Ask about this productRelated genes to: GALNT14 antibody
- Gene:
- GALNT14 NIH gene
- Name:
- polypeptide N-acetylgalactosaminyltransferase 14
- Previous symbol:
- -
- Synonyms:
- GalNac-T10, FLJ12691, GalNac-T14
- Chromosome:
- 2p23.1
- Locus Type:
- gene with protein product
- Date approved:
- 2003-11-13
- Date modifiied:
- 2016-10-05
Related products to: GALNT14 antibody
Related articles to: GALNT14 antibody
- Sepsis lacks reliable biomarkers for early diagnosis and treatment. This study integrates systems biology approaches, weighted gene coexpression network analysis (WGCNA), and experimental validation to identify novel diagnostic and therapeutic targets. - Source: PubMed
Publication date: 2026/05/13
Zhu XiuqiZhai YiYao JialiChen YueGe Wenhan - Cisplatin-induced acute kidney injury (Cis-AKI) is a significant cause of renal damage, characterized by tubular injury, ferroptosis, and oxidative stress. While therapeutic options for Cis-AKI remain limited, identifying novel targets to prevent kidney injury is critical. This study focuses on GALNT14, a gene associated with ferroptosis, and its potential role in mitigating Cis-AKI. - Source: PubMed
Publication date: 2025/09/04
Yuan ChengYe YuluZhou YinjieXu LuYi TingzhuangNi Lihua - Surgical resection is the primary curative treatment for hepatocellular carcinoma (HCC), while high recurrence rates can limit the prognosis, emphasizing the need for reliable biomarkers. -rs9679162 is associated with postoperative prognosis and therapeutic responses. However, relying on one single nucleotide polymorphism (SNP) greatly limits its predictive power. This study aims to identify an SNP panel to improve prognosis prediction and explore its role in modulating tumor-infiltrating immune cells (TIICs). - Source: PubMed
Publication date: 2025/08/04
Chu Yu-DeHo Pei-HuanChen Wei-TingShih Yu-LinLai Ming-WeiHsu Chao-WeiYeh Chau-Ting - IgA nephropathy (IgAN) is a highly prevalent type of primary glomerulonephritis. IgAN involves mesangial deposition of immune complexes leading to complement activation, inflammation, and glomerular injury. A key hit for pathogenesis involves aberrant O-glycosylation in the hinge region of IgA. Despite its prevalence, however, the mechanisms underlying IgAN remain incompletely understood. In this issue of the JCI, Prakash and colleagues used whole-exome sequencing of two IgAN probands to identify loss-of-function variants in GALNT14 leading to loss of the enzyme GalNAc-T14, which is involved in O-glycosylation. The authors then performed a classical bedside-to-bench investigation using a Galnt14-/- mouse model and connected loss of GalNAc-T14 to excess IgA production, impaired B lymphocyte homing, and defective intestinal mucus production. These findings build a more unified understanding of IgAN pathogenesis from defective O-glycosylation with loss-of-function variants in GALNT14. - Source: PubMed
Publication date: 2025/05/15
Pell JohnMenon Madhav C - Recent advancements in biomarker identification and machine learning have significantly enhanced the prediction and diagnosis of Bronchopulmonary Dysplasia (BPD) and neonatal respiratory distress syndrome (nRDS) in preterm infants. Key predictors of BPD severity include elevated cytokines like Interleukin-6 (IL-6) and Tumor Necrosis Factor-alpha (TNF-α), as well as inflammatory markers such as the Neutrophil-to-Lymphocyte Ratio (NLR) and soluble gp130. Research into endoplasmic reticulum stress-related genes, differentially expressed genes, and ferroptosis-related genes provides valuable insights into BPD's pathophysiology. Machine learning models like XGBoost and Random Forest have identified important biomarkers, including CYYR1, GALNT14, and OLAH, improving diagnostic accuracy. Additionally, a five-gene transcriptomic signature shows promise for early identification of at-risk neonates, underscoring the significance of immune response factors in BPD. For nRDS, biomarkers such as the lecithin/sphingomyelin (L/S) ratio and oxidative stress indicators have been effectively used in innovative diagnostic methods, including attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and high-content screening for ABCA3 modulation. Machine learning algorithms like Partial Least Squares Regression (PLSR) and C5.0 have shown potential in accurately identifying critical health indicators. Furthermore, advanced feature extraction methods for analyzing neonatal cry signals offer a non-invasive means to differentiate between conditions like sepsis and nRDS. Overall, these findings emphasize the importance of combining biomarker analysis with advanced computational techniques to improve clinical decision-making and intervention strategies for managing BPD and nRDS in vulnerable preterm infants. - Source: PubMed
Publication date: 2025/04/25
Talebi HaniehDastgheib Seyed AlirezaVafapour MaryamBahrami RezaGolshan-Tafti MohammadDanaei MahsaAzizi SepidehShahbazi AmirhosseinPourkazemi MelinaYeganegi MaryamShiri AmirmasoudMasoudi AliRashnavadi HeewaNeamatzadeh Hossein