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
Small interfering RNA (siRNA) screening approaches used with quantitative single-cell analysis can uncover the roles of genes in cell morphogenesis. Here, we present a high-throughput automated phenotypic screening technique to quantify a single cell shape in cancer cells cultured on top of soft 3D hydrogels. We describe reverse transfection of cells with siRNAs and seeding of these cells on top of collagen, followed by image analysis to quantify morphology of a single cell and population levels in low-elasticity matrices. For complete details on the use and execution of this protocol, please refer to Bousgouni et al. (2022)..
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9792547 | PMC |
http://dx.doi.org/10.1016/j.xpro.2022.101942 | DOI Listing |
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