Current Animal Models of Postoperative Spine Infection and Potential Future Advances.

Implant related infection following spine surgery is a devastating complication for patients and can potentially lead to significant neurological compromise, disability, morbidity, and even mortality. This paper provides an overview of the existing animal models of postoperative spine infection and highlights the strengths and weaknesses of each model. In addition, there is discussion regarding potential modifications to these animal models to better evaluate preventative and treatment strategies for this challenging complication. Current models are effective in simulating surgical procedures but fail to evaluate infection longitudinally using multiple techniques. Potential future modifications to these models include using advanced imaging technologies to evaluate infection, use of bioluminescent bacterial species, and testing of novel treatment strategies against multiple bacterial strains. There is potential to establish a postoperative spine infection model using smaller animals, such as mice, as these would be a more cost-effective screening tool for potential therapeutic interventions

In-situ hybridization of an epoxy resin using polyurethane and MXene nanoplatelets for thermally stable nanocomposites with improved strength and toughness

A novel ternary composite system has been developed by combining MXene nanoplatelets with pre-polyurethane (PU) and an epoxy (EP) resin through in-situ polymerization and solution blending. Our approach aims to enhance the strength and toughness of the EP matrix while maintaining its thermal stability. The strong compatibility between isocyanate-terminated PU and hydroxyl-terminated MXene with the resin was demonstrated through chemical grafting and hydrogen bonding processes. In this ternary composite, significant improvements were observed, including a 32 % increase in tensile strength, a 46.4 % increase in flexural strength, and a 13.4 % increase in fracture toughness, even at very low filler contents of 0.05 wt% for MXene and 1 wt% for PU. A thorough examination of the fractured surfaces revealed the underlying mechanisms responsible for the improved strength and toughness. These mechanisms involve a transition from a brittle to a ductile fracture mode, which can be attributed to the combined effects of thermoplastic toughness, strong chemical bonding between PU and EP, and crack-anchoring and bridging effects facilitated by MXene nanoplatelets. The results presented herein are relevant to a wide range of applications in aerospace, automotive, electronics and various other industries where durability and thermomechanical performance of materials are critical

Biofilter aquaponic system for nutrients removal from fresh market wastewater

Aquaponics is a significant wastewater treatment system which refers to the combination of conventional aquaculture (raising aquatic organism) with hydroponics (cultivating plants in water) in a symbiotic environment. This system has a high ability in removing nutrients compared to conventional methods because it is a natural and environmentally friendly system (aquaponics). The current chapter aimed to review the possible application of aquaponics system to treat fresh market wastewater with the intention to highlight the mechanism of phytoremediation occurs in aquaponic system. The literature revealed that aquaponic system was able to remove nutrients in terms of nitrogen and phosphorus

Pilot-scale continuous synthesis of a vanadium-doped LiFePO4/C nanocomposite high-rate cathodes for lithium-ion batteries

A high performance vanadium-doped LiFePO4 (LFP) electrode is synthesized using a continuous hydrothermal method at a production rate of 6 kg per day. The supercritical water reagent rapidly generates core/shell nanoparticles with a thin, continuous carbon coating on the surface of LFP, which aids electron transport dynamics across the particle surface. Vanadium dopant concentration has a profound effect on the performance of LFP, where the composition LiFe0.95V0.05PO4, achieves a specific discharge capacity which is among the highest in the comparable literature (119 mA h g−1 at a discharge rate of 1500 mA g−1). Additionally, a combination of X-ray absorption spectroscopy analysis and hybrid-exchange density functional theory, suggest that vanadium ions replace both phosphorous and iron in the structure, thereby facilitating Li+ diffusion due to Li+ vacancy generation and changes in the crystal structure

Evidence for Anthropogenic Surface Loading as Trigger Mechanism of the 2008 Wenchuan Earthquake

Two and a half years prior to China's M7.9 Wenchuan earthquake of May 2008, at least 300 million metric tons of water accumulated with additional seasonal water level changes in the Minjiang River Valley at the eastern margin of the Longmen Shan. This article shows that static surface loading in the Zipingpu water reservoir induced Coulomb failure stresses on the nearby Beichuan thrust fault system at <17km depth. Triggering stresses exceeded levels of daily lunar and solar tides and perturbed a fault area measuring 416+/-96km^2. These stress perturbations, in turn, likely advanced the clock of the mainshock and directed the initial rupture propagation upward towards the reservoir on the "Coulomb-like" Beichuan fault with rate-and-state dependent frictional behavior. Static triggering perturbations produced up to 60 years (0.6%) of equivalent tectonic loading, and show strong correlations to the coseismic slip. Moreover, correlations between clock advancement and coseismic slip, observed during the mainshock beneath the reservoir, are strongest for a longer seismic cycle (10kyr) of M>7 earthquakes. Finally, the daily event rate of the micro-seismicity (M>0.5) correlates well with the static stress perturbations, indicating destabilization.Comment: 22 pages, 4 figures, 3 table

A glutathione s-transferase confers herbicide tolerance in rice

Plant glutathione S-transferases (GSTs) have been a focus of attention due to their role in herbicide detoxification. OsGSTL2 is a glutathione S-transferase, lambda class gene from rice (Oryza sativa L.). Transgenic rice plants over-expressing OsGSTL2 were generated from rice calli by the use of an Agrobacterium transformation system, and were screened by a combination of hygromycin resistance, PCR and Southern blot analysis. In the vegetative tissues of transgenic rice plants, the over-expression of OsGSTL2 not only increased levels of OsGSTL2 transcripts, but also GST and GPX expression, while reduced superoxide. Transgenic rice plants also showed higher tolerance to glyphosate and chlorsulfuron, which often contaminate agricultural fields. The findings demonstrate the detoxification role of OsGSTL2 in the growth and development of rice plants. It should be possible to apply the present results to crops for developing herbicide tolerance and for limiting herbicide contamination in the food chain

Identification of Pns6, a putative movement protein of RRSV, as a silencing suppressor

RNA silencing is a potent antiviral response in plants. As a counterdefense, most plant and some animal viruses encode RNA silencing suppressors. In this study, we showed that Pns6, a putative movement protein of Rice ragged stunt virus (RRSV), exhibited silencing suppressor activity in coinfiltration assays with the reporter green fluorescent protein (GFP) in transgenic Nicotiana benthamiana line 16c. Pns6 of RRSV suppressed local silencing induced by sense RNA but had no effect on that induced by dsRNA. Deletion of a region involved in RNA binding abolished the silencing suppressor activity of Pns6. Further, expression of Pns6 enhanced Potato virus × pathogenicity in N. benthamiana. Collectively, these results suggested that RRSV Pns6 functions as a virus suppressor of RNA silencing that targets an upstream step of the dsRNA formation in the RNA silencing pathway. This is the first silencing suppressor to be identified from the genus Oryzavirus

DeepReg: a deep learning toolkit for medical image registration

Image fusion is a fundamental task in medical image analysis and computer-assisted intervention. Medical image registration, computational algorithms that align different images together (Hill et al., 2001), has in recent years turned the research attention towards deep learning. Indeed, the representation ability to learn from population data with deep neural networks has opened new possibilities for improving registration generalisability by mitigating difficulties in designing hand-engineered image features and similarity measures for many realworld clinical applications (Fu et al., 2020; Haskins et al., 2020). In addition, its fast inference can substantially accelerate registration execution for time-critical tasks. DeepReg is a Python package using TensorFlow (Abadi et al., 2015) that implements multiple registration algorithms and a set of predefined dataset loaders, supporting both labelledand unlabelled data. DeepReg also provides command-line tool options that enable basic and advanced functionalities for model training, prediction and image warping. These implementations, together with their documentation, tutorials and demos, aim to simplify workflows for prototyping and developing novel methodology, utilising latest development and accessing quality research advances. DeepReg is unit tested and a set of customised contributor guidelines are provided to facilitate community contributions. A submission to the MICCAI Educational Challenge has utilised the DeepReg code and demos to explore the link between classical algorithms and deep-learning-based methods (Montana Brown et al., 2020), while a recently published research work investigated temporal changes in prostate cancer imaging, by using a longitudinal registration adapted from the DeepReg code (Yang et al., 2020)