Skin in the game: pannexin channels in healthy and cancerous skin
Bibliographic record
Abstract
The skin is a highly organized tissue composed of multiple layers and cell types that require coordinated cell to cell communication to maintain tissue homeostasis. In skin cancer, this organized structure and communication is disrupted, prompting the malignant transformation of healthy cells into melanoma, basal cell carcinoma or squamous cell carcinoma tumours. One such family of channel proteins critical for cellular communication is pannexins (PANX1, PANX2, PANX3), all of which are present in the skin. These heptameric single-membrane channels act as conduits for small molecules and ions like ATP and Ca2+ but have also been shown to have channel-independent functions through their interacting partners or action in signalling pathways. Pannexins have diverse roles in the skin such as in skin development, aging, barrier function, keratinocyte differentiation, inflammation, and wound healing, which were discovered through work with pannexin knockout mice, organotypic epidermis models, primary cells, and immortalized cell lines. In the context of cutaneous cancer, PANX1 is present at high levels in melanoma tumours and functions in melanoma carcinogenesis, and both PANX1 and PANX3 expression is altered in non-melanoma skin cancer. PANX2 has thus far not been implicated in any skin cancer. This review will discuss pannexin isoforms, structure, trafficking, post-translational modifications, interactome, and channel activity. We will also outline the expression, localization, and function of pannexin channels within the diverse cell types of the epidermis, dermis, hypodermis, and adnexal structures of the skin, and how these properties are exploited or abrogated in instances of skin cancer.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".