Proteomics evaluation of five economical commercial abundant protein depletion kits for enrichment of diseases-specific biomarkers from blood serum.

Blood serum is arguably the most analyzed biofluid for disease prediction and diagnosis. Herein, we benchmarked five different serum abundant protein depletion (SAPD) kits with regard to the identification of disease-specific biomarkers in human serum using bottom-up proteomics. As expected, the IgG removal efficiency among the SAPD kits is highly variable, ranging from 70% to 93%. A pairwise comparison of database search results showed a 10%-19% variation in protein identification among the kits. Immunocapturing-based SAPD kits against IgG and albumin outperformed the others in the removal of these two abundant proteins. Conversely, non-antibody-based methods (i.e., kits using ion exchange resins) and kits leveraging a multi-antibody approach were proven to be less efficient in depleting IgG/albumin from samples but led to the highest number of identified peptides. Notably, our results indicate that different cancer biomarkers could be enriched up to 10% depending on the utilized SAPD kit compared with the undepleted sample. Additionally, functional analysis of the bottom-up proteomic results revealed that different SAPD kits enrich distinct disease- and pathway-specific protein sets. Overall, our study emphasizes that a careful selection of the appropriate commercial SAPD kit is crucial for the analysis of disease biomarkers in serum by shotgun proteomics.

Digital economy and pollution reduction-Mechanism and regional heterogeneity.

The digital economy and ecological environment are two major issues related to high-quality economic development. Scholars have not yet reached a unified conclusion about the link between the digital economy and pollution emissions, and the impact mechanism of the former on the latter needs further study. Using data from 278 Chinese cities from 2010 to 2019, this research employs coupling coordination analysis, fixed effect analysis and mediation analysis to examine the heterogeneous impact mechanisms of the expansion of the digital economy on urban pollution reduction from many angles. It discovers that, first, the growth of the digital economy has decreased the discharge of urban pollutants overall. Second, the impact mechanisms of the digital economy are heterogeneous. From a regional perspective, industrial structure supererogation plays an intermediary role in the relationship between digital economy development and pollution reduction in the eastern and central regions, but the mediating effect is not significant in the western and northeastern regions. In terms of the city development level, industrial structure supererogation has significantly mediated the relationship between the growth of the digital economy and the reduction of pollution in first- and second-tier cities, but this mediating effect is not significant in third-tier and other cities. Third, the above conclusions are still valid after the robustness test is carried out using instrumental variable estimation, replacement of the estimation method, and replacement of explanatory variables. This study is a useful contribution to research on the effects of the digital economy and the factors influencing pollution reduction. The results advance the study of the digital economy and also have practical implications for improving China's ecological environment and fostering high-quality economic growth. Finally, we provide policy suggestions for the coordinated promotion of the digital economy's development, industrial structure supererogation and environmental pollution reduction.

A simple and economical site-directed mutagenesis method for large plasmids by direct transformation of two overlapping PCR fragments.

Despite the development of various methods and commercial kits, site-directed mutagenesis of large plasmids remains a challenge in many laboratories. A site-directed mutagenesis method was developed for large plasmids by directly transforming two overlapping PCR fragments into Escherichia coli. This method successfully generated mutations for plasmids of 8.3 kb and 11.0 kb with high efficiencies. The method only requires Q5 DNA polymerase and DpnI, which greatly reduces costs. The procedure is simple, including PCR reaction, DpnI treatment and transformation. This simple, efficient and economical site-directed mutagenesis method for large plasmids is likely to be widely applied in the future.

The Longer the Storage Time, the Higher the Price, the Better the Quality? A 1H-NMR Based Metabolomic Investigation of Aged Ya'an Tibetan Tea (Camellia sinensis).

As an essential beverage beneficial for Tibetan people, Ya'an Tibetan tea has received scarce attention, particularly from the point of view of the characterization of its metabolome. The aim of the study is to systematically characterize the metabolome of Tibetan tea by means of untargeted 1H-NMR. Moreover, the variations of its metabolome along ageing time are evaluated by taking advantage of univariate and multivariate analyses. A total of 45 molecules are unambiguously identified and quantified, comprising amino acids, peptides and analogues, carbohydrates and derivates, organic acids and derivates, nucleosides, nucleotides and catechins. The concentrations of amino acids, organic acids, carbohydrates and catechins are mainly determined by ageing time. The present study would serve as a reference guide for further work on the Ya'an Tibetan tea metabolome, therefore contributing to the related industries.

Bearing Performance Degradation Assessment Based on SC-RMI and Student's t-HMM.

Bearing performance degradation assessment (PDA), as an important part of prognostics and health management (PHM), is significant to prevent major accidents and economic losses in industry. For the data-driven PDA, the extraction and selection of features is quite important. To better integrate the degradation information, the bearing performance degradation assessment based on SC-RMI and Student's t-HMM is proposed in this article. Firstly, spectral clustering was used as a preprocessing step to cluster features with similar degradation curves. Then, rank mutual information, which is more suitable for trendability estimation of long time series, was utilized to select the optimal feature from each cluster. The feature selection method based on these two steps is called SC-RMI for short. With the selected features, Student's t-HMM, which is more robust to outliers, was utilized for performance degradation modeling and assessment. The verifications based on an accelerated life test and the public XJTU-SY dataset showed the superiority of the proposed method.

MicroRNA-146a and miR-99a are potential biomarkers for disease activity and clinical efficacy assessment in psoriasis patients treated with traditional Chinese medicine.

ETHNOPHARMACOLOGICAL RELEVANCE: Psoriasis is a common chronic inflammatory skin disease. A number of clinical investigations have indicated that traditional Chinese medicine (TCM) is an effective and safe treatment for psoriasis. Zhuhuang Granule (ZG) is a modified formulation of Zhuhuang Decoction, which is used traditionally in China for the treatment of psoriasis in clinical practice. AIM OF THE STUDY: Recent studies have found that microRNAs (miRNAs) play important roles in the pathogenesis of some skin diseases. The objective of our study was to investigate the effect of ZG on the expression of miRNAs in peripheral blood mononuclear cells (PBMCs) from psoriasis patients and to identify specific miRNA biomarkers for psoriasis disease activity and assessment of clinical efficacy. MATERIALS AND METHODS: Twenty-five psoriasis patients and 15 healthy control subjects were recruited to participate in this study from October 2013 to October 2014. Microarray and quantitative real-time PCR (qRT-PCR) were used to measure the global miRNA expression in PBMCs from psoriasis patients and healthy control subjects. We also measured the changes in the Psoriasis Area and Severity Index (PASI) score and miRNA expression of patients before and after treatment with ZG. RESULTS: The microarray results showed that 26 miRNAs were upregulated and 13 miRNAs were decreased in psoriasis patients. qRT-PCR validated 3 upregulated miRNAs (miR-146a, miR-31, miR-192-5p) and 2 downregulated miRNAs (miR-99a, miR-200c) in PBMCs from psoriasis patients compared with healthy controls (p<0.01). Moreover, after 8 weeks of ZG treatment, patients achieved a significant reduction in PASI scores. QRT-PCR analysis indicated that the expression of miR-146a and miR-99a is closely correlated with psoriasis severity (R2=0.772, p<0.01; R2=0.672, p<0.01). CONCLUSION: We suggest that both miR-146a and miR-99a may serve as potential biomarkers for disease activity and clinical efficacy in psoriasis patients treated with ZG.

Quantitative damage detection and sparse sensor array optimization of carbon fiber reinforced resin composite laminates for wind turbine blade structural health monitoring.

The active structural health monitoring (SHM) approach for the complex composite laminate structures of wind turbine blades (WTBs), addresses the important and complicated problem of signal noise. After illustrating the wind energy industry's development perspectives and its crucial requirement for SHM, an improved redundant second generation wavelet transform (IRSGWT) pre-processing algorithm based on neighboring coefficients is introduced for feeble signal denoising. The method can avoid the drawbacks of conventional wavelet methods that lose information in transforms and the shortcomings of redundant second generation wavelet (RSGWT) denoising that can lead to error propagation. For large scale WTB composites, how to minimize the number of sensors while ensuring accuracy is also a key issue. A sparse sensor array optimization of composites for WTB applications is proposed that can reduce the number of transducers that must be used. Compared to a full sixteen transducer array, the optimized eight transducer configuration displays better accuracy in identifying the correct position of simulated damage (mass of load) on composite laminates with anisotropic characteristics than a non-optimized array. It can help to guarantee more flexible and qualified monitoring of the areas that more frequently suffer damage. The proposed methods are verified experimentally on specimens of carbon fiber reinforced resin composite laminates.