Exploring the application of machine learning to identify the correlations between phthalate esters and disease: enhancing nursing assessments.

Background: Health risks associated with phthalate esters depend on exposure level, individual sensitivities, and other contributing factors.

Purpose: This study employed artificial intelligence algorithms while applying data mining techniques to identify correlations between phthalate esters [di(2-ethylhexyl) phthalate, DEHP], lifestyle factors, and disease outcomes.

Methods: We conducted exploratory analysis using demographic and laboratory data collected from the Taiwan Biobank.

Identification of a new type of haematopoietic progenitor kinase-interacting protein (HIP-55) in Aedes aegypti mosquito haemocytes and its involvement in immunity-like functions in mosquito: a molecular study.

In this study, we characterize the HIP-55 protein in the mosquito Aedes aegypti for the first time. HIP-55 is a 55-kDa HPK1-interacting protein that is also called SH3P7. HIP-55 constitutively binds HPK1 'via' an HPK1 proline-rich motif 2(PR2) through its C-terminal SH3 domain.