Evaluation of Autophagy Process in Differentiation of Human Induced Pluripotent Stem Cells toward Insulin Producing Cells.
Bibliographic record
Abstract
Background: Autophagy is an intracellular self-degradative homeostasis process which eliminates undesirable and harmful macromolecules and organelles. Autophagy is also involved in self-renewal and differentiation of induced pluripotent stem cell (iPSCs). Objective: In this study, we investigated the expression profile of autophagy marker genes in human iPSCs during their differentiation induction toward insulin producing β-like cells. Methods: Human iPSC line, R1-hiPSC1, was used for differentiation induction toward β-like cells. The mRNA expression of Nanog, OCT4 (pluripotency markers), SOX17, FOXA2 (endodermic markers), PTF1A, NKX6.1 (exocrine/endocrine determinants), and PDX1 were measured during differentiation stages. Autophagy was monitored by genes expression study of four autophagy markers, MAP1LC3B, BECN1, SQSTM1/P62 and ATG5, along with protein expression profile of LC3b-II during differentiation stages. Results: The mRNA expression measurement of pluripotency, endoderm and exocrine/endocrine marker genes confirmed that hiPSCs skipped pluripotency, differentiated into endoderm, passed through the pancreatic lineage commitment stage and successfully generated insulin producing β-like cells. Expression profile of autophagy genes during differentiation stages indicated the decreased expression levels at the early stages (EB and MEI) and then increased at the definitive endoderm stages (DEI 1, DEI 2 and DE) followed by a subtractive pattern toward the end of differentiation. The results of protein expression of LC3b-II were consistent with gene expression data. Conclusion: This study demonstrated the high contribution of key autophagy genes/proteins during the differentiation of hiPSC toward β-like cells. The enhanced autophagy levels were a prominent feature of early stages of differentiation and DE rather than the later stages.
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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 | 0.000 | 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 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".