Beta2-microglobulin (B2M) a key component of major histocompatibility complex class I molecules, which aid cytotoxic T-lymphocyte (CTL) immune response. However, the majority of studies of B2M have ...focused only on amyloid fibrils in pathogenesis to the neglect of its role of antimicrobial activity. Indeed, B2M also plays an important role in innate defense and does not only function as an adjuvant for CTL response. A previous study discovered that human aggregated B2M binds the surface protein structure in Streptococci, and a similar study revealed that sB2M-9, derived from native B2M, functions as an antibacterial chemokine that binds Staphylococcus aureus. An investigation of sB2M-9 exhibiting an early lymphocyte recruitment in the human respiratory epithelium with bacterial challenge may uncover previously unrecognized aspects of B2M in the body’s innate defense against Mycobactrium tuberculosis. B2M possesses antimicrobial activity that operates primarily under pH-dependent acidic conditions at which B2M and fragmented B2M may become a nucleus seed that triggers self-aggregation into distinct states, such as oligomers and amyloid fibrils. Modified B2M can act as an antimicrobial peptide (AMP) against a wide range of microbes. Specifically, these AMPs disrupt microbe membranes, a feature similar to that of amyloid fibril mediated cytotoxicity toward eukaryotes. This study investigated two similar but nonidentical effects of B2M: the physiological role of B2M, in which it potentially acts against microbes in innate defense and the role of B2M in amyloid fibrils, in which it disrupts the membrane of pathological cells. Moreover, we explored the pH-governing antibacterial activity of B2M and acidic pH mediated B2M amyloid fibrils underlying such cytotoxicity.
Fluorescent nanodiamond is a new nanomaterial that possesses several useful properties, including good biocompatibility, excellent photostability and facile surface functionalizability. Moreover, ...when excited by a laser, defect centres within the nanodiamond emit photons that are capable of penetrating tissue, making them well suited for biological imaging applications. Here, we show that bright fluorescent nanodiamonds can be produced in large quantities by irradiating synthetic diamond nanocrystallites with helium ions. The fluorescence is sufficiently bright and stable to allow three-dimensional tracking of a single particle within the cell by means of either one- or two-photon-excited fluorescence microscopy. The excellent photophysical characteristics are maintained for particles as small as 25 nm, suggesting that fluorescent nanodiamond is an ideal probe for long-term tracking and imaging in vivo, with good temporal and spatial resolution.
In this paper, a recently new semi-analytical method, i.e., He's variational iteration method is developed to apply to free vibration analysis of conveying fluid pipe. The critical flow velocity and ...frequency of pipe conveying fluid are obtained with considering the various boundary conditions. The results are compared with the ones of different transform method, and prove VIM that has the same precision and efficient with DTM. The mode shapes of cantilevered pipe and both ends with elastic support pipe are shown under different flow velocity.
The excellent molecular recognition capabilities of monoclonal antibodies (mAbs) have opened up exciting opportunities for biotherapeutic discovery. Taking advantage of the full potential of this ...tool necessitates affinity ligands capable of conjugating directly with small molecules to a defined degree of biorthogonality, especially when modifying natural Abs. Herein, a bioorthogonal boronate‐affinity‐based Ab ligand featuring a 4‐(dimethylamino)pyridine and an S‐aryl thioester to label full‐length Abs is reported. The photoactivatable linker in the acyl donor facilitated purification of azide‐labelled Ab (N3‐Ab) was quantitatively cleaved upon brief exposure to UV light while retaining the original Ab activity. Click reactions enabled the precise addition of biotin, a fluorophore, and a pharmacological agent to the purified N3‐Abs. The resulting immunoconjugate showed selectivity against targeted cells. Bioorthogonal traceless design and reagentless purification allow this strategy to be a powerful tool to engineer native antibodies amenable to therapeutic intervention.
Adding function: A boronate‐affinity ligand and an S‐aryl thioester have been developed that are capable of labelling native Abs with a functional molecule. Additionally, a photoactivatable crosslinker allows purification of labelled Abs in a reagentless manner, thereby producing homogeneous Ab‐drug conjugates.
We present a novel domain adaptation approach for solving cross-domain pattern recognition problems, i.e., the data or features to be processed and recognized are collected from different domains of ...interest. Inspired by canonical correlation analysis (CCA), we utilize the derived correlation subspace as a joint representation for associating data across different domains, and we advance reduced kernel techniques for kernel CCA (KCCA) if nonlinear correlation subspace are desirable. Such techniques not only makes KCCA computationally more efficient, potential over-fitting problems can be alleviated as well. Instead of directly performing recognition in the derived CCA subspace (as prior CCA-based domain adaptation methods did), we advocate the exploitation of domain transfer ability in this subspace, in which each dimension has a unique capability in associating cross-domain data. In particular, we propose a novel support vector machine (SVM) with a correlation regularizer, named correlation-transfer SVM, which incorporates the domain adaptation ability into classifier design for cross-domain recognition. We show that our proposed domain adaptation and classification approach can be successfully applied to a variety of cross-domain recognition tasks such as cross-view action recognition, handwritten digit recognition with different features, and image-to-text or text-to-image classification. From our empirical results, we verify that our proposed method outperforms state-of-the-art domain adaptation approaches in terms of recognition performance.
SUMMARY
As an alternative to the moment tensor (MT) model for earthquake sources, the shear-tensile-compressive (STC) model offers a kinematic description of the source mechanism and leads to a more ...robust inversion problem. However, the premise of the source inversion based on STC is to ensure the accuracy of parameter $\kappa $ defined as the ratio of the Lamé constants, $\kappa $=$\lambda /\mu $, in a fault zone. In this study, we carry out a series of synthetic experiments using P-wave amplitudes in source mechanism inversions based on both the STC and MT models, and consider the influence of noise, the uncertainties in source locations and in the velocity model. We show that the nonlinear STC inversion with an appropriate value of $\kappa $ leads to more accurate result compared to the linear MT inversion. We also propose a new joint-STC inversion method to jointly invert for parameter $\kappa $ and the remaining parameters of the STC model (magnitude and the strike, dip, rake and slope angles). The results indicate that our proposed method yields robust results for both the parameter $\kappa $ and focal mechanisms. We apply our joint-STC inversion method to field microearthquake data observed in the West Bohemia region to validate some of the conclusions drawn from the synthetic experiments.
Deep learning technology has been widely used in various field in recent years. This study intends to use deep learning algorithms to analyze the aeroelastic phenomenon and compare the differences ...between Deep Neural Network (DNN) and Long Short-term Memory (LSTM) applied on the flutter speed prediction. In this present work, DNN and LSTM are used to address complex aeroelastic systems by superimposing multi-layer Artificial Neural Network. Under such an architecture, the neurons in neural network can extract features from various flight data. Instead of time-consuming high-fidelity computational fluid dynamics (CFD) method, this study uses the K method to build the aeroelastic flutter speed big data for different flight conditions. The flutter speeds for various flight conditions are predicted by the deep learning methods and verified by the K method. The detailed physical meaning of aerodynamics and aeroelasticity of the prediction results are studied. The LSTM model has a cyclic architecture, which enables it to store information and update it with the latest information at the same time. Although the training of the model is more time-consuming than DNN, this method can increase the memory space. The results of this work show that the LSTM model established in this study can provide more accurate flutter speed prediction than the DNN algorithm.
•The LCPCP has significantly reduced the carbon intensity of pilot cities.•Secondary-industry-heavy locations reduced carbon more effectively.•The LCPCP achieved carbon emission reductions through ...technological innovation.•The mechanism of technological innovation was mainly concentrated in the eastern region.•Our findings assist policymakers create better climate governance and low-carbon economic development.
The low-carbon pilot cities policy (LCPCP) aims to stimulate economic growth and ensure the attainment of greenhouse gas emission reduction targets to address climate change. China issued the LCPCP in 2010 and steadily expanded the size of its pilot zones. This study builds a quasi-natural experiment based on China's LCPCP and a difference-in-difference model employing urban carbon intensity data over a 10-year period beginning in 2007 to examine the implementation repercussions of the LCPCP. According to the findings, the LCPCP has significantly reduced the carbon intensity of pilot cities. Additionally, an analysis of heterogeneity suggests that the LCPCP is more prevalent in regions with higher concentrations of secondary industries. Moreover, the mechanism reveals that the decarbonization program reduces carbon intensity through technological innovation, particularly in eastern China. In conclusion, our findings provide strong support for the operation and promotion of China's LCPCP as well as guidance and support for China's goal of reducing carbon emissions.
Climate change is one of the most important global problems faced by the international community. It is generally believed that increasing the consumption of renewable energy is an effective measure ...to promote CO2 emissions reduction. Therefore, renewable energy consumption has become one of the best alternative strategies for sustainable development. Based on this, this paper employs the 3SLS model to conduct an empirical study on the relations among real output, renewable energy consumption, and CO2 emissions of BRICS countries (except Russia) in 1999–2014. The empirical results support, for BRICS group, the complete tri-variate relationships (energy-output-emission nexus), and renewable energy had a significant positive impact on the real output, and vice versa. Besides, compared with other countries, Brazil also has the same tri-variate relationships as BRICS group. However, China has no relationship from real output to renewable energy consumption and from real output to CO2 emissions; India does not have the relationship from real output to renewable energy consumption and the bilateral relationship between real output and CO2 emissions; the relationship between variables in South Africa only occurs in the energy output chain. Finally, according to the estimation results of the simultaneous equation, the BRICs governments should consider the importance of human capital level and financial development when controlling the real output level and pollution. In addition, it should be noted that effective energy policies help to reduce carbon dioxide emissions without compromising real output.
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