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Record W2803326208 · doi:10.1007/s10456-018-9613-x

Consensus guidelines for the use and interpretation of angiogenesis assays

2018· review· en· W2803326208 on OpenAlexaff
Patrycja Nowak‐Sliwinska, Kari Alitalo, Elizabeth Allen, Andrey Anisimov, Alfred C. Aplin, Robert Auerbach, Hellmut G. Augustin, David O. Bates, Judy R. van Beijnum, R. Hugh F. Bender, Gabriele Bergers, Andréas Bikfalvi, Joyce Bischoff, Barbara C. Böck, Peter C. Brooks, Federico Bussolino, Bertan Cakir, Peter Carmeliet, Daniel Castranova, Anca Maria Cîmpean, Ondine Cleaver, George Coukos, George E. Davis, Michele De Palma, Anna Dimberg, Ruud P.M. Dings, Valentin Djonov, Andrew C. Dudley, Neil Dufton, Sarah‐Maria Fendt, Napoleone Ferrara, Marcus Fruttiger, Dai Fukumura, Bart Ghesquière, Yan Gong, Robert J. Griffin, Adrian L. Harris, Christopher C.W. Hughes, Nan W. Hultgren, M. Luisa Iruela‐Arispe, Melita Irving, Raghu Kalluri, Joanna Kalucka, Robert S. Kerbel, Jan Kitajewski, Ingeborg Klaassen, Hynda K. Kleinmann, Pieter Koolwijk, Elisabeth Kuczynski, Brenda R. Kwak, Koen M. Marien, Juan M. Melero‐Martin, Lance L. Munn, Roberto F. Nicosia, Agnès Noël, Jussi Nurro, Anna-Karin Olsson, Tatiana V. Petrova, Kristian Pietras, Роберто Пили, Jeffrey W. Pollard, Mark J. Post, Paul H.A. Quax, Gabriel A. Rabinovich, Marius Raica, Anna M. Randi, Doménico Ribatti, Curzio Rüegg, Reinier O. Schlingemann, Stefan Schulte‐Merker, Lois E. H. Smith, Jonathan W. Song, Steven A. Stacker, Jimmy Stalin, Amber N. Stratman, Maureen Van de Velde, Victor W.M. van Hinsbergh, Peter Vermeulen, Johannes Waltenberger, Brant M. Weinstein, Hong Xin, Bahar Yetkin-Arik, Seppo Ylä‐Herttuala, Mervin C. Yöder, Arjan W. Griffioen

Bibliographic record

VenueAngiogenesis · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersNational Eye InstituteNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Allergy and Infectious DiseasesMedical Research CouncilVlaamse regeringAXA Research FundInstitut National de la Santé et de la Recherche MédicaleFonds Wetenschappelijk OnderzoekEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentRosetrees TrustNational Institutes of HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Heart, Lung, and Blood InstituteAustralian GovernmentAssociation pour la Recherche sur le CancerNational Science FoundationCancer Research UKNational Cancer InstituteBritish Heart FoundationFondation contre le CancerWellcome Trust
KeywordsAngiogenesisBioassayEx vivoComputational biologyIn vivoProcess (computing)BiologyComputer scienceBioinformaticsCancer researchBiotechnologyGenetics

Abstract

fetched live from OpenAlex

The formation of new blood vessels, or angiogenesis, is a complex process that plays important roles in growth and development, tissue and organ regeneration, as well as numerous pathological conditions. Angiogenesis undergoes multiple discrete steps that can be individually evaluated and quantified by a large number of bioassays. These independent assessments hold advantages but also have limitations. This article describes in vivo, ex vivo, and in vitro bioassays that are available for the evaluation of angiogenesis and highlights critical aspects that are relevant for their execution and proper interpretation. As such, this collaborative work is the first edition of consensus guidelines on angiogenesis bioassays to serve for current and future reference.

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)0.020
metaresearch head score (Gemma)0.030
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: Methods · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.030
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0070.004
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0070.003
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0100.011

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 head0.171
GPT teacher head0.388
Teacher spread0.217 · 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
GenreMethods

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

Citations597
Published2018
Admission routes1
Has abstractyes

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