LRRC8/VRAC Channels and the Redox Balance: A Complex Relationship
Bibliographic record
Abstract
to the recovery of normal cell volume. For years, scientists have tried unsuccessfully to find their molecular identity, leading to controversy within the field that only ended in 2014 when two independent groups demonstrated that VRACs were formed by heteromers of LRRC8 proteins. This breakthrough gave a second breath to the research field and was followed by many publications regarding LRRC8/VRACs structure/ function, physiological roles and 3D structures. Nevertheless, far from simplifying the field, these discoveries have instead exponentially increased its complexity. Indeed, the channel's biophysical properties seem to be dependent on the LRRC8 subunits composition with each heteromer showing different ion/molecule permeabilities and regulatory mechanisms. One clear example of this complexity is the intricate relationship between LRRC8/VRACs and the redox system. On one hand, VRACs appear to be directly regulated by oxidation or reduction depending on their subunit composition. On the other hand, VRACs can also impact the redox balance within the cells, through their permeability to reduced glutathione or through other as yet uncharacterized pathways. Unravelling this issue is particularly crucial as LRRC8/VRACs play an important role in a wide variety of physiological processes involving oxidative stress signaling. In this regard, we have tried to systematically identify in the literature both preand post-LRRC8 discovery as well as the interplay between VRACs and the redox system to provide new insights into this complex relationship.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".