Absence of tissue inhibitor of metalloproteinases 3 disrupts alveologenesis in the mouse
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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 it