Lung Inflammation Induced by Lipoteichoic Acid or Lipopolysaccharide in Humans
Bibliographic record
Abstract
RATIONALE: Recognition of pathogen-associated molecular patterns by Toll-like receptors (TLRs) is considered to be important for an appropriate immune response against pathogens that enter the lower airways. OBJECTIVES: We studied the effects of two different TLR agonists relevant for respiratory infections in the human lung: lipoteichoic acid (LTA; TLR2 agonist, component of gram-positive bacteria) and lipopolysaccharide (LPS; TLR4-agonist, component of gram-negative bacteria). METHODS: Fifteen healthy subjects were given LPS or LTA: by bronchoscope, sterile saline was instilled into a lung segment followed by instillation of LTA or LPS into the contralateral lung. After 6 hours, a bronchoalveolar lavage was performed and inflammatory parameters were determined. Isolated RNA from purified alveolar macrophages was analyzed by multiplex ligation-dependent probe amplification. In addition, spontaneous cytokine release by alveolar macrophages was measured. MEASUREMENTS AND MAIN RESULTS: Marked differences were detected between LTA- and LPS-induced lung inflammation. Whereas both elicited neutrophil recruitment, only LPS instillation was associated with activation of neutrophils (CD11b surface expression, degranulation product levels) and consistent rises of chemo-/cytokine levels. Moreover, LPS but not LTA activated alveolar macrophages, as reflected by enhanced expression of 10 different mRNAs encoding proinflammatory mediators and increased spontaneous cytokine release upon incubation ex vivo. Remarkably, only LTA induced C5a release. CONCLUSIONS: This is the first study to report the in vivo effects of LTA in men and to compare inflammation induced by LTA and LPS in the human lung. Our data suggest that stimulation of TLR2 or TLR4 results in differential pulmonary inflammation, which may be of relevance for understanding pathogenic mechanisms at play during gram-positive and gram-negative respiratory tract infection.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".