DCMD: Distance-based Classification Using Mixture Distributions on Microbiome Data

Current advances in next generation sequencing techniques have allowed researchers to conduct comprehensive research on microbiome and human diseases, with recent studies identifying associations between human microbiome and health outcomes for a number of chronic conditions. However, microbiome data structure, characterized by sparsity and skewness, presents challenges to building effective classifiers. To address this, we present an innovative approach for distance-based classification using mixture distributions (DCMD). The method aims to improve classification performance when using microbiome community data, where the predictors are composed of sparse and heterogeneous count data. This approach models the inherent uncertainty in sparse counts by estimating a mixture distribution for the sample data, and representing each observation as a distribution, conditional on observed counts and the estimated mixture, which are then used as inputs for distance-based classification. The method is implemented into a k-means and k-nearest neighbours framework and we identify two distance metrics that produce optimal results. The performance of the model is assessed using simulations and applied to a human microbiome study, with results compared against a number of existing machine learning and distance-based approaches. The proposed method is competitive when compared to the machine learning approaches and showed a clear improvement over commonly used distance-based classifiers. The range of applicability and robustness make the proposed method a viable alternative for classification using sparse microbiome count data.Comment: 27 pages, 3 figure

An Efficient Process for Pretreatment of Lignocelluloses in Functional Ionic Liquids

Background and Aims. The complex structure of the lignocelluloses is the main obstacle in the conversion of lignocellulosic biomass into valuable products. Ionic liquids provide the opportunities for their efficient pretreatment for biomass. Therefore, in this work, pretreatment of corn stalk was carried out in ultrasonic-assisted ionic liquid including 1-butyl-3-methylimidazolium chloride [BMIM]Cl, 1-H-3-methylimidazolium chloride [HMIM]Cl, and 1-(1-propylsulfonic)-3-imidazolium chloride [HSO3-pMIM]Cl at 70°C for 2 h. We compared the pretreatments by ionic liquid with and without the addition of deionized water. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) were employed to analyze the chemical characteristics of regenerated cellulose-rich materials. Results. [HMIM]Cl and [HSO3-pMIM]Cl were effective in lignin extraction to obtain cellulose-rich materials. FTIR analysis and SEM analysis indicated the effective lignin removal and the reduced crystallinity of cellulose-rich materials. Enzymatic hydrolysis of cellulose-rich materials was performed efficiently. High yields of reducing sugar and glucose were obtained when the corn stalk was pretreated by [HMIM]Cl and [HSO3-pMIM]Cl. Conclusions. Ionic liquids provided the ideal environment for lignin extraction and enzymatic hydrolysis of corn stalk and [HMIM]Cl and [HSO3-pMIM]Cl proved the most efficient ionic liquids. This simple and environmentally acceptable method has a great potential for the preparation of bioethanol for industrial production

Bayesian parameter estimation of massive black hole binaries with TianQin-LISA

This paper analyses the impact of various parameter changes on the estimation of parameters for massive black hole binary (MBHB) systems using a Bayesian inference technique. Several designed MBHB systems were chosen for comparison with a fiducial system to explore the influence of parameters such as sky location, inclination angle, anti-spin, large mass ratio and light mass. And the two reported MBHB candidates named OJ287 and Tick-Tock are also considered. The study found that the network of TianQin and LISA can break certain degeneracies among different parameters, improving the estimation of parameters, particularly for extrinsic parameters. Meanwhile, the degeneracies between different intrinsic parameters are highly sensitive to the value of the parameters. Additionally, the small inclination angles and limited detection of the inspiral phase can introduce significant bias in the estimation of parameters. The presence of instrument noise will also introduce bias and worsen the precision. The paper concludes that the network of TianQin and LISA can significantly improve the estimation of extrinsic parameters by about one order of magnitude while yielding slight improvements in the intrinsic parameters. Moreover, parameter estimation can still be subject to biases even with a sufficiently high signal-to-noise ratio if the detected signal does not encompass all stages of the inspiral, merger, and ringdown.Comment: 17 pages, 10 figure

Effects of different stocking densities on the CO2 fluxes at water-air interface and the respiration metabolism in sea cucumber Apostichopus japonicus (Selenka)

Recently, abundant research has been devoted to investigating the variations of CO2 concentration in the atmosphere. However, the information of CO2 fluxes at the water-air interface remains limited, especially those from the respiratory metabolism of aquatic organisms. In the present study, a comprehensive analysis was carried out to evaluate the effects of different stocking densities of sea cucumber (Apostichopus japonicus) on the CO2 fluxes at water-air interface, and to explore the relationships between CO2 fluxes and respiratory metabolism. A total of 60 sea cucumbers were randomly classified into 4 groups with different stocking densities, including 2, 5 and 8 ind./tank (namely D2, D5 and D8 groups). After 34-day feeding trial, individuals in D5 had superior growth performance rather than D2 and D8. The analysis of modified floating static chambers clearly showed that the mean CO2 flux at the water-air interface in D5 was significantly higher than D2 and D8. Meanwhile, energy budget analysis revealed that D5 had higher carbon and nitrogen utilization, excretion energy and metabolizable energy, suggesting relatively active respiration metabolism in moderate stocking density. The activities of pyruvate dehydrogenase (PDH) and α-ketoglutarate dehydrogenase (OGDH) in respiratory tree and body wall tissues provided additional evidence for the higher respiration metabolism rate of individuals at D5, which may be responsible for the higher CO2 fluxes at the water-air interface. Transcriptome analysis was performed to uncover the molecular mechanism of respiratory metabolism affected by different stocking densities. The differentially expressed genes in respiration trees and body walls were significantly enriched in peroxisome, fatty acid degradation, and oxidative phosphorylation pathways. It may explain the differences of respiration metabolism rates at different stocking densities. The present study preliminarily revealed the CO2 fluxes variation at the water-air interface from aquatic invertebrates, and provided the scientific basis for the efficient and low-carbon agricultural technologies of sea cucumber

The roles of serum vitamin D and tobacco smoke exposure in insomnia: a cross-sectional study of adults in the United States

AimTobacco smoke exposure and vitamin D (VD) status were both associated with insomnia. However, the combined effect of smoking and VD on insomnia has not been discussed. This study aimed to explore the role of VD in the association between tobacco smoke exposure and insomnia.MethodsData on adults were extracted from the National Health and Nutrition Examination Surveys (NHANES) database in 2005–2008 for this cross-sectional study. Weighted univariate and multivariate logistic regression analyses were used to explore the associations between serum cotinine, serum VD, and insomnia. A surface diagram was drawn to reflect the effect of VD on the association between serum cotinine and insomnia. In addition, the potential regulating effect of VD in subgroups of smoking status was also performed. The evaluation index was odds ratios (ORs) with 95% confidence intervals (CIs).ResultsAmong the eligible participants, 1,766 had insomnia. After adjusting for covariates, we found that elevated serum cotinine levels were associated with higher odds of insomnia [OR = 1.55, 95% CI: (1.22, 1.97)]. However, the relationship between serum VD level and insomnia was not significant (P = 0.553). Higher serum cotinine levels were also associated with higher odds of insomnia [OR = 1.52, 95% CI: (1.17, 1.98)] when serum VD level was <75 nmol/L; however, this relationship became non-significant when serum VD concentration was elevated (P = 0.088). Additionally, the potential regulating effect of VD was also found in adults who were not smoking.ConclusionVD may play a potential regulative role in the association between tobacco smoke exposure and insomnia. Further studies are needed to clarify the causal relationships between VD, tobacco smoke exposure, and insomnia

3-[(E)-2-Chloro-3,3,3-trifluoro­prop-1-en-1-yl]-N-(2-fluoro­phen­yl)-2,2-dimethyl­cyclo­propane-1-carboxamide

The phenyl ring in the title compound, C15H14ClF4NO, makes a dihedral angle of 80.3 (3)° with the cyclo­propane ring. In the crystal, mol­ecules are linked by N—H⋯O hydrogen bonds into chains running along the a axis

Involvement and therapeutic implications of airway epithelial barrier dysfunction in type 2 inflammation of asthma

Type 2 inflammation is a complex immune response and primary mechanism for several common allergic diseases including allergic rhinitis, allergic asthma, atopic dermatitis, and chronic rhinosinusitis with nasal polyps. It is the predominant type of immune response against helminths to prevent their tissue infiltration and induce their expulsion. Recent studies suggest that epithelial barrier dysfunction contributes to the development of type 2 inflammation in asthma, which may partly explain the increasing prevalence of asthma in China and around the globe. The epithelial barrier hypothesis has recently been proposed and has received great interest from the scientific community. The development of leaky epithelial barriers leads to microbial dysbiosis and the translocation of bacteria to inter- and sub-epithelial areas and the development of epithelial tissue inflammation. Accordingly, preventing the impairment and promoting the restoration of a deteriorated airway epithelial barrier represents a promising strategy for the treatment of asthma. This review introduces the interaction between type 2 inflammation and the airway epithelial barrier in asthma, the structure and molecular composition of the airway epithelial barrier, and the assessment of epithelial barrier integrity. The role of airway epithelial barrier disruption in the pathogenesis of asthma will be discussed. In addition, the possible mechanisms underlying the airway epithelial barrier dysfunction induced by allergens and environmental pollutants, and current treatments to restore the airway epithelial barrier are reviewed