Prevention

A multi-strain probiotic administered via drinking water enhances feed conversion efficiency and meat quality traits in indigenous chickens.

Whereas the use of probiotics is commonplace in commercial production of improved chicken strains, little is known about the impact of these live microbial feed additives in indigenous chickens in South Africa. This study investigated the effect of a multi-strain probiotic (containing , , and total bacteria number was 1.4 × 10 cfu/mL), administered via drinking water, on growth performance, bloo...

Afferent Input Induced by Rhythmic Limb Movement Modulates Spinal Neuronal Circuits in an Innovative Robotic In Vitro Preparation.

Locomotor patterns are mainly modulated by afferent feedback, but its actual contribution to spinal network activity during continuous passive limb training is still unexplored. To unveil this issue, we devised a robotic in vitro setup (Bipedal Induced Kinetic Exercise, BIKE) to induce passive pedaling, while simultaneously recording low-noise ventral and dorsal root (VR and DR) potentials in isol...

Social and nutritional factors shape larval aggregation, foraging, and body mass in a polyphagous fly.

The majority of insect species have a clearly defined larval stage during development. Larval nutrition is crucial for individuals' growth and develop...

Deep learning-based quantification of abdominal fat on magnetic resonance images.

Obesity is increasingly prevalent and associated with increased risk of developing type 2 diabetes, cardiovascular diseases, and cancer. Magnetic reso...

Classifier Personalization for Activity Recognition Using Wrist Accelerometers.

Intersubject variability in accelerometer-based activity recognition may significantly affect classification accuracy, limiting a reliable extension o...

Wearable Sensor Data to Track Subject-Specific Movement Patterns Related to Clinical Outcomes Using a Machine Learning Approach.

Wearable sensors can provide detailed information on human movement but the clinical impact of this information remains limited. We propose a machine ...

Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms.

Inflammation, oxidative stress, myocardial injury biomarkers and clinical parameters (longer AF duration, left atrial enlargement, the metabolic syndr...

Designing robot-assisted neurorehabilitation strategies for people with both HIV and stroke.

There is increasing evidence that HIV is an independent risk factor for stroke, resulting in an emerging population of people living with both HIV and...

Twelve weeks of supervised exercise improves self-reported symptom burden and fatigue in chronic kidney disease: a secondary analysis of the 'ExTra CKD' trial.

BACKGROUND: Chronic kidney disease (CKD) patients experience a high symptom burden including fatigue, sleep difficulties, muscle weakness and pain. Th...

Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms.

BACKGROUND: The risk factors of diabetic retinopathy (DR) were investigated extensively in the past studies, but it remains unknown which risk factors...

A step towards intelligent EBSD microscopy: machine-learning prediction of twin activity in MgAZ31.

UNLABELLED: Although microscopy is often treated as a quasi-static exercise for obtaining a snapshot of events and structure, it is clear that a more ...

Cardiac Phase Space Tomography: A novel method of assessing coronary artery disease utilizing machine learning.

BACKGROUND: Artificial intelligence (AI) techniques are increasingly applied to cardiovascular (CV) medicine in arenas ranging from genomics to cardia...

Use of Deep Learning to Examine the Association of the Built Environment With Prevalence of Neighborhood Adult Obesity.

IMPORTANCE: More than one-third of the adult population in the United States is obese. Obesity has been linked to factors such as genetics, diet, phys...

Incorporating Unannounced Meals and Exercise in Adaptive Learning of Personalized Models for Multivariable Artificial Pancreas Systems.

BACKGROUND: Despite the recent advancements in the modeling of glycemic dynamics for type 1 diabetes mellitus, automatically considering unannounced m...

Behavioral Modeling in Weight Loss Interventions.

Designing systems with human agents is difficult because it often requires models that characterize agents' responses to changes in the system's state...

Shoulder physiotherapy exercise recognition: machine learning the inertial signals from a smartwatch.

OBJECTIVE: Participation in a physical therapy program is considered one of the greatest predictors of successful conservative management of common sh...

Machine learning algorithm-based risk prediction model of coronary artery disease.

In view of high mortality associated with coronary artery disease (CAD), development of an early predicting tool will be beneficial in reducing the bu...

Pump Speed Optimization in Patients Implanted With the HeartMate 3 Device.

BACKGROUND: Pump speed optimization in patients implanted with a ventricular assist device represents a major challenge during the follow-up period. W...

Detraining effects of regular Tai Chi exercise on postural control ability in older women: A randomized controlled trial.

BACKGROUND/OBJECTIVE: This study aimed to investigate the training and detraining effects of Tai Chi (TC) on postural control ability in single leg st...

A comparison of statistical and machine-learning techniques in evaluating the association between dietary patterns and 10-year cardiometabolic risk (2002-2012): the ATTICA study.

Statistical methods are usually applied in examining diet-disease associations, whereas factor analysis is commonly used for dietary pattern recogniti...