Primary assessment of the diversity of Omicron sublineages and the epidemiologic features of autumn/winter 2022 COVID-19 wave in Chinese mainland.

With the recent ongoing autumn/winter 2022 COVID-19 wave and the adjustment of public health control measures, there have been widespread SARS-CoV-2 infections in Chinese mainland. Here we have analyzed 369 viral genomes from recently diagnosed COVID-19 patients in Shanghai, identifying a large number of sublineages of the SARS-CoV-2 Omicron family. Phylogenetic analysis, coupled with contact history tracing, revealed simultaneous community transmission of two Omicron sublineages dominating the infections in some areas of China (BA.5.2 mainly in Guangzhou and Shanghai, and BF.7 mainly in Beijing) and two highly infectious sublineages recently imported from abroad (XBB and BQ.1). Publicly available data from August 31 to November 29, 2022 indicated an overall severe/critical case rate of 0.035% nationwide, while analysis of 5706 symptomatic patients treated at the Shanghai Public Health Center between September 1 and December 26, 2022 showed that 20 cases (0.35%) without comorbidities progressed into severe/critical conditions and 153 cases (2.68%) with COVID-19-exacerbated comorbidities progressed into severe/critical conditions. These observations shall alert healthcare providers to place more resources for the treatment of severe/critical cases. Furthermore, mathematical modeling predicts this autumn/winter wave might pass through major cities in China by the end of the year, whereas some middle and western provinces and rural areas would be hit by the upcoming infection wave in mid-to-late January 2023, and the duration and magnitude of upcoming outbreak could be dramatically enhanced by the extensive travels during the Spring Festival (January 21, 2023). Altogether, these preliminary data highlight the needs to allocate resources to early diagnosis and effective treatment of severe cases and the protection of vulnerable population, especially in the rural areas, to ensure the country's smooth exit from the ongoing pandemic and accelerate socio-economic recovery.

Novel economy and carbon emissions prediction model of different countries or regions in the world for energy optimization using improved residual neural network.

Nowadays, the world has achieved tremendous economic development at the expense of the long-term habitability of the planet. With the rapid economic development, the global greenhouse effect caused by excessive carbon dioxide (CO2) emissions is also accumulating, which generates the negative impact of global warming on nature and human beings. Meanwhile, economy and CO2 emissions prediction methods based on traditional neural networks lead to gradient disappearance or gradient explosion, making the economy and CO2 emissions prediction inaccurate. Therefore, this paper proposes a novel economy and CO2 emissions prediction model based on a residual neural network (RESNET) to optimize and analyze energy structures of different countries or regions in the world. The skip links are used in the inner residual block of the RESNET to alleviate vanishing gradients due to increasing depth in deep neural networks. Consequently, the proposed RESNET can optimize this problem and protect the integrity of information by directly bypassing the input information to the output, which can increase the precision of the prediction model. The needs for natural gas, hydroelectricity, oil, coal, nuclear energy, and renewable energy in 24 different countries or regions from 2009 to 2020 are used as inputs, the CO2 emissions and the gross domestic product (GDP) per capita are respectively used as the undesired output and the desired output of the RESNET to build an economy and CO2 emissions prediction model. The experimental results show that the RESNET has higher correctness and functionality than the traditional convolutional neural network (CNN), the radial basis function (RBF), the extreme learning machine (ELM) and the back propagation (BP). Furthermore, the proposed model provides guidance and development plans for countries or regions with low energy efficiency, which can improve energy efficiency, economic development and reasonably control CO2 emissions.

Differential subsampling with cartesian ordering: A high spatial-temporal resolution dixon imaging sequence for assessment of dural arteriovenous fistula.

Objective: To evaluate the accuracy of differential subsampling with cartesian ordering (DISCO) in comparison to time of flight (TOF) in detecting dural arteriovenous fistulas (DAVF), cerebral venous thrombosis (CVT) and hemodynamics. Methods: Sixty-two cases (24 female; aged 14-75; mean age, 51.3 years) were included in our study, with 42 positive and 20 negative cases via Digital Subtraction Angiography (DSA). Two neuroradiologists independently evaluated the DISCO and TOF. The sensitivity, specificity, and accuracy of the DISCO and TOF-MRA were individually calculated using DSA as the gold standard. Inter-observer reliability was assessed by using a weighted Cohen's kappa (κ) test; P < 0.05 was set as the threshold for statistical significance. Results: Diagnostic sensitivities of DISCO and TOF for DAVF were 92.86 and 64.29%; specificities were 95.0% and 95.0%; while accuracies were 93.55 and 74.19% respectively. For detected CVT, sensitivities of DISCO and TOF were 100 and 92.31%; specificities were 96.55 and 93.10%; with accuracies 97.62 and 92.86% respectively. In hemodynamic analysis, sensitivity of DISCO for reflux was 95.45%; with a specificity of 95.0%; and accuracy 95.24%. The inter-observer kappa values were 0.857 for DISCO (P < 0.001). Conclusion: DISCO showed a high degree of sensitivity and specificity, suggesting its effectiveness in detecting DAVF with or without CVT. Intracranial hemodynamics can be identified using DISCO in DAVF patients, providing accurate evaluation of cerebral blood flow dynamics during the pre-treatment phase.

Estrogenicity assessment of membrane concentrates from landfill leachate treated by the UV-Fenton process using a human breast carcinoma cell line.

Membrane concentrates (MCs) are generated when membranes are used to concentrate landfill leachate. It contains high concentrations of inorganic and organic environmental pollutants, which are highly toxic and carcinogenic. In this paper, the proliferation effect (PE) from MC before and after treatment with the UV-Fenton process was assessed using the human breast carcinoma cell line MCF-7. The highest value of 116% was found at 5% (v/v) concentration after a 10 min reaction. Phthalic acid esters (PAEs) play an important role in the MC estrogenicity. Estrogen simulation solutions (ESS) of PAEs were prepared to simulate the changes in estrogenic active substances during the UV-Fenton process. The ESS degradation conformed to the first-order kinetics model. The estrogenicity decreased after an initial increase until it acted in a non-estrogenic manner. Convincingly, the intermediates were determined by GC/MS, and the estrogenicity was assessed during the degradation process. The estrogenicity was highly related to the generation of intermediates and the PAE concentration. The results provide guidance for UV-Fenton application in MC estrogenicity reduction.

Genotoxicity assessment of membrane concentrates of landfill leachate treated with Fenton reagent and UV-Fenton reagent using human hepatoma cell line.

Membrane concentrates of landfill leachates contain organic and inorganic contaminants that could be highly toxic and carcinogenic. In this paper, the genotoxicity of membrane concentrates before and after Fenton and UV-Fenton reagent was assessed. The cytotoxicity and genotoxicity was determined by using the methods of methyltetrazolium (MTT), cytokinesis-block micronucleus (CBMN) and comet assay in human hepatoma cells. MTT assay showed a cytotoxicity of 75% after 24h of exposure to the highest tested concentration of untreated concentrates, and no cytotoxocity for UV-Fenton and Fenton treated concentrates. Both CBMN and comet assays showed increased levels of genotoxicity in cells exposed to untreated concentrates, compared to those occurred in cells exposed to UV-Fenton and Fenton reagent treated concentrates. There was no significant difference between negative control and UV-Fenton treated concentrates for micronucleus and comet assay parameters. UV-Fenton and Fenton treatment, especially the former, were effective methods for degradation of bisphenol A and nonylphenol in concentrates. These findings showed UV-Fenton and Fenton reaction were effective methods for treatment of such complex concentrates, UV-Fenton reagent provided toxicological safety of the treated effluent, and the genotoxicity assays were found to be feasible tools for assessment of toxicity risks of complex concentrates.

Quantitative assessment of gait and neurochemical correlation in a classical murine model of Parkinson's disease.

BACKGROUND: Gait deficits are important clinical symptoms of Parkinson's disease (PD). However, existing behavioral tests for the detection of motor impairments in rodents with systemic dopamine depletion only measure akinesia and dyskinesia, and data focusing on gait are scarce. We evaluated gait changes in the methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced C57BL/6 murine model of PD by using a computer-assisted CatWalk system. Correlations of gait parameters with tyrosine hydroxylase (TH) protein levels in the substantia nigra (SN) were also investigated. RESULTS: The gait readouts, including the walking duration, variation of walking speed, step cycle, duty cycle, stance, initial dual stance, terminal dual stance, three- and four-point supports, and the base of support between hind limbs was noted to increase significantly one week after MPTP injection. In contrast, values of the stride length, cadence, swing speed, and diagonal dual support decreased substantially following MPTP treatment (p < 0.05). All of these changes lasted for three weeks after the last MPTP administration. Except for the stance in the fore limbs and the swing speed in the hind limbs, the gait variability in the PD mice showed a closer correlation with the protein levels of TH in the SN than the walking distances in the conventional open field test. Coordination parameters of the regularity index and step pattern were not affected in mice treated with MPTP. CONCLUSION: Data of the study suggest that the computer-assisted CatWalk system can provide reliable and objective criteria to stratify gait changes arising from MPTP-induced bilateral lesions in C57/BL6 mice. The extent of gait changes was noted to correlate with the expression of the biomarker for dopaminergic neurons. This novel analytical method may hold promise in the study of disease progression and new drug screening in a murine PD model.