Effects of Prenatal Nicotine Exposure on Short-Term and Long-Term Memory: A Literature Review
Bibliographic record
Abstract
Introduction: Maternal smoking impacts the health of both the mother and the baby. During gestation, nicotine can pass through the maternal-fetal blood interface in the placenta, accumulating in the fetal circulation and amniotic fluid. Because nicotine is a teratogenic agent, it can affect the development of the structures and functions in the brain of the fetus. Short-term and long-term memory are two areas of cognitive function that are affected. This literature review seeks to understand how prenatal nicotine exposure affects short-term and long-term memory, and how these effects will present in exposed individuals. Methods: An extensive literature search was performed to find pre-clinical trials, clinical trials, and reviews on the effects of prenatal nicotine exposure on memory. The databases used for the search were PubMed, CINHL, and EMBASE. After removing duplicates and studies that did not meet inclusion criteria, 17 studies remained. Results: 8 preclinical studies, 2 clinical studies, and 7 reviews that met inclusion criteria were included in this review. These studies found that exposed participants did not perform as well in memory and learning tests as compared to non-exposed control participants. Decreased integrity of structures in the brain, decreased function and size of neuronal structures, and low birth weight were noted in exposed subjects in multiple studies. Discussion: Prenatal nicotine exposure impairs short-term and long-term memory by altering the development of structures and processes in the brain such as the hippocampus, prefrontal cortex, blood-brain barrier, cerebellum, and cholinergic functioning. Placental dysfunction associated with prenatal nicotine exposure can cause abnormal development of the brain and cerebral vasculature due to chronic hypoxia and fetal growth restriction. Due to the abnormal development of crucial systems used in short-term and long-term memory function, memory and learning deficits can be observed in adolescence and adulthood of individuals exposed to prenatal nicotine. Conclusion: Information summarized in this literature review can be used to conduct future research and aid in public education on the negative effects of maternal smoking. Therapeutic strategies to lessen the effects of cognitive issues faced by individuals prenatally exposed to nicotine can be derived from future research on this subject.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".