Cellular Mechanisms of Saline Extract of Alligator Pepper (Zingiberaceae Aframomum melegueta) for Specific Protection against Preeclampsia
Bibliographic record
Abstract
Preeclampsia is a clinical syndrome defined as the new onset of hypertension and proteinuria during the second half of pregnancy. Though it is easily diagnosed clinically, affected persons must book in a health service facility for the diagnosis to be made. Furthermore regular screening is necessary during several antenatal visits and skilled attendant’s supervised labor before diagnosis can be made. Predictive tests are not yet well developed and not readily available in developing countries and medically underserved areas where they are needed most. There is therefore a need for specific protection against preeclampsia to be developed. This will ensure that all women are protected even when they choose not to visit an antenatal clinic. Specific protection is potentially capable of preventing preeclampsia in 5 % to 7% of pregnant women, the proportion of pregnant women that are affected by preeclampsia worldwide. This article builds on a previous article on the study of the cellular mechanisms underlying gestational weight gain and litter weight reduction effect of aqueous extract of Alligator pepper and attempts to analyze how the anti-hyperinsulinemic property of the constituents of Alligator pepper in that study can also prevent preeclampsia and suggests the use of some of the constituents of alligator pepper as specific protection (vaccine) for the prevention of preeclampsia.
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) | 0.000 | 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".