Data from: Tissue-specific changes in apoplastic proteins and cell wall structure during cold acclimation of winter wheat crowns
Bibliographic record
Abstract
The wheat (Triticum aestivum L.) crown is the critical organ of low temperature stress survival over winter. In cold-acclimated crowns, ice formation in the apoplast causes severe tissue disruption as it grows at the expense of intracellular water. While previous crown studies have shown the vascular transition zone (VTZ) to have a higher freezing sensitivity than the shoot apical meristem (SAM), the mechanism behind the differential freezing response is not fully understood. Cooling cold-acclimated crowns to –10 °C resulted in an absence of VTZ tetrazolium chloride staining, whereas the temperatures at which 50% of the SAM stained positive and 50% of plants recovered (LT50) were similar after cold acclimation for 21 (–16 °C) and 42 d (–20 °C) at 4 °C. Proteomic analysis of the apoplastic fluids identified dehydrins, vernalization-responsive proteins, and cold shock proteins preferentially accumulated in the SAM. In contrast, modifications to the VTZ centered on increases in pathogenesis-related proteins, anti-freeze proteins, and sugar hydrolyzing enzymes. Fourier transform infrared spectroscopy focal plane array analysis identified the biochemical modification of the cell wall to enhance methyl-esterified cross-linking of glucuronoarabinoxylans in the VTZ. These findings indicate that the SAM and VTZ express two distinct tissue-specific apoplastic responses during cold acclimation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.009 |
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".