Population variation alters aggression-associated oxytocin and vasopressin expressions in brains of Brandt’s voles in field conditions
Bibliographic record
Abstract
Density-dependent change in aggressive behavior contributes to the population regulation of many small rodents, but the underlying neurological mechanisms have not been examined in field conditions. We hypothesized that crowding stress and aggression-associated oxytocin (OT) and arginine vasopressin (AVP) in specific regions of the brain may be closely related to aggressive behaviors and population changes of small rodents. We analyzed the association of OT and AVP expression, aggressive behavior, and population density of Brandt's voles in 24 large semi-natural enclosures (0.48 ha each) in Inner Mongolia grassland. We tested the effects of population density on the OT/AVP system and aggressive behavior by experimentally manipulating populations of Brandt's voles in the grassland enclosures. High density was positively and significantly associated with more aggressive behavior, and increased expression of mRNA and protein of AVP and its receptor, but decreased expression of mRNA and protein of OT and its receptor in specific brain regions of the voles. Our study suggests that changes in OT/AVP expression are likely a result of the increased psychosocial stress that these voles experience during overcrowding, and thus the OT/AVP system can be used as indicators of density-dependent stressors in Brandt's voles.
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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".