Beyond the gut: Systemic levels of short-chain fatty acids are altered in patients with heart failure.

Background & Aim: The gut microbiome produces short-chain fatty acids (SCFAs), which serve as a substantial energy source and provide a link between the microbiome and (cardiac) metabolism. It has been demonstrated that the composition of the microbiome is altered in patients with heart failure (HF), but whether circulating levels of SCFAs are altered in HF is unknown.

Methods & Results: Serum concentrations of the SCFAs acetate, propionate, and butyrate were measured in 205 patients with HF and in 54 healthy controls, using isotope dilution liquid chromatography-tandem mass spectrometry.

Associations between body composition, metabolic mediators and osteoarthritis in cats.

Background: Osteoarthritis (OA) is a common, age-related joint disease in cats. The common finding of bilateral symmetric joint involvement may suggest influence from systemic factors, and could imply that body parameters such as excess body fat and cat size are important for OA development. We aimed to investigate associations between body composition and whole-body OA scores in 72 cats, using whole-body computed tomography (CT), and if serum concentrations of the metabolic mediators leptin, adiponectin and insulin-like growth factor-1 (IGF-1) reflected the total OA load.

Digital twin systems for musculoskeletal applications: A current concepts review.

Digital twin (DT) systems, which involve creating virtual replicas of physical objects or systems, have the potential to transform healthcare by offering personalised and predictive models that grant deeper insight into a patient's condition. This review explores current concepts in DT systems for musculoskeletal (MSK) applications through an overview of the key components, technologies, clinical uses, challenges, and future directions that define this rapidly growing field. DT systems leverage computational models such as multibody dynamics and finite element analysis to simulate the mechanical behaviour of MSK structures, while integration with wearable technologies allows real-time monitoring and feedback, facilitating preventive measures, and adaptive care strategies.

Association between the use of daily injury risk estimation feedback (I-REF) based on machine learning techniques and injuries in athletics (track and field): results of a prospective cohort study over an athletics season.

Objective: To analyse the association between the level of use of injury risk estimation feedback (I-REF) provided to athletes and the injury burden during an athletics season.

Method: We conducted a prospective cohort study over a 38-week follow-up period on athletes competing at the French Federation of Athletics. Athletes completed daily questionnaires on their athletics activity, psychological state, sleep, self-reported level of I-REF use, and injuries.

Boosting any learning algorithm with Statistically Enhanced Learning.

Feature engineering is of critical importance in the field of Data Science. While any data scientist knows the importance of rigorously preparing data to obtain good performing models, only scarce literature formalizes its benefits. In this work, we present the method of Statistically Enhanced Learning (SEL), a formalization framework of existing feature engineering and extraction tasks in Machine Learning (ML).