Strokes

MiR-138 reprograms dental pulp stem cells into GABAergic neurons via the GATAD2B/MTA3/WNTs axis for stroke treatment.

Prolonged periods of ischemia and hypoxia pose significant challenges to exogenous stem cell transplantation, including minimal cell survival, varied differentiation, and poor integration with existing neural networks. Dental pulp stem cells (DPSCs) are an important choice for stem cell treatment for their excellent potential of neural differentiation and easy accessibility. Stable overexpression ...

Pre-interventional transesophageal echocardiography as a reliable predictor of residual shunt following patent foramen ovale closure.

BACKGROUND: Closure of a patent foramen ovale (PFO) is an effective strategy in the prevention of recurrent stroke after cryptogenic stroke. Residual shunt (RS) is a common issue following PFO closure and may affect safety and efficacy. Transesophageal echocardiography (TEE) is the key diagnostic tool, but standardized assessment of morphological parameters to prevent RS remains challenging. AIMS:...

Comparison of the effects of robot-assisted gait training using FES versus virtual reality for stroke patients. A randomized clinical trial.

BACKGROUND: Robot-assisted gait training is becoming an effective alternative to therapist-assisted gait training in stroke rehabilitation. This metho...

Assessment and management of portal hypertension in patients with MASLD: advances and caveats.

INTRODUCTION: Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly gaining relevance both as a public health issue and a c...

Inflammatory, fibrotic and endothelial biomarker profiles in COVID-19 patients during and following hospitalization.

Survivors of severe COVID-19 often suffer from long-term respiratory issues, but the molecular drivers of this damage remain unclear. This study explo...

A machine learning model reveals invisible microscopic variation in acute ischaemic stroke (≤ 6 h) with non-contrast computed tomography.

BACKGROUND: In most medical centers, particularly in primary hospitals, non-contrast computed tomography (NCCT) serves as the primary imaging modality...

Evolution of CT perfusion software in stroke imaging: from deconvolution to artificial intelligence.

Computed tomography perfusion (CTP) represents one of the main determinants in the decision-making strategy of stroke patients, being very useful in t...

Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients.

BACKGROUND: Hypertension (HTN) is a complex condition with significant heterogeneity in presentation and treatment response. Identifying distinct subp...

Enhancing stroke risk prediction through class balancing and data augmentation with CBDA-ResNet50.

Accurate prediction of stroke risk at an early stage is essential for timely intervention and prevention, especially given the serious health conseque...

Integrating Machine Learning into Myositis Research: a Systematic Review.

Idiopathic inflammatory myopathies (IIM) are a group of autoimmune rheumatic diseases characterized by proximal muscle weakness and extra muscular man...

Artificial intelligence and digital twins for the personalised prediction of hypertension risk.

Hypertension is a significant global health challenge, contributing substantially to morbidity and mortality through its association with various card...

Feature selection using metaheuristics to predict annual amyotrophic lateral sclerosis progression.

OBJECTIVE: Amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disease with no curative treatment and affecting motor neurons, leads ...

Deep Learning based Collateral Scoring on Multi-Phase CTA in patients with acute ischemic stroke in MCA region.

BACKGROUND AND PURPOSE: Collateral circulation is a critical determinant of clinical outcomes in acute ischemic stroke (AIS) patients and plays a key ...

Correction to "Deep Learning Enhanced Near Infrared-II Imaging and Image-Guided Small Interfering Ribonucleic Acid Therapy of Ischemic Stroke".

An enhanced fusion of transfer learning models with optimization based clinical diagnosis of lung and colon cancer using biomedical imaging.

Lung and colon cancers (LCC) are among the foremost reasons for human death and disease. Early analysis of this disorder contains various tests, namel...

Effects of device-assisted practice of activities of daily living in a close-to-normal pattern on upper extremity motor recovery in individuals with moderate to severe stroke: study protocol of a randomized control trial.

BACKGROUND: The majority of individuals with chronic stroke have residual upper extremity (UE) disability which they cite as their greatest barrier to...

Exploratory development of human-machine interaction strategies for post-stroke upper-limb rehabilitation.

BACKGROUND: Stroke and its related complications, place significant burdens on human society in the twenty-first century, and lead to substantial dema...

Machine learning-based prognostic prediction for acute ischemic stroke using whole-brain and infarct multi-PLD ASL radiomics.

INTRODUCTION: Accurate early prognostic prediction for acute ischemic stroke (AIS) is essential for guiding personalized treatment. This study aimed t...

Network-based machine learning reveals cardiometabolic multimorbidity patterns and modifiable lifestyle factors: a community-focused analysis of NHANES 2015-2018.

Cardiometabolic Multimorbidity (CMM) has emerged as one of the primary threats to human health globally due to its high incidence, disability, and mor...

Beyond Recanalization: Machine Learning-Based Insights into Post-Thrombectomy Vascular Morphology in Stroke Patients.

Many stroke patients have poor outcomes despite successful endovascular therapy (EVT). We hypothesized that machine learning (ML)-based analysis of va...