Inferring bacterial interspecific interactions from microcolony growth expansion.

Bacterial species interactions significantly shape growth and behavior in communities, determining the emergence of community functions. Typically, these interactions are studied through bulk population measurements, overlooking the role of cell-to-cell variability and spatial context. This study uses real-time surface growth measurements of thousands of sparsely positioned microcolonies to investigate interactions and kinetic variations in monocultures and cocultures of and under substrate competition (succinate) or substrate independence (d-mannitol and putrescine).

Sensor-Derived Measures of Motor and Cognitive Functions in People With Multiple Sclerosis Using Unsupervised Smartphone-Based Assessments: Proof-of-Concept Study.

Background: Smartphones and wearables are revolutionizing the assessment of cognitive and motor function in neurological disorders, allowing for objective, frequent, and remote data collection. However, these assessments typically provide a plethora of sensor-derived measures (SDMs), and selecting the most suitable measure for a given context of use is a challenging, often overlooked problem.

Objective: This analysis aims to develop and apply an SDM selection framework, including automated data quality checks and the evaluation of statistical properties, to identify robust SDMs that describe the cognitive and motor function of people with multiple sclerosis (MS).

Identification of Psychological Treatment Dropout Predictors Using Machine Learning Models on Italian Patients Living with Overweight and Obesity Ineligible for Bariatric Surgery.

According to the main international guidelines, patients with obesity and psychiatric/psychological disorders who cannot be addressed to surgery are recommended to follow a nutritional approach and a psychological treatment. A total of 94 patients (T0) completed a battery of self-report measures: Symptom Checklist-90-Revised (SCL-90-R), Barratt Impulsiveness Scale-11 (BIS-11), Binge-Eating Scale (BES), Obesity-Related Well-Being Questionnaire-97 (ORWELL-97), and Minnesota Multiphasic Personality Inventory-2 (MMPI-2). Then, twelve sessions of a brief psychodynamic psychotherapy were delivered, which was followed by the participants completing the follow-up evaluation (T1).

DISPEL: A Python Framework for Developing Measures From Digital Health Technologies.

: This paper introduces DISPEL, a Python framework to facilitate development of sensor-derived measures (SDMs) from data collected with digital health technologies in the context of therapeutic development for neurodegenerative diseases. : Modularity, integrability and flexibility were achieved adopting an object-oriented architecture for data modelling and SDM extraction, which also allowed standardizing SDM generation, naming, storage, and documentation. Additionally, a functionality was designed to implement systematic flagging of missing data and unexpected user behaviors, both frequent in unsupervised monitoring.