KvLQT1 Function in Lung Physiology
Bibliographic record
Abstract
Acute lung injury and its more severe form, acute respiratory distress syndrome (ARDS), are characterized by extensive alveolar injury and lung edema. It has been established that the resolution of ARDS parameters is highly dependent on alveolar regeneration and edema resorption. Because we previously demonstrated that KvLQT1 potassium channels are involved in alveolar repair processes and in the control of ion and liquid transports in vitro , we now decided to investigate their role in lung function and in the resolution of ARDS parameters in vivo , using a KvLQT1 knockout (KO) mice model. We first noted an absence of morphological difference in airway structures (trachea, bronchus and alveolus) between control (wild type, WT) and KvLQT1 KO mice. We then evaluated the impact of KvLQT1 extinction on the mechanical properties of the respiratory system using the flexiVent system (SCIREQ Inc.). Our results showed a significant increase of tissue damping and dynamic resistance of the respiratory system in KvLQT1 KO mice compared to WT. The role of KvLQT1 was then evaluated in a model of lung edema induced by thiourea, disrupting the integrity of endothelial/alveolar barrier. We observed a significant increase in the wet/dry ratio (W/D, index of lung edema) in both WT and KO mice. Interestingly, the thiourea‐induced W/D increase was partially prevented by a treatment with R‐L3, a KvLQT1 activator, in WT mice. However, this beneficial effect of R‐L3 was lost in KO mice. Our results show that the activation of KvLQT1 K + channels could play a role in the resolution of ARDS parameters, especially pulmonary edema resorption. Funded by CIHR, NSERC, FRQS.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".