Teneurin C-Terminal Associated Peptide (TCAP)-3 Increases Metabolic Activity in Zebrafish
Bibliographic record
Abstract
Teneurin C-terminal associated peptides (TCAP), bioactive peptides located on the C-terminal end of teneurin proteins, have been shown to regulate stress axis functions due to the high conservation between TCAP and corticotropin releasing factor (CRF). Additionally, recent work demonstrated that TCAP can increase metabolism in rats via glucose metabolism. These metabolic actions are not well described in other organisms, including teleosts. Here we investigated the expression of a tcap isoform, tcap-3, and the potential role of TCAP-3 as a regulator of metabolism across zebrafish life-stages. Using pcr-based analyses, tcap-3 appears to be independently transcribed, in relation to teneurin-3, in muscle tissue of adult zebrafish. Resazurin, respirometry chambers, and mitochondrial metabolism analyses were used to study the metabolic effects of synthetic rainbow trout TCAP-3 (rtTCAP-3) in larval and adult zebrafish. Overall, metabolic activity was enhanced by 48 h of rtTCAP-3 treatment in larvae (bath immersion) and adults (intraperitoneal injections). This metabolic activity increase was due to mitochondrial uncoupling, as mitochondrial respiration increase by rtTCAP-3 was due to proton leak. Additionally, rtTCAP-3 protected larval fish from reduced metabolic activity induced by low temperatures. Subsequently, rtTCAP-3 increased metabolic output in adult zebrafish subjected to accelerated swimming speeds, demonstrating the potent role of rtTCAP-3 in zebrafish metabolism regulation during metabolic challenges. Collectively, these results demonstrate the conserved roles for rtTCAP-3 as a metabolic activator in zebrafish.
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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 | 0.001 |
| 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".