Leukemia

Sorafenib nanomedicine in HCC: nano-bio interactions and combination therapies.

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, with systemic therapies offering only limited benefit. Sorafenib, the first-line multi-kinase inhibitor, is constrained by poor pharmacokinetics, dose-limiting toxicities, and the rapid emergence of resistance. Nanotechnology-based drug delivery systems (NDDS) provide promising strategies to address these...

Prediction of renal cell carcinoma: Development and validation of machine learning model.

Renal cell carcinoma (RCC) is the leading cause of urinary system morbidity and mortality. Early identification is crucial for improving RCC patient outcomes. This study aims to construct and validate an RCC prediction model for at-risk individuals using machine learning (ML) based on routine clinical data. Data from the Quanzhou First Hospital Affiliated with Fujian Medical University between Mar...

Predicting the Efficacy of Breast Cancer Neoadjuvant Chemotherapy Using Ultrasonography and Machine Learning.

OBJECTIVE: This study aimed to develop a machine learning model based on ultrasonography (US) and clinicopathological features to predict pathological...

Coriandrum sativum improves prognosis in clear cell renal cell carcinoma by targeting NEK6 to modulate the immune microenvironment: a predictive study based on network pharmacology and multi-omics analysis.

Coriandrum sativum L. (coriander) is a medicinal herb with diverse pharmacological properties, but its molecular mechanism in clear cell renal cell ca...

Rapid Single-Cell Phenotypic Antifungal Susceptibility Testing on a SlipChip Enabled by Deep Learning.

Fungal infections cause over 1.5 million deaths annually, yet current antifungal susceptibility testing (AFST) methods require 24-48 h, delaying criti...

Identifying Key Predictors of Appropriate Discharge Destinations for Older Inpatients in Acute Care: Scoping Review.

BACKGROUND: Postacute care (PAC) services are important to ensure functional recovery and provide adequate care for geriatric inpatients in acute care...

How do chronic diseases affect personal and household income? A double debiased machine learning analysis of the China health and retirement longitudinal study (CHARLS) in older adults.

OBJECTIVES: This study aimed to investigate the impacts of chronic diseases such as hypertension, dyslipidaemia and diabetes on personal and household...

Protein buffering of aneuploidy is driven by coordinated factors identified through machine learning.

Aneuploidy, a hallmark of cancer, alters chromosome copy numbers and with that the abundance of hundreds of proteins. Evidence suggests that levels of...

Artificial intelligence in idiopathic pulmonary fibrosis: advances, challenges and future directions.

Idiopathic pulmonary fibrosis (IPF) is a progressive disease of unknown aetiology, characterised by a radiological and/or morphological pattern of usu...

Investigation on the Molecular Mechanism of ORF7a Suppressing BST-2 Antiviral Activity through Structural Modeling of Their Protein-Protein Interface.

In the present work, a structural model for the protein-protein interface of bone marrow stromal cell antigen 2 (BST-2) and severe acute respiratory s...

Single-Cell Morphometrics From Hematoxylin and Eosin-Stained Images Reveals Subtype-Specific Features in Chronic Lymphocytic Leukemia.

Chronic lymphocytic leukemia (CLL) is a highly heterogeneous B-cell malignancy, spanning a spectrum from indolent conventional forms (C-CLL) to Richte...

Pathomics Signature for Prognosis and CA19-9 Interception in Pancreatic Ductal Adenocarcinoma: A Real-Life, Multi-Center Study.

Histopathological hematoxylin and eosin (H&E) slides contain valuable prognostic information for pancreatic ductal adenocarcinoma (PDAC), yet systemat...

Translational and real-world evidence of trastuzumab biosimilar CT-P6 plus pertuzumab in neoadjuvant HER2-positive early breast cancer.

BACKGROUND: Data on neoadjuvant treatment with trastuzumab biosimilars, particularly CT-P6, in combination with pertuzumab, are limited. This study ev...

SVASCilia is an open-source, deep learning-based tool for 3D analysis of cochlear hair cell stereocilia bundles.

Cochlear hair cells are essential for hearing, and their stereocilia bundles are critical for mechanotransduction. However, analyzing the 3D morpholog...

Machine learning prediction for AML based on 3D genome selected circRNA.

Acute myeloid leukemia (AML) is a clinically aggressive hematologic malignancy driven by complex genetic and epigenetic aberrations. Circular RNAs (ci...

Loss of biomechanical features reveals smooth muscle disruption and disease progression in prostate cancer.

BACKGROUND: Biomechanical features show notable heterogeneity in tumor risk stratification, yet their role in prostate cancer (PCa) progression remain...

Prediction of myeloid malignant cells in Fanconi anemia using machine learning.

Fanconi anemia (FA) is an inherited bone marrow failure syndrome with cancer predisposition. Most FA patients develop aplastic anemia during childhood...

Fibroblast-like cells accumulate late in human coronary atherosclerosis contributing to necrotic core formation.

AIMS: Proliferation of arterial smooth muscle cells (SMCs) and their modulation to alternative mesenchymal phenotypes is central to atherosclerotic le...

A prognostic signature of ferroptosis and lipid metabolism related genes predicts survival and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a common and aggressive form of cancer. There is an interplay between ferroptosis and lipid metabolism i...

scPlantAnnotate: an accurate and robust transformer-based model for plant cell type annotation.

INTRODUCTION: Accurate cell type annotation remains a major bottleneck in plant single-cell RNA sequencing (scRNA-seq), where existing tools are often...