Fabrication and characterization of graphene hydrogel via hydrothermal approach as a scaffold for preliminary study of cell growth

BACKGROUND: Three-dimensional assembly of graphene hydrogel is rapidly attracting the interest of researchers because of its wide range of applications in energy storage, electronics, electrochemistry, and waste water treatment. Information on the use of graphene hydrogel for biological purposes is lacking, so we conducted a preliminary study to determine the suitability of graphene hydrogel as a substrate for cell growth, which could potentially be used as building blocks for biomolecules and tissue engineering applications. METHODS: A three-dimensional structure of graphene hydrogel was prepared via a simple hydrothermal method using two-dimensional large-area graphene oxide nanosheets as a precursor. RESULTS: The concentration and lateral size of the graphene oxide nanosheets influenced the structure of the hydrogel. With larger-area graphene oxide nanosheets, the graphene hydrogel could be formed at a lower concentration. X-ray diffraction patterns revealed that the oxide functional groups on the graphene oxide nanosheets were reduced after hydrothermal treatment. The three-dimensional graphene hydrogel matrix was used as a scaffold for proliferation of a MG63 cell line. CONCLUSION: Guided filopodia protrusions of MG63 on the hydrogel were observed on the third day of cell culture, demonstrating compatibility of the graphene hydrogel structure for bioapplications

RIDI: Robust IMU Double Integration

This paper proposes a novel data-driven approach for inertial navigation, which learns to estimate trajectories of natural human motions just from an inertial measurement unit (IMU) in every smartphone. The key observation is that human motions are repetitive and consist of a few major modes (e.g., standing, walking, or turning). Our algorithm regresses a velocity vector from the history of linear accelerations and angular velocities, then corrects low-frequency bias in the linear accelerations, which are integrated twice to estimate positions. We have acquired training data with ground-truth motions across multiple human subjects and multiple phone placements (e.g., in a bag or a hand). The qualitatively and quantitatively evaluations have demonstrated that our algorithm has surprisingly shown comparable results to full Visual Inertial navigation. To our knowledge, this paper is the first to integrate sophisticated machine learning techniques with inertial navigation, potentially opening up a new line of research in the domain of data-driven inertial navigation. We will publicly share our code and data to facilitate further research

Simple room-temperature preparation of high-yield large-area graphene oxide

Graphene has attracted much attention from researchers due to its interesting mechanical, electrochemical, and electronic properties. It has many potential applications such as polymer filler, sensor, energy conversion, and energy storage devices. Graphene-based nanocomposites are under an intense spotlight amongst researchers. A large amount of graphene is required for preparation of such samples. Lately, graphene-based materials have been the target for fundamental life science investigations. Despite graphene being a much sought-after raw material, the drawbacks in the preparation of graphene are that it is a challenge amongst researchers to produce this material in a scalable quantity and that there is a concern about its safety. Thus, a simple and efficient method for the preparation of graphene oxide (GO) is greatly desired to address these problems. In this work, one-pot chemical oxidation of graphite was carried out at room temperature for the preparation of large-area GO with ~100% conversion. This high-conversion preparation of large-area GO was achieved using a simplified Hummer’s method from large graphite flakes (an average flake size of 500 μm). It was found that a high degree of oxidation of graphite could be realized by stirring graphite in a mixture of acids and potassium permanganate, resulting in GO with large lateral dimension and area, which could reach up to 120 μm and ~8000 μm2, respectively. The simplified Hummer’s method provides a facile approach for the preparation of large-area GO

Multi-factor service design: identification and consideration of multiple factors of the service in its design process

Service design is a multidisciplinary area that helps innovate services by bringing new ideas to customers through a design-thinking approach. Services are affected by multiple factors, which should be considered in designing services. In this paper, we propose the multi-factor service design (MFSD) method, which helps consider the multi-factor nature of service in the service design process. The MFSD method has been developed through and used in five service design studies with industry and government. The method addresses the multi-factor nature of service for systematic service design by providing the following guidelines: (1) identify key factors that affect the customer value creation of the service in question (in short, value creation factors), (2) define the design space of the service based on the value creation factors, and (3) design services and represent them based on the factors. We provide real stories and examples from the five service design studies to illustrate the MFSD method and demonstrate its utility. This study will contribute to the design of modern complex services that are affected by varied factors

Microhardness and friction coefficient of multi-walled carbon nanotube-yttria-stabilized ZrO2 composites prepared by spark plasma sintering

Multi-walled carbon nanotubes (eight walls) are mixed with an yttria-stabilized ZrO2 powder. The specimens are densified by spark plasma sintering. Compared to ZrO2, there is a 3.8-fold decrease of the friction coefficient against alumina upon the increase in carbon content. Examinations of the friction tracks show that wear is very low when the carbon content is sufficient. Exfoliation of the nanotubes due to shearing stresses and incorporation of the debris into a lubricating film over the contact area is probable

Lysosomal acidification dysfunction in microglia: an emerging pathogenic mechanism of neuroinflammation and neurodegeneration

Microglia are the resident innate immune cells in the brain with a major role in orchestrating immune responses. They also provide a frontline of host defense in the central nervous system (CNS) through their active phagocytic capability. Being a professional phagocyte, microglia participate in phagocytic and autophagic clearance of cellular waste and debris as well as toxic protein aggregates, which relies on optimal lysosomal acidification and function. Defective microglial lysosomal acidification leads to impaired phagocytic and autophagic functions which result in the perpetuation of neuroinflammation and progression of neurodegeneration. Reacidification of impaired lysosomes in microglia has been shown to reverse neurodegenerative pathology in Alzheimer's disease. In this review, we summarize key factors and mechanisms contributing to lysosomal acidification impairment and the associated phagocytic and autophagic dysfunction in microglia, and how these defects contribute to neuroinflammation and neurodegeneration. We further discuss techniques to monitor lysosomal pH and therapeutic agents that can reacidify impaired lysosomes in microglia under disease conditions. Finally, we propose future directions to investigate the role of microglial lysosomal acidification in lysosome-mitochondria crosstalk and in neuron-glia interaction for more comprehensive understanding of its broader CNS physiological and pathological implications

Left atrial enhancement correlates with myocardial conduction velocity in patients with persistent atrial fibrillation

Background: Conduction velocity (CV) heterogeneity and myocardial fibrosis both promote re-entry, but the relationship between fibrosis as determined by left atrial (LA) late-gadolinium enhanced cardiac magnetic resonance imaging (LGE-CMRI) and CV remains uncertain. Objective: Although average CV has been shown to correlate with regional LGE-CMRI in patients with persistent AF, we test the hypothesis that a localized relationship exists to underpin LGE-CMRI as a minimally invasive tool to map myocardial conduction properties for risk stratification and treatment guidance. Method: 3D LA electroanatomic maps during LA pacing were acquired from eight patients with persistent AF following electrical cardioversion. Local CVs were computed using triads of concurrently acquired electrograms and were co-registered to allow correlation with LA wall intensities obtained from LGE-CMRI, quantified using normalized intensity (NI) and image intensity ratio (IIR). Association was evaluated using multilevel linear regression. Results: An association between CV and LGE-CMRI intensity was observed at scales comparable to the size of a mapping electrode: −0.11 m/s per unit increase in NI (P < 0.001) and −0.96 m/s per unit increase in IIR (P < 0.001). The magnitude of this change decreased with larger measurement area. Reproducibility of the association was observed with NI, but not with IIR. Conclusion: At clinically relevant spatial scales, comparable to area of a mapping catheter electrode, LGE-CMRI correlates with CV. Measurement scale is important in accurately quantifying the association of CV and LGE-CMRI intensity. Importantly, NI, but not IIR, accounts for changes in the dynamic range of CMRI and enables quantitative reproducibility of the association

Induction of fibroblast senescence generates a non-fibrogenic myofibroblast phenotype that differentially impacts on cancer prognosis

Cancer-associated fibroblasts (CAF) remain a poorly characterized, heterogeneous cell population. Here we characterized two previously described tumor-promoting CAF sub-types, smooth muscle actin (SMA)-positive myofibroblasts and senescent fibroblasts, identifying a novel link between the two