Applications of Stem Cells in Cancer Therapy: A Literature Based Studies
Bibliographic record
Abstract
Stem cells, are extraordinary kind of cells having unique ability of self-renewal, lineage differentiation and regeneration of damaged organ or parts of body. Stem cells experience asymmetric cell divisions, bringing forth two cells from each cell, one cell is alike to SCs in stemnessess whereas, other is differentiated into various lineage. These cells have been known for decades for their highest regenerative potential but their clinical applications remain delayed due to several unknown mechanisms of their actions. With the discovery of Cancer Stem Cells, it was described that understanding the stem cell biology is important for a proper way of cancer cure. Stem cells are successfully being transplanted in several clinical trials to treat the retinal disease, visual disorders including retinitis pigmentosa, Stargardt's disease, wound healing, skin regeneration and age related macular degeneration. Their role in cancer progression is the hot debate of research by cell biologists as understanding their role will help to remove the hurdles in cancer therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.000 |
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 teacher head, 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".