Harmonization and standardization of nucleus pulposus cell extraction and culture methods
Bibliographic record
Abstract
Background: In vitro studies using nucleus pulposus (NP) cells are commonly used to investigate disc cell biology and pathogenesis, or to aid in the development of new therapies. However, lab-to-lab variability jeopardizes the much-needed progress in the field. Here, an international group of spine scientists collaborated to standardize extraction and expansion techniques for NP cells to reduce variability, improve comparability between labs and improve utilization of funding and resources. Methods: The most commonly applied methods for NP cell extraction, expansion, and re-differentiation were identified using a questionnaire to research groups worldwide. NP cell extraction methods from rat, rabbit, pig, dog, cow, and human NP tissue were experimentally assessed. Expansion and re-differentiation media and techniques were also investigated. Results: Recommended protocols are provided for extraction, expansion, and re-differentiation of NP cells from common species utilized for NP cell culture. Conclusions: This international, multilab and multispecies study identified cell extraction methods for greater cell yield and fewer gene expression changes by applying species-specific pronase usage, 60-100 U/ml collagenase for shorter durations. Recommendations for NP cell expansion, passage number, and many factors driving successful cell culture in different species are also addressed to support harmonization, rigor, and cross-lab comparisons on NP cells worldwide.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.058 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".