Tight junction protein abundance is altered in Metformin treated airway epithelial cells
Bibliographic record
Abstract
Airway epithelial tight junction (TJ) proteins form a resistive barrier to the external environment, however during respiratory bacterial infection TJ abundance is altered. Metformin used for the treatment of diabetes is known to increase transepithelial resistance (TEER) of airway epithelial cells. We investigated the effect of metformin and Staphylococcus aureus inoculation on TJ abundance and the assembly/reassembly of the TJ protein in airway epithelial cells. Occludin protein was detected by immunoblot analysis with a major protein band at 60 kD with cleavage products at 46, 44 and 37 kD in human airway epithelial cells (H441), pre‐treatment with 1 mM metformin for 18h, resulted in an increase in the 60 kD protein band (13 ± 7%, P <0.05; n=4) and a decrease in the cleavage product at 44 kD (37 ± 4%, P <0.05; n=4). Inoculating H441 monolayers with S.aureus produced a significant reduction in abundance in both 60 and 44 kD protein bands (35 ± 11% and 41 ± 5% respectively, P <0.05; n=4) which was not reversed with metformin pre‐treatment. Similarly occludin and Z0‐1 abundance were both enhanced with metformin and reduced with S.aureus in immunostained epithelial monolayers. Disassembly and reassembly of TJs in the presence of a calcium chelating agent was not protected or enhanced by metformin pre‐treatment. These data provide evidence that metformin regulates TJ protein abundance through a mechanism that does not involve changes in assembly. Support or Funding Information MRC‐MICA MR/K012770/1
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".