CXCL1 Regulates Pulmonary Host Defense to <i>Klebsiella</i> Infection via CXCL2, CXCL5, NF-κB, and MAPKs
Bibliographic record
Abstract
Pulmonary bacterial infections are a leading cause of death. Since the introduction of antibiotics, multidrug-resistant Klebsiella pneumoniae became an escalating threat. Therefore, development of methods to augment antibacterial defense is warranted. Neutrophil recruitment is critical to clear bacteria, and neutrophil migration in the lung requires the production of ELR(+) CXC chemokines. Although lung-specific CXCL1/keratinocyte cell-derived chemokine (KC) transgene expression causes neutrophil-mediated clearance of K. pneumoniae, the mechanisms underlying KC-mediated host defense against K. pneumoniae have not been explored. In this study, we delineated the host defense functions of KC during pulmonary K. pneumoniae infection using KC(-/-) mice. Our findings demonstrate that KC is important for expression of CXCL2/MIP-2 and CXCL5/LPS-induced CXC chemokine, and activation of NF-κB and MAPKs in the lung. Furthermore, KC derived from both hematopoietic and resident cells contributes to host defense against K. pneumoniae. Neutrophil depletion in mice before K. pneumoniae infection reveals no differences in the production of MIP-2 and LPS-induced CXC chemokine or activation of NF-κB and MAPKs in the lung. Using murine bone marrow-derived and alveolar macrophages, we confirmed KC-mediated upregulation of MIP-2 and activation of NF-κB and MAPKs on K. pneumoniae infection. Moreover, neutralizing KC in bone marrow-derived macrophages before K. pneumoniae challenge decreases bacteria-induced production of KC and MIP-2, and activation of NF-κB and MAPKs. These findings reveal the importance of KC produced by hematopoietic and resident cells in regulating pulmonary host defense against a bacterial pathogen via the activation of transcription factors and MAPKs, as well as the expression of cell adhesion molecules and other neutrophil chemoattractants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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".