Bibliographic record
Abstract
Abstract The mammalian pannexin family of channel‐forming proteins consisting of Panx1, Panx2, and Panx3 has received considerable attention in the last 10 years given their newly discovered physiological roles in development and disease. Pannexins exhibit diverse subcellular profiles indicating that they may serve distinct roles in cells and tissues of different origin. This complexity in cellular residencies may be rooted in the fact that pannexin genes consist of multiple exons that have led to the identification of several splice variants. Additionally, post‐translational modifications, especially N‐glycosylation, appear to be important in regulating trafficking and intermixing of pannexin family members increasing the diversity of assembled channels. These long‐lived membrane proteins are typically trafficked through the classical secretory pathway before reaching the plasma membrane although Panx2 tends to often be retained in intracellular compartments. Trafficking, stability, and function of pannexins likely enlist the services of an interactome that continues to expand. The research field has been amazed by the fact that Panx1 null mice are generally healthy with distinct phenotypes only being revealed when mutant mice encounter additional stress or have comorbidities. The emerging field of pannexin biology has also begun to explore the relationships and potential cross‐talk between pannexin channels and connexin hemichannels. It is imperative to dissect the different constituents of the channels and the molecules that pass through these distinct channel types. Finally, as witnessed in connexin biology throughout the 90s, the field awaits to see if germline mutations in the genes that encode pannexins also cause disease. WIREs Membr Transp Signal 2012, 1:621–632. doi: 10.1002/wmts.63 For further resources related to this article, please visit the WIREs website .
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 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 | 0.001 | 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) | 0.000 | 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".