Characterization of nucleus pulposus‐like tissue formed in vitro
Bibliographic record
Abstract
In order to be able to study the metabolism of nucleus pulposus (NP) tissue, we developed a cell culture system that resulted in the formation of NP-like tissue in vitro. NP cells were isolated from sheep lumbar spines and grown on filter inserts (Millicell CM). Histological examination showed that the cells accumulated extracellular matrix and formed a continuous layer of NP-like tissue. The accumulation of sulfated proteoglycans in the NP-like tissue continued up to 10 weeks and this was paralleled by an increase in tissue thickness and dry weight. DNA content remained stable during the first 4 weeks but then decreased over time. The amount of DNA, glycosaminoglycan (GAG) and collagen per mg dry weight of the tissue generated after 10 weeks in culture were 1.25+/-0.02, 301.6+/-27.7 and 411+/-65 microg, respectively, compared with 1.04+/-0.08, 320.6+/-21.2 and 399+/-4.4 microg (mean +/- SEM) for the in vivo tissue. There was no significant difference between in vitro and in vivo tissue. The cells in culture synthesized large proteoglycans (kav = 0.26+/-0.03, mean +/- S.D.) which were similar in size to those synthesized by cells in NP tissue in ex vivo culture (kav = 0.22+/-0.02, mean +/- S.D.) as determined by Sepharose CL-2B column chromatography. The in vitro generated tissue contained type II collagen as demonstrated by sodium dodecyl sulfate-polyacrylamide gel (SDS-PAGE) and silver staining as well as Western blot analysis. NP cells grown on filters generate tissue similar in composition to the in vivo tissue, for the characteristics examined to date, and should be a suitable model to use to study NP metabolism and extracellular matrix turnover.
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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".