Drought affects both photosystems in <i>Arabidopsis thaliana</i>
Bibliographic record
Abstract
Summary Drought is a major abiotic stress that impairs plant growth and development. Despite this, a comprehensive understanding of drought effects on the photosynthetic apparatus is lacking. In this work, we studied the consequences of 14‐d drought treatment on Arabidopsis thaliana. We used biochemical and spectroscopic methods to examine photosynthetic membrane composition and functionality. Drought led to the disassembly of PSII supercomplexes and the degradation of PSII core. The light‐harvesting complexes (LHCII) instead remain in the membrane but cannot act as an antenna for active PSII, thus representing a potential source of photodamage. This effect can also be observed during nonphotochemical quenching (NPQ) induction when even short pulses of saturating light can lead to photoinhibition. At a later stage, under severe drought stress, the PSI antenna size is also reduced and the PSI‐LHCI supercomplexes disassemble. Surprisingly, although we did not observe changes in the PSI core protein content, the functionality of PSI is severely affected, suggesting the accumulation of nonfunctional PSI complexes. We conclude that drought affects both photosystems, although at a different stage, and that the operative quantum efficiency of PSII (ΦPSII) is very sensitive to drought and can thus be used as a parameter for early detection of drought stress.
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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 | 0.001 |
| 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".