Oxidative stress‐induced methemoglobinemia is the silent killer during snakebite: a novel and strategic neutralization by melatonin
Bibliographic record
Abstract
Oxidative stress-induced methemoglobinemia remained an untouched area in venom pharmacology till date. This study for the first time explored the potential of animal venoms to oxidize hemoglobin to methemoglobin. In in vitro whole-blood assay, methemoglobin forming ability of venoms varied as Naja naja > Ophiophagus hannah > Echis carinatus > Daboia russellii > Apis mellifera > Mesobuthus tamulus > Hippasa partita. Being highly potential, N. naja venom was further studied to observe methemoglobin formation in RBCs and in combinations with PMNs and PBMCs, where maximum effect was observed in RBCs + PMNs combination. Naja naja venom/externally added methemoglobin-induced methemoglobin formation was in parallel with ROS generation in whole blood/RBCs/RBCs + PMNs/RBCs + PBMCs. In in vivo studies, the lethal dose (1 mg/kg body weight, i.p.) of N. naja venom readily induced methemoglobin formation, ROS generation, expression of inflammatory markers, and hypoxia-inducible factor-3α. Although the mice administered with three effective doses of antivenom recorded zero mortality; the methemoglobin and ROS levels remained high. However, one effective dose of antivenom when administered along with melatonin (1:50; venom/melatonin, w/w), not only offered 100% survival of experimental mice, but also significantly reduced methemoglobin level, and oxidative stress markers including hypoxia-inducible factor-3α. This study provides strong drive that, complementing melatonin would not only reduce the antivenom load, but for sure greatly increase the success rate of antivenom therapy and drastically minimize the global incidence of snakebite deaths. However, further detailed investigations are needed before translating the combined therapy towards the bed side.
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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".