Patient clusters based on demographics, clinical characteristics and cancer-related symptoms: A cross-sectional pilot study.

Purpose: This study aimed to identify and preliminary validate distinct clusters of patients with cancer based on demographics, clinical characteristics, and symptoms and to inform future research on sample size requirements for achieving sufficient power in clustering analyses.

Methods: This cross-sectional pilot study involved 114 patients with cancer from two hospitals in northern Italy. Data were collected on demographics, clinical characteristics, and 20 symptoms using the Edmonton Symptom Assessment System in October 2022.

Experiences and perspectives of patients undergoing colorectal cancer surgery: A qualitative study.

Purpose: This study aimed to explore the experiences of patients with colorectal cancer undergoing surgical treatment, capturing their perspectives from diagnosis through to post-discharge recovery.

Methods: A qualitative methodology was adopted, utilising semi-structured virtual interviews with ten patients recruited from a specialist colorectal clinic. Interviews were transcribed verbatim, and data analysed by the process of inductive thematic analysis, using interpretive description.

The chiral 5,6-cyclohexane-fused uracil ring-system: A molecular platform with promising activity against SARS-CoV-2.

The recurrent global exposure to highly challenging viral epidemics, and the still limited spectrum of effective pharmacological options step on the accelerator towards the development of new antiviral medicines. In this work we explored the anti-SARS-CoV-2 potential of a recently launched chiral ring system based on the uracil scaffold fused to carbocycle rings. The asymmetric synthesis of two generations of chiral uracil-based compounds (overall 31 different products), and their in vitro cytotoxicity and antiviral screening against wild-type SARS-CoV-2 in U87.

Optimal oesophagogastric anastomosis techniques for oesophageal cancer surgery - A systematic review and network meta-analysis of randomised clinical trials.

Background: The optimal oesophagogastric anastomosis technique for oesophageal cancer surgery remains unclear. The aim of this study was to perform a network meta-analysis (NMA) of randomised clinical trials (RCTs) to compare oesophagogastric anastomosis techniques for oesophageal cancer surgery.

Methods: A systematic review and NMA were performed as per the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines-NMA extension.

The relationship between trajectories of intrinsic capacity and differences in the risk of functional ability decline in community-dwelling older adults: A socio-ecological approach.

Background: Functional ability (FA), a key determinant of healthy aging, is determined by intrinsic capacity (IC), environmental factors, and their interactions. IC is a composite of physical and mental capacities that undergo constant change. Therefore, understanding the factors that influence IC requires a multi-level analysis of individuals to optimize its trajectory.

Dyadic adjustment of persons with albinism and their significant other: A Bayesian mediation model of the Actor-Partner Interdependence (APIMeM).

Background: Limited standardized empirical research exists in France on the psychosocial implications of albinism, prompting an investigation into how affected persons adapt to their disabilities. Recent advancements in health psychology have led researchers to adopt a systemic approach, considering disabilities and involving close relatives in the adaptation process. The aim of this study was to explore the mediating role of dyadic coping within family dyads, where one is a person with albinism (PWA) and the other is a close relative.

Sick of debt: How over-indebtedness is hampering health in rural Cambodia.

This paper evidences how many rural poor Cambodians are sick of debt. Based on original, mixed-method data (2020-2022), exploring credit provisioning in this context, the aim of this paper is to illuminate some of the conditions leading to rural Cambodians taking on debt to bolster their health, and the effects this is having on borrowers' physical, psychological, emotional and social health. Specifically, we show how the health of our participants is constrained by a range of major illnesses that many suffer from and their poor food conditions, both exacerbated by the effects of climate change.

Crisis management in the operating room: A systematic review of simulation training to develop non-technical skills.

Aims: Crises in the operating room, often resulting from human factors, endangers patient safety. Simulation-based training to develop non-technical skills shows promise in managing these crises. This review examines the simulation techniques, targeted healthcare professionals, non-technical skills, crisis scenarios, and evaluation metrics used in operating room crisis management training.

Risk factors of anxiety, depression, stress, job burnout, and characteristics of sleep disorders in critical care nurses: An observational study.

Aim/objective: The aim of this study was to determine risk factors and associations between anxiety, depression, stress, and job burnout and describe sleep disorders in critical care nurses.

Setting: Data were collected in six intensive care units.

Methods: A descriptive cross-sectional design was used.

Biomechanical mechanisms for modulating stride frequency in walking.

Humans typically choose to walk at a self-selected stride frequency that minimizes their metabolic cost. However, when environmental constraints are present (e.g.

Reliability, validity and practicability of the Chelsea Critical Care Physical Assessment tool (CPAx) following an e-learning programme: A clinimetric study.

Objectives: To investigate inter- and intra-rater reliability, content and concurrent validity, and practicability of the Chelsea Critical Care Physical Assessment tool (CPAx) - a measurement instrument for physical function and activity for patients with a critical illness - from multidisciplinary, German-speaking healthcare professionals.

Methods: This was a prospective, longitudinal, clinimetric study. Participants who completed a novel German CPAx e-learning were invited to participate in a voluntary, web-based, piloted, two-round survey.

Advancing newborn care: Precise time of birth detection using ai-driven thermal imaging with adaptive normalization.

Around 5%-10% of newborns need assistance to start breathing. Currently, there is a lack of evidence-based research, objective data collection, and opportunities for learning from real newborn resuscitation emergency events. Generating and evaluating automated newborn resuscitation algorithm activity timelines relative to the Time of Birth (ToB) offers a promising opportunity to enhance newborn care practices.

Deep learning image registration for cardiac motion estimation in adult and fetal echocardiography via a focus on anatomic plausibility and texture quality of warped image.

Temporal echocardiography image registration is important for cardiac motion estimation, myocardial strain assessments, and stroke volume quantifications. Deep learning image registration (DLIR) is a promising way to achieve consistent and accurate registration results with low computational time. DLIR seeks the image deformation that enables the moving image to be warped to match the fixed image.

ExPDrug: Integration of an interpretable neural network and knowledge graph for pathway-based drug repurposing.

Precision medicine aims to provide personalized therapies by analyzing patient molecular profiles, often focusing on gene expression data. However, effectively linking these data to actionable drug discovery for clinical application remains challenging. In this paper, we introduce ExPDrug, a neural network (NN) model that integrates biological pathways from transcriptomic data with a biomedical knowledge graph to facilitate pathway-based drug repurposing.

Prospective trial of the Oncobox platform RNA sequencing bioinformatic analysis for personalized prescription of targeted drugs.

Interrogating gene expression in tumor can identify up- and downregulated molecular targets of cancer drugs. Here we report the results of prospective clinical investigation of using RNA sequencing analysis for personalized cancer therapy. Transcriptomic profiles were analyzed using Oncobox platform that identifies altered expression of drug target genes and molecular pathways and builds a personalized rating of targeted therapeutics.

Paediatric traumatic brain injuries: A descriptive analysis of incidence, visits, cause, and admission rates in Iceland from 2010 to 2021.

Background: Traumatic brain injuries (TBI) are common in emergency departments (ED) and may cause long-term negative outcomes but knowledge on how the first assessment of children with TBI may predict outcomes is lacking. This study aimed to expand the knowledge by describing the incidence, visits, causes, and outcomes of TBI in children in Iceland.

Methods: A retrospective descriptive data analysis was conducted on electronic medical records of children aged 0-17 that visited Landspitali EDs due to a traumatic head injury in 2010-2021.

A systematic review on suction-based airway clearance devices for foreign body airway obstruction.

Objective: The objective of this systematic review is to comprehensively evaluate the effectiveness and safety of negative pressure, anti-choking devices (ACDs) in managing severe foreign body airway obstructions (FBAO) compared to traditional techniques such as the Heimlich maneuver.

Methods: A comprehensive literature search was conducted in major databases to identify studies published within the past five years. Eligible studies were appraised for quality using the Critical Appraisal and Data Extraction Tool.

Demonstrating performance in scaled-up production and quality control of polyhydroxyalkanoates using municipal waste activated sludge.

Significant progress has been made over the past decade with pilot scale polyhydroxyalkanoate (PHA) production by direct accumulation using municipal waste activated sludge (WAS). However, industrial upscaling experiences are still lacking in the research literature. In this study, a demonstration scale (4 m) PHA production process was operated using industrially relevant equipment and compared favourably to those from parallel pilot scale (200 L) production runs.

Effect of postpartum oral furosemide use on postpartum readmissions and blood pressure trends.

Background: Oral furosemide postpartum improves the time to hypertension resolution in randomized control trials. Further investigation is needed to determine the impact of furosemide in routine clinical practice.

Objective: Real world study to assess impact of furosemide on rates of postpartum hypertension and readmissions for patients with hypertensive disorders of pregnancy.

Effects of microplastics on energy accumulation in a migratory shorebird in the coastal wetlands of the Yellow Sea, China.

Microplastic pollution has emerged as a significant environmental concern at the global level, potentially threatening biodiversity conservation and human wellbeing. As an important biological group with a wide global distribution, migratory shorebirds face considerable stress due to plastic and microplastic pollution. However, few studies have explored the ecotoxic impact of microplastic pollution on migratory shorebirds.

Hip prosthesis failure prediction through radiological deep sequence learning.

Background: Existing deep learning studies for the automated detection of hip prosthesis failure only consider the last available radiographic image. However, using longitudinal data is thought to improve the prediction, by combining temporal and spatial components. The aim of this study is to develop artificial intelligence models for predicting hip implant failure from multiple subsequent plain radiographs.

Optimal placement of ambulance stations using data-driven direct and surrogate search methods.

Objective: In this paper, we implement and validate a set of optimization approaches that were applied on ambulance data from the Västerbotten county in Sweden collected 2018, with the objective to find the optimal placement of the ambulance stations (or stand-by positions) in Umeå, a municipality in the county with regards to median of response times for priority 1 alarms, the most urgent type of alarms (MRT1).

Methods: Here, we use data-driven approaches for optimizing the placement of ambulance stations. For a given allocation, i.

Long-term, continuous, subcutaneous levodopa/carbidopa infusion with ND0612 in Parkinson's disease: 3-year outcomes from the open-label BeyoND study.

Introduction: ND0612 is being investigated as a continuous, subcutaneous levodopa/carbidopa infusion, in combination with oral levodopa/carbidopa, for motor fluctuations in Parkinson's disease (PD). One-year data from the ongoing BeyoND study (NCT02726386) showed that the ND0612 regimen was safe and well tolerated and provided a sustained ≥2-h improvement in daily Good ON-time through 12 months of treatment.

Methods: We describe 3-year safety and efficacy outcomes for participants who completed 12 months of ND0612 treatment in the core study period and entered the extension phase.

Probabilistic learning of the Purkinje network from the electrocardiogram.

The identification of the Purkinje conduction system in the heart is a challenging task, yet essential for a correct definition of cardiac digital twins for precision cardiology. Here, we propose a probabilistic approach for identifying the Purkinje network from non-invasive clinical data such as the standard electrocardiogram (ECG). We use cardiac imaging to build an anatomically accurate model of the ventricles; we algorithmically generate a rule-based Purkinje network tailored to the anatomy; we simulate physiological electrocardiograms with a fast model; we identify the geometrical and electrical parameters of the Purkinje-ECG model with Bayesian optimization and approximate Bayesian computation.