ANILLIN _ Scraps (internal)
- Known as:
- ANILLIN _ Scraps (middlesequence)
- Catalog number:
- Y213562
- Product Quantity:
- 200ul
- Category:
- -
- Supplier:
- ABM
- Gene target:
- ANILLIN _ Scraps (internal)
Related genes to: ANILLIN _ Scraps (internal)
- Gene:
- ANLN NIH gene
- Name:
- anillin actin binding protein
- Previous symbol:
- -
- Synonyms:
- ANILLIN, Scraps, scra
- Chromosome:
- 7p14.2
- Locus Type:
- gene with protein product
- Date approved:
- 2001-01-03
- Date modifiied:
- 2016-10-05
Related products to: ANILLIN _ Scraps (internal)
(I) LightCycler 1. 0; (Internal Control can't be used for this system) ; (II) LightCycler2. 0; (III) PE5700, MJ_Opticon etc. single color systems; (IV) ABI7000, ABI7300, ABI7500, ABI7900, ABI StepO1.0ml Self-Standing Cryovial Internal Thread w/ O-Ring Seal1.2ml Cryogenic Vial,Self-Standing, Internal Thread1.2ml Self-Standing Cryovial Internal Thread w per O-Ring Seal1.2ml Self-Standing Cryovial Internal Thread w per Silicone Wa1.2ml Self-Standing Cryovial Internal Thread w per Washer Seal1.2ml Self-Standing Cryovial Internal Thread w/ O-Ring Seal1.2ml Self-Standing Cryovial Internal Thread w/ O-Ring Seal1.2ml Self-Standing Cryovial Internal Thread w/ Silicone Wa1.2ml Self-Standing Cryovial Internal Thread w/ Silicone Wa1.2ml Self-Standing Cryovial Internal Thread w/Washer Seal1.2ml Self-Standing Cryovial Internal Thread w/Washer Seal1.2ml Self-Standing Cryovial Internal Thread w_ O-Ring Seal1.2ml Self-Standing Cryovial Internal Thread w_ Silicone Wa1.5-times expansion model of ear dissection, external, middle & internal ear, 4 parts Related articles to: ANILLIN _ Scraps (internal)
- Lung cancer recurrence and metastasis are major causes of cancer-related mortality, but the molecular determinants underlying these processes remain incompletely understood. This study aimed to identify key regulators of lung cancer progression through integrative analyses of bulk and single-cell transcriptomic datasets. - Source: PubMed
Publication date: 2026/04/15
Quan HaiweiXu ZhiguangHuo LizhenWang Zhibin - Efficient separation of trivalent minor actinides from lanthanides remains a central challenge in advanced nuclear fuel cycle strategies. Here, we develop a machine-learning-guided ligand design framework to optimize intrinsic Am/Eu coordination discrimination under limited availability of experimental stability-constant data. A graph neural network model is trained via stepwise transfer learning and semi-supervised refinement to predict first-step metal-ligand stability constants (log) for phenanthroline-derived ligands. The predicted differential descriptor (Δlog) is embedded as a reward to guide constrained molecular generation using a scaffold-preserving generative model. The resulting framework maintains chemical validity and structural diversity while enriching candidate ligands with enhanced predicted intrinsic Am/Eu coordination preference relative to literature-reported references. This work demonstrates that coordination-chemistry-informed machine learning enables systematic exploration of ligand chemical space under data-scarce conditions and provides a practical computational screening route for candidate extractants targeting challenging An/Ln discrimination problems. - Source: PubMed
Publication date: 2026/04/30
Yang DongshengZhang ZhiyuanQue YulongWu YihuangYu TongxinJiang ShiyiLiu Chong - This study explores the transcriptomic, mutational, and immunogenic characteristics linked to significantly differentially expressed genes (DEGs) in colorectal (COAD), liver (LIHC), lung (LUAD), gastric (STAD), and breast (BRCA) cancers. Applying integrated bioinformatics algorithms, we discovered common upregulated and downregulated hub genes and assessed their prognostic importance, genomic modifications, copy number variations, functional enrichment, and pathway engagement. The persistent overexpression of ANLN and CTHRC1 in five cancer types, along with poor survival outcomes, underscores their suitability for multi-epitope vaccine development, emphasizing their antigenic potential and significance as universal therapeutic targets. Five genes-ABCA8, PDK4, MT1M, TMEM100, and LIFR-exhibited consistent downregulation and demonstrated tumor-suppressive characteristics. Genomic analyses demonstrated elevated mutation frequencies in ABCA8 and LIFR, predominantly C>T transitions that suggest age-related mutational signatures. Copy number alterations confirmed oncogenic amplifications (ANLN and CTHRC1) and tumor suppressor deletions (e.g., ABCA8). Functional enrichment associated differentially expressed genes with mitosis, chromosome segregation, and metabolic pathways. A multi-epitope vaccine targeting ANLN and CTHRC1 has been established leveraging predicted B-cell and T-cell epitopes, β-defensin as an adjuvant, and efficient linkers. Structural validation indicated desirable folding, stability, and solubility. The vaccine exhibited significant MHC binding, accomplishing 99% global population coverage, alongside strong immune simulation findings. Codon optimization and subsequent cloning into the pET28a(+) vector confirmed the preparation for bacterial expression. ANLN and CTHRC1 demonstrate significant targets for universal immunotherapy. The multi-epitope vaccine demonstrates significant efficacy in silico and has the potential to be widely employed as a cancer immunotherapeutic. - Source: PubMed
Publication date: 2026/04/19
Roy Suronjit KumarHasan RubaitBiswas Mohammad ShahangirPodder Munna KumarMoin Abu TayabPatil Rajesh B - Although there are several proteomic studies testing brain responses to glucocorticoids, there were no attempts to integrate these data and compare them with responses at the level of mRNAs. Furthermore, the utility of available data is compromised by changes in nomenclature and usage of different types of identifiers. Therefore, the aim of this study was to identify the most consistent changes in protein expression in standardized mouse, rat, and human datasets and compare them with transcriptomic responses to glucocorticoids. The analysis showed that the two most frequently and consistently detected proteins were ATP synthase F1 subunit beta (Atp5f1b) and aldolase, fructose-bisphosphate C (Aldoc), while the most consistent proteomic and transcriptomic findings included Aldoc, Plin4, Aqp4, Endod1, Glul, Anln, Aldh1l1, Parp1, Trf, Fermt2, Tmem63a, and Trim2. The study also revealed limitations of available proteomic data indicating significant gaps in knowledge. Finally, the study provides an integrated dataset with updated protein nomenclature and a complete set of major identifiers to facilitate usage of proteomic data. - Source: PubMed
Juszczak Grzegorz R - Non-small cell lung cancer (NSCLC) remains a major cause of cancer mortality. The Tumor Immune Dysfunction and Exclusion (TIDE) score is widely used to estimate immune-checkpoint blockade response, but its broader prognostic relevance in unselected NSCLC populations is unclear. This study aimed to determine whether TIDE-informed strata carry prognostic information beyond immunotherapy settings, and to develop and externally validate an immune gene expression-based prognostic signature derived from differentially expressed genes (DEGs) between these strata. - Source: PubMed
Publication date: 2026/02/26
Zhou JiaxuanLi NaLi ZimengChen JinmiaoDu YifeiLi XinchunWan Qi