Effect of glutathione depletion, hyperthermia, and a 100‐mT static magnetic field on an hsp70/luc reporter system
Bibliographic record
Abstract
Heat shock proteins, in particular hsp70, are induced under conditions of cellular stress. It has been reported that environmental stimuli such as hyperthermia, oxidative stress, and exposure to magnetic fields increase levels of hsp70. It has also been reported that hyperthermia in combination with magnetic field exposure results in a synergistic increase in hsp70 production. We tested the hypothesis that oxidative stress induced by glutathione (GSH) depletion in combination with static magnetic field (SMF) exposure will produce a similar synergistic increase in hsp70 production. We exposed cells to heat, SMF, and diethylmaleate (DEM), which depletes GSH levels alone and in combination with each other, and measured hsp70 production using an hsp70/luciferase reporter and mRNA levels using PCR. We found that treatment with DEM significantly reduced the rate of luciferase bioluminescence production, particularly in the presence of heat. There was no significant effect of a 100-mT SMF exposure either alone or in combination with heat, DEM, or both on bioluminescence, however there was a significant interaction between SMF and DEM on hsp70 mRNA levels. Therefore, under our exposure conditions, GSH depletion reduced hsp70 levels but a synergistic effect of combining this stress with other external stimuli was only observed at the level of mRNA.
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) | 0.001 | 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".