With a Little Help from My Cell Wall: Structural Modifications in Pectin May Play a Role to Overcome Both Dehydration Stress and Fungal Pathogens
Bibliographic record
Abstract
Cell wall structural modifications through pectin cross-linkages between calcium ions and/or boric acid may be key to mitigating dehydration stress and fungal pathogens. Water loss was profiled in a pure pectin system and in vivo. While calcium and boron reduced water loss in pure pectin standards, the impact on Allium species was insignificant (p > 0.05). Nevertheless, synchrotron X-ray microscopy showed the localization of exogenously applied calcium to the apoplast in the epidermal cells of Allium fistulosum. Exogenous calcium application increased viscosity and resistance to shear force in Allium fistulosum, suggesting the formation of calcium cross-linkages (“egg-box” structures). Moreover, Allium fistulosum (freezing tolerant) was also more tolerant to dehydration stress compared to Allium cepa (freezing sensitive). Furthermore, the addition of boric acid (H3BO3) to pure pectin reduced water loss and increased viscosity, which indicates the formation of RG-II dimers. The Arabidopsis boron transport mutant, bor1, expressed greater water loss and, based on the lesion area of leaf tissue, a greater susceptibility to Colletotrichum higginsianum and Botrytis cinerea. While pectin modifications in the cell wall are likely not the sole solution to dehydration and biotic stress resistance, they appear to play an important role against multiple stresses.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".