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Establishment and Validation of a Machine-Learning Prediction Nomogram Based on Lymphocyte Subtyping for Intra-Abdominal Candidiasis in Septic Patients.
Clin Transl Sci
January 2025
Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
This study aimed to develop and validate a nomogram based on lymphocyte subtyping and clinical factors for the early and rapid prediction of Intra-abdominal candidiasis (IAC) in septic patients. A prospective cohort study of 633 consecutive patients diagnosed with sepsis and intra-abdominal infection (IAI) was performed. We assessed the clinical characteristics and lymphocyte subsets at the onset of IAI.
View Article and Find Full Text PDFThe IR Biotyper as a tool for typing organisms of significance for hospital epidemiology- A subject review.
Diagn Microbiol Infect Dis
December 2024
Department of Laboratory Medicine and Pathobiology, University of Toronto, 1 King's College Circle, Toronto M5S 1A8, Ontario, Canada; Division of Microbiology, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, 555 University Ave., Toronto M5G 1X8, Ontario, Canada. Electronic address:
The IR Biotyper is a novel real-time typing tool, based on a Fourier-transform infrared (FTIR) spectroscopy system. It has emerged as a promising method for the strain typing of various microorganisms and for the detection of their clonal spread within hospitals. In this review, we aim to present the applications and accuracy of the IR Biotyper in hospital epidemiology.
View Article and Find Full Text PDFPredicting intra-abdominal candidiasis in elderly septic patients using machine learning based on lymphocyte subtyping: a prospective cohort study.
Front Pharmacol
December 2024
Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
Objective: Intra-abdominal candidiasis (IAC) is difficult to predict in elderly septic patients with intra-abdominal infection (IAI). This study aimed to develop and validate a nomogram based on lymphocyte subtyping and clinical factors for the early and rapid prediction of IAC in elderly septic patients.
Methods: A prospective cohort study of 284 consecutive elderly patients diagnosed with sepsis and IAI was performed.
Changes in metabolite profiles in solid fermentation of glutamate waste treatment solution by Aspergillus niger and Candida tropicalis.
J Appl Microbiol
December 2024
College of Life Science and Agroforestry, Qiqihar University, Qiqihar, Heilongjiang, 161006, China.
Aims: Glutamate wastewater poses a great environmental challenge to the monosodium glutamate production industry. However, its treatment solution is rich in crude protein, which has the potential to be developed as a new protein source for animal feed.
Methods And Results: Given that the fermentation process generates functionally different metabolites, this study innovatively utilized two strains of feed microorganisms, Aspergillus niger and Candida tropicalis, to perform solid-state fermentation of glutamate wastewater treatment solution.
Pathogen class-specific transcriptional responses derived from PBMCs accurately discriminate between fungal, bacterial, and viral infections.
PLoS One
December 2024
Division of Infectious Diseases, Duke University, Durham, North Carolina, United States of America.
Article Synopsis
- Immune responses to acute infections share common elements across different pathogens, which can aid in creating better diagnostics and treatments.
- Analysis of gene expression in white blood cells shows these common patterns, helping to identify the type of infection (viral or bacterial).
- A study identified a 41-gene signature that classifies infections with high accuracy and a smaller 21-gene subset that distinguishes between specific infections, underscoring the potential for developing effective diagnostic tools.
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