Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Raman spectroscopy is an effective tool for detecting and discriminating microorganisms that is robust, reliable, and rapid.
Objectives: To develop a polymerase chain reaction technique (PCR) based on Surface Enhanced Raman Spectroscopy (SERS) technique with principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to assess diagnostic capability of SERS for distinguishing between tuberculosis (TB) positive rifampin resistant and tuberculosis (TB) positive rifampin susceptible samples.
Methods: Silver nanoparticles (Ag NPs) were used as SERS substrates and technique was used to distinguish TB positive rifampin (RIF) resistant and TB positive rifampin (RIF) susceptible patients on the basis of characteristic SERS spectral features of their respective PCR products. SERS spectra were acquired from 52 samples of PCR products including 22 samples of TB positive rifampin susceptible, 30 samples of TB positive rifampin resistant and negative control samples. All these samples were collected from individuals of same age. Furthermore, multivariate data analyses techniques such as PCA and PLS-DA were used to assess diagnostic capability of SERS for distinguishing between TB positive rifampin resistant and TB positive rifampin susceptible samples.
Results: PCA is found helpful for successful differentiation among these two groups of spectral data sets. Moreover, PLS-DA provides this classification quantitatively by predicting the class of SERS spectral data set with 73% area under curve, 96% sensitivity, 95.6% specificity and 95% accuracy.
Conclusion: SERS can be employed for the rapid distinguishing between TB positive rifampin resistant and TB positive rifampin susceptible samples.
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Source |
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http://dx.doi.org/10.1016/j.pdpdt.2022.102758 | DOI Listing |
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