<i>Smed-dynA-1</i> is a planarian nervous system specific <i>dynamin 1</i> homolog required for normal locomotion
Bibliographic record
Abstract
Dynamins are GTPases that are required for separation of vesicles from the plasma membrane and thus are key regulators of endocytosis in eukaryotic cells. This role for dynamin proteins is especially crucial for the proper function of neurons, where they ensure that synaptic vesicles and their neurotransmitter cargo are recycled in the presynaptic cell. Here we have characterized the dynamin protein family in the freshwater planarian Schmidtea mediterranea and showed that it possesses six dynamins with tissue specific expression profiles. Of these six planarian homologs, two are necessary for normal tissue homeostasis, and the loss of another, Smed-dynA-1, leads to an abnormal behavioral phenotype, which we have quantified using automated center of mass tracking. Smed-dynA-1 is primarily expressed in the planarian nervous system and is a functional homolog of the mammalian Dynamin I. The distinct expression profiles of the six dynamin genes makes planarians an interesting new system to reveal novel dynamin functions, which may be determined by their differential tissue localization. The observed complexity of neurotransmitter regulation combined with the tools of quantitative behavioral assays as a functional readout for neuronal activity, renders planarians an ideal system for studying how the nervous system controls behavior.
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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) | 0.001 | 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".