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Record W2068003168 · doi:10.1002/dvdy.21722

Leading edge‐secreted Dpp cooperates with ACK‐dependent signaling from the amnioserosa to regulate myosin levels during dorsal closure

2008· article· en· W2068003168 on OpenAlexafffund
Baharak Zahedi, Weiping Shen, Xing Xu, Xi Chen, Meena Mahey, Nicholas Harden

Bibliographic record

VenueDevelopmental Dynamics · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsSimon Fraser University
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsBiologyZipperCell biologyMorphogenesisMyosinEmbryoTranscription factorRNA interferenceMyosin light-chain kinaseEpidermis (zoology)Signal transductionGeneGeneticsAnatomyRNA

Abstract

fetched live from OpenAlex

Dorsal closure of the Drosophila embryo is an epithelial fusion in which the epidermal flanks migrate to close a hole in the epidermis occupied by the amnioserosa, a process driven in part by myosin-dependent cell shape change. Dpp signaling is required for the morphogenesis of both tissues, where it promotes transcription of myosin from the zipper (zip) gene. Drosophila has two members of the activated Cdc42-associated kinase (ACK) family: DACK and PR2. Overexpression of DACK in embryos deficient in Dpp signaling can restore zip expression and suppress dorsal closure defects, while reducing the levels of DACK and PR2 simultaneously using mutations or amnioserosa-specific knock down by RNAi results in loss of zip expression. ACK function in the amnioserosa may generate a signal cooperating with Dpp secreted from the epidermis in driving zip expression in these two tissues, ensuring that cell shape changes in dorsal closure occur in a coordinated manner.

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 score0.001
Threshold uncertainty score0.003

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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

Citations23
Published2008
Admission routes2
Has abstractyes

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