Bibliographic record
Abstract
Connexins form tightly‐regulated large‐pore channels that facilitate the passage of various ions, metabolites, and signaling molecules directly between cells, or in some cases and/or pathologies, to the extracellular milieu. The human connexin encoding gene family consists of 21 members and mutations in half of these genes leads to over two dozen diseases ranging in severity from manageable developmental abnormalities to life‐shortening organ failure. Developmentally, connexin expression and gap junctional intercellular communication begins at the 8 cell stage and persists throughout organogenesis resulting in most adult cells expressing two or more connexin subtypes. Connexin genes are exquisitely regulated during all developmental processes before birth, and in many tissues like the skin, after birth. Connexins regulate their function by channel gating processes and notably through their turnover owing to their short half‐life of only a few hours. Given their ubiquitous distribution it is not at all surprising that gene mutations lead to disease. In fact, it is probably more surprising that patients harbouring connexin gene mutations do not present with more clinical morbidities. Our laboratory has used tissue‐relevant cells, primary cells, organotypic cultures, mouse models of human diseases, and induced pluripotent stem cells from connexin‐linked disease patients to uncover ten distinct mechanisms by which connexin gene mutations cause disease. Collectively, connexin‐disease linked mutants have been classified into distinct gain‐ and loss‐of function molecular mechanisms of action. Our long‐term goals include developing strategies to compensate or overcome the cellular and tissue defects triggered by these mutants. This presentation will discuss how connexins have emerged as therapeutic targets in disease and in injury repair. We anticipate that once it is better understood how connexin gene mutations cause disease and abnormalities, which often present more acutely during aging, these findings could be translated into pre‐clinical studies leading to possible treatments for gap junction‐linked diseases. Support or Funding Information Supported by the Canadian Institutes of Health Research. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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 | 0.001 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".