Association between magnetic resonance imaging use and recovery time following concussion: a CARE consortium study.

Researchers may implement magnetic resonance imaging (MRI) to evaluate neurophysiological metrics (e.g. connectivity) in athletes with sports-related concussion (SRC).

SCAT Symptom Evolution in the Acute Concussion Phase: Findings from the NCAA-DoD CARE Consortium.

The Sport Concussion Assessment Tool (SCAT) is the most widely used tool following sport-related concussion (SRC). Initial SCAT symptom burden is a strong predictor of recovery in collegiate athletes; however, it is unknown if symptom presentation varies within the acute (<48 h) post-SRC phase. The purpose of this cohort study was to examine acute SRC symptom presentation among the National Collegiate Athletic Association (NCAA) athletes.

Deciphering the Complexities of Pulmonary Hypertension: The Emergent Role of Single-Cell Omics.

Expanding upon the critical advancements brought forth by single-cell omics in pulmonary hypertension (PH) research, this review delves deep into how these technologies have been piloted in a new era of understanding this complex disease. By leveraging the power of single cell transcriptomics (scRNA-seq), researchers can now dissect the complicated cellular ecosystem of the lungs, examining the key players such as endothelial cells, smooth muscle cells, pericytes, and immune cells, and their unique roles in the pathogenesis of PH. This more granular view is beyond the limitations of traditional bulk analysis, allowing for the identification of novel therapeutic targets previously obscured in the aggregated data.

Why do Stayers Stay? Perceptions of White and Black Long-Term Employees in a Community Mental Health Center.

Previous research has focused on factors influencing turnover of employees in the mental health workforce, yet little research has explored reasons why employees stay. To facilitate retaining a diverse mental health workforce, the current study aimed to elucidate factors that contributed to employees' tenure at a community mental health center (CHMC) as well as compare these perceptions between Black and White employees. Long-term employees (7 years or more) from one urban CMHC (n = 22) completed semi-structured stayer interviews.

Enhancing patient-clinician collaboration during treatment decision-making: study protocol for a community-engaged, mixed method hybrid type 1 trial of collaborative decision skills training (CDST) for veterans with psychosis.

Background: Patient participation in treatment decision making is a pillar of recovery-oriented care and is associated with improvements in empowerment and well-being. Although demand for increased involvement in treatment decision-making is high among veterans with serious mental illness, rates of involvement are low. Collaborative decision skills training (CDST) is a recovery-oriented, skills-based intervention designed to support meaningful patient participation in treatment decision making.

Predicting future occlusion or stenosis of lower extremity bypass grafts using artificial intelligence to simultaneously analyze all flow velocities collected in current and previous ultrasound examinations.

Objective: Routine surveillance with duplex ultrasound (DUS) examination is recommended after femoral-popliteal and femoral-tibial-pedal vein bypass grafts with various intervals postoperatively. The presently used methodology to analyze bypass graft DUS examination does not use all the available data and has been shown to have a significant rate for missing impending bypass graft failure. The objective of this research is to investigate recurrent neural networks (RNNs) to predict future bypass graft occlusion or stenosis.

Examining associations between social vulnerability indices and COVID-19 incidence and mortality with spatial-temporal Bayesian modeling.

This study compares two social vulnerability indices, the U.S. CDC SVI and SoVI (the Social Vulnerability Index developed at the Hazards Vulnerability & Resilience Institute at the University of South Carolina), on their ability to predict the risk of COVID-19 cases and deaths.

Trauma-informed climate scale-10 and attitudes related to trauma-informed care-10: An examination of scale psychometrics using data from disability service providers.

Background: Assessment is fundamental to the implementation of trauma-informed care. As trauma-informed care advances among organizations supporting people with intellectual and developmental disabilities (IDD), it is critical that they have access to validated assessment tools.

Objective: This is the first study to examine the psychometric properties of two brief measures associated with trauma-informed care, Trauma-Informed Climate Scale (TICS-10) and Attitudes Related to Trauma-Informed Care (ARTIC-10), using data from the IDD service industry.

Thermoplastic polyurethane surface coated with polymer brushes for reduced protein and cell attachment.

The objective of this study was to coat negatively charged polymer brushes covalently onto the surface of thermoplastic polyurethane (TPU) using a simple conventional surface free-radical polymerization technique. The coated surfaces were assessed with contact angle, protein adsorption, cell adhesion and bacterial adhesion. Bovine serum albumin (BSA) and bovine fibrinogen (BFG) were used for protein adsorption evaluation.

(Un)safe Spaces: The Relationship Between Slavery and Sexual Victimization of Black Women.

Research exploring the correlates of sexual victimization has found sexual victimization to be associated with both individual- and contextual-level factors, including age, gender, poverty, and size of the female population. However, to date, research has been limited in exploring how historical factors, such as slavery, may be associated with the contemporary prevalence of sexual victimization of women. Historical accounts have often suggested that enslaved women often experienced sexual victimization during their enslavement.

Reciprocal coproduction as a basis for the diffusion of global health innovations.

Global health reciprocal innovations originate in low-income and middle-income countries as well as high-income countries before their developers communicate about them with potential adopters in other countries as a transnational team. While communication technology has enabled a more rapid and broader sharing of information about innovations to prevent disease and improve health, innovations of various types have spread among countries, at all levels of income, for many centuries. In this article, we introduce the idea of reciprocal coproduction as a basis for the international sharing of information about innovations that exhibit potential for improving global health.

Neutrophils resist ferroptosis and promote breast cancer metastasis through aconitate decarboxylase 1.

Metastasis causes breast cancer-related mortality. Tumor-infiltrating neutrophils (TINs) inflict immunosuppression and promote metastasis. Therapeutic debilitation of TINs may enhance immunotherapy, yet it remains a challenge to identify therapeutic targets highly expressed and functionally essential in TINs but under-expressed in extra-tumoral neutrophils.

Short- and Long-Term Prediction of the Post-Pubertal Mandibular Length and -Axis in Females Utilizing Machine Learning.

The aim of this study was to create a novel machine learning (ML) algorithm for predicting the post-pubertal mandibular length and -axis in females. Cephalometric data from 176 females with Angle Class I occlusion were used to train and test seven ML algorithms. For all ML methods tested, the mean absolute errors (MAEs) for the 2-year prediction ranged from 2.

Using machine learning to detect sarcopenia from electronic health records.

Introduction: Sarcopenia (low muscle mass and strength) causes dysmobility and loss of independence. Sarcopenia is often not directly coded or described in electronic health records (EHR). The objective was to improve sarcopenia detection using structured data from EHR.

Posttraumatic stress and depressive symptoms and symptom clusters in a sample of treatment-seeking US veterans: Longitudinal associations with meaning in life and general self-efficacy.

Objectives: To quantify the associations between general self-efficacy, subjective meaning in life, and posttraumatic stress and depressive symptoms and symptom clusters in US veterans, both cross-sectionally and longitudinally.

Methods: Data from a Veteran Affairs (VA) funded intervention study (n = 191) were examined. Self-report measures of depressive symptoms, general self-efficacy, and meaning in life were collected, along with clinician-rated symptoms of PTSD.

Predicting body mass index in early childhood using data from the first 1000 days.

Few existing efforts to predict childhood obesity have included risk factors across the prenatal and early infancy periods, despite evidence that the first 1000 days is critical for obesity prevention. In this study, we employed machine learning techniques to understand the influence of factors in the first 1000 days on body mass index (BMI) values during childhood. We used LASSO regression to identify 13 features in addition to historical weight, height, and BMI that were relevant to childhood obesity.

Characteristics of Chemosensory Perception in Long COVID and COVID Reinfection.

Emerging data suggest an increasing prevalence of persistent symptoms in individuals affected by coronavirus disease-19 (COVID-19). The objective of this study was to determine the relative frequency of altered taste and smell in COVID reinfection (multiple COVID positive tests) and long COVID (one COVID positive test). We sent an electronic survey to patients in the Indiana University Health COVID registry with positive COVID test results, querying if they were experiencing symptoms consistent with long COVID including altered chemosensory perceptions.

A machine learning model for orthodontic extraction/non-extraction decision in a racially and ethnically diverse patient population.

Introduction: The purpose of the present study was to create a machine learning (ML) algorithm with the ability to predict the extraction/non-extraction decision in a racially and ethnically diverse sample.

Methods: Data was gathered from the records of 393 patients (200 non-extraction and 193 extraction) from a racially and ethnically diverse population. Four ML models (logistic regression [LR], random forest [RF], support vector machine [SVM], and neural network [NN]) were trained on a training set (70% of samples) and then tested on the remaining samples (30%).

Prediction of the Post-Pubertal Mandibular Length and Y Axis of Growth by Using Various Machine Learning Techniques: A Retrospective Longitudinal Study.

The aim was to predict the post-pubertal mandibular length and Y axis of growth in males by using various machine learning (ML) techniques. Cephalometric data obtained from 163 males with Class I Angle malocclusion, were used to train various ML algorithms. Analysis of variances (ANOVA) was used to compare the differences between predicted and actual measurements among methods and between time points.

Perceptions on Oral Ulcers From Facebook Page Categories: Observational Study.

Background: Oral ulcers are a common condition affecting a considerable proportion of the population, and they are often associated with trauma and stress. They are very painful, and interfere with eating. As they are usually considered an annoyance, people may turn to social media for potential management options.