Human umbilical cord Wharton's jelly as a source of mesenchymal progenitors capable of expressing a functional osteogenic phenotype in vitro
Bibliographic record
Abstract
One of the most important challenges in the development of cell-based therapies, including those of the emerging field of tissue engineering, is to find a source of useful cells. Solutions are not readily available when addressing the need to reconstitute the connective tissues of the body. Yet it is these tissues, bone, cartilage etc., which are increasingly needed as connective tissue degenerative diseases become a more significant problem with the increasing aged population. Thus, there is an acute need to find a practical and simple source of connective tissue cells for such applications. The work represented here has clearly demonstrated a unique population of cells which can be easily isolated from Wharton's jelly, the tissue surrounding the vessels of the human umbilical cord. Among these cells, which are not from the blood, but from the connective tissue of the cord, are a sub-population which is able to rapidly form human bone matrix in cell culture. The cell isolation procedure is novel, the harvested cells proliferate and differentiate rapidly compared to existing sources of connective tissue progenitors and, the results show that the cells presenting neither class of major histocompatibility complex (MHC) antigens can be enriched for by cryopreservation. Thus, this unique cell population may represent a significant alternative source of cells for allogeneic cell-based therapies and tissue engineering.
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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) | 0.003 | 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".