TIMP3 Regulates Mammary Epithelial Apoptosis with Immune Cell Recruitment Through Differential TNF Dependence
Bibliographic record
Abstract
Post-lactation mammary involution is a homeostatic process requiring epithelial apoptosis and clearance. Given that the deficiency of the extracellular metalloproteinase inhibitor TIMP3 impacts epithelial apoptosis and heightens inflammatory response, we investigated whether TIMP3 regulates these distinct processes during the phases of mammary gland involution in the mouse. Here we show that TIMP3 deficiency leads to TNF dysregulation, earlier caspase activation and onset of mitochondrial apoptosis. This accelerated first phase of involution includes faster loss of initiating signals (STAT3 activation; TGFβ3) concurrent with immediate luminal deconstruction through E-cadherin fragmentation. Epithelial apoptosis is followed by accelerated adipogenesis and a greater macrophage and T-cell infiltration in Timp3(-/-) involuting glands. Crossing in Tnf deficiency abrogates caspase 3 activation, but heightens macrophage and T-cell influx into Timp3(-/-) glands. The data indicate that TIMP3 differentially impacts apoptosis and inflammatory cell influx, based on involvement of TNF, during the process of mammary involution. An understanding of the molecular factors and wound healing microenvironment of the postpartum mammary gland may have implications for understanding pregnancy-associated breast cancer risk.
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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) | 0.001 | 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".