Overgrowth with increased proliferation of fibroblast and matrix metalloproteinase activity related to reduced TIMP1: A newly recognized syndrome?
Bibliographic record
Abstract
We report on a child with prenatal onset of overgrowth associated with thick, excessive wrinkled skin and other abnormalities including cleft palate, Chiari malformation and polymicrogyria. His clinical features do not resemble any of the known reported overgrowth syndromes. Genetic evaluations, including karyotype, oligoarray, methylation-sensitive multiplex ligation-dependent probe amplification (MLPA) for 11p11.2 region, CDKN1C sequencing, GPC3 sequencing and dosage analysis, and HRAS sequencing, have been un-revealing. Immunohistochemistry done on the patient's cultured skin fibroblasts showed normally assembled elastic fibers and normal pattern of chondroitin sulfate deposition with defective deposition of Collagen I fibers. In addition, there were high levels of immuno-detectable metalloproteinase 3 (MMP3) and undetectable tissue inhibitor of metalloproteinase 1 (TIMP1). The defective collagen deposition in the fibroblast culture could be reversed by the broad spectrum MMP inhibitor, doxycycline. We also present evidence that the fibroblasts of this patient have an increased rate of cellular proliferation. We propose that this is a previously unrecognized overgrowth syndrome associated with increased cellular proliferation and defective collagen I deposition due to an imbalance between MMP and TIMP in fibroblasts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".