Inhibition of RANKL-Induced Osteoclastogenesis by Novel Mutant RANKL

Background: Recently, it was reported that leucine-rich repeat-containing G-protein-coupled receptor 4 (LGR4, also called GPR48) is another receptor for RANKL and was shown to compete with RANK to bind RANKL and suppress canonical RANK signaling during osteoclast differentiation. The critical role of the protein triad RANK–RANKL in osteoclastogenesis has made their binding an important target for the development of drugs against osteoporosis. In this study, point-mutations were introduced in the RANKL protein based on the crystal structure of the RANKL complex and its counterpart receptor RANK, and we investigated whether LGR4 signaling in the absence of the RANK signal could lead to the inhibition of osteoclastogenesis.; Methods: The effects of point-mutated RANKL (mRANKL-MT) on osteoclastogenesis were assessed by tartrate-resistant acid phosphatase (TRAP), resorption pit formation, quantitative real-time polymerase chain reaction (qPCR), western blot, NFATc1 nuclear translocation, micro-CT and histomorphological assay in wild type RANKL (mRANKL-WT)-induced in vitro and in vivo experimental mice model. Results: As a proof of concept, treatment with the mutant RANKL led to the stimulation of GSK-3β phosphorylation, as well as the inhibition of NFATc1 translocation, mRNA expression of TRAP and OSCAR, TRAP activity, and bone resorption, in RANKL-induced mouse models; and Conclusions: The results of our study demonstrate that the mutant RANKL can be used as a therapeutic agent for osteoporosis by inhibiting RANKL-induced osteoclastogenesis via comparative inhibition of RANKL. Moreover, the mutant RANKL was found to lack the toxic side effects of most osteoporosis treatments.     

Fire safe,sustainable loose furnishing

The aim of this exploratory study has been to investigate the fire properties and environmental aspects of different upholstery material combinations, mainly for domestic applications. An analysis of the sustainability and circularity of selected textiles, along with lifecycle assessment, is used to qualitatively evaluate materials from an environmental perspective. The cone calorimeter was the primary tool used to screen 20 different material combinations from a fire performance perspective. It was found that textile covers of conventional fibres such as wool, cotton and polyester, can be improved by blending them with fire resistant speciality fibres. A new three‐dimensional web structure has been examined as an alternative padding material, showing preliminary promising fire properties with regard to ignition time, heat release rates and smoke production.     

Magnetically Guidable Proteinaceous Adhesive Microbots for Targeted Locoregional Therapeutics Delivery in the Highly Dynamic Environment of the Esophagus

The esophagus is a tubular-shaped muscular organ where swallowed fluids and muscular contractions constitute a highly dynamic environment. The turbulent, coordinated processes that occur through the oropharyngeal conduit can often compromise targeted administration of therapeutic drugs to a lesion, significantly reducing therapeutic efficacy. Here, magnetically guidable drug vehicles capable of strongly adhering to target sites using a bioengineered mussel adhesive protein (MAP) to achieve localized delivery of therapeutic drugs against the hydrodynamic physiological conditions are proposed. A suite of highly uniform microparticles embedded with iron oxide (IO) nanoparticles (MAP@IO MPs) is microfluidically fabricated using the genipin-mediated covalent cross-linking of bioengineered MAP. The MAP@IO MPs are successfully targeted to a specific region and prolongedly retained in the tubular-structured passageway. In particular, orally administered MAP@IO MPs are effectively captured in the esophagus in vivo in a magnetically guidable manner. Moreover, doxorubicin (DOX)-loaded MAP@IO MPs exhibit a sustainable DOX release profile, effective anticancer therapeutic activity, and excellent biocompatibility. Thus, the magnetically guidable locomotion and robust underwater adhesive properties of the proteinaceous soft microbots can provide an intelligent modular approach for targeted locoregional therapeutics delivery to a specific lesion site in dynamic fluid-associated tubular organs such as the esophagus.     

A Lane-Level Road Marking Map Using a Monocular Camera

The essential requirement for precise localization of a self-driving car is a lane-level map which includes road markings (RMs). Obviously, we can build the lane-level map by running a mobile mapping system (MMS) which is equipped with a high-end 3D LiDAR and a number of high-cost sensors. This approach, however, is highly expensive and ineffective since a single high-end MMS must visit every place for mapping. In this paper, a lane-level RM mapping system using a monocular camera is developed. The developed system can be considered as an alternative to expensive high-end MMS. The developed RM map includes the information of road lanes (RLs) and symbolic road markings (SRMs). First, to build a lane-level RM map, the RMs are segmented at pixel level through the deep learning network. The network is named RMNet. The segmented RMs are then gathered to build a lane-level RM map. Second, the lane-level map is improved through loop-closure detection and graph optimization. To train the RMNet and build a lane-level RM map, a new dataset named SeRM set is developed. The set is a large dataset for lane-level RM mapping and it includes a total of 25157 pixel-wise annotated images and 21000 position labeled images. Finally, the proposed lane-level map building method is applied to SeRM set and its validity is demonstrated through experimentation.      

Investigation of bacterial and fungal communities in indoor and outdoor air of elementary school classrooms by 16S rRNA gene and ITS region sequencing

The advent of high-throughput sequencing methods allowed researchers to fully characterize microbial community in environmental samples, which is crucial to better understand their health effects upon exposures. In our study, we investigated bacterial and fungal community in indoor and outdoor air of nine classrooms in three elementary schools in Seoul, Korea. The extracted bacterial 16S rRNA gene and fungal ITS regions were sequenced, and their taxa were identified. Quantitative polymerase chain reaction for total bacteria DNA was also performed. The bacterial community was richer in outdoor air than classroom air, whereas fungal diversity was similar indoors and outdoors. Bacteria such as Enhydrobacter, Micrococcus, and Staphylococcus that are generally found in human skin, mucous membrane, and intestine were found in great abundance. For fungi, Cladosporium, Clitocybe, and Daedaleopsis were the most abundant genera in classroom air and mostly related to outdoor plants. Bacterial community composition in classroom air was similar among all classrooms but differed from that in outdoor air. However, indoor and outdoor fungal community compositions were similar for the same school but different among schools. Our study indicated the main source of airborne bacteria in classrooms was likely human occupants; however, classroom airborne fungi most likely originated from outdoors.     

Nanogrooved carbon microtubes for wet three‐dimensional printing of conductive composite structures

Recent advances in three‐dimensional (3D) printing have enabled the fabrication of interesting structures which are not achievable using traditional fabrication approaches. The 3D printing of carbon microtube composite inks allows fabrication of conductive structures for practical applications in soft robotics and tissue engineering. However, it is challenging to achieve 3D printed structures from solution‐based composite inks, which requires an additional process to solidify the ink. Here, we introduce a wet 3D printing technique which uses a coagulation bath to fabricate carbon microtube composite structures. We show that through a facile nanogrooving approach which introduces cavitation and channels on carbon microtubes, enhanced interfacial interactions with a chitosan polymer matrix are achieved. Consequently, the mechanical properties of the 3D printed composites improve when nanogrooved carbon microtubes are used, compared to untreated microtubes. We show that by carefully controlling the coagulation bath, extrusion pressure, printing distance and printed line distance, we can 3D print composite lattices which are composed of well‐defined and separated printed lines. The conductive composite 3D structures with highly customised design presented in this work provide a suitable platform for applications ranging from soft robotics to smart tissue engineering scaffolds. © 2019 Society of Chemical Industry     

Modification of narrow‐spectrum peptidomimetic polyurethanes with fatty acid chains confers broad‐spectrum antibacterial activity

Each year, thousands of patients die from antimicrobial‐resistant bacterial infections that fail to respond to conventional antibiotic treatment. Antimicrobial polymers are a promising new method of combating antibiotic‐resistant bacterial infections. We have previously reported the synthesis of a series of narrow‐spectrum peptidomimetic antimicrobial polyurethanes that are effective against Gram‐negative bacteria, such as Escherichia coli; however, these polymers are not effective against Gram‐positive bacteria, such as Staphylococcus aureus. With the aim of understanding the correlation between chemical structure and antibacterial activity, we have subsequently developed three structural variants of these antimicrobial polyurethanes using post‐polymerization modification with decanoic acid and oleic acid. Our results show that such modifications converted the narrow‐spectrum antibacterial activity of these polymers into broad‐spectrum activity against Gram‐positive species such as S. aureus, however, also increasing their toxicity to mammalian cells. Mechanistic studies of bacterial membrane disruption illustrate the differences in antibacterial action between the various polymers. The results demonstrate the challenge of balancing antimicrobial activity and mammalian cell compatibility in the design of antimicrobial polymer compositions. © 2019 Society of Chemical Industry     

Bayesian Inference for ARFIMA Models

This article develops practical methods for Bayesian inference in the autoregressive fractionally integrated moving average (ARFIMA) model using the exact likelihood function, any proper prior distribution, and time series that may have thousands of observations. These methods utilize sequentially adaptive Bayesian learning, a sequential Monte Carlo algorithm that can exploit massively parallel desktop computing with graphics processing units (GPUs). The article identifies and solves several problems in the computation of the likelihood function that apparently have not been addressed in the literature. Four applications illustrate the utility of the approach. The most ambitious is an ARFIMA(2,d,2) model for the Campito tree ring time series (length 5405), for which the methods developed in the article provide an essentially uncorrelated sample of size 16,384 from the exact posterior distribution in under four hours. Less ambitious applications take as little as 4 minutes without exploiting GPUs.