Packaging of mycosporine-like amino acids in dinoflagellates
Bibliographic record
Abstract
Synthesis of mycosporine-like amino acids (MAAs) can significantly protect phytoplankton cells against damaging ultraviolet (UV) radiation, depending on the concentration, type and cellular distribution of these UV sunscreens. We addressed the hypothesis that MAAs are concentrated around UV-sensitive organelles for improved efficiency, thereby increasing their 'package effect'. This was investigated for 2 species of MAA-producing dinoflagellates, with comparative analyses of a MAA-free diatom. Spectral absorbance of dinoflagellates suspended in their growth medium was relatively small throughout the MAA-absorbing region despite high concentrations of these compounds (determined by HPLC), suggesting that MAAs are highly packaged in intact cells. The measured in vivo absorbance of suspended and filtered phytoplankton cells revealed an extracellular release of water-soluble MAAs during freezing. The release of MAAs upon thawing enabled the calculation of an MAA packaging index based on the comparison between absorption characteristics before (MAAs inside cells in suspension) and after freezing (MAAs released from cells on thawed filters). Additionally, MAA packaging was evaluated from the reconstruction of absorption spectra from the individual MAA concentration. Consistent with our hypothesis, the results showed that UV absorption was up to 80% lower in the intact cells relative to the MAAs dissolved in solution. These results imply a high degree of MAA packaging in these dinoflagellates, that may increase the protection efficiency for specific cellular targets.
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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) | 0.000 | 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".