MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase (www.facebase.org, https://doi.org/10.25550/3-HXMC) and GitHub (https://github.com/jaydevine/MusMorph)

MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses.

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase ( www.facebase.org , https://doi.org/10.25550/3-HXMC ) and GitHub ( https://github.com/jaydevine/MusMorph )

An Efficient Snell's-Law Method for Optimal-Path Planning Across Multiple Two-dimensional Irregular Homogeneous-Cost Regions

International Journal of Robotics Research, 9, no. 6 (December 1990), 48-66. The equations were redrawn in 2008.We are exploring a new approach to high-level optimal-path planning when homogeneous irregularlyshaped regions of a plane have different traversal costs per unit distance. It is based on the simple idea that optimal paths must be straight in homogeneous regions, and so those regions need not be subdivided for path planning. Our approach uses optics analogies, ray tracing, and Snell's Law, and reduces the problem to an efficient graph search with a variety of pruning criteria...Supported in part by the U. S. Army Combat Developments Experimentation Center under MIPR ATEC 88-86.Approved for public release; distribution is unlimited

Exploiting capability constraints to solve global, two dimensional path planning problems

Mobile autonomous vehicles require the capability of planning routes over ranges that are too great to be characterized by local sensor systems. Completion of this task requires some form of map data. Much work has been done concerning planning paths through local areas, those which can be scanned by on-board sensor systems. However, planning paths based on long range map data is a very different problem. Extant solution techniques require the search of discrete, node and link representations which characterize continuous, two dimensional problem environments. The authors assume the availability of topographic data organized into regions of homogenous traversal cost. Given this, they present a solution technique for the long range planning problem which relies on a Snell's Law heuristic to limit a graph search for the optimal solutionSupported in part by the Foundation Research Program of the Naval Postgraduate School with funds provided by the Chief of Naval Researchhttp://archive.org/details/exploitingcapabi00richN0001485WR41005NAApproved for public release; distribution is unlimited

Fundamental, model-driven investigations of structure and physical properties of poly(vinyl alcohol) hydrogels and multi-arm poly(ethylene glycol) hydrogels : decoupling stiffness and solute transport

Synthetic hydrogels are advanced biomaterials frequently used in cutting-edge biomedical engineering research and clinical interventions. Their value is highly associated with their tunability and ability to mimic the extracellular matrix properties of a variety of tissues such as bone marrow and brain tissue, but many of the fundamental properties of hydrogels are overly generalized and under-investigated. Recent studies have shown that cells respond to both the stiffness and solute transport profile of their environment, but standard hydrogel synthesis methods cause those two properties to be highly correlated. New insight into structural control of hydrogel properties is needed to independently tune stiffness and solute transport in hydrogels. This dissertation combines fundamental modeling, the full capabilities of multi-arm poly(ethylene glycol) (PEG) hydrogel design, and high-throughput, standardized methods for measuring hydrogel swelling, stiffness, and solute transport to decouple stiffness and solute diffusivity in hydrogels without changing their chemical properties. First, we coordinated equilibrium swelling theory, rubberlike elasticity theory, and mesh transport theory into the fundamental predictive swollen polymer network model. From the model and prior studies relating hydrogel structure and function, we identified four structural parameters that could be independently controlled at synthesis. The swollen polymer network model predicted that simultaneously manipulating these four structural parameters would decouple stiffness and solute diffusivity. Poly(vinyl alcohol) (PVA) hydrogels were used to establish model-compatible, high-throughput measurement methods for swelling, stiffness, and solute transport. The eighteen PVA hydrogel formulations with variation in two of the four structural parameters also served as a control group for the multi-arm PEG hydrogels. The extensive validation studies with PVA hydrogels identified limitations of the swollen polymer network model not addressed by the following multi-arm PEG hydrogel studies, such as how solute diffusivity scales differently with solute size for different solute chemical profiles. Stiffness and solute transport were decoupled by the four structural parameters in multi-arm PEG hydrogels. However, the structure-property relationship that facilitated the decoupling was not predicted by the swollen polymer network model, highlighting an opportunity for further model development. The fundamental model-based hydrogel design approach described here provides a foundation for robust hydrogel design for biomedical applications.Biomedical Engineerin

A Lumped-parameter Model to Investigate the Effect of Plantar Pressure on Arterial Blood Flow in a Diabetic Foot

This paper presents a lumped-parameter model for the big-toe region that investigates the effect of plantar pressure on the diameter of the blood vessels, specifically the arteries, in the presence of arterial and/or tissue changes. The model developed in this paper uses a multi-domain energy system approach to develop the lumped-parameter differential equations. Blood flow is modelled as fluidic flow through compliant pipes that have inertia, stiffness, and damping. The tissue material is treated as a soft compliant material that transmits the external force to the blood vessels. Conclusions have been drawn to show the effect of plantar pressure, tissue damage, and their combination on the diameter of the blood vessels. The principles used here can be used to model the entire foot and the model used to investigate the effect of plantar pressure, tissue damage, and arterial changes on different parts of the foot. The work presented here may also have applications in other vascular diseases