Anxiety & Stress

Quality control of entomopathogenic nematodes through infrared spectroscopy (FTIR-ATR, 2D-COS): Tracing, modelling and prediction.

Entomopathogenic nematodes (EPNs) are widely used in biological pest control, yet their efficacy in field applications is highly dependent on physiological quality during storage; an area lacking direct, predictive quality control tools. Current assessments rely solely on labor-intensive infectivity tests using insect hosts like Galleria mellonella. This study breaks new ground by combining Fourie...

Assessing the influence of generative artificial intelligence (GenAI) on awareness and behavior in medical research integrity: An online survey study.

BACKGROUND: Generative Artificial Intelligence(GenAI) significantly enhances medical research efficiency but raises ethical concerns regarding research integrity. The lack of systematic guidelines for its ethical use underscores the need to investigate GenAI's impact on researchers' awareness and behavior concerning integrity. METHODS/MATERIALS: A cross-sectional survey of 718 valid responses from...

Research experience and career factors in relation to mental health problems: Prevalence, risk factors, and machine learning-based predictive estimates.

BACKGROUND: Mental health issues, including depression, anxiety, and insomnia, are increasingly prevalent among university students and graduates, esp...

Can the mind perception of perceived artificial intelligence-generated content alleviate involution anxiety? A longitudinal study with social support as a mediator.

Involution anxiety, characterized by heightened stress and competition in educational and professional settings, is a significant psychological trait ...

AI fragment based optimization of saffron and chamomile phytochemicals as aryl hydrocarbon receptor inhibitors for dementia therapy an integrated computational approach.

Dementia represents a rapidly rising global health challenge as a progressive neurodegenerative disease with few options for disease-modifyingtreatmen...

Integrating molecular generation and fingerprints transferring for single-molecule theranostics targeting endoplasmic reticulum stress.

INTRODUCTION: Precise diagnosis and treatment of diseases necessitate quantitative visualization and modulation of subcellular structures. The endopla...

Beyond Adverse Childhood Experiences: What Should be Considered for Trauma-Focused Adolescent Mental Health Risk Assessments?

To align with emerging policies for adolescents, feasible, accurate, and equitable trauma-focused assessment protocols need to be developed. To date, ...

Predictive Modeling of Comorbid Depression and Anxiety Symptoms Among Prospective University Students: A GIS-Based and Machine Learning Study.

Prospective university students are highly susceptible to mental health issues such as depression and anxiety. This study investigates the prevalence ...

Screening and investigating the regulatory mechanisms of oxidative stress-related biomarkers in thoracic aortic aneurysms.

Excess reactive oxygen species leading to oxidative stress has been identified as a significant factor in cardiovascular disease. However, the molecul...

PREACT-digital: study protocol for a longitudinal, observational multicentre study on digital phenotypes of non-response to cognitive behavioural therapy for internalising disorders.

INTRODUCTION: Cognitive behavioural therapy (CBT) serves as a first-line treatment for internalising disorders (ID), encompassing depressive, anxiety ...

Deep learning to assess erythritol in zebrafish development, circadian rhythm, and cardiovascular disease risk.

Erythritol is one of the most widely used artificial sweeteners, yet the potential risks remain a subject of debate. In this experiment, the concentra...

Gut microbiota composition is related to anxiety and aggression scores in companion dogs.

There is mounting evidence for a link between behaviour and the gut microbiome in animal and human health. However, the role of the gut microbiome in ...

Future water stress in China: Projections under socioeconomic and climate change scenarios.

Estimating future water stress under socioeconomic and climate change is crucial for sustainable management. However, previous studies in China normal...

Harnessing technology for hope: a systematic review of digital suicide prevention tools.

This systematic review scrutinizes digital interventions in suicide prevention, telehealth, mobile applications, artificial intelligence (AI), and dig...

Comparing traditional natural language processing and large language models for mental health status classification: a multi-model evaluation.

The substantial increase in mental health disorders globally necessitates scalable, accurate tools for detecting and classifying these conditions in d...

Data Acquisition of Exercise and Fitness Pressure Measurement Based on Artificial Intelligence Technology.

This project aims to improve the accuracy of fitness and physical pressure ratings, focusing on basketball, by integrating artificial intelligence (AI...

Personality predicts internalizing symptoms and quality of life in police cadets: a comparison of artificial intelligence and parametric approaches.

BACKGROUND: Police cadets undergo persistent and elevated stress due to continuous training and evaluation. Identifying resilience and risk factors in...

Unraveling the oxidative stress landscape in diabetic foot ulcers: insights from bulk RNA and single-cell RNA sequencing data.

BACKGROUND: Oxidative stress plays a crucial role in the development of diabetic foot ulcers (DFU). However, its underlying mechanisms are not fully u...

Using Machine Learning to Predict Treatment Outcome in a Concatenated Dataset of Youth Anxiety Treatments.

Machine Learning (ML) is a promising approach for predicting outcomes of youth anxiety treatments. To this end, data from nine randomized controlled t...

Recognition of anxiety and depression using gait data recorded by the kinect sensor: a machine learning approach with data augmentation.

Anxiety and depression disorders are increasingly common, necessitating methods for real-time assessment and early identification. This study investig...