Bibliographic record
Abstract
Mesenchymal stem cells (MSCs) have gained remarkable interest in the field of regenerative medicine because of their innate high proliferation ability, paracrine effects, multipotent differentiation potential, and immunomodulatory properties. Autologous bone marrow aspirate has been the gold standard source for MSCs. However, the number of MSCs in BMA has been shown to decline with age, warranting cell expansion to achieve therapeutic efficiency. Additionally, the efficacy of MSCs is dependent on several factors such as source of MSCs, viability of MSCs after implantation, potency of MSCs, and severity of the disease condition.1 One of the major limitations of cell therapy is the loss of cell viability that may occur shortly after implantation. This shortcoming can potentially be resolved by (A) in vitro priming of MSCs to make them potent enough that paracrine effects trigger the tissue regenerative cascade, and (B) optimization of the delivery mechanism of MSCs to enhance cell viability. In vitro priming of MSCs may be accomplished by predisposing them to survive in hypoxic and ischemic conditions commonly seen with bone defects. Growth factors and cytokines have been shown to direct MSC fate. However, increased costs due to use of recombinant proteins, failure to capture the complex microenvironment of the native extracellular matrices (ECM), and inadequate knowledge of required dosage are some of the shortcomings of this approach. Cell-secreted ECMs have been shown to possess the underlying structure and trophic factors needed to facilitate MSC attachment and differentiation.2 ECM-coated microcarrier beads incorporated within alginate hydrogels have been used to promote osteogenesis with MSCs.3 Additionally, it has been shown that the survival and osteogenic potential of MSCs can be improved by the formation of three-dimensional spheroids compared with monolayer culturing of MSCs.4 MSCs cultured by this method were shown to have significantly higher vascular endothelial growth factor secretion and to better resist apoptosis posttransplantation compared with dissociated MSCs. MSCs have a promising role in cell therapy for the treatment of various disorders. However, many challenges remain in making this cell population safe and effective. It is important to select optimal cell sources, culture conditions, scaffolding materials, and delivery methods to overcome the challenges associated with MSCs.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".