Vicia sativa subsp. sativa native to the Middle East comprises Pea Albumin1 b-like homologs: A promising natural biopesticide
Bibliographic record
Abstract
The extensive and indiscriminate use of chemical pesticides in agriculture has led to adverse effects on human health, environmental pollution, and the emergence of pesticide-resistant pests. To mitigate these challenges, the development of environmentally friendly alternatives is crucial, with biopesticides emerging as promising solutions such as peptides. Legume seeds naturally contain diverse insecticidal peptides or proteins to combat pest attacks. One such peptide is PA1b (Pea Albumin 1, subunit b), a 37 amino acid extracted from pea seeds ( Pisum sativum ). PA1b has shown significant potential in controlling cereal weevils ( Sitophilus spp.), a major pest of stored cereals. Here, we screened PA1b-like peptides in five wild seeds of vetches ( Vicia sativa subsp. sativa) from the Middle East. Using a comprehensive set of biochemical, biological, and molecular techniques, we characterized different PA1b homologs and assessed their toxicity and expression profiles. Our results reveal that PA1b homolog from Vicia sativa subsp. sativa originating from turkey displays outstanding insecticidal activity against Sitophilus oryzae through binding to the receptor site found in the midgut of the insect. Moreover, it exhibits a strong cytotoxic effect against Sf9 cells. This cysteine-rich peptide shows sequence identity and the same hydrophobic pole as AG41, a tenfold more toxic isoform of PA1b from Medicago truncatula . Such observations pave the way for the development of bioinsecticides, with PA1b-like peptides as lead compounds.
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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".