GAS7 antibody - N-terminal region (ARP30004_T100)
- Known as:
- GAS7 (anti-) - N-terminal region (ARP30004_T100)
- Catalog number:
- arp30004_t100
- Product Quantity:
- USD
- Category:
- -
- Supplier:
- Aviva Systems Biology
- Gene target:
- GAS7 antibody - N-terminal region (ARP30004_T100)
Ask about this productRelated genes to: GAS7 antibody - N-terminal region (ARP30004_T100)
- Gene:
- GAS7 NIH gene
- Name:
- growth arrest specific 7
- Previous symbol:
- -
- Synonyms:
- KIAA0394, MGC1348
- Chromosome:
- 17p13.1
- Locus Type:
- gene with protein product
- Date approved:
- 1998-10-19
- Date modifiied:
- 2015-11-23
Related products to: GAS7 antibody - N-terminal region (ARP30004_T100)
Related articles to: GAS7 antibody - N-terminal region (ARP30004_T100)
- Bladder cancer (BC) screening contributes to better patient outcomes. However, existing diagnostic methods for BC are not suitable for large-scale screening. Serum microRNAs (miRNAs) are expected to be simple, cost-effective, and non-invasive screening tools for BC. This study aims to identify whether relevant serum miRNAs as diagnostic markers for BC. - Source: PubMed
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Zhou HuimeiGe ZhenjianLin ShengjieWu YutongZhang PengwuLi XutaiZhao ZhengpingLai YongqingTao Lingzhi - are characterized by their ability to tolerate coarse feed, strong disease resistance, and delicious meat. Lower reproductive efficiency has become one of the key factors limiting its development. Therefore, this study investigated the developmental patterns of follicles and screened key candidate genes for in vitro experimental validation. Research collected granulosa cells from small follicles (<5 mm), medium (5-8 mm), and big (>8 mm), followed by RNA extraction for transcriptomic sequencing. A total of 20,775 genes were identified, including 13,777 (66.3%) differentially expressed genes (DEGs). DEGs showing up-regulation and down-regulated in B vs. S, B vs. M, and M vs. S groups were collected. A total of 19 commonly up-regulated DEGs across the three groups were identified, including genes such as , , and . Additionally, 227 commonly down-regulated DEGs were identified, including genes such as , , and . Protein interaction network analysis revealed an interaction between and . ovarian granulosa cells (GCs) were collected to investigate the effect of the on GCs proliferation. The results revealed that expression was highest in small follicles and was almost absent in big follicles. Subsequently, the gene was knocked down in GCs using small interfering RNA. RT-qPCR results demonstrated that both si-INSL3 (239) and si-INSL3 (392) significantly knock down expression ( < 0.01), si-INSL3 (239) for follow-up research. CCK-8 was used to assess cell proliferation, revealing that knockdown significantly enhanced GCs viability and number at 24, 48, and 72 h ( < 0.05). Flow cytometry was used to detect cell cycle distribution. The results showed that knockdown of expression significantly decreased the proportion of G1 phase cells and significantly increased the number of S phase cells ( < 0.01). RT-qPCR was used to detect the expression of cell proliferation-related genes. The results showed that compared with the siNC group, the expression levels of , , , and were significantly increased in the si-INSL3 group. In conclusion, knockdown of affects follicular development in by regulating granulosa cell proliferation in the ovaries, providing new insights into the regulatory mechanisms of follicular development in cattle. - Source: PubMed
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Li HongxianHe FenglouLi XinyeNie JunjieKhan Hasnain AliChen ChaoHua Jinling - Responsiveness to mood-stabilizing pharmacotherapy varies in bipolar disorder (BD). We investigated clinical correlates of second-generation antipsychotic (SGA) treatment response and conducted the first genome-wide association study (GWAS), including exploratory polygenic scores (PGS), of SGA pharmacogenomic treatment response in BD. - Source: PubMed
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Chen Shu YingLing AnniChan Poemen PHuang ChukaiKawashima RumiUsui ShinichiMatsushita KenjiTam Pancy OYoung Alvin LYam Jason CNishida KohjiTsujikawa MotokazuZhang MingzhiPang Chi PuiTham Clement CChen Li Jia - Colorectal cancer is a highly lethal gastrointestinal tract malignancy whose pathogenesis and molecular drivers are not fully understood. This study focused on searching for genes that are differentially expressed in cancer versus normal mucosa, with the goal of identifying molecular patterns of expression that are mechanistically linked to colorectal cancer pathogenesis. We analyzed 585 colorectal cancer samples and 329 normal samples from the Gene Expression Omnibus database, creating a weighted gene coexpression network analysis across 24,069 genes. Through this approach, five modules associated with colorectal cancer were identified, which were enriched in MAPK signaling and cholesterol metabolism pathways. Using least absolute shrinkage and selection operator (LASSO) regression, we selected 13 hub genes [ABCB5, AOC1, ARHGAP44, CACNG3, dysbindin domain-containing protein 1 (DBNDD1), GAS7, GTF2IRD1, PRSS22, SCN4A, TTC22, DLX6, PDK4, and SLC13A2] from these modules. Survival analysis indicated that higher expression of DBNDD1 correlated with worse overall survival in patients with colorectal cancer. Machine learning validation confirmed the stability of these genetic markers. Experimental validation demonstrated increased levels of DBNDD1 and growth differentiation factor 15 (GDF15) in colorectal cancer, promoting constant NF-κB (RELA) activation via DBNDD1-dependent GDF15 induction. Knocking down DBNDD1 inhibited cell proliferation, migration, and invasion in vitro (DLD1/HCT116 cells), alongside decreased GDF15 expression and reduced p-NF-κB p65-p-I-κB signaling. Additionally, DBNDD1 knockdown resulted in reduced tumor growth in vivo, highlighting that the DBNDD1-GDF15-NF-κB signaling pathway drives colorectal cancer pathogenesis. - Source: PubMed
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