Sponge cell aggregation: checkpoints in development indicate a high level of organismal complexity
Bibliographic record
Abstract
Abstract Studies of regeneration provide insight across many scales of animal biology from the processes of cellular communication to the ecology of whole populations. Sponges are highly regenerative animals, with studies showing adults can both recover large portions of their body after predation or damage due to storms, and even reform whole individuals, via an aggregation stage, from dissociated tissues. While sponges are clearly highly regenerative, few studies actually show dissociated cells forming functional individuals. As sponges often serve as model organisms for studying the development and function of traits in metazoans, determining the universality and mechanics of their regeneration potential is important. We tested the capacity of members of seven sponge species from temperate freshwater and marine environments, from a range of taxonomic positions, and with different habits, to form functional sponges after dissociation. Development to a functional sponge progressed through a series of checkpoints: the sorting of cells and removal of debris; adhesion to a substrate and differentiation of cells; organization of cells into tissues; and regionalization of tissues. Two of the seven species tested, Spongilla lacustris and Haliclona cf. permollis, progressed through all four checkpoints, while the remaining five species progressed to various levels of development before aggregates disintegrated. Our findings highlight three important conclusions: (1) The ability of aggregates to differentiate into functional sponges is not as widespread as previously thought; (2) The species‐specific ability of aggregates to develop to functional sponges appears to be an adaptive trait; and (3) The progression of development in aggregates through checkpoints, which in later development involves formation of tissues and regionalization of tissues, highlights the complexity of the sponge body plan and suggests fundamental rules in development shared across metazoans.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".