Ovarian Cancer

HRD-Informed Digital Histology Model for Predicting Platinum Chemo-Response and Prognosis in High-Grade Serous Ovarian Cancer.

Homologous recombination deficiency (HRD) is a critical biomarker in high-grade serous ovarian cancer for the clinical benefit from platinum-based chemotherapy and poly polymerase inhibitors, but molecular testing is costly, time-consuming, and limited by tissue requirements. In this study, we introduce dPathHRD (digital Pathological assessment of Homologous Recombination Deficiency), a deep learn...

Optimizing Prediction of Chemical Bonds in Interfacial Dynamics through Local Uncertainty Estimates with Neural Network Ensembles.

We present a framework for data-efficient training of machine-learning interatomic potentials for interfacial chemistry, especially heterogeneous catalytic systems. We establish strategies for density functional theory training data generation consisting of procedurally generated bulk, surface, and gas-phase atomic geometries, as well as moderately randomized structures. We show how ensembles of n...

Utilization of machine learning algorithms for the identification of the RLN associated prognostic model and feature biomarkers of RLN-related subtypes in breast cancer.

BACKGROUND: Breast cancer (BC) is the most common malignancy afflicting women worldwide, yet the role of relaxin-related genes (RLN) in BC progression...

Incidence and implications of abstinence-induced recompensation in alcohol-related cirrhosis.

BACKGROUND & AIMS: Alcohol abstinence enables hepatic recompensation in patients with decompensated alcohol-related cirrhosis. This study investigated...

Integrative multi-omics and machine learning framework identifies PRDX4 as a redox-EMT regulator and predictive marker in bone-metastatic breast cancer.

Bone metastasis is a major cause of morbidity and mortality in breast cancer, yet effective prognostic models and targeted therapies remain limited. H...

iMCN: information compression-based multimodal confidence-guided fusion network for cancer survival prediction.

The rapid development of deep learning-based computational pathology and genomics has demonstrated the significant promise of effectively integrating ...

Proteomic profiling of single extracellular vesicles as a promising new approach for the diagnosis and treatment modality of advanced ovarian cancer.

This study utilized a novel Proximity Barcoding Assay to perform high-resolution proteomic profiling of individual plasma extracellular vesicles from ...

Iron Oxide-Based Surface-Enhanced Raman Spectroscopy Bioprobes for Detecting Tumor Cells in Serous Effusion.

Serous effusions, including pleural effusion and ascites, commonly occur in advanced cancers like lung and ovarian carcinomas. Detecting tumor cells i...

A Framework Integrating Single-Cell Metallomic Data in Health Effect Analysis via Quantile Features and Machine Learning.

Heavy and essential metals coexist in a cell, collectively participate in cellular biological processes, and lead to overall health consequences. Howe...

Domain adaptation, self-supervision, and generative augmentation enhance GNNs for breast cancer prediction.

Breast cancer presents substantial molecular heterogeneity, requiring accurate subtype classification, receptor-status prediction, and survival estima...

Towards interpretable prediction of recurrence risk in breast cancer using pathology foundation models.

Transcriptomic assays such as the PAM50-based ROR-P score guide recurrence risk stratification in non-metastatic, ER-positive, HER2-negative breast ca...

Performance analysis of liver segmentation using nn-UNet TotalSegmentator: Focus on atypical livers, pathologies, and variants.

RATIONALE AND OBJECTIVES: This study evaluates the accuracy of the nn-UNet TotalSegmentator (TS) by Wasserthal et al. (2023) in segmenting atypical li...

IdentifiHR predicts homologous recombination deficiency in high-grade serous ovarian carcinoma using gene expression.

BACKGROUND: Approximately half of all high-grade serous ovarian carcinomas (HGSCs) have a therapeutically targetable defect in homologous recombinatio...

Machine learning-guided identification of metastasis-associated miRNAs and their integration into a PFI-based cox risk score and nomogram.

BACKGROUND: Metastasis drives mortality in breast invasive carcinoma. We sought miRNA biomarkers that (i) discriminate metastatic potential, (ii) stra...

Deep Learning for Ultrasound-Based Auxiliary Diagnosis of Emergency Ascites.

OBJECTIVE: The Focused Assessment with Sonography for Trauma (FAST) enables rapid detection of free intraperitoneal fluid, facilitating timely managem...

Construction and validation of a screening model for minimal hepatic encephalopathy in patients with cirrhosis: A multi-center study.

BACKGROUND: Clinical practice currently lacks objective and accurate screening tools for minimal hepatic encephalopathy (MHE). Therefore, we aimed to ...

Integrated m6A reader network in acute myeloid leukemia: prognostic modeling, immune modulation, and functional validation of YTHDF3.

Emerging evidence highlights RNA N6-methyladenosine (m6A) modifications as pivotal regulators of tumorigenesis, yet the synergistic roles of m6A reade...

Deep learning-assisted SERS platform for label-free detection of celecoxib in serum using ag@Pt@porous silicon Bragg mirror composite substrate.

Celecoxib (CXB) is a non-steroidal anti-inflammatory drug used to prevent and treat arthritis. However, overdosing or improper use can cause adverse r...

Reversible temperature-induced shape transition of Pt nanoparticles supported on Al2O3.

Supported platinum catalysts are widely used in industry for hydrogenation reactions. The variations of the electronic and geometric properties of Pt ...

Development and validation of a breast cancer survival prediction model based on perioperative anesthesia-related drug target genes and analysis of immune microenvironment and drug sensitivity.

INTRODUCTION: This study aimed to create a survival prediction model for breast cancer(BC) using perioperative anesthesia - related drug target genes(...