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Record W178935713

Development and Modeling of a Polymer Construct for Perfusion Imaging and Tissue Engineering.

2014· article· en· W178935713 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
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.

Bibliographic record

VenueDeep Blue (University of Michigan) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicAdvanced Computing and Algorithms
Canadian institutionsnot available
FundersNational Institutes of HealthMcGill University
KeywordsConstruct (python library)Biomedical engineeringTissue engineeringComputer scienceEngineeringProgramming language
DOInot available

Abstract

fetched live from OpenAlex

The physical and computational modeling of distributed fluid flow to vascular beds remains a challenging issue. The computational resources required, and the complexity of capillary networks makes modeling infeasible. The resolution limits of manufacturing techniques make physical models difficult to fabricate and manipulate under experimental conditions. As such, an in vitro polymer construct was developed with structural properties of small arteries and the bulk flow characteristics of capillary beds. Rapid prototyping and scaffolding techniques were used to fabricate vascular trees amendable to scaffold compartments. Several scaffold architectures were evaluated to achieve target fluid flow characteristics for implementation in a dynamic contrast-enhanced computed tomography (DCE-CT) imaging phantom and endothelial cell bioreactor, respectively. Experimental flow measurements were compared to measurements from computational simulations. In addition, the flow-induced shear stress across the construct was modeled to identify the optimal settings within the bioreactor. In addition, the cytocompatibility of the polymer construct was optimized. Vascular trees were reliably fabricated to achieve arteriole-like flow. Rapid prototyped polycaprolactone (PCL) scaffolds produced distinct differential flow ranges, marked by a decrease in flow rate across the network. The construct served as a viable dynamic flow phantom capable of generating signals typical of organs imaged with DCE-CT. Furthermore, simulations of the construct as a bioreactor provided guidance on the boundary conditions required for stimulatory shear stress within the scaffolds. Under static conditions, endothelial cells were cultured on PCL scaffolds modified with extra-cellular matrix mimicking biological and chemical agents. All surface modifications exhibited similar cell proliferation and function. However, the Arg-Gly-Asp (RGD) surface-modified constructs exhibited an optimal spatial distribution for future endothelial cell bioreactor investigations. This work demonstrates a method for modeling and physically simulating a bifurcating vascular tree adjoined to scaffold compartments with tunable flow, for application to perfusion imaging and in vitro tissue engineering (tissue and tumors).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score0.228

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.008
GPT teacher head0.213
Teacher spread0.205 · 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