Modulation of Calu‐3 Anion Channels by H1N1 Infection
Bibliographic record
Abstract
Influenza virus A infection leads to pulmonary edema through a disruption of the fluid balance in the lungs. Part of this balance is maintained by the regulation of the anion channels in the respiratory epithelium lining the airway. Upon influenza infection this respiratory epithelium produces cytokines that aid in fighting the infection starting around 6 hours. These same cytokines by themselves have been shown to alter anion channel function. In this study, using the Calu‐3 respiratory epithelial cell line, we measure cytokine production by real time quantitative RT‐PCR as well as anion channel function as short‐circuit current produced by a Calu‐3 monolayer in a Ussing Chamber. Viral protein production was shown along with an increase in pro‐inflammatory cytokines at 24 hours post infection. Interestingly, no change in short‐circuit current response was found at 24 hours. A change in short‐circuit current response was first noted at 48 hours post infection. This change in short‐circuit current seems to be a direct effect on anion channel conductance and not a decrease in tissue viability as the resistance of the Calu‐3 monolayer did not significantly change. This study is the first step in understanding the pathophysiology which drives fluid into the lungs during an influenza A infection. This study was supported by SHRF, EHRF, CAHF, CFI and NSERC.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".