmu-mir-19a, mmu-mir-100, mmu-mir-181a-1, mmu-mir-29b-2, mmu-mir-19b-1, mmu-mir-92a-1, mmu-mir-9-1, mmu-mir-9-3, mmu-mir-138-1, hsa-mir-29c, hsa-mir-30c-1, hsa-mir-34c, hsa-mir-296, hsa-mir-130b, hsa-mir-30e, hsa-mir-375, hsa-mir-381, mmu-mir-375, mmu-mir-381, hsa-mir-330, mmu-mir-133a-2, hsa-mir-346, hsa-mir-196b, mmu-mir-196b, hsa-mir-18b, hsa-mir-20b, hsa-mir-146b, hsa-mir-519d, hsa-mir-501, hsa-mir-503, mmu-mir-20b, mmu-mir-503, hsa-mir-92b, mmu-mir-146b, mmu-mir-669c, mmu-mir-501, mmu-mir-718, mmu-mir-18b, mmu-mir-92b, hsa-mir-298, mmu-mir-1b, hsa-mir-103b-2, hsa-mir-718, mmu-mir-21b, mmu-let-7j, mmu-mir-21c, mmu-mir-30f, mmu-let-7k, mmu-mir-9b-2, mmu-mir-9b-1, mmu-mir-9b-3
miR-143 and also miR-103 can induce adipogenesis in 3T3-L1 adipocytes and augment or accelerate expression of several key adipogenesis-regulated genes, such as FABP4 and adiponectin [27]. [score:4]
However, Xie et al. additionally found miR-107 and miR-103 to be upregulated, similarly to Ortega's findings in human adipocytes, but contrary to our results. [score:4]
As the regulation of mir-107 and mir-103 exists in man and mouse, differences in the differentiation protocols applied could explain the discrepancy. [score:2]
However, our results are not in accordance with Esau regarding miR-20, miR-93, miR-103 and miR-107. [score:1]
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Two miRNAs significantly upregulated in infected horses, as identified by DESeq2 (miR-16 and miR-32), were also upregulated when expression levels were measured by qRT-PCR and normalized against relative levels of miR-103 (Fig.   6). [score:7]
MiR-103 was selected as an initial housekeeping miRNA based on previous studies [24] and our own observation that miR-103 expression levels were not significantly different between infected and uninfected horses (data not shown). [score:3]
Data is normalized against relative levels of miR-103. [score:1]
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The dysregulation of miRNAs in CRC has been reported using miRNA expression profiling studies with different miRNAs identified either as enhancers (miR-21, miR-31, miR-103, miR-107) or suppressors (miR-135, miR-145, miR-200c) in the initiation and evolution of tumor metastasis [8- 13]. [score:6]
Chen HY, Lin YM, Chung HC, Lang YD, Lin CJ, Huang J, Wang WC, Lin FM, Chen Z, Huang HD, Shyy JY, Liang JT, Chen RH: miR-103/107 promote metastasis of colorectal cancer by targeting the metastasis suppressors DAPK and KLF4. [score:5]
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We also found that overexpression of miR-145 and miR-103 did not inhibit SIRT1 translation in differentiated 3T3-L1 cells, although luciferase activity was significantly repressed (Supplementary Figure 1). [score:7]
Among the miRNAs identified, overexpression of miR-377, miR-145a and miR-103 significantly repressed the activity of luciferase by 50%, with miR-377 showing the most significant effect (Figure 1A). [score:3]
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Other miRNAs from this paper: hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-mir-15a, hsa-mir-18a, hsa-mir-33a, hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-107, mmu-mir-27b, mmu-mir-126a, mmu-mir-128-1, mmu-mir-140, mmu-mir-146a, mmu-mir-152, mmu-mir-155, mmu-mir-191, hsa-mir-10a, hsa-mir-211, hsa-mir-218-1, hsa-mir-218-2, mmu-mir-297a-1, mmu-mir-297a-2, hsa-mir-27b, hsa-mir-128-1, hsa-mir-140, hsa-mir-152, hsa-mir-191, hsa-mir-126, hsa-mir-146a, mmu-let-7a-1, mmu-let-7a-2, mmu-mir-15a, mmu-mir-18a, mmu-mir-103-1, mmu-mir-103-2, mmu-mir-342, hsa-mir-155, mmu-mir-107, mmu-mir-10a, mmu-mir-218-1, mmu-mir-218-2, mmu-mir-33, mmu-mir-211, hsa-mir-374a, hsa-mir-342, gga-mir-33-1, gga-let-7a-3, gga-mir-155, gga-mir-18a, gga-mir-15a, gga-mir-218-1, gga-mir-103-2, gga-mir-107, gga-mir-128-1, gga-mir-140, gga-let-7a-1, gga-mir-146a, gga-mir-103-1, gga-mir-218-2, gga-mir-126, gga-let-7a-2, gga-mir-27b, mmu-mir-466a, mmu-mir-467a-1, hsa-mir-499a, hsa-mir-545, hsa-mir-593, hsa-mir-600, hsa-mir-33b, gga-mir-499, gga-mir-211, gga-mir-466, mmu-mir-675, mmu-mir-677, mmu-mir-467b, mmu-mir-297b, mmu-mir-499, mmu-mir-717, hsa-mir-675, mmu-mir-297a-3, mmu-mir-297a-4, mmu-mir-297c, mmu-mir-466b-1, mmu-mir-466b-2, mmu-mir-466b-3, mmu-mir-466c-1, mmu-mir-466e, mmu-mir-466f-1, mmu-mir-466f-2, mmu-mir-466f-3, mmu-mir-466g, mmu-mir-466h, mmu-mir-467c, mmu-mir-467d, mmu-mir-466d, hsa-mir-297, mmu-mir-467e, mmu-mir-466l, mmu-mir-466i, mmu-mir-466f-4, mmu-mir-466k, mmu-mir-467f, mmu-mir-466j, mmu-mir-467g, mmu-mir-467h, hsa-mir-664a, hsa-mir-1306, hsa-mir-1307, gga-mir-1306, hsa-mir-103b-2, gga-mir-10a, mmu-mir-1306, mmu-mir-3064, mmu-mir-466m, mmu-mir-466o, mmu-mir-467a-2, mmu-mir-467a-3, mmu-mir-466c-2, mmu-mir-467a-4, mmu-mir-466b-4, mmu-mir-467a-5, mmu-mir-466b-5, mmu-mir-467a-6, mmu-mir-466b-6, mmu-mir-467a-7, mmu-mir-466b-7, mmu-mir-467a-8, mmu-mir-467a-9, mmu-mir-467a-10, mmu-mir-466p, mmu-mir-466n, mmu-mir-466b-8, hsa-mir-466, hsa-mir-3173, hsa-mir-3618, hsa-mir-3064, hsa-mir-499b, mmu-mir-466q, hsa-mir-664b, gga-mir-3064, mmu-mir-126b, gga-mir-33-2, mmu-mir-3618, mmu-mir-466c-3, gga-mir-191
Out of the 26 miRNA/host gene pairs with coordinated expression, 11 have been found to be coordinately expressed in both, human and mouse [19], [27], [59], [61]– [64], [67]– [69], [71], [73]– [79]: mir-103/ PANK3, mir-107/ PANK1, mir-126/ EGFL7, mir-128-1/ R3HDM1, mir-140/ WWP2, mir-211/ TRPM1, mir-218-1/ SLIT2, mir-218-2/ SLIT3, mir-27b/ C9orf3, mir-33/ SREBF2, and mir-499/ MYH7B. [score:5]
We also found opposing results regarding the expression of two miRNA/host gene pairs, murine mmu-mir-103/Pank3 and mmu-mir-107/Pank1– these have previously been demonstrated to have coordinate [71] as well as anti-correlative (or discordant) expression patterns [72]. [score:5]
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It has been shown that cytosolic tRNase Z [L] modulates the PPM1F gene expression by cleaving its mRNA under the direction of 5′-half-tRNA [Glu] [3] and that miR-103 can downregulate gene expression through directing mRNA cleavage by cytosolic tRNase Z [L] [4]. [score:10]
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Other miRNAs from this paper: hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7d, hsa-let-7e, hsa-let-7f-1, hsa-let-7f-2, hsa-mir-15a, hsa-mir-16-1, hsa-mir-17, hsa-mir-20a, hsa-mir-21, hsa-mir-25, hsa-mir-26a-1, hsa-mir-26b, hsa-mir-27a, hsa-mir-29a, hsa-mir-30a, hsa-mir-33a, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-99a, hsa-mir-101-1, hsa-mir-29b-1, hsa-mir-29b-2, hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-106a, hsa-mir-16-2, hsa-mir-148a, hsa-mir-30c-2, hsa-mir-30d, hsa-mir-10a, hsa-mir-34a, hsa-mir-181a-2, hsa-mir-181b-1, hsa-mir-181c, hsa-mir-182, hsa-mir-204, hsa-mir-205, hsa-mir-181a-1, hsa-mir-216a, hsa-mir-217, hsa-mir-223, hsa-mir-200b, hsa-let-7g, hsa-let-7i, hsa-mir-1-2, hsa-mir-15b, hsa-mir-23b, hsa-mir-27b, hsa-mir-30b, hsa-mir-122, hsa-mir-125b-1, hsa-mir-130a, hsa-mir-133a-1, hsa-mir-133a-2, hsa-mir-142, hsa-mir-191, hsa-mir-9-1, hsa-mir-9-2, hsa-mir-9-3, hsa-mir-125a, hsa-mir-125b-2, hsa-mir-126, hsa-mir-146a, hsa-mir-149, hsa-mir-150, hsa-mir-200c, hsa-mir-1-1, hsa-mir-155, hsa-mir-181b-2, hsa-mir-106b, hsa-mir-29c, hsa-mir-200a, hsa-mir-101-2, hsa-mir-26a-2, hsa-mir-365a, hsa-mir-365b, hsa-mir-370, hsa-mir-375, hsa-mir-378a, hsa-mir-148b, hsa-mir-335, hsa-mir-133b, hsa-mir-451a, hsa-mir-146b, hsa-mir-494, hsa-mir-193b, hsa-mir-181d, hsa-mir-92b, hsa-mir-574, hsa-mir-605, hsa-mir-33b, hsa-mir-378d-2, hsa-mir-216b, hsa-mir-103b-2, hsa-mir-378b, hsa-mir-378c, hsa-mir-378d-1, hsa-mir-378e, hsa-mir-378f, hsa-mir-378g, hsa-mir-378h, hsa-mir-378i, hsa-mir-451b, hsa-mir-378j
Interestingly, downregulation of miR-103 was not shown to affect fat accumulation in caprine milk lactocytes, suggesting that there may be alternative and/or compensatory mechanisms controlling mammary fat metabolism [165]. [score:4]
Overexpression of miR-103 has been identified as a crucial regulator of milk fat synthesis and composition as well as milk nutrient levels [165]. [score:4]
Furthermore, HM miR-103 [30, 44] is known to regulate milk fat synthesis, promoting fat globule synthesis and accumulation of triglyceride and unsaturated fatty acids [165]. [score:2]
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Subsequently, we compared the expression levels of 410 co-expressed miRNAs between XY and YY testis (Table S5), and found a similar expression level for 93% co-expressed miRNAs, such as 5 dominantly expressed miRNAs, miR-26a, miR-7g, miR-200a, miR-200b and miR-103. [score:10]
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50
[+] score: 10
However, in the group of inconsistently reported miRNAs, miR-107 was reported in nine studies with upregulation in eight studies and downregulation in one study followed by miR-103 in eight studies with seven and one study showing up- and downregulation, respectively. [score:10]
[1 to 20 of 1 sentences]
51
[+] score: 10
Of these, 14 (miR-23b, miR-28, miR-98, miR-103, miR-107, miR-193a,0, miR-324-5p, miR-324-3p, miR-331, miR-374, miR-432, miR-502, and miR-660) were upregulated and 6 (miR-31, miR-451, miR-452, miR-565, miR-594 and miR-659) were downregulated. [score:7]
[26]↑ C2C12 diff [33]↑ muscle development [31] 16miR-30d↑↑(this study)↑ pMyo diff [33]  17miR-30e-3p↑(this study)↑ pMyo diff [33]  18 miR-31 (n)↓(this study)   19 miR-98 (n)↑(this study)   20miR-99a↓(this study)↑ C2C12 diff [33] ↑ pMyo diff [33]  21 miR-101↑↑(this study)-↑ muscle development [31] 22 miR-103 (n)↑(this study)   23 miR-107 (n)↑(this study)-  24miR-126↑↑(this study)↓ C2C12 diff [33]  25↑↑↑↑ pMyo diff. [score:3]
[1 to 20 of 2 sentences]
52
[+] score: 10
The analysis of adipose tissue-derived exosomal miRNA content pre- and post-gastric bypass showed upregulation of miR-103-3p which is known to target the insulin receptor signaling pathway and was previously found to be downregulated in diabetes (229– 231). [score:9]
Among the adipogenic miRNA found in adipose tissue-derived exosomes are miR-103, miR-146-b, and miR-148-a (225– 227). [score:1]
[1 to 20 of 2 sentences]
53
[+] score: 10
Additionally, 3 miRNAs (miR-103, miR-191 and miR-423-5p) with stable expression in human testis tissue were included to serve as reference miRNAs in the expression analysis. [score:5]
We found that miR-204, miR-99b-3p, miR-191, miR-509-3-5p, miR-99b, miR-10b, miR-126, miR-126-5p, miR-103 are downregulated in samples from men with SCO pathology pattern. [score:4]
No hsa-miR-10b-3p ACAGAUUCGAUUCUAGGGGAAU 204514 hsa-miR-10b UACCCUGUAGAACCGAAUUUGUG 204753 hsa-miR-34c-3p AAUCACUAACCACACGGCCAGG 204373 hsa-miR-34c-5p AGGCAGUGUAGUUAGCUGAUUGC 204407 hsa-miR-99b-3p CAAGCUCGUGUCUGUGGGUCCG 204064 hsa-miR-99b CACCCGUAGAACCGACCUUGCG 204367 hsa-miR-125a-3p ACAGGUGAGGUUCUUGGGAGCC 204446 hsa-miR-125a-5p UCCCUGAGACCCUUUAACCUGUGA 204339 hsa-miR-126-5p CAUUAUUACUUUUGGUACGCG 204584 hsa-miR-126 UCGUACCGUGAGUAAUAAUGCG 204227 hsa-miR-202-5p UUCCUAUGCAUAUACUUCUUUG 204730 hsa-miR-202 AGAGGUAUAGGGCAUGGGAA 204101 hsa-miR-204 UUCCCUUUGUCAUCCUAUGCCU 204507 hsa-miR-506 UAAGGCACCCUUCUGAGUAGA 204539 hsa-miR-508-3p UGAUUGUAGCCUUUUGGAGUAGA 204480 hsa-miR-508-5p UACUCCAGAGGGCGUCACUCAUG 204077 hsa-miR-509-3p UGAUUGGUACGUCUGUGGGUAG 204458 hsa-miR-509-3-5p UACUGCAGACGUGGCAAUCAUG 204503 hsa-miR-514 AUUGACACUUCUGUGAGUAGA 204645 hsa-miR-103 AGCAGCAUUGUACAGGGCUAUGA 204063 hsa-miR-191 CAACGGAAUCCCAAAAGCAGCUG 204306 hsa-miR-423-5p UGAGGGGCAGAGAGCGAGACUUU 204593 First strand of cDNA was synthesized using a Universal cDNA Synthesis Kit II (Exiqon, Cat. [score:1]
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54
[+] score: 9
Other miRNAs from this paper: hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-103b-2
We have shown that a subset of miRNAs can guide target RNA cleavage by tRNase Z [L] in vitro, and that human miR-103 can downregulate the luciferase gene expression through directing its mRNA cleavage by tRNase Z [L] [[8, unpublished data]]. [score:9]
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55
[+] score: 9
Activated B cells and CLL cells exhibit similar miR expression profiles that include the upregulation of miR-34a, miR-155, and miR-342-3p and the downregulation of miR-103, miR-181a, and miR-181b [10]. [score:9]
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56
[+] score: 9
Other miRNAs from this paper: hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-122, hsa-mir-103b-2
Joven J. Espinel E. Rull A. Aragones G. Rodriguez-Gallego E. Camps J. Micol V. Herranz-Lopez M. Menendez J. A. Borras I. Plant-derived polyphenols regulate expression of mirna paralogs mir-103/107 and mir-122 and prevent diet -induced fatty liver disease in hyperlipidemic miceBiochim. [score:6]
The chronic oral administration of HS polyphenols in mice under a fat-enriched diet reverted the changes observed in non-specific microRNAs miR103/107 concomitantly with the prevention of diet -induced fatty liver disease and changes in lipid and glucose metabolism (Figure 5). [score:3]
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57
[+] score: 9
A regulatory feedback loop exists through which Dicer expression is regulated by mature miRNAs such as miR-103/107 and let-7 family members [18], [62]. [score:5]
Dicer mRNA was lower in cell lines that underwent epithelial to mesenchymal transition (EMT) [15], [69] and down-regulation of Dicer protein by miR-103/107 was shown to be associated with EMT and metastasis [18]. [score:4]
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58
[+] score: 9
Other miRNAs from this paper: hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7d, hsa-let-7e, hsa-let-7f-1, hsa-let-7f-2, hsa-mir-19a, hsa-mir-20a, hsa-mir-23a, hsa-mir-24-1, hsa-mir-24-2, hsa-mir-25, hsa-mir-26a-1, hsa-mir-30a, hsa-mir-33a, hsa-mir-96, hsa-mir-98, hsa-mir-103a-2, hsa-mir-103a-1, mmu-let-7g, mmu-let-7i, mmu-mir-23b, mmu-mir-30a, mmu-mir-30b, mmu-mir-99b, mmu-mir-125a, mmu-mir-125b-2, mmu-mir-9-2, mmu-mir-133a-1, mmu-mir-146a, mmu-mir-155, mmu-mir-182, mmu-mir-183, mmu-mir-24-1, mmu-mir-191, mmu-mir-199a-1, hsa-mir-199a-1, mmu-mir-200b, hsa-mir-30c-2, hsa-mir-30d, mmu-mir-30e, hsa-mir-181b-1, hsa-mir-182, hsa-mir-183, hsa-mir-199a-2, hsa-mir-199b, hsa-mir-221, hsa-mir-223, hsa-mir-200b, mmu-mir-299a, mmu-let-7d, hsa-let-7g, hsa-let-7i, hsa-mir-23b, hsa-mir-30b, hsa-mir-125b-1, hsa-mir-133a-1, hsa-mir-133a-2, hsa-mir-191, hsa-mir-9-1, hsa-mir-9-2, hsa-mir-9-3, hsa-mir-125a, hsa-mir-125b-2, hsa-mir-146a, mmu-mir-30c-1, mmu-mir-30c-2, mmu-mir-30d, mmu-let-7a-1, mmu-let-7a-2, mmu-let-7b, mmu-let-7c-1, mmu-let-7c-2, mmu-let-7e, mmu-let-7f-1, mmu-let-7f-2, mmu-mir-20a, mmu-mir-21a, mmu-mir-23a, mmu-mir-24-2, mmu-mir-26a-1, mmu-mir-96, mmu-mir-98, mmu-mir-103-1, mmu-mir-103-2, mmu-mir-148b, mmu-mir-351, hsa-mir-200c, hsa-mir-155, hsa-mir-181b-2, mmu-mir-19a, mmu-mir-25, mmu-mir-200c, mmu-mir-223, mmu-mir-26a-2, mmu-mir-221, mmu-mir-199a-2, mmu-mir-199b, mmu-mir-9-1, mmu-mir-9-3, mmu-mir-181b-1, mmu-mir-125b-1, hsa-mir-30c-1, hsa-mir-299, hsa-mir-99b, hsa-mir-30e, hsa-mir-26a-2, hsa-mir-361, mmu-mir-361, hsa-mir-365a, mmu-mir-365-1, hsa-mir-365b, hsa-mir-375, mmu-mir-375, hsa-mir-148b, mmu-mir-133a-2, mmu-mir-133b, hsa-mir-133b, mmu-mir-181b-2, mmu-mir-433, hsa-mir-429, mmu-mir-429, mmu-mir-365-2, hsa-mir-433, hsa-mir-490, hsa-mir-193b, hsa-mir-92b, mmu-mir-490, mmu-mir-193b, mmu-mir-92b, hsa-mir-103b-2, mmu-mir-299b, mmu-mir-133c, mmu-let-7j, mmu-mir-30f, mmu-let-7k, mmu-mir-9b-2, mmu-mir-9b-1, mmu-mir-9b-3
In addition to the targeting sites for miR-155, miR-181b, and miR-361, the 3′ UTR of mouse Aicda mRNA also contains the putative target sites for miR-125a, miR-351, miR-92b, miR-26a, and miR-103 (identified by using miRNA -targeting prediction tools: TargetScan. [score:9]
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59
[+] score: 9
Other miRNAs from this paper: hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7d, hsa-let-7e, hsa-let-7f-1, hsa-let-7f-2, hsa-mir-15a, hsa-mir-17, hsa-mir-21, hsa-mir-24-1, hsa-mir-24-2, hsa-mir-27a, hsa-mir-30a, hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-107, mmu-let-7g, mmu-let-7i, mmu-mir-27b, mmu-mir-30a, mmu-mir-30b, mmu-mir-125b-2, mmu-mir-9-2, mmu-mir-150, mmu-mir-24-1, mmu-mir-204, hsa-mir-30c-2, hsa-mir-30d, mmu-mir-30e, hsa-mir-204, hsa-mir-210, hsa-mir-221, hsa-mir-222, mmu-let-7d, hsa-let-7g, hsa-let-7i, hsa-mir-27b, hsa-mir-30b, hsa-mir-125b-1, hsa-mir-9-1, hsa-mir-9-2, hsa-mir-9-3, hsa-mir-125b-2, hsa-mir-150, mmu-mir-30c-1, mmu-mir-30c-2, mmu-mir-30d, mmu-let-7a-1, mmu-let-7a-2, mmu-let-7b, mmu-let-7c-1, mmu-let-7c-2, mmu-let-7e, mmu-let-7f-1, mmu-let-7f-2, mmu-mir-15a, mmu-mir-21a, mmu-mir-24-2, mmu-mir-27a, mmu-mir-103-1, mmu-mir-103-2, mmu-mir-326, mmu-mir-107, mmu-mir-17, mmu-mir-210, mmu-mir-221, mmu-mir-222, mmu-mir-9-1, mmu-mir-9-3, mmu-mir-125b-1, hsa-mir-30c-1, hsa-mir-30e, hsa-mir-378a, mmu-mir-378a, hsa-mir-326, ssc-mir-125b-2, ssc-mir-24-1, ssc-mir-326, ssc-mir-27a, ssc-let-7c, ssc-let-7f-1, ssc-let-7i, ssc-mir-103-1, ssc-mir-107, ssc-mir-204, ssc-mir-21, ssc-mir-30c-2, ssc-mir-9-1, ssc-mir-9-2, hsa-mir-378d-2, hsa-mir-103b-2, ssc-mir-15a, ssc-mir-17, ssc-mir-30b, ssc-mir-210, ssc-mir-221, ssc-mir-30a, ssc-let-7a-1, ssc-let-7e, ssc-let-7g, ssc-mir-378-1, ssc-mir-30d, ssc-mir-30e, ssc-mir-103-2, ssc-mir-27b, ssc-mir-24-2, ssc-mir-222, ssc-mir-125b-1, hsa-mir-378b, hsa-mir-378c, ssc-mir-30c-1, ssc-mir-378-2, hsa-mir-378d-1, hsa-mir-378e, hsa-mir-378f, hsa-mir-378g, hsa-mir-378h, hsa-mir-378i, mmu-mir-378b, ssc-let-7a-2, hsa-mir-378j, mmu-mir-21b, mmu-let-7j, mmu-mir-378c, mmu-mir-21c, mmu-mir-378d, mmu-mir-30f, ssc-let-7d, ssc-let-7f-2, ssc-mir-9-3, ssc-mir-150-1, ssc-mir-150-2, mmu-let-7k, ssc-mir-378b, mmu-mir-9b-2, mmu-mir-9b-1, mmu-mir-9b-3
Cai et al. (2014) found that 18 miRNAs were differentially expressed between intact and castrated male pigs, including miR-15a, miR-21, miR-27, miR-30, and so on [23]; Bai et al. (2014) reported that 177 miRNAs had more than 2-fold differential expression between castrated and intact male pigs, including miR-21, miR-30, miR-27, miR-103, and so on [22]. [score:5]
We found 13 adipogenesis-promoting miRNAs (let-7、miR-9、miR-15a、miR-17、miR-21、miR-24、miR-30、miR-103、miR-107、miR-125b、miR-204、miR-210、and miR-378) target 860 lncRNA loci. [score:3]
We analyzed the relationship between the 343 identified lncRNAs with the 13 promoting adipogenesis miRNAs (let-7、miR-9、miR-15a、miR-17、miR-21、miR-24、miR-30、miR-103、miR-107、miR-125b、miR-204、miR-210、and miR-378) and five depressing adipogenesis miRNAs (miR-27, miR-150, miR-221, miR-222, and miR-326). [score:1]
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60
[+] score: 8
A recent study has reported that miR-103 also expressed in testis of piglets but not in adult pig testis, which indicates that miR-103 expression pattern depends on the developmental stages of pigs and may have important biological roles in testis [8]. [score:6]
Previous studies demonstrated that miR-103 was involved in various biological processis such as brain development, adipocyte differentiation, lipid metabolism, hematopoiesis, and immunity [55]– [58]. [score:2]
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61
[+] score: 8
Deng and coworkers identified miR-103/107 as directly targeting HIF-1β subunits in rat PASMCs [119]. [score:4]
They showed that hypoxia reduces miR-103/107 levels in PASMCs and leads to upregulation of HIF-1β, but not HIF-1α [119]. [score:4]
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62
[+] score: 8
For example, isomiRs of hsa-miR-143 in severe sample showed different expression pattern with normal and mild samples, while isomiRs of hsa-miR-103 and hsa-miR-424 in normal sample showed inconsistent expression patterns with diseased samples (Figure 5). [score:7]
There were 3 common isomiRs between normal and mild samples, while only hsa-miR-103-U was shared by normal and severe samples (Figure 3C). [score:1]
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63
[+] score: 8
Other miRNAs from this paper: hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-103b-2
Moreover, salidroside, a glycoside from Rhodiola rosea, has been shown to reduce H [2]O [2] -induced ROS generation via the upregulation of miR-103 [15]. [score:4]
Xu M. C. Gao X. F. Ruan C. Ge Z. R. Lu J. D. Zhang J. J. Zhang Y. Wang L. Shi H. M. miR-103 Regulates Oxidative Stress by Targeting the BCL2/Adenovirus E1B 19 kDa Interacting Protein 3 in HUVECs Oxidative Med. [score:4]
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64
[+] score: 8
Other miRNAs from this paper: hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-mir-18a, hsa-mir-21, hsa-mir-23a, hsa-mir-26a-1, hsa-mir-30a, hsa-mir-99a, hsa-mir-103a-2, hsa-mir-103a-1, mmu-mir-1a-1, mmu-mir-23b, mmu-mir-30a, mmu-mir-99a, mmu-mir-126a, mmu-mir-9-2, mmu-mir-133a-1, mmu-mir-138-2, hsa-mir-192, mmu-mir-204, mmu-mir-122, hsa-mir-204, hsa-mir-1-2, hsa-mir-23b, hsa-mir-122, hsa-mir-133a-1, hsa-mir-133a-2, hsa-mir-138-2, hsa-mir-9-1, hsa-mir-9-2, hsa-mir-9-3, hsa-mir-126, hsa-mir-138-1, mmu-mir-192, mmu-let-7a-1, mmu-let-7a-2, mmu-mir-18a, mmu-mir-21a, mmu-mir-23a, mmu-mir-26a-1, mmu-mir-103-1, mmu-mir-103-2, hsa-mir-1-1, mmu-mir-1a-2, mmu-mir-26a-2, mmu-mir-9-1, mmu-mir-9-3, mmu-mir-138-1, hsa-mir-26a-2, hsa-mir-376c, hsa-mir-381, mmu-mir-381, mmu-mir-133a-2, rno-let-7a-1, rno-let-7a-2, rno-mir-9a-1, rno-mir-9a-3, rno-mir-9a-2, rno-mir-18a, rno-mir-21, rno-mir-23a, rno-mir-23b, rno-mir-26a, rno-mir-30a, rno-mir-99a, rno-mir-103-2, rno-mir-103-1, rno-mir-122, rno-mir-126a, rno-mir-133a, rno-mir-138-2, rno-mir-138-1, rno-mir-192, rno-mir-204, mmu-mir-411, hsa-mir-451a, mmu-mir-451a, rno-mir-451, hsa-mir-193b, rno-mir-1, mmu-mir-376c, rno-mir-376c, rno-mir-381, hsa-mir-574, hsa-mir-652, hsa-mir-411, bta-mir-26a-2, bta-mir-103-1, bta-mir-16b, bta-mir-18a, bta-mir-21, bta-mir-99a, bta-mir-126, mmu-mir-652, bta-mir-138-2, bta-mir-192, bta-mir-23a, bta-mir-30a, bta-let-7a-1, bta-mir-122, bta-mir-23b, bta-let-7a-2, bta-let-7a-3, bta-mir-103-2, bta-mir-204, mmu-mir-193b, mmu-mir-574, rno-mir-411, rno-mir-652, mmu-mir-1b, hsa-mir-103b-2, bta-mir-1-2, bta-mir-1-1, bta-mir-133a-2, bta-mir-133a-1, bta-mir-138-1, bta-mir-193b, bta-mir-26a-1, bta-mir-381, bta-mir-411a, bta-mir-451, bta-mir-9-1, bta-mir-9-2, bta-mir-376c, bta-mir-1388, rno-mir-9b-3, rno-mir-9b-1, rno-mir-126b, rno-mir-9b-2, hsa-mir-451b, bta-mir-574, bta-mir-652, mmu-mir-21b, mmu-mir-21c, mmu-mir-451b, bta-mir-411b, bta-mir-411c, mmu-mir-126b, rno-mir-193b, mmu-mir-9b-2, mmu-mir-9b-1, mmu-mir-9b-3
The qRT-PCR data showed similar expression trend of detected expression of these miRNAs from the library except miR-103. [score:5]
To validate above miRNA expression patterns, quantitative RT-PCR was performed on tissue-specific miRNAs (miR-122, -133a), high cloning frequency miRNAs (miR-26a, -99a and -150) and low cloning frequency miRNAs (miR-103, -107, -411, -423-5p, -574-3p and -652). [score:3]
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65
[+] score: 8
miR-103, miR-106b, and miR-424 were significantly up-regulated in GPI [high]-patients and IFM high-risk (Supplementary Table S6A). [score:4]
However, 6 of 8 miRNAs which are significantly higher expressed in GPI [high]-patients, and five of ten miRNAs being positively correlated with the GPI are overlapping, but for miR-103 all being part of the miR-17–92 cluster. [score:3]
Seventeen correlations were negative, twelve positive, and five miRNAs (miR-19b, miR-103, miR-106b, miR-424, and miR-623) were correlated with more than one mRNA. [score:1]
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66
[+] score: 8
In the same context, miR-103 was found to be downregulated in tumor samples from spleen and liver of infected chickens, where it targets cyclin E1 and the transcription factor Dp-2, which normally causes suppression of cell migration and tumor formation (138). [score:8]
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67
[+] score: 8
Using published mouse miRNA expression data [55], we found that our strongest candidates, mir-107 and mir-103, are indeed strongly expressed in brain, heart, and muscle. [score:5]
In this mo del, CTG repeat -binding miRNAs, such as mir-107 and mir-103, preferentially bind to the mutated DMPK transcript. [score:1]
Together, these results support a role for miRNAs in DM1 pathogenesis, and, in particular, highlight mir-107 and mir-103 as attractive candidates for binding to DMPK. [score:1]
All seven miRNAs were associated with DMPK repression using the RE metric (P = 0.02 by binomial test), with mir-107 and mir-103 repressing DMPK among the most at about 15% (Figure 4d). [score:1]
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[+] score: 8
We observed that miR-143 was, in fact, down-regulated during human adipocyte maturation while miR-103 did not change significantly. [score:4]
However, these authors found that miR-143 and miR-103 were significantly up-regulated in differentiated human fat cells. [score:4]
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69
[+] score: 7
The amplification plot and melting curve was generated during analysis og the expression of miR-654-5p and the two endogenous controls (miR-103 and U6) in granulosa cells co-cultured with exosomes derived from follicular fluid containing growing (BCB-) oocytes. [score:3]
0078505.g003 Figure 3 The amplification plot and melting curve was generated during analysis og the expression of miR-654-5p and the two endogenous controls (miR-103 and U6) in granulosa cells co-cultured with exosomes derived from follicular fluid containing growing (BCB-) oocytes. [score:3]
Representative amplification plot (A) and melting curve (B) of miR-654-5p, miR-103 and U6. [score:1]
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70
[+] score: 7
The down-regulated miRNAs were highly enriched for LCL specific miRNAs (miR-155, let-7a-i, miR-21, miR-142, miR103, miR-320, miR-146a-b) and the up-regulated miRNAs were highly enriched for iPSC specific miRNAs (miR-302a, miR-302c, miR-371a, miR-302b, miR-302d, miR-372, miR-373miR-92a-1, miR-92a-2, miR-92b, miR-17, miR-20a, miR-18a). [score:7]
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71
[+] score: 7
Specifically, five miRNAs (miR-26b, miR-26a, miR-212, miR-107, and miR-103) were upregulated and twelve miRNAs (miR-125b, miR-141, miR-144, miR-164, miR-145, miR-143, miR-15b, miR-16, miR-186, let-7b, let-7a3, and miR-128) were downregulated. [score:7]
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72
[+] score: 7
Consistent with those data, in our study, curcumin upregulated miR-103, miR-22, and miR-23b and downregulated miR-195, miR-15b, miR-196, and miR-92. [score:7]
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73
[+] score: 7
These miRNAs have been shown to be over-expressed in several types of cancers including lung cancers [17, 50, 51], and high expression of miR-103 and miR-107 were correlated with poor survival in cancer patients (esophageal squamous and pancreatic tumors) [51, 52]. [score:5]
For example, we found significant overexpression of miR-103, miR-107, miR-301 and miR-338 in lung cancer cells as compared to HBECs. [score:2]
[1 to 20 of 2 sentences]
74
[+] score: 7
Average expression values of MO, OC 48 h and OC were normalized with respect to the reference gene miR-103. [score:3]
Data normalized with respect to miR-103. [score:1]
Data are as follows: RAW crossing point (Cp) values as produced by the qPCR system (columns B, D, F, N, P, R, Z, AB, AD), RAW concentration (Conc) as produced by the qRT-PCR system (columns C, E, G, O, Q, S, AA, AC, AE), concentration values relative to miR103 (housekeeping) levels (columns H, I, J, T, U, V, AF, AG, AH). [score:1]
Data relative to miR-103 levels. [score:1]
qRT-PCR data were normalized with respect to miR-103. [score:1]
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75
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Expression was normalized to miR-16 and miR-103. [score:3]
An RNA pool from 20 different tissues was used as a positive control and the results were normalized to the expression of miR-16 and miR-103. [score:3]
26.19 (9/9) 25.72 (9/9) 25.92 (9/9) 31.83 (3/3) miR-103 contr. [score:1]
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76
[+] score: 7
Ectopic expression of miR-103 in preadipocytes accelerated adipogenesis as measured by both the up-regulation of many adipogenesis markers and by an increase in triglyceride accumulation at an early stage of adipogenesis [105]. [score:4]
However, the most striking difference between milk and muscle or plant proteins is the high amount of specific exosomal miRs, like miR-21 and miR-103 [50, 51], that may play an important role as an additional layer of metabolic regulation. [score:2]
miR-103 is a component of cow´s milk [51] (Table  1). [score:1]
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77
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Exposure of colorectal cancer cell lines to hypoxia has been shown to result in enhanced expression of miR-103/107 that targeted the metastasis suppressors KLF-4 and death -associated protein kinase (DAPK), conferring an invasive phenotype on them [76]. [score:7]
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The miRNA expression data were normalized to the reference gene combination of miR-28, miR-103, and miR-106a [18]. [score:3]
Expression stability of the reference miRNA combination (miR-28, miR-103, and miR-106a) and reference gene PPIA. [score:3]
Normalization was assessed with the reference miRNA combination miR-28, miR-103, and miR-106a [18], (S2 Fig). [score:1]
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79
[+] score: 7
Specifically, miR-338 and let-7a were consistently reduced in ICC in the two studies, while the miR-103 was up-regulated in Chen’s study and downregulated in our study. [score:7]
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80
[+] score: 7
Our experimental data matched the published data for seven miRNAs (miRNAs 29, 30, 100, 101, 125, and 143 were down-regulated in BC and miR103 was up-regulated) (Figure 2). [score:7]
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81
[+] score: 6
miR-107 is enriched in neurons and recent studies indicate that numerous members of miR-15/107 family having the target sites in BACE1 gene including miR-15a, miR-15b, mR-16, miR-195, miR-103 as well as miR-107; all of these miRNAs are down-regulated in gray matter of AD patients (Wang et al., 2011). [score:6]
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82
[+] score: 6
In addition, several miRNAs clearly have a role in metabolic pathways for example, miR-33a/b inhibition in nonhuman primates raises plasma HDL cholesterol and lowers triglycerides [9], and silencing of miR103/107 seems to have beneficial effects on insulin sensitivity in obese mice possibly through its target gene caveolin-1 which is a critical regulator of the insulin receptor [10]. [score:6]
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83
[+] score: 6
In another paper, Garofalo et al. reported that c-Met expression downregulates miR-103 and miR-203, inducing gefitinib resistance, and epithelial−mesenchymal transition in non-small cells lung cancer (NSCLCs). [score:6]
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84
[+] score: 6
miR-103 was shown to promote colorectal cancer through downregulation of the tumor-suppressor genes DICER and PTEN (101). [score:6]
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85
[+] score: 6
While there is no evidence in the literature of miRNAs affecting TARBP2 expression, let-7 and miR-103/- 107 family are known to regulate expression of DICER (Forman et al. 2008, Martello et al. 2010). [score:6]
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86
[+] score: 6
Of the two non-miR-17 family members (miR-103 and miR-149) among the agonists in our study, miR-103 is upregulated in bladder cancer [59], esophageal squamous cell carcinoma [67], gastric cancer [68], and colon cancer [69]. [score:4]
The agonistic group of miRNAs shares 8 members of the miR-17 cluster plus miR-103 and miR-149 in all three cancers, based on the analysis of both positively and negatively correlating genes (Additional file 9: Table S8-1). [score:1]
In each cancer, all 10 agonistic miRNAs (miR-17 family members, miR-103 and miR-149) were clustered, as were the antagonistic miRNAs (miR-221/222). [score:1]
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87
[+] score: 6
High throughput analysis of OA cartilage samples, employing miRNA array analysis, revealed that the expression of distinct miRNAs, exemplified by miRNA-22 and miRNA-103, is deregulated in OA. [score:4]
Specifically, a positive correlation among the body mass index (BMI, a measure of obesity) and the up-regulated miRNAs, miRNA-22 and miRNA-103, was reported. [score:2]
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88
[+] score: 6
However, significant overexpression of miR-107 (and its highly homologous miR-103) has been observed in pancreatic tumors [70]. [score:3]
High expression of miR-103/107 was also correlated with poor survival for patients with esophageal squamous cell carcinoma [96]. [score:3]
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89
[+] score: 6
Over -expression of miR-506 and miR-103/107 decreased Rad51 expression and subsequently reduced HR-directed repair of DNA damage induced by cisplatin, leading to an augmented response to cisplatin [33, 34]. [score:6]
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90
[+] score: 6
miRNA Mature sequence Location Potential target genes CPM per total CPM (%) eca-let-7f UGAGGUAGUAGAUUGUAUAGUU Chr23: 54150758–54150844 [–] PKD1L3, SETD9, SOS2, SRPK2, WAC 16.9 eca-let-7a UGAGGUAGUAGGUUGUAUAGUU Chr7: 29543908–29543979 [–] WAC 13.2 eca-miR-191a CAACGGAAUCCCAAAAGCAGCUG Chr16: 38001159–38001232 [+] IL13RA1, TRPM3 10.5 eca-let-7g UGAGGUAGUAGUUUGUACAGUU Chr16: 35442180–35442267 [+] ACSM3, BTRC, CDH7, RIMS2, WAC, WDR20, ZSWIM5 7.58 eca-miR-486-5p UCCUGUACUGAGCUGCCCCGAG Chr27: 3709569–3709634 [+] Not Found 5.90 eca-miR-24 UGGCUCAGUUCAGCAGGAACAG Chr7: 44930163–44930230 [+] AHDC1, AVEN, DCAF10, KANSL3, OTOP1 3.16 eca-miR-223 UGUCAGUUUGUCAAAUACCCCA ChrX: 48492588–48492691 [+] Not Found 3.07 eca-miR-21 UAGCUUAUCAGACUGAUGUUGA Chr11: 33863745–33863816 [+] ESR1, SMARCA2, ZNF800 2.91 eca-miR-92a UAUUGCACUUGUCCCGGCCUGU Chr17: 61793120–61793180 [+] STT3A 2.87 eca-miR-103 AGCAGCAUUGUACAGGGCUAUGA Chr14: 12370468–12370539 [+] Not Found 2.52 Total 68.6 (A) Venn diagram representing the numbers of miRNA species identified in the libraries. [score:3]
miRNA Mature sequence Location Potential target genes CPM per total CPM (%) eca-let-7f UGAGGUAGUAGAUUGUAUAGUU Chr23: 54150758–54150844 [–] PKD1L3, SETD9, SOS2, SRPK2, WAC 16.9 eca-let-7a UGAGGUAGUAGGUUGUAUAGUU Chr7: 29543908–29543979 [–] WAC 13.2 eca-miR-191a CAACGGAAUCCCAAAAGCAGCUG Chr16: 38001159–38001232 [+] IL13RA1, TRPM3 10.5 eca-let-7g UGAGGUAGUAGUUUGUACAGUU Chr16: 35442180–35442267 [+] ACSM3, BTRC, CDH7, RIMS2, WAC, WDR20, ZSWIM5 7.58 eca-miR-486-5p UCCUGUACUGAGCUGCCCCGAG Chr27: 3709569–3709634 [+] Not Found 5.90 eca-miR-24 UGGCUCAGUUCAGCAGGAACAG Chr7: 44930163–44930230 [+] AHDC1, AVEN, DCAF10, KANSL3, OTOP1 3.16 eca-miR-223 UGUCAGUUUGUCAAAUACCCCA ChrX: 48492588–48492691 [+] Not Found 3.07 eca-miR-21 UAGCUUAUCAGACUGAUGUUGA Chr11: 33863745–33863816 [+] ESR1, SMARCA2, ZNF800 2.91 eca-miR-92a UAUUGCACUUGUCCCGGCCUGU Chr17: 61793120–61793180 [+] STT3A 2.87 eca-miR-103 AGCAGCAUUGUACAGGGCUAUGA Chr14: 12370468–12370539 [+] Not Found 2.52 Total 68.6 As shown in the dendrogram at the top of Fig 2, samples were clustered according to tissue origins. [score:3]
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91
[+] score: 6
In the female pigs mir-9, mir-124a, mir-103, mir-10b and mir-99a were differentially expressed (Table 6). [score:3]
Mir-103 has previously been found to be expressed during adipocyte differentiation and to accelerate adipogenesis [70, 71]. [score:2]
Mir-103 is up regulated in the obese female pigs in both the sequencing study and the qPCR study (Tables 5 and 6). [score:1]
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92
[+] score: 6
Besides the identification of differential expression of miRNAs, our initial studies identified three reference endogenous miRNAs (miR-103, miR-191, and miR-423-3p). [score:3]
Additionally, GeNorm and NormFinder algorithms were run and identified miR-103, miR-191, and miR-423-3p as appropriate reference miRNAs 11. [score:1]
Three reference miRNAs, in addition to the spiked in UniSp2 were used for normalization in the validation experiments (ΔCq = NF − Cq [miRNA]) were NF is the normalization factor and NF = (Cq [miR-103] + Cq [miR-191] + Cq [miR-423-3p] + Cq [UniSp2])/4. [score:1]
M values and stability factors for GeNorm and NormFinder identify miR-423-3p, miR-191, and miR-103 as endogenous reference miRNAs for mouse experiments. [score:1]
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93
[+] score: 6
Joven J. Espinel E. Rull A. Aragonès G. Rodríguez-Gallego E. Camps J. Micol V. Herranz-López M. Menéndez J. A. Borrás I. Plant-derived polyphenols regulate expression of miRNA paralogs miR-103/107 and miR-122 and prevent diet -induced fatty liver disease in hyperlipidemic mice Biochim. [score:6]
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94
[+] score: 6
We found that LMP1 could induce the expression of several miRNAs such as miR-155, miR-188, miR-181b while other cellular miRNAs such as miR-103, miR-107 were downregulated. [score:6]
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95
[+] score: 6
By miRNA-network analysis, tissue-specific patterns of miRNA deregulation were traced: the driving miRNAs were miR-195, miR-1280, miR-140-3p and miR-1246 in colorectal tumors, and miR-103, miR-23a and miR-15b in pancreatic cancers. [score:2]
In PC network, as shown in panel B, miR-103, miR-23a and miR-15b have the highest degrees and are all linked to miR-199a-3p as well as to each other forming a four nodes clique. [score:1]
In particular, after excluding the nodes of the clique (miR-103, miR-15b, miR-199a-3p and miR-23a) the lowest ranks, namely 5.78, 5.85, 6.05 and 6.14 were obtained, respectively. [score:1]
Focusing on the principal nodes detected in PC network, miR-103 was associated with alteration of TGF-β signaling pathway, and miR-23a with KRAS -mediated signaling pathway, while for miR-15b a number of biological relevant associations with cellular signaling pathways were observed [26]. [score:1]
In particular, the maximum number of ties was found for miR-103 (degree: 8.88), miR-23a (degree: 8.84) and miR-15b (degree: 8.38). [score:1]
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96
[+] score: 6
Data have been normalized to the endogenous controls miR-26a and miR-103, and are expressed as fold change from unstimulated samples at time 0 (2 [-ΔΔCT]). [score:3]
0177664.g005 Fig 5PCR data have been normalized to the endogenous controls miR-26a and miR-103. [score:1]
PCR data have been normalized to the endogenous controls miR-26a and miR-103. [score:1]
Data were normalized to the geometric mean of two endogenous controls, miR-26a-5p and miR-103. [score:1]
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97
[+] score: 5
Hypoxia -induced miRs, such as Let-7 and miR103–104 are induced by HIF-1α and target argonaute 1, which in turn increases VEGF mRNA expression and tumor xenograft growth (28). [score:5]
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98
[+] score: 5
Other miRNAs from this paper: hsa-mir-103a-2, hsa-mir-103a-1, hsa-mir-103b-2
Here we show the effective delivery of antagomiRs to the PHH spheroids, and an increase in CYP2C8 expression when miR103 is specifically targeted 40. [score:5]
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99
[+] score: 5
Li et al. (2015) found that MEF2D is an authentic target of miR-103, which promotes cell differentiation by targeting the AKT/mTOR signaling mediated activation of MEF2D [82]. [score:5]
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100
[+] score: 5
Equivalent and high-level expression of miR-103 was detected in cord and adult blood samples (data not shown). [score:3]
Variation of mean Ct of miR-103 across four cord blood and four adult blood samples remained low (Avg_Ct = 19.75, Stdev = 1.09). [score:1]
miR-103 was chosen as the endogenous control for signal normalization across different samples based on the recommendation of previous report [14]. [score:1]
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