Menadione as a Novel Approach to Increasing Carbon Monoxide Production in Pregnancy: Establishing a Possible Therapeutic Role in Pre-eclampsia
Bibliographic record
Abstract
Despite its negative connotation as a toxic gas, carbon monoxide (CO) is involved in anti-inflammatory, cytoprotective and vasodilatory processes, suggesting a possible therapeutic role in many disease states. Endogenous CO production results in a resting percent carboxyhemoglobin (%COHb) level of 0.5 – 1.5% in humans. In smokers, this can rise to 17%. It has been shown that women who smoke have a lower risk of developing pre-eclampsia (PE), which is thought to be due to an increase in CO. PE is a pregnancy-related disease that is characterized by new-onset hypertension and proteinuria. PE is multifactorial, but a common belief is that poor placentation and systemic maternal endothelial dysfunction are involved in its pathogenesis. Menadione (MD), synthetic vitamin K3, increases CO production in rat brain microsomes. This research tested the hypothesis that MD could also raise CO in the blood and tissue of pregnant mice. A dose-response study was first conducted in non-pregnant mice to determine an efficacious, non-lethal dose. After determining their baseline water consumption rate, non-pregnant CD-1 mice were given one of three doses of MD in drinking water for seven days. No significant differences in %COHb between groups were observed. Splenic CO production and mass doubled in the 4 g/L and 6.5 g/L MD groups, compared to the 1.5 g/L and control cohorts. In a separate experiment, the effect of MD on gestational day (GD) 15 placental tissue CO production was tested using two different tissue preparation methods. Non-linear regression showed that while absolute levels of CO were higher in sonicated placentas than whole placentas, the relative increase in CO between concentrations was the same using either method. Lastly, oral administration of 6.5 g/L MD from GD10.5 – 17.5 significantly decreased maternal weight gain and fetal survival. Significant increases in %COHb and splenic CO were seen in the treatment group on GD17.5, with a positive trend for CO production in the liver, placenta and kidney. Overall, the findings demonstrate that MD can induce CO production in vivo. However, further studies in a mouse model of PE at a safer dose must be done to establish the drug’s therapeutic potential.
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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) | 0.002 | 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".