Doxycycline impairs neutrophil migration to the airspaces of the lung in mice exposed to intratracheal lipopolysaccharide
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Tetracyclines are broad-spectrum antibiotics that are also used to induce gene expression using the reverse tetracycline transactivator / tetracycline operator system (rtTA/tetO system). The system assumes that tetracyclines have no effects on mammals. However, a number of studies suggest that tetracyclines may have powerful anti-inflammatory effects. We report that the tetracycline, doxycycline, inhibits neutrophil (PMN) influx into the lungs of mice treated with bacterial endotoxin (LPS). METHODS: Mice were challenged with intratracheal LPS in the presence or absence of doxycyline. bronchoalveolar lavage cell counts and differential, total bronchoalveolar lavage protein, lung homogenate caspase-3 and tissue imaging were used to assess lung injury. In addition, PMN chemotaxis was measured in vitro and syndecan-1 was measured in bronchoalveolar lavage fluid. RESULTS: The administration of doxycycline resulted in a significant decrease in the number of bronchoalveolar lavage PMNs in LPS-treated mice. Doxycycline had no effect on other markers of lung injury such as total bronchoalveolar lavage protein and whole lung caspase-3 activity. However, doxycycline resulted in a decrease in shed syndecan-1 in bronchoalveolar lavage fluid. CONCLUSION: We conclude that doxycycline has an important anti-inflammatory effect that can potentially confound the experiments in which the rtTA/tetO system is being used to study the immune response.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it