Impact of time intervals on drug efficacy and phenotypic outcomes in acute respiratory distress syndrome in mice
Bibliographic record
Abstract
Acute respiratory distress syndrome is a severe lung condition resulting from various causes, with life-threatening consequences that necessitate intensive care. The phenomenon can be modeled in preclinical models, notably through the use of lipopolysaccharide (LPS) instillation in mice. The phenotype induced closely recapitulates the human syndrome, including pulmonary edema, leukocyte infiltration, acute inflammation, impaired pulmonary function, and histological damage. However, the experimental designs using LPS instillations are extremely diverse in the literature. This highly complicates the interpretation of the induced phenotype chronology for future study design and hinders the proper identification of the optimal time frame to assess different readouts. Therefore, the definition of the treatment window in relation to the beginning of the disease onset also presents a significant challenge to address questions or test compound efficacy. In this context, the temporality of the different readouts usually measured in the model was evaluated in both normal and neutrophil-depleted male C57bl/6 mice using LPS-induction to assess the best window for proper readout evaluation with an optimal dynamic response range. Ventilation parameters were evaluated by whole-body plethysmography and neutrophil recruitment were evaluated in bronchoalveolar lavage fluids and in lung tissues directly. Imaging evaluation of myeloperoxidase along with activity in lung lysates and fluids were compared, along with inflammatory cytokines and lung extravasation by enzyme-linked immunoassays. Moreover, dexamethasone, the gold standard positive control in this model, was also administered at different times before and after phenotype induction to assess how kinetics affected each parameter. Overall, our data demonstrate that each readout evaluated in this study has a singular kinetic and highlights the key importance of the timing between ARDS phenotype and treatment administration and/or analysis. These findings also strongly suggest that analyzes, both in-life and post-mortem should be conducted at multiple time points to properly capture the dynamic phenotype of the LPS-ARDS model and response to treatment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".