Bibliographic record
Abstract
Even though the stem cells have been studied for decades, only during the past few years has there been an overwhelming proliferation of publications covering isolation, cultivation and utilization of the body's master cells. This paper attempts to summarize the recent studies in the field of stem cells. A number of studies have reported the existence of multipotent stem cells in the cord, cord blood, placenta, bone marrow, brain, heart, teeth, skin, liver, hair follicles and many other tissues and organs, giving rise to cell types other than their tissue of origin. Increased therapeutic use of stem cells has resulted in scientific methods of collection, testing, processing and storage of these cells, with minimal cell damage and differentiation. Cell expansion, bioreactors and tissue engineering are employed extensively to improve the cell dose and outcome. Stem cell infusion, transplantation and implantation are accepted curative therapies for many malignant and non-malignant conditions. Stem cell therapies also provide alternative solutions for the repair and regeneration of various tissues and organs. There has been a dramatic improvement in the understanding of immunosuppressive properties of stem cells on various immune cell types. Stem cells are found to secrete angiogenic cytokines that increase neovascularization. They bring the promise of curing a disease state as these cells normally regenerate tissues in a healthy organism. Stem cell transplantation, in isolation or in combination with other procedures, has been found to be effective. Stem cell therapy is also seen as a possible alternative for the treatment of different diseases such as juvenile diabetes, amyotrophic lateral sclerosis, cerebral palsy, stroke, spinal cord injury and Parkinson's disease. Regenerative medicine using human stem cells is one of the new and promising fields for treating various intractable diseases and damaged organs.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".