Evaluation of plant commercial feed additives for equine cyathostomin control.

The increasing emergence of anthelmintic-resistant parasitic isolates prompts us to reassess the management of intestinal strongylosis in horses. Additionally, societal demand is shifting toward reducing the use of chemical treatments, aligning with environmentally-friendly practices and the exploration of natural alternatives. In this context, we provide an initial view of the antiparasitic activity and the effect on immune circulating blood cells of three commercialized plant-based feed additives in ponies.

Kidney Volume and Risk of Incident Kidney Outcomes.

Background: Low total kidney volume (TKV) is a risk factor for chronic kidney disease (CKD). However, evaluations of nonlinear relationships, incident events, causal inference, and prognostic utility beyond traditional biomarkers are lacking.

Methods: TKV, height-adjusted TKV, and body surface area-adjusted TKV (BSA-TKV) of 34,595 White British ancestry participants were derived from the UK Biobank.

Immunogenicity and safety in rabbits of a Clostridioides difficile vaccine combining novel toxoids and a novel adjuvant.

Clostridioides difficile infection (CDI) is a serious healthcare-associated disease, causing symptoms such as diarrhea and pseudomembranous colitis. The major virulence factors responsible for the disease symptoms are two secreted cytotoxic proteins, TcdA and TcdB. A parenteral vaccine based on formaldehyde-inactivated TcdA and TcdB supplemented with alum adjuvant, has previously been investigated in humans but resulted in an insufficient immune response.

Predicting odor profile of food from its chemical composition: Towards an approach based on artificial intelligence and flavorists expertise.

Odor is central to food quality. Still, a major challenge is to understand how the odorants present in a given food contribute to its specific odor profile, and how to predict this olfactory outcome from the chemical composition. In this proof-of-concept study, we seek to develop an integrative model that combines expert knowledge, fuzzy logic, and machine learning to predict the quantitative odor description of complex mixtures of odorants.