Oxytocin and estrogen receptor α and β knockout mice provide discriminably different odor cues in behavioral assays
Bibliographic record
Abstract
Social behavior involves both the recognition and pro-duction of social cues. Mice with selective deletion(knockout) of either the gene for oxytocin (OT) or genes for the estrogen receptor (ER) -c or -B display impaired social recognition. In this study we demonstrate that these gene knockout mice also provide discriminably different social stimuli in behavioral assays. In an odor choice test, which is a measure of social interest and discrimination, outbred female Swiss-Webster mice discriminated the urine odors of male knock-outs IKO: OTKO, alphaERKO, betaERKO) from the odors of their wildtype littermates (WT: OTWT, alphaERWT, betaERWT). Females showed marked initial choices of the urine odors of OTWT and betaERWT males over those of OTKOand PERKO males, and alphaERKO males over alphaERWT males. The odors of OTKO and betaERKO males also induced aversive, analgesic responses, with the odors of WTs having no significant effects. Odors of both the alphaERWT andalphaERKO males induced aversive, analgesic responses,with the odors of the WT inducing significantly greater analgesia. The odors of restraint stressed WT and KO males also elicited analgesia with, again, females dis-playing significantly greater responses to the odors of stressed OTKO and betaERKO males than their WTs, and significantly lower analgesia to the odors of stressedalphaERKO than alphaERWT males. These findings show that the KO mice are discriminated from their WTs on the basis of odor and that the various KOs differ in the relative attractiveness/aversiveness of their odors. Therefore, in behavioral assays one causal route by which gene inactivation alters the social behavior of knockout mice may be mediated through the partners'modified responses to their odors.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".