Examining Changes in Gramicidin Current Induced by Endocannabinoids
Bibliographic record
Abstract
ABSTRACT Endocannabinoids are a diverse family of lipid molecules, which circulate in the human body, impacting the cardiovascular and the nervous systems. Endocannabinoids can influence pain perception, appetite, stress responses, mood, memory and learning. Regulation of these lipids present a promising therapeutic avenue for numerous neurological disorders. In addition to acting as agonists to cannabinoid receptors (CBRs), endocannabinoids can also modulate the function of various ion channels and receptors independently of CBRs. This modulation of function can arise from direct binding to the channel proteins, or via changes to the lipid properties such as membrane elasticity/stiffness, curvature, or hydrophobic thickness. Here, we assess the effects of endocannabinoids on membrane properties by examining changes in gramicidin (gA) currents in Xenopus oocytes. Endocannabinoids from both classes (Fatty acid ethanolamides (FAEs) and 2-monoacylglycerols (2-MGs)) are studied and current-voltage relationships are assessed. Employing gramicidin channels as molecular force probes can enable both predictive and quantitative studies on the impact of bilayer-mediated regulation on membrane protein function by endocannabinoids.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".