Compromised Regeneration, Damage to Blood Vessels and the Endomysium Underpin Permanent Muscle Damage Induced by Puff Adder (Bitis arietans) Venom
Bibliographic record
Abstract
The puff adder (Bitis arietans) is a clinically relevant viper species found throughout Africa, and it is responsible for a greater incidence of health-related envenomations than all other snake species on the continent combined. Unresolved skeletal muscle damage is a common consequence of B. arietans envenomation that can result in long-term morbidity and even death. Antivenom treatment can mitigate the systemic effects of the venom but offers little protection against local tissue damage. Identifying the mechanisms through which B. arietans venom induces tissue damage and impedes skeletal muscle regeneration could identify possible treatment alternatives that could help alleviate the long-term consequences of envenomation. Skeletal muscle has an innate ability to regenerate, but constituents within the venom can impede multiple stages of this regeneration process. In this study, we employed a combination of biochemical analyses, cell-based assays, and in vivo experiments to assess the toxicological implications of B. arietans envenomation and its impacts on key processes of regeneration. Our findings demonstrate that the pathological characteristics of permanent muscle damage resulting from B. arietans envenomation may be attributed to the venom’s effects on muscle stem cell precursors, the extracellular matrix (ECM), and the influence of blood-borne proteins that promote fibrosis.
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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) | 0.001 | 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".