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Record W4246478678 · doi:10.26434/chemrxiv.13487247.v1

Programmed Assembly of Bespoke Prototissue Spheroids on a Microfluidic Platform

2020· preprint· en· W4246478678 on OpenAlex
Kaitlyn Ramsay, Jae Levy, Pierangelo Gobbo, Katherine S. Elvira

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemRxiv · 2020
Typepreprint
Languageen
FieldEngineering
TopicModular Robots and Swarm Intelligence
Canadian institutionsUniversity of Victoria
FundersEngineering and Physical Sciences Research CouncilBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaUniversity of VictoriaFondation pour la Recherche sur AlzheimerUniversity of BristolMichael Smith Health Research BC
KeywordsProtocellBespokeMicrofluidicsNanotechnologyComputer scienceBiochemical engineeringEngineeringMaterials scienceChemistryMembrane

Abstract

fetched live from OpenAlex

The precise assembly of protocell building blocks into prototissues that are stable in water, capable of sensing the external environment and which display collective behaviours remains a considerable challenge in prototissue engineering. In this work we explore the use of microfluidic technologies for the programmed assembly of bio-orthogonally reactive protein-polymer protocells into prototissue spheroids of precise size, composition and with unique Janus configurations. We then show that by controlling the number and phenotype of the protocells that compose the prototissue spheroids it is possible to modulate both the amplitude of the thermally induced contractions of the biomaterial and its collective endogenous biochemical reactivity. Overall, our results show that microfluidic technologies enable a new route to the precise and high-throughput fabrication of tissue-like materials with programmable collective properties that can be tuned through a careful assembly of protocell building blocks of different phenotypes. We anticipate that our bespoke prototissues will be a starting point for the development of more sophisticated artificial tissues for use in medicine, soft robotics and environmentally beneficial bioreactor technologies.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.262
Teacher spread0.220 · 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