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Record W3110641336 · doi:10.5812/gct.110361

Evaluation of ATG5 Gene Expression in Human Induced Pluripotent Stem Cells During Endoderm Induction

2020· article· en· W3110641336 on OpenAlexaff
Alice Sabet, Negar Azarpira, Saeid Ghavami, Leila Kohan

Bibliographic record

VenueGene Cell and Tissue · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsATG5AutophagyInduced pluripotent stem cellBiologyEndodermCell biologyEmbryonic stem cellEmbryoid bodyCellular differentiationGene expressionStem cellGeneGeneticsApoptosis

Abstract

fetched live from OpenAlex

Background: Autophagy is a vital cell survival mechanism that authorizes cells to assort to metabolic stress and is essential for the development and maintenance of cellular and tissue homeostasis, as well as the prevention of human disease. It has also been shown that autophagy plays a significant role in the development and differentiation of stem cells, as well as induced pluripotent stem cells (iPSCs). Objectives: The present study aimed to examine the mRNA expression of the ATG5 gene, one of the key markers of autophagy in human iPSCs (hiPSCs) during endoderm induction. Methods: In this study, we cultured the human iPSC line (R1-hiPSC1) on mitomycin-C, inactivated mouse embryonic fibroblasts (MEF) layer, and used hanging drop protocol to generate embryoid body (EB) and expose differentiation. The Real-time PCR method was used to examine the mRNA expression level of ATG5 in hiPSC during endoderm induction. Results: Our results demonstrated the high mRNA expression of ATG5 in the mesendoderm induction (MEI) stage, which shows the high rate of autophagy in MEI days rather than the other stages of differentiation. Conclusions: The modification of ATG5 gene expression within hiPSC during endoderm induction shows the importance of autophagy assessments in hiPSC differentiation. Therefore, subsequent studies are needed to clarify the details of autophagy effects on hiPSC differentiation.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.283
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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