Non-Lethal Heat Shock of the Asian Green Mussel, Perna viridis, Promotes Hsp70 Synthesis, Induces Thermotolerance and Protects Against Vibrio Infection
Bibliographic record
Abstract
Mild heat stress promotes thermotolerance and protection against several different stresses in aquatic animals, consequences correlated with the accumulation of heat shock protein 70 (Hsp70). The purpose of this study was to determine if non-lethal heat shock (NLHS) of the Asian green mussel, Perna viridis, an aquatic species of commercial value, promoted the production of Hsp70 and enhanced its resistance to stresses. Initially, the LT50 and LHT for P. viridis were determined to be 42°C and 44°C, respectively, with no heat shock induced death of mussels at 40°C or less. Immunoprobing of western blots revealed augmentation of constitutive (PvHsp70-1) and inducible (PvHsp70-2) Hsp70 in tissue from adductor muscle, foot, gill and mantel of P. viridis exposed to 38°C for 30 min followed by 6 h recovery, NLHS conditions for this organism. Characterization by liquid chromatography-tandem mass spectrometry (LC-MS/MS) revealed that PvHsp70-1 and PvHsp70-2 respectively corresponded most closely to Hsp70 from P. viridis and Mytilus galloprovincialis. Priming of adult mussels with NLHS promoted thermotolerance and increased resistance to V. alginolyticus. The induction of Hsp70 in parallel with enhanced thermotolerance and improved protection against V. alginolyticus, suggests Hsp70 functions in P. viridis as a molecular chaperone and as a stimulator of the immune system.
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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".