Neurology

Mandibular Symphysis Bone for Alveolar Grafting: 3D Outcomes and Donor Site Regeneration in Patients With Unilateral Cleft Lip and Alveolus.

ObjectiveThe mandibular symphysis is a donor site for alveolar bone grafting (ABG) in patients with cleft lip and/or palate, offering reduced morbidity. This prospective study evaluated ABG outcomes and donor site regeneration using artificial intelligence (AI)-powered 3-dimensional (3D) tools.DesignProspective study.SettingTertiary-level craniofacial hospital.Patients, ParticipantsTwenty-one pati...

Real-time photoelectric sensing of edaravone for therapeutic efficacy in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) requires precise therapeutic monitoring of Edaravone, but current methods lack real-time capability. Herein, we developed a photoelectrochemical (PEC) sensor using a Bi4Ti3O12/BiOBr heterojunction for ultrasensitive Edaravone detection. The heterojunction interface enables Type II band alignment, facilitating efficient charge separation through electron transfer...

Unconscious elevated bottom-up processing in depression: Insights from dynamic causal modeling with EEG and fMRI.

INTRODUCTION: MRI compatible EEG systems enable simultaneous EEG-fMRI data assessment, which provides high spatial and high temporal resolution of neu...

Revealing EEG signatures of intervention in disorder of consciousness using artificial intelligence: methodology and feasibility.

BACKGROUND AND OBJECTIVE: Electroencephalography (EEG) is a crucial tool for monitoring recovery in patients with disorders of consciousness (DOC) aft...

Neurovista: A bidirectional masked cross-Modal fusion network for robust EEG-to-Image decoding.

Electroencephalography (EEG)-based visual decoding has significant potential in brain-computer interfaces but faces substantial challenges due to nois...

Digital twins in stroke rehabilitation: a scoping review of objectives, data sources, mechanisms, outcomes, and desirable properties.

BACKGROUND: Digital Twins (DTs) have transitioned from theory to reality, with growing applications in healthcare. Data generated by technologies (e.g...

Swallowing Dysfunction in Stroke: The Role of Nurses and Rehabilitation Strategies Across Recovery Phases.

BACKGROUND: Swallowing dysfunction is a common consequence of neurological disorders such as stroke, and may lead to malnutrition, aspiration, and red...

TurkerPat: EEG-Based detection of hunger, thirst, and nicotine withdrawal.

BACKGROUND: One of the primary objectives of neuroscience is to gather information from the brain. Therefore, brain data are crucial for understanding...

Single-cell resolution spatial transcriptomic signature of the retrosplenial cortex during memory consolidation.

The retrosplenial cortex (RSC) is a critical brain region that is activated during spatial memory tasks and plays a crucial role in the consolidation ...

Multiomic insights into the MPO-mediated NET formation pathway in alcohol-induced epilepsy risk.

Epilepsy is a highly prevalent chronic central nervous system disorder that imposes substantial societal and economic burdens. Inconsistent associatio...

Precision medicine in orthopaedics: A review of current technologies and future directions.

PURPOSE: To synthesise the paradigm shift towards precision medicine in orthopaedics, where individual anatomical, biomechanical, molecular and kinema...

Subgrouping non-specific low back pain based on spinal marker trajectory data: An unsupervised machine learning approach.

BACKGROUND: Non-specific low back pain (LBP) is a heterogeneous condition. Therefore, it is important to investigate whether clinically feasible asses...

The ICeX framework: Brain age estimation from thalamic nuclei with conformalized and eXplainable random forest regression.

BACKGROUND AND OBJECTIVE: Accurate estimation of brain age is essential to identify deviations from typical aging trajectories, which may signal early...

Multi-omics technologies: Novel tools and methods for assessing nerve injury and regeneration.

Recently, with the rapid advancement of multi-omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, new tools and app...

From Big to Small: Emerging Methods for Enhancing Precision Psychiatry Through Transfer Learning.

Identifying reliable links between individual differences in neurobiological features and differences in symptom profiles or treatment outcomes is a p...

Deep machine learning methods for Parkinson's disease diagnosis: a new direction in decision-making systems.

Parkinson's disease (PD) is a progressive neurodegenerative disorder primarily characterized by the gradual loss of dopamine-producing neurons in the ...

Systematic post-translational modification genome wide identifies therapeutic targets for Alzheimer's disease: evidence from multi-cohort analysis.

BACKGROUND: The rapid increase in the incidence of Alzheimer's disease (AD) has raised concerns, given its profound effects on both society and the ec...

MSDA-Net: Multiscale Spatiotemporal Dual-Attention Network for EEG-Based Driver Fatigue Detection.

Driver fatigue poses a severe risk to road safety, contributing to approximately 20% of fatal accidents worldwide. While EEG signals are the gold stan...

Using precision medicine methods to identify disease stages for chronic limb-threatening ischemia in participants of the BEST-CLI trial.

BACKGROUND: Chronic limb-threatening ischemia (CLTI), the most severe form of peripheral artery disease, is associated with a high risk of limb loss. ...

Integrating structural and functional brain features to classify major depressive disorder: a multi modal approach.

Major Depressive Disorder (MDD) is a common mental disorder that markedly impairs psychosocial functioning and quality of life. Multi-modal fusion met...