1,308 research outputs found
Rapid model-guided design of organ-scale synthetic vasculature for biomanufacturing
Our ability to produce human-scale bio-manufactured organs is critically
limited by the need for vascularization and perfusion. For tissues of variable
size and shape, including arbitrarily complex geometries, designing and
printing vasculature capable of adequate perfusion has posed a major hurdle.
Here, we introduce a model-driven design pipeline combining accelerated
optimization methods for fast synthetic vascular tree generation and
computational hemodynamics models. We demonstrate rapid generation, simulation,
and 3D printing of synthetic vasculature in complex geometries, from small
tissue constructs to organ scale networks. We introduce key algorithmic
advances that all together accelerate synthetic vascular generation by more
than 230-fold compared to standard methods and enable their use in arbitrarily
complex shapes through localized implicit functions. Furthermore, we provide
techniques for joining vascular trees into watertight networks suitable for
hemodynamic CFD and 3D fabrication. We demonstrate that organ-scale vascular
network models can be generated in silico within minutes and can be used to
perfuse engineered and anatomic models including a bioreactor, annulus,
bi-ventricular heart, and gyrus. We further show that this flexible pipeline
can be applied to two common modes of bioprinting with free-form reversible
embedding of suspended hydrogels and writing into soft matter. Our synthetic
vascular tree generation pipeline enables rapid, scalable vascular model
generation and fluid analysis for bio-manufactured tissues necessary for future
scale up and production.Comment: 58 pages (19 main and 39 supplement pages), 4 main figures, 9
supplement figure
Review of the mathematical foundations of data fusion techniques in surface metrology
The recent proliferation of engineered surfaces, including freeform and structured surfaces, is challenging current metrology techniques. Measurement using multiple sensors has been proposed to achieve enhanced benefits, mainly in terms of spatial frequency bandwidth, which a single sensor cannot provide. When using data from different sensors, a process of data fusion is required and there is much active research in this area. In this paper, current data fusion methods and applications are reviewed, with a focus on the mathematical foundations of the subject. Common research questions in the fusion of surface metrology data are raised and potential fusion algorithms are discussed
3D mesh processing using GAMer 2 to enable reaction-diffusion simulations in realistic cellular geometries
Recent advances in electron microscopy have enabled the imaging of single
cells in 3D at nanometer length scale resolutions. An uncharted frontier for in
silico biology is the ability to simulate cellular processes using these
observed geometries. Enabling such simulations requires watertight meshing of
electron micrograph images into 3D volume meshes, which can then form the basis
of computer simulations of such processes using numerical techniques such as
the Finite Element Method. In this paper, we describe the use of our recently
rewritten mesh processing software, GAMer 2, to bridge the gap between poorly
conditioned meshes generated from segmented micrographs and boundary marked
tetrahedral meshes which are compatible with simulation. We demonstrate the
application of a workflow using GAMer 2 to a series of electron micrographs of
neuronal dendrite morphology explored at three different length scales and show
that the resulting meshes are suitable for finite element simulations. This
work is an important step towards making physical simulations of biological
processes in realistic geometries routine. Innovations in algorithms to
reconstruct and simulate cellular length scale phenomena based on emerging
structural data will enable realistic physical models and advance discovery at
the interface of geometry and cellular processes. We posit that a new frontier
at the intersection of computational technologies and single cell biology is
now open.Comment: 39 pages, 14 figures. High resolution figures and supplemental movies
available upon reques
Topological and geometric inference of data
The overarching problem under consideration is to determine the structure
of the subspace on which a distribution is supported, given
only a finite noisy sample thereof. The special case in
which the subspace is an embedded manifold is given particular
attention owing to its conceptual elegance, and asymptotic bounds are
obtained on the admissible level of noise such that the
manifold can be recovered up to homotopy equivalence.
Attention is turned on how to accomplish this in practice.
Following ideas from topological data analysis, simplicial complexes are used
as discrete analogues of spaces suitable for computation. By utilising
the prior assumption that the data lie on a manifold, topologically
inspired techniques are proposed for refining the simplicial complex
to better approximate this manifold. This is applied to the
problem of nonlinear dimensionality reduction and found to improve accuracy
of reconstructing several synthetic and real-world datasets.
The second chapter focuses on extending this work to the
case where the ambient space is non-Euclidean. The interfaces between
topological data analysis, functional data analysis, and shape analysis
are thoroughly explored. Lipschitz bounds are proved which relate several
metrics on the space of positive semidefinite matrices; they are then
interpreted in the context of topological data analysis. This is
applied to diffusion tensor imaging and phonology.
The final chapter explores the case where the points are
non-uniformly distributed over the embedded subspace. In particular, a method
is proposed to overcome the shortcomings of witness complex construction
when there are large deviations in the density. The theory
of multidimensional persistence is leveraged to provide a succinct setting
in which the structure of the data can be interpreted
as a generalised stratified space.EPSR
- …