gastric-mucosa-quantitative-polymerase-chain-reaction-analysis-for

Gastric Mucosa Quantitative Polymerase Chain Reaction Analysis for Detecting Helicobacter pylori and Antibiotic Resistance

Helicobacter pylori is a main pathogen that infects nearly half of the global population and is threatening public health due to its increasing antibiotic ...

detection-helicobacter-pylori-infection-antibiotic-resistance-via

Detection of Helicobacter pylori Infection and Antibiotic Resistance via Stool Quantitative Polymerase Chain Reaction Analysis

Helicobacter pylori (H. pylori) is widely prevalent worldwide, with approximately 50% of the global population having a history of H. pylori infection. In ...

rapid-detection-helicobacter-pylori-virulence-typing-using-quantum

Rapid Detection of Helicobacter pylori Virulence and Typing Using Quantum Dot Labeling Technology

We present a method based on quantum dot labeling technology for rapidly detecting the virulence of Helicobacter pylori and performing typing, aiming to ...

application-polyacrylamide-gel-electrophoresis-analyzing-lipoprotein

Application of Polyacrylamide Gel Electrophoresis in Analyzing Lipoprotein Subfractions Relevant to Atherosclerotic Cardiovascular Disease

Low-density lipoprotein cholesterol (LDL-C) is a key factor in the development of atherosclerotic cardiovascular disease (ASCVD). Elevated levels of LDL-C ...

advanced-application-capillary-electrophoresis-high-resolution-serum

Advanced Application of Capillary Electrophoresis in High-resolution Serum Monoclonal Protein Detection

Monoclonal immunoglobulin, also known as M protein or paraprotein, is produced by clonal proliferation of plasma cells or B lymphocytes and serves as a ...

Southern Medical University

Surface-enhanced Raman spectroscopy (SERS) has emerged as a powerful tool for clinical microorganism identification, offering significant advantages over traditional culture-based methods, including minimal sample requirements, rapid detection, and operational simplicity. However, bacterial SERS spectra are subject to variations due to various experimental factors. To evaluate the influence of two key factors, growth media and culture time, on bacterial SERS spectra, we inoculated three important clinical pathogens, Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa, on three solid growth media (BHI, LB, and TSB) and acquired their SERS spectra at three time points (6 h, 12 h, and 24 h) for analysis. The clear differentiation of SERS spectra in the clustering analysis across various media and time points confirms that both culture time and growth media lead to significant changes of SERS spectra. Using the best-performing convolutional neural network (CNN) models, we achieved a classification accuracy of 98.11 % in distinguishing bacterial species across varying growth media and time points, with an area under the curve (AUC) of 99.76 %. Notably, temporal factor exerted greater impact than media types on SERS spectral signatures because classification accuracy reached 98.30 ± 1.65 % for bacteria collected at identical time points, compared to 91.29 ± 2.31 % under identical media conditions (p = 0.0128). These findings underscore the critical need for standardized protocols, consistent growth media and culture time, to ensure spectral reproducibility and enhance the reliability of diagnostics in SERS-based microbial identification in medical laboratories.

ArticleTotal : 5	Year
Publication title	2025
Publication title	2025
Publication title Cited by 1	2025
$Application of Polyacrylamide Gel Electrophoresis in Analyzing Lipoprotein Subfractions Relevant to Atherosclerotic Cardiovascular Disease$ Publication title	2025
Publication title	2026

Ya-Nan Yao

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