Proteomic Response of Cotton Leaves to Verticillium Wilt Infection
Why this work is in the frame
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Bibliographic record
Abstract
Verticillium wilt, caused by Verticillium dahliae , poses a significant threat to global cotton ( Gossypium hirsutum ) production, leading to substantial yield and quality losses. In this study, we employed a proteomic approach to investigate the molecular responses of cotton leaves to V. dahliae infection, aiming to elucidate defense mechanisms at the protein level. Using high-resolution mass spectrometry and bioinformatics analyses, we identified and quantified differentially expressed proteins (DEPs) in infected versus healthy cotton leaves, focusing on cultivar CRI 12 as a representative case. The identified DEPs were functionally categorized into defense and stress-related proteins, metabolic reprogramming factors, and signaling regulators, reflecting a complex reorganization of cellular processes in response to infection. Comparative proteomic analysis between susceptible and resistant cultivars revealed distinct defense protein profiles and metabolic adjustments associated with disease resistance. These findings provide insights into the molecular basis of cotton defense against V. dahliae and highlight candidate proteins for breeding and genetic engineering. This study underscores the value of integrative omics approaches in advancing our understanding of cotton-pathogen interactions and paves the way for the development of Verticillium wilt-resistant varieties through proteomic-guided breeding strategies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it