MicroRNA Regulation in Extreme Environments: Differential Expression of MicroRNAs in the Intertidal Snail <i>Littorina Littorea</i> During Extended Periods of Freezing and Anoxia
Bibliographic record
Abstract
Several recent studies of vertebrate adaptation to environmental stress have suggested roles for microRNAs (miRNAs) in regulating global suppression of protein synthesis and/or restructuring protein expression patterns. The present study is the first to characterize stress-responsive alterations in the expression of miRNAs during natural freezing or anoxia exposures in an invertebrate species, the intertidal gastropod Littorina littorea. These snails are exposed to anoxia and freezing conditions as their environment constantly fluctuates on both a tidal and seasonal basis. The expression of selected miRNAs that are known to influence the cell cycle, cellular signaling pathways, carbohydrate metabolism and apoptosis was evaluated using RT-PCR. Compared to controls, significant changes in expression were observed for miR-1a-1, miR-34a and miR-29b in hepatopancreas and for miR-1a-1, miR-34a, miR-133a, miR-125b, miR-29b and miR-2a in foot muscle after freezing exposure at -6 °C for 24 h (P<0.05). In addition, in response to anoxia stress for 24 h, significant changes in expression were also observed for miR-1a-1, miR-210 and miR-29b in hepatopancreas and for miR-1a-1, miR-34a, miR-133a, miR-29b and miR-2a in foot muscle (P<0.05). Moreover, protein expression of Dicer, an enzyme responsible for mature microRNA processing, was increased in foot muscle during freezing and anoxia and in hepatopancreas during freezing. Alterations in expression of these miRNAs in L. littorea tissues may contribute to organismal survival under freezing and anoxia.
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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) | 0.001 | 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".