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BackgroundThe purpose of this study is to assess the effectiveness of methylprednisolone in severe COVID-19.MethodsPubMed, the Cochrane Library and Web of Science were searched for literatures comparing methylprednisolone and control treatment in severe COVID-19 patients. Statistical pooling was reported as risk ratio (RR) with corresponding 95% confidence interval (CI). The outcomes of interest in the literature survey were mortality and adverse events.ResultsA total of 13 studies were included, including 3,138 patients with severe COVID-19, of which 1,634 patients were treated with methylprednisolone and 1,504 patients were treated with control treatment. Five of the 13 studies reported severe adverse events. Our meta-analysis indicates that methylprednisolone treatment in COVID-19 patients is associated with a significant reduction in mortality (RR 0.62, 95% CI 0.46–0.85, p = 0.003) compared to control treatment, without an increased risk of adverse events (RR 1.20, 95% CI 0.92–1.56, p = 0.17). Moreover, high-dose methylprednisolone treatment (RR 0.57; 95% CI 0.40–0.82, p = 0.003) and short-course methylprednisolone treatment (RR 0.54; 95% CI 0.38–0.89, p = 0.01) found to significantly reduce mortality. Additionally, it was found that younger severe COVID-19 patients (RR 0.40; 95% CI 0.20–0.80, p = 0.01) had better outcomes to methylprednisolone than older patients.ConclusionMethylprednisolone was correlated with lower mortality compared with control treatment in severe COVID-19 patients without increasing serious adverse reactions. Furthermore, high-doses and short-term of methylprednisolone treatment were linked with better younger COVID-19 reported higher benefit from methylprednisolone than older COVID-19 patients.

Atherosclerosis, formed by fibrofatty lesions in the artery wall, underpins myocardial infarctions, strokes and disabling peripheral artery diseases. Inflammation with multiple maladaptive roles runs through atherosclerotic inception, propagation, and complications. Given degree of inflammation differing among atherosclerotics, inflammation-targeted nanomedicine may produce individualized monitoring and manipulation of inflammatory regulators beyond traditionally slowing down atherosclerosis progression. Equipped with biomimetic membrane, microenvironment-responsive and targeting structures, nanomedicines could escape from the innate immune system and autonomously navigate to targeted lesions, thereby muting inflammation in atherosclerotic sites. Moreover, nanoparticles’ advantages go beyond advancing pharmacology. The optimal physicochemical properties of nanoparticles favor noninvasive imaging function to provide diagnostic and prognostic information of atherosclerotic plaques. Despite efficacious ability of the preclinical anti-inflammation nanotherapeutics to reduce atherosclerotic risks, future translation of inflammation-targeted nanomedicines requires to comprehensively refine the strategies that the nanomedicines forestall inflammatory pathways via systemic exposure, drug-cell interactions, and endothelial barrier reconstruction. In this review, we outline the development of diverse nanomedicines to specifically identify pathophysiological changes and combat advanced atherosclerosis along with dynamically tracing inflammatory markers. Finally, challenges and opportunities of inflammation-targeted nanomedicines are highlighted to pave avenues toward personalized medicine for atherosclerosis to stem the growing global burden of cardiovascular diseases.

Abstract Skeletal muscle atrophy is a common clinical feature of many acute and chronic conditions. Circular RNAs (circRNAs) are covalently closed RNA transcripts that are involved in various physiological and pathological processes, but their role in muscle atrophy remains unknown. Global circRNA expression profiling indicated that circRNAs are involved in the pathophysiological processes of muscle atrophy. circTmeff1 is identified as a potential circRNA candidate that influences muscle atrophy. It is further identified that circTmeff1 is highly expressed in multiple types of muscle atrophy in vivo and in vitro. Moreover, the overexpression of circTmeff1 triggers muscle atrophy in vitro and in vivo, while the knockdown of circTmeff1 expression rescues muscle atrophy in vitro and in vivo. In particular, the knockdown of circTmeff1 expression partially rescues muscle mass in mice during established atrophic settings. Mechanistically, circTmeff1 directly interacts with TAR DNA‐binding protein 43 (TDP‐43) and promotes aggregation of TDP‐43 in mitochondria, which triggers the release of mitochondrial DNA (mtDNA) into cytosol and activation of the cyclic GMP‐AMP synthase (cGAS)/ stimulator of interferon genes (STING) pathway. Unexpectedly, TMEFF1‐339aa is identified as a novel protein encoded by circTmeff1 that mediates its pro‐atrophic effects. Collectively, the inhibition of circTmeff1 represents a novel therapeutic approach for multiple types of skeletal muscle atrophy.

Abstract Muscle atrophy is a frequently observed complication, characterized by the loss of muscle mass and strength, which diminishes the quality of life and survival. No effective therapy except exercise is currently available. In our previous study, repressing miR-29b has been shown to reduce muscle atrophy. In our current study, we have constructed artificially engineered extracellular vesicles for the delivery of CRISPR/Cas9 to target miR-29b (EVs-Cas9-29b). EVs-Cas9-29b has shown a favorable functional effect with respect to miR-29b repression in a specific and rapid manner by gene editing. In in vitro conditions, EVs-Cas9-29b could protect against muscle atrophy induced by dexamethasone (Dex), angiotensin II (AngII), and tumor necrosis factor-alpha (TNF-α). And EVs-Cas9-29b introduced in vivo preserved muscle function in the well-established immobilization and denervation-induced muscle atrophy mice model. Our work demonstrates an engineered extracellular vesicles delivery of the miR-29b editing system, which could be potentially used for muscle atrophy therapy.

Background Leymus secalinus is a pioneer plant grown in the Zoige desertified alpine grassland and it is also one of the dominant plant species used for environmental remediation. L. secalinus plays a large role in vegetation reconstruction in sandy land, but the abundance and diversity of its endophytes have not yet been investigated. Objectives This study was performed to investigate the changes in the endophytic bacterial community structure of L. secalinus under different ecological environments and to analyze the effects of environmental changes and different plant tissues on the L. secalinus endophytic bacteria. Methods Leaf, stem, and root tissue samples of L. secalinus were collected from Zoige Glassland (Alpine sandy land) and an open field nursery (Control). DNA was extracted and the 16S ribosomal DNA was amplified. The sequence library was sequenced on an Illumina MiSeq platform and clustered by operational taxonomic units (OTUs). α-diversity and β-diversity analyses, species diversity analyses, functional prediction, and redundancy (RDA) analyses for the soil physicochemical properties were conducted. Results α-diversity and β-diversity analyses showed that the endophytic bacteria in L. secalinus varied in different areas and tissues. The abundance of Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium, which is related to nitrogen fixation, increased significantly in the L. secalinus found in the Zoige Grassland. Moreover, the abundance of nutrition metabolism and anti-stress abilities increased in functional prediction in the desert samples. The soil physicochemical properties had an insignificant influence on bacterial diversity. Conclusion The changes in the endophytic bacterial community structure in L. secalinus were significant and were caused by environmental alterations and plant choice. The endophytic bacteria in L. secalinus grown in alpine sandy land may have greater anti-stress properties and the ability to fix nitrogen, which has potential value in environmental remediation and agricultural production.

The genus Dendronereis Peters, 1854 is characterized in the polychaete family Nereididae by its feather-shaped branchiae on the anterior segments. In this study, we present the first complete mitogenome of Dendronereis, represented by D. chipolini Hsueh, , collected from Beibu Gulf, China. The nucleotide composition is biased toward A + T nucleotides, accounting 31.5% for A, 22.3% for C, 14.7% for G and 31.5% for T. The assembled mitogenome is 15,763 bp in length, with a typical set of 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA), 2 ribosomal RNA (rRNA), and 1 non-coding control region. All genes are encoded on H-strand. The control region is 1260 bp in length and located between tRNA-Gly and tRNA-Met. Phylogenetic study showed that D. chipolini is arranged with high support into the clade of Namanereidinae. The complete mitogenome provides important molecular data for investigating the phylogeny and evolution of the nereid animals.

Summary: Background: Pathological cardiac hypertrophy occurs in response to numerous stimuli and precedes heart failure (HF). Therapies that ameliorate pathological cardiac hypertrophy are highly needed. Methods: The expression level of miR-30d was analyzed in hypertrophy models and serum of patients with chronic heart failure by qRT-PCR. Gain and loss-of-function experiments of miR-30d were performed in vitro. miR-30d gain of function were performed in vivo. Bioinformatics, western blot, luciferase assay, qRT-PCR, and immunofluorescence were performed to examine the molecular mechanisms of miR-30d. Findings: miR-30d was decreased in both murine and neonatal rat cardiomyocytes (NRCMs) models of hypertrophy. miR-30d overexpression ameliorated phenylephrine (PE) and angiotensin II (Ang II) induced hypertrophy in NRCMs, whereas the opposite phenotype was observed when miR-30d was downregulated. Consistently, the miR-30d transgenic rat was found to protect against isoproterenol (ISO)-induced pathological hypertrophy. Mechanistically, methyltransferase EZH2 could promote H3K27me3 methylation in the promotor region of miR-30d and suppress its expression during the pathological cardiac hypertrophy. miR-30d prevented pathological cardiac hypertrophy via negatively regulating its target genes MAP4K4 and GRP78 and inhibiting pro-hypertrophic nuclear factor of activated T cells (NFAT). Adeno-associated virus (AAV) serotype 9 mediated-miR-30d overexpression exhibited beneficial effects in murine hypertrophic model. Notably, miR-30d was reduced in serum of patients with chronic heart failure and miR-30d overexpression could significantly ameliorate pathological hypertrophy in human embryonic stem cell-derived cardiomyocytes. Interpretation: Overexpression of miR-30d may be a potential approach to treat pathological cardiac hypertrophy. Funding: This work was supported by the grants from National Key Research and Development Project (2018YFE0113500 to J Xiao), National Natural Science Foundation of China (82020108002 to J Xiao, 81900359 to J Li), the grant from Science and Technology Commission of Shanghai Municipality (20DZ2255400 and 21XD1421300 to J Xiao, 22010500200 to J Li), Shanghai Sailing Program (19YF1416400 to J Li), the “Dawn” Program of Shanghai Education Commission (19SG34 to J Xiao), the “Chen Guang” project supported by the Shanghai Municipal Education Commission and Shanghai Education Development Foundation (19CG45 to J Li).

Labanotation is one of the well-known notation systems for the documenting and archiving of human motion. It plays a powerful role in dance protection, choreography analysis, and so on. Recently, researchers are committed to using computer technology to automatically generate Labanotation rather than manually drawing. However, the existing generation methods cannot deal with the various changes in motion data, such as different scales, angles, motion modes and limbs. In this paper, we aim to generate Labanotation from motion capture data acquired through real folk dance performances. The main steps include feature extraction, motion segmentation and unit movement analysis. Firstly, a normalized feature named Lie group feature is extracted, which can cope with the challenges of different scales and angles in motion data. Secondly, in order to divide motion with different modes into unit fragments for further recognizing, we propose a segmentation method that combines the speed threshold and the region partition. Thirdly, to generate Laban symbols of unit movements for different limbs, two kinds of neural networks are used for the analysis. On the one hand, LieNet, a powerful network for analyzing time series data based on Lie group structure, is utilized to recognize the lower limb movements. On the other hand, extreme-learning machine, a single hidden layer feedforward neural network, is used to identify the upper limb postures. Experimental results demonstrate that our method of feature extraction, motion segmentation and unit movement analysis achieves better results than the previous works, which makes the generated Labanotation score more reliable.

Owing to the accuracy and flexibility, mobile advertising has become a very attractive marketing method based on smart mobile terminals. The more common mobile advertisement distribution methods are based on location and content. But most of them donart take into account the limited duration time of mobile users and the timeliness of advertising, which makes mobile advertisement distribution suffer from low propagation efficiency. To make up for this deficiency, we propose the advertisement platformars expected income maximization problem (EIMP), and prove its NP-hardness. As far as we know, EIMP is a combination of the 0–1 multi-dimensional and multiple knapsack problem, which is even harder. In dealing with this difficulty, we fortunately find that this problem could be transformed into a maximizing monotone submodular set function, which is subject to partition matroid constraints. Then we propose a simple but effective greedy algorithm TIMAO (Time-sensitive Mobile Advertisement Offloading) which has a constant approximation ratio of 1/3 to provide a performance guarantee for this issue. Finally, extensive evaluations are conducted. The results show that compared with the random selection method, TIMAO increases the expected income of the platform by about two times. And it achieves 99.2% of the near optimal results obtained by the CPLEX tool-box. Moreover, we propose an important metric, the duty cycle, to evaluate system performance in time domain. The results show that our scheme could increase the time duty cycle by about average 10% compared with the random selection.

Wireless energy transfer technologies have played an important role in the development of Internet of Things. Most of the previous studies focus on scheduling mobile chargers efficiently for rechargeable sensor nodes. In this paper, we investigate the deployment problem for wireless charging stations (WCSs) in urban areas with respect to the users detouring cost when they move to the candidate WCSs. With pre-known user's trajectories and given number of WCSs, we deploy the WCSs to maximize the number of recharged users with guaranteed probability. We convert our deployment problem into an NP-hard weighted maximum coverage problem, and prove the objective function is a maximum submodular set function. To this end, a simple but efficient greedy algorithm with approximation factor of (1 - 1/ε) is proposed for the threshold detouring mode. In addition, an improved algorithm with an approximation factor of (1 - 1/√e) is presented for the linear/nonlinear detouring mode. Finally, we evaluate the performance of our algorithms by comparing them with two typical heuristic algorithms (flow-centric and random-based), and the impacts of different detouring thresholds on our algorithms by synthetic traces. Moreover, real trace-driven evaluations validate that our algorithm improves the coverage quality by 75% when compared to the two aforementioned algorithms.

We investigate how to leverage limited local information for mobile advertisement popularization, where users are motivated to propagate advertisements with rewards or credits distributed from a centralized platform. Previous solutions on social networks failed to be applicable for mobile advertisement propagation because of the mobility, which would lead to extremely high overhead and low propagation efficiency. Participants need to be selected carefully and efficiently in dealing with the highly dynamic network and uncertain contacts among users. Even worse, the propagation effects are difficult to quantify with the increased number of mobile users. In tackling these difficulties, we propose αMAP (α here means efficient mobile advertisement popularization with local information), a lightweight but effective propagation user selection scheme with local information. Two key technologies inspire us to achieve efficient and effective mobile advertisement propagation. First, we advocate propagation effects instead of influence for user selection, where mobile users with strong information dissemination ability could be selected. Second, we use local information instead of the global information to achieve near optimal performance for propagation. In our proposed scheme, the information potentials proposed by Loukas et al. are leveraged to find the influential users with local information. With extensive experimental study, we find that αMAP could effectively improve the mobile advertisements delivery ratio. Using the propagation instead of popularization is validated with different aspects of investigations when the budget is constrained. To evaluate the impact of mobility, we leverage the mobile trace data set for comprehensive evaluations. αMAP performs fairly well when more realistic experimental settings are incorporated.

In recent years, Innovative Schools in Dali have received increasing coverage in Chinese social media and have also attracted middle-class parents from cities, as viable bottom-up educational initiatives. This paper explores the rationales for Chinese middle-class parents' choice of Innovative Schools in Dali. Analysis of data from online interviews with 33 parents from seven Innovative Schools in Dali revealed three types of narratives parents provided in explaining their alternative school choices: investors, escapees, and idealists. The narratives reflect different ways in which parents negotiate their relationship with mainstream education and Innovative Schools, how they define the "educational goods" they would like to pursue and how they deal with potential tensions within their practice. We then situate the phenomenon within the Chinese educational landscape and discuss its social implications in light of social reproduction theories.