The Antibacterial and Anti-inflammatory Activity of Chicken Cathelicidin-2 combined with Exogenous Surfactant for the Treatment of Cystic Fibrosis-Associated Pathogens
Bibliographic record
Abstract
Cystic fibrosis (CF) is characterized by recurrent airway infections with antibiotic-resistant bacteria and chronic inflammation. Chicken cathelicin-2 (CATH-2) has been shown to exhibit antimicrobial activity against antibiotic-resistant bacteria and to reduce inflammation. In addition, exogenous pulmonary surfactant has been suggested to enhance pulmonary drug delivery. It was hypothesized that CATH-2 when combined with an exogenous surfactant delivery vehicle, bovine lipid extract surfactant (BLES), would exhibit antimicrobial activity against CF-derived bacteria and downregulate inflammation. Twelve strains of CF-pathogens were exposed to BLES+CATH-2 in vitro and killing curves were obtained to determine bactericidal activity. Secondly, heat-killed bacteria were administered in vivo to elicit a pro-inflammatory response with either a co-administration or delayed administration of BLES+CATH-2 to assess the antimicrobial-independent, anti-inflammatory properties of BLES+CATH-2. CATH-2 alone exhibited potent antimicrobial activity against all clinical strains of antibiotic-resistant bacteria, while BLES+CATH-2 demonstrated a reduction, but significant antimicrobial activity against bacterial isolates. Furthermore, BLES+CATH-2 reduced inflammation in vivo when either co-administered with killed bacteria or after delayed administration. The use of a host-defense peptide combined with an exogenous surfactant compound, BLES+CATH-2, is shown to exhibit antimicrobial activity against antibiotic-resistant CF bacterial isolates and reduce inflammation.
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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) | 0.000 | 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 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".