Monoclonal Mouse NENF Antibody
- Known as:
- Monoclonal Mouse NENF Antibody
- Catalog number:
- abx000090
- Product Quantity:
- EUR
- Category:
- -
- Supplier:
- Abbexa
- Gene target:
- Monoclonal Mouse NENF Antibody
Related genes to: Monoclonal Mouse NENF Antibody
- Gene:
- NENF NIH gene
- Name:
- neudesin neurotrophic factor
- Previous symbol:
- -
- Synonyms:
- CIR2, SCIRP10, SPUF
- Chromosome:
- 1q32.3
- Locus Type:
- gene with protein product
- Date approved:
- 2005-07-26
- Date modifiied:
- 2014-11-18
Related products to: Monoclonal Mouse NENF Antibody
Related articles to: Monoclonal Mouse NENF Antibody
- This study aimed to identify novel circulating protein biomarkers for hepatocellular carcinoma (HCC) superior to alpha-fetoprotein (AFP) by integrating tumor stemness index and secreted protein screening, and to explore their roles in prognosis, immune microenvironment, and tumor mechanisms. - Source: PubMed
Publication date: 2026/01/09
Gao CaiLi XuebingLiu XinweiYan ShaRan XiaodanHan Jingxian - To explore the key risk genes involved in developing NAFLD into HCC. Four datasets-related NAFLD progression (NAFLD, NASH, Hepatofibrosis, Cirrhotic, and Tumor) were obtained from the GEO database. GO and KEGG analyses were performed to identify the biological functions, pathways, and cellular processes associated with the genes. GSVA analyses were performed to assess the variation in pathway activity across different samples based on gene expression profiles. We performed ordinal logistic regression analysis, collinearity analysis, importance analysis of influence factors (LASSO, XGBoost, and RandomForest), and Venn analysis to identify the hub genes within disease progression. The SHAP model and K-M survival analysis screened out risk genes-related development of NAFLD into HCC. The mRNAsi_score analysis evaluates the correlation of NENF expression and tumor stemness. A vector expressing NENF transfection was used to increase its expression. CCK8, cell spheroid formation assay, colony formation, transwell, western blot, and RT-PCR assays were used to detect cell viability, tumor stemness, and gene and protein expression. NENF high expression was associated with NAFLD progression NENF was identified as the risk gene and positively associated with mRNAsi_score. Its expressions gradually increased with the progress of NAFLD to HCC. NENF promoted cells' lipid accumulation. NENF enhanced the induction of L02 cells into stem cells and augmented the tumor-like stem cell properties of L02 cells. NENF, as an important biomarker, promoted the development of NAFLD devolved to HCC by enhancing the tumor-like stem cell properties of normal cells. - Source: PubMed
Luo YuanYao Qi - Accurate identification of Human Phenotype Ontology (HPO) terms from biomedical text is crucial for disease diagnosis and analysis. However, traditional named entity recognition (NER) methods often fall short by overlooking synonyms and entity variants, resulting in reduced accuracy and coverage. To address these limitations, we introduce three strategic enhancements to improve HPO concept recognition. The first strategy augments the training data by incorporating HPO synonyms at the instance level, which enhances the model's ability to recognize diverse phenotypic expressions. The second strategy introduces HPOBERT, a semantic approach that models HPO synonyms through self-aligned pretraining. This method closely aligns synonym representations while effectively distinguishing them from non-synonyms, thereby improving the model's ability to differentiate between concepts. The third strategy integrates both the instance level and semantic approach. We evaluated these enhancement strategies on four clinical text datasets annotated with HPO concepts. The results demonstrate significant improvements in classification accuracy, recall, and both micro and macro F1 scores. Additionally, our enhancement strategies showed strong performance in Named Entity Normalization (NEN) after NER, accurately linking recognized HPO concepts to standardized knowledge bases. Specifically, we observe improvements of 2.44% and 4.38% in NEN-F on the gold and silver standard datasets, respectively, highlighting the effectiveness of our approach. The source code is available at https://github.com/ZhuLab-Fudan/HPOTagger. - Source: PubMed
Publication date: 2025/10/24
Zhai WeiqiJiang RongzeHuang XiaodiBian JunyiZhu Shanfeng - Uveal melanoma (UM) stands as the predominant primary intraocular malignancy encountered among adults. There is still limited research on the function of RNA pseudouridylation-associated genes in UM. This study identified RNA modification-related genes that play crucial role in UM by single-cell RNA sequencing analysis. We validated their expression in UM tissues and cell lines using immunohistochemistry and Western blotting experiments. Gene knockdown and overexpression experiments were conducted in UM cell lines, and their effects on UM proliferation, migration, invasion and apoptosis were verified using CCK-8, colony formation, Edu, scratch wound healing, Transwell assays and flow cytometry. RNA pseudouridylation (RNA-Ψ) modification-related genes NHP2 were identified to be highly expressed in UM tissues and cells. Cox and Lasso regression analysis suggested that NHP2 had a significant impact on the overall survival probability of UM patients. Knockdown of NHP2 inhibited the proliferation, migration, and invasion of UM cells, and promoted apoptosis, while overexpression resulted in the opposite effects. In vivo experiments confirmed that the elevated expression of NHP2 promoted the growth of UM tumors. The molecular subtypes of UM obtained through unsupervised clustering based on the gene set related to high NHP2 expression effectively distinguished the survival statuses of patients. There was a relatively strong immune response and interaction among cytokines in UM with high-risk state, which may be related to the RNA-Ψ modification mediated by NHP2. The prognostic model constructed relied on NHP2-related molecular subtypes efficiently predicted the survival probability and the metastasis risk of UM patients, and experimental validation confirmed the increased expression of the prognostic genes NENF, ILKAP, and SRD5A3 in clinical tissue samples of UM. NHP2 serves as a biomarker related to RNA-Ψ modification in UM, with increased expression promoting disease progression, indicating poor prognosis for patients, and suggesting its potential role as a molecular target for UM treatment. - Source: PubMed
Publication date: 2025/08/12
Tao YulinZhu HaiboPeng YiruiLin YetingHu WeiwenWang YicangXiong MinqiOuyang JunQu XiaoyongZhou Qiong - Prostatitis is a common condition in andrology and urology that significantly impacts the quality of life of affected individuals. Current treatments often fail to provide lasting benefits. To identify novel therapeutic targets, we conducted a drug-targeted Mendelian randomization (MR) study. Using cis-expression quantitative trait loci (cis-eQTL) data from the eQTLGen Consortium combined with Genome-Wide Association Studies (GWAS) data on prostatitis from FinnGen, we performed a two-sample MR analysis. This analysis identified nine potential causal genes: ANXA1, CRY2, DSTYK, FKBP1A, LAMA5, NENF, PTGIR, STK39, and TGFA. Following heterogeneity testing, horizontal pleiotropy assessment, and bidirectional MR, CRY2 and PTGIR were validated in the Genotype-Tissue Expression (GTEx) portal replication phase. Bayesian colocalization analysis and genetic correlation analysis investigations provided strong evidence of shared causal variants with prostatitis and negative genetic correlations for these genes. PheWAS indicated negligible horizontal pleiotropy, and drug prediction analysis identified potential targeting agents for CRY2 and PTGIR. This study highlights CRY2 and PTGIR as promising therapeutic targets for prostatitis, providing new insights into its genetic underpinnings and offering potential pathways for developing effective treatments. - Source: PubMed
Publication date: 2025/05/30
Yan KunTao YifangChen BohongZhang DongLi ZihaoLi CaogangZhang Peng