Surfactant Protein D is cleaved by matrix metalloprotease-9, resulting in disruption of collectin function (133.16)
Bibliographic record
Abstract
Abstract Surfactant protein D (SP-D) is a pulmonary collectin, containing collagen and lectin domains, important in innate host defense in the lung. It agglutinates and opsonizes bacteria and leads to phagocytosis by macrophages. Matrix metalloproteinase-9 (MMP-9) is a gelatinase upregulated in many inflammatory diseases of the lung. We tested SP-D as a substrate for MMP-9, and assessed SP-D function in this context. We show cleavage at three discrete sites of the collagen domain, generating C-terminal fragments of 34, 27, and 19KDa identified by western blot and with specific cleavage sites verified by mass spectrometry. SP-D is not, however, hydrolyzed by the related protease MMP-8, nor the serine protease prolyl endopeptidase, both of which cleave collagen. Incubation with these three proteases separately or in combination did not generate any detectable quantity of the neutrophil chemoattractant proline-glycine-proline (PGP), though SP-D contains many PGP motifs in the collagen domain. Furthermore, with MMP-9 cleavage, SP-D’s intrinsic neutrophil chemoattractant activity was eliminated and its ability to aggregate Pseudomonas aeruginosa was also decreased. These studies indicate that in inflammatory lung diseases where MMP-9 is upregulated, impairment of SP-D’s innate immunologic properties may increase frequency and severity of pulmonary infection, emphasizing the role of MMP-9 in disease.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".