ANTI RAT CD3 FITC_CD45RA RPE_CD161 Alexa Fluor® 647, Product Type Triple Color Reagent, Specificity CD3_CD45RA_CD161, Target Species Rat, Host Mouse, Format FITC _ RPE _ ALEXA FLUOR®647, Isotypes
- Known as:
- ANTI RAT CD3 FITC_CD45RA RPE_CD161 Alexa Fluor® 647, Product Type Triple Color Reagent, Specificity CD3_CD45RA_CD161, Target Species Rat, Host Mouse, Format fluorecein _ RPE _ ALEXA FLUOR®647, Isotypes
- Catalog number:
- TC019
- Product Quantity:
- 50 TESTS
- Category:
- -
- Supplier:
- AbD
- Gene target:
- ANTI RAT CD3 FITC_CD45RA RPE_CD161 Alexa Fluor® 647 Product Type Triple Color Reagent Specificity CD3_CD45RA_CD161 Target Species Rat Host Mouse Format FITC _ RPE ALEXA FLUOR®647 Isotypes
Related genes to: ANTI RAT CD3 FITC_CD45RA RPE_CD161 Alexa Fluor® 647, Product Type Triple Color Reagent, Specificity CD3_CD45RA_CD161, Target Species Rat, Host Mouse, Format FITC _ RPE _ ALEXA FLUOR®647, Isotypes
- Gene:
- GNL2 NIH gene
- Name:
- G protein nucleolar 2
- Previous symbol:
- -
- Synonyms:
- Ngp-1, HUMAUANTIG, Nog2, Nug2
- Chromosome:
- 1p34.3
- Locus Type:
- gene with protein product
- Date approved:
- 2004-09-06
- Date modifiied:
- 2019-02-08
Related products to: ANTI RAT CD3 FITC_CD45RA RPE_CD161 Alexa Fluor® 647, Product Type Triple Color Reagent, Specificity CD3_CD45RA_CD161, Target Species Rat, Host Mouse, Format FITC _ RPE _ ALEXA FLUOR®647, Isotypes
Related articles to: ANTI RAT CD3 FITC_CD45RA RPE_CD161 Alexa Fluor® 647, Product Type Triple Color Reagent, Specificity CD3_CD45RA_CD161, Target Species Rat, Host Mouse, Format FITC _ RPE _ ALEXA FLUOR®647, Isotypes
- Liver hepatocellular carcinoma (LIHC) is a common malignancy, yet the core genes driving its progression and potential therapeutic targets remain insufficiently explored. Ribosome biogenesis (RB) is a critical biological process linked to various cancers; however, its systematic role in LIHC remains unclear. - Source: PubMed
Publication date: 2026/05/14
Qi YajieLi KunLi PinchengYan JianyuFeng ShuyueWan DanDu KeLiang XiaoYang FanZhou ErzhengHuang NaWang QianLiu Nanbin - Production of the eukaryotic ribosomal subunits (40S and 60S) is a highly dynamic process in which numerous assembly factors (AFs) coordinate structural rearrangements of pre-ribosomal complexes to achieve their mature, functional architectures. Across the domains of life, GTPases leverage their functions as molecular switches to induce conformational changes that drive key steps in subunit maturation. Three GTPases, GTPBP4, GNL2, and GNL3, have been detected in nucleolar/nucleoplasmic human pre-60S complexes. Here, we compositionally analyze the pre-ribosomal particles associated with each of these GTPases and demonstrate the requirement of these enzymes, and their abilities to bind and hydrolyze GTP, for distinct steps in pre-ribosomal RNA processing. We further reveal that the GNL3 paralog, GNL3L, also associates with pre-ribosomes, and we map GNL3L binding sites on pre-rRNAs as well as identifying RNA contact sites on GNL3L. Lack of GNL3L impairs synthesis of the 60S rRNAs and expression of GTPase-inactive GNL3L causes defects in early steps of pre-rRNA processing. Impaired GTP hydrolysis by GNL3L leads to its accumulation on pre-60S particles, together with other AFs with proximal binding sites. Our data further demonstrate that the GTPase activity of GNL3L is required for maintaining 60S subunit levels, protein synthesis, and cellular proliferation. - Source: PubMed
Thomé Chairini CLemus-Diaz NicolasBloch von Blottnitz Katja ITagnères SophieKlein Helmkamp MerleHonemann-Capito MonaHackert PhilippMoshkovskii SergeiLenz ChristofBohnsack Markus TUrlaub HenningBohnsack Katherine E - : Carfilzomib (CFZ) and bortezomib (BTZ) are proteasome inhibitors used as the first-line therapy for relapsed or refractory multiple myeloma (MM) but are associated with cardiovascular adverse events (CVAEs). This study aims to identify differentially methylated positions (DMPs) and regions (DMRs), and enriched pathways associated with CVAEs related to CFZ or BTZ-based treatment. : Baseline germline DNA methylation profiles from 79 MM patients (49 on CFZ and 30 on BTZ) in the Prospective Study of Cardiac Events During Proteasome Inhibitor Therapy (PROTECT) were analyzed. Epigenome-wide analyses were performed within each group, followed by meta-analyses to identify signals common to CVAEs associated with both medicines. : Four DMPs were significantly associated with CFZ-CVAEs, including cg15144237 within ( = 9.45 × 10), cg00927646 within ( = 9.78 × 10), and cg10965131 within ( = 1.00 × 10). One DMR was identified in the region ( = 5.46 × 10). There was no evidence of any DMPs in BTZ-treated patients, however two DMPs and one DMR reached a suggestive level of significance ( < 1.00 × 10): cg09666417 in ( = 3.41 × 10) and cg12987761 in ( = 5.00 × 10), and a DMR mapped to the region ( = 8.11 × 10). Meta-analysis did not find any significant DMPs, with the top CpG being cg17933807 in ( = 7.38 × 10). Pathway enrichment analyses identified peroxisome, MAPK, Rap1, adherens junction, phospholipase D, autophagy, and aldosterone-related pathways to be implicated in CVAEs. : Our study identified distinct DMPs, DMRs, and pathways enrichment associated with CVAE, suggesting epigenetic contributors to CVAEs and supporting the need for larger validation studies. - Source: PubMed
Publication date: 2026/02/03
Alshammari Raed AwadhRubinstein Samuel MFarber-Eger EricShaffer Lauren LeeTantawy MarwaAlomar Mohammed EWells Quinn SLenihan DanielCornell Robert FShain Kenneth HBaz Rachid CGong Yan - Liver hepatocellular carcinoma (LIHC) represents a category of malignant neoplasms that present a considerable risk to public health. Recent studies have increasingly focused on the biological roles of messenger RNAs (mRNAs) linked to deubiquitinating enzymes in the context of LIHC. These deubiquitinating enzyme-associated mRNAs have been utilized to construct a prognostic model for this type of cancer. Prognostic mRNAs associated with LIHC were identified through univariate Cox regression and co-expression analysis. A clinical risk prediction model was established utilizing multivariate Cox regression and least absolute shrinkage and selection operator analysis, resulting in the stratification of patients into high-risk and low-risk categories. The model's accuracy and clinical significance were assessed through various methodologies, including receiver operating characteristic curves, area under the curve calculations, univariate and multivariate Cox regression analyses, principal component analysis, t-distributed stochastic neighbor embedding, Kaplan-Meier Plotter, gene set enrichment analysis, tumor mutation burden analysis, immune infiltration analysis, and drug sensitivity prediction. The UALCAN database was employed to validate the aberrant expression of the identified characteristic genes, and consistency clustering analysis was conducted to delineate and compare the molecular subtypes of LIHC. The risk model we developed exhibited robust predictive capabilities, with the high-risk cohort demonstrating reduced survival rates across various clinical contexts. This group also presented a more pronounced tumor mutation burden, exhibited stronger correlations with immune cell populations, and displayed heightened activation of numerous immune checkpoints. Notably, the characteristic genes (CBX2, ERGIC3, GNL2) were found to be aberrantly overexpressed in the cancer genome atlas cohort, correlating with unfavorable prognostic outcomes, and may play a role in tumor invasion and metastasis. Consistency clustering analysis revealed 3 distinct subtypes (C1, C2, C3), with subtype C3 showing elevated activation levels at the majority of immune checkpoints in comparison to subtypes C2 and C1, as well as increased sensitivity to pharmacological agents such as 5-fluorouracil and afatinib. The prognostic assessment model developed in this research offers an innovative approach for the identification of novel prognostic markers in patients diagnosed with (LIHC). - Source: PubMed
Liu HaodongLiu YinanLiang ShijieYang ZhengMo Wuning - Patient-derived xenograft (PDX) models are crucial for tumor biology and therapeutic response evaluations. The metabolic, transcriptomic, and proteomic changes in PDX models derived from pancreatic ductal adenocarcinoma (PDAC) during serial passaging remain poorly understood. - Source: PubMed
Publication date: 2025/07/02
Guo PengfeiFang HaizongShi HanZhang JunrongSong GeFan ChongjiuQiu XinyuLin XianchaoWen ShiFeng JianghuaHuang HeguangTeng Tianhong