Lipid transfer proteins from <i>Brassica campestris</i> and mung bean surpass mung bean chitinase in exploitability
Bibliographic record
Abstract
Antifungal peptides with a molecular mass of 9 kDa and an N-terminal sequence demonstrating remarkable similarity to those of nonspecific lipid transfer proteins (nsLTPs) were isolated from seeds of the vegetable Brassica campestris and the mung bean. The purified peptides exerted an inhibitory action on mycelial growth in various fungal species. The antifungal activity of Brassica and mung bean nsLTPs were thermostable, pH-stable, and stable after treatment with pepsin and trypsin. In contrast, the antifungal activity of mung bean chitinase was much less stable to changes in pH and temperature. Brassica LTP inhibited proliferation of hepatoma Hep G2 cells and breast cancer MCF 7 cells with an IC(50) of 5.8 and 1.6 microM, respectively, and the activity of HIV-1 reverse transcriptase with an IC(50) of 4 microM. However, mung bean LTP and chitinase were devoid of antiproliferative and HIV-1 reverse transcriptase inhibitory activities. In contrast to the mung bean LTP, which exhibited antibacterial activity, Brassica LTP was inactive. All three antifungal peptides lacked mitogenic activity toward splenocytes. These results indicate that the two LTPs have more desirable activities than the chitinase and that there is a dissociation between the antifungal and other activities of these antifungal proteins.
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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".