The clinical features and immune responses of asymptomatic individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have not been well described. We studied 37 ...asymptomatic individuals in the Wanzhou District who were diagnosed with RT-PCR-confirmed SARS-CoV-2 infections but without any relevant clinical symptoms in the preceding 14 d and during hospitalization. Asymptomatic individuals were admitted to the government-designated Wanzhou People's Hospital for centralized isolation in accordance with policy
. The median duration of viral shedding in the asymptomatic group was 19 d (interquartile range (IQR), 15-26 d). The asymptomatic group had a significantly longer duration of viral shedding than the symptomatic group (log-rank P = 0.028). The virus-specific IgG levels in the asymptomatic group (median S/CO, 3.4; IQR, 1.6-10.7) were significantly lower (P = 0.005) relative to the symptomatic group (median S/CO, 20.5; IQR, 5.8-38.2) in the acute phase. Of asymptomatic individuals, 93.3% (28/30) and 81.1% (30/37) had reduction in IgG and neutralizing antibody levels, respectively, during the early convalescent phase, as compared to 96.8% (30/31) and 62.2% (23/37) of symptomatic patients. Forty percent of asymptomatic individuals became seronegative and 12.9% of the symptomatic group became negative for IgG in the early convalescent phase. In addition, asymptomatic individuals exhibited lower levels of 18 pro- and anti-inflammatory cytokines. These data suggest that asymptomatic individuals had a weaker immune response to SARS-CoV-2 infection. The reduction in IgG and neutralizing antibody levels in the early convalescent phase might have implications for immunity strategy and serological surveys.
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FZAB, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Why investment and financial reform are essential to China's continued economic well-being Although China's economy has grown spectacularly over the last twenty-five years, economists disagree about ...how the Chinese economy is likely to fare in the short- and long-term future. Is China's growth sustainable, or has China relied too much on investment, which is subject to diminishing returns, and not enough on technological change? The first book on the relation between investment, finance, and growth in China, How China Grows dismisses this concern. James Riedel, Jing Jin, and Jian Gao argue that investment has not only been the engine of growth, but also the main source of technological progress and structural change in China.What threatens future growth instead, the authors argue, are the weaknesses of China's financial system that undermine efficiency in investment allocation. Financial-sector reform and development are necessary, not only for sustaining long-term growth, but also for maintaining macroeconomic stability.Although it includes some technical economic analysis, How China Grows is accessible to noneconomists and will benefit anyone who is interested in development finance in general and in China's economic growth in particular—whether economists, political scientists, bankers, or business people.
Purpose
Cancer, a major public health problem, exhibits significant redox alteration. Thioredoxin (Trx) system, including Trx and Trx reductase (TrxR), as well as Trx-interacting protein (TXNIP) play ...important roles in controlling the cellular redox balance in cancer cells. In most cancers, Trx and TrxR are usually overexpressed and TXNIP is underexpressed. In recent years, some agents targeting Trx, TrxR, and TXNIP were used to explore a therapy approach for cancer patients.
Methods
A systematic search of PMC and the PubMed Database was conducted to summarize the potential of Trx system inhibitors for cancer treatment.
Results
In this article, we first summarize the functions of Trx, TrxR, and TXNIP in cancers. We also review some small molecule inhibitors of Trx/TrxR and
d
-allose (TXNIP inducer) and discuss their antitumor mechanisms. We highlight the combined inhibition of Trx system and GSH system in cancer therapy. We expect that a highly specific and selective antitumor agent with no cytotoxicity on human normal cells could be developed in the future.
Conclusion
In conclusion, Trx system may be very promising for clinical therapy of cancer in the future.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Parkinson disease (PD) is the second most common neurodegenerative movement disorder. Pharmacological animal models are invaluable tools to study the pathological mechanisms of PD. Currently, ...invertebrate and vertebrate animal models have been developed by using several main neurotoxins, such as 6-hydroxydopamine, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, paraquat, and rotenone. These models achieve to some extent to reproduce the key features of PD, including motor defects, progressive loss of dopaminergic neurons in substantia nigra pars compacta, and the formation of Lewy bodies. In this review, we will highlight the pathogenic mechanisms of those neurotoxins and summarize different neurotoxic animal models with the hope to help researchers choose among them accurately and to promote the development of modeling PD.
Nanoparticles (NPs) have been increasingly studied for radiosensitization. The principle of NPs radio-enhancement is to use high-atomic number NPs (e.g. gold, hafnium, bismuth and gadolinium) or ...deliver radiosensitizing substances, such as cisplatin and selenium. Nowadays, cancer immunotherapy is emerged as a promising treatment and immune checkpoint regulation has a potential property to improve clinical outcomes in cancer immunotherapy. Furthermore, NPs have been served as an ideal platform for immunomodulator system delivery. Owing to enhanced permeability and retention (EPR) effect, modified-NPs increase the targeting and retention of antibodies in target cells. The purpose of this review is to highlight the latest progress of nanotechnology in radiotherapy (RT) and immunotherapy, as well as combining these three strategies in cancer treatment. Overall, nanomedicine as an effective strategy for RT can significantly enhance the outcome of immunotherapy response and might be beneficial for clinical transformation.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Effective common spatial pattern (CSP) feature extraction for motor imagery (MI) electroencephalogram (EEG) recordings usually depends on the filter band selection to a large extent. Subband ...optimization has been suggested to enhance classification accuracy of MI. Accordingly, this study introduces a new method that implements sparse Bayesian learning of frequency bands (named SBLFB) from EEG for MI classification. CSP features are extracted on a set of signals that are generated by a filter bank with multiple overlapping subbands from raw EEG data. Sparse Bayesian learning is then exploited to implement selection of significant features with a linear discriminant criterion for classification. The effectiveness of SBLFB is demonstrated on the BCI Competition IV IIb dataset, in comparison with several other competing methods. Experimental results indicate that the SBLFB method is promising for development of an effective classifier to improve MI classification.
Multiple sclerosis (MS) lesions that do not resolve in the months after they form harbour ongoing demyelination and axon degeneration, and are identifiable in vivo by their paramagnetic rims on MRI ...scans
. Here, to define mechanisms underlying this disabling, progressive neurodegenerative state
and foster development of new therapeutic agents, we used MRI-informed single-nucleus RNA sequencing to profile the edge of demyelinated white matter lesions at various stages of inflammation. We uncovered notable glial and immune cell diversity, especially at the chronically inflamed lesion edge. We define 'microglia inflamed in MS' (MIMS) and 'astrocytes inflamed in MS', glial phenotypes that demonstrate neurodegenerative programming. The MIMS transcriptional profile overlaps with that of microglia in other neurodegenerative diseases, suggesting that primary and secondary neurodegeneration share common mechanisms and could benefit from similar therapeutic approaches. We identify complement component 1q (C1q) as a critical mediator of MIMS activation, validated immunohistochemically in MS tissue, genetically by microglia-specific C1q ablation in mice with experimental autoimmune encephalomyelitis, and therapeutically by treating chronic experimental autoimmune encephalomyelitis with C1q blockade. C1q inhibition is a potential therapeutic avenue to address chronic white matter inflammation, which could be monitored by longitudinal assessment of its dynamic biomarker, paramagnetic rim lesions, using advanced MRI methods.
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GEOZS, IJS, IMTLJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZAGLJ
Regularization has been one of the most popular approaches to prevent overfitting in electroencephalogram (EEG) classification of brain-computer interfaces (BCIs). The effectiveness of regularization ...is often highly dependent on the selection of regularization parameters that are typically determined by cross-validation (CV). However, the CV imposes two main limitations on BCIs: 1) a large amount of training data is required from the user and 2) it takes a relatively long time to calibrate the classifier. These limitations substantially deteriorate the system's practicability and may cause a user to be reluctant to use BCIs. In this paper, we introduce a sparse Bayesian method by exploiting Laplace priors, namely, SBLaplace, for EEG classification. A sparse discriminant vector is learned with a Laplace prior in a hierarchical fashion under a Bayesian evidence framework. All required model parameters are automatically estimated from training data without the need of CV. Extensive comparisons are carried out between the SBLaplace algorithm and several other competing methods based on two EEG data sets. The experimental results demonstrate that the SBLaplace algorithm achieves better overall performance than the competing algorithms for EEG classification.
•Multi-kernel extreme learning machine based method is proposed for EEG classification.•Supplementary information from different kernels are integrated for better accuracy.•Extensive experimental ...comparison confirms superiority of the proposed method.
One of the most important issues for the development of a motor-imagery based brain-computer interface (BCI) is how to design a powerful classifier with strong generalization capability. Extreme learning machine (ELM) has recently proven to be comparable or more efficient than support vector machine for many pattern recognition problems. In this study, we propose a multi-kernel ELM (MKELM)-based method for motor imagery electroencephalogram (EEG) classification. The kernel extension of ELM provides an elegant way to circumvent calculation of the hidden layer outputs and inherently encode it in a kernel matrix. We investigate effects of two different kernel functions (i.e., Gaussian kernel and polynomial kernel) on the performance of kernel ELM. The MKELM method is subsequently developed by integrating these two types of kernels with a multi-kernel learning strategy, which can effectively explore the supplementary information from multiple nonlinear feature spaces for more robust classification of EEG. An extensive experimental comparison with two public EEG datasets indicates that the MKELM method gives higher classification accuracy than those of the other competing algorithms. The experimental results confirm that superiority of the proposed MKELM-based method for accurate classification of EEG associated with motor imagery in BCI applications. Our method also provides a promising and generalized solution to investigate the complex and nonlinear information for various applications in the fields of expert and intelligent systems.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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Introduction
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Neurodegeneration and neurofibrillary degeneration in Alzheimer's disease brains
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Dysfunction of protein synthesis mediated by mTOR‐dependent signalling in Alzheimer's disease ...brains
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Neurodegeneration mediated by mTOR‐dependent signalling
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Tau phosphorylation mediated by mTOR‐dependent signalling
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mTOR‐dependent signalling in lymphocytes of AD: potential biomarkers for AD diagnosis
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mTOR‐dependent signalling and other neurodegenerative diseases
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Perspectives
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Conclusions
Neurodegeneration and neurofibrillary degeneration are the two main pathological mechanisms of cognitive impairments in Alzheimer's disease (AD). It is not clear what factors determine the fates of neurons during the progress of the disease. Emerging evidence has suggested that mTOR‐dependent signalling is involved in the two types of degeneration in AD brains. This review focuses on the roles of mTOR‐dependent signalling in the pathogenesis of AD. It summarizes the recent advancements in the understanding of its roles in neu‐rodegeneration and neurofibrillary degeneration, as well as the evidence achieved when mTOR‐related signalling components were tested as potential biomarkers of cognitive impairments in the clinical diagnosis of AD.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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