Designing a multi-epitope vaccine candidate against human rhinovirus C utilizing immunoinformatics approach.

Human rhinovirus C (HRV-C) is a significant contributor to respiratory tract infections in children and is implicated in asthma exacerbations across all age groups. Despite its impact, there is currently no licensed vaccine available for HRV-C. Here, we present a novel approach to address this gap by employing immunoinformatics techniques for the design of a multi-epitope-based vaccine against HRV-C.

Benchmarking the most popular XAI used for explaining clinical predictive models: Untrustworthy but could be useful.

Objective: This study aimed to assess the practicality and trustworthiness of explainable artificial intelligence (XAI) methods used for explaining clinical predictive models.

Methods: Two popular XAIs used for explaining clinical predictive models were evaluated based on their ability to generate domain-appropriate representations, impact clinical workflow, and consistency. Explanations were benchmarked against true clinical deterioration triggers recorded in the data system and agreement was quantified.

Genome-wide association studies of milk composition traits in indicine Badri cattle using ddRAD sequencing approach.

Genome-wide association studies (GWAS) offer potential for discovering genomic regions that can be exploited to increase milk production. However, available GWAS and single nucleotide polymorphism (SNP) datasets are heavily skewed towards taurine breeds, which restricts their utility for genomic research in indicine cattle breeds. This study conducts a GWAS on the Badri breed of Indicine cattle to estimate variance components and identify significant variants associated with milk composition traits, utilizing double digest restriction-site associated DNA (ddRAD) sequencing data.