Arctic Micromonas uses protein pools and non-photochemical quenching to cope with temperature restrictions on Photosystem II protein turnover
Bibliographic record
Abstract
Micromonas strains of small prasinophyte green algae are found throughout the world's oceans, exploiting widely different niches. We grew arctic and temperate strains of Micromonas and compared their susceptibilities to photoinactivation of Photosystem II, their counteracting Photosystem II repair capacities, their Photosystem II content, and their induction and relaxation of non-photochemical quenching. In the arctic strain Micromonas NCMA 2099, the cellular content of active Photosystem II represents only about 50 % of total Photosystem II protein, as a slow rate constant for clearance of PsbA protein limits instantaneous repair. In contrast, the temperate strain NCMA 1646 shows a faster clearance of PsbA protein which allows it to maintain active Photosystem II content equivalent to total Photosystem II protein. Under growth at 2 °C, the arctic Micromonas maintains a constitutive induction of xanthophyll deepoxidation, shown by second-derivative whole-cell spectra, which supports strong induction of non-photochemical quenching under low to moderate light, even if xanthophyll cycling is blocked. This non-photochemical quenching, however, relaxes during subsequent darkness with kinetics nearly comparable to the temperate Micromonas NCMA 1646, thereby limiting the opportunity cost of sustained downregulation of PSII function after a decrease in light.
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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 | 0.001 |
| 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 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".