Protein Tyrosine Phosphatase (PTP) PTPRC
- Known as:
- Protein Tyrosine Phosphatase (PTP) PTPRC
- Catalog number:
- E-3360
- Product Quantity:
- 20 ug
- Category:
- -
- Supplier:
- Bioner
- Gene target:
- Protein Tyrosine Phosphatase (PTP) PTPRC
Related genes to: Protein Tyrosine Phosphatase (PTP) PTPRC
- Gene:
- ACP1 NIH gene
- Name:
- acid phosphatase 1
- Previous symbol:
- -
- Synonyms:
- HAAP, LMW-PTP, LMWPTP
- Chromosome:
- 2p25.3
- Locus Type:
- gene with protein product
- Date approved:
- 1986-01-01
- Date modifiied:
- 2017-09-15
- Gene:
- DUSP1 NIH gene
- Name:
- dual specificity phosphatase 1
- Previous symbol:
- PTPN10
- Synonyms:
- HVH1, CL100, MKP-1
- Chromosome:
- 5q35.1
- Locus Type:
- gene with protein product
- Date approved:
- 1993-03-03
- Date modifiied:
- 2015-09-11
- Gene:
- HACD1 NIH gene
- Name:
- 3-hydroxyacyl-CoA dehydratase 1
- Previous symbol:
- PTPLA
- Synonyms:
- CAP
- Chromosome:
- 10p12.33
- Locus Type:
- gene with protein product
- Date approved:
- 1999-01-22
- Date modifiied:
- 2016-01-15
- Gene:
- HACD2 NIH gene
- Name:
- 3-hydroxyacyl-CoA dehydratase 2
- Previous symbol:
- PTPLB
- Synonyms:
- -
- Chromosome:
- 3q21.1
- Locus Type:
- gene with protein product
- Date approved:
- 1999-01-22
- Date modifiied:
- 2016-01-15
- Gene:
- HACD3 NIH gene
- Name:
- 3-hydroxyacyl-CoA dehydratase 3
- Previous symbol:
- PTPLAD1
- Synonyms:
- B-ind1, HSPC121
- Chromosome:
- 15q22.31
- Locus Type:
- gene with protein product
- Date approved:
- 2005-11-11
- Date modifiied:
- 2016-01-15
Related products to: Protein Tyrosine Phosphatase (PTP) PTPRC
Related articles to: Protein Tyrosine Phosphatase (PTP) PTPRC
- Osteoarthritis (OA) is widely recognized as the most prevalent degenerative disorder affecting the joints, representing a major contributor to chronic pain and disability. Despite its high burden, the molecular mechanisms underlying OA pathogenesis remain poorly understood, particularly in the context of immune microenvironment modulation. This study explores the immune-related OA progression mechanisms and investigates potential biomarkers to aid diagnosis and therapeutic intervention. - Source: PubMed
Publication date: 2026/04/13
Zhang ZhengyaoWang YilinTan ZhiwenYu XiaohuiLiu Bo - The absence of accessible and reliable biomarkers constitutes a critical barrier for the early diagnosis and stratification of neurodegenerative diseases. While peripheral blood offers a minimally invasive window into systemic pathophysiology, identifying molecular signatures that survive biological heterogeneity and technical noise remains an unresolved challenge. In this study, this issue was addressed through a comparative systemic transcriptomic analysis of Amyotrophic Lateral Sclerosis (ALS), Alzheimer’s disease (AD), and Parkinson’s disease (PD) in whole blood, implementing a comprehensive workflow integrating unsupervised network analysis and supervised machine-learning methods. By employing LASSO regression and cross-validation across independent external cohorts, a stable and specific transcriptomic signature for ALS was identified, comprising key crosstalk genes involved in systemic immune dysregulation and microglial function, including , and . In contrast, AD and PD exhibited weak transcriptomic signatures with poor predictive reproducibility, suggesting a distinctive systemic pathology in ALS. In addition, the study confirms the superiority of linear modeling for this genomic signature: while complex non-linear algorithms, specifically Radial Basis Function (RBF) kernel Support Vector Machine (SVM) and Random Forest, displayed high initial performance, they collapsed due to overfitting during external validation. Conversely, the linear LASSO model demonstrated superior robustness and generalizability (AUC 0.74). In conclusion, this study not only defines a unique systemic immunotranscriptomic signature for ALS, distinguishable from other neurodegenerative pathologies, but also establishes interpretability and linear simplicity as essential factors for developing reproducible blood-based biomarkers with clinical translational potential. - Source: PubMed
Publication date: 2026/04/29
Gascón ElisaCalvo Ana CristinaZaragoza PilarOsta Rosario - γδ T cells boost inflammatory responses and exacerbate tissue damage after ischemic stroke. However, the origin, dynamics, and tissue adaptation of γδ T cells in the ischemic brain and its border regions remain poorly understood. A systematic integration of large-scale datasets is urgently needed. Here, we investigated the impact of ischemic stroke on the state of meningeal and brain-infiltrating γδ T cells and explored their potential contributions to post-stroke inflammation. - Source: PubMed
Publication date: 2026/04/09
Zha MingmingJander AlinaCai HaodiPiepke MariusDegenhardt KarolineWinter LeoMagnus TimGelderblom Mathias - Diabetic kidney disease (DKD) is a common diabetes complication that increases global morbidity and mortality. To identify DKD biomarkers and explore autophagy-related mechanisms to find potential therapeutic targets for DKD treatment. - Source: PubMed
Wang QinLi XiaoqiYe WenWang QiBi Xianjin - India harbours a diverse range of indigenous goat breeds that have adapted to varied climatic zones over centuries. This study investigated the genomic basis of local adaptation in these populations (n= 11) divided into seven agro-climatic zones using genome-wide SNP data and century-scale environmental variables. A total of 2,295,833 SNPs and 15 non-collinear bioclimatic predictors were analyzed using the landscape genomics tool R SamBada for genotype-environment association. Models were selected based on G-score and q-value thresholds (q < 0.01). Several loci showed strong signatures of selection, with associated genes enriched in key adaptive pathways, including HIF-1 signalling, insulin signalling, and toll-like receptor pathways. Many key genes and pathways were identified with both direct and indirect roles in adaptation to specific agro-climatic zone. Only 9 SNP variants showed SIFT score < 0.05 (deleterious) out of which, only 2 variants each harbouring gene PTPRC and PLCB1 were predicted to be deleterious with high confidence. Further downstream technical validation for functionality was done using PTPRC and PLCB1 present in coding region and exhibited significant environmental associations. Missense mutations in these genes were further characterized using I-Mutant, ConSurf, and Phyre2. The PTPRC variant was predicted to reduce protein stability within a moderately conserved immune domain, and structural modelling indicated altered folding in mutant proteins. These adaptive variants likely contribute to resilience against heat, humidity, and pathogen-driven stress. This integrative landscape genomics approach reveals how natural selection and environmental pressures have shaped the adaptive genome of Indian indigenous goats and provides a foundation for marker-assisted selection to enhance climate resilience in future breeding programs. This study represents the first landscape genomics analysis in indigenous goat populations of India. - Source: PubMed
Publication date: 2026/04/06
Rathi PallaviSukhija NidhiGanguly IndrajitDixit S PSingh SanjeevChinnareddyvari Chandana SreeDharaamshaw C A