AIP _ ARA9 Antibody
- Known as:
- AIP _ ARA9 Antibody
- Catalog number:
- AF1040a
- Product Quantity:
- 0.1mg
- Category:
- -
- Supplier:
- Abgen
- Gene target:
- AIP _ ARA9 Antibody
Related genes to: AIP _ ARA9 Antibody
- Gene:
- AIP NIH gene
- Name:
- aryl hydrocarbon receptor interacting protein
- Previous symbol:
- -
- Synonyms:
- XAP2, ARA9, FKBP16
- Chromosome:
- 11q13.2
- Locus Type:
- gene with protein product
- Date approved:
- 1999-01-22
- Date modifiied:
- 2019-04-23
Related products to: AIP _ ARA9 Antibody
Related articles to: AIP _ ARA9 Antibody
- Central adiposity is a major determinant of cardiometabolic risk. However, routinely used composite lipid-glucose indices are often interpreted to indicate a uniform metabolic signal across individuals with different body fat distributions. This study examined whether the interpretive behavior of the atherogenic index of plasma (AIP) and the triglyceride-glucose (TyG) index varies with central adiposity and the evaluated three-variant triglyceride-weighted genetic risk score (wGRS) in Mexican adults. - Source: PubMed
Publication date: 2026/08/26
Hernández-Guerrero CésarTejeda-Miramontes José PMendivil Edgar JGarcía-Mena JaimeArenas ErikaRamírez-Saad HugoTeruel Graciela - Cognitive decline is a growing concern in the United States as the population ages. Risk scores such as the Cardiovascular Risk Factors Aging and Incidence of Dementia (CAIDE) have been validated to assess long-term risk for cognitive decline. The existing literature has primarily focused on biological risk factors; however, there is a growing emphasis on integrating psychological and social factors that may contribute to a greater risk of cognitive decline. - Source: PubMed
Publication date: 2026/08/26
Xavier Hall Casey DMeng ZhuoOkantey BethSabuncu CrimLane BrittanyRamirez Surmeier LadanyaSheffler JuliaOviedo Diana CWong Frank YBritton Gabrielle BMillender Eugenia - The atherogenic index of plasma (AIP), calculated as log(triglycerides/HDL-C), reflects atherogenic dyslipidemia and is associated with insulin resistance. Its continuous dose-response relationship and incremental predictive value for non-alcoholic fatty liver disease (NAFLD) beyond traditional risk factors remain undefined in community-dwelling older adults-a population with a high metabolic comorbidity burden where low-cost, integrated risk markers are urgently needed. - Source: PubMed
Publication date: 2026/08/26
Xiao MengyuanXiao ChengwenZhang JiayuJi YuchenZhuang JiayanChen YingqiYuan ZhihongChen Siying - This narrative review provides an update of the literature on autoimmune pancreatitis type 2 (AIP-2) and its relationship with inflammatory bowel disease (IBD) in adults. Due to the rarity of this condition, the literature on the topic is sparse. AIP-2 is a pancreas specific condition in contrast to autoimmune pancreatitis type 1, which is the pancreatic manifestation of immunoglobulin G4-related disease. AIP-2 has a strong association with IBD, especially ulcerative colitis. - Source: PubMed
Publication date: 2026/09/10
Ejsing J GJensen M DJørgensen M T - Tropical cyclones are among the most dangerous and costly weather phenomena, but forecasting them remains challenging. Here we introduce WeatherNext Cyclones (WN-C), an artificial intelligence (AI)-based operational weather model that produces state-of-the-art ensemble forecasts of the track, intensity and size of tropical cyclones worldwide. Trained on a combination of global analysis data and a global database of historical tropical cyclones, WN-C generates large ensembles of possible global weather and cyclone scenarios extending 15 days into the future. When evaluated on tropical cyclones from 2023 to 2025, the track, intensity and wind-radius predictions from WN-C offer an average lead-time advantage of 1 day or more over leading operational models-an improvement in accuracy comparable to the progress seen in the last decade of operational development. We achieved these results using inputs that are orders of magnitude coarser than regional models, suggesting that high resolution is not a strict prerequisite for state-of-the-art intensity forecasting and that these coarse atmospheric data contain more intensity signal than has been previously recognized. Including predictions from WN-C in a weighted-average consensus ensemble improves its skill substantially. The scalability of WN-C enables ensembles of up to 1,000 members, which are better at capturing rare events than conventional 50-member ensembles. By providing advanced operational ensemble guidance to human forecasters, this work represents a step change towards more reliable and timely forecasts and warnings that can help to protect lives and to mitigate the devastating effects of tropical cyclones. - Source: PubMed
Publication date: 2026/08/06
Alet FerranAndersson Tom RPrice IlanMarkou StratisEl-Kadi AndrewMasters DominicLi AmyMerchant SamierWilliams NatalieThornton GregoryMacKay KenGraham OliviaUddin AkibGaiarin BenShah DevajaKruse ElinorHogsett WallaceZelinsky DavidCangialosi JohnMartinez JonathanFranklin JamesDeMaria MarkMusgrave KateBain Caroline LTitley HelenStott JacklynnLam RemiBell AaronKomarek PaulWillson MatthewSanchez-Gonzalez AlvaroBattaglia Peter