A CNN-based method to reconstruct 3-D spine surfaces from US images in vivo.

Three-dimensional (3-D) reconstruction of the spine surface is of strong clinical relevance for the diagnosis and prognosis of spine disorders and intra-operative image guidance. In this paper, we report a new technique to reconstruct lumbar spine surfaces in 3-D from non-invasive ultrasound (US) images acquired in free-hand mode. US images randomly sampled from in vivo scans of 9 rabbits were used to train a U-net convolutional neural network (CNN). More specifically, a late fusion (LF)-based U-net trained jointly on B-mode and shadow-enhanced B-mode images was generated by fusing two individual U-nets and expanding the set of trainable parameters to around twice the capacity of a basic U-net. This U-net was then applied to predict spine surface labels in in vivo images obtained from another rabbit, which were then used for 3-D spine surface reconstruction. The underlying pose of the transducer during the scan was estimated by registering stacks of US images to a geometrical model derived from corresponding CT data and used to align detected surface points. Final performance of the reconstruction method was assessed by computing the mean absolute error (MAE) between pairs of spine surface points detected from US and CT and by counting the total number of surface points detected from US. Comparison was made between the LF-based U-net and a previously developed phase symmetry (PS)-based method. Using the LF-based U-net, the averaged number of US surface points across the lumbar region increased by 21.61% and MAE reduced by 26.28% relative to the PS-based method. The overall MAE (in mm) was 0.24±0.29. Based on these results, we conclude that: 1) the proposed U-net can detect the spine posterior arch with low MAE and large number of US surface points and 2) the newly proposed reconstruction framework may complement and, under certain circumstances, be used without the aid of an external tracking system in intra-operative spine applications.

Microglia as therapeutic targets after neurological injury: strategy for cell therapy.

INTRODUCTION: Microglia is the resident tissue macrophages of the central nervous system. Prolonged microglial activation often occurs after traumatic brain injury and is associated with deteriorating neurocognitive outcomes. Resolution of microglial activation is associated with limited tissue loss and improved neurocognitive outcomes. Limiting the prolonged pro-inflammatory response and the associated secondary tissue injury provides the rationale and scientific premise for considering microglia as a therapeutic target. AREAS COVERED: In this review, we discuss markers of microglial activation, such as immunophenotype and microglial response to injury, including cytokine/chemokine release, free radical formation, morphology, phagocytosis, and metabolic shifts. We compare the origin and role in neuroinflammation of microglia and monocytes/macrophages. We review potential therapeutic targets to shift microglial polarization. Finally, we review the effect of cell therapy on microglia. EXPERT OPINION: Dysregulated microglial activation after neurologic injury, such as traumatic brain injury, can worsen tissue damage and functional outcomes. There are potential targets in microglia to attenuate this activation, such as proteins and molecules that regulate microglia polarization. Cellular therapeutics that limit, but do not eliminate, the inflammatory response have improved outcomes in animal models by reducing pro-inflammatory microglial activation via secondary signaling. These findings have been replicated in early phase clinical trials.

Conditioning of 3D Printed Nanoengineered Ionic-Covalent Entanglement Scaffolds with iP-hMSCs Derived Matrix.

Additive manufacturing is a promising method for producing customized 3D bioactive constructs for regenerative medicine. Here, 3D printed highly osteogenic scaffolds using nanoengineered ionic-covalent entanglement ink (NICE) for bone tissue engineering are reported. This NICE ink consists of ionic-covalent entanglement reinforced with Laponite, a 2D nanosilicate (nSi) clay, allowing for the printing of anatomic-sized constructs with high accuracy. The 3D printed structure is able to maintain high structural stability in physiological conditions without any significant swelling or deswelling. The presence of nSi imparts osteoinductive characteristics to the NICE scaffolds, which is further augmented by depositing pluripotent stem cell-derived extracellular matrix (ECM) on the scaffolds. This is achieved by stimulating human induced pluripotent stem cell-derived mesenchymal stem cells (iP-hMSCs) with 2-chloro-5-nitrobenzanilide, a PPARγ inhibitor that enhances Wnt pathway, resulting in the deposition of an ECM characterized by high levels of collagens VI and XII found in anabolic bone. The osteoinductive characteristics of these bioconditioned NICE (bNICE) scaffolds is demonstrated through osteogenic differentiation of bone marrow derived human mesenchymal stem cells. A significant increase in the expression of osteogenic gene markers as well as mineralized ECM are observed on bioconditioned NICE (bNICE) scaffolds compared to bare scaffolds (NICE). The bioconditioned 3D printed scaffolds provide a unique strategy to design personalized bone grafts for in situ bone regeneration.

The many ways adherent cells respond to applied stretch.

Cells in various tissues are subjected to mechanical stress and strain that have profound effects on cell architecture and function. The specific response of the cell to applied strain depends on multiple factors, including cell contractility, spatial and temporal strain pattern, and substrate dimensionality and rigidity. Recent work has demonstrated that the cell response to applied strain depends on a complex combination of these factors, but the way these factors interact to elicit a specific response is not intuitive. We submit that an understanding of the integrated response of a cell to these factors will provide new insight into mechanobiology and contribute to the effective design of deformable engineered scaffolds meant to provide appropriate mechanical cues to the resident cells.