3D-cultured dermal fibroblasts self-produce a brain-like matrisome that promotes neurogenesis in silico and supports neuronal survival in vitro
Bibliographic record
Abstract
Studying neurological disorders in vitro is still challenging due to the human brain’s complexity and the difficulty of obtaining primary neural cells. However, tissue engineering and tridimensional (3D) cell culture have become increasingly important tools for disease modeling. By providing an extracellular matrix (ECM) substrate that closely resembles physiological conditions, 3D cell culture offers several advantages over standard monolayer cell culture, including enhanced cell-cell and cell-matrix interactions. This results in a microenvironment that more accurately reflects in vivo biology. In this study, we performed an in-depth analysis of the proteome and matrisome of 3D tissue-engineered dermis, made from human primary dermal fibroblasts cultivated in 3D and embedded in a self-produced ECM. Interestingly, in silico analysis revealed that neurogenesis and associated functions were predicted to be strongly activated in this tissue-engineered 3D model. Indeed, we showed that ECM proteins involved in neuronal development and maintenance, typically produced by cerebral cells, were also expressed by dermal fibroblasts. Of particular interest, the 3D co-cultivation of dermal fibroblasts with iPSC-derived motor neurons readily enabled long-lasting culture periods without costly media supplementation with exogenous additives. Patient-derived dermal fibroblasts, cultivated in 3D, could therefore become valuable models for the study of neurological diseases. This approach offers a cost-effective and a less invasive alternative to brain biopsies for modeling complex neurological disorders in vitro.
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How this classification was reachedexpand
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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".