Altered blood chemistry and hippocampal histomorphology in adult rats following prenatal exposure to physiologically-patterned, weak (50–500 nanoTesla range) magnetic fields
Bibliographic record
Abstract
PURPOSE: To discern changes in blood chemistry, cerebral sizes, and hippocampal cytomorphology in adult male and female albino Wistar rats that had been exposed during their entire prenatal development to one of two patterns of magnetic fields and one of four intensities: Very low 5 - 20 nT; low 30 - 50 nT; medium 90 - 580 nT; and high 590 nT to 1.2 microT. MATERIALS AND METHODS: A total of 48 pregnant females were exposed to either a repetitive frequency-modulated magnetic field or to a complex sequence of 50, 200-msec physiologically-patterned fields. As adults blood, cerebral, and histomorphological data were obtained from the 137 rats that had been exposed to one of these eight conditions. RESULTS: Compared to other groups, adult rats that had been exposed prenatally to the physiologically-patterned magnetic fields at the low (30 - 50 nT) and medium (90 - 580 nT) intensities exhibited peak elevations of aminotransaminase, glucose, and uric acid. Numbers of cytometric anomalies were also significantly elevated within regions of the hippocampus known for neuronal neogenesis in adults. CONCLUSIONS: The results suggest that a common factor in cellular adhesion or plasticity might be permanently altered by prenatal exposure to a narrow intensity of a series of physiologically-patterned magnetic fields.
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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 | 0.000 |
| 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".