Absence of tissue inhibitor of metalloproteinases 3 disrupts alveologenesis in the mouse
Bibliographic record
Abstract
Tissue inhibitors of metalloproteinases (TIMPs) regulate extracellular matrix (ECM) degradation by matrix metalloproteinases (MMPs) throughout lung development. We examined lungs from TIMP3 null mice and found significant air space enlargement compared with wild type (WT) animals during a time course spanning early alveologenesis (post-partum days 1, 5, 9 and 14). Trichrome staining revealed a similar pattern of collagen distribution in the walls of nascent alveoli; however, the alveolar walls of TIMP3 mutant mice appeared to be thinner than controls. Assessment of MMP2 and MMP9 activities by gelatin zymography demonstrated a significant elevation in the active form of MMP2 at post-partum days 1 and 5. Treatment of null pregnant dams with a broad spectrum synthetic metalloproteinase inhibitor, GM6001, on embryonic day 16.5 enhanced the formation of primitive alveoli during the saccular stage of lung development as evidenced by a partial, but significant, rescue of alveolar size in post-partum day 1 animals. We propose that increased MMP activity in the absence of TIMP3 enhances ECM proteolysis, upsetting proper formation of primitive alveolar septa during the saccular stage of alveologenesis. Therefore, TIMP3 indirectly regulates alveolar formation in the mouse. To our knowledge, ours is the first study to demonstrate that in utero manipulation of the TIMP/MMP proteolytic axis, to specifically inhibit proteolysis, significantly affects lung development.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".