Neural speech tracking contribution of lip movements predicts behavioral deterioration when the speaker's mouth is occluded.

Observing lip movements of a speaker facilitates speech understanding, especially in challenging listening situations. Converging evidence from neuroscientific studies shows stronger neural responses to audiovisual stimuli compared to audio-only stimuli. However, the interindividual variability of this contribution of lip movement information and its consequences on behavior are unknown.

Impact of Demographics and Psychological Factors on Three-Day Postoperative Pain Perception Following Hand Surgery.

Effective pain management is crucial for both comfort and outcomes, yet predicting and managing this pain is difficult. This study aimed to analyze postoperative pain in patients undergoing hand surgery at the Mayo Clinic Florida, examining how patient characteristics and anxiety affect pain outcomes. We conducted a single-arm clinical trial at Mayo Clinic Florida, recruiting patients undergoing hand surgery.

The Algorithmic Divide: A Systematic Review on AI-Driven Racial Disparities in Healthcare.

Introduction: As artificial intelligence (AI) continues to permeate various sectors, concerns about disparities arising from its deployment have surfaced. AI's effectiveness correlates not only with the algorithm's quality but also with its training data's integrity. This systematic review investigates the racial disparities perpetuated by AI systems across diverse medical domains and the implications of deploying them, particularly in healthcare.

The Impact of Digital Health Solutions on Bridging the Health Care Gap in Rural Areas: A Scoping Review.

Digital health tools can improve health care access and outcomes for individuals with limited access to health care, particularly those residing in rural areas. This scoping review examines the existing literature on using digital tools in patients with limited access to health care in rural areas. It assesses their effectiveness in improving health outcomes.

Single-nucleus RNA sequencing reveals glial cell type-specific responses to ischemic stroke in male rodents.

Neuroglia critically shape the brain´s response to ischemic stroke. However, their phenotypic heterogeneity impedes a holistic understanding of the cellular composition of the early ischemic lesion. Here we present a single cell resolution transcriptomics dataset of the brain´s acute response to infarction.

Clinical and Surgical Applications of Large Language Models: A Systematic Review.

Large language models (LLMs) represent a recent advancement in artificial intelligence with medical applications across various healthcare domains. The objective of this review is to highlight how LLMs can be utilized by clinicians and surgeons in their everyday practice. A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

Artificial Intelligence Support for Informal Patient Caregivers: A Systematic Review.

This study aims to explore how artificial intelligence can help ease the burden on caregivers, filling a gap in current research and healthcare practices due to the growing challenge of an aging population and increased reliance on informal caregivers. We conducted a search with Google Scholar, PubMed, Scopus, IEEE Xplore, and Web of Science, focusing on AI and caregiving. Our inclusion criteria were studies where AI supports informal caregivers, excluding those solely for data collection.

Cell-mediated cytotoxicity within CSF and brain parenchyma in spinal muscular atrophy unaltered by nusinersen treatment.

5q-associated spinal muscular atrophy (SMA) is a motoneuron disease caused by mutations in the survival motor neuron 1 (SMN1) gene. Adaptive immunity may contribute to SMA as described in other motoneuron diseases, yet mechanisms remain elusive. Nusinersen, an antisense treatment, enhances SMN2 expression, benefiting SMA patients.

Physiologic validation of the Compensatory Reserve Metric obtained from pulse oximetry: A step toward advanced medical monitoring on the battlefield.

Background: The Compensatory Reserve Metric (CRM) provides a time sensitive indicator of hemodynamic decompensation. However, its in-field utility is limited because of the size and cost-intensive nature of standard vital sign monitors or photoplethysmographic volume-clamp (PPG VC ) devices used to measure arterial waveforms. In this regard, photoplethysmographic measurements obtained from pulse oximetry may serve as a useful, portable alternative.

Comparing the compensatory reserve metric obtained from invasive arterial measurements and photoplethysmographic volume-clamp during simulated hemorrhage.

Purpose: The compensatory reserve metric (CRM) is a novel tool to predict cardiovascular decompensation during hemorrhage. The CRM is traditionally computed using waveforms obtained from photoplethysmographic volume-clamp (PPG), yet invasive arterial pressures may be uniquely available. We aimed to examine the level of agreement of CRM values computed from invasive arterial-derived waveforms and values computed from PPG-derived waveforms.

AI and Ethics: A Systematic Review of the Ethical Considerations of Large Language Model Use in Surgery Research.

Introduction: As large language models receive greater attention in medical research, the investigation of ethical considerations is warranted. This review aims to explore surgery literature to identify ethical concerns surrounding these artificial intelligence models and evaluate how autonomy, beneficence, nonmaleficence, and justice are represented within these ethical discussions to provide insights in order to guide further research and practice.

Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

The usefulness of artificial intelligence in breast reconstruction: a systematic review.

Background: Artificial Intelligence (AI) offers an approach to predictive modeling. The model learns to determine specific patterns of undesirable outcomes in a dataset. Therefore, a decision-making algorithm can be built based on these patterns to prevent negative results.

Targeting the EGFR pathway: An alternative strategy for the treatment of tuberous sclerosis complex?

Introduction: Tuberous sclerosis complex (TSC) is caused by variants in TSC1/TSC2, leading to constitutive activation of the mammalian target of rapamycin (mTOR) complex 1. Therapy with everolimus has been approved for TSC, but variations in success are frequent. Recently, caudal late interneuron progenitor (CLIP) cells were identified as a common origin of the TSC brain pathologies such as subependymal giant cell astrocytomas (SEGA) and cortical tubers (CT).

Artificial-Intelligence-Based Clinical Decision Support Systems in Primary Care: A Scoping Review of Current Clinical Implementations.

Primary Care Physicians (PCPs) are the first point of contact in healthcare. Because PCPs face the challenge of managing diverse patient populations while maintaining up-to-date medical knowledge and updated health records, this study explores the current outcomes and effectiveness of implementing Artificial Intelligence-based Clinical Decision Support Systems (AI-CDSSs) in Primary Healthcare (PHC). Following the PRISMA-ScR guidelines, we systematically searched five databases, PubMed, Scopus, CINAHL, IEEE, and Google Scholar, and manually searched related articles.

PhyLab - a virtual reality laboratory for experiments in physics: a pilot study on intervention effectiveness and gender differences.

Introduction: New technologies have great potential to facilitate students' understanding and appreciation of one of the most abstract and challenging school subjects - physics. This study aimed to examine the effects of a game-based virtual reality teaching method on secondary school students' self-beliefs, interest, and performance in physics through a quasi-experimental design using pre- and post-test data. The evaluation is based on the systemic actiotope model that explains a person's goal-oriented actions by an interplay of their environment, action repertoire (i.

New insights into neuropathology and pathogenesis of autoimmune glial fibrillary acidic protein meningoencephalomyelitis.

Anti-glial fibrillary acidic protein (GFAP) meningoencephalomyelitis (autoimmune GFAP astrocytopathy) is a new autoimmune central nervous system (CNS) disease diagnosable by the presence of anti-GFAP autoantibodies in the cerebrospinal fluid and presents as meningoencephalomyelitis in the majority of patients. Only few neuropathological reports are available and little is known about the pathogenic mechanisms. We performed a histopathological study of two autopsies and nine CNS biopsies of patients with anti-GFAP autoantibodies and found predominantly a lymphocytic and in one autopsy case a granulomatous inflammatory phenotype.

Stability of One-Step Spray-on Splint for Lower Extremity Fractures During Splinting, MEDEVAC, and Impact.

Introduction: Military transport can induce whole-body vibrations, and combat almost always involves high impact between lower extremities and the ground. Therefore, robust splinting technology is necessary for lower extremity fractures in these settings. Our team compared a novel one-step spray-on foam splint (FastCast) to the current military standard structured aluminum malleable (SAM) splint.

Towards a Lightweight Classifier to Detect Hypovolemic Shock.

Predicting the ability of an individual to compensate for blood loss during hemorrhage and detect the likely onset of hypovolemic shock is necessary to permit early clinical intervention. Towards this end, the compensatory reserve metric (CRM) has been demonstrated to directly correlate with an individual's ability to maintain compensatory mechanisms during loss of blood volume from onset (one-hundred percent health) to exsanguination (zero percent health). This effort describes a lightweight, three-class predictor (good, fair, poor) of an individual's compensatory reserve using a linear support-vector machine (SVM) classifier.

Predicting Cardiopulmonary Arrest with Digital Biomarkers: A Systematic Review.

(1) Background: Telemetry units allow the continuous monitoring of vital signs and ECG of patients. Such physiological indicators work as the digital signatures and biomarkers of disease that can aid in detecting abnormalities that appear before cardiac arrests (CAs). This review aims to identify the vital sign abnormalities measured by telemetry systems that most accurately predict CAs.

Neural Speech Tracking Highlights the Importance of Visual Speech in Multi-speaker Situations.

Visual speech plays a powerful role in facilitating auditory speech processing and has been a publicly noticed topic with the wide usage of face masks during the COVID-19 pandemic. In a previous magnetoencephalography study, we showed that occluding the mouth area significantly impairs neural speech tracking. To rule out the possibility that this deterioration is because of degraded sound quality, in the present follow-up study, we presented participants with audiovisual (AV) and audio-only (A) speech.

Exploring the heterogeneous transcriptional response of the CNS to systemic LPS and Poly(I:C).

Peripheral contact to pathogen-associated molecular patterns (PAMPs) evokes a systemic innate immune response which is rapidly relayed to the central nervous system (CNS). The remarkable cellular heterogeneity of the CNS poses a significant challenge to the study of cell type and stimulus dependent responses of neural cells during acute inflammation. Here we utilized single nuclei RNA sequencing (snRNAseq), serum proteome profiling and primary cell culture methods to systematically compare the acute response of the mammalian brain to the bacterial PAMP lipopolysaccharide (LPS) and the viral PAMP polyinosinic:polycytidylic acid (Poly(I:C)), at single cell resolution.