Early Life Maternal Separation and Maternal Behaviour Modulate Acoustic Characteristics of Rat Pup Ultrasonic Vocalizations
Bibliographic record
Abstract
Early separation of preterm infants from their mothers has adverse, long-term neurodevelopmental consequences. We investigated the effects of daily maternal separation (MS) of rat pups from postnatal days 2-10 (PND2-10) on neurobehavioural responses to brief isolation at PND12 compared with pups receiving controlled handling without MS. Ultrasonic vocalizations (USV) were measured at PND12 during two, 3-minute isolations occurring immediately before and after a 3-minute maternal reunion. There were no significant differences in acoustic characteristics between MS and control animals in the first isolation. However, in the second isolation, MS pups produced a greater proportion of high (~60 kHz) vs low (~40 kHz) frequency calls. During this isolation, control pups made longer and louder low frequency calls compared to the first isolation, whereas MS pups did the opposite. Maternal behaviour of control and MS mothers modulated pup acoustic characteristics in opposite directions; higher maternal care was associated with more low frequency calls in control pups but more high frequency calls in MS pups. We hypothesize that MS results in USV emission patterns reflective of a greater stress response to isolation. This translational model can be used to identify mechanisms and interventions that may be exploited to overcome the negative, long-term effects of MS.
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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 | 0.001 |
| 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".