The rectification of heterotypic Cx46/Cx50 gap junction channels depends on intracellular magnesium
Bibliographic record
Abstract
Gap junction (GJ) intercellular communication is crucial in many physiological and pathological processes. A GJ channel is formed by head-to-head docking of two hexameric hemichannels from two neighboring cells. Heterotypic GJ channels formed by two different homomeric connexin hemichannels often display rectification properties in the current–voltage relationship while the underlying mechanisms are not fully clear. Here we studied heterotypic Cx46/Cx50 GJs at a single GJ channel level. Our data showed unitary Cx46/Cx50 GJ channel conductance (γj) rectification when 5 mmol/L Mg2+ was included in the patch pipette solution, while no γj rectification was observed when no Mg2+ was added. Including 5 mmol/L Mg2+ in pipette solution significantly decreased the γj of homotypic Cx46 GJ with little change in homotypic Cx50 γj. A missense point variant in Cx46 (E43F) reduced the Mg2+-dependent reduction in γj of Cx46 E43F GJ, indicating that E43 might be partially responsible for Mg2+-dependent decrease in γj of Cx46. A comprehensive understanding of Mg2+ modulation of GJ at the individual channel level is useful in understanding factors in modulating GJ-mediated intercellular communication in health and diseases.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".