Bioink properties before, during and after 3D bioprinting

Bioprinting is a process based on additive manufacturing from materials containing living cells. These materials, often referred to as bioink, are based on cytocompatible hydrogel precursor formulations, which gel in a manner compatible with different bioprinting approaches. The bioink properties before, during and after gelation are essential for its printability, comprising such features as achievable structural resolution, shape fidelity and cell survival. However, it is the final properties of the matured bioprinted tissue construct that are crucial for the end application. During tissue formation these properties are influenced by the amount of cells present in the construct, their proliferation, migration and interaction with the material. A calibrated computational framework is able to predict the tissue development and maturation and to optimize the bioprinting input parameters such as the starting material, the initial cell loading and the construct geometry. In this contribution relevant bioink properties are reviewed and discussed on the example of most popular bioprinting approaches. The effect of cells on hydrogel processing and vice versa is highlighted. Furthermore, numerical approaches were reviewed and implemented for depicting the cellular mechanics within the hydrogel as well as for prediction of mechanical properties to achieve the desired hydrogel construct considering cell density, distribution and material-cell interaction

ToScA North America (6 – 8 June 2017, The University of Texas, Austin, TX) Program

ToScA North America will address key areas of science, including Multi-modal Imaging, Geosciences, Forensics, Increasing Contrast, Educational Outreach, Data, Materials Science and Medical and Biological Science.University of Texas High-Resolution X-ray CT Facility (UTCT); Jackson School of Geosciences, The University of Texas at Austin; Natural History Museum (London); Royal Microscopical Society (Oxford, UK)Geological Science

Deep deformable models for 3D human body

Deformable models are powerful tools for modelling the 3D shape variations for a class of objects. However, currently the application and performance of deformable models for human body are restricted due to the limitations in current 3D datasets, annotations, and the model formulation itself. In this thesis, we address the issue by making the following contributions in the field of 3D human body modelling, monocular reconstruction and data collection/annotation. Firstly, we propose a deep mesh convolutional network based deformable model for 3D human body. We demonstrate the merit of this model in the task of monocular human mesh recovery. While outperforming current state of the art models in mesh recovery accuracy, the model is also light weighted and more flexible as it can be trained end-to-end and fine-tuned for a specific task. A second contribution is a bone level skinned model of 3D human mesh, in which bone modelling and identity-specific variation modelling are decoupled. Such formulation allows the use of mesh convolutional networks for capturing detailed identity specific variations, while explicitly controlling and modelling the pose variations through linear blend skinning with built-in motion constraints. This formulation not only significantly increases the accuracy in 3D human mesh reconstruction, but also facilitates accurate in the wild character animation and retargetting. Finally we present a large scale dataset of over 1.3 million 3D human body scans in daily clothing. The dataset contains over 12 hours of 4D recordings at 30 FPS, consisting of 7566 dynamic sequences of 3D meshes from 4205 subjects. We propose a fast and accurate sequence registration pipeline which facilitates markerless motion capture and automatic dense annotation for the raw scans, leading to automatic synthetic image and annotation generation that boosts the performance for tasks such as monocular human mesh reconstruction.Open Acces

Non-rigid registration of 2-D/3-D dynamic data with feature alignment

In this work, we are computing the matching between 2D manifolds and 3D manifolds with temporal constraints, that is we are computing the matching among a time sequence of 2D/3D manifolds. It is solved by mapping all the manifolds to a common domain, then build their matching by composing the forward mapping and the inverse mapping. At first, we solve the matching problem between 2D manifolds with temporal constraints by using mesh-based registration method. We propose a surface parameterization method to compute the mapping between the 2D manifold and the common 2D planar domain. We can compute the matching among the time sequence of deforming geometry data through this common domain. Compared with previous work, our method is independent of the quality of mesh elements and more efficient for the time sequence data. Then we develop a global intensity-based registration method to solve the matching problem between 3D manifolds with temporal constraints. Our method is based on a 4D(3D+T) free-from B-spline deformation model which has both spatial and temporal smoothness. Compared with previous 4D image registration techniques, our method avoids some local minimum. Thus it can be solved faster and achieve better accuracy of landmark point predication. We demonstrate the efficiency of these works on the real applications. The first one is applied to the dynamic face registering and texture mapping. The second one is applied to lung tumor motion tracking in the medical image analysis. In our future work, we are developing more efficient mesh-based 4D registration method. It can be applied to tumor motion estimation and tracking, which can be used to calculate the read dose delivered to the lung and surrounding tissues. Thus this can support the online treatment of lung cancer radiotherapy

Spatiotemporal release of VEGF from biodegradable polylactic-co-glycolic acid microspheres induces angiogenesis in chick chorionic allantoic membrane assay

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.While vascular endothelial growth factor (VEGF) is an acknowledged potent pro-angiogenic agent there is a need to deliver it at an appropriate concentration for several days to achieve angiogenesis. The aim of this study was to produce microspheres of biodegradable polylactic-co-glycolic acid (PLGA) tailored to achieve sustained release of VEGF at an appropriate concentration over seven days, avoiding excessive unregulated release of VEGF that has been associated with the formation of leaky blood vessels. Several formulations were examined to produce microspheres loaded with both human serum albumin (HSA) and VEGF to achieve release of VEGF between 3 and 10 ng per ml for seven days to match the therapeutic window desired for angiogenesis. In vitro experiments showed an increase in endothelial cell proliferation in response to microspheres bearing VEGF. Similarly, when microspheres containing VEGF were added to the chorionic membrane of fertilised chicken eggs, there was an increase in the development of blood vessels over seven days in response, which was significant for microspheres bearing VEGF and HSA, but not VEGF alone. There was an increase in both blood vessel density and branching – both signs of proangiogenic activity. Further, there was clearly migration of cells to the VEGF loaded microspheres. In summary, we describe the development of an injectable delivery vehicle to achieve spatiotemporal release of physiologically relevant levels of VEGF for several days and demonstrate the angiogenic response to this. We propose that such a treatment vehicle would be suitable for the treatment of ischemic tissue or wounds

Advances in FAI Imaging: a Focused Review

Purpose of review: Femoroacetabular impingement (FAI) is one of the main causes of hip pain in young adults and poses clinical challenges which have placed it at the forefront of imaging and orthopedics. Diagnostic hip imaging has dramatically changed in the past years, with the arrival of new imaging techniques and the development of magnetic resonance imaging (MRI). This article reviews the current state-of-the-art clinical routine of individuals with suspected FAI, limitations, and future directions that show promise in the field of musculoskeletal research and are likely to reshape hip imaging in the coming years. Recent findings: The largely unknown natural disease course, especially in hips with FAI syndrome and those with asymptomatic abnormal morphologies, continues to be a problem as far as diagnosis, treatment, and prognosis are concerned. There has been a paradigm shift in recent years from bone and soft tissue morphological analysis towards the tentative development of quantitative approaches, biochemical cartilage evaluation, dynamic assessment techniques and, finally, integration of artificial intelligence (AI)/deep learning systems. Imaging, AI, and hip preserving care will continue to evolve with new problems and greater challenges. The increasing number of analytic parameters describing the hip joint, as well as new sophisticated MRI and imaging analysis, have carried practitioners beyond simplistic classifications. Reliable evidence-based guidelines, beyond differentiation into pure instability or impingement, are paramount to refine the diagnostic algorithm and define treatment indications and prognosis. Nevertheless, the boundaries of morphological, functional, and AI-aided hip assessment are gradually being pushed to new frontiers as the role of musculoskeletal imaging is rapidly evolving.info:eu-repo/semantics/publishedVersio

G\mathcal{G}-SELC: Optimization by sequential elimination of level combinations using genetic algorithms and Gaussian processes

Identifying promising compounds from a vast collection of feasible compounds is an important and yet challenging problem in the pharmaceutical industry. An efficient solution to this problem will help reduce the expenditure at the early stages of drug discovery. In an attempt to solve this problem, Mandal, Wu and Johnson [Technometrics 48 (2006) 273--283] proposed the SELC algorithm. Although powerful, it fails to extract substantial information from the data to guide the search efficiently, as this methodology is not based on any statistical modeling. The proposed approach uses Gaussian Process (GP) modeling to improve upon SELC, and hence named $\mathcal{G}$-SELC. The performance of the proposed methodology is illustrated using four and five dimensional test functions. Finally, we implement the new algorithm on a real pharmaceutical data set for finding a group of chemical compounds with optimal properties.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS199 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Applications and multidisciplinary perspective on 3D printing techniques: Recent developments and future trends

In industries as diverse as automotive, aerospace, medical, energy, construction, electronics, and food, the engineering technology known as 3D printing or additive manufacturing facilitates the fabrication of rapid prototypes and the delivery of customized parts. This article explores recent advancements and emerging trends in 3D printing from a novel multidisciplinary perspective. It also provides a clear overview of the various 3D printing techniques used for producing parts and components in three dimensions. The application of these techniques in bioprinting and an up-to-date comprehensive review of their positive and negative aspects are covered, as well as the variety of materials used, with an emphasis on composites, hybrids, and smart materials. This article also provides an updated overview of 4D bioprinting technology, including biomaterial functions, bioprinting materials, and a targeted approach to various tissue engineering and regenerative medicine (TERM) applications. As a foundation for anticipated developments for TERM applications that could be useful for their successful usage in clinical settings, this article also examines present challenges and obstacles in 4D bioprinting technology. Finally, the article also outlines future regulations that will assist researchers in the manufacture of complex products and in the exploration of potential solutions to technological issues