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Record W3092117119 · doi:10.1089/ten.teb.2020.0182

Designing Biomaterials to Modulate Notch Signaling in Tissue Engineering and Regenerative Medicine

2020· review· en· W3092117119 on OpenAlex

Why this work is in the frame

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

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTissue Engineering Part B Reviews · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsWestern University
Fundersnot available
KeywordsNotch signaling pathwayRegenerative medicineTissue engineeringBiomaterialHes3 signaling axisCell biologyCell signalingSignal transductionStem cellBiologyNanotechnologyBiomedical engineeringMedicineMaterials science

Abstract

fetched live from OpenAlex

The design of cell-instructive biomaterials for tissue engineering and regenerative medicine is at a crossroads. Although the conventional tissue engineering approach is top-down (cells seeded to macroporous scaffolds and mature to form tissues), bottom-up tissue engineering strategies are becoming appealing. With such developments, we can study cell signaling events, thus enabling functional tissue assembly in physiologic and diseased models. Among many important signaling pathways, the Notch signaling pathway is the most diverse in its influence during tissue morphogenesis and repair following injury. Although Notch signaling is extensively studied in developmental biology and cancer biology, our knowledge of designing biomaterial-based Notch signaling platforms and incorporating Notch signaling components into engineered tissue systems is limited. By incorporating Notch signaling to tissue engineering scaffolds, we can direct cell-specific responses and improve engineered tissue maturation. This review will discuss recent progress in the development of Notch signaling biomaterials as a promising target to control cellular fate decisions, including the influences of ligand identity, biophysical material cues, ligand presentation strategies, and mechanotransduction. Notch signaling is consequently of interest to direct, control, and reprogram cellular behavior on a biomaterial surface. We anticipate that discussions in this article will allow for enhanced knowledge and insight into designing Notch targeted biomaterials for various tissue engineering and cell fate determinations. Impact statement Notch signaling is recognized as an important pathway in tissue engineering and regenerative medicine; however, there is no systematic review on this topic. The comprehensive review and perspectives presented here provide an in-depth discussion on ligand presentation strategies both in 2D and in 3D cell culture environments involving biomaterials/scaffolds. In addition, this review article provides insight into the challenges in designing cell surrogate biomaterials capable of providing Notch signals. To the best of the authors' knowledge, this is the first review relevant to the fields of tissue engineering.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.925
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.315
Teacher spread0.277 · 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