Anesthetic Alterations of Collective Terahertz Oscillations in Tubulin Correlate with Clinical Potency: Implications for Anesthetic Action and Post-Operative Cognitive Dysfunction
Bibliographic record
Abstract
Anesthesia blocks consciousness and memory while sparing non-conscious brain activities. While the exact mechanisms of anesthetic action are unknown, the Meyer-Overton correlation provides a link between anesthetic potency and solubility in a lipid-like, non-polar medium. Anesthetic action is also related to an anesthetic's hydrophobicity, permanent dipole, and polarizability, and is accepted to occur in lipid-like, non-polar regions within brain proteins. Generally the protein target for anesthetics is assumed to be neuronal membrane receptors and ion channels, however new evidence points to critical effects on intra-neuronal microtubules, a target of interest due to their potential role in post-operative cognitive dysfunction (POCD). Here we use binding site predictions on tubulin, the protein subunit of microtubules, with molecular docking simulations, quantum chemistry calculations, and theoretical modeling of collective dipole interactions in tubulin to investigate the effect of a group of gases including anesthetics, non-anesthetics, and anesthetic/convulsants on tubulin dynamics. We found that these gases alter collective terahertz dipole oscillations in a manner that is correlated with their anesthetic potency. Understanding anesthetic action may help reveal brain mechanisms underlying consciousness, and minimize POCD in the choice and development of anesthetics used during surgeries for patients suffering from neurodegenerative conditions with compromised cytoskeletal microtubules.
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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".