Transplantation of Umbilical Cord Blood–Derived Cells for Novel Indications in Regenerative Therapy or Immune Modulation: A Scoping Review of Clinical Studies
Bibliographic record
Abstract
Although used mainly for transplantation of hematopoietic stem cells in the treatment of blood disorders, umbilical cord blood (UCB)-based therapies are now being used increasingly for novel applications in nonhematopoietic diseases and as a form of cellular regenerative therapy or immune modulation. We performed a systematic scoping review by searching Medline, EMBASE, and the Cochrane Library for published articles, and we searched www.clinicaltrials.com and the World Health Organization International Clinical Trials Registry Platform to describe the breadth of published studies and ongoing clinical activity in umbilical cord-based cellular therapy for regenerative therapy and immune modulation. The most commonly published area of expertise in the use of UCB-derived cellular transplantation for novel indications is for neurological disorders and this remains the most active area of study in ongoing registered trials. An increasingly broad range of disorders, however, are reflected in ongoing registered trials, which suggests greater activity, interest, and investment in UCB-derived cellular therapy. Interestingly, adult patients compose the majority of patients reported in published reports and registered ongoing clinical studies continue to enroll predominantly adult subjects. Geographically, Asian countries appear most active in UCB-derived cellular therapy and our analysis of ongoing studies suggests this trend will likely continue. Regular assessment of published and ongoing activity in UCB transplantation for emerging novel indications will be critical for informing UCB banking establishments and funding agencies to guide changes in banking practices related to emerging trends in cell therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".