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BACKGROUND AND AIMS: Mental health problem is a rising public health concern. People of all ages, specially Bangladeshi university students, are more affected by this burden. Thus, the objective of the study was to use tree-based machine learning (ML) models to identify major risk factors and predict anxiety, depression, and insomnia in university students. METHODS: A social media-based cross-sectional survey was employed for data collection. We used Generalized Anxiety Disorder (GAD-7), Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index (ISI-7) scale for measuring students' anxiety, depression and insomnia problems...

INTRODUCTION: Alzheimer's disease (AD) is a progressive neurological disorder characterized by mild memory loss and ranks as a leading cause of mortality in the USA, accounting for approximately 120,000 deaths per year. It is also the primary form of dementia. Early detection is critical for timely intervention as the neurodegenerative process often starts 15-20 years before cognitive symptoms manifest. This study focuses on determining feature importance in AD classification using fused texture features from 3D magnetic resonance imaging hippocampal and entorhinal cortex and standardized uptake value ratio (SUVR) derived from positron emission tomography (PET) images...

PURPOSE: Uveitis is a heterogenous group of inflammatory eye disease for which current cytokine-targeted immune therapies are effective for only a subset of patients. We hypothesized that despite pathophysiologic nuances that differentiate individual disease states, all forms of eye inflammation might share common mechanisms for immune cell recruitment. Identifying these mechanisms is critical for developing novel, broadly acting therapeutic strategies. DESIGN: Experimental study...

INTRODUCTION: Pro-inflammatory cytokine - tumor necrosis factor-alpha (TNF) is one of the components of the seminal plasma proteome; its meaning has not been definitively revealed. A comparative analysis of the concentration of this protein in the blood serum and in the ejaculate and changes in its level in the semen of men with infertility is f scientific interest. THE PURPOSE OF THE STUDY: determination of TNF- level in the blood serum and seminal plasma of healthy men and patients with reduced fertility...

PURPOSE: This work reports for the first time on the implementation and application of cardiac diffusion-weighted MRI on a Connectom MR scanner with a maximum gradient strength of 300 mT/m. It evaluates the benefits of the increased gradient performance for the investigation of the myocardial microstructure. METHODS: Cardiac diffusion-weighted imaging (DWI) experiments were performed on 10 healthy volunteers using a spin-echo sequence with up to second- and third-order motion compensation ( <mml:math xmlns:mml="https://www...

PURPOSE: MRI using 3D stack-of-spirals (SoS) readout on a high-performance gradient system is subject to strong second-order, spatially varying concomitant fields, which can lead to signal dropout and blurring artifacts that become more significant at locations farther from the gradient isocenter. A method for compensating for second-order concomitant fields in 3D axial SoS image reconstruction is described. METHODS: We retrospectively correct for second-order concomitant field-induced phase error in the 3D SoS data by slice-dependent k-space phase compensation based on the nominal spiral readout trajectories...

BACKGROUND: Previous research has shown that the use of dental care services has a significant socioeconomic gradient. Lower income groups tend to use dental care services less, and they often have poorer dental health than higher income groups. The purpose of this study is to evaluate how an increase in income affects the use of dental care services among a low-income population. METHODS: The study examines the causal effect of increasing cash transfers on the use of dental care services by utilizing unique register-based data from a randomized field experiment conducted in Finland in 2017-2018...

Analyzing new psychoactive substances (NPSs) in forensic laboratories present a formidable challenge globally. Within illicit drug analysis, gas chromatography-mass spectrometry (GC-MS) emerges as a robust analytical tool. This study endeavors to assess and compare peak resolution in the analysis of illicit drugs, specifically focusing on 21 synthetic cathinones, encompassing 9 cathinone isomers. Varied GC-MS operating conditions, including distinct GC-MS columns and thermal gradients, were systematically employed for the simultaneous analysis of these synthetic cathinones...

Geometry scaling of microwave circuits is an essential but challenging task. In particular, the employment of a given passive structure in a different application area often requires re-adjustment of the operating frequencies/bands while maintaining top performance. Achieving this necessitates the utilization of numerical optimization methods. Nonetheless, if the intended frequencies are distant from the ones at the starting point, local search procedures tend to fail, whereas global search algorithms are computationally expensive...

This study aimed to analyze peripheral blood lymphocyte subsets in lupus nephritis (LN) patients and use machine learning (ML) methods to establish an effective algorithm for predicting co-infection in LN. This study included 111 non-infected LN patients, 72 infected LN patients, and 206 healthy controls (HCs). Patient information, infection characteristics, medication, and laboratory indexes were recorded. Eight ML methods were compared to establish a model through a training group and verify the results in a test group...

AIMS: Delineation variations and organ motion produce difficult-to-quantify uncertainties in planned radiation doses to targets and organs at risk. Similar to manual contouring, most automatic segmentation tools generate single delineations per structure; however, this does not indicate the range of clinically acceptable delineations. This study develops a method to generate a range of automatic cardiac structure segmentations, incorporating motion and delineation uncertainty, and evaluates the dosimetric impact in lung cancer...

BACKGROUND: High-risk emergency department (ED) revisit is considered an important quality indicator that may reflect an increase in complications and medical burden. However, because of its multidimensional and highly complex nature, this factor has not been comprehensively investigated. This study aimed to predict high-risk ED revisit with a machine-learning (ML) approach. METHODS: This 3-year retrospective cohort study assessed adult patients between January 2019 and December 2021 from National Taiwan University Hospital Hsin-Chu Branch with high-risk ED revisit, defined as hospital or intensive care unit admission after ED return within 72 hours...

Ammonia (NH3 ) contributes significantly to the formation of particulate matter, and vehicles represent a major source of NH3 in urban areas. However, there remains a lack of comprehensive understanding regarding the emission characteristics of NH3 from vehicles. This study conducted real-world driving emission (RDE) measurements and dynamometer measurements on 33 light-duty gasoline vehicles (LDGVs) to investigate their emission characteristics and impact factors. The tested vehicles include China 3 to China 6 emission standards...

Magnetogenetics has shown great potential for cell function and neuromodulation using heat or force effects under different magnetic fields; however, there is still a contradiction between experimental effects and underlying mechanisms by theoretical computation. In this study, we aimed to investigate the role of reactive oxygen species (ROS) in mechanical force-dependent regulation from a physicochemical perspective. The transient receptor potential vanilloid 4 (TRPV4) cation channels fused to ferritin (T4F) were overexpressed in HEK293T cells and exposed to static magnetic fields (sMF, 1...

PURPOSE: This study aimed to construct a predictive model integrating deep learning-derived radiomic features from computed tomography angiography (CTA) and clinical biomarkers to forecast postoperative adverse events (AEs) in patients with acute uncomplicated Stanford type B aortic dissection (uTBAD) undergoing initial thoracic endovascular aortic repair (TEVAR). METHODS: We retrospectively evaluated 369 patients treated with TEVAR for acute uTBAD from January 2015 to December 2022...

We present a thorough investigation into the efficacy of 19 density functional theory (DFT) functionals, relative to RI-CC2 results, for computing two-photon absorption (2PA) cross sections (σ2PA ) and key dipole moments (|μ00 |, |μ11 |, |Δμ|, |μ01 |) for a series of coumarin dyes in the gas-phase. The functionals include different categories, including local density approximation (LDA), generalized gradient approximation (GGA), hybrid-GGA (H-GGA), range-separated hybrid-GGA (RSH-GGA), meta -GGA (M-GGA), and hybrid M-GGA (HM-GGA), with 14 of them being subjected to analysis for the first time with respect to predicting σ2PA values...

Making healthy dietary choices is essential for keeping weight within a normal range. Yet many people struggle with dietary self-control despite good intentions. What distinguishes neural processing in those who succeed or fail to implement healthy eating goals? Does this vary by weight status? To examine these questions, we utilized an analytical framework of gradients that characterize systematic spatial patterns of large-scale neural activity, which have the advantage of considering the entire suite of processes subserving self-control and potential regulatory tactics at the whole-brain level...

Flagellar motility is a key bacterial trait as it allows bacteria to navigate their immediate surroundings. Not all bacteria are capable of flagellar motility, and the distribution of this trait, its ecological associations, and the life history strategies of flagellated taxa remain poorly characterized. We developed and validated a genome-based approach to infer the potential for flagellar motility across 12 bacterial phyla (26 192 genomes in total). The capacity for flagellar motility was associated with a higher prevalence of genes for carbohydrate metabolism and higher maximum potential growth rates, suggesting that flagellar motility is more prevalent in environments with higher carbon availability...

Effectively assessing psychological resilience for medical students is vital for identifying at-risk individuals and developing tailored interventions. At present, few studies have combined physiological indexes of the human body and machine learning for psychological resilience assessment. This study presents a novel approach that employs pupil diameter features and machine learning to predict psychological resilience risk objectively. Firstly, we designed a stimulus paradigm (via auditory and visual stimuli) and collected pupil diameter data from participants using eye-tracking technology...

Surface reconstruction for point clouds is an important task in 3D computer vision. Most of the latest methods resolve this problem by learning signed distance functions from point clouds, which are limited to reconstructing closed surfaces. Some other methods tried to represent open surfaces using unsigned distance functions (UDF) which are learned from ground truth distances. However, the learned UDF is hard to provide smooth distance fields due to the discontinuous character of point clouds. In this paper, we propose CAP-UDF, a novel method to learn consistency-aware UDF from raw point clouds...