RNase A Solution, 20mg_ml Modifying Enzymes
- Known as:
- RNase A Solution, 20mg_ml Modifying Enzymes
- Catalog number:
- 43015
- Product Quantity:
- 10ml
- Category:
- -
- Supplier:
- mbiote
- Gene target:
- RNase Solution 20mg_ml Modifying Enzymes
Related genes to: RNase A Solution, 20mg_ml Modifying Enzymes
- Gene:
- RNASE6 NIH gene
- Name:
- ribonuclease A family member k6
- Previous symbol:
- RNS6
- Synonyms:
- RAD1, RNaseK6
- Chromosome:
- 14q11.2
- Locus Type:
- gene with protein product
- Date approved:
- 1997-01-08
- Date modifiied:
- 2016-10-05
Related products to: RNase A Solution, 20mg_ml Modifying Enzymes
Related articles to: RNase A Solution, 20mg_ml Modifying Enzymes
- Several studies have reported an up-regulation of interleukin (IL)-36 in the serum of patients with systemic lupus erythematosus (SLE). Here, we sought to define the mechanisms whereby IL-36 may contribute to the over-activation of type I Interferon (IFN) responses observed in SLE. - Source: PubMed
Publication date: 2026/01/13
Welsh Emma JMcCluskey DanielBaum PatrickLewis Myles JCapon Francesca - Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the interplay of genetic and environmental factors, and currently, there there is a lack of effective diagnostic or therapeutic strategies available. This study aims to identify circulating biomarkers for ALS and investigate their interactions with environmental toxins. - Source: PubMed
Publication date: 2025/11/06
Xu LeiHuang BinZhou YaqiuLiao XiaolinChen TingHe Hongping - Cutaneous melanoma is a highly invasive tumor. It enhances metastasis and resistance to immunotherapy immunosuppressive mechanisms. Understanding RNA-binding proteins (RBPs) in melanoma's immune alterations is limited. This study explores immune-regulatory RBPs in metastasis and clarifies RNASE6's role in immune regulation. - Source: PubMed
Publication date: 2025/10/07
Gao PengfeiGao XiaoluZeng XueHua XiangHe WanmeiMin LiYuan ZiqiZhang QianweiPeng Xuebiao - Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline and memory loss. While the precise causes of AD remain unclear, emerging evidence suggests that messenger RNA (mRNA) dysregulation contributes to AD pathology and risk. This study examined exosomal mRNA expression profiles of 15 individuals diagnosed with AD and 15 healthy controls from Barranquilla, Colombia. Utilizing advanced bioinformatics and machine learning (ML) techniques, we identified differentially expressed mRNAs and assessed their predictive power for AD diagnosis and AD age of onset (ADAOO). Our results showed that ENST00000331581 () and ENST00000382258 () were significantly upregulated in AD patients. Key predictors for AD diagnosis included ENST00000311550 (), ENST00000278765 (), ENST00000331581 (), ENST00000372572 (), and ENST00000636358 (), achieving > 90% accuracy in both training and testing datasets. For ADAOO, ENST00000340552 () expression correlated with a delay of ~12.6 years, while ENST00000304677 (), ENST00000640218 (), ENST00000602017 (), ENST00000224950 (), and ENST00000322088 () emerged as the most important predictors. ENST00000304677 () and ENST00000602017 () showed promising predictive accuracy in unseen data. These findings suggest that mRNA expression profiles may serve as effective biomarkers for AD diagnosis and ADAOO, providing a cost-efficient and minimally invasive tool for early detection and monitoring. Further research is needed to validate these results in larger, diverse cohorts and explore the biological roles of the identified mRNAs in AD pathogenesis. - Source: PubMed
Publication date: 2024/11/15
Bolívar Daniel AMosquera-Heredia María IVidal Oscar MBarceló ErnestoAllegri RicardoMorales Luis CSilvera-Redondo CarlosArcos-Burgos MauricioGaravito-Galofre PilarVélez Jorge I - It is known that monocytes can make a significant contribution to the development of chronic obstructive pulmonary disease (COPD); however, the features of the transcriptome of these cells associated with the disease remain poorly understood. - Source: PubMed
Publication date: 2024/10/31
Naumov D EKotova O OGassan D ASugaylo I YuSheludko E GGorchakova Y G