ArticleInternational journal of molecular sciences2022
SERS-PLSR Analysis of Vaginal Microflora: Towards the Spectral Library of Microorganisms.
Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- Integrated characterization of extracellular matrix remodeling in Candida parapsilosis biofilms by surface-enhanced raman spectroscopy, protein analysis, ultrastructural imaging and multivariate analysis.World journal of microbiology & biotechnology · 2026Article
- Investigating microbiota and biochemical changes in vaginal fluid toward point-of-care microbial monitoring using surface-enhanced Raman spectroscopy.Biophotonics discovery · 2025Article
- Leveraging the microbiome to combat antibiotic resistant gynecological infections.npj antimicrobials and resistance · 2025Review
- Rapid diagnosis of bacterial vaginosis using machine-learning-assisted surface-enhanced Raman spectroscopy of human vaginal fluids.mSystems · 2025Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
The accurate identification of microorganisms belonging to vaginal microflora is crucial for establishing which microorganisms are responsible for microbial shifting from beneficial symbiotic to pathogenic bacteria and understanding pathogenesis leading to vaginosis and vaginal infections. In this study, we involved the surface-enhanced Raman spectroscopy (SERS) technique to compile the spectral signatures of the most significant microorganisms being part of the natural vaginal microbiota and some vaginal pathogens. Obtained data will supply our still developing spectral SERS database of microorganisms. The SERS results were assisted by Partial Least Squares Regression (PLSR), which visually discloses some dependencies between spectral images and hence their biochemical compositions of the outer structure. In our work, we focused on the most common and typical of the reproductive system microorganisms (
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Registered trials
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