A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 197

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1075
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3195
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 317
Function: require_once

Fully automated standalone microfluidic integrated electrochemiluminescence platform for sample-to-answer detection of diabetes complication markers. | LitMetric

Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

The current standard for diabetes care primarily relies on the finger prick blood sample method to monitor glucose levels. However, this approach is often painful, poses a risk of infection to patients, and provides limited metabolic insights. To address these limitations, a non-invasive approach using easily accessible biofluids such as sweat and urine offers a painless alternative to traditional blood tests. Moreover, monitoring other biochemical markers alongside glucose, such as lactate and uric acid, can offer a more comprehensive assessment of diabetes and help detect early signs of complications. Herein, a microfluidic integrated electrochemiluminescence (μfluidic-ECL) biosensing chip and a fully automated standalone ECL sample-to-answer diagnostic platform were designed to perform the detection of multiple diabetes markers accurately and sensitively. The developed ECL platform can perform all the functions of a benchtop ECL analyzer without compromising on performance and accuracy. The developed diagnostic platform has been successfully implemented and validated for the detection of glucose, lactate, and uric acid in a laboratory setting and shows promising results for field deployment, positioning it at the technology readiness level (TRL) 4-5. The μfluidic-ECL biosensing chip performance was numerically investigated using COMSOL software to achieve the optimum fluid mixing efficiency and fluid interaction with the electrode surface. The sensor has shown a wide linear range of 10 μM to 10 mM, 10 μM to 2.5 mM, and 10 μM to 1 mM, a limit of detection of 27 μM, 20 μM, and 10.9 μM, and a limit of quantification of 84 μM, 61 μM, and 32.9 μM for glucose, lactate, and uric acid, respectively. The sensor analytical performance was evaluated in terms of stability, reproducibility against potential interferents, and real sample analysis using artificial sweat and artificial urine. The finding suggested that the developed μfluidic-ECL would be a comprehensive and integrated solution for the non-invasive and accurate detection of diabetes complication markers to offer personalized diagnostics.

Download full-text PDF

Source
http://dx.doi.org/10.1039/d5lc00275cDOI Listing

Publication Analysis

Top Keywords

μm μm
16
glucose lactate
12
lactate uric
12
uric acid
12
μm
9
fully automated
8
automated standalone
8
microfluidic integrated
8
integrated electrochemiluminescence
8
detection diabetes
8

Similar Publications