Oncology/Hematology

Shortcoming of serum B-cell maturation antigen measurement by enzyme-linked immunosorbent assay in one laboratory's experience: Unsatisfactory assay reproducibility.

INTRODUCTION: Serum protein electrophoresis and serum free light chain (SFLC) assays are standard methods for monitoring patients with multiple myeloma (MM). However, patients with non-secretory MM often require invasive bone marrow biopsies to monitor treatment response and disease progression. Recently, serum soluble B-cell maturation antigen (sBCMA) has been proposed as an alternative biomarker...

Mechanisms and Applications of Apolipoproteins and Apolipoprotein Mimetic Peptides: Common Pathways in Cardiovascular Disease and Cancer.

Apolipoproteins are the defining functional component of lipoproteins and play critical roles in lipid transport and metabolism. High-density lipoprotein (HDL) and its primary functional constituent, apolipoprotein A-I, are of particular importance because of anti-inflammatory and antioxidant properties. Apolipoprotein mimetic peptides are short-chain amino acids designed to mimic the functions an...

Breakthroughs and challenges of organoid models for assessing cancer immunotherapy: a cutting-edge tool for advancing personalised treatments.

Organoid models are powerful tools for evaluating cancer immunotherapy that provide a more accurate representation of the tumour microenvironment (TME...

Machine learning approaches reveal methylation signatures associated with pediatric acute myeloid leukemia recurrence.

Acute myeloid leukemia (AML) is a severe hematological malignancy characterized by high recurrence rates, especially in pediatric patients, highlighti...

Integrative bioinformatics and machine learning identify key crosstalk genes and immune interactions in head and neck cancer and Hodgkin lymphoma.

Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive malignancy with complex molecular underpinnings. Hodgkin lymphoma (HL), another d...

Stacking classifiers based on integrated machine learning model: fusion of CT radiomics and clinical biomarkers to predict lymph node metastasis in locally advanced gastric cancer patients after neoadjuvant chemotherapy.

BACKGROUND: The early prediction of lymph node positivity (LN+) after neoadjuvant chemotherapy (NAC) is crucial for optimizing individualized treatmen...

Deep learning-based computational approach for predicting ncRNAs-disease associations in metaplastic breast cancer diagnosis.

Non-coding RNAs (ncRNAs) play a crucial role in breast cancer progression, necessitating advanced computational approaches for precise disease classif...

Enhancing biomarker based oncology trial matching using large language models.

Clinical trials are an essential component of drug development for new cancer treatments, yet the information required to determine a patient's eligib...

Identification of Npas4 as a biomarker for CICI by transcriptomics combined with bioinformatics and machine learning approaches.

Chemotherapy is one of the most successful strategies for treating cancer. Unfortunately, up to 70 % of cancer survivors develop cognitive impairment ...

A biorefinery approach for the simultaneous obtention of essential oils, organic acids and polyphenols from citrus peels: Phytochemical characterization and bioactive potential.

This investigation evaluates the valorization of citrus peels (lemon, tangerine, and orange) to recover both on-polar and polar fractions simultaneous...

Artificial intelligence and colorectal neoplasia detection performances in patients with positive fecal immunochemical test: Meta-analysis and systematic review.

OBJECTIVES: The combination of fecal immunochemical test (FIT) followed by colonoscopy has established itself as one of the preferred population-based...

Multimodal AI model for preoperative prediction of axillary lymph node metastasis in breast cancer using whole slide images.

In breast cancer management, predicting axillary lymph node (ALN) metastasis using whole-slide images (WSIs) of primary tumor biopsies is a challengin...

New Targets for Imaging in Nuclear Medicine.

Nuclear medicine is rapidly evolving with new molecular imaging targets and advanced computational tools that promise to enhance diagnostic precision ...

Adaptive Cross-Feature Fusion Network With Inconsistency Guidance for Multi-Modal Brain Tumor Segmentation.

In the context of contemporary artificial intelligence, increasing deep learning (DL) based segmentation methods have been recently proposed for brain...

Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma From Multi-Sequence Magnetic Resonance Imaging Based on Deep Fusion Representation Learning.

Recent studies have identified microvascular invasion (MVI) as the most vital independent biomarker associated with early tumor recurrence. With advan...

Frozen Large-Scale Pretrained Vision-Language Models are the Effective Foundational Backbone for Multimodal Breast Cancer Prediction.

Breast cancer is a pervasive global health concern among women. Leveraging multimodal data from enterprise patient databases-including Picture Archivi...

Progressive Distillation With Optimal Transport for Federated Incomplete Multi-Modal Learning of Brain Tumor Segmentation.

Multi-modal Magnetic Resonance Imaging (MRI) provide sufficient complementary information for brain tumor segmentation, however, most current approach...

MHFNet: A Multimodal Hybrid-Embedding Fusion Network for Automatic Sleep Staging.

Scoring sleep stages is essential for evaluating the status of sleep continuity and comprehending its structure. Despite previous attempts, automating...

Development and Validation of a Novel Prediction Model for Hearing Loss From Cisplatin Chemotherapy.

PURPOSE: Cisplatin treats many common tumors but causes permanent and debilitating hearing loss (HL). The objective of this study was to develop and e...

An efficient patient's response predicting system using multi-scale dilated ensemble network framework with optimization strategy.

The forecasting of a patient's response to radiotherapy and the likelihood of experiencing harmful long-term health impacts would considerably enhance...