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Record W4306404638 · doi:10.1242/dev.200713

Modeling mammalian spermatogonial differentiation and meiotic initiation<i>in vitro</i>

2022· article· en· W4306404638 on OpenAlexaff
Oleksandr Kirsanov, Taylor A. Johnson, Taylor Malachowski, Bryan A. Niedenberger, Emma A. Gilbert, Debajit Bhowmick, P. Hande Özdi̇nler, Douglas A. Gray, Kelsey H. Fisher‐Wellman, Brian P. Hermann, Christopher B. Geyer

Bibliographic record

VenueDevelopment · 2022
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNational Institutes of HealthEast Carolina UniversityEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentMale Contraceptive Initiative
KeywordsBiologyMeiosisRetinoic acidCell biologyIn vitroCellular differentiationGeneticsGerm cellCell sortingHomologous recombinationGene

Abstract

fetched live from OpenAlex

In mammalian testes, premeiotic spermatogonia respond to retinoic acid by completing an essential lengthy differentiation program before initiating meiosis. The molecular and cellular changes directing these developmental processes remain largely undefined. This wide gap in knowledge is due to two unresolved technical challenges: (1) lack of robust and reliable in vitro models to study differentiation and meiotic initiation; and (2) lack of methods to isolate large and pure populations of male germ cells at each stage of differentiation and at meiotic initiation. Here, we report a facile in vitro differentiation and meiotic initiation system that can be readily manipulated, including the use of chemical agents that cannot be safely administered to live animals. In addition, we present a transgenic mouse model enabling fluorescence-activated cell sorting-based isolation of millions of spermatogonia at specific developmental stages as well as meiotic spermatocytes.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score0.294

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 head0.018
GPT teacher head0.228
Teacher spread0.209 · 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 designObservational
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

Citations9
Published2022
Admission routes1
Has abstractyes

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