Cocoa Butter Injections, but not Sealed or Perforated Silastic Implants, of Corticosterone can be used to Chronically Elevate Corticosterone in Free-Living Painted Turtles (<i>Chrysemys picta</i>)
Bibliographic record
Abstract
Chronic stress can result in an elevation of circulating levels of glucocorticoid (GC) hormones in vertebrates, which may affect their fitness. To isolate the effect of GCs on stressed organisms, one approach consists of manipulating circulating levels of GCs. We investigated the usefulness of two corticosterone (CORT) administration methods, Silastic® implants and cocoa butter injections, in chronically elevating circulating CORT levels in Painted Turtles (Chrysemys picta). First, free-living turtles received subcutaneous Silastic implants for 2 mo. We observed no significant difference in baseline CORT levels between two doses of CORT and sham-treated turtles. Then, captive turtles received a subcutaneous Silastic implant for 28 d. We observed no effect on baseline CORT levels, hormonal stress response, or body mass, suggesting that sealed and perforated Silastic implants of CORT may not be an effective way to elevate CORT in Painted Turtles. Second, we tested injections of CORT-laden cocoa butter for the first time in an ectothermic tetrapod. Free-living turtles received an epicoelomic injection of liquid cocoa butter mixed with CORT and were recaptured in the field over 2 mo. Despite large interindividual variation, we found that this injection approach generally kept circulating CORT levels elevated for up to 3 wk. Achieved CORT concentrations were probably physiologically and ecologically relevant for the species, although concentrations possibly remained elevated longer than would be the case in wild animals. Cocoa butter injections, but not sealed or perforated Silastic implants, can be used in Painted Turtles to chronically elevate CORT. Further, this represents a promising method for other temperate ectotherms such as amphibians and reptiles.
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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) | 0.001 | 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".