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Development and validation of a metabolic syndrome and its components to predict the efficacy of neoadjuvant chemotherapy in breast cancer: An observational, single-center, cohort study.
Medicine (Baltimore)
January 2025
Department of Thyroid and Breast Surgery, Hebei General Hospital, Shijiazhuang, Hebei Province, China.
To assess whether metabolic syndrome can be used as a reference index to evaluate the efficacy of neoadjuvant chemotherapy treatment for breast cancer (BC). Seventy cases of female BC patients who received neoadjuvant chemotherapy treatment and surgical treatment at the Glandular Surgery Department of Hebei Provincial People's Hospital from January 2021 to December 2023 were retrospectively collected, and clinical data such as puncture pathology were recorded. The clinical data were analyzed by 1-way analysis using the χ2 test, and further multifactorial logistic regression analysis was performed for statistically significant differences.
View Article and Find Full Text PDFdeep-AMPpred: A Deep Learning Method for Identifying Antimicrobial Peptides and Their Functional Activities.
J Chem Inf Model
January 2025
School of Information and Artificial Intelligence, Anhui Provincial Engineering Research Center for Beidou Precision Agriculture Information, Key Laboratory of Agricultural Sensors for Ministry of Agriculture and Rural Affairs, Anhui Agricultural University, Hefei, Anhui 230036, China.
Antimicrobial peptides (AMPs) are small peptides that play an important role in disease defense. As the problem of pathogen resistance caused by the misuse of antibiotics intensifies, the identification of AMPs as alternatives to antibiotics has become a hot topic. Accurately identifying AMPs using computational methods has been a key issue in the field of bioinformatics in recent years.
View Article and Find Full Text PDFValidity and Utility of a Risk Prediction Model for Wound Infection After Lower Third Molar Surgery.
Oral Dis
January 2025
Laboratory of Clinical Pharmaceutics & Therapeutics, Faculty of Pharmaceutical Sciences, Hokkaido University, Sapporo, Japan.
Objectives: To externally validate a clinical prediction model for surgical site infection (SSI) after lower third molar (L3M) surgery and evaluate its clinical usefulness.
Methods: We conducted a retrospective cohort study of patients who underwent L3M surgery at Hokkaido University Hospital. The study was designed to evaluate the historical and methodological transportability.
Population Pharmacokinetic Modeling of Certepetide in Human Subjects With Metastatic Pancreatic Ductal Adenocarcinoma.
Clin Pharmacol Drug Dev
January 2025
Department of Pharmacometrics Modeling, A2-Ai LLC, Ann Arbor, MI, USA.
Certepetide (aka LSTA1 and CEND-1) is a novel cyclic tumor-targeting internalizing arginyl glycylaspartic acid peptide being developed to treat solid tumors. Certepetide is designed to overcome existing challenges in treating solid tumors by delivering co-administered anticancer drugs into the tumor while selectively depleting immunosuppressive T cells, enhancing cytotoxic T cells in the tumor microenvironment, and inhibiting the metastatic cascade. A population pharmacokinetic (PK) analysis was conducted to characterize the concentration-time profile of patients with metastatic exocrine pancreatic cancer receiving certepetide in combination with nab-paclitaxel and gemcitabine, and to investigate the effects of clinically relevant covariates on PK parameters.
View Article and Find Full Text PDFMining functional gene modules by multi-view NMF of phenome-genome association.
BMC Genomics
January 2025
College of Software, Nankai University, TianJin, China.
Background: Mining functional gene modules from genomic data is an important step to detect gene members of pathways or other relations such as protein-protein interactions. This work explores the plausibility of detecting functional gene modules by factorizing gene-phenotype association matrix from the phenotype ontology data rather than the conventionally used gene expression data. Recently, the hierarchical structure of phenotype ontologies has not been sufficiently utilized in gene clustering while functionally related genes are consistently associated with phenotypes on the same path in phenotype ontologies.
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