Applying machine learning techniques to predict the risk of distant metastasis from gastric cancer: a real world retrospective study.

Background: Distant metastasis of gastric cancer can seriously affect the treatment strategy of gastric cancer patients, so it is essential to identify patients at high risk of distant metastasis of gastric cancer earlier.

Method: In this study, we retrospectively collected research data from 18,472 gastric cancer patients from the SEER database. We applied six machine learning algorithms to construct a model that can predict distant metastasis of gastric cancer.

Fluorinated chitosan mediated transepithelial delivery of sanguinarine-loaded platinum (IV) prodrug for intravesical instillation therapy of muscle-invasive bladder cancer.

Cisplatin-based neoadjuvant chemotherapy is first-line strategy to inhibit progression and metastasis of muscle-invasive bladder cancer (MIBC). However, its clinical efficacy is often limited by drug resistance and severe systemic side effects, highlighting the urgent need for innovative therapeutic approaches. Despite advancements in cisplatin-based regimens, research on intravesical cisplatin delivery systems remains scarce.

Enhanced phase prediction of high-entropy alloys through machine learning and data augmentation.

The phase structure information of high-entropy alloys (HEAs) is critical for their design and application, as different phase configurations are associated with distinct chemical and physical properties. However, the broad range of elements in HEAs presents significant challenges for precise experimental design and rational theoretical modeling and simulation. To address these challenges, machine learning (ML) methods have emerged as powerful tools for phase structure prediction.

Ononin Inhibits Tumor Bone Metastasis and Osteoclastogenesis By Targeting Mitogen-Activated Protein Kinase Pathway in Breast Cancer.

Breast cancer (BC) often spreads to bones, leading to bone metastasis (BM). Current targeted therapies have limited effectiveness in the treatment of this condition. Osteoclasts, which contribute to bone destruction, are crucial in supporting tumor cell growth in the bones.

Helicid: A novel Anti-Staphylococcus aureus adjuvant.

Staphylocoagulase (Coa) plays a critical role in the pathogenicity of Staphylococcus aureus (S. aureus). The present study was undertaken to investigate the underlying mechanism which helicid (HEL) suppressed the virulence factor Coa, as well as to assess the synergistic inhibitory effects of HEL in conjunction with antibiotics, thereby establishing the potential of HEL as an antibacterial adjuvant.

Magnetic-Powered Spora Lygodii Microrobots Loaded with Doxorubicin for Active and Targeted Therapy of Bladder Cancer.

Background And Purpose: Bladder cancer has high recurrence rates despite standard treatments, necessitating innovative therapeutic approaches. This study introduces magnetically powered microrobots utilizing Traditional Chinese Medicine (TCM) Spora Lygodii (SL) encapsulated with Doxorubicin (DOX) and FeO nanoparticles (Fe/DOX@SL) for targeted therapy.

Methods: FeO nanoparticles were synthesized via co-precipitation and combined with SL spores and DOX through dip-coating to form Fe/DOX@SL microrobots.

A new perspective on GC-MS urinary metabolomics analysis and efficient risk assessment of urolithiasis: morning urine organic acid profiles.

Introduction: Urolithiasis is characterized by a high morbidity and recurrence rate, primarily attributed to metabolic disorders. The identification of more metabolic biomarkers would provide valuable insights into the etiology of stone formation and the assessment of disease risk. The present study aimed to seek potential organic acid (OA) biomarkers from morning urine samples and explore new methods based on machine learning (ML) for metabolic risk prediction of urolithiasis.

Fibroblast Growth Factor Receptor 4 Promotes Triple-Negative Breast Cancer Progression via Regulating Fatty Acid Metabolism Through the AKT/RYR2 Signaling.

Background: Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Previous studies have found that fibroblast growth factor receptor 4 (FGFR4) plays a crucial role in tumor development and metastasis. However, the potential role and underlying mechanisms of FGFR4 in the progression of TNBC remain unclear.

Application and research progress of synthetic lethality in the development of anticancer therapeutic drugs.

With the tremendous success of the PARP inhibitor olaparib in clinical practice, synthetic lethality has become an important field for the discovery and development of anticancer drugs. More and more synthetic lethality targets have been discovered with the rapid development of biotechnology in recent years. Currently, many drug candidates that were designed and developed on the basis of the concept of synthetic lethality have entered clinical trials.

Activity-driven polymer knotting for macromolecular topology engineering.

Macromolecules can gain special properties by adopting knotted conformations, but engineering knotted macromolecules is a challenging task. Here, we unexpectedly find that knots can be efficiently generated in active polymer systems. When one end of an actively reptative polymer is anchored, it undergoes continual self-knotting as a result of intermittent giant conformation fluctuations and the outward reptative motion.

Ultrafast joule-heating-assisted O, N dual-doping of unfunctionalized carbon enhances Ru nanoparticle-catalyzed hydrogen production.

The development of a rapid and convenient strategy to regulate the surface microenvironment of inert carbon supports, along with the physicochemical properties of their supported metal nanoparticles, is essential for enhancing catalytic performance. In this study, we describe a straightforward and efficient solid-state microwave method that utilizes a household microwave oven to achieve the co-doping of oxygen and nitrogen in unfunctionalized carbon black (ONCB) using urea as a nitrogen source. The microwave solid-state treatment of commercial carbon black (CB) with urea not only introduces a significant number of heteroatomic functional groups but also substantially increases the pore size and pore volume of the matrix.

ITGB4/GNB5 axis promotes M2 macrophage reprogramming in NSCLC metastasis.

Objective: Metastasis of non-small cell lung cancer (NSCLC) is a leading cause of high mortality. In recent years, the role of M2 macrophages in promoting tumor metastasis within the tumor microenvironment has garnered increasing attention. This study aims to investigate the role and potential mechanisms of the ITGB4/GNB5 axis in regulating M2 macrophage reprogramming and influencing NSCLC metastasis.

Multi-omics analysis of the toxic effects on gill tissues of crucian carp (Carassius auratus) from chronic exposure to environmentally relevant concentrations of Di(2-ethylhexyl) phthalate (DEHP).

The pervasive use of the plasticizer di(2-ethylhexyl) phthalate (DEHP) poses potential risks to global aquatic ecosystems. This study systematically evaluated the adverse effects of chronic exposure to environmentally relevant concentrations of DEHP on gill tissues of crucian carp, utilizing histological examination, metabolomic, and transcriptomic analysis. The results demonstrated that DEHP induced significant histopathological alterations in gill tissues, with significant enrichment observed in multiple pathways associated with amino acid, hormone, lipid, and xenobiotic metabolism.

Development and Validation of a Blood-Biomarker-Based Predictive Model for HBV-Associated Hepatocellular Carcinoma.

Objective: This study aims to explore the optimal predictors of HBV-associated HCC using Lasso, and establish a prediction model.

Methods: A retrospective analysis was conducted on patients who underwent CBC and CRP testing between January 2016 and March 2024. The study population comprised 5441 cases divided into three cohorts: non-HBV-infected (1333 cases), HBV-infected (1023 cases), and HBV-associated HCC (3085 cases).

Morbidity and quality of life of totally laparoscopic versus laparoscopy-assisted distal gastrectomy for early gastric cancer: a multi-center prospective randomized controlled trial (CKLASS01).

Background: There is a paucity of confirmatory randomized controlled trials (RCTs) comparing the effectiveness of totally laparoscopic distal gastrectomy (TLDG) vs laparoscopy-assisted distal gastrectomy (LADG) for early gastric cancer (EGC).

Methods: A phase III, prospective, multi-center RCT was conducted, wherein patients (n = 442) with clinical stage I gastric cancer eligible for laparoscopic distal gastrectomy were randomized 1:1 to the TLDG or the LADG group. Postoperative morbidity and quality of life (QoL) were compared.

The state-of-the-art machine learning model for plasma protein binding prediction: Computational modeling with OCHEM and experimental validation.

Plasma protein binding (PPB) is closely related to pharmacokinetics, pharmacodynamics and drug toxicity. Existing models for predicting PPB often suffer from low prediction accuracy and poor interpretability, especially for high PPB compounds, and are most often not experimentally validated. Here, we carried out a strict data curation protocol, and applied consensus modeling to obtain a model with a coefficient of determination of 0.

EryDB: A Transcriptomic Profile Database for Erythropoiesis and Erythroid-related Diseases.

Erythropoiesis is a finely regulated and complex process that involves multiple transformations from hematopoietic stem cells to mature red blood cells at hematopoietic sites from the embryonic to the adult stages. Investigations into its molecular mechanisms have generated a wealth of expression data, including bulk and single-cell RNA sequencing data. A comprehensively integrated and well-curated erythropoiesis-specific database will greatly facilitate the mining of gene expression data and enable large-scale research of erythropoiesis and erythroid-related diseases.