Hypometabolism to survive the long polar night and subsequent successful return to light in the diatom <i>Fragilariopsis cylindrus</i>
Bibliographic record
Abstract
Diatoms, the main eukaryotic phytoplankton of the polar marine regions, are essential for the maintenance of food chains specific to Arctic and Antarctic ecosystems, and are experiencing major disturbances under current climate change. As such, it is fundamental to understand the physiological mechanisms and associated molecular basis of their endurance during the long polar night. Here, using the polar diatom Fragilariopsis cylindrus, we report an integrative analysis combining transcriptomic, microscopic and biochemical approaches to shed light on the strategies used to survive the polar night. We reveal that in prolonged darkness, diatom cells enter a state of quiescence with reduced metabolic and transcriptional activity, during which no cell division occurs. We propose that minimal energy is provided by respiration and degradation of protein, carbohydrate and lipid stores and that homeostasis is maintained by autophagy in prolonged darkness. We also report internal structural changes that manifest the morphological acclimation of cells to darkness, including the appearance of a large vacuole. Our results further show that immediately following a return to light, diatom cells are able to use photoprotective mechanisms and rapidly resume photosynthesis, demonstrating the remarkable robustness of polar diatoms to prolonged darkness at low temperature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".