Unrestrictive identification of post-translational modifications in <i>Hevea brasiliensis</i> latex
Bibliographic record
Abstract
The natural rubber latex extracted from the bark of Hevea brasiliensis plays various important roles in modern society. Post-translational modifications (PTMs) of the latex proteins are important for the stability and functionality of the proteins. In this study, latex proteins were acquired from the C-serum, lutoids, and rubber particle layers of latex without using prior enrichment steps; they were fragmented using collision-induced dissociation (CID), higher-energy collisional dissociation (HCD), and electron-transfer dissociation (ETD) activation methods. PEAKS 7 were used to search for unspecified PTMs, followed by analysis through PTM prediction tools to crosscheck both results. There were 73 peptides in 47 proteins from H. brasiliensis protein sequences derived from UniProtKB were identified and predicted to be post-translationally modified. The peptides with PTMs identified include phosphorylation, lysine acetylation, N-terminal acetylation, hydroxylation, and ubiquitination. Most of the PTMs discovered have yet to be reported in UniProt, which would provide great assistance in the research of the functional properties of H. brasiliensis latex proteins, as well as being useful biomarkers. The data are available via the MassIVE repository with identifier MSV000082419.
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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 | 0.000 |
| 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".