Novispirin G10-Induced Lung Toxicity in a<i>Klebsiella pneumoniae</i>InfectionModel
Bibliographic record
Abstract
Mammalian cathelicidins are a class of innate antimicrobial peptides isolated from leukocytes and epithelial cells that aid host defense against bacterial infections. Synthetic analogs of cathelicidins offer the promise of potent broad-spectrum antimicrobial efficacy. We developed a combined lung infection and ex vivo whole-blood assay model to characterize the toxicity and efficacy of synthetic cathelicidin-derived peptides. Male C57BL/6 mice were administered saline or Klebsiella pneumoniae by intratracheal instillation. Five hours later, the Klebsiella-infected mice were instilled with saline, tobramycin (1 mg/kg of body weight or 10 mg/kg), novispirin G10 (0.4 mg/kg), or a combination of tobramycin (1 mg/kg) and G10 (0.4 mg/kg). At 24 h, bronchoalveolar lavage fluid (BAL) was collected for analysis of culturable bacteria and for markers of inflammation and lung toxicity. Blood samples were analyzed for circulating cytokines. Recovery of Klebsiella from the lung, recruitment of neutrophils, and production of interleukin-6 (IL-6) in BAL samples were highly correlated (r=0.68 and 0.84, respectively; P<0.01). Animals treated with G10 or G10 plus tobramycin had increased hemoglobin (P<0.001) and protein (P<0.001) levels compared to those for Klebsiella-infected or tobramycin-alone-treated animals. The levels of circulating IL-6 in mice infected with Klebsiella were 1000- to 10,000-fold higher than in the noninfected controls. The highest levels of IL-6 were measured in mice given G10 alone or in combination with tobramycin. These studies demonstrated that G10 was relatively nontoxic in saline-treated mice but was highly toxic in mice infected with Klebsiella. This finding establishes the importance of investigating candidate antimicrobial agents in an in vivo infection model.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".