Detection and diagnosis of bacterial pathogens in urine using laser-induced breakdown spectroscopy
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Notice bibliographique
Résumé
The presence of bacterial cells from three species has been detected in clinical specimens of human urine using laser-induced breakdown spectroscopy (LIBS) by using a partial least squares discriminant analysis (PLS-DA) of 360 spectra obtained from 12 specimens of infected urine and 239 spectra obtained from eight specimens of sterile urine. Nominally sterile urine specimens obtained from four patients at a local hospital after being screened negative for the presence of bacterial pathogens were spiked with known aliquots of Escherichia coli , Staphylococcus aureus , and Enterobacter cloacae to simulate clinical urinary tract infections . Fifteen emission line intensities measured from the LIBS spectra and 92 ratios of those line intensities were used as 107 independent variables in the PLS-DA for discrimination between bacteria-containing specimens and sterile specimens. The PLS-DA models possessed a 98.3% sensitivity and a 97.9% specificity for the detection of pathogenic cells in urine when single-shot LIBS spectra were tested. To increase the signal to noise ratio , thirty spectra acquired from a single specimen were also averaged together and the averaged spectra were used to construct a model. When each averaged spectrum was withheld from the model individually for testing, the diagnostic test possessed a 100% sensitivity and a 100% specificity for the detection of bacterial cells in urine, although the number of test spectra was necessarily reduced. The entire LIBS spectrum from 200 nm – 590 nm was input into an artificial neural network analysis with principal component analysis pre-processing (PCA-ANN) to diagnose the bacterial species once detected. This PCA-ANN test possessed an overall sensitivity of 97.2%, an overall specificity of 98.6%, and an overall classification accuracy of 97.9% when using 80% of the data to build a model and withholding 20% for cross-validation testing. The PCA-ANN was also performed on each of the 12 bacteria-containing filters individually, using the other 11 filters to build the model. The average sensitivity of this test, calculated by averaging the sensitivities measured for each of the three bacterial species , was 70.9% and the average specificity was 85.5%. Based on these results, the average classification accuracy for the test when used to discriminate between the three microorganisms was 80.6%. These results indicate the potential usefulness of LIBS for rapidly detecting and possibly diagnosing urinary tract infections in a clinical setting.
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Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle