Oncology/Hematology

Search for Specific Inhibitors Targeting Type IA Topoisomerases.

The type IA topoisomerase subfamily includes bacterial topoisomerase I and topoisomerase III encoded by topA and topB genes, reverse gyrase found in thermophilic bacteria and archaea, as well as eukaryotic topoisomerase III. Type IA topoisomerases also act on RNA as substrate. Important functions in neurological development have been demonstrated for human TOP3B. Type IA topoisomerase present in a...

Crafting an innovative one health-aligned machine learning framework for neglected tropical diseases elimination.

INTRODUCTION: Strategic investment in new interventions is crucial for controlling and eliminating NTDs. However, selecting the optimal intervention combination is challenging, especially with limited resources and urgent disease transmission. Hybrid models offer a flexible framework for simulating intervention scenarios, but their use in NTDs control remains underexplored. OBJECTIVES: To propose ...

B4GALT3 as a Key Glycosyltransferase Gene in Multiple Myeloma Progression: Insights From Bioinformatics, Machine Learning, and Experimental Validation.

Glycosylation abnormalities are critical in the progression of various cancers. However, their role in the onset and prognosis of multiple myeloma (MM...

Machine learning modeling and analysis of prognostic hub genes in cervical adenocarcinoma: a multi target therapy for enhancement in immunosurveillance.

Endocervical adenocarcinoma (ECA) the fatal and intrusive subtype of cervical carcinoma is on rise from the last decade. Its improper detection leads ...

Early breast cancer detection via infrared thermography using a CNN enhanced with particle swarm optimization.

Breast cancer remains the most prevalent cause of cancer-related mortality among women worldwide, with an estimated incidence exceeding 500,000 new ca...

Predictors of frontline doublet or triplet regimen initiation in transplant-ineligible newly diagnosed multiple myeloma.

AIMS: To identify predictors for initiation of frontline doublet versus triplet therapy for transplant-ineligible newly diagnosed multiple myeloma.

Machine learning-based risk prediction model for central nervous system involvement in diffuse large B-cell lymphoma.

Accurate prediction of CNS relapse in DLBCL remains challenging despite existing models like IPI and CNS-IPI. This study aimed to develop a machine le...

Accurate and real-time brain tumour detection and classification using optimized YOLOv5 architecture.

The brain tumours originate in the brain or its surrounding structures, such as the pituitary and pineal glands, and can be benign or malignant. While...

Integrative analysis of multi-omics data and gut microbiota composition reveals prognostic subtypes and predicts immunotherapy response in colorectal cancer using machine learning.

Colorectal cancer (CRC) exhibits substantial heterogeneity in molecular subtypes and clinical outcomes. We performed an integrative analysis of multi-...

Development and validation of a machine learning-based nomogram for survival prediction of patients with hilar cholangiocarcinoma after curative-intent resection.

Hilar cholangiocarcinoma (hCCA), a rare cancer of the biliary system, has a poor prognosis. This study aimed to investigate the risk factors affecting...

Development and validation of a prognostic model for predicting survival and immunotherapy benefits in melanoma based on metabolism-relevant genes.

Skin cutaneous melanoma (SKCM) is a fatal form of skin cancer. Metabolism-related genes (MRGs) comprise a group of genes that possess the ability to m...

AI-driven robotic surgery in oncology: advancing precision, personalization, and patient outcomes.

Artificial intelligence (AI) integrated with robotic systems is transforming oncologic surgery by significantly improving precision, safety, and perso...

Cost-effectiveness analysis of artificial intelligence (AI) in earlier detection of liver lesions in cirrhotic patients at risk of hepatocellular carcinoma in Italy.

BACKGROUND: Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the third most common cause of cancer-related death. Cirrhosi...

Diffusion-weighted imaging in rectal cancer MRI from theory to practice.

Diffusion-weighted imaging (DWI) has become a cornerstone of high-resolution rectal MRI, providing critical functional information that complements T2...

SLC3A2 as a key anoikis-related gene for prognosis and tumor microenvironment remodeling in melanoma.

OBJECTIVE: Anoikis, a form of programmed cell death triggered by detachment from the extracellular matrix, plays a crucial role in metastasis and immu...

Machine Learning for Genomic Profiling and Drug Discovery in Personalised Lung Cancer Therapeutics.

Lung cancer is a prevalent and lethal malignancy characterised by the uncontrolled growth of abnormal cells in lung tissues, often leading to function...

Size-Specific Predictors for Malignancy Risk in Follicular Thyroid Neoplasms: Machine Learning Analysis.

BACKGROUND: Surgeons often face challenges in distinguishing between benign and malignant follicular thyroid neoplasms (FTNs), particularly small tumo...

SPP1 promotes malignant characteristics and drug resistance in hepatocellular carcinoma by activating fatty acid metabolic pathway.

Hepatocellular carcinoma (HCC) progression and prognosis are influenced by various molecular markers. This study aimed to identify the hub gene associ...

Solving Mazes of Organelle-Targeted Therapies with DNA Nanomachines.

Despite decades of research, cancer remains a growing global health challenge. Nanomaterials-based therapeutics have shown promise, but their clinical...

A Network-Driven Framework for Drug Response Precision Prediction of Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is a clonal malignancy of myeloid progenitor cells that demonstrates highly variable responses to current regimens, highl...