SHEEP ANTI BENZOYLECGONINE
- Known as:
- SHEEP ANTI BENZOYLECGONINE
- Catalog number:
- ABS3160
- Product Quantity:
- 1 ml
- Category:
- Antibodies
- Supplier:
- AbD
- Gene target:
- SHEEP ANTI BENZOYLECGONINE
Related genes to: SHEEP ANTI BENZOYLECGONINE
- 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: SHEEP ANTI BENZOYLECGONINE
Alkaline Phosphatase Conjugated Affinity Purified anti-Swine IgG (H&L) [Goat] Secondary_Antibodies(endo,anti)_((rac,anti)-4-Deschloro-sertraline CAS: Formula: C17H18ClN(Tyr1)-Adipokinetic Hormone I, Rabbit anti-Locusta migratoria(Tyr1)-Adipokinetic Hormone I, Rabbit anti-Locusta migratoria, IF Kit(Tyr1)-Adipokinetic Hormone I, Rabbit anti-Locusta migratoria; IH(Tyr1)-Adipokinetic Hormone I, Rabbit anti-Locusta migratoria; RIA1 JAR WITH WIDE BOTTOM PLATE (ANTI-TILT)1 JAR WITH WIDE BOTTOM PLATE (ANTI-TILT)1-step Polymer HISTO-STAT; HRP anti Hamster (Secondary Reagent Component) for staining Hamster antibodies, 250 plus slides1-step Polymer HISTO-STAT; HRP anti Chicken (Secondary Reagent Component) for staining Chicken antibodies, 250 plus slides1-step Polymer HISTO-STAT; HRP anti Goat (Secondary Reagent Component) for staining Goat antibodies, 250 plus slides1-step Polymer HISTO-STAT; HRP anti Mouse Adsorbed (Secondary Reagent Component) for staining Rat antibody- on- Mouse tissues, 250 plus slides1-step Polymer HISTO-STAT; HRP anti Mouse Secondary Reagent Component) for staining Mouse and Rat antibodies, 250 plus slides1-step Polymer HISTO-STAT; HRP anti Rat (SecondaryReagent Component) for staining Rat antibodies, 250 plus slides Related articles to: SHEEP ANTI BENZOYLECGONINE
- Liver cancer ranks sixth in incidence and third in mortality globally and hepatocellular carcinoma (HCC) accounts for 90% of it. Hypoxia, glycolysis, and lactate metabolism have been found to regulate the progression of HCC separately. However, there is a lack of studies linking the above three to predict the prognosis of HCC. The present study aimed to identify a hypoxia-glycolysis-lactate-related gene signature for assessing the prognosis of HCC. - Source: PubMed
Publication date: 2024/04/16
Qin XiaodanSun HuilingHu ShangshangPan YuqinWang Shukui - Pulmonary arterial hypertension (PAH) is a devastating chronic cardiopulmonary disease without an effective therapeutic approach. The underlying molecular mechanism of PAH remains largely unexplored at single-cell resolution. - Source: PubMed
Publication date: 2023/12/18
Qin YuhanYan GaoliangQiao YongWang DongTang Chengchun - Eukaryotic ribosome assembly is a highly orchestrated process that involves over two hundred protein factors. After early assembly events on nascent rRNA in the nucleolus, pre-60S particles undergo continuous maturation steps in the nucleoplasm, and prepare for nuclear export. Here, we report eleven cryo-EM structures of the nuclear pre-60S particles isolated from human cells through epitope-tagged GNL2, at resolutions of 2.8-4.3 Å. These high-resolution snapshots provide fine details for several major structural remodeling events at a virtual temporal resolution. Two new human nuclear factors, L10K and C11orf98, were also identified. Comparative structural analyses reveal that many assembly factors act as successive place holders to control the timing of factor association/dissociation events. They display multi-phasic binding properties for different domains and generate complex binding inter-dependencies as a means to guide the rRNA maturation process towards its mature conformation. Overall, our data reveal that nuclear assembly of human pre-60S particles is generally hierarchical with short branch pathways, and a few factors display specific roles as rRNA chaperones by confining rRNA helices locally to facilitate their folding, such as the C-terminal domain of SDAD1. - Source: PubMed
Publication date: 2023/07/25
Zhang YunyangLiang XiaomengLuo ShaChen YanLi YuMa ChengyingLi NingningGao Ning - Sarcopenia is a geriatric disease associated with increased mortality and disability. Early diagnosis and intervention are required to prevent it. This study investigated biomarkers for sarcopenia by using a combination of comprehensive clinical data and messenger RNA-sequencing (RNA-seq) analysis obtained from peripheral blood mononuclear cells. We enrolled a total of 114 older adults aged 66-94 years (52 sarcopenia diagnosed according to the Asian Working Group for Sarcopenia 2019 consensus and 62 normal older people). We used clinical data which were not included diagnosis criteria of sarcopenia, and stride length showed significance by logistic regression analysis (Bonferroni corrected p = .012, odds ratio = 0.14, 95% confidence interval [CI]: 0.05-0.40). RNA-seq analysis detected 6 differential expressed genes (FAR1, GNL2, HERC5, MRPL47, NUBP2, and S100A11). We also performed gene-set enrichment analysis and detected 2 functional modules (ie, hub genes, MYH9, and FLNA). By using any combination of the 9 candidates and basic information (age and sex), risk-prediction models were constructed. The best model by using a combination of stride length, HERC5, S100A11, and FLNA, achieved a high area under the curve (AUC) of 0.91 in a validation cohort (95% CI: 0.78-0.95). The quantitative PCR results of the 3 genes were consistent with the trend observed in the RNA-seq results. When BMI was added, the model achieved a high AUC of 0.95 (95% CI: 0.84-0.99). We have discovered potential biomarkers for the diagnosis of sarcopenia. Further refinement may lead to their future practical use in clinical use. - Source: PubMed
Furutani MotokiSuganuma MutsumiAkiyama ShintaroMitsumori RisaTakemura MarieMatsui YasumotoSatake ShosukeNakano YukikoNiida ShumpeiOzaki KouichiHosoyama TohruShigemizu Daichi - This study aims to investigate the differences in the epigenomic patterns of N6-methyladenosine (m6A) methylation in gingival tissues between patients with periodontitis (PD) and healthy controls, identifying potential biomarkers. - Source: PubMed
Publication date: 2023/03/20
Wang ZhenxiangChen HangPeng LiminHe YujuanWei JingjingZhang Xiaonan