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.

Smartphone-Based Assessment of Mobility and Manual Dexterity in Adult People with Spinal Muscular Atrophy.

Background: More responsive, reliable, and clinically valid endpoints of disability are essential to reduce size, duration, and burden of clinical trials in adult persons with spinal muscular atrophy (aPwSMA).

Objective: The aim is to investigate the feasibility of smartphone-based assessments in aPwSMA and provide evidence on the reliability and construct validity of sensor-derived measures (SDMs) of mobility and manual dexterity collected remotely in aPwSMA.

Methods: Data were collected from 59 aPwSMA (23 walkers, 20 sitters and 16 non-sitters) and 30 age-matched healthy controls (HC).

Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study.

Background: Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing.

Automatic segmentation of lower limb muscles from MR images of post-menopausal women based on deep learning and data augmentation.

Individual muscle segmentation is the process of partitioning medical images into regions representing each muscle. It can be used to isolate spatially structured quantitative muscle characteristics, such as volume, geometry, and the level of fat infiltration. These features are pivotal to measuring the state of muscle functional health and in tracking the response of the body to musculoskeletal and neuromusculoskeletal disorders.

Sex dimorphism controls dysbindin-related cognitive dysfunctions in mice and humans with the contribution of COMT.

Cognitive dysfunctions are core-enduring symptoms of schizophrenia, with important sex-related differences. Genetic variants of the DTBPN1 gene associated with reduced dysbindin-1 protein (Dys) expression negatively impact cognitive functions in schizophrenia through a functional epistatic interaction with Catechol-O-methyltransferase (COMT). Dys is involved in the trafficking of dopaminergic receptors, crucial for prefrontal cortex (PFC) signaling regulation.

Clinical Significance of the Cystic Phenotype in Alport Syndrome.

Rationale & Objective: Alport syndrome (AS) is the most common genetic glomerular disease caused by mutations that affect type IV collagen. However, the clinical characteristics and significance of AS with kidney cysts are not well defined. This study investigated the prevalence and clinical significance of cystic kidney phenotype in AS.

Monoallelic pathogenic variants are a common cause of autosomal dominant polycystic kidney disease-spectrum phenotype.

Background: Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disorder, characterized by development and enlargement of kidney cysts, eventually leading to end-stage kidney disease (ESKD). Pathogenic variants in the and genes are the major cause of ADPKD; additional rare variants in the and genes have been found in a minority of ADPKD patients. More recently, a significant number of ADPKD families have been linked to monoallelic variants in the gene.

Social network characteristics and well-being in Italy: insights from the PHRASI Study.

Background: Mental well-being should be prioritized in public health as it represents a valuable resource for individuals and communities, influencing behavior, social cohesion and social inclusion. The support individuals receive from their social networks can have a significant impact on mental well-being. This study used data from the Public Health Residents' Anonymous Survey in Italy, a nationwide cross-sectional survey.

Work-Related Stress Questionnaire: confirmatory factor analysis for construct validation by the PHRASI study.

Objective: The purpose of this study is to validate the 13-item version of the Work-Related Stress Questionnaire (WRSQ) on a representative sample of Italian public health residents.

Materials And Methods: The WRSQ was administered as part of the Public Health Residents' Anonymous Survey in Italy (PHRASI) from 14 June to 26 July 2022. Collinearity between each questionnaire item was assessed with Kendall's τ statistic.

Digital Mobility Measures: A Window into Real-World Severity and Progression of Parkinson's Disease.

Background: Real-world monitoring using wearable sensors has enormous potential for assessing disease severity and symptoms among persons with Parkinson's disease (PD). Many distinct features can be extracted, reflecting multiple mobility domains. However, it is unclear which digital measures are related to PD severity and are sensitive to disease progression.

Social Network Characteristics and Depressive Symptoms of Italian Public Health Medical Residents: The Public Health Residents' Anonymous Survey in Italy (PHRASI).

Despite the high impact of the COVID-19 pandemic on social interactions and healthcare workers' (HWs') mental health, few studies have investigated the association between social network characteristics and HWs' mental health, particularly during the pandemic. Therefore, we aimed to assess the associations between public health residents' (PHRs') social network characteristics and depression. We used data from the Public Health Residents' Anonymous Survey in Italy (PHRASI), a nationwide cross-sectional study.

Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases.

Introduction: The clinical assessment of mobility, and walking specifically, is still mainly based on functional tests that lack ecological validity. Thanks to inertial measurement units (IMUs), gait analysis is shifting to unsupervised monitoring in naturalistic and unconstrained settings. However, the extraction of clinically relevant gait parameters from IMU data often depends on heuristics-based algorithms that rely on empirically determined thresholds.

Laboratory and free-living gait performance in adults with COPD and healthy controls.

Background: Gait characteristics are important risk factors for falls, hospitalisations and mortality in older adults, but the impact of COPD on gait performance remains unclear. We aimed to identify differences in gait characteristics between adults with COPD and healthy age-matched controls during 1) laboratory tests that included complex movements and obstacles, 2) simulated daily-life activities (supervised) and 3) free-living daily-life activities (unsupervised).

Methods: This case-control study used a multi-sensor wearable system (INDIP) to obtain seven gait characteristics for each walking bout performed by adults with mild-to-severe COPD (n=17; forced expiratory volume in 1 s 57±19% predicted) and controls (n=20) during laboratory tests, and during simulated and free-living daily-life activities.

On Gait Consistency Quantification Through ARX Residual Modeling and Kernel Two-Sample Testing.

Objective: The quantification of the way an individual walks is key to the understanding of diseases affecting the neuromuscular system. More specifically, to improve diagnostics and treatment plans, there is a continuous interest in quantifying gait consistency, allowing clinicians to distinguish natural variability of the gait patterns from disease progression or treatment effects. To this end, the current article presents a novel objective method for assessing the consistency of an individual's gait, consisting of two major components.

Surf therapy for improving child and adolescent mental health: A pilot randomised control trial.

The aim of this pilot randomised control trial (RCT) was to test, 1) feasibility and acceptability of a surf therapy program to improve symptoms of mental ill-health among children and adolescents, and 2) the design and procedures of an evaluative study. This pilot RCT compared a 6-week mentor-supported surf therapy program with a wait list control group, in Australian children and adolescents aged 8-18yrs (M age = 11.28, SD = 2.

The ecological validity of the IOP-29: A follow-up study using the MMPI-2-RF and the SIMS as criterion variables.

Current guidelines for conducting symptom validity assessments require that professionals administer multiple symptom validity tests (SVTs) and that the SVTs selected for their evaluations provide nonredundant information. However, not many SVTs are currently available, and most of them rely on the same, (in)frequency-based, feigning detection strategy. In this context, the Inventory of Problems (IOP-29) could be a valuable addition to the assessor's toolbox because of its brevity (29 items) and its different approach to assessing the credibility of presented symptoms.

Regulated bacterial interaction networks: A mathematical framework to describe competitive growth under inclusion of metabolite cross-feeding.

When bacterial species with the same resource preferences share the same growth environment, it is commonly believed that direct competition will arise. A large variety of competition and more general 'interaction' models have been formulated, but what is currently lacking are models that link monoculture growth kinetics and community growth under inclusion of emerging biological interactions, such as metabolite cross-feeding. In order to understand and mathematically describe the nature of potential cross-feeding interactions, we design experiments where two bacterial species Pseudomonas putida and Pseudomonas veronii grow in liquid medium either in mono- or as co-culture in a resource-limited environment.

A Single-Sensor Approach to Quantify Gait in Patients with Hereditary Spastic Paraplegia.

Hereditary spastic paraplegia (HSP) is characterised by progressive lower-limb spasticity and weakness resulting in ambulation difficulties. During clinical practice, walking is observed and/or assessed by timed 10-metre walk tests; time, feasibility, and methodological reliability are barriers to detailed characterisation of patients' walking abilities when instrumenting this test. Wearable sensors have the potential to overcome such drawbacks once a validated approach is available for patients with HSP.

Complexity of spatio-temporal plantar pressure patterns during everyday behaviours.

The human foot sole is the primary interface with the external world during balance and walking, and also provides important tactile information on the state of contact. However, prior studies on plantar pressure have focused mostly on summary metrics such as overall force or centre of pressure under limited conditions. Here, we recorded spatio-temporal plantar pressure patterns with high spatial resolution while participants completed a wide range of daily activities, including balancing, locomotion and jumping tasks.