Hypometabolism to survive the long polar night in the diatom <i>Fragilariopsis cylindrus</i>
Bibliographic record
Abstract
Abstract Diatoms, the major eukaryotic phytoplankton in polar regions, are essential to sustain Arctic and Antarctic ecosystems. As such, it is fundamental to understand the physiological mechanisms and associated molecular basis of their resilience to the long polar night. Here, we report an integrative approach revealing that in prolonged darkness, diatom cells enter a state of quiescence associated 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. Our results further indicate that immediately following a return to light, diatom cells are able to use photoprotective mechanisms and rapidly resume photosynthesis. Cell division resumed rates similar to those before darkness. Our study demonstrates the remarkable robustness of polar diatoms to prolonged darkness at low temperatures. Graphical abstract Teaser To survive the long winter, polar diatoms slow down metabolism and express genes to assure survival following return to light.
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) | 0.003 | 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".