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Record W3007150229 · doi:10.1093/jcag/gwz047.191

A192 DEPLETING ASCL2 IN ESOPHAGEAL ORGANOIDS TO INVESTIGATE ITS ROLE IN STEM CELLS MAINTENANCE

2020· article· en· W3007150229 on OpenAlexaff
M Hamilton, Dominique Jean, Véronique Giroux

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsOrganoidStem cellBiologyCell biologyMatrigelPopulationStem cell markerWnt signaling pathwayCell cultureMedicineSignal transductionGenetics

Abstract

fetched live from OpenAlex

Abstract Background Recently, the first population of stem cells in the esophageal epithelium was identified with the help of the Keratin 15(Krt15) marker. However, little is known about the mechanisms underlying the expansion and the function of stem cells in the esophagus. It was shown that ASCL2, a transcription factor, is upregulated in Krt15+cells compared with Krt15- cells. ASCL2 is a gene target of the Wnt/β-catenin pathway, which act as a regulator of proliferation and maintenance of the stemness state. The ultimate goal of my research project is to determine the role of ASCL2 in the maintenance of esophageal stem cells and to identify his binding partners. Aims To investigate the role of ASCL2 in esophageal epithelial biology, we aim at establishingAscl2knockout esophageal organoid lines. Methods Lentiviral infection and CRISPR/Cas9 knockout approach were optimized in mouse esophageal organoids. ASCL2was invalidated with CRISPR/Cas9 and/or inducible specific shRNAs in primary mouse esophageal cell line and organoids. Antibodies directed against ASCL2 were also tested to validate cell lines. Results First, to optimize lentiviral infection in mouse esophageal organoids, we produced GFP-expressing lentiviruses. Viruses were then concentrated and incubated with a single cell suspension of mouse organoid cells under gentle activation. Infected cells were embedded in Matrigel and grown in organoids. GFP+ cells were then selected using an antibiotic resistance strategy. Second, we used our optimized lentiviral infection protocol to express specific gRNAs in mouse esophageal organoids, which were previously screened in a primary mouse esophageal cell line. Knockout were validated using Western Blot. Invalidation of ASCL2 was performed using CRISPR/Cas9 and inducible shRNAs. We also validated three commercially available ASCL2 antibodies in WB and IF. Conclusions ASCL2 is expressed in the mouse esophagus tissue and organoids, and it can be invalidated in cell lines and organoids. Funding Agencies NSERC, CRC Tier2

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.005
GPT teacher head0.188
Teacher spread0.182 · 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 source (direct Gemma or distilled Codex), 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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