Glycogen: A must have storage to survive stressful emergencies
Bibliographic record
Abstract
Mechanisms of adaptation to acute changes in osmolarity are fundamental for life. When exposed to hyperosmotic stress, cells and organisms utilize conserved strategies to prevent water loss and maintain cellular integrity and viability. The production of glycerol is a common strategy utilized by the nematode Caenorhabditis elegans (C. elegans) and many other organisms to survive hyperosmotic stress. Specifically, the transcriptional upregulation of glycerol-3-phosphate dehydrogenase, a rate-limiting enzyme in the production of glycerol, has been previously implicated in many model organisms. However, what fuels this massive and rapid production of glycerol upon hyperosmotic stress has not been clearly elucidated. We have recently discovered an AMPK-dependent pathway that mediates hyperosmotic stress resistance in C. elegans. Specifically, we demonstrated that the chronic activation of AMPK leads to glycogen accumulation, which under hyperosmotic stress exposure, is rapidly degraded to mediate glycerol production. Importantly, we demonstrate that this strategy is utilized by flcn-1 mutant C. elegans nematodes in an AMPK-dependent manner. FLCN-1 is the worm homolog of the human renal tumor suppressor Folliculin (FLCN) responsible for the Birt-Hogg-Dubé neoplastic syndrome. Here, we comment on the dual role for glycogen in stress resistance: it serves as an energy store and a fuel for osmolyte production. We further discuss the potential utilization of this mechanism by organisms in general and by human cancer cells in order to survive harsh environmental conditions and notably hyperosmotic stress.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".