Pannexin channels and their links to human disease
Bibliographic record
Abstract
In less than a decade, a small family of channel-forming glycoproteins, named pannexins, have captured the interest of many biologists, in large part due to their association with common diseases, ranging from cancers to neuropathies to infectious diseases. Although the pannexin family consists of only three members (Panx1, Panx2 and Panx3), one or more of these pannexins are expressed in virtually every mammalian organ, implicating their potential role in a diverse array of pathophysiologies. Panx1 is the most extensively studied, but features of this pannexin must be cautiously extrapolated to the other pannexins, as for example we now know that Panx2, unlike Panx1, exhibits unique properties such as a tendency to be retained within intracellular compartments. In the present review, we assess the biochemical and channel features of pannexins focusing on the literature which links these unique molecules to over a dozen diseases and syndromes. Although no germ-line mutations in genes encoding pannexins have been linked to any diseases, many cases have shown that high pannexin expression is associated with disease onset and/or progression. Disease may also occur, however, when pannexins are underexpressed, highlighting that pannexin expression must be exquisitely regulated. Finally, we discuss some of the most pressing questions and controversies in the pannexin field as the community seeks to uncover the full biological relevance of pannexins in healthy organs and during disease.
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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 | 0.001 |
| 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) | 0.000 | 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".