Strand Displacement Amplification for Multiplex Detection of Nucleic Acids

The identification of various targets such as bacteria, viruses, and other cells remains a prerequisite for point-of-care diagnostics and biotechnological applications. Nucleic acids, as encoding information for all forms of life, are excellent biomarkers for detecting pathogens, hereditary diseases, and cancers. To date, many techniques have been developed to detect nucleic acids. However, most of them are based on polymerase chain reaction (PCR) technology. These methods are sensitive and robust, but they require expensive instruments and trained personnel. DNA strand displacement amplification is carried out under isothermal conditions and therefore does not need expensive instruments. It is simple, fast, sensitive, specific, and inexpensive. In this chapter, we introduce the principles, methods, and updated applications of DNA strand displacement technology in the detection of infectious diseases. We also discuss how robust, sensitive, and specific nucleic acid detection could be obtained when combined with the novel CRISPR/Cas system

Graphene Oxide-Based Biosensors

In this chapter, the latest developments in graphene oxide-based biosensors are presented. These biosensors are complexes of graphene oxide and biomacromolecules, including enzymes such as glucose oxidase, horseradish peroxidase, laccase, and nucleic acids such as DNA and RNA. The structure, design and preparation process (immobilization process) of the above graphene oxide-biomacromolecule composites were summarized. Some typical examples of immobilization of biological macromolecules are described. The immobilization efficiency and electrochemical performance of immobilized biomolecules based on graphene oxide were discussed, which may guide designing better graphene oxide-based biosensors

3D characterization of ultrasonic melt processing on the microstructural refinement of Al-Cu alloys by synchrotron X-ray tomography

The effect of ultrasonic melting processing on three-dimensional architecture of intermetallic phases and pores in two multicomponent cast Al-5.0Cu-0.6Mn-0.5 Fe alloys is characterized using conventional microscopy and synchrotron X-ray microtomography. The two alloys are found to contain intermetallic phases such as Al15(FeMn)3Cu2, Al7Cu2Fe, Al3(FeMn), Al6(FeMn), and Al2Cu that have complex networked morphology in 3D. The application of USP in alloys can obtained refined and equiaxed microstructures. The grain size of 0.5Fe and 1.0 Fe alloys is greatly decreased from 16.9 m, 15.8 m without USP to 13.3 m, 12.2 m with USP, respectively. The results show that USP significantly reduce the volume fraction, grain size, interconnectivity, and equivalent diameter of the intermetallic phases in both alloys. The volume fraction of pores in both alloys is reduced due to the USP degassing effect. The refinement mechanism of USP induced fragmentation of primary and secondary dendrites via acoustic bubbles and acoustic streaming flow were discussed.Comment: 28 pages, 16 figures

CloudBrain-NMR: An Intelligent Cloud Computing Platform for NMR Spectroscopy Processing, Reconstruction and Analysis

Nuclear Magnetic Resonance (NMR) spectroscopy has served as a powerful analytical tool for studying molecular structure and dynamics in chemistry and biology. However, the processing of raw data acquired from NMR spectrometers and subsequent quantitative analysis involves various specialized tools, which necessitates comprehensive knowledge in programming and NMR. Particularly, the emerging deep learning tools is hard to be widely used in NMR due to the sophisticated setup of computation. Thus, NMR processing is not an easy task for chemist and biologists. In this work, we present CloudBrain-NMR, an intelligent online cloud computing platform designed for NMR data reading, processing, reconstruction, and quantitative analysis. The platform is conveniently accessed through a web browser, eliminating the need for any program installation on the user side. CloudBrain-NMR uses parallel computing with graphics processing units and central processing units, resulting in significantly shortened computation time. Furthermore, it incorporates state-of-the-art deep learning-based algorithms offering comprehensive functionalities that allow users to complete the entire processing procedure without relying on additional software. This platform has empowered NMR applications with advanced artificial intelligence processing. CloudBrain-NMR is openly accessible for free usage at https://csrc.xmu.edu.cn/CloudBrain.htmlComment: 11 pages, 13 figure

Role of glucose in the repair of cell membrane damage during squeeze distortion of erythrocytes in microfluidic capillaries

The rapid development of portable precision detection methods and the crisis of insufficient blood supply worldwide has led scientists to study mechanical visualization features beyond the biochemical properties of erythrocytes. Combined evaluation of currently known biochemical biomarkers and mechanical morphological biomarkers will become the mainstream of single-cell detection in the future. To explore the mechanical morphology of erythrocytes, a microfluidic capillary system was constructedin vitro, with flow velocity and glucose concentration as the main variables, and the morphology and ability of erythrocytes to recover from deformation as the main objects of analysis. We showed the mechanical distortion of erythrocytes under various experimental conditions. Our results showed that glucose plays important roles in improving the ability of erythrocytes to recover from deformation and in repairing the damage caused to the cell membrane during the repeated squeeze process. These protective effects were also confirmed inin vivoexperiments. Our results provide visual detection markers for single-cell chips and may be useful for future studies in cell aging

PO-304 Caffeine Supplementation Altered Metabolic Profiles in High-intensity Interval Training

Objective Caffeine supplementation is a commonly used nutritional practice. Exogenous metabolites from caffeine, such as paraxanthine, theobromine and theophylline, are eventually excreted through urine. Yet, it is less clear whether caffeine would induce endogenous metabolites altered during exercise. Urine metabolomics is non-invasive method, which mainly focus on alterations of endogenous metabolic profiles caused by diseases, drugs, and lifestyle and nutritional interventions as well. Therefore, the purpose of the present study was to examine the effects of supplementation with caffeine in a well-designed high intensity interval training (HITT). We identified significant alterations in urinary metabolite levels and revealed key metabolic pathways involved in caffeine supplementation in HITT. Methods We performed a randomized, double-blind, placebo- controlled crossover study. Twelve women basketball players (age:19.12 ± 2.64 years, mass: 174.73 ± 5.18 cm, height: 62 ± 5.09 kg, with 8.50±2.11 years training period for basketball) were randomized to placebo (PLA) or caffeine (CAF) with dosage of 3mg on the basis of body weight (kg) 45min before a field HITT test. The test was repeated after three days when players were crossed over to the alternate test. The test began with a 30 min warmup, followed by a high intensity intermittent exercise trail with incremental load for about 25min, and a cool-down. Players are familiar with the test program which included 55 sets of dribble shuttle-run, pass, shoot, and rebound with basketball with a distance of 1540m (55 × 28m), the interval between two sets was gradually reduced. Performance (completed time), heart rates immediate (HR0min) and 1 min (HR1min) after test, blood lactate (BLa), proteinuria and ratings of perceived exertion (RPE) were collected during each protocol. Urine samples were obtained before and 1 h after of the test. 1H-NMR spectra (Bruker AVANCE III HD 600MHz) were obtained and then processed by NMR spectra (MestReNova 9.0). The binning values of NMR spectra are imported into MATLAB, and the peaks are aligned with the icoshift algorithm. Then concentrations of the aligned metabolites were calculated by converting the integral area of proton signals with that of the TSP. Pattern recognition was performed to the processed NMR data, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Characteristic metabolites were identified that contribute most to the metabolic pattern between groups according to the OPLS-DA models. Finally, we analyzed the metabolic pathway by importing characteristic metabolites with concentrations into the Enrichment Analysis (MetaboAnalysis 3.0) to determine the metabolic pathways with the greatest disturbance related to caffeine during exercise. Moreover, the main effects of exercise, caffeine and the interaction between exercise and caffeine were determined by Repeated measure GLM analysis (Spss 22.0). Results (1) Compared with PLA, CAF had no significant difference in the completed time (25.9 min vs. 26.8 min). Repeated measured analysis showed that there was significant overall time effect on the routine training monitoring parameters, while no statistically group differences in HR0min, HR1min, BLa (199.02±21.36 vs.189.00±22.38 bpm; 148.02±12.60 vs.148.02±20.34 bpm, and 8.89±2.23 vs. 9.52±2.91 mmol/L, respectively). For the qualitative indexes, the positive rate of urine ketone bodies was increased, while RPE did not changed. (2) We identified 32 metabolites in urine sample. PCA showed distinct differentiation of metabolic patterns between each two groups in the four groups (PLAbefore, PLApost, CAFbefore, CAFafter). By using OPLS-DA, we found that the urine metabolic profiles were differences in between caffeine supplementation group and placebo group during the test. OPLS-DA revealed the identified metabolites of exercise and caffeine respectively, among them, lactate, butyric acid, isobutyric acid, 3-hydroxybutyric acid and pyruvic acid could be used as metabolic biomarkers in the HITT response. Supplementation of caffeine increased the production of fat metabolites in urine compared to the PLA. Enrichment analysis showed that the disturbed metabolic pathways shared by PLA and CAF were purine metabolism, glycolysis, insulin signal transduction, galactose metabolism, gluconeogenesis, glucose-alanine cycle, sphingolipid metabolism, alanine metabolism and citric acid cycle. Yet, when compared to the PLA, CAF enhanced fat metabolism and increased pyruvate metabolism, cysteine metabolism and mitochondrial electron transport. These results suggest that caffeine could promote fatty acid metabolism and amino acid metabolism to improve aerobic metabolism and to reduce oxidative stress, and thus promote exercise capacity. (3) Covariance analysis showed that there were significant individual-specific effects of caffeine supplementation. Conclusions Caffeine supplementation during HITT promoted the fat metabolism, and upregulated the TCA, pyruvate metabolism and mitochondrial electron transfer. It is suggested that caffeine could, to some extent, promote energy supply shift from anaerobic metabolic to an aerobic manner, and the enhancement of fat oxidation would be beneficial to glycogen storage for intensively long-duration exercise. Moreover, there are obvious individual differences in caffeine response on sports

Solution structural analysis of the single-domain parvulin TbPin1

10.1371/journal.pone.0043017PLoS ONE78

ONCache: A Cache-Based Low-Overhead Container Overlay Network

Recent years have witnessed a widespread adoption of containers. While containers simplify and accelerate application development, existing container network technologies either incur significant overhead, which hurts performance for distributed applications, or lose flexibility or compatibility, which hinders the widespread deployment in production. We design and implement ONCache (\textbf{O}verlay \textbf{N}etwork \textbf{Cache}), a cache-based container overlay network, to eliminate the overhead while keeping flexibility and compatibility. We carefully analyze the difference between an overlay network and a host network, and find that an overlay network incurs extra packet processing, including encapsulating, intra-host routing, namespace traversing and packet filtering. Fortunately, the extra processing exhibits an \emph{invariance property}, e.g., most packets of the same flow have the same processing results. This property motivates us to cache the extra processing results. With the proposed cache, ONCache significantly reduces the extra overhead while maintaining the same flexibility and compatibility as standard overlay networks. We implement ONCache using eBPF with only 524 lines of code, and deploy ONCache as a plugin of Antrea. With ONCache, container communication achieves similar performance as host communication. Compared to the standard overlay network, ONCache improves the throughput and request-response transaction rate by 12\% and 36\% for TCP (20\% and 34\% for UDP), while significant reduces per-packet CPU overhead. Many distributed applications also benefit from ONCache