Using lung-on-a-chip to characterize HIF-1α-dependent inflammatory responses during acute <i>Streptococcus pneumoniae</i> infection
Bibliographic record
Abstract
Abstract Current models used to study Streptococcus pneumoniae (SP) infections do not account for complex organ microenvironments or species-specific signaling pathways. To address this, we created a vascularized 3D lung-on-a-chip (LoC) that better recapitulates the physiologic lung, including cellular components, immune cell recruitment, blood flow, and oxygen tension. Hypoxia inducible factor 1-alpha (HIF-1α) is a transcription factor known to activate inflammatory pathways during infectious diseases, but its role in acute SP infection remains unclear. LoC was used to validate HIF-1α upregulation and characterize its role in immune cell recruitment. Whole human blood with fluorescently-labeled immune cells were perfused in LoC +/− BAY 87-2243 (HIF-1α chemical inhibitor). HIF1α-dependent inflammatory mediators involved in SP infection were identified by scRNA-seq and confirmed at the protein level by Western blot and ELISA. Preliminary studies of LoC stimulated with SP demonstrated HIF-1α early target gene activation. LoC showed increased CD15+-neutrophil recruitment from perfused whole blood in microvessels to tissue and airway during SP infection, partially mediated by HIF-1α. IL-17C was identified as the top differentially expressed gene activated by SP and 2D protein analysis showed increased IL-17C levels during HIF-1α knockdown, suggesting that HIF-1α is a negative regulator of IL-17C transcription. These preliminary findings suggest that HIF-1α mediates immune cell recruitment during acute SP infection and support the use of LoC as a pre-clinical human model that can identify key mediators during pneumonia.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".