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: 1057
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3175
Function: GetPubMedArticleOutput_2016
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
Measuring cell-generated forces by Traction Force Microscopy (TFM) has become a standard tool in cell mechanobiology. Although widely used in two dimensional (2D) experiments, only a few methods exist to measure traction in three-dimensional (3D) cell culture, since 3D volumetric high-resolution microscopy and more demanding computational approaches are required. Although it is commonly known that the selected experimental and computational setup highly influence the quality and accuracy of the results, no existing methods can adequately assess the errors involved in this process. We present a fully integrated simulation and evaluation platform that allows one to simulate TFM images and quantify errors of an applied approach for traction stress reconstruction, in order to improve experiments that attempt to measure mechanical interaction in cellular systems. In this context, we show that a careful parameter selection can decrease the reconstructed traction error by up to 40%.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1080/10255842.2019.1599866 | DOI Listing |
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