Myeloma

Advancing child health: forecasting the next great research achievements.

Advances in pediatric research have improved the lives of infants, children, adolescents, and societ...

Cyclosporine in hematological disorders: mechanisms, clinical practice and emerging advances.

Cyclosporine A (CsA) functions as a calcineurin inhibitor that perturbs T cell activation via calcin...

Wide-range and multi-target trace-level quantification of renal biomarkers in serum via a chromatography-SERS-AI platform.

BACKGROUND: Trace blood analysis (TBA) holds irreplaceable value in chronic disease management, elde...

Machine Learning Model Predicts Clinical Adverse Events of Small Molecule Kinase Inhibitors in Cancer Patients Using On-/Off-Target Engagement and Tissue Selectivity.

Adverse events (AEs) of small molecule kinase inhibitors (SMKIs) at therapeutic doses in cancer pati...

Whole-body reduced-dose dual-energy CT with deep learning image reconstruction for detection of osteolytic lesions in multiple myeloma.

INTRODUCTION: Deep learning image reconstruction (DLIR) has been incorporated into dual-energy CT (D...

KIF23 in disease pathogenesis and its therapeutic and diagnostic potential.

BACKGROUND: Kinesin family member 23 (KIF23) is a microtubule-dependent motor protein essential for ...

Ontology-Aligned Representation of Adverse Events in a Multiple Myeloma Clinical Trial.

To explore the potential of ontologies in improving adverse event identification, we developed ontol...

Circadian Deregulation in Multiple Myeloma: BMAL1/CLOCK Expression Patterns and Diagnostic Performance.

BACKGROUND: Circadian clock disruption has emerged as a relevant axis in cancer; however, the expres...

Few-shot learning-driven discovery of Lutein suppresses Th1-mediated inflammation via glucose metabolism.

The discovery of selective immunosuppressants for T cell-mediated diseases like Ulcerative Colitis (...

Predicting anemia treatment outcomes in maintenance hemodialysis patients using multiple machine learning models.

BACKGROUND: Based on machine learning prediction models, we explored the anemia treatment attainment...

Unsupervised risk factor identification across cancer types and data modalities via explainable artificial intelligence.

Risk stratification is an important tool in clinical decision-making, yet current approaches often f...

The negative sigmoid loss for controlling false positive rate in osteolytic lesion segmentation.

Multiple Myeloma (MM) is a malignancy that is commonly associated with the development of osteolytic...

Contemporary Trends in Calcium Levels and Related Clinical Conditions: A Two Decade Analysis of U.S. National Health and Nutritional Examination Survey Data.

Ambulatory hypercalcemia is a proxy for primary hyperparathyroidism. Reports of an increased inciden...

Machine learning models for predicting childhood anemia in Mozambique: analysis from national survey data.

A deep dive into ferritin nanoparticle advancements: experimental and computational perspectives.

Ferritin, a natural iron-storage protein, has emerged as a versatile platform in nanotechnology and ...

Bridging In Silico Design and Experimental Validation: Virtual Screening and In Vitro Assessment of Biomimetic Anticancer Peptides Inspired by Horseshoe Crab Hemolymph Proteins.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality, necessitati...

Contextualizing the Patient Blood Management (PBM) Program Through the Lens of Bioethical Principles.

In an increasingly specialized medical landscape, Patient Blood Management (PBM) has emerged as a mu...

Cardiovascular toxicity of ethyl maltol exposure: a comprehensive investigation from virtual screening to experimental validation.

Ethyl maltol is a ubiquitous synthetic flavor enhancer. Despite its widespread use in foods, beverag...

Co-occurrence patterns of malnutrition indicators among children in sub-Saharan Africa.

BACKGROUND: Despite progress towards SDG2, malnutrition remains a major concern. Little is known abo...

Towards noninvasive blood count using a deep learning pipeline from bulbar conjunctiva videos.

Invasive venous blood draws remain the clinical standard for hematology, yet they are invasive, time...

HACR-Net: An Efficient hybrid attention network for MRI image super-resolution.

High-resolution Magnetic Resonance Imaging (MRI) plays an important role in clinical diagnosis and p...