Long‐term depression in vivo: Effects of sex, stress, diet, and prenatal ethanol exposure
Bibliographic record
Abstract
Long-term depression (LTD) of synaptic efficacy has proven a difficult phenomenon to examine in vivo, despite the ease with which it is induced in a variety of in vitro preparations. Prior exposure to an acute stressful episode does however seem to enhance the capacity of the hippocampus to exhibit LTD in vivo in male animals. In the present experiments, we examined the capacity for low-frequency stimuli (low-frequency stimulation (LFS)) to induce LTD in juvenile male and female animals following an acute stress episode. Interestingly, prior exposure to stress was only required for the induction of LTD in male animals, while both control and stressed female animals exhibited equivalent LTD. In animals that were exposed to ethanol in utero, a similar requirement for prior exposure to stress to elicit LTD was found for male, but not female animals. This prenatal ethanol exposure did not in itself alter the capacity for LTD induction in either sex; however, in utero food restriction did enhance LTD induction in both male and female animals, irrespective of whether they were exposed to stress just prior to being administered LFS. These results indicate that in utero dietary restriction more drastically affects CA1 LTD than in utero ethanol exposure. In addition, female animals seem to exhibit LTD in vivo in the absence of stress much more easily than their male counterparts.
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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".