Neurology

Pathogenic mechanism of the K141E mutation in HSPB8: Insights from smFRET and simulations.

Pathogenic mutations can have a large impact on the conformational ensemble of intrinsically disordered proteins, but revealing those effects and their physiological relevance can be challenging. We used large-scale all-atom explicit-solvent molecular dynamics simulations and single-molecule Förster resonance energy transfer (smFRET) experiments to investigate the conformational dynamics of the ch...

HyTract: Advancing tractography for neurosurgical planning with a hybrid method integrating neural networks and a path search algorithm.

The advent of advanced MRI techniques has opened up promising avenues for exploring the intricacies of brain neurophysiology, including the network of neural connections. A more comprehensive understanding of this network provides invaluable insights into the human brain's underlying structural architecture and dynamic functionalities. Consequently, determining the location of the neural fibers, k...

The analgesic mechanism of electroacupuncture at the central level for neuropathic pain: a review of studies based on animal experiments.

This article analyzes the progress of animal experiments on the analgesic mechanism of electroacupuncture (EA) at the central level for neuropathic pa...

Association between the stress hyperglycemia ratio and all-cause mortality in patients with hemorrhagic stroke: a retrospective analysis based on MIMIC-IV database.

BACKGROUND: Research on the associations between the stress hyperglycemia ratio (SHR) and adverse outcomes in patients with hemorrhagic stroke is limi...

Comparison of quality, empathy and readability of physician responses versus chatbot responses to common cerebrovascular neurosurgical questions on a social media platform.

BACKGROUND: Social media platforms are utilized by patients prior to scheduling formal consultations and also serve as a means of pursuing second opin...

An Artificial Intelligence Olfactory-Based Diagnostic Model for Parkinson's Disease Using Volatile Organic Compounds from Ear Canal Secretions.

Parkinson's Disease (PD), a frequently diagnosed neurodegenerative condition, poses a major global challenge. Early diagnosis and intervention are cru...

Soft Bioelectronic Interfaces for Continuous Peripheral Neural Signal Recording and Robust Cross-Subject Decoding.

Accurate decoding of peripheral nerve signals is essential for advancing neuroscience research, developing therapeutics for neurological disorders, an...

Brain stimulation outcome prediction in Major Depressive Disorder by deep learning models using EEG representations.

Major Depressive Disorder (MDD) is known as a widespread illness and needs a timely treatment. The treatment procedure is currently based on the trial...

Multiscale Organization of Neural Networks in a 3D Bioprinted Matrix.

The efficient establishment of in vitro neural models that accurately mimic the structural and functional connectivity of neural networks is critical ...

Operationalizing postmortem pathology-MRI association studies in Alzheimer's disease and related disorders with MRI-guided histology sampling.

Postmortem neuropathological examination, while the gold standard for diagnosing neurodegenerative diseases, often relies on limited regional sampling...

Machine learning algorithms with body fluid parameters: an interpretable framework for malignant cell screening in cerebrospinal fluid.

OBJECTIVES: This study aimed to develop and validate a machine learning (ML) model utilizing cerebrospinal fluid (CSF) body fluid parameters from hema...

Gastrointestinal microbiota and inflammasomes interplay in health and disease: a gut feeling.

The intricate interplay between the gut microbiota and the GI tract has garnered significant attention, as growing evidence has identified the inflamm...

Artificial Intelligence Augmented Cerebral Nuclear Imaging.

Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has significant potential to advance the capabilities of nucl...

Deep Learning Differentiates Papilledema, NAION, and Healthy Eyes with Unsegmented 3D OCT Volumes.

OBJECTIVE: Deep learning (DL) has been used to differentiate papilledema from healthy eyes and optic disc elevation on fundus photos. As we described ...

Unbiased Quantification of Persistent Postural and Motor Deficits Following Spinal Cord Injury in Mice.

Spinal cord injury (SCI) causes multifaceted postural and motor impairments that are challenging to quantify. Conventional behavioral tests, such as t...

Advanced predictive modeling for enhanced mortality prediction in ICU stroke patients using clinical data.

Background Stroke is second-leading cause of disability and death among adults. Approximately 17 million people suffer from a stroke annually, with ab...

A scientometric analysis of machine learning in schizophrenia neuroimaging: Trends and insights (2012-2024).

Machine learning applications in schizophrenia neuroimaging research have undergone significant evolution since 2012. However, a comprehensive sciento...

Automatic identification of Parkinsonism using clinical multi-contrast brain MRI: a large self-supervised vision foundation model strategy.

BACKGROUND: Valid non-invasive biomarkers for Parkinson's disease (PD) and Parkinson-plus syndrome (PPS) are urgently needed. Based on our recent self...

Radiomic and proteomic signatures of body mass index on brain ageing and Alzheimer's-like patterns of brain atrophy.

BACKGROUND: The impact of high body mass index (BMI) states and associated proteomic factors on brain ageing and Alzheimer's disease (AD) remains uncl...

An adaptive frequency partitioning framework for epileptic seizure detection using TransseizNet.

OBJECTIVES: Epilepsy is a disorder causing repeated seizures because of unusual brain activity recorded using electroencephalography. Nevertheless, co...