Short-Term Chromium-Stress-Induced Alterations in the Maize Leaf Proteome
Bibliographic record
Abstract
Soil contamination by chromium (Cr) has become an increasing problem worldwide as a result of extensive industrial activities. Chromium, especially hexavalent Cr, impairs the growth and productivity of plants. Although it has been proposed that plants could modify their metabolism to adapt to Cr stress by reprogramming the expression of genes, especially those related to the antioxidant system, damage response, and electron transport chain, evidence at the protein expression level is lacking. To better understand the precise mechanisms underlying Cr phytoxicity and the plant response to Cr exposure, the time-course of changes in the protein expression profile induced by short-term hexavalent Cr exposure (1, 6 and 24 h) were analyzed in maize leaves. Among the over 1200 protein spots detected reproducibly by two-dimensional electrophoresis (2-DE), 60 were found to be differentially accumulated during Cr stress treatment. Of the Cr-regulated proteins, 58 were identified using tandem mass spectrometry (MS/MS). The Cr-regulated proteins identified were mainly involved in ROS detoxification and defense responses (26%), photosynthesis and chloroplast organization (22%), post-transcriptional processing of mRNA and rRNA (12%), protein synthesis and folding (10%), the DNA damage response (5%), and the cytoskeleton (3%). The possible involvement of these Cr stress-responsive proteins in Cr phytoxicity and the plant response to Cr exposure in maize is discussed, taking into consideration the information available from other plant models. Our results provide preliminary evidence that will facilitate understanding the molecular mechanisms underlying Cr toxicity in maize.
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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".