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: 3165
Function: getPubMedXML
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
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Trade restrictions for endangered elasmobranch species exist to disincentivise their exploitation and curb their declines. However, trade monitoring is challenging due to product variety and the complexity of import/export routes. We investigate the use of a portable, universal, DNA-based tool which would greatly facilitate monitoring. We collected shark and ray samples across the Island of Java, Indonesia, and selected 28 commonly encountered species (including 22 CITES-listed species) to test a recently developed real-time PCR single-assay originally developed for screening bony fish. In the absence of a bespoke elasmobranch identification online platform in the original FASTFISH-ID model, we employed a deep learning algorithm to recognize species based on DNA melt-curve signatures. By combining visual and machine-learning assignment methods, we distinguished 25/28 species, 20 of which were CITES-listed. With further refinement, this method can improve monitoring of the elasmobranch trade worldwide, without a lab or species-specific assays.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10300358 | PMC |
http://dx.doi.org/10.1016/j.isci.2023.107065 | DOI Listing |