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The outbreak of COVID-19 in December 2019 sent tens of thousands of people into panic; For sudden outbreak, due to the variability and immune virus, in view of the research and development will be to contain virus vaccine, so the country should not only possess strong vaccine research and development team and scientific research ability, and more need a kind of epidemic development simulation platform, the simulationof the real effective epidemic trends, provide high quality data for prevention and research department reference value; In this paper, the minimum deviation is sought through Logistics prediction model to improve the reliability and authenticity of epidemic simulation and prediction data. Real-time communication is completed by combining big data technology Spark training model and Kafka, and the simple and intuitive H5 realistic visual interface is adopted.

The application of rapid and accurate diagnostic methods can improve colorectal cancer (CRC) survival rates dramatically. Here, we used a non-targeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry (iEESI-MS) to detect metabolite ions associated with the progression of CRC from 172 tissues (45 stage I/II CRC, 41 stage III/IV CRC, and 86 well-matched normal tissues). A support vector machine (SVM) model based on 10 differential metabolite ions for differentiating early-stage CRC from normal tissues was built with a good prediction accuracy of 92.6%. The biomarker panel consisting of lysophosphatidylcholine (LPC) (18:0) has good diagnostic potential in differentiating early-stage CRC from advanced-stage CRC. We showed that the down-regulation of LPC (18:0) in tumor tissues is associated with CRC progression and related to the regulation of the epidermal growth factor receptor. Pathway analysis showed that metabolic pathways in CRC are related to glycerophospholipid metabolism and purine metabolism. In conclusion, we built an SVM model with good performance to distinguish between early-stage CRC and normal groups based on iEESI-MS and found that LPC (18:0) is associated with the progression of CRC.

Hao-Ran Zheng,1,2,&ast; Ai-Min Jiang,1,&ast; Huan Gao,1 Na Liu,1 Xiao-Qiang Zheng,1 Xiao Fu,1 Rui Zhang,1 Zhi-Ping Ruan,1 Tao Tian,1 Xuan Liang,1 Yu Yao1 1Department of Medical Oncology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China; 2Department of Medical Oncology, Xi’an No.3 Hospital, Xi’an, Shaanxi, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xuan Liang; Yu Yao, Department of Medical Oncology, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277 Yanta West Road, Xi’an, Shaanxi, 710061, People’s Republic of China, Tel +86-29-85324600, Fax +86-29-85324086, Email liangxuan029@163.com; 13572101611@163.comPurpose: Anlotinib, an antiangiogenic multi-target tyrosine kinase inhibitor (TKI), has shown favorable anticancer efficacy and acceptable safety in treating extensive-stage small cell lung cancer (ES-SCLC) in some clinical studies. This research aimed to explore the real-world efficacy and safety of anlotinib in ES-SCLC.Methods: Pathologically confirmed ES-SCLC patients receiving anlotinib were enrolled for this retrospective study. The primary endpoint of this study was progression-free survival (PFS), and secondary endpoints included overall survival (OS), objective response rate (ORR), disease control rate (DCR), and adverse reactions.Results: In total, 202 patients were included in this study. The median PFS of all patients was 4.8 months [95% confidence interval (CI): 3.9– 5.7], and the median OS was 7.6 months (95% CI 6.5– 8.7). Respectively, the overall ORR and DCR were 30.2% and 87.1%. The univariate and multivariate Cox regression analyses revealed that patients with Eastern Cooperative Oncology Group Performance Status (ECOG PS) ≤ 1, plus chemotherapy or immunotherapy, plus radiotherapy, and post-medication hypertension might have longer PFS and OS. The PFS and OS were significantly prolonged in combination group than that in monotherapy group [PFS 6.0 vs 3.6 months, hazards ratio (HR)=0.49, 95% CI 0.34– 0.70, P < 0.001; OS 9.2 vs 4.8 months, HR = 0.48, 95% CI 0.32– 0.72, P < 0.001]. The main treatment-related adverse reactions were generally tolerated. The incidence of adverse reactions in combination group was higher than that in monotherapy group (75.0% vs 52.6%, P = 0.001). The most common adverse reaction was hypertension, followed by hand-foot syndrome and fatigue, regardless of monotherapy or combination group.Conclusion: Anlotinib is effective and well tolerated in patients with ES-SCLC in the real-world. The clinical efficacy of anlotinib combined with chemotherapy or immunotherapy is better than that of monotherapy. Further investigations are needed for prospective studies with larger sample size.Keywords: anlotinib, small cell lung cancer, real-world, efficacy, safety

Degree management is considered the kernel of the Degree Informationization Construction. With the continue population and development of information and technology, the government put great emphasis on college graduation student, effective and standard graduate student degree management system has been the mainstream direction of college graduation management system, as well as thenecessary means and effective ways to educate college graduation student. Firstly, this paper introduced the application status of graduate comprehensive information management system at home and abroad. Citing Anhui University of technology’s graduation student education, we have analysised and researched the reality problems and emergency situations in the process of degree management, proposing reasonable solutions. Next, basing on Anhui University of Technology graduation degree management rules and degree management requirements, we designed graduation comprehensive information management system—degeree management software. The system has been devided five subsystem: thesis proposal management subsystem, mid-term examination subsystem, degree management subsystem,scientific information subsystem and fostering plan subsystem. Lastly, this paper not only introduced the test cases of the system but also summarized the system and put forward the prospect. This system is based on B/S(Browse/Server) and used OOD(Object-Oriented Design) method. In addition, software reuse and MVC(Model + View + Hibernate) pattern has been used in the paper. The degeree management software has improved the development efficiency greatly and reduced the development cost.Users can learn and master the software by its simple interactive inference.

Optoelectronic devices consist of heterointerfaces formed between dissimilar semiconducting materials. The relative energy-level alignment between contacting semiconductors determinately affects the heterointerface charge injection and extraction dynamics. For perovskite solar cells (PSCs), the heterointerface between the top perovskite surface and a charge-transporting material is often treated for defect passivation(1-4) to improve the PSC stability and performance. However, such surface treatments can also affect the heterointerface energetics(1). Here we show that surface treatments may induce a negative work function shift (that is, more n-type), which activates halide migration to aggravate PSC instability. Therefore, despite the beneficial effects of surface passivation, this detrimental side effect limits the maximum stability improvement attainable for PSCs treated in this way. This trade-off between the beneficial and detrimental effects should guide further work on improving PSC stability via surface treatments.

The generation of terahertz (THz) waves by focusing a femtosecond pulsed laser beam at a distance is able to overcome the strong absorption properties of air and has rapidly attracted the attention of the industry. However, the poor directionality of the THz wave radiation generated by this method is not conducive to THz wave applications. By controlling the morphology of the ultrafast laser-excited plasma filament and its electron density distribution through coherent beam combining (CBC) technology, we achieve direct THz beam shaping and are able to obtain THz wave radiation of Gaussian or arbitrary transverse distribution. The novel experimental approach proposed in this paper opens up the research field of direct THz wave shaping using plasma. Moreover, it innovates multi-parameter convergence algorithms and, by doing so, has the potential to find beam patterns with higher energy conversion efficiency and break the energy limit of THz waves emitted by lasers at high power.

Background Grain weight/size influences not only grain yield (GY) but also nutritional and appearance quality and consumer preference in Tartary buckwheat. The identification of quantitative trait loci (QTLs)/genes for grain weight/size is an important objective of Tartary buckwheat genetic research and breeding programs. Results Herein, we mapped the QTLs for GY, 1000-grain weight (TGW), grain length (GL), grain width (GW) and grain length–width ratio (L/W) in four environments using 221 recombinant inbred lines (XJ-RILs) derived from a cross of 'Xiaomiqiao × Jinqiaomai 2'. In total, 32 QTLs, including 7 for GY, 5 for TGW, 6 for GL, 11 for GW and 3 for L/W, were detected and distributed in 24 genomic regions. Two QTL clusters, qClu-1-3 and qClu-1-5, located on chromosome Ft1, were revealed to harbour 7 stable major QTLs for GY (qGY1.2), TGW (qTGW1.2), GL (qGL1.1 and qGL1.4), GW (qGW1.7 and qGW1.10) and L/W (qL/W1.2) repeatedly detected in three and above environments. A total of 59 homologues of 27 known plant grain weight/size genes were found within the physical intervals of qClu-1-3 and qClu-1-5. Six homologues, FtBRI1, FtAGB1, FtTGW6, FtMADS1, FtMKK4 and FtANT, were identified with both non-synonymous SNP/InDel variations and significantly differential expression levels between the two parents, which may play important roles in Tatary buckwheat grain weight/size control and were chosen as core candidate genes for further investigation. Conclusions Two stable major QTL clusters related to grain weight/size and six potential key candidate genes were identified by homology comparison, SNP/InDel variations and qRT‒qPCR analysis between the two parents. Our research provides valuable information for improving grain weight/size and yield in Tartary buckwheat breeding.

Lanthanide metal-organic frameworks (Ln-MOFs) are promising for luminescence detection of volatile organic compound (VOC) vapors, but usually suffer from the silent or quenched Ln3+ emission. Herein, we report a new dual-emissive Eu-MOF composed of the coordinatively unsaturated Eu9 clusters that afford abundant open metal sites to form a confined "binding pocket" to facilitate the preconcentration and recognition of VOCs. Single-crystal structural analyses reveal that specific analytes can replace the OH oscillators in the first coordination sphere of Eu3+ and form a unique hydrogen-bonding second-sphere adduct tying adjacent Eu9 clusters together to minimize their nonradiative vibrational decay. With the promoted Eu3+ luminescence, the MOF realizes real-time in situ visual sensing of THF vapor (1 s) and shows a quantitative ratiometric response to the vapor pressure with a limit of detection down to 17.33 Pa. Also, it represents a top-performing ratiometric luminescent thermometer.

BACKGROUND Emerging evidence indicates that the apolipoprotein E (APOE) e4 exacerbates α-synuclein pathology. OBJECTIVE To determine whether APOE e4 contributes to motor progression in early Parkinson's disease (PD). METHODS Longitudinal data were obtained from 384 patients with PD divided into APOE e4 carriers (n = 85) and noncarriers (n = 299) in the Parkinson's Progression Marker Initiative. Participants underwent yearly motor assessments over a mean follow-up period of 78.9 months. Repeated measures and linear mixed models were used to test the effects of APOE e4. RESULTS The motor progression was significantly more rapid in patients with PD carrying APOE e4 than in noncarriers (β = 0.283, P = 0.026, 95% confidence interval: 0.033-0.532). Through subgroup analysis, we found that the effect of APOE e4 was significant only in patients with high amyloid β burden (β = 0.761, P

With the rapid growth of real-world graphs, the size of which can easily exceed the on-chip (board) storage capacity of an accelerator, processing large-scale graphs on a single Field Programmable Gate Array (FPGA) becomes difficult. The multi-FPGA acceleration is of great necessity and importance. Many cloud providers (e.g., Amazon, Microsoft, and Baidu) now expose FPGAs to users in their data centers, providing opportunities to accelerate large-scale graph processing. In this paper, we present a communication library, called FDGLib, which can easily scale out any existing single FPGA-based graph accelerator to a distributed version in a data center, with minimal hardware engineering efforts. FDGLib provides six APIs that can be easily used and integrated into any FPGA-based graph accelerator with only a few lines of code modifications. Considering the torus-based FPGA interconnection in data centers, FDGLib also improves communication efficiency using simple yet effective torus-friendly graph partition and placement schemes. We interface FDGLib into AccuGraph, a state-of-the-art graph accelerator. Our results on a 32-node Microsoft Catapult-like data center show that the distributed AccuGraph can be 2.32x and 4.77x faster than a state-of-the-art distributed FPGA-based graph accelerator ForeGraph and a distributed CPU-based graph system Gemini, with better scalability.

Ran Zheng, Yang Ruan, Yiqun Yan, Zhihao Lin, Naijia Xue, Yaping Yan, Jun Tian, Xinzhen Yin, Jiali Pu, Baorong Zhang Department of Neurology, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Zhejiang, 310009, People’s Republic of ChinaCorrespondence: Baorong Zhang; Jiali PuDepartment of Neurology, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Zhejiang, People’s Republic of ChinaFax +86-571-87784752Email brzhang@zju.edu.cn; jialipu@zju.edu.cnBackground: Inflammasome-induced neuroinflammation is a key contributor to the pathology of Parkinson’s disease (PD). NLR family pyrin domain-containing 3 (NLRP3) inflammasome activation has been implicated in PD in postmortem human PD brains, indicating it as a potential target for PD treatment. Melatonin, a multitasking molecule, has been found to have anti-inflammatory activities, mediated by silence information regulator 1 (SIRT1). However, whether and how melatonin is involved in inflammasome-induced neuroinflammation in PD pathogenesis remains unclear.Methods: We investigated the potential anti-inflammatory effects of melatonin in vitro and in vivo, using 1-methyl-4-phenylpyridinium (MPP+)-simulated BV2 and primary microglia cell models, and a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced murine PD model, with or without melatonin treatment. Rotarod, grip strength, and open-field tests were performed to measure the effects of melatonin on MPTP-induced motor disorders. Degeneration of dopaminergic neurons was evaluated by immunofluorescence. Changes in microglia were examined by immunofluorescence and Western blotting, and the expression levels of the involved signaling molecules were assessed by Western blotting and enzyme-linked immunosorbent assay (ELISA). Intracellular reactive oxygen species (ROS) was detected using fluorescent probes via flow cytometry.Results: We found that melatonin significantly alleviated motor dysfunction and prevented MPTP-induced neurotoxicity in dopaminergic neurons. Additionally, melatonin reduced MPTP-induced microglial activation and suppressed NLRP3 inflammasome activity, and also inhibited IL-1β secretion. Moreover, in MPP+-primed BV2 cells, melatonin markedly restored the downregulation of SIRT1 and attenuated the activation of the NLRP3 inflammasome. This was reversed by SIRT1 inhibitor treatment.Conclusion: In conclusion, our data demonstrated that melatonin attenuates neuroinflammation by negatively regulating NLRP3 inflammasome activation via a SIRT1-dependent pathway in MPTP-induced PD models. These findings provide novel insights into the mechanism underlying the anti-inflammatory effects of melatonin in PD.Keywords: inflammasomes, melatonin, NLRP3, Parkinson disease, sirtuin 1

Summary Human extended pluripotent stem cells (EPSCs), with bidirectional chimeric ability to contribute to both embryonic and extraembryonic lineages, can be obtained and maintained by converting conventional pluripotent stem cells using chemicals. However, the transition system is based on inactivated mouse fibroblasts, and the underlying mechanism is not clear. Here we report a Matrigel-based feeder-free method to convert human embryonic stem cells and induced pluripotent stem cells into EPSCs and demonstrate the extended pluripotency in terms of molecular features, chimeric ability, and transcriptome. We further identify chemicals targeting glycolysis and histone methyltransferase to facilitate the conversion to and maintenance of feeder-free EPSCs. Altogether, our data not only establish a feeder-free system to generate human EPSCs, which should facilitate the mechanistic studies of extended pluripotency and further applications, but also provide additional insights into the transitions among different pluripotent states., Graphical abstract, Highlights • EPSCs can be generated under feeder-free (LCDM-IY-Matrigel) conditions • Feeder-free EPSCs exhibit bidirectional developmental ability • GSK126 promotes the transition to human feeder-free EPSCs from ESCs/iPSCs • Inhibitors of glycolysis benefit the maintenance of feeder-free EPSCs, In this article, Zheng et al. establish human feeder-free extended pluripotent stem cells (ffEPSCs) from ESCs and iPSCs and characterize the extended pluripotency in terms of molecular markers and bidirectional developmental ability. They further identify that chemicals targeting histone modifiers andglycolysis could facilitate the transition and maintenance of ffEPSCs.

Due to their solution processability and unique photoelectric characteristics, perovskite solar cells (PSCs) have shown considerable promise in the area of renewable energy. Although their power conversion efficiency (PCE) has risen from 3.8% to 25.7% in only a few years, their short lifetime and high material prices continue to be key roadblocks to commercial viability. Charge transporting materials (CTMs), such as hole/electron transporting materials, are critical components in PSCs because they not only govern hole or electron extraction and transporting from the perovskite layer to the electrodes but also protect the perovskite from direct contact with the ambient environment. CTMs are split into two types: inorganic CTMs (ICTMs) and organic CTMs (OCTMs). Because of their inexpensive prices, well-adjusted energy levels, and low temperature solution-processed features, OCTMs have been more frequently explored and employed than ICTMs. Various forms of OCTMs with more straightforward synthetic pathways and better performance have been thoroughly researched. Recent achievements in the development of OCTMs will be discussed and evaluated on a molecular level in this study, which will include a systematic categorization of OCTMs based on molecular functionalization techniques. In order to achieve highly efficient and stable PSCs, we will present insights on the structure-property relationship in the design of OCTMs as well as device stability. We hope that this analysis will serve as a comprehensive reference to molecular design guidelines for various types of OCTMs, spurring greater research toward designing highly efficient and OCTMs for stable PSCs.

MCrAlY can be used as bond coats for thermal barrier coatings (TBCs) with good ductility and excellent resistance against high temperature oxidation and hot corrosion. The behavior of the microstructure development in the MCrAlY coatings plays a key role on the oxidation resistance. In this paper, the microstructure in the coatings oxidized at 750~1100 °C was analyzed. The formation of the phases and their fraction were studied by comparing thermodynamic simulation results with the experimental observations. At higher temperatures (>1000 °C) β-to-γ’-to-γ phase transformation took place while at lower temperatures (

MCrAlY can be used as bond coats for thermal barrier coatings (TBCs) with good ductility and excellent resistance against high temperature oxidation and hot corrosion. The behavior of the thermally grown oxide (TGO) scale formed at the MCrAlY coatings plays a key role on the oxidation resistance. In this paper, the oxidation kinetic curves of a MCrAlY coating at 900~1000 °C were obtained by measuring the thickness of the TGO scales. The curves basically conveyed parabolic laws, indicating a diffusion-controlled mechanism of the TGO growth. The thickness of TGO was positively correlated with the consumption of β phase during the early stage of the oxidation processes. After about the half-life of the β phase consumption, the depletion of the β phase significantly accelerated, which was caused by coating-substrate interdiffusion. In addition, the microstructure of the TGO was analyzed

Pneumoconiosis is one of the most universal and severe occupational diseases in the world today. The diagnosis of pneumoconiosis mainly depends on the doctors’ analysis of chest X-ray films. However, diagnostic accuracy is related to a doctor’s expertise. Recent research has suggested that deep convolutional neural network (CNN) could better identify diseases than experts. Deep CNN can efficiently extract features from data for discrimination. Nevertheless, high volumes of training data are usually necessary to achieve, which is not desirable from the research. This article studies pneumoconiosis identification from the perspective of CNN-based transfer learning. In this work, we raise two transfer learning patterns from “frozen layers” and “finetuned layers” to solve those problems. The knowledge learned from the ImageNet is transferred to pneumoconiosis identification. Also, we propose some methods of image denoising, lung segmentation, and data amplification for preprocessing to improve image qualities. The experimental results show that both transfer learning patterns are better than starting from scratch with limited training data. Notably, the “finetuned layers” transfer learning pattern achieves a higher performance.

The variations among shapes, sizes, and locations of tumors are obstacles for accurate automatic segmentation. U-Net is a simplified approach for automatic segmentation. Generally, the convolutional or the dilated convolutional layers are used for brain tumor segmentation. However, existing segmentation methods of the significant dilation rates degrade the final accuracy. Moreover, tuning parameters and imbalance ratio between the different tumor classes are the issues for segmentation. The proposed model, known as Residual-Dilated Dense Atrous-Spatial Pyramid Pooling (RD2A) 3D U-Net, is found adequate to solve these issues. The RD2A is the combination of the residual connections, dilation, and dense ASPP to preserve more contextual information of small sizes of tumors at each level encoder path. The multi-scale contextual information minimizes the ambiguities among the tissues of the white matter (WM) and gray matter (GM) of the infant’s brain MRI. The BRATS 2018, BRATS 2019, and iSeg-2019 datasets are used on different evaluation metrics to validate the RD2A. In the BRATS 2018 validation dataset, the proposed model achieves the average dice scores of 90.88, 84.46, and 78.18 for the whole tumor, the tumor core, and the enhancing tumor, respectively. We also evaluated on iSeg-2019 testing set, where the proposed approach achieves the average dice scores of 79.804, 77.925, and 80.569 for the cerebrospinal fluid (CSF), the gray matter (GM), and the white matter (WM), respectively. Furthermore, the presented work also obtains the mean dice scores of 90.35, 82.34, and 71.93 for the whole tumor, the tumor core, and the enhancing tumor, respectively on the BRATS 2019 validation dataset. Experimentally, it is found that the proposed approach is ideal for exploiting the full contextual information of the 3D brain MRI datasets.

Polychlorinated naphthalene (PCN) concentrations in the soil at an e-waste recycling area in Guiyu, China, were measured and the associated human cancer risk due to e-waste-related exposures was investigated. We quantified PCNs in the agricultural soil and used these concentrations with predictive equations to calculate theoretical concentrations in outdoor air. We then calculated theoretical concentrations in indoor air using an attenuation factor and in the local diet using previously published models for contaminant uptake in plants and fruits. Potential human cancer risks of PCNs were assessed for multiple exposure pathways, including soil ingestion, inhalation, dermal contact, and dietary ingestion. Our calculations indicated that local residents had a high cancer risk from exposure to PCNs and that the diet was the primary pathway of PCN exposure, followed by dermal contact as the secondary pathway. We next repeated the risk assessment using concentrations for other carcinogenic contaminants reported in the literature at the same site. We found that polychlorinated dibenzodioxins and dibenzofurans (PCDD/Fs) and PCNs caused the highest potential cancer risks to the residents, followed by polychlorinated biphenyls (PCBs). The relative importance of different exposure pathways depended on the physicochemical properties of specific chemicals.

Metal lithium anodes, with extremely high specific capacity, low density, and lowest potential, are considered to be the most promising anode materials for next-generation high-energy density batteries. However, in the process of repeated plating and stripping of lithium, lithium dendrites are easily grown on the surface of the metal lithium anode, which greatly reduces the capacity of the battery, even causes hidden safety risks and shortens the battery life. This paper reviews the modification methods of lithium anodes based on the growth process of lithium dendrites, and introduces several current modification methods, including electrolyte additives, artificial SEI and new structure of lithium anodes. Finally, the future research direction and development trend of metal lithium anodes are prospected.

Metabolic syndrome (MetS) is a pathological condition characterized by obesity, hyperglycemia, hypertension and hyperlipidemia that increases the risk of cardiovascular disease, type 2 diabetes and non-alcoholic fatty liver disease. The traditional Chinese medicine Lian-Qu formula (LQF) is modified from Xiaoxianxiong decoction, which has been used for coronary heart disease or metabolic disease in clinical for a long time. However, the pharmacological mechanism of LQF on MetS is unclear.Here, we explored the actions of LQF on MetS via network pharmacology and validated the mechanism in the MetS mice.The compounds of LQF were searched in the traditional Chinese medicine systems pharmacology database and the natural product activityspecies source database. The related targets of MetS disease were gathered from genes cluster with literature profiles database. The protein-protein interaction network was constructed to obtain the key target genes. The gene ontology analysis and kyoto encyclopedia of genes and genomes pathway enrichment of the key targets were performed to predict the potential mechanisms of LQF action on MetS. And then, the high-fat diet-induced MetS mice were used to validate its therapeutic effect and molecular targets. Insulin tolerance and oral glucose tolerance tests were used. Body weight and visceral fat index were measured to assess obesity. Liver metabolism was detected by HE section, oil red O staining and untargeted lipid metabolomics experiments. Finally, the key targets of LQF were verified by PCR and ELISA experiments.A total of 466 compounds in LQF were obtained, among which 71 were active. These compounds correspond to 74 targets associated with MetS. The predicted key targets of LQF worked on MetS were AKT1, INSR, PPARs, FASN, LDLR, TNF, CRP, IL-6, IL-1β and so on. Furthermore, these key targets were related to pathways in cellular response to lipid, inflammatory response, glucose transmembrane transport and insulin resistance. Finally, the animal experiments validated that LQF inhibited lipids accumulation by inhibiting the gene expression of FASN and increasing ADPN, and it relieved insulin resistance by increasing GLUT-4 expression. Moreover, LQF alleviated inflammation by reducing IL-6 and CRP levels.LQF exerted anti-MetS effects through improving insulin sensitivity, ameliorating hyperlipidemia and obesity, reducing liver injury, and inhibiting inflammatory response.

Contemporary social reform promotes rapid social transformation, and social practice has a special educational function in higher education. However, research shows weak willingness to participate in social practice among college students. Using the mixed research method, 438 completed questionnaire surveys on perceived environmental support were collected from college students. The influence of perceived environmental support on Chinese college students’ willingness to participate in social practice was analyzed using partial least squares structural equation modeling, and an empirical test was conducted. The findings are as follows: (1) Perceived environmental support significantly impacts students’ participation attitude and perceived behavioral control. (2) Participation attitude and perceived behavioral control significantly influence participation intention, but behavioral norms have no significant influence. (3) Participation intention and perceived behavioral control significantly influence actual behavior. This study provides the theoretical basis of perceived environmental support for future research on social practice participation intention and offers some theoretical guidance for the implementation of social practice in China.

The insidious onset of Parkinson's disease (PD) makes early diagnosis difficult. Notably, idiopathic rapid eye movement sleep behavior disorder (iRBD) was reported as a prodrome of PD, which may represent a breakthrough for the early diagnosis of PD. However, currently there is no reliable biomarker for PD diagnosis. Considering that α-synuclein (α-Syn) and neuroinflammation are known to develop prior to the onset of clinical symptoms in PD, it was hypothesized that plasma total exosomal α-Syn (t-exo α-Syn), neural-derived exosomal α-Syn (n-exo α-Syn) and exosomal apoptosis-associated speck-like protein containing a caspase activation and recruitment domain (ASC) may be potential biomarkers of PD.In this study, 78 PD patients, 153 probable iRBD patients (pRBD) and 63 healthy controls (HCs) were recruited. α-Syn concentrations were measured using a one-step paramagnetic particle-based chemiluminescence immunoassay, and ASC levels were measured using the Ella system.It was found that t-exo α-Syn was significantly increased in the PD group compared to the pRBD and HC groups (p lt; 0.0001), whilst n-exo α-Syn levels were significantly increased in both the PD and pRBD groups compared to HCs (p lt; 0.0001). Furthermore, although no difference was found in ASC levels between the PD and pRBD groups, there was a positive correlation between ASC and α-Syn in exosomes.Our results suggest that both t-exo α-Syn and n-exo α-Syn were elevated in the PD group, whilst only n-exo α-Syn was elevated in the pRBD group. Additionally, the adaptor protein of inflammasome ASC is correlated with α-Syn and may facilitate synucleinopathy.

Ferroptosis, a novel form of regulated cell death, is caused by accumulation of lipid peroxides and excessive iron deposition. This process has been linked to the death of dopaminergic neurons in substantia nigra compacta (SNc) of Parkinson's disease (PD) patients. Quercetin (QCT), a natural flavonoid, has multiple pharmacological activities. However, it has not been established whether QCT can protect against dopaminergic neuron death by inhibiting ferroptosis. In this study, we investigated the potential antiferroptotic effects of QCT in cellular models established using specific ferroptosis inducers (Erastin and RSL-3) and MPP

Hand, foot, and mouth disease (HFMD) is an infectious disease that usually occurs in children under 5 years and is caused by a group of enteroviruses. This study aimed to investigate the epidemiological characteristics of HFMD clusters from 2016 to 2020 in Tongzhou, Beijing, and explored the genetic evolution of CV-A6. The HFMD case information came from the Information System of China Center for Disease Control and Prevention (CDC), as well as the clusters information verification and on-site investigation by Tongzhou CDC. ARIMA model was applied to forecast HFMD clusters in 2020. Totally 440 HFMD clusters were reported during 2016-2020. The large peak of the clusters occurred in April-July, followed by a smaller peak in October-November during 2016-2019. However, in 2020, the two peaks disappeared. The main site of HFMD clusters was childcare facilities (65.0%) and mostly occurred in urban areas (46.1%). The detection rate of CV-A6 was the highest (36.1%), and cases with CV-A6 infection had the highest proportion of fever. The phylogenetic analysis based on CV-A6 VP1 gene showed that the predominant strains mainly located in Group F during 2016-2017, while changed into Group A during 2018-2020. HFMD clusters presented seasonality, mainly located in childcare facilities and urban areas, and CV-A6 was the major causative agent. Targeted prevention and control measures should be taken to reduce HFMD clusters.

Human endogenous retroviruses, also called LTR elements, can be bound by transcription factors and marked by different histone modifications in different biological contexts. Recently, individual LTR or certain subclasses of LTRs such as LTR7/HERVH and LTR5_Hs/HERVK families have been identified as cis-regulatory elements. However, there are still many LTR elements with unknown functions. Here, we dissected the landscape of histone modifications and regulatory map of LTRs by integrating 98 ChIP-seq data in human embryonic stem cells (ESCs), and annotated the active LTRs enriching enhancer/promoter-related histone marks. Notably, we found that MER57E3 functionally acted as proximal regulatory element to activate respective ZNF gene. Additionally, HERVK transcript could mainly function in nucleus to activate the adjacent genes. Since LTR5_Hs/LTR5 was bound by many early embryo-specific transcription factors, we further investigated the expression dynamics in different pluripotent states. LTR5_Hs/LTR5/HERVK exhibited higher expression level in naïve ESCs and extended pluripotent stem cells (EPSCs). Functionally, the LTR5_Hs/LTR5 with high activity could serve as a distal enhancer to regulate the host genes. Ultimately, our study not only provides a comprehensive regulatory map of LTRs in human ESCs, but also explores the regulatory models of MER57E3 and LTR5_Hs/LTR5 in host genome.

Perivascular spaces in the brain have been known to communicate with cerebrospinal fluid and contribute to waste clearance in animal models. In this study, we sought to determine the association between MRI-visible enlarged perivascular spaces (EPVS) and disease markers in Parkinson’s disease (PD). We obtained longitudinal data from 245 patients with PD and 98 healthy controls from the Parkinson’s Progression Marker Initiative. Two trained neurologists performed visual ratings on T2-weighted images to characterize EPVS in the centrum semiovale (CSO), the basal ganglia (BG) and the midbrain. We found that a greater proportion of patients with PD had low grade BG-EPVS relative to healthy controls. In patients with PD, lower grade of BG-EPVS and CSO-EPVS predicted lower CSF α-synuclein and t-tau. Lower grade of BG-EPVS were also associated with accelerated Hoehn &Yahr stage progression in patients with baseline stage 1. BG-EPVS might be a valuable predictor of disease progression.

General purpose graphics processing units (GPGPUs) can be used to improve computing performance considerably for regular applications. However, irregular memory access exists in many applications, and the benefits of graphics processing units (GPUs) are less substantial for irregular applications. In recent years, several studies have presented some solutions to remove static irregular memory access. However, eliminating dynamic irregular memory access with software remains a serious challenge. A pure software solution without hardware extensions or offline profiling is proposed to eliminate dynamic irregular memory access, especially for indirect memory access. Data reordering and index redirection are suggested to reduce the number of memory transactions, thereby improving the performance of GPU kernels. To improve the efficiency of data reordering, an operation to reorder data is offloaded to a GPU to reduce overhead and thus transfer data. Through concurrently executing the compute unified device architecture (CUDA) streams of data reordering and the data processing kernel, the overhead of data reordering can be reduced. After these optimizations, the volume of memory transactions can be reduced by 16.7%–50% compared with CUSPARSE-based benchmarks, and the performance of irregular kernels can be improved by 9.64%–34.9% using an NVIDIA Tesla P4 GPU.

Magnetic Resonance Imaging (MRI) is dominant modality for infant brain analysis. Segmenting the whole infant MRI brain into number of tissues such as Cerebrospinal fluid (CSF), White matter (WM), and Gray Matter (GM) are highly desirable in the clinical environment. However, traditional methods tend to be degrading due to low contrast between GM and WM in isointense phase (about 6–8 months of early life). Recently, Convolutional Neural Network (CNN) emerged as a robust intelligent approach to examine medical image. The UNet model is among the preferred CNN models that have been widely used for medical imaging applications and achieved excellent results. The UNet architecture is a combination of convolutional, pooling, and up-sampling layers. Recently, 3D-UNet architecture used to exploit 3D-contextual information of volumetric data in many applications. However, CNN faces challenge to distinguish the similar brain tissues. In this paper, we present a variant of 3D-UNet to extract the volumetric contextual information of medical data. We propose a novel combined architecture of dense connection, residual connection, and inception module. The proposed architecture contains three stages, namely the densely connected stage, a residual inception stage, and an up-sampling stage. Our proposed approach provides state-of-art results in comparison to other existing approaches. This suggested approach achieves dice scores of 0.95, 0.905, and 0.92 in CSF, WM, and GM tissues respectively.

Genomic evolution among bacteriophages infecting Caulobacter crescentus is inevitable. However, the conservation of the proteins associated with intact phage particles has not been investigated. In this study, we compared the structural proteins associated with two genomically diverse but morphologically similar C. crescentus-infecting bacteriophages, phiCbK and CcrSC. We were able to detect more than 20 proteins that are part of the bacteriophage particle in both phages, and we were able to identify a small number of proteins that were found in only one of the two phage particles. All but one of the genes coding for these structural proteins were located in a region of the genome that had been designated a structural region, confirming the idea that the genes in these phage genomes are clustered according to their function. During the purification process, we also discovered that phiCbk has a replication complex that can be recovered from the cell lysate, and this complex allowed us to identify many of the phage proteins involved in phage genome replication.

Background Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, and mainly characterized by the progressive degeneration of dopaminergic (DA) neurons in the midbrain substantia nigra and non-DA neurons in many other parts of the brain. Previous studies have shown that several genes associated with the causes of PD can influence neurite outgrowth. Mutations of PRKN (encoding parkin, an E3 ubiquitin ligase) are the most frequent cause of recessively inherited PD. The lack of a PD phenotype in Prkn-knockout mice may imply a unique vulnerability of neurons to parkin mutations. Methods CRISPR/Cas9 technology was used to target random mutations into exon3 of PRKN in human fibroblasts cell line MRC-5. The induced DA neurons were achieved from direct conversion of fibroblasts (with or without PRKN mutations) via a cocktail of transcriptional factors (Ascl1, Nurr1, Lmx1a, miRNA124, p53 shRNA) and chemicals (CHIR99021, Purmorphamine, TGFβ3, BDNF, GDNF, NGF and Y27632). Results Herein, we successfully established human neuronal cell models with parkin mutations from fibroblast-reprogrammed neurons. In these neurons, not only were the induced ratio and number of mature neurons markedly decreased, but also the complexity of the neuronal processes, measured by total neurite length and number of terminals, was greatly reduced, in TH+ and TH−neurons with PRKN mutations. Conclusions The results suggest that parkin not only maintains the morphological complexity of human neurons, but also influences maturation and differentiation in the fibroblast reprogramming process.