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Record W3016896071 · doi:10.1155/2020/6051210

Human Organ‐Specific 3D Cancer Models Produced by the Stromal Self‐Assembly Method of Tissue Engineering for the Study of Solid Tumors

2020· review· en· W3016896071 on OpenAlexafffund
Vincent Roy, Brice Magne, Maude Vaillancourt-Audet, Stéphane Chabaud, Emil Grammond, Léo Piquet, Julie Fradette, Isabelle Laverdière, Véronique Moulin, Solange Landreville, Lucie Germain, François A. Auger, François Gros‐Louis, Stéphane Bolduc

Bibliographic record

VenueBioMed Research International · 2020
Typereview
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversité LavalCentre hospitalier de l'Université LavalCentre hospitalier universitaire de Québec
FundersFonds de Recherche du Québec - SantéCanada Research ChairsFondation CHU de QuébecCanadian Urological Oncology Group
KeywordsStromal cellTissue engineeringSolid organCancerMedicinePathologyCancer researchBiologyBiomedical engineeringSurgeryInternal medicineOrgan transplantationTransplantation

Abstract

fetched live from OpenAlex

Cancer research has considerably progressed with the improvement of in vitro study models, helping to understand the key role of the tumor microenvironment in cancer development and progression. Over the last few years, complex 3D human cell culture systems have gained much popularity over in vivo models, as they accurately mimic the tumor microenvironment and allow high‐throughput drug screening. Of particular interest, in vitro human 3D tissue constructs, produced by the self‐assembly method of tissue engineering, have been successfully used to model the tumor microenvironment and now represent a very promising approach to further develop diverse cancer models. In this review, we describe the importance of the tumor microenvironment and present the existing in vitro cancer models generated through the self‐assembly method of tissue engineering. Lastly, we highlight the relevance of this approach to mimic various and complex tumors, including basal cell carcinoma, cutaneous neurofibroma, skin melanoma, bladder cancer, and uveal melanoma.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.173
GPT teacher head0.482
Teacher spread0.310 · 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

Citations61
Published2020
Admission routes2
Has abstractyes

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Same venueBioMed Research InternationalSame topic3D Printing in Biomedical ResearchFrench-language works237,207