A Dual Strategy to Cope with High Light in <i>Chlamydomonas reinhardtii</i>
Bibliographic record
Abstract
Absorption of light in excess of the capacity for photosynthetic electron transport is damaging to photosynthetic organisms. Several mechanisms exist to avoid photodamage, which are collectively referred to as nonphotochemical quenching. This term comprises at least two major processes. State transitions (qT) represent changes in the relative antenna sizes of photosystems II and I. High energy quenching (qE) is the increased thermal dissipation of light energy triggered by lumen acidification. To investigate the respective roles of qE and qT in photoprotection, a mutant (npq4 stt7-9) was generated in Chlamydomonas reinhardtii by crossing the state transition-deficient mutant (stt7-9) with a strain having a largely reduced qE capacity (npq4). The comparative phenotypic analysis of the wild type, single mutants, and double mutants reveals that both state transitions and qE are induced by high light. Moreover, the double mutant exhibits an increased photosensitivity with respect to the single mutants and the wild type. Therefore, we suggest that besides qE, state transitions also play a photoprotective role during high light acclimation of the cells, most likely by decreasing hydrogen peroxide production. These results are discussed in terms of the relative photoprotective benefit related to thermal dissipation of excess light and/or to the physical displacement of antennas from photosystem II.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".