Complex training

Objective: Hands-on surgical training (HOST) for congenital heart surgery (CHS), utilizing silicone-molded models created from 3D-printing of patients' imaging data, was shown to improve surgical skills. However, the impact of repetition and frequency of repetition in retaining skills has not been previously investigated. We aimed to longitudinally evaluate the outcome for HOST on two example procedures of different technical difficulties with repeated attempts over a 15-week period. Methods: Five CHS trainees were prospectively recruited...

Community health workers (CHWs) are increasingly being required to perform complex health care activities, especially in community cardiovascular disease and stroke prevention. However, currently, there are no psychometrically validated instruments for assessing CHW competencies in these roles. This article describes the development and validation of the stroke literacy assessment test (SLAT)-pertaining to the Life's Simple Seven (LS7) risk factors for stroke-for evaluating CHWs' competencies in the context of education and training programs...

Major histocompatibility complex Class II (MHCII) proteins initiate and regulate immune responses by presentation of antigenic peptides to CD4+ T-cells and self-restriction. The interactions between MHCII and peptides determine the specificity of the immune response and are crucial in immunotherapy and cancer vaccine design. With the ever-increasing amount of MHCII-peptide binding data available, many computational approaches have been developed for MHCII-peptide interaction prediction over the last decade...

Transformer neural networks show promising capabilities, in particular for uses in materials analysis, design, and manufacturing, including their capacity to work effectively with human language, symbols, code, and numerical data. Here, we explore the use of large language models (LLMs) as a tool that can support engineering analysis of materials, applied to retrieving key information about subject areas, developing research hypotheses, discovery of mechanistic relationships across disparate areas of knowledge, and writing and executing simulation codes for active knowledge generation based on physical ground truths...

Electronic health records (EHR) have revolutionized healthcare by providing efficient access to patient information, but their implementation poses various challenges. This paper examines the ethical and legal issues surrounding EHR adoption, particularly focusing on the healthcare landscape in India. Ethical considerations, including patient autonomy, confidentiality, beneficence, and justice, must guide EHR implementation to protect patient rights and privacy. Legal issues such as medical errors, malpractice, data breaches, and billing inaccuracies underscore the importance of robust policies and security measures...

BACKGROUND: Skin-to-skin care (SSC) between newborns and their parents provides many positive outcomes for both newborns and their parents. However, there is a lack of research assessing the perception of parents, especially fathers, of SSC in Saudi Arabia. PURPOSE: The aim of the study is to assess parents' perception of SSC in Saudi Arabia. METHODS: This cross-sectional study used an online survey. Data were collected from a convenience sample of 140 parents of hospitalized neonates between January and June 2023...

Machine learning interatomic potential (MLIP) overcomes the challenges of high computational costs in density-functional theory and the relatively low accuracy in classical large-scale molecular dynamics, facilitating more efficient and precise simulations in materials research and design. In this review, the current state of the four essential stages of MLIP is discussed, including data generation methods, material structure descriptors, six unique machine learning algorithms, and available software. Furthermore, the applications of MLIP in various fields are investigated, notably in phase-change memory materials, structure searching, material properties predicting, and the pre-trained universal models...

INTRODUCTION: blood transfusion remains an essential therapeutic intervention, but the occurrence of transfusion reactions makes its administration even more complex. Vigilant reporting of such reactions by recipients of blood products is essential for effective haemovigilance. This study aimed to determine the frequency and nature of transfusion reactions. METHODS: conducted over five years (2017-2021) at the Haemovigilance Department of the Rabat Regional Blood Transfusion Centre, this retrospective study exploited incident forms notified by health establishments and data from the regional blood transfusion centre's computer system...

There is an increased awareness of the importance of data publication, data sharing, and open science to support research, monitoring and control of vector-borne disease (VBD). Here we describe the efforts of the Global Biodiversity Information Facility (GBIF) as well as the World Health Special Programme on Research and Training in Diseases of Poverty (TDR) to promote publication of data related to vectors of diseases. In 2020, a GBIF task group of experts was formed to provide advice and support efforts aimed at enhancing the coverage and accessibility of data on vectors of human diseases within GBIF...

BACKGROUND AND OBJECTIVE: Nurses have an essential role in dealing with public health emergencies (PHE). This study explored the knowledge, attitude, and practice (KAP) towards preventing occupational exposure in PHE among nurses in Wuhan. METHODS: This cross-sectional study was conducted in May 2023 to assess the KAP of nurses in Wuhan, China. Questionnaires were created and distributed to evaluate the KAP of nurses and explore the factors associated with KAP. Univariate and multivariate logistic regression analyses were used to assess the association between baseline demographic characteristics and KAP, and structural equation modeling (SEM) was used to explore complex relationships and causal pathways among relevant factors...

The intrinsic dynamics of human brain activity display a recurring pattern of anti-correlated activity between the default mode network (DMN), associated with internal processing and mentation, and task positive regions, associated with externally directed attention. In human functional magnetic resonance imaging (fMRI) data, this anti-correlated pattern is detectable on the infraslow timescale (<0.1 Hz) as a quasi-periodic pattern (QPP). While the DMN is implicated in creativity and musicality in traditional time-averaged functional connectivity studies, no one has yet explored how creative training may alter dynamic spatiotemporal patterns involving the DMN such as QPPs...

A variety of cutting-edge methods and good knowledge of the illness's complex causes are causing a sea change in the field of Alzheimer's Disease (A.D.) research and treatment. Precision medicine is at the vanguard of this change, where individualized treatment plans based on genetic and biomarker profiles give a ray of hope for customized therapeutics. Combination therapies are becoming increasingly popular as a way to address the multifaceted pathology of Alzheimer's by simultaneously attacking Aβ plaques, tau tangles, neuroinflammation, and other factors...

The physical interactions between proteins are largely determined by the structural properties at their binding interfaces. It was found that the binding interfaces in distinctive protein complexes are highly similar. The structural properties underlying different binding interfaces could be further captured by artificial intelligence. In order to test this hypothesis, we broke protein-protein binding interfaces into pairs of interacting fragments. We employed a generative model to encode these interface fragment pairs in a low-dimensional latent space...

Accurately identifying cancer driver genes (CDGs) is crucial for guiding cancer treatment and has recently received great attention from researchers. However, the high complexity and heterogeneity of cancer gene regulatory networks limit the precition accuracy of existing deep learning models. To address this, we introduce a model called SCIS-CDG that utilizes Schur complement graph augmentation and independent subspace feature extraction techniques to effectively predict potential CDGs. Firstly, a random Schur complement strategy is adopted to generate two augmented views of gene network within a graph contrastive learning framework...

The skeletal muscle proteome alterations to aging and resistance training have been reported in prior studies. However, conventional proteomics in skeletal muscle typically yields wide protein abundance ranges that mask the detection of lowly expressed proteins. Thus, we adopted a novel deep proteomics approach whereby myofibril (MyoF) and non-MyoF fractions were separately subjected to protein corona nanoparticle complex formation prior to digestion and Liquid Chromatography Mass Spectrometry (LC-MS). Specifically, we investigated MyoF and non-MyoF proteomic profiles of the vastus lateralis muscle of younger (Y, 22±2 years old; n=5) and middle-aged participants (MA, 56±8 years old; n=6)...

BACKGROUND: Accurate assessment and timely intervention play a crucial role in ameliorating poor short-term prognosis of acute pulmonary embolism (APE) patients. The currently employed scoring models exhibit a degree of complexity, and some models may not comprehensively incorporate relevant indicators, thereby imposing limitations on the evaluative efficacy. Our study aimed to construct and externally validate a nomogram that predicts 30-day all-cause mortality risk in APE patients. METHODS: Clinical data from APE patients in Intensive Care-IV database was included as a training cohort...

PURPOSE: Videos and images are becoming an educational tool in every domain. The objective was to assess the contribution of short educational endoscopic videos in learning the complex anatomy of the tympanic cavity. METHODS: We conducted a prospective study amongst all the otolaryngology residents in 2021 in the greater Paris area (n = 74), from the first year to fifth year. We divided the residents into two groups who had the same 30-min anatomy class based on anatomical drawings...

BACKGROUND: The utilization of robot-assisted approaches to surgery has increased significantly over the last two decades. This has introduced novel complexities into the operating room environment, requiring management of new challenges and workflow adaptation. This study aimed to analyze challenges in the surgical setup for complex upper gastrointestinal robot-assisted surgery (UGI-RAS) and identify opportunities for solutions. METHODS: Direct observations of surgical setup processes for UGI-RAS were performed by a trained Human Factors researcher at a non-profit academic medical center in Southern California...

BACKGROUND: Mode of delivery in women with previous history of cesarean delivery (CD) is highly modifiable by the practices of the delivery unit. Vaginal birth after a cesarean (VBAC) delivery is a safe and preferred alternative in most cases. The aim of this study was to assess the impact of adopting a complex set of measures aimed at the mode of delivery in this group. METHODS: This was a retrospective observational study comparing two birth cohorts before and after the implementation of a series of quality improvement (QI) interventions...

BACKGROUND: Children and adolescents with complex medical issues need home care services; however, few studies have provided insight into the unmet home care needs of the families of patients with osteogenesis imperfecta (OI). In this study, we aimed to assess the home care needs of caregivers of children and adolescents with OI and the associated factors. METHODS: A self-administered questionnaire was administered online to 142 caregivers of patients with OI aged 3-17 years between May and October 2022 from 25 provinces in China...