Gerotherapeutic compound picolinic acid supports locomotor function and bone health in aged zebrafish
Bibliographic record
Abstract
Abstract Objectives This study aimed to evaluate the impact of picolinic acid (PIC), a metabolite derived from tryptophan, on age-related tissue regeneration and physical decline in zebrafish. Additionally, it examined changes in whole-body mass index (WB-BMI) as an indicator of musculoskeletal aging. Methods Siblings born in August 2022 were randomly assigned to four groups at age 20 mo: (1) PIC in water (25 mg/kg/day), (2) PIC in water + 25 mg/kg oral gavage, (3) PIC in water + 75 mg/kg oral gavage, and (4) control (system water + gavage) for eight weeks. The treatment groups consisted of 15 fish. At week 7, swimming performance was recorded over a 30-minute period. Caudal fins were amputated for regeneration analysis. In week 8, fish were euthanized for whole-body micro-CT and for β-galactosidase (X-gal) staining to evaluate cellular senescence. The Mann-Whitney U test was used to compare WB-BMI between groups. Results Group 2 showed the highest swimming speed (44.5 m/min), followed by Group 1 (34.7 m/min) (p = 0.01 and p = 0.09, respectively) than the control group (31.7 m/min). WB-BMI was decreasing over the duration of the experiment in all 4 groups, with Group 1 maintaining the highest BMD compared to the control (non-significant, p > 0.5). Regeneration in Groups 2 and 3 was more advanced than in Group 1, with stronger staining by β-galactosidase. Conclusion PIC at moderate doses supports locomotor function and overall health in aged zebrafish. It may influence regenerative outcomes through mechanisms involving cellular aging.
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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".