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Record W4241566183 · doi:10.3410/f.736800323.793566846

Faculty Opinions recommendation of A unicellular relative of animals generates a layer of polarized cells by actomyosin-dependent cellularization.

2019· dataset· en· W4241566183 on OpenAlexaff
Tony Harris

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2019
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMarie curieChemistryCell biologyBiologyEuropean union

Abstract

fetched live from OpenAlex

In animals, cellularization of a coenocyte is a specialized form of cytokinesis that results in the formation of a polarized epithelium during early embryonic development. It is characterized by coordinated assembly of an actomyosin network, which drives inward membrane invaginations. However, whether coordinated cellularization driven by membrane invagination exists outside animals is not known. To that end, we investigate cellularization in the ichthyosporean Sphaeroforma arctica, a close unicellular relative of animals. We show that the process of cellularization involves coordinated inward plasma membrane invaginations dependent on an actomyosin network and reveal the temporal order of its assembly. This leads to the formation of a polarized layer of cells resembling an epithelium. We show that this stage is associated with tightly regulated transcriptional activation of genes involved in cell adhesion. Hereby we demonstrate the presence of a self-organized, clonally-generated, polarized layer of cells in a unicellular relative of animals.© 2019, Dudin et al. PMID: 31647412 Funding information This work was supported by: Marie Sklodowska-Curie individual fellowship, International Grant ID: MSCA-IF 747086 Marie Sklodowska-Curie individual fellowship, International Grant ID: MSCA-IF 746044 Young Research Talents grant from the Research Council of Norway, International Grant ID: 240284 MEXT KAKENHI, International Grant ID: 26891021 MEXT KAKENHI, International Grant ID: 221S0002 European Research Council Consolidator Grant, International Grant ID: ERC-2012-Co -616960 H2020 Marie Skłodowska-Curie Actions, International Grant ID: Individual fellowship MSCA-IF 747086 H2020 Marie Skłodowska-Curie Actions, International Grant ID: Individual fellowship MSCA-IF 746044 Swiss National Science Foundation, Switzerland Grant ID: P2LAP3_171815 Research Council of Norway, International Grant ID: Young Research Talents grant 240284 Ministry of Education, Culture, Sports, Science and Technology, International Grant ID: MEXT KAKENHI 26891021 Ministry of Education, Culture, Sports, Science and Technology, International Grant ID: MEXT KAKENHI 221S0002 European Research Council, International Grant ID: Consolidator Grant ERC-2012-Co-616960 More Less keyboard_arrow_down

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.635
Threshold uncertainty score0.520

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.6350.397

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 head0.026
GPT teacher head0.310
Teacher spread0.284 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2019
Admission routes1
Has abstractyes

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