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Record W2077462602 · doi:10.1083/jcb.200601018

The epithelial–mesenchymal transition: new insights in signaling, development, and disease

2006· review· en· W2077462602 on OpenAlexafffundabout
Jonathan M. Lee, Shoukat Dedhar, Raghu Kalluri, Erik W. Thompson

Bibliographic record

VenueThe Journal of Cell Biology · 2006
Typereview
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversity of British ColumbiaBC Cancer AgencyUniversity of Ottawa
FundersMedical Research and Materiel CommandNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthNational Cancer InstituteNational Institute on Alcohol Abuse and AlcoholismCanadian Breast Cancer Research Alliance
KeywordsEpithelial–mesenchymal transitionBiologyCancerMesenchymal stem cellCancer researchMetastasisBioinformaticsCell biologyGenetics

Abstract

fetched live from OpenAlex

The conversion of an epithelial cell to a mesenchymal cell is critical to metazoan embryogenesis and a defining structural feature of organ development. Current interest in this process, which is described as an epithelial-mesenchymal transition (EMT), stems from its developmental importance and its involvement in several adult pathologies. Interest and research in EMT are currently at a high level, as seen by the attendance at the recent EMT meeting in Vancouver, Canada (October 1-3, 2005). The meeting, which was hosted by The EMT International Association, was the second international EMT meeting, the first being held in Port Douglas, Queensland, Australia in October 2003. The EMT International Association was formed in 2002 to provide an international body for those interested in EMT and the reverse process, mesenchymal-epithelial transition, and, most importantly, to bring together those working on EMT in development, cancer, fibrosis, and pathology. These themes continued during the recent meeting in Vancouver. Discussion at the Vancouver meeting spanned several areas of research, including signaling pathway activation of EMT and the transcription factors and gene targets involved. Also covered in detail was the basic cell biology of EMT and its role in cancer and fibrosis, as well as the identification of new markers to facilitate the observation of EMT in vivo. This is particularly important because the potential contribution of EMT during neoplasia is the subject of vigorous scientific debate (Tarin, D., E.W. Thompson, and D.F. Newgreen. 2005. Cancer Res. 65:5996-6000; Thompson, E.W., D.F. Newgreen, and D. Tarin. 2005. Cancer Res. 65:5991-5995).

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0010.003
Scholarly communication0.0030.006
Open science0.0010.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.002

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 head0.038
GPT teacher head0.309
Teacher spread0.271 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2,032
Published2006
Admission routes3
Has abstractyes

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