Transforming Growth Factor β Enhances Tissue Formation by Passaged Nucleus Pulposus Cells In Vitro
Bibliographic record
Abstract
The nucleus pulposus (NP) is composed of NP and notochord cell. It is a paucicellular tissue and if it is to be used as a source of cells for tissue engineering the cell number will have to be expanded by cell passaging. The hypothesis of this study is that passaged NP and notochordal cells grown in three-dimensional (3D) culture in the presence of transforming growth factor β (TGFβ) will show enhanced NP tissue formation compared with cells grown in the absence of this growth factor. Bovine NP cells isolated by sequential enzymatic digestion from caudal intervertebral discs were either placed directly in 3D culture (P0) or serially passaged up to passage 3 (P3) prior to placement in 3D culture. Serial cell passage in monolayer culture led to de-differentiation, increased senescence and oxidative stress and decreases in the gene expression of NP and notochordal associated markers and increases in de-differentiation markers. The NP tissue regeneration capacity of cells in 3D culture decreases with passaging as indicated by diminished tissue thickness and total collagen content when compared with tissues formed by P0 cells. Immunohistochemical studies showed that type II collagen accumulation appeared to decrease. TGFβ1 or TGFβ3 treatment enhanced the ability of cells at each passage to form tissue, in part by decreasing cell death. However, neither TGFβ1 nor TGFβ3 were able to restore the notochordal phenotype. Although TGFβ1/3 recovered NP tissue formation by passaged cells, to generate NP in vitro that resembles the native tissue will require identification of conditions facilitating retention of notochordal cell differentiation. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 38:438-449, 2020.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".