Faculty Opinions recommendation of Transgene persistence and cell turnover in the diarthrodial joint: implications for gene therapy of chronic joint diseases.
Bibliographic record
Abstract
Local gene therapy for chronic joint diseases requires prolonged transgenic expression, but this has not been reliably achieved in animal models. Using normal and immunocompromised animals, we examined the capacity of various cell types in joint tissues to maintain and express exogenous transgenes after direct intra-articular gene delivery. We found that transgenic expression could persist for the lifetime of the animal but required precise immunological compatibility between the vector, transgene product, and host. It was not dependent on vector integration or promoter origin. We identified two phenotypically distinct sub-populations of genetically modified cells within the joint: (i) transient cells, with a half-life of a few weeks, and (ii) stable cells that reside in the joint tissues indefinitely. Contrary to the prevailing assumption, the transient sub-population was composed almost exclusively of synovial fibroblasts, indicating that the synovium is not an appropriate tissue upon which to base a long-term therapy. Instead, fibroblasts in the ligaments, tendons, and capsule emerged as the primary cell types capable of sustained therapeutic transgene expression. This study sheds new light on the cellular dynamics of articular tissues and suggests that cell turnover and immune reactivity are the key determinants in achieving sustained transgenic expression intra-articularly. PMID: 17440444 Funding information This work was supported by: NIAMS NIH HHS, United States Grant ID: AR48566 NIAMS NIH HHS, United States Grant ID: AR050249
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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 | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.356 | 0.173 |
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".