Distributed eQTL analysis with auxiliary information.

Expression quantitative trait locus (eQTL) analysis is a useful tool to identify genetic loci that are associated with gene expression levels. Large collaborative efforts such as the Genotype-Tissue Expression (GTEx) project provide valuable resources for eQTL analysis in different tissues. Most existing methods, however, either focus on one tissue at a time, or analyze multiple tissues to identify eQTLs jointly present in multiple tissues. There is a lack of powerful methods to identify eQTLs in a target tissue while effectively borrowing strength from auxiliary tissues. In this paper, we propose a novel statistical framework to improve the eQTL detection efficacy in the tissue of interest with auxiliary information from other tissues. This framework can enhance the power of the hypothesis test for eQTL effects by incorporating shared and specific effects from multiple tissues into the test statistics. We also devise data-driven and distributed computing approaches for efficient implementation of eQTL detection when the number of tissues is large. Numerical studies in simulation demonstrate the efficacy of the proposed method, and the real data analysis of the GTEx example provides novel insights into eQTL findings in different tissues.

Super-amphiphobic arabic gum-based coatings on textile for on-demand oily and dye wastewater treatment.

Different membrane materials have broadly been constructed for oil-containing water separation, but most of preparation routes involve corrosive or toxic chemicals and especially many materials have only single superwetting property. Herein, a novel and eco-friendly cellulose-based textile membrane is developed by incorporating the composite coating consisting of arabic gum (AG), attapulgite (APT), and iron (Fe) onto cellulose textiles. The functionalized textile is superoleophobic underwater and superhydrophobic underoil. As a result, the textile prewetted with water or oil can be employed to separate light oil layer/water and heavy oil layer/water mixtures, respectively, and the separation efficiency to the two types of mixtures is larger than 98.3 %. Results also reveal that the decorated textile possesses superior stability and recyclability in purifying oily wastewater. More importantly, such coated textile is capable of filtrating water-soluble contaminants (dyes) from polluted water. Due to the versatility and environmental compatibility of product as well as the accessibility as agricultural and forestry product as raw materials, the advanced textiles may offer effective solutions to oily wastewater purification and water-soluble contaminant removal.

Durably dual superlyophobic cationic guar gum­calcium complex decorated cellulose fabrics for on-demand oil/water separation.

The removal to oils from water has become a global issue because of the growing of wastewater discharge and unceasing appearance of oil leaks. Herein, a kind of durably dual superlyophobic (superhydrophobic under oil and superoleophobic under water) cotton fabric (CF) was fabricated via simple assembly route that introduced guar hydroxypropyltrimonium chloride­calcium (GHTC-Ca) chelate compound on the fabric surface. The coated CF exhibits good resistance to mechanical abrasion, corrosive aqueous solution, high temperature, and organic solvent immersion. Furthermore, due to prewetting-caused superoleophobicity underwater and superhydrophobicity underoil, the as-prepared CF can selectively separate both heavy oils and light oils in water under extremely harsh conditions with separation efficiencies as high as 98.7 % and 98.4 %, respectively. More importantly, the as-prepared fabrics are able to remove dispersed oil droplets from oil-in-water emulsions and water droplets from water-in-oil emulsions with separation efficiency of over 89 % and 91.4 %, respectively. Hence, this prominent separation performance suggests a good application prospect of GHTC-Ca functionalized CF in oily water purification.

Efficacy of neurointerventional therapy in patients with ischemic stroke and risk factors affecting cognitive function recovery.

OBJECTIVE: To investigate the efficacy of neurointervention combined with intravenous thrombolysis in ischemic stroke patients and the risk factors affecting cognitive function recovery. METHODS: A total of 114 patients with acute ischemic stroke (AIS) treated in Baoji People's Hospital from January 2017 to December 2020 were retrospectively selected and divided into an observation group and a control group according to different treatment methods. The observation group was treated with neurointervention + intravenous thrombolysis (n = 64), and the control group underwent intravenous thrombolysis (n = 50). The efficacy, recanalization rate, incidence of adverse events, National Institutes of Health Stroke Scale (NIHSS) score, Mini-Mental State Examination (MMSE) score and modified Rankin Scale (mRS) score were evaluated and compared between the two groups. Patients were further divided into a cognitive dysfunction group and a non-disorder group according the MMSE score after treatment, and logistics regression was used to analyze the risk factors of cognitive dysfunction. RESULTS: The overall response rate and the total recanalization rate of the observation group were significantly higher than those of the control group (both P < 0.05). Compared with those before operation, the NIHSS score at 7 d after operation and the mRS score 3 months after operation decreased, while the MMSE score increased in both groups (P < 0.05). The postoperative NIHSS score and mRS score were lower and MMSE score was higher in the observation group than those in the control group (P < 0.05). No significant difference was identified in the incidence of adverse events between the two groups (P > 0.05). Logistics regression analysis revealed that age, diabetes mellitus, hyperlipidemia and lesions at critical sites were independent risk factors for cognitive impairment in patients with AIS. CONCLUSION: Interventional thrombectomy combined with intravenous thrombolysis is effective in the treatment of cerebral infarction. This regimen can reduce neurological deficits and improve the recanalization rate. In addition, age, diabetes, hyperlipidemia and lesions at critical sites are independent risk factors for the development of cognitive impairment in AIS patients.

Generalized fiducial methods for testing the homogeneity of a three-sample problem with a mixture structure.

Recently, the likelihood ratio (LR) test was proposed to test the homogeneity of a three-sample model with a mixture structure. Because of the presence of the mixture structure, the null limiting distribution of the LR test has a complicated supremum form, which leads to challenges in determining p-values. In addition, the LR test cannot control type-I errors well under small to moderate sample size. In this paper, we propose seven generalized fiducial methods to test the homogeneity of the three-sample model. Via simulation studies, we find that our methods perform significantly better than the LR test method in controlling the type-I errors under small to moderate sample size, while they have comparable powers in most cases. A halibut data example is used to illustrate the proposed methods.

Online monitoring of high-dimensional binary data streams with application to extreme weather surveillance.

With the rapid development of modern sensor technology, high-dimensional data streams appear frequently nowadays, bringing urgent needs for effective statistical process control (SPC) tools. In such a context, the online monitoring problem of high-dimensional and correlated binary data streams is becoming very important. Conventional SPC methods for monitoring multivariate binary processes may fail when facing high-dimensional applications due to high computational complexity and the lack of efficiency. In this paper, motivated by an application in extreme weather surveillance, we propose a novel pairwise approach that considers the most informative pairwise correlation between any two data streams. The information is then integrated into an exponential weighted moving average (EWMA) charting scheme to monitor abnormal mean changes in high-dimensional binary data streams. Extensive simulation study together with a real-data analysis demonstrates the efficiency and applicability of the proposed control chart.

The complete chloroplast genome of 'Yulinglong' (Narcissus tazetta var. chinensis) with double-petaled in southeast of China.

In this study, the complete chloroplast (cp) genome of Narcissus tazetta var. chinensis cv 'Yulinglong' was sequenced and assembled by next-generation sequencing. The complete cp genome is 159,376 in length and contained 137 genes, consisting of 91 protein-coding genes, eight ribosomal RNA genes, and 38 transfer RNA genes. Phylogenetic analyses based on chloroplast genomes highly supported that 'Yulinglong' was evolutionarily close to Narcissus tazetta subsp.chinensis, which may provide more desirable information for the phylogenetic relationship between Narcissus tazetta var. chinensis and its relative species.

One Stone, Two Birds: pH- and Temperature-Sensitive Nitrogen-Doped Carbon Dots for Multiple Anticounterfeiting and Multiple Cell Imaging.

Carbon dots (CDs) as new fluorescent materials with excellent fluorescence properties have shown enormous potential applications, especially in anticounterfeiting and cell imaging. Herein, nitrogen-doped CDs (NCDs) with excellent biocompatibility were prepared by a simple thermal sintering method. An extremely large red shift (∼130 nm) of the emission peak was observed when the excitation wavelength changes from 355 to 550 nm, indicating that NCDs are excellent fluorescent labeling materials for multiple cell imaging. On the other hand, NCDs showed obvious changes of emission intensity and peak position when the temperature increased from 223 to 323 K and the pH values changed from 1 to 13, respectively, which has been demonstrated by the "horse" pattern printed with NCD water-soluble fluorescent inks. The nontoxic NCDs dispersed in a multiple matrix are highly sensitive to excitation wavelength, temperature, and pH, indicating their great potential application in multiple anticounterfeiting and multiple cell imaging.

EM-test for homogeneity in a two-sample problem with a mixture structure.

In many applications such as case-control studies with contaminated controls, or the test of a treatment effect in the presence of nonresponders in biological experiments or clinical trials, a two-sample problem with one of the samples having a mixture structure often arises. Due to the importance and wide applications of scale mixtures and location mixtures, we consider in this paper the case that the component densities differ only in scale parameters and the case that the component densities differ only in location parameters, and further construct an EM-test for the two-sample problem under each case. We show that both the EM-tests possess a chi-squared null limiting distribution. The local power analysis and sample size calculations are also investigated. Finally, the simulation studies and real data analysis demonstrate that the proposed EM-tests have better performance than the existing methods.