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Coronavirus disease 2019 (COVID-19) remains a serious emerging global health problem, and little is known about the role of oropharynx commensal microbes in infection susceptibility and severity. Here, we present the oropharyngeal microbiota characteristics identified by full-length 16S rRNA gene sequencing through the NANOPORE platform of oropharynx swab specimens from 10 mild COVID-19 patients and 10 healthy controls. Our results revealed a distinct oropharyngeal microbiota composition in mild COVID-19 patients, characterized by enrichment of opportunistic pathogens such as Peptostreptococcus anaerobius and Pseudomonas stutzeri and depletion of Sphingomonas yabuuchiae , Agrobacterium sullae , and Pseudomonas veronii. Based on the relative abundance of the oropharyngeal microbiota at the species level, we built a microbial classifier to distinguish COVID-19 patients from healthy controls, in which P. veronii , Pseudomonas fragi , and S. yabuuchiae were identified as the most prominent signatures for their depletion in the COVID-19 group. Several members of the genus Campylobacter , especially Campylobacter fetus and Campylobacter rectus , which were highly enriched in COVID-19 patients with higher severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load and showed a significant correlation with disease status and several routine clinical blood indicators, indicate that several bacteria may transform into opportunistic pathogen in COVID-19 patients when facing the challenges of viral infection. We also found the diver taxa Streptococcus anginosus and Streptococcus alactolyticus in the network of disease patients, suggesting that these oropharynx microbiota alterations may impact COVID-19 severity by influencing the microbial association patterns. In conclusion, the low sample size of SARS-CoV-2 infection patients (n = 10) here makes these results tentative; however, we have provided the overall characterization that oropharyngeal microbiota alterations and microbial correlation patterns were associated with COVID-19 severity in Anhui Province. [ABSTRACT FROM AUTHOR]

In the context of the coronavirus disease 2019 pandemic, we investigated the epidemiological and clinical characteristics of a young patient infected by avian influenza A (H5N6) virus in Anhui Province, East China, and analyzed genomic features of the pathogen in 2020. Through the cross‐sectional investigation of external environment monitoring (December 29–31, 2020), 1909 samples were collected from Fuyang City. It was found that the positive rate of H5N6 was higher than other areas obviously in Tianma poultry market, where the case appeared. In addition, dual coinfections were detected with a 0.057% polymerase chain reaction positive rate the surveillance years. The virus was the clade 2.3.4.4, which was most likely formed by genetic reassortment between H5N6 and H9N2 viruses. This study found that the evolution rates of the hemagglutinin and neuraminidase genes of the virus were higher than those of common seasonal influenza viruses. The virus was still highly pathogenic to poultry and had a preference for avian receptor binding. Highlights: Various avian influenza virus (AIV) subtypes naturally have caused zoonotic infections, but the subtypes H5N1 and H7N9 have caused a prominent impact.At present, the outbreak of novel coronavirus pneumonia (coronavirus disease 2019 [COVID‐19]) has caused a worldwide pandemic.To our knowledge, this is the youngest child infected with H5N6 subtype avian influenza in Anhui Province.Herein, we analyzed the epidemiology of the case and the characteristics of the pathogen genome, to find out the possible evolution of the virus. [ABSTRACT FROM AUTHOR]

A novel multi-functional fluorescence nanosensor was developed by introducing carboxyl groups into graphitic carbon nitride. This oxidized graphitic carbon nitride nanoparticles (nano-CNO), which display enhanced fluorescence and water-solubility, exhibited sensitive and selective recognition of iodides and chromium(VI), with a limit of detection (LOD) as 12.4 and 9.6 nM, respectively. In the nano-CNO system containing iodides, the reversible quenching effect, switched by an acid–base reaction, was attributed to the hydrogen bonds established between the I− ions and the carboxyl groups of the nano-CNO, in conjunction with the effect of the heavy I− ion. This "on–off–on" nanosensor for I− (created by introducing no metal ions at all) is promising for potential use in applications in the field of biosensors. The mechanism of highly sensitive probe for Cr(VI) depends on inner filter effect (IFE) and collision quenching, which can also be turned on though the reduction of Cr(VI) by ascorbic acid (AA). Density functional theory (DFT) calculations shed light on the mechanism of the enhanced fluorescence intensity of nano-CNO and on the mechanism for detecting iodides. [ABSTRACT FROM AUTHOR]

Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the minority samples and generated high total accuracy meanwhile. The proposed approach makes CBR useful in imbalanced forecasting. [ABSTRACT FROM AUTHOR]

With the development of the Chinese economy, how to make the right decision regarding firms' risk is becoming more and more important. Case-based reasoning (CBR) is a potential method that can help forecast business risk status in advance; it is easy to apply and is able to provide good explanations of output. In order to obtain more accurate prediction with CBR, it is essential to investigate factors that influence CBR's performance, and to optimize these factors sequentially for the improvement of CBR's performance in firm risk prediction in emerging markets under a more practicable assumption. We verified that sequential optimization of feature selection, feature weighting, instance selection and the number of nearest neighbours is a possible alternative for improving predictive performance of CBR forecasting under the assumption that the number of failed samples is smaller than that of nonfailed samples. The detailed implementation includes: (1) selecting significant features through a correlation matrix and reducing feature dimensions with factor analysis; (2) using variance contribution ratios of features from factor analysis as feature weights; (3) eliminating noisy cases via a state matrix; and (4) obtaining the optimal number of nearest neighbours from empirical results among different numbers of nearest neighbours. To validate the usefulness of the sequential optimization approach, we applied it to a real-world case: firm risk prediction with imbalanced data from the emerging market of China. Experimental results show that predictive accuracy of CBR applied in the emerging market was improved with the sequential optimization approach. Insightful thoughts from the results of the sequential optimization of the CBR forecasting system on modelling social tasks are also provided. [ABSTRACT FROM AUTHOR]

To investigate and compare the clinical and imaging features among family members infected with COVID-19. We retrospectively collected a total of 34 COVID-19 cases (15 male, 19 female, aged 48 ± 16 years, ranging from 10 to 81 years) from 13 families from January 17, 2020 through February 15, 2020. Patients were divided into two groups: Group 1 - part of the family members (first-generation) who had exposure history and others (second-generation) infected through them, and Group 2 - patients from the same family having identical exposure history. We collected clinical symptoms, laboratory findings, and high-resolution computed tomography (HRCT) features for each patient. Comparison tests were performed between the first- and second-generation patients in Group 1. In total there were 21 patients in Group 1 and 20 patients in Group 2. For Group 1, first-generation patients had significantly higher white blood cell count (6.5 × 109/L (interquartile range (IQR): 4.9–9.2 × 109/L) vs 4.5 × 109/L (IQR: 3.7–5.3 × 109/L); P = 0.0265), higher neutrophil count (4.9 × 109/L (IQR: 3.6–7.3 × 109/L) vs 2.9 × 109/L (IQR: 2.1–3.3 × 109/L); P = 0.0111), and higher severity scores on HRCT (3.9 ± 2.4 vs 2.0 ± 1.3, P = 0.0362) than the second-generation patients. Associated underlying diseases (odds ratio, 8.0, 95% confidence interval: 3.4–18.7, P = 0.0013) were significantly correlated with radiologic severity scores in second-generation patients. Analysis of the family cluster cases suggests that COVID-19 had no age or sex predominance. Secondarily infected patients in a family tended to develop milder illness, but this was not true for those with existing comorbidities. • Family cluster is an important transmission route of COVID-19. • Secondarily infected cases are generally milder than the initially infected cases in family cluster cases. • Family members with a similar exposure history might have cross infection with each other. [ABSTRACT FROM AUTHOR]

Abstract: Excessive glutamatergic neurotransmission is considered an underlying factor of epilepsy. The modulation of the synaptic activity occurs both by the removal of glutamate from the synaptic cleft and by excitatory amino acid transporters (EAATs) and by modulation of glutamate receptors. The spontaneously epileptic rat (SER), a double mutant (zi/zi, tm/tm), exhibits both tonic convulsions and absence-like seizures from the age of 8 weeks. However, there are no reports that can elucidate the effects of EAATs and metabotropic glutamate receptors (mGluRs) in SER. The present study was undertaken to detect EAATs (GLAST, GLT-1 and EAAC-1) and Group I metabotropic glutamate receptors (mGluR1) in SER hippocampus from both the level of mRNA and protein in SERs hippocampus compared with control Wistar rats. In this study, the glutamate concentration in SERs hippocampus was increased compared with that of control rats by high performance liquid chromatography; the mRNA expressions of GLAST and mGluR1 in SERs hippocampus were significantly lower than those in control rats hippocampus, whereas an abundant increase in mRNA for GLT-1 was observed by RT-PCR; EAAC-1 and mGluR1 protein in SERs and control rats were localized widely in the hippocampus including CA1, CA3 and dentate gyrus regions by immunohistochemistry; the number of GLAST and mGluR1-positive cells in the hippocampus of SERs were less than those in control rats, especially for CA3 and DG region; the protein expression of GLT-1 was up-regulated, but the protein expressions of GLAST and mGluR1 were down-regulated in SER hippocampus by western blot. Our data show that epileptogenesis in SER are associated with regulations of glutamate transporters and mGluR1, which might be potential targets for therapy in genetic epilepsy. [Copyright &y& Elsevier]

Abstract Porous SiOC ceramic membranes (PSCM), with a narrow pore size distribution, were prepared by a casting method, using a polymer liquid (polydimethylsiloxane, PDMS), as a pore-forming agent, and a pre-ceramic liquid (polysiloxane, PSO), followed by pyrolysis at 1200 °C in flowing Ar gas. Pore size, porosity, and N 2 and water permeation increased with increasing PDMS content in the mixture of the precursors. An oil-in-water emulsion, with an average oil diameter of 0.83 μm, was effectively separated (95% rejection rate) with membranes which had an average pore size of 0.59 μm. PDMS was also used for membrane surface modification and the surfaces became super-hydrophobic. After modification, membranes with an average pore size of 0.95 μm were tested in sweeping gas membrane distillation. High salt rejection of 99.9% was achieved with NaCl solution (at various concentrations, 4–16 wt%) at several temperatures (55–85 °C). A stable performance was recorded for over 100 h, using 4 wt% NaCl in the feed at 75 °C. The produced membranes displayed clear separation and high efficiency in separation rates, which was reflected in the high permeation flux in both oil-in-water emulsion filtration and membrane distillation, attributed to the narrow pore size distribution. Graphical abstract Image 1 Highlights • Polymer-derived porous SiOC ceramic membranes were fabricated. • The membranes display a narrow pore size distribution. • They exhibit good performance in oil-water separation and membrane distillation. [ABSTRACT FROM AUTHOR]

Influenza-like illness (ILI) is one of the most important public health problems globally, causing an enormous disease burden. Influenza infections are the most common cause of ILI. Bacterial and virus co-infection is common yet the data of co-infection with influenza A and B viruses are scarce. To identify the epidemiological patterns of and co-infection of influenza A and B in Anhui province, China, we analyzed the surveillance data of 5 years from 2009 to 2014 collected by the Chinese National influenzas network. The results showed that the weekly ratio of ILI was 3.96 ± 1.9% (95% CI 3.73-4.2%) in outpatients and the highest affected population was children under 5 years old. The epidemic of influenza viruses was highest during 2009-2010. For the other 4 surveillance years, school-aged people (5-14 years) were the most highly affected population. Influenza B and H3N2 viruses were more prevalent than H1N1pdm09 virus after 2010. In addition, a significant co-circulation of influenza A (H1N1pdm09 and H3N2) and influenza B virus was detected with 0.057% PCR positive rate during 2009-2014 in Eastern China, yet isolated only in pediatric patients. Our data reveals school-aged population would be the main vulnerable population and a distinct seasonality for influenza. In addition, the co-infection of influenza A and B were found in Anhui Province, China. Ongoing surveillance is critical to understand the seasonality variation and make evidence-based vaccination recommendations. Information on the epidemiological patterns and co-infections of influenza A and B can help us to implement different strategies for selecting vaccine formulations and monitoring new emerging influenza strains. In addition, the identification of the susceptible population can help us to develop more precise protection measures., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 He, Hou, Chen, Yu, Chen, He, Liu, Gong, Huang, Wu, Pan and Gao.)

Detection of serum-specific SARS-CoV-2 antibody has become a complementary means for the identification of coronavirus disease 2019 (COVID-19). As we already know, the neutralizing antibody titers in patients with COVID-19 decrease during the course of time after convalescence, whereas the duration of antibody responses in the convalescent patients has not been defined clearly. In the current study, we collected 148 serum samples from 37 confirmed COVID-19 cases with different disease severities. The neutralizing antibodies (Nabs), IgM and IgG against COVID-19 were determined by CLIA Microparticle and microneutralization assay, respectively. The time duration of serum titers of SARS-CoV-2 antibodies were recorded. Our results indicate that IgG (94.44%) and Nabs (89.19%) can be detected at low levels within 190-266 days of disease onset. The findings can advance knowledge regarding the antibody detection results for COVID-19 patients and provide a method for evaluating the immune response after vaccination., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Chen, Gong, Wu, Feng, Luo, Zhou, Yuan, Yu, He, Wang, Ge, Hou, Li, Sun, Wu, Su, Pan, He and Liu.)

Background and Aims: H9N2 subtype avian influenza virus (AIV) has low-pathogenicity but causes respiratory symptoms and drop in egg production in chicken with long-term virus shedding, resulting in great economic losses due to high mortality related to secondary infection with other pathogens. In recent years, H9N2 viruses have been posing a threat to public health, causing human infection in China. Compared to studies on other AIV subtypes, there are relatively few studies on the pathogenic mechanism of the H9N2 virus in mammals. H9N2 subtype AIV has been circulating worldwide in many avian species and transmitting with high efficiency in poultry. It can provide internal genes for other subtypes to produce new viruses, causing a pandemic risk. It is important to carry out long-term surveillance and pathogenic characteristics of the H9N2 virus. In this study, we conducted environmental surveillance of live poultry markets in Anhui province from 2013 to 2018, and 33 representative environmental isolates were selected and studied systematically., Methods: The genomic RNA of Anhui H9N2 isolates was subjected to RT-PCR amplification followed by sequencing analysis., Results: Thirty-three strains were isolated from the embryonated eggs of specific-pathogen-free chickens. Phylogenetic analysis indicated that h9.4.2.5-like H9N2 viruses were predominant during 2013-2018 and acquired multiple specific amino acid mutations that may have increased their affinity for mammals and enhanced their infectivity and transmissibility. Additionally, six internal genes of H9N2 clustered together with the novel human-lethal reassortant viruses, such as the low-pathogenicity H7N9, H10N8, and Anhui H5N6 viruses, and even HPAI H7N9., Conclusion: Because H9N2 viruses may be the donors of internal genes that lead to the generation of novel reassortant viruses with enhanced pathogenicity in Anhui province, continuous environmental surveillance of live poultry markets, a key source of reassorted H9N2 and other avian influenza viruses, is of great importance., Competing Interests: The authors declare no conflicts of interest., (© 2021 The Authors. Health Science Reports published by Wiley Periodicals LLC.)