Childhood physical abnormalities following paternal exposure to sulfur mustard gas in Iran: a case-control study
Bibliographic record
Abstract
BACKGROUND: Mustard gas, a known chemical weapon, was used during the Iran-Iraq war of 1980-1988. We aimed to determine if exposure to mustard gas among men was significantly associated with abnormalities and disorders among progenies. METHODS: Using a case-control design, we identified all progenies of Sardasht men (exposed group, n = 498), who were born at least nine months after the exposure, compared to age-matched controls in Rabat, a nearby city (non-exposed group, n = 689). We conducted a thorough medical history, physical examination, and appropriate paraclinical studies to detect any physical abnormality and/or disorder. Given the presence of correlated data, we applied Generalized Estimating Equation (GEE) multivariable models to determine associations. RESULTS: The overall frequency of detected physical abnormalities and disorders was significantly higher in the exposed group (19% vs. 11%, Odds Ratio [OR] 1.93, 95% Confidence Interval [CI], 1.37-2.72, P = 0.0002). This was consistent across sexes. Congenital anomalies (OR 3.54, 95% CI, 1.58-7.93, P = 0.002) and asthma (OR, 3.12, 95% CI, 1.43-6.80, P = 0.004) were most commonly associated with exposure. No single abnormality was associated with paternal exposure to mustard gas. CONCLUSION: Our study demonstrates a generational effect of exposure to mustard gas. The lasting effects of mustard gas exposure in parents effects fertility and may impact child health and development in the long-term.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".