Leukemia

Proliferative activity of a blend of Echinacea angustifolia and Echinacea purpurea root extracts in human vein epithelial, HeLa, and QBC-939 cell lines, but not in Beas-2b cell lines.

Echinacea is used for its immunostimulating properties and may have a role in modulating adverse immune effects of chemotherapy (i.e., use of 5-fluorouracil (5-FU); fluorouracil and its immunosuppressive effect). Patients may seek herbal remedies such as Echinacea (Echinacea angustifolia and Echinacea purpurea) for immune stimulation. Echinacea extracts have been prescribed to supplement cancer ch...

HemOnc.org: A Collaborative Online Knowledge Platform for Oncology Professionals.

PURPOSE: Cancer care involves extensive knowledge about numerous chemotherapy drugs and chemotherapy regimens. This information is constantly evolving, and there has been no freely available, comprehensive, centralized repository of chemotherapy information to date.

Colored Traveling Salesman Problem.

The multiple traveling salesman problem (MTSP) is an important combinatorial optimization problem. It has been widely and successfully applied to the ...

Integrating GO and KEGG terms to characterize and predict acute myeloid leukemia-related genes.

BACKGROUND/OBJECTIVE: Acute myeloid leukemia (AML) is a progressive and malignant cancer of myelogenous blood cells, which disturbs the production of ...

Accept/decline decision module for the liver simulated allocation model.

Simulated allocation models (SAMs) are used to evaluate organ allocation policies. An important component of SAMs is a module that decides whether eac...

An Integrative Computational Approach to Predict Viral Epitopes by Targeting the MHC-TCR Complexation

T-cell immunity acts as a major defense system against controlling viral infections in vertebrates. During viral entry, innate immune cells degrade th...

RECON infers regions of interest from H&E images and reconstructs whole-slide molecular profiles at single-cell resolution

Spatial omics technologies resolve molecular expression and spatial architecture at single-cell resolution, but profiling whole slides remains costly....

Where Identity Lives: Localized, Retain-Free Identity Unlearning in Multimodal Large Language Models

Removing a specific individual's information from multimodal large language models (MLLMs) is often needed after deployment, but existing methods rely...

A closed-loop reinforcement learning framework for rapid compound directed optimization

Generative artificial intelligence (AI) holds transformative potential for drug discovery, yet existing architectures typically operate in open loops ...

Deep Learning Segmentation of Diffusion-Weighted MRI Acute Ischaemic Stroke: A Pragmatic Evaluation Across Three Datasets

Objective: Diffusion-weighted MRI (DWI-MRI) is the gold standard for visualizing and quantifying acute ischaemic stroke (AIS). Although deep learning ...

Cell type-resolved chromatin accessibility clocks for brain aging

Aging is a progressive decline in biological function that is proposed to be driven by the accumulation of epigenetic noise and the loss of epigenetic...

Glucagon-like peptide-1 receptor agonist initiation and risk of clinically recorded Alzheimer's disease-type dementia in older adults with type 2 diabetes: a target trial emulation using causal machine learning

Background Glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 (SGLT2) inhibitors are increasingly used for type 2 di...

Evaluating computational assays of chronic fatigue using UK Biobank data

Chronic fatigue, characterized by persistent physical and/or mental exhaustion, is a frequent and debilitating symptom in medicine. Despite its impact...

Local retraining mitigates domain shift in sepsis prediction: Lessons from translating a neonatal model to mixed intensive care data

Background: Machine learning models leveraging electronic health records (EHRs) can support earlier detection of sepsis in intensive care units (ICUs)...

bulk2scDiff: A Pseudobulk-Conditioned Diffusion Model for Bulk-to-Single-Cell RNASeq Generation

Bulk RNA sequencing remains the predominant profiling strategy for large clinical cohorts, but it aggregates transcriptional signals across cell popul...

Placental derived Extracellular Matrix Supports multi-lineage cell attachment and nuclear remodeling revealed by quantitative imaging

Decellularized extracellular matrix (dECM) scaffolds are increasingly used in regenerative medicine, yet the extent to which processed placental dECM ...

Feasibility of a 2-Minute Multi-Echo UTE Acquisition for Simultaneous CT-Like Bone-Weighted Imaging and Quantitative T2* Mapping of Short-T2 Tissue

Purpose: To determine the feasibility of a 2-minute multi-echo UTE (mecho-UTE) for CT-like bone-weighted contrast and T2* quantification of tissues wi...

Retrieval-Augmented Large Language Models for Clinically Aligned Adverse Event Coding in Acute Myeloid Leukemia Clinical Trials

Background: Adverse event (AE) coding is essential for safety monitoring in oncology clinical trials, particularly in acute myeloid leukemia (AML), wh...

Preoperative Prediction of Residual Cancer Burden After Neoadjuvant Chemotherapy in Breast Cancer: A Multimodal Machine Learning Approach and Implications for Clinical Decision Support

Background. Residual cancer burden (RCB) after neoadjuvant chemotherapy (NAC) offers finer prognostic stratification than binary pathologic complete r...

Deep Learning-Based Classification of Bone Lesions on CT Scans of Metastatic Spine Disease Patients: A 3D-Convolutional Neural Network Approach

Purpose: Clinical assessment of vertebral lesion quality (osteolytic, osteoblastic, mixed) remains subjective, with limited interobserver reliability....