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Disease modelling in human organoids

2019· review· en· 383 citations· W2964772567 on OpenAlex· 10.1242/dmm.039347

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.149
GPT teacher head0.362
Teacher spread
0.213 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

disease modelling, in particular the development of organoids. These self-organizing tissues derived from stem cells provide a unique system to examine mechanisms ranging from organ development to homeostasis and disease. Because organoids develop according to intrinsic developmental programmes, the resultant tissue morphology recapitulates organ architecture with remarkable fidelity. Furthermore, the fact that these tissues can be derived from human progenitors allows for the study of uniquely human processes and disorders. This article and accompanying poster highlight the currently available methods, particularly those aimed at modelling human biology, and provide an overview of their capabilities and limitations. We also speculate on possible future technological advances that have the potential for great strides in both disease modelling and future regenerative strategies.

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.

The record

Venue
Disease Models & Mechanisms
Topic
Cancer Cells and Metastasis
Field
Medicine
Canadian institutions
Funders
H2020 European Research CouncilHorizon 2020 Framework ProgrammeNational Centre for the Replacement, Refinement and Reduction of Animals in ResearchNational Centre for the Replacement Refinement and Reduction of Animals in ResearchMedical Research CouncilRoyal SocietyMedical Research Council CanadaWellcome Trust
Keywords
OrganoidBiologyHuman diseaseRegenerative medicineComputational biologyProgenitor cellDiseaseStem cellNeuroscienceCell biologyMedicinePathology
Has abstract in OpenAlex
yes