Pannexin channels are not gap junction hemichannels
Bibliographic record
Abstract
Pannexins, a class of membrane channels, bear significant sequence homology with the invertebrate gap junction proteins, innexins and more distant similarities in their membrane topologies and pharmacological sensitivities with the gap junction proteins, connexins. However, the functional role for the pannexin oligomers, or pannexons, is different from connexin oligomers, the connexons. Many pannexin publications have used the term "hemichannels" to describe pannexin oligomers while others use the term "channels" instead. This has led to confusion within the literature about the function of pannexins that promotes the idea that pannexons serve as gap junction hemichannels and thus have an assembly and functional state as gap junctional intercellular channels. Here we present the case that unlike the connexin gap junction intercellular channels, so far, pannexin oligomers have repeatedly been shown to be channels that are functional in single membranes, but not as intercellular channel in appositional membranes. Hence, they should be referred to as channels and not hemichannels. Thus, we advocate that in the absence of firm evidence that pannexins form gap junctions, the use of the term "hemichannel" be discontinued within the pannexin literature.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".