Proteome Decomplexation of <i>Trimeresurus erythrurus</i> Venom from Mizoram, India
Bibliographic record
Abstract
Green pit vipers are the largest group of venomous vipers in tropical and subtropical Asia, which are responsible for most of the bite cases across this region. Among the green pit vipers of the Indian subcontinent, Trimeresurus erythrurus is the most prevalent; however, limited knowledge is available about its venomics. Proteome decomplexation of T. erythrurus venom using mass spectrometry revealed a blend of 53 different proteins/peptides belonging to 10 snake venom protein families. Phospholipase A 2 and snake venom serine proteases were found to be the major enzymatic families, and Snaclec was the major nonenzymatic family in this venom. These protein families might be responsible for consumptive coagulopathy in victims. Along with these, snake venom metalloproteases, l -amino acid oxidases, disintegrins, and cysteine-rich secretory proteins were also found, which might be responsible for inducing painful edema, tissue necrosis, blistering, and defibrination in patients. Protein belonging to C-type lectins, C-type natriuretic peptides, and glutaminyl-peptide cyclotransfreases were also observed as trace proteins. The crude venom shows platelet aggregation in the absence of any agonist, suggesting their role in alterations in platelet functions. This study is the first proteomic analysis of T. erythrurus venom, contributing an overview of different snake venom proteins/peptides responsible for various pathophysiological disorders obtained in patients. Data are available via ProteomeXchange with the identifier PXD038311 .
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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 | 0.001 | 0.001 |
| 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".