Natural extracellular matrix scaffolds recycled from human salivary digests: a morphometric study
Bibliographic record
Abstract
OBJECTIVE: A challenge in engineering tissues is to supply parenchymal cells with suitable scaffolds which ideally reproduce the extracellular matrix (ECM). This study tested the hypothesis of preserving the 'residual connective tissue' remaining after mechanical and enzymatic release of cells from human submandibular gland biopsies (that we named 'natural ExtraCellular Matrix scaffolds', nECMsc) to be used as recycled natural scaffolds. The objective was to test whether nECMsc and native salivary tissue were comparable morphologically, in ECM proteins composition, and in cell seeding efficiency. METHODS: Following cell isolation procedures, nECMsc were kept, either fresh or frozen (sectioned into 12-μm-thick slices), and examined with high-resolution electron microscopy (HRSEM) for its three-dimensional structure, and with picrosirius red staining and immunogold staining for ECM protein composition and distribution, respectively. nECMsc were seeded with human epithelial cells and fibroblasts to assess cell attachment and proliferation in short-term experiments. RESULTS: Under HRSEM, nECMsc had comparable fiber arrangement to original glands. Histochemical and immunogold-labeling examinations revealed the presence of collagen types I, III, and IV. Seeded epithelial cells and fibroblasts attached, proliferated (14-55%), and were alive (86-99%) after 4-8 days of culture. CONCLUSIONS: nECMsc retained native ECM proteins and maintained their distribution. Seeded cells remained viable on nECMsc.
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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 | 0.000 |
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".