EP80317 Restrains Inflammation and Mortality Caused by Scorpion Envenomation in Mice
Bibliographic record
Abstract
Over 1 million cases of scorpion stings are estimated every year, whereas current treatment is limited to antivenom serum combined with supportive therapy. Tityus serrulatus scorpion venom (TsV) is composed of diverse molecules, including toxins that induce a catecholamine storm and mediate classical symptoms of scorpion envenomation. However, the same toxins promote an intense inflammatory response coordinated by innate immune cells, such as macrophages, contributing significantly to the lung edema and mortality caused by TsV injection. Macrophages sense TsV via innate immune receptors, including TLR2, TLR4, and CD14 that promote inflammation and mortality via PGE2/cAMP/PKA/NF-κB/IL-1β axis. The scavenger receptor CD36 also recognizes TsV, but in contrast to the other receptors, it drives the production of leukotriene B4 (LTB4). This lipid mediator operates via BLT1 receptor to reduce cAMP production and consequently IL-1β release, which results in resistance to fatal outcomes of experimental scorpion envenomation. EP80317 is an hexapeptide that serves as a ligand for CD36 and features protective effects under conditions such as atherosclerosis and vascular inflammation. In this study, we evaluated the effects of EP80317 treatment during experimental scorpion envenomation. EP80317 treatment suppressed mouse peritoneal macrophage production of IL-1β, IL-6, tumor necrosis factor (TNF-α), CCL3, and PGE2in vitro. EP80317 treatment also boosted the production of LTB4 and IL-10 in response to TsV. Importantly, EP80317 restrained lung inflammation and mortality caused by TsV in vivo. Taken together, these data indicate a strong therapeutic potential of EP80317 as a supportive treatment to control inflammation induced by scorpion envenomation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".