A lentinan-loaded calcium alginate hydrogel with a core-shell structure induces broad-spectrum resistance to plant viruses by activating CML19
Bibliographic record
Abstract
Control of plant virus diseases largely depends on the induced plant defense achieved by the external application of synthetic chemical inducers with the ability to modify defense-signaling pathways. However, most of the molecular mechanisms underlying these chemical inducers remain unknown. Here, we developed a lentinan-loaded hydrogel with a core-shell structure and discovered how it protects plants from different virus infections. The hydrogel was synthesized by adding a chitosan shell on the surface of the polyanion sodium alginate-Ca2+-lentinan (LNT) hydrogel (SL-gel) to form a CSL-gel. CSL-gels exhibit the capacity to prolong the stable release of lentinan and promote Ca2+ release. Application of CSL-gels on the root of plants induces broad-spectrum resistance against TMV, TRV, PVX and TuMV). RNA-seq analysis identified that the calmodulin-like protein 19 gene (CML19) is upregulated by the sustained release of Ca2+ from the CSL-gel, and silencing and overexpression of CML19 alter the susceptibility and resistance of tobacco to TMV. Our findings provide evidence that this novel and synthetic CSL-gel strongly inhibits the infection of plant viruses by the sustainable release of LNT and Ca2+. This study uncovers a novel mode of action by which CSL-gels trigger CML19 expression through the stable and sustained release of Ca2+.
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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".