Neurology

Molecular Characterization and Immune Modulation of Schwann Cells in Vestibular Schwannoma.

Vestibular schwannoma (VS) is a benign tumor originating from the vestibular nerve, and its complex tumor microenvironment presents significant challenges for research. This study employs single-cell transcriptome sequencing to comprehensively investigate the molecular characteristics of Schwann cells within VS and their potential immunoregulatory roles in the tumor microenvironment. We identified...

Evolution of the Neurometabolic Cascade of Traumatic Brain Injury.

Since the original descriptions by Giza and Hovda of the acute neurometabolic cascade of concussion 25 years ago, there has been a broad evolution in the understanding of concussion and other types of traumatic brain injuries (TBI) to include not only acute, neuro, and metabolic aspects of pathophysiology but also the impact and risk of TBI on numerous molecular and cellular processes, neural netw...

MIF-MAPMS: Enhancing identification of myelin autoantigenic peptides in multiple sclerosis through multimodal information fusion.

Multiple sclerosis (MS) arises from an autoimmune response in which the immune system erroneously targets myelin autoantigens within the central nervo...

Predictive Modeling of the Need for Tracheostomy after Traumatic Cervical Spinal Cord Injury Using Machine Learning.

PURPOSE: Traumatic cervical spinal cord injury (TCSCI) frequently necessitates mechanical ventilation, and early tracheostomy has been shown to reduce...

AI-assisted VMAT planning incorporating deep learning-based dose prediction for head and neck cancer: feasibility of quality standardization and human intervention for irregular cases.

BACKGROUND: Volumetric-modulated arc therapy (VMAT) represents a standard of care for head and neck cancer (HNC). However, treatment plan quality depe...

Prediction Model for Mild Cognitive Impairment in Older Chinese Patients With Cerebral Small Vessel Disease Based on XGBoost Algorithms and Shapley Additive Explanations.

OBJECTIVE: This study aims to evaluate cognitive function in patients with Cerebral Small Vessel Disease (CSVD) and investigate its association with v...

Hexagonal Hollow-Core Photonic Crystal Fiber for High-Sensitivity Terahertz Glucose Detection.

Diabetes mellitus is a rapidly escalating global health concern, often leading to severe complications such as neuropathy, vision impairment, vascular...

[Care Transformation: The AI- and Data-Driven Shift From Reactive to Proactive and Predictive Care].

With global population aging and the increasing prevalence of chronic diseases, the traditional reactive medical model, which focuses on post-illness ...

Classification of tau status with machine learning models in amyloid-positive cohorts.

INTRODUCTION: Although tau positron emission tomography (PET) imaging is effective for staging tau pathology, it is limited clinically by cost and ava...

Bulk and single-cell RNA-seq analyses characterize a DBP-related circadian signature in ischemic stroke.

Circadian rhythm disruption is associated with ischemic stroke outcomes, yet the roles of circadian genes in stroke pathology remain unclear. This stu...

Machine-Learning-Based Evaluation of the Prognostic Significance of the Non-High-Density Lipoprotein to High-Density Lipoprotein Cholesterol Ratio in Critical Ischemic Stroke.

BACKGROUND This study examined associations of the non-high-density lipoprotein to high-density lipoprotein cholesterol ratio (NHHR) with short-term (...

Artificial intelligence in retinal imaging for early Alzheimer's disease detection: A review.

BackgroundAlzheimer's disease (AD) is a progressive neurodegenerative disorder that necessitates early, accessible, and non-invasive diagnostic method...

The role of catastrophizing in anxiety and depression symptom scores among knee osteoarthritis patients: a multimodal assessment with EEG and machine learning.

To examine dimensional associations between anxiety- and depression-related symptom severity, pain catastrophizing, and resting-state EEG features in ...

Predicting stroke risk using retinal imaging with artificial intelligence: a scoping review of current evidence.

BACKGROUND: Stroke remains a leading cause of mortality and long-term disability worldwide, while currently used clinical risk prediction tools demons...

Diagnostic accuracy of image-based deep learning for glaucomatous optic neuropathy detection: a systematic review and meta-analysis.

BACKGROUND: Several studies have explored the use of deep learning (DL) algorithms based on fundus photography (FP) and optical coherence tomography (...

Multimodal Management of Pain in Oral Squamous Cell Carcinoma: A Mechanism-Based Approach.

PURPOSE OF REVIEW: Oral squamous cell carcinoma (OSCC) is frequently associated with severe nociceptive and neuropathic pain that adversely affects pa...

Artificial intelligence for early diagnosis of mild cognitive impairment: A scoping review comparing diagnostic accuracy with physician performance.

BACKGROUND: Mild cognitive impairment (MCI) represents a clinically critical and heterogeneous syndrome characterized by cognitive decline exceeding n...

Adaptive intrathecal nanorobotics in mice and nonhuman primates for navigated CNS therapy.

Intrathecal delivery for central nervous system (CNS) therapy lacks spatiotemporal control due to spinal canal anatomical constraints, especially at h...

Accuracy of Machine Learning Algorithms Based on Electroencephalogram in Sleep Apnea Detection: Systematic Review and Meta-Analysis.

BACKGROUND: Sleep apnea (SA) is a serious sleep disorder, and its diagnostic gold standard, polysomnography, is costly and time-consuming. Electroence...

Mental simulation practices in stroke rehabilitation reorganize brain connectivity: a systematic review.

BACKGROUND AND PURPOSE: Stroke is a leading cause of disability, associated with impaired motor function and brain connectivity. Mental Simulation Pra...