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
Organoids and stem-cell-based embryo models (SEMs) are imperfect organ or embryo representations that explore a much larger space of possible forms, or morphospace, compared to their counterparts. Here, we discuss SEM biology in light of seminal work by Pere Alberch, a leading figure in early evo-devo, interpreting SEMs as developmental 'monstrosities' in the Alberchian sense. Alberch suggested that ordered patterns in aberrant development-i.e. 'the logic of monsters'-reveal developmental constraints on possible morphologies. In the same vein, we detail how SEMs have begun to shed light on structural features of normal development, such as developmental variability, the relative importance of internal versus external constraints, boundary conditions and design principles governing robustness and canalization. We argue that SEMs represent a powerful experimental tool to explore and expand developmental morphospace and propose that the 'monstrosity' of SEMs can be leveraged to uncover the 'hidden' rules and developmental constraints that robustly shape and pattern the embryo.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11503023 | PMC |
http://dx.doi.org/10.1098/rsfs.2024.0023 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!