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A Preliminary Investigation on the Antiviral Activities of the Philippine Marshmint (Mentha arvensis) Leaf Extracts against Dengue Virus Serotype 2 In Vitro.

The Kobe journal of medical sciences
In this study, we investigated the antiviral activity of lyophilized crude leaf extracts of the Philippine marshmint (Mentha arvensis L., commonly called yerba buena) against DENV-2 in vitro. The plant specimen was authenticated by DNA barcoding anal...

Accurate virus identification with interpretable Raman signatures by machine learning.

Proceedings of the National Academy of Sciences of the United States of America
Rapid identification of newly emerging or circulating viruses is an important first step toward managing the public health response to potential outbreaks. A portable virus capture device, coupled with label-free Raman spectroscopy, holds the promise...

Nondestructive microbial discrimination using single-cell Raman spectra and random forest machine learning algorithm.

STAR protocols
Raman microspectroscopy is a powerful tool for obtaining biomolecular information from single microbial cells in a nondestructive manner. Here, we detail steps to discriminate prokaryotic species using single-cell Raman spectra acquisitions followed ...

Semiquantitative Fingerprinting Based on Pseudotargeted Metabolomics and Deep Learning for the Identification of and Its Major Serotypes.

Analytical chemistry
The rapid identification of pathogenic microorganism serotypes is still a bottleneck problem to be solved urgently. Compared with proteomics technology, metabolomics technology is directly related to phenotypes and has higher specificity in identifyi...

Rapid identification of Salmonella serovars Enteritidis and Typhimurium using whole cell matrix assisted laser desorption ionization - Time of flight mass spectrometry (MALDI-TOF MS) coupled with multivariate analysis and artificial intelligence.

Journal of microbiological methods
Salmonella is a common food-borne pathogen with Enteritidis and Typhimurium being among the most important serovars causing numerous outbreaks. A rapid method was investigated to identify these serovars using whole-cell MALDI-TOF MS coupled with mult...

Rapid discrimination of four Salmonella enterica serovars: A performance comparison between benchtop and handheld Raman spectrometers.

Journal of cellular and molecular medicine
Foodborne illnesses, particularly those caused by Salmonella enterica with its extensive array of over 2600 serovars, present a significant public health challenge. Therefore, prompt and precise identification of S. enterica serovars is essential for...

Characterization of the prevalence of Salmonella in different retail chicken supply modes using genome-wide and machine-learning analyses.

Food research international (Ottawa, Ont.)
Salmonella is a foodborne pathogen that causes salmonellosis, of which retail chicken meat is a major source. However, the prevalence of Salmonella in different retail chicken supply modes and the threat posed to consumers remains unclear. The preval...

Machine-learning-assisted high-throughput identification of potent and stable neutralizing antibodies against all four dengue virus serotypes.

Scientific reports
Several computational methods have been developed to identify neutralizing antibodies (NAbs) covering four dengue virus serotypes (DENV-1 to DENV-4); however, limitations of the dataset and the resulting performance remain. Here, we developed a new c...

Predicting the infecting dengue serotype from antibody titre data using machine learning.

PLoS computational biology
The development of a safe and efficacious vaccine that provides immunity against all four dengue virus serotypes is a priority, and a significant challenge for vaccine development has been defining and measuring serotype-specific outcomes and correla...

Using core genome and machine learning for serovar prediction in Salmonella enterica subspecies I strains.

FEMS microbiology letters
This study presents a dual investigation of Salmonella enterica subspecies I, focusing on serovar prediction and core genome characteristics. We utilized two large genomic datasets (panX and NCBI Pathogen Detection) to test machine learning methods f...