Maternal Exposure to PM2.5 during Pregnancy Induces Impaired Development of Cerebral Cortex in Mice Offspring
Bibliographic record
Abstract
Air pollution is a serious environmental health problem closely related to the occurrence of central nervous system diseases. Exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5) during pregnancy may affect the growth and development of infants. The present study was to investigate the effects of maternal exposure to PM2.5 during pregnancy on brain development in mice offspring. Pregnant mice were randomly divided into experimental groups of low-, medium-, or high-dosages of PM2.5, a mock-treated group which was treated with the same amount of phosphate buffer solution (PBS), and acontrol group which was untreated. The ethology of offspring mice on postnatal days 1, 7, 14, 21, and 30, along with neuronal development and apoptosis in the cerebral cortex were investigated. Compared with the control, neuronal mitochondrial cristae fracture, changed autophagy characteristics, significantly increased terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) positive cell rate, and mRNA levels of apoptosis-related caspase-8 and caspase-9 were found in cerebral cortex of mice offspring from the treatment groups, with mRNA levels of Bcl-2 and ratio of Bcl-2 to Bax decreased. Treatment groups also demonstrated enhanced protein expressions of apoptosis-related cleaved caspase-3, cleaved caspase-8 and cleaved caspase-9, along with declined proliferating cell nuclear antigen (PCNA), Bcl-2, and ratio of Bcl-2 to Bax. Open field experiments and tail suspension experiments showed that exposure to high dosage of PM2.5 resulted in decreased spontaneous activities but increased static accumulation time in mice offspring, indicating anxiety, depression, and social behavioral changes. Our results suggested that maternal exposure to PM2.5 during pregnancy might interfere with cerebral cortex development in mice offspring by affecting cell apoptosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".