Hematology

Gene delivery for cerebral neurodegenerative disorders - current advancements and limitations.

Gene delivery for neurodegenerative cerebral disorders faces formidable structural and practical challenges. The blood-brain, blood- cerebrospinal fluid (CSF), and arachnoid barriers tightly regulate molecular traffic, restrict paracellular diffusion, and actively clear xenobiotics, limiting brain penetration and retention of large molecules and nucleic acid therapeutics. Additional barriers inclu...

Next Generation Digital Morphology: Blast Preclassification in Bone Marrow Aspirates.

INTRODUCTION: Morphologic evaluation of peripheral blood (PB) smears and bone marrow aspirates (BMA) remains central to the diagnosis of acute leukemias, particularly for the identification and quantification of blasts. However, this process is time-consuming, operator-dependent, and subject to inter-observer variability. Recent advances in artificial intelligence (AI), particularly deep learning,...

A smart nutrition system for vitamin B12 deficiency management from sensing to precision intervention.

Vitamin B12 is essential for neural function, red blood cell formation, and DNA synthesis, yet its deficiency persists as a global health burden drivi...

Preoperative and intraoperative localization of small pulmonary nodules for thoracoscopic surgery: a contemporary narrative review.

For thoracoscopic resection to be successful, accurate preoperative and intraoperative localization is necessary due to the growing detection of small...

Interpretable Machine Learning for Early Risk Stratification of Carbapenem Resistance Among ICU Patients with Sterile-Site Pseudomonas aeruginosa Isolates: Development and Internal Validation Using MIMIC-IV.

OBJECTIVES: We developed and internally validated an interpretable machine learning model to stratify carbapenem-resistance probability among ICU pati...

Gut microbiome signatures discriminate deep vein thrombosis through machine learning and metabolic analysis.

Deep vein thrombosis (DVT) remains difficult to distinguish because of its often silent presentation and the limited specificity of current diagnostic...

Machine learning model for predicting rebleeding risk after endoscopic variceal ligation in esophageal variceal bleeding.

Rebleeding is a severe complication following recovery from esophageal variceal bleeding (EVB), yet robust predictive tools for assessing post-treatme...

Identifying predictive hematological biomarkers for radiation exposure by machine learning in mouse models.

BACKGROUND: Population-scale radiation exposure assessment during radiological emergencies is hindered by the slow and costly nature of current method...

AI-driven cellular immunotherapy: transforming CAR-T engineering and translation.

Chimeric antigen receptor T (CAR-T) cell therapy has demonstrated remarkable success in hematologic malignancies but faces persistent challenges in so...

From biomimicry to clinical actionability: rethinking high-shear thrombosis as a mechanobiological system.

PURPOSE OF REVIEW: Arterial thrombosis remains a leading cause of morbidity and mortality worldwide, while its mechanistic understanding and clinical ...

Engineered small extracellular vesicles in hematologic malignancies: mechanisms, therapeutic strategies, and translational challenges.

Hematologic malignancies remain among the most challenging cancers to treat due to genetic heterogeneity, clonal evolution, and therapy resistance. Ex...

Stem Cell Therapy for Traumatic Brain Injury: Translational Mechanisms, Biomarkers, and Clinical Trials.

Traumatic brain injury (TBI) is a leading cause of persistent cognitive, motor, and neuropsychiatric impairment, arising from both the initial mechani...

Artificial Intelligence-Based Risk Prediction Models for Complications After Tongue Cancer Surgery.

IMPORTANCE: Glossectomy and reconstruction for tongue tumors carries substantial risk of postoperative morbidity, yet current tools offer limited indi...

Digital Twin Applications in Diabetes Management: Scoping Review.

BACKGROUND: Digital twin (DT) systems have emerged as a promising approach in health care, enabling real-time, patient-specific virtual modeling and p...

Continuous predictive mortality risk monitoring after allogeneic hematopoietic stem cell transplantation.

Allogeneic hematopoietic stem cell transplantation remains critical for treating high-risk hematological malignancies like leukemia. Despite advances ...

Intelligent automation cognitive system for accurate malaria diagnosis using digital blood smears.

Malaria is a potentially fatal illness caused by a parasite of the genus Plasmodium that humans get by being bitten by female Anopheles mosquitoes car...

Machine learning algorithms develop a tumor-educated platelets-related gene signature to predict colorectal cancer prognosis and therapy response.

Tumor-educated platelets (TEPs) have recently emerged as an important component of liquid biopsy, yet the clinical relevance in colorectal cancer (CRC...

Applying machine learning to pharmacovigilance data: A proof-of-concept study.

AIM: Machine learning (ML) applications in pharmacovigilance remain limited and underexplored. Using data from the French National pharmacovigilance d...

Machine learning discriminates bacterial, fungal, and viral infections using temporal blood analyte dynamics in bottlenose dolphins (Tursiops truncatus).

OBJECTIVE: To determine underlying infectious disease as bacterial, fungal, or viral in origin from longitudinal assessment of biochemistry and hemato...

Clinical and laboratory characteristics associated with liver failure in hospitalized dengue patients: insights from a non-endemic region.

BACKGROUND: Dengue fever is an emerging public health issue expanding into non-endemic regions like Changsha, China. Liver involvement is a critical c...