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
Wildlife diseases are a considerable threat to human health, conservation, and the economy. Surveillance is a critical component to mitigate the impact of animal diseases in these sectors. To monitor human diseases, CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR-associated protein) biosensors have proven instrumental as diagnostic tools capable of detecting unique DNA and RNA sequences related to their associated pathogens. However, despite the significant advances in the general development of CRISPR-Cas biosensors, their use to support wildlife disease management is lagging. In some cases, wildlife diseases of concern could be rapidly surveyed using these tools with minimal technical, operational, or cost requirements to end users. This review explores the potential to further leverage this technology to advance wildlife disease monitoring and highlights how concerted standardization of protocols can help to ensure data reliability.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1089/crispr.2024.0030 | DOI Listing |
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