Molecular biomarkers of glial activation and injury in epilepsy.

Increasing evidence from fluid biopsies suggests activation and injury of glial cells in epilepsy. The prevalence of clinical and subclinical seizures in neurodegenerative conditions such as Alzheimer's disease, frontotemporal dementia, and others merits review and comparison of the effects of seizures on glial markers in epilepsy and neurodegenerative diseases with concomitant seizures. Herein, we revisit preclinical and clinical reports of alterations in glial proteins in cerebrospinal fluid and blood associated with various types of epilepsy.

Identification of cardiac wall motion abnormalities in diverse populations by deep learning of the electrocardiogram.

Cardiac wall motion abnormalities (WMA) are strong predictors of mortality, but current screening methods using Q waves from electrocardiograms (ECGs) have limited accuracy and vary across racial and ethnic groups. This study aimed to identify novel ECG features using deep learning to enhance WMA detection, referencing echocardiography as the gold standard. We collected ECG and echocardiogram data from 35,210 patients in California and labeled WMA using unstructured language parsing of echocardiographic reports.

Self-Contamination Risk and Failure Modes During High-Level PPE Doffing: A Comparison of Two Powered Air Purifying Respirator (PAPR) Hoods: A Pilot Study.

Background: Personal protective equipment (PPE) doffing protocols can reduce risks of pathogen self-contamination. Powered air purifying respirators (PAPRs) may increase these risks. This study compares viral contamination and errors during simulated doffing of single layer vs double layer hood PAPRs.

Default mode network functional connectivity as a transdiagnostic biomarker of cognitive function.

The default mode network (DMN) is intricately linked with processes such as self-referential thinking, episodic memory recall, goal-directed cognition, self-projection, and theory of mind. Over recent years, there has been a surge in examining its functional connectivity, particularly its relationship with frontoparietal networks (FPN) involved in top-down attention, executive function, and cognitive control. The fluidity in switching between these internal and external modes of processing-highlighted by anti-correlated functional connectivity-has been proposed as an indicator of cognitive health.

Automatic medical imaging segmentation via self-supervising large-scale convolutional neural networks.

Purpose: This study aims to develop a robust, large-scale deep learning model for medical image segmentation, leveraging self-supervised learning to overcome the limitations of supervised learning and data variability in clinical settings.

Methods And Materials: We curated a substantial multi-center CT dataset for self-supervised pre-training using masked image modeling with sparse submanifold convolution. We designed a series of Sparse Submanifold U-Nets (SS-UNets) of varying sizes and performed self-supervised pre-training.

Parametric finite element modeling of reinforced polymeric leaflets for improved durability.

Hyaluronic acid-enhanced polyethylene polymeric TAVR shows excellent in vivo anti-calcific, anti-thrombotic, and in vitro hydrodynamic performance. However, during durability testing, impact wear and fatigue cause early valve failure. Heart valve durability can be improved by strengthening the leaflet with fiber reinforcement.

Allocation of Semaglutide According to Coronary Artery Calcium and BMI: Applying the SELECT Trial to MESA.

Background: Implementation of semaglutide weight loss therapy has been challenging due to drug supply and cost, underscoring a need to identify those who derive the greatest absolute benefit.

Objectives: Allocation of semaglutide was modeled according to coronary artery calcium (CAC) among individuals without diabetes or established atherosclerotic cardiovascular disease (CVD).

Methods: In this analysis, 3,129 participants in the MESA (Multi-Ethnic Study of Atherosclerosis) without diabetes or clinical CVD met body mass index criteria for semaglutide and underwent CAC scoring on noncontrast cardiac computed tomography.

Atomic Gap-State Engineering of MoS for Alkaline Water and Seawater Splitting.

Transition-metal dichalcogenides (TMDs), such as molybdenum disulfide (MoS), have emerged as a generation of nonprecious catalysts for the hydrogen evolution reaction (HER), largely due to their theoretical hydrogen adsorption energy close to that of platinum. However, efforts to activate the basal planes of TMDs have primarily centered around strategies such as introducing numerous atomic vacancies, creating vacancy-heteroatom complexes, or applying significant strain, especially for acidic media. These approaches, while potentially effective, present substantial challenges in practical large-scale deployment.

Caught in the Crossfire: Unmasking the Silent Renal Threats of Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia.

Background: Renal adverse drug reactions (ADRs) associated with tyrosine kinase inhibitors (TKIs) in the treatment of chronic myeloid leukemia (CML) are relatively rare, and there is currently no standardized protocol for their management. Therefore, this study aimed to summarize renal ADRs related to TKIs use in CML and propose an evidence-based approach to monitor and manage these ADRs.

Methods: A systematic literature review was performed to identify renal ADRs associated with TKIs in CML.

Exploring the Potential Effects of Soybean By-Product (Hulls) and Enzyme (Beta-Mannanase) on Laying Hens During Peak Production.

This study determined the interaction between soybean hulls (SHs) and enzymes (β-mannanase) to improve the sustainability and efficacy of feeding programs for laying hens during peak production while ensuring the best health and efficiency. In a completely randomized design (CRD), 200 golden-brown hens were fed for four weeks (33 to 36 weeks) and randomly distributed into four groups, each containing four replicates of ten birds, with one group receiving a control diet (P0) and the others receiving diets that contained four combinations of SHs and enzymes (ENZs). e.

Clinicopathologic Parameters of Peritoneal Fluid as Predictors of Gastrointestinal Lesions, Complications, and Outcomes in Equine Colic Patients: A Retrospective Study.

Neutrophil characteristics in peritoneal fluid (PF) may aid in diagnosing and treating specific colic lesions and complications. The objective of this retrospective study was to evaluate quantitative PF leukocyte values, as well as PF total protein (TP) and lactate, for associations with diagnosis, morbidity, and mortality in horses with acute colic. Three hundred and forty-two horses that presented to one institution between January 2010-2020 for the evaluation of acute colic were included.

Serial systemic immune inflammation indices: markers of acute migraine events or indicators of persistent inflammatory status?

Background: Migraine is the most common complex neurological disorder, affecting over a billion people worldwide. Neurogenic inflammation has long been recognized as a key factor in the pathophysiology of migraine though little research has been directed to investigating whether inflammation is greatest in migraine with aura or without, and whether inflammation is a permanent state in migraine or whether is an event related transitory state. Thus, the primary aim of this single-centre, retrospective study was to explore the potential clinical utility of the Serial Systemic Immune-Inflammatory Indices (SSIIi) as a comparative measure of duration and severity of inflammation derived from routine blood cell counts in migraine patients with aura and no-aura both within an acute inpatient setting and as outpatients.

Genetic parameters and genome-wide association studies including the X chromosome for various reproduction and semen quality traits in Nellore cattle.

Background: The profitability of the beef industry is directly influenced by the fertility rate and reproductive performance of both males and females, which can be improved through selective breeding. When performing genomic analyses, genetic markers located on the X chromosome have been commonly ignored despite the X chromosome being one of the largest chromosomes in the cattle genome. Therefore, the primary objectives of this study were to: (1) estimate variance components and genetic parameters for eighteen male and five female fertility and reproductive traits in Nellore cattle including X chromosome markers in the analyses; and (2) perform genome-wide association studies and functional genomic analyses to better understand the genetic background of male and female fertility and reproductive performance traits in Nellore cattle.

Endothelial IGFBP6 suppresses vascular inflammation and atherosclerosis.

Beyond dyslipidemia, inflammation contributes to the development of atherosclerosis. However, intrinsic factors that counteract vascular inflammation and atherosclerosis remain scarce. Here we identify insulin-like growth factor binding protein 6 (IGFBP6) as a homeostasis-associated molecule that restrains endothelial inflammation and atherosclerosis.

Identifying novel response markers for spinal muscular atrophy revealed by targeted proteomics following gene therapy.

Spinal muscular atrophy (SMA) is a progressive disease that affects motor neurons, with symptoms usually starting in infancy or early childhood. Recent breakthroughs in treatments targeting SMA have improved both lifespan and quality of life for infants and children with the disease. Given the impact of these treatments, it is essential to develop methods for managing treatment-induced changes in disease characteristics.

Ultrastructural Localization of Glutamate Delta Receptor 1 in the Rodent and Primate Lateral Habenula.

Glutamate delta receptor 1 (GluD1) is a unique synaptogenic molecule expressed at excitatory and inhibitory synapses. The lateral habenula (LHb), a subcortical structure that regulates negative reward prediction error and major monoaminergic systems, is enriched in GluD1. LHb dysfunction has been implicated in psychiatric disorders such as depression and schizophrenia, both of which are associated with GRID1, the gene that encodes GluD1.

Location of Primary Tumor Impacts Survival After Pulmonary Metastasectomy for Colorectal Cancer.

Background: The benefit of pulmonary metastasectomy (PM) in patients with colorectal cancer (CRC) with isolated lung metastases remains unclear and failure to separate colon from rectal cancer may contribute. Utilizing a large national database, we investigate whether PM is associated with survival benefits in patients presenting with CRC with synchronous lung metastases based upon primary tumor location.

Methods: The Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015 was queried to identify patients with stage IV CRC with isolated synchronous lung metastases at initial diagnosis.

Selective lead ion sensing via cotton pad-based NaEDTA capped AuNPs: A smartphone-assisted colorimetric method.

Herein, NaEDTA-capped AuNPs specifically designed for selective smartphone-assisted colorimetric detection are synthesized and characterized. NaEDTA-capped AuNPs was synthesized and characterized by UV-Visible spectroscopy, ATR, Raman, XRD, SEM and EDX. The calculated activation energy of the produced nanoparticles was 0.

Screening for Health-Related Social Needs: American College of Preventive Medicine's Practice Statement.

Interest is rapidly growing around screening for health-related social needs (HRSN) in direct patient care settings. The screening and provision of HRSN is often done in the context of trying to address social determinants of health (SDOH). While there is emerging evidence that screening and referral for HRSN can improve health outcomes, there are educational, operational, and systemic gaps that need to be filled in order for HRSN screening and referral to be implemented system-wide and result in meaningful improvement in population health outcomes.

Predictive Modeling of Non-functioning Giant Pituitary Neuroendocrine Tumor Resection: A Multi-Planar Perspective.

Background: Giant pituitary neuroendocrine tumor (GPitNET) are challenging tumors with low rates of gross total resection (GTR) and high morbidity. Previously reported machine-learning (ML) models for prediction of pituitary neuroendocrine tumor extent of resection (EOR) using preoperative imaging included a heterogenous dataset of functional and non-functional pituitary neuroendocrine tumors of various sizes leading to variability in results.

Objective: The aim of this pilot study is to construct a ML model based on the multi-dimensional geometry of tumor to accurately predict the EOR of non-functioning GPitNET.

Evaluation of Multi-Lingual Simplifications of IR Procedural Reports Using GPT-4.

This study assesses the feasibility of Large Language Models like GPT-4 (OpenAI, San Francisco, CA, USA) to summarize interventional radiology (IR) procedural reports to improve layperson understanding and translate medical texts into multiple languages. 200 reports from eight categories were summarized using GPT-4. Readability was assessed with Flesch-Kincaid Reading Level (FKRL) and Flesch Reading Ease Score (FRES).