Enhanced efficiency in isolation and expansion of hAMSCs via dual enzyme digestion and micro-carrier
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract A two-stage method of obtaining viable human amniotic stem cells (hAMSCs) in large-scale is described. First, human amniotic stem cells are isolated via dual enzyme (collagenase II and DNAase I) digestion. Next, relying on a culture of the cells from porous chitosan-based microspheres in vitro, high purity hAMSCs are obtained in large-scale. Dual enzymatic (collagenase II and DNase I) digestion provides a primary cell culture and first subculture with a lower contamination rate, higher purity and a larger number of isolated cells. The obtained hAMSCs were seeded onto chitosan microspheres (CM), gelatin–chitosan microspheres (GCM) and collagen–chitosan microspheres (CCM) to produce large numbers of hAMSCs for clinical trials. Growth activity measurement and differentiation essays of hAMSCs were realized. Within 2 weeks of culturing, GCMs achieved over 1.28 ± 0.06 × 10 7 hAMSCs whereas CCMs and CMs achieved 7.86 ± 0.11 × 10 6 and 1.98 ± 0.86 × 10 6 respectively within this time. In conclusion, hAMSCs showed excellent attachment and viability on GCM-chitosan microspheres, matching the hAMSCs’ normal culture medium. Therefore, dual enzyme (collagenase II and DNAase I) digestion may be a more useful isolation process and culture of hAMSCs on porous GCM in vitro as an ideal environment for the large-scale expansion of highly functional hAMSCs for eventual use in stem cell-based 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.
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 it