Maternal sleep deprivation at different stages of pregnancy impairs the emotional and cognitive functions, and suppresses hippocampal long-term potentiation in the offspring rats
Bibliographic record
Abstract
BACKGROUND: Sleep deprivation during pregnancy is a serious public health problem as it can affect the health of pregnant women and newborns. However, it is not well studied whether sleep deprivation at different stages of pregnancy has similar effects on emotional and cognitive functions of the offspring, and if so, the potential cellular mechanisms also remain poorly understood. METHODS: In the present study, the pregnant rats were subjected to sleep deprivation for 6 h per day by gentle handling during the first (gestational days 1-7), second (gestational days 8-14) and third trimester (gestational days 15-21) of pregnancy, respectively. The emotional and cognitive functions as well as hippocampal long-term potentiation (LTP) were tested in the offspring rats (postnatal days 42-56). RESULTS: The offspring displayed impaired hippocampal-dependent spatial learning and memory, and increased depressive- and anxiety-like behaviors. Quantification of BrdU-positive cells revealed that adult hippocampal neurogenesis was significantly reduced compared to control. Electrophysiological recording showed that maternal sleep deprivation impaired hippocampal CA1 LTP and reduced basal synaptic transmission, as reflected by a decrease in the frequency and amplitude of miniature excitatory postsynaptic current in the hippocampal CA1 pyramidal neurons. CONCLUSIONS: Taken together, these results suggest that maternal sleep deprivation at different stages of pregnancy disrupts the emotional and cognitive functions of the offspring that might be attributable to the suppression of hippocampal LTP and basal synaptic transmission.
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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".