AIF1_RAT Mrf1 ELISA tesk kit
- Known as:
- AIF1_RAT Mrf1 Enzyme-linked immunosorbent assay test tesk reagent
- Catalog number:
- gen16132
- Product Quantity:
- 1
- Category:
- Peptides
- Supplier:
- Other suppliers
- Gene target:
- AIF1_RAT Mrf1 ELISA tesk kit
Related genes to: AIF1_RAT Mrf1 ELISA tesk kit
- Gene:
- TRIM59 NIH gene
- Name:
- tripartite motif containing 59
- Previous symbol:
- TRIM57
- Synonyms:
- TSBF1, Mrf1, RNF104
- Chromosome:
- 3q25.33
- Locus Type:
- gene with protein product
- Date approved:
- 2004-07-12
- Date modifiied:
- 2016-10-05
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- Age estimation using DNA methylation analysis is one of the tools currently used in forensic science to facilitate human identification. A total of 117 buccal swab samples from individuals aged 18 to 67 years were analyzed using a custom panel encompassing 610 CpG sites across 12 age-related genes. The analysis was performed using the amplicon-based technology Ion AmpliSeq™, which incorporates Ion Torrent S5 sequencing (Thermo Fisher Scientific, Waltham, MA, USA). The resulting methylation data were used to develop and compare age-prediction models based on Watson-strand, Crick-strand, and combined Watson + Crick methylation matrices. After candidate CpG selection and model reduction, the final Watson-strand model used 5 CpG sites from the age-related genes C1orf132, ELOVL2, KLF14, PDE4C and TRIM59 and was fitted using Elastic Net regression with alpha grid search, lambda selection and internal cross-validation. Model validation yielded prediction results with a mean absolute error of 4.42 years for the Watson matrix, 4.75 years for the Crick matrix, and 5.08 years for the WC matrix. These results allow for the evaluation of the suitability of using Ion AmpliSeq™ technology in forensic age estimation studies based on DNA methylation analysis. - Source: PubMed
Publication date: 2026/08/06
Puerto-Parra Yecith DGómez-Martín AntonioAndújar-Vera FranciscoSaiz MaríaVinueza-Espinosa Diana CLópez-Guarnido OlgaÁlvarez Juan CarlosLorente José Antonio - MECOM rearrangements (MECOM-r) are high-risk events in myeloid neoplasms often cryptic or incompletely characterized by conventional karyotype analysis. We used optical genome mapping (OGM) to define the frequency and spectrum of MECOM-r in an unselected, consecutively collected cohort of individuals with high-grade myeloid neoplasms (HGMNs) and compared these findings with standard cytogenetic approaches. - Source: PubMed
Salcedo-Porras NicolasAlBulushi FatmaParlow Julia N CMcGinnis EricSpence Tara - DNA methylation is an established biomarker of human ageing and is used by a variety of tools to identify meaningful epigenetic signals. We investigated whether analysing CpGs grouped by transcript as functional units could generate a ranked list of transcripts most correlated with age that might otherwise be overlooked in genome-wide CpG-based studies. Here we present Epitage ( https://github.com/a00s/epitage ), a continuously updated ranked list of transcripts built from the GSE87571 dataset (714 whole-blood samples, ages 14-94 years) through intensive testing with machine-learning models. To support reproducible analyses, we developed ugPlot ( https://github.com/a00s/ugplot ), an open-source R/Shiny tool with a graphical user interface that automates model training, testing, and comparison. Initially, we identified 48 transcripts across 13 genes, with some transcripts from the genes OBSCN, PRRT1, and SPTBN4 showing better predictive performance when multiple associated CpGs were analysed together rather than individually. In contrast, for the majority of transcripts, a dominant individual CpG still showed a higher Spearman correlation with age, as seen in established ageing genes such as ELOVL2, FHL2, and TRIM59. Epitage is a transcript-ranking list based on the methylation patterns observed in the analysed dataset. It provides a reproducible framework for prioritising transcripts associated with human ageing and for guiding future epigenetic studies. - Source: PubMed
Publication date: 2026/07/22
Benazzi Maia ThiagoPfeffer Ulrich - Background Cognitive symptoms after SARS-CoV-2 infection, often described as "brain fog," remain difficult to measure objectively and are biologically heterogeneous. DNA methylation may provide a stable, blood-accessible layer of information linking post-COVID immune remodeling, biological aging, and neuropsychiatric vulnerability. We re-analyzed GSE247869, a whole-blood Illumina MethylationEPIC dataset from individuals sampled six months after COVID-19 infection, to identify age-associated methylation signals with translational relevance. The present analysis was designed to characterize age-associated methylation within this post-COVID cohort, not to establish a COVID-19-specific signature or biological age acceleration. Methodology This was a cross-sectional analysis of a single post-COVID cohort, with 94 samples included in the age models and no COVID-19-negative comparator included in the analyzed model. Processed beta values were aligned to metadata, converted to M-values, and modeled at each cytosine-phosphate-guanine (CpG) using ordinary least squares with age and sex as predictors. Differentially methylated positions were corrected by Benjamini-Hochberg false discovery rate (FDR). CpGs were mapped to genes using robust annotation and Illumina manifest fallback. Gene-level signals were integrated using a multi-evidence prioritization score that incorporated statistical strength, effect size, multi-CpG support, direction consistency, known epigenetic-clock membership, and curated pathway membership. Results Within this cohort, the analysis identified 3,467 age-associated CpGs at FDR < 0.05, with an overall hypomethylation bias but focal hypermethylation at canonical aging loci. In total, 11 of 12 reference clock CpGs were recovered, including , , , , , and . The strongest exploratory signal was enrichment of glutamatergic/N-methyl-D-aspartate (NMDA) genes, including , , , , , and and had high integrated evidence scores and showed age-associated hypermethylation. The prioritized genes mapped interpretively to glutamatergic synapse, calcium signaling, and cAMP signaling pathways, although these complete KEGG pathways were not tested as formal enrichment categories. Conclusions This re-analysis recovered established age-associated CpGs and identified age-associated methylation enrichment near glutamatergic/NMDA genes within this post-COVID cohort. It cannot determine whether these signals are specific to COVID-19 infection, reflect accelerated biological aging, or relate to cognitive symptoms because no COVID-19-negative comparator or symptom-level cognitive phenotyping was included in the present analysis. The glutamatergic finding is hypothesis-generating, particularly because the curated set was small and no independent replication cohort was analyzed. Future longitudinal and case-control studies integrating / methylation with cognitive and inflammatory phenotyping are needed. Glutamatergic and calcium-signaling pathways may be evaluated in appropriately designed mechanistic and intervention studies, including but not limited to hypotheses related to the Cheung Glutamatergic Regimen, only after independent validation and careful safety evaluation. - Source: PubMed
Publication date: 2026/07/18
Cheung Ngo - Ischemic stroke is a cerebrovascular disease that activates the complement system, leading to inflammation and neuronal injury. TRIM59, an E3 ubiquitin ligase, has been extensively studied in cancer, sepsis, and myocardial infarction, and is upregulated in macrophages after ischemic stroke. This study used myeloid cell Trim59 conditional knockout and macrophage-specific Trim59 overexpression mice to investigate the role of macrophage TRIM59 in regulating complement C3 release and neuronal phagocytosis following cerebral ischemia. - Source: PubMed
Publication date: 2026/06/30
Li XiangTian XinjuanZhang JingjingPan MengtianXu BaohuiWei JieYan DongmeiFang Weirong