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Record W4388128565 · doi:10.1016/j.celrep.2023.113354

Single-cell transcriptomics identifies a WNT7A-FZD5 signaling axis that maintains fallopian tube stem cells in patient-derived organoids

2023· article· en· W4388128565 on OpenAlexaff
Abdulkhaliq Alsaadi, Mara Artibani, Zhiyuan Hu, Nina Wietek, Matteo Morotti, Laura Santana González, Móiad Alazzam, Jason Jiang, Beena Abdul, Hooman Soleymani majd, Levi L. Blazer, Jarrett Adams, Francesca Silvestri, Sachdev S. Sidhu, Joan S. Brugge, Ahmed A. Ahmed

Bibliographic record

VenueCell Reports · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsUniversity of Waterloo
FundersNIHR Oxford Biomedical Research CentreOvarian Cancer ActionNational Institute for Health and Care Research
KeywordsStem cellWnt signaling pathwayCell biologyOrganoidBiologyTranscriptomeExtracellular matrixCellular differentiationSignal transductionGeneticsGene expressionGene

Abstract

fetched live from OpenAlex

The study of fallopian tube (FT) function in health and disease has been hampered by limited knowledge of FT stem cells and lack of in vitro models of stem cell renewal and differentiation. Using optimized organoid culture conditions to address these limitations, we find that FT stem cell renewal is highly dependent on WNT/β-catenin signaling and engineer endogenous WNT/β-catenin signaling reporter organoids to biomark, isolate, and characterize these cells. Using functional approaches, as well as bulk and single-cell transcriptomics analyses, we show that an endogenous hormonally regulated WNT7A-FZD5 signaling axis is critical for stem cell renewal and that WNT/β-catenin pathway-activated cells form a distinct transcriptomic cluster of FT cells enriched in extracellular matrix (ECM) remodeling and integrin signaling pathways. Overall, we provide a deep characterization of FT stem cells and their molecular requirements for self-renewal, paving the way for mechanistic work investigating the role of stem cells in FT health and disease.

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 categoriesMeta-epidemiology (narrow)
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 score0.010
Threshold uncertainty score1.000

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 head0.011
GPT teacher head0.200
Teacher spread0.188 · 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.

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

Citations19
Published2023
Admission routes1
Has abstractyes

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