ArticleDevelopment (Cambridge, England)2025
Building and rebuilding complex tissues: strategic visions from a research-led workshop.
Article in Development (Cambridge, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
How complex tissues develop and regenerate post-injury is one of the most fascinating and important processes in biology. Recent technical advances that enable the generation of a quantitative understanding of these processes have the potential to transform the field. However, to achieve this, concerted and long-term studies are required at the community level to compare regeneration and wound healing in both regenerative and non-regenerative contexts and organisms. To stimulate such collaboration, we recently organised a focused workshop around this topic to identify key outstanding questions that focus on cross-comparisons of regenerative competence, and the cellular, molecular and physical drivers of regeneration. Importantly, the discussions also highlighted significant logistical and financial challenges in initiating and sustaining large-scale, long-term interdisciplinary studies, particularly those involving non-model organisms.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.