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Record W4285013313 · doi:10.3389/fcell.2022.940197

Enhancement of Chromatin and Epigenetic Reprogramming in Porcine SCNT Embryos—Progresses and Perspectives

2022· article· en· W4285013313 on OpenAlexafffund
Werner Giehl Glanzner, Mariana Priotto de Macedo, Karina Gutierrez, Vilceu Bordignon

Bibliographic record

VenueFrontiers in Cell and Developmental Biology · 2022
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaMitacsCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsSomatic cell nuclear transferReprogrammingCloning (programming)BiologyEpigeneticsEmbryoChromatinSomatic cellMiniature pigCell biologyGeneticsAndrologyBlastocystEmbryogenesisGeneMedicine

Abstract

fetched live from OpenAlex

Over the last 25 years, cloned animals have been produced by transferring somatic cell nuclei into enucleated oocytes (SCNT) in more than 20 mammalian species. Among domestic animals, pigs are likely the leading species in the number of clones produced by SCNT. The greater interest in pig cloning has two main reasons, its relevance for food production and as its use as a suitable model in biomedical applications. Recognized progress in animal cloning has been attained over time, but the overall efficiency of SCNT in pigs remains very low, based on the rate of healthy, live born piglets following embryo transfer. Accumulating evidence from studies in mice and other species indicate that new strategies for promoting chromatin and epigenetic reprogramming may represent the beginning of a new era for pig cloning.

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 score0.034
Threshold uncertainty score0.374

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 head0.014
GPT teacher head0.249
Teacher spread0.235 · 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

Citations13
Published2022
Admission routes2
Has abstractyes

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