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
The use of the smartphone is an ideal platform to realize the future point-of-care (POC) diagnostic system. Herein, we propose an integrated smartphone-based genetic analyzer. It consists of a smartphone and an ntegrated tic analysis unit (i-Gene), in which the power of the smartphone was utilized for heating the gene amplification reaction, and the camera function was used for imaging the colorimetric change of the reaction for quantitative and multiplex foodborne pathogens. The housing of i-Gene was fabricated by using a 3D printer, which was equipped with a macro lens, white LEDs, a disposable microfluidic chip for loop-mediated isothermal amplification (LAMP), a thin-film heater, and a power booster. The i-Gene was installed on the iPhone in alignment with a camera. The LAMP mixture for Eriochrome Black T (EBT) colorimetric detection was injected into the LAMP chip to identify O157:H7, , and . The proportional-integral-derivative controller-embedded film heater was powered by a 5.0 V power bank to maintain 63 °C for the LAMP reaction. When the LAMP proceeded, the color was changed from violet to blue, which was real-time monitored by the smartphone complementary metal oxide semiconductor camera. The images were transported to the desktop computer via Wi-Fi. The quantitative LAMP profiles were obtained by plotting the ratio of green/red intensity versus the reaction time. We could identify O157:H7 with a limit of detection of 10 copies/μL within 60 min. Our proposed smartphone-based genetic analyzer offers a portable, simple, rapid, and cost-effective POC platform for future diagnostic markets.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7482303 | PMC |
http://dx.doi.org/10.1021/acsomega.0c02317 | DOI Listing |
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