Predators inhibit brain cell proliferation in natural populations of electric fish, <i>Brachyhypopomus occidentalis</i>
Bibliographic record
Abstract
Compared with laboratory environments, complex natural environments promote brain cell proliferation and neurogenesis. Predators are one important feature of many natural environments, but, in the laboratory, predatory stimuli tend to inhibit brain cell proliferation. Often, laboratory predatory stimuli also elevate plasma glucocorticoids, which can then reduce brain cell proliferation. However, it is unknown how natural predators affect cell proliferation or whether glucocorticoids mediate the neurogenic response to natural predators. We examined brain cell proliferation in six populations of the electric fish, Brachyhypopomus occidentalis, exposed to three forms of predator stimuli: (i) natural variation in the density of predatory catfish; (ii) tail injury, presumably from predation attempts; and (iii) the acute stress of capture. Populations with higher predation pressure had lower density of proliferating (PCNA+) cells, and fish with injured tails had lower proliferating cell density than those with intact tails. However, plasma cortisol did not vary at the population level according to predation pressure or at the individual level according to tail injury. Capture stress significantly increased cortisol, but only marginally decreased cell proliferation. Thus, it appears that the presence of natural predators inhibits brain cell proliferation, but not via mechanisms that depend on changes in basal cortisol levels. This study is the first demonstration of predator-induced alteration of brain cell proliferation in a free-living vertebrate.
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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".