Molecular mechanisms underlying nuchal hump formation in dolphin cichlid, Cyrtocara moorii
Bibliographic record
Abstract
East African cichlid fishes represent a model to tackle adaptive changes and their connection to rapid speciation and ecological distinction. In comparison to bony craniofacial tissues, adaptive morphogenesis of soft tissues has been rarely addressed, particularly at the molecular level. The nuchal hump in cichlids fishes is one such soft-tissue and exaggerated trait that is hypothesized to play an innovative role in the adaptive radiation of cichlids fishes. It has also evolved in parallel across lakes in East Africa and Central America. Using gene expression profiling, we identified and validated a set of genes involved in nuchal hump formation in the Lake Malawi dolphin cichlid, Cyrtocara moorii. In particular, we found genes differentially expressed in the nuchal hump, which are involved in controlling cell proliferation (btg3, fosl1a and pdgfrb), cell growth (dlk1), craniofacial morphogenesis (dlx5a, mycn and tcf12), as well as regulators of growth-related signals (dpt, pappa and socs2). This is the first study to identify the set of genes associated with nuchal hump formation in cichlids. Given that the hump is a trait that evolved repeatedly in several African and American cichlid lineages, it would be interesting to see if the molecular pathways and genes triggering hump formation follow a common genetic track or if the trait evolved in parallel, with distinct mechanisms, in other cichlid adaptive radiations and even in other teleost fishes.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".