Appendicular lean mass and the risk of stroke and Alzheimer's disease: a mendelian randomization study.

BACKGROUND: Appendicular lean mass (ALM) is a good predictive biomarker for sarcopenia. And previous studies have reported the association between ALM and stroke or Alzheimer's disease (AD), however, the causal relationship is still unclear, The purpose of this study was to evaluate whether genetically predicted ALM is causally associated with the risk of stroke and AD by performing Mendelian randomization (MR) analyses. METHODS: A two-sample MR study was designed. Genetic variants associated with the ALM were obtained from a large genome-wide association study (GWAS) and utilized as instrumental variables (IVs). Summary-level data for stroke and AD were generated from the corresponding GWASs. We used random-effect inverse-variance weighted (IVW) as the main method for estimating causal effects, complemented by several sensitivity analyses, including the weighted median, MR-Egger, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods. Multivariable analysis was further conducted to adjust for confounding factors, including body mass index (BMI), type 2 diabetes mellitus (T2DM), low density lipoprotein-C (LDL-C), and atrial fibrillation (AF). RESULTS: The present MR study indicated significant inverse associations of genetically predicted ALM with any ischemic stroke ([AIS], odds ratio [OR], 0.93; 95% confidence interval [CI], 0.89-0.97; P = 0.002) and AD (OR, 090; 95% CI 0.85-0.96; P = 0.001). Regarding the subtypes of AIS, genetically predicted ALM was related to the risk of large artery stroke ([LAS], OR, 0.86; 95% CI 0.77-0.95; P = 0.005) and small vessel stroke ([SVS], OR, 0.80; 95% CI 0.73-0.89; P < 0.001). Regarding multivariable MR analysis, ALM retained the stable effect on AIS when adjusting for BMI, LDL-C, and AF, while a suggestive association was observed after adjusting for T2DM. And the estimated effect of ALM on LAS was significant after adjustment for BMI and AF, while a suggestive association was found after adjusting for T2DM and LDL-C. Besides, the estimated effects of ALM were still significant on SVS and AD after adjustment for BMI, T2DM, LDL-C, and AF. CONCLUSIONS: The two-sample MR analysis indicated that genetically predicted ALM was negatively related to AIS and AD. And the subgroup analysis of AIS revealed a negative causal effect of genetically predicted ALM on LAS or SVS. Future studies are required to further investigate the underlying mechanisms.

Supplement of Caulerpa lentillifera polysaccharide by pre-prandial gavage and free feeding demonstrates differences to prevent obesity and gut microbiota disturbance in mice.

BACKGROUND: Caulerpa lentillifera has received extensive attention regarding expansion of its farming and increasing consumption. In our previous study, the structure of C. lentillifera polysaccharide (CLP) was elucidated. However, little information is available about its health effects. In this study, the anti-obesity effect of CLP was investigated by using a high-fat diet-induced obese mice model with two different supplementation methods. RESULTS: In vitro simulated digestion results showed that CLP significantly decreased the lipid digestibility and induced the lipid droplets aggregation in the intestinal stage to inhibit the absorption of lipids. As revealed by 16S ribosomal RNA sequencing and non-targeted metabolomics, supplement of CLP by both pre-prandial gavage and free feeding patterns effectively prevented mice obesity via ameliorating intestinal flora disturbance and regulating bile acids circulation metabolism. Of note was that CLP administration had no effect on short-chain fatty acids production, suggesting the anti-obesity effect was uncorrelated with their production. Moreover, pre-prandial administration of CLP had a better anti-obesity effect in lowering body weight and serum lipid levels, but the free feeding resulted in a higher α-diversity of gut microbiota. CONCLUSION: The findings of this study indicate that CLP could be a potential anti-obesity nutraceutical and that pre-prandial supplement of CLP may be a better intake method to exhibit its hypolipidemic effect. © 2022 Society of Chemical Industry.

[Mammalian DMRTs: Structure, function and relationship with cancer].

DMRT, a gene family related to sexual determination, encodes a large group of transcription factors (DMRTs) with the double-sex and mab-3 (DM) domain (except for DMRT8), which is able to bind to and regulate DNAs. Current studies have shown that the DMRT gene family plays a critical role in the development of sexual organs (such as gender differentiation, gonadal development, germ cell development, etc.) as well as extrasexual organs (such as musculocartilage development, nervous system development, etc.). Additionally, it has been suggested that DMRTs may be involved in the cancer development and progression (such as prostate cancer, breast cancer, lung cancer, etc.). This review summarizes the research progress about the mammalian DMRTs' structure, function and its critical role in cancer development, progression and therapy (mainly in human and mice), which suggests that DMRT gene could be a candidate gene in the study of tumor formation and therapeutic strategy.

Quasi-omnidirectional retroreflective metagrating for TE-polarized waves based on wave-vector reversions.

Structuring elements of gratings brings more freedom in manipulating diffraction waves, e.g., retroreflection using diffraction orders other than the 0th order. Most retroreflective metagratings (RMs) can achieve retroreflection only under one particular direction, limiting their applications. In this paper, we propose a quasi-omnidirectional RM based on wave-vector reversion for TE-polarized waves. The metagrating element is composed of four rotationally-symmetric sub-elements, which is composed of one probe and two directors on its two sides. The substrate-air-metal layer can reverse kz while directors can reverse kx. Therefore, the wave-vector k of reflected waves can be completely reversed by the sub-element, providing necessary momentum for retroreflection. The -2nd diffraction order of the metagrating is tailored to channel out waves with reversed k, leading to retroreflection. Due to the element's four-fold rotational symmetry, retroreflection can be achieved along four directions, covering all of the four quarters of azimuth angle. We demonstrate prototypes in Ku band, and the average backscattering enhancement compared with a metal plane with the same area (SAMP) along the four directions reaches up to 31.3 dB with incident angle 50.0° at 15.0 GHz. Both simulated and measured results verify our design. This work provides another perspective on retroreflection and may find applications in retroreflective functional devices.

Fluxes, characteristics and influence on the aquatic environment of inorganic nitrogen deposition in the Danjiangkou reservoir.

Atmospheric reactive nitrogen (Nr) deposition has caused serious damage to the terrestrial and freshwater ecosystems and also affected human health. Measuring temporal and spatial characteristics of Nr deposition is critical for proposing control strategy to decrease negative effects. We investigated the fluxes of ammonia nitrogen (NH4-N) and nitrate nitrogen (NO3-N) in both dry and wet deposition from October 2017 to September 2020 at six sites around the Danjiangkou reservoir. The results showed that the fluxes of dissolved inorganic nitrogen (DIN) decreased from 24.39 kg ha-1 yr-1 (2017-2018) to 16.11 kg ha-1 yr-1 (2019-2020) for dry deposition, and from 19.71 kg ha-1 yr-1 (2017-2018) to 12.29 kg ha-1 yr-1 (2019-2020) for wet deposition. Both NH4-N and NO3-N in wet deposition exhibited significant (P < 0.01) differences among four seasons, and were markedly influenced by the precipitation. The fluxes of NO3-N deposition showed significant (P < 0.05) difference among six samples. Dry component contributed more to total DIN deposition, and NH4-N was the dominant species in DIN deposition. The ratios of NH4-N to NO3-N in four seasons were higher than 2. A positive matrix factorization (PMF) model estimated that the factors of agriculture and fossil fuel combustion accounted for 77.1 % and 17.0 %, respectively, to the dry NH4-N deposition; and that the factors of agricultural source and biomass burning accounted for 56.2 % and 21.1 %, respectively, to the wet NH4-N deposition. The DIN deposition contributed to 7.7 % of the total Nr input into the reservoir, and the contribution of DIN deposition to the increase in the nitrogen concentration (ΔN) of the Danjiangkou reservoir was 0.13 mg L-1 yr-1. The dry DIN deposition was significantly correlated with the concentration of nitrogen in Danjiangkou reservoir (P < 0.01). This study suggested that the control measures of agricultural activity were essential to reduce Nr deposition, and to decrease the potential risks of water pollution in the reservoir. Furthermore, more long-term study is necessary to understand the relation between control measures, Nr deposition and water quality.

Chromosomal-level assembly of the Leptodermis oblonga (Rubiaceae) genome and its phylogenetic implications.

Rubiaceae is the fourth largest and a taxonomically complex family of angiosperms. Many species in this family harbor low reproductive isolation and frequently exhibit inconsistent phenotypic characteristics. Therefore, taxonomic classification and their phylogenetic relationships in the Rubiaceae family is challenging, especially in the genus Leptodermis. Considering the low taxonomic confusion and wide distribution, Leptodermis oblonga is selected as a representative Leptodermis for genome sequencing. The assemblies resulted in 497 Mbp nuclear and 155,100 bp chloroplast genomes, respectively. Using the nuclear genome as a reference, SNPs were called from 37 Leptodermis species or varieties. The phylogenetic tree based on SNPs exhibited high resolution for species delimitation of the complex and well-resolved phylogenetic relationships in the genus. Moreover, 28,987 genes were predicted in the nuclear genome and used for comparative genomics study. As the first chromosomal-level genome of the subfamily Rubioideae in Rubiaceae, it will provide fruitfully evolutionary understanding in the family.

Edible CaCO3 nanoparticles stabilized Pickering emulsion as calcium-fortified formulation.

BACKGROUND: Nanoparticles assembled from food-grade calcium carbonate have attracted attention because of their biocompatibility, digestibility, particle and surface features (such as size, surface area, and partial wettability), and stimuli-responsiveness offered by their acid-labile nature. RESULTS: Herein, a type of edible oil-in-water Pickering emulsion was structured by calcium carbonate nanoparticles (CaCO3 NPs; mean particle size: 80 nm) and medium-chain triglyceride (MCT) for delivery of lipophilic drugs and simultaneous oral supplementation of calcium. The microstructure of the as-made CaCO3 NPs stabilized Pickering emulsion can be controlled by varying the particle concentration (c) and oil volume fraction (φ). The emulsification stabilizing capability of the CaCO3 NPs also favored the formation of high internal phase emulsion at a high φ of 0.7-0.8 with excellent emulsion stability at room temperature and at 4 °C, thus protecting the encapsulated lipophilic bioactive, vitamin D3 (VD3), against degradation. Interestingly, the structured CaCO3 NP-based Pickering emulsion displayed acid-trigged demulsification because of the disintegration of the CaCO3 NPs into Ca2+ in a simulated gastric environment, followed by efficient lipolysis of the lipid in simulated intestinal fluid. With the encapsulation and delivery of the emulsion, VD3 exhibited satisfying bioavailability after simulated gastrointestinal digestion. CONCLUSIONS: Taken together, the rationally designed CaCO3 NP emulsion system holds potential as a calcium-fortified formulation for food, pharmaceutical and biomedical applications.

Visual paper-based sensor for the highly sensitive detection of caffeine in food and biological matrix based on CdTe-nano ZnTPyP combined with chemometrics.

Caffeine naturally occurs in tea and cocoa, which is also used as an additive in beverages and has pharmacological effects such as refreshing, antidepressant, and digestion promotion, but excessive caffeine can cause harm to the human body. In this work, based on the specific response between nano zinc 5, 10, 15, 20-tetra(4-pyridyl)-21H-23H-porphine (nano ZnTPyP)-CdTe quantum dots (QDs) and caffeine, combined with chemometrics, a visual paper-based sensor was constructed for rapid and on-site detection of caffeine. The fluorescence of QDs can be quenched by nano ZnTPyP. When caffeine is added to the system, it can pull nano ZnTPyP off the surface of the QDs to achieve fluorescence recovery through electrostatic attraction and nitrogen/zinc coordination. The detection range is 5 × 10-11~3 × 10-9 mol L-1, and the detection limit is 1.53 × 10-11 mol L-1 (R2 = 0.9990) (S/N = 3). The paper-based sensor constructed exhibits good results in real samples, such as tea water, cell culture fluid, newborn bovine serum, and human plasma. Therefore, the sensor is expected to be applied to the rapid instrument-free detection of caffeine in food and biological samples.Graphical abstract.

Determination of l-theanine in tea water using fluorescence-visualized paper-based sensors based on CdTe quantum dots/corn carbon dots and nano-porphyrin with chemometrics.

BACKGROUND: The quality of tea is influenced by numerous factors, especially l-theanine, which is one of the important markers used to evaluate the sweetness and freshness of tea. Sensitive, rapid, and accurate detection of l-theanine is therefore useful to identify the grade and quality of tea. RESULTS: A high-sensitivity, paper-based fluorescent sensor combined with chemometrics was established to detect l-theanine in tea water based on CdTe quantum dots / corn carbon dots and nano tetra pyridel-porphine zinc (ZnTPyP). To verify the reliability of this method, fluorescence spectra and fluorescence-visualized paper-based sensors were compared. The fluorescence spectrum method demonstrated a linear range of 1 to 10 000 nmol L-1 and a limit of detection (LOD) of 0.19 nmol L-1 . In the fluorescence-visualized paper-based sensors there was a linear range of 10-1000 nmol L-1 , and the LOD was 10 nmol L-1 . Partial least squares discriminant analysis (PLSDA) and partial least squares regression analysis (PLSR) were used successfully to determine l-theanine accurately in tea water with this approach. The accuracy of the PLSDA model was 100% both in the training set and the predicting set, and the correlation coefficient between the actual concentration and the predicted concentration was greater than 0.9997 in the PLSR model. CONCLUSION: This fluorescence-visualized paper-based sensor, combined with chemometrics, could be applied efficiently to the practical analysis of tea water samples, which provides a new idea to ensure the flavor and quality of tea. © 2020 Society of Chemical Industry.

Increased insulin resistance is associated with vascular cognitive impairment in Chinese patients with cerebral small vessel disease.

BACKGROUND: The aim of this study was to investigate the association between insulin resistance (IR) and vascular cognitive impairment (VCI) in patients with cerebral small vessel disease (CSVD). METHODS: A total of 275 CSVD patients were enrolled in this retrospective case-control study. The homeostatic model assessment of insulin resistance (HOMA-IR) was used to measure the index of insulin resistance. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Spearman's correlation coefficient was used to evaluate the correlation between HOMA-IR and MoCA score. The variance inflation factor (VIF) was used to detect collinearity between variables. Multivariate logistic regression analysis was employed to confirm whether HOMA-IR is an independent risk factor for VCI in CVSD. Finally, receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic value of HOMA-IR in VCI. RESULTS: Of the 275 patients, 164 displayed VCI. VCI patients showed a significantly higher level of HOMA-IR compared to non-VCI patients (P < 0.001). HOMA-IR was negatively correlated with the MoCA score (r = -0.593, P < 0.001). After adjusting for potential confounding variables, using HOMA-IR quartile 1 (<1.11) as the reference, HOMA-IR quartile 3 (1.71-2.50) and quartile 4 (≥2.50) were independently associated with the occurrence of VCI; for each one unit increase in the HOMA-IR, the risk of VCI increased by 177.3% (odds ratio 2.773, 95% confidence interval: 1.050-7.324, P = 0.040) and 444.3% (odds ratio 5.443, 95% confidence interval: 2.109-14.050, P < 0.001), respectively. According to the ROC curve, the optimal cut-off point of HOMA-IR in predicting VCI was 1.55, and the area under the curve was 0.744, with a sensitivity of 71.3% and a specificity of 69.4%. CONCLUSION: This study demonstrated that increased IR is significantly associated with VCI in CSVD patients.

Comparative Study on Soil Microbial Diversity and Structure Under Wastewater and Groundwater Irrigation Conditions.

Wastewater (WW) irrigation to agricultural soils is one of the most economical and effective water-saving strategies. The effects of WW irrigation on soil microbial communities have gained increasing focus as these effects are not well understood. In this study, the effects of WW and groundwater (GW) irrigation on microbial diversity and structure were compared using the high-throughput sequencing analysis of 16S rDNA amplicons. Soil samples irrigated by WW for several decades and maize soil (loamy) samples irrigated by GW were collected from Luancheng Town, Shijiazhuang City, China. Compared to the GW groups, WW groups exhibited non-significant soil bacterial community abundance at the 0-20 and 20-40 cm depths. WW irrigation significantly altered the bacterial community composition and structures compared to GW irrigation. The relative abundance of Proteobacteria and Firmicutes increased in WW irrigated soil, while Actinobacteria decreased. Moreover, 14 significantly abundant biomarkers from Proteobacteria and Firmicutes that corresponded with WW irrigation were identified. Additionally, WW irrigation enriched some KEGG pathways that corresponded with metabolism and human diseases. The physical and chemical properties of WW irrigated soil may shape the compositions and structures of soil bacterial communities. The findings of this study illuminated the effects of wastewater irrigation on microbial characteristics, which is important for estimating the effects of long-term wastewater irrigation on soil environmental health.

Vertical distribution and affecting factors of Escherichia coli over a 0-400 cm soil profile irrigated with sewage effluents in northern China.

Quantification and evaluation of the spatial distribution and the primary factors that affect Escherichia coli (E. coli) distribution in soils is important to assess soil pollution and potential contamination of groundwater. However, little information is available on distribution of E. coli in deep soil layers. To analyze the spatial distribution and factors affecting E. coli over a 0-400 cm soil profile, soil samples were collected from two land use type in the sewage irrigation fields. The primary factors dominating the spatial distribution of E. coli were quantified by the model of principal component analysis with multiple linear regression (PCA-MLR). The results indicated that the number of E. coli under cropland decreased greatly with soil depth. The average number of E. coli over the 0-400 cm profile under forestland was 49 × 104 colony-forming unit/g (cfu/g), which was significantly higher than that under cropland (20 × 104 cfu/g). For forestland and cropland, the average number of E. coli at depths of 300-400 cm decreased by 85% and 88%, respectively, compared to that at depths of 0-100 cm. The presence of E. coli at the depths of 300-400 cm was at high level (forestland: 3 × 104 cfu/g; cropland: 2 × 104 cfu/g) for the potential risks of shallow groundwater. The PCA-MLR model estimated that the factors of soil organism, soil salt and land type use contributed 28%, 29% and 43%, respectively, to the distribution of E. coli. According to the Monte Carlo simulation, the average number of E. coli over the 0-400 cm profile was 46 ± 17 × 104 cfu/g in the sewage irrigated area, and the interval distribution with a probability of 95% varied between 14 × 104 cfu/g and 78 × 104 cfu/g. The findings of this study are useful for understanding negative effects of sewage irrigation on pathogens in deep soil and are critical to assess the potential risks of groundwater pollution.

Genomic identification and characterization of MYC family genes in wheat (Triticum aestivum L.).

BACKGROUND: MYC transcriptional factors are members of the bHLH (basic helix-loop-helix) superfamily, and play important roles in plant growth and development. Recent studies have revealed that some MYCs are involved in the crosstalk between Jasmonic acid regulatory pathway and light signaling in Arabidopsis, but such kinds of studies are rare in wheat, especially in photo-thermo-sensitive genic male sterile (PTGMS) wheat line. RESULTS: 27 non-redundant MYC gene copies, which belonged to 11 TaMYC genes, were identified in the whole genome of wheat (Chinese Spring). These gene copies were distributed on 13 different chromosomes, respectively. Based on the results of phylogenetic analysis, 27 TaMYC gene copies were clustered into group I, group III, and group IV. The identified TaMYC genes copies contained different numbers of light, stress, and hormone-responsive regulatory elements in their 1500 base pair promoter regions. Besides, we found that TaMYC3 was expressed highly in stem, TaMYC5 and TaMYC9 were expressed specially in glume, and the rest of TaMYC genes were expressed in all tissues (root, stem, leaf, pistil, stamen, and glume) of the PTGMS line BS366. Moreover, we found that TaMYC3, TaMYC7, TaMYC9, and TaMYC10 were highly sensitive to methyl jasmonate (MeJA), and other TaMYC genes responded at different levels. Furthermore, we confirmed the expression profiles of TaMYC family members under different light quality and plant hormone stimuli, and abiotic stresses. Finally, we predicted the wheat microRNAs that could interact with TaMYC family members, and built up a network to show their integrative relationships. CONCLUSIONS: This study analyzed the size and composition of the MYC gene family in wheat, and investigated stress-responsive and light quality induced expression profiles of each TaMYC gene in the PTGMS wheat line BS366. In conclusion, we obtained lots of important information of TaMYC family, and the results of this study was supposed to contribute novel insights and gene and microRNA resources for wheat breeding, especially for the improvement of PTGMS wheat lines.

HS-SA-Based Precise Modeling of the Aircraft Fuel Center of Gravity Using Sensors Data.

The traditional modeling methods of aircraft fuel center of gravity (CG) based on sensor data have some disadvantages, such as large data storage requirements and low computational efficiency. In this article, a novel hybrid heuristic search-simulated annealing (HS-SA) algorithm is used to reduce the data storage requirements and improve the efficiency of the established models based on sensor data. First, a fuel CG model is established based on the multidimensional interpolation of flight sensors and fuel tank data, which can accurately reflect the nonlinear characteristics of the problem and reduce the data storage needs. Then, the calculation nodes are reasonably selected and optimized based on the proposed HS-SA algorithm to improve the precision of the model of the aircraft fuel CG. The established model of the fuel CG has obvious advantages over traditional methods in improving the temporal efficiency and meeting the storage requirements for sensor data in actual flights. Finally, detailed simulations are conducted based on more than 16,000 sets of sensor data, and the results demonstrate the effectiveness of the proposed HS-SA algorithm.

Research on Fault Extraction Method of Variational Mode Decomposition Based on Immunized Fruit Fly Optimization Algorithm.

In recent years, a new method of fault diagnosis, named variational mode decomposition (VMD), has been widely used in industrial production, but the decomposition accuracy of VMD is determined by two parameters, which are respectively the decomposition layer number k and the penalty factor α, if the parameters are not properly selected, there will be over-decomposition or under-decomposition. In order to find an approach to determine the parameters adaptively, a method to optimize VMD by using the immune fruit fly optimization algorithm (IFOA) is proposed in this paper. In this method, permutation entropy is used as the fitness function, firstly, the immune fruit fly optimization algorithm is used to search the combined parameters of k and α in VMD, searching for the best combination parameters of k and α by iteration, and then uses the combined parameters to perform VMD, finally, the center frequency is determined through frequency spectrum analysis. The method mentioned is applied to the fault extraction of a simulated signal and a measured signal of a wind turbine gearbox, and the fault frequency is successfully extracted. Using ensemble empirical mode decomposition (EEMD) and singular spectrum decomposition (SSD) to compare with the proposed method, which validated feasibility of the proposed method.

A New Fuzzy Logic Classifier Based on Multiscale Permutation Entropy and Its Application in Bearing Fault Diagnosis.

The self-organizing fuzzy (SOF) logic classifier is an efficient and non-parametric classifier. Its classification process is divided into an offline training stage, an online training stage, and a testing stage. Representative samples of different categories are obtained through the first two stages, and these representative samples are called prototypes. However, in the testing stage, the classification of testing samples is completely dependent on the prototype with the maximum similarity, without considering the influence of other prototypes on the classification decision of testing samples. Aiming at the testing stage, this paper proposed a new SOF classifier based on the harmonic mean difference (HMDSOF). In the testing stage of HMDSOF, firstly, each prototype was sorted in descending order according to the similarity between each prototype in the same category and the testing sample. Secondly, multiple local mean vectors of the prototypes after sorting were calculated. Finally, the testing sample was classified into the category with the smallest harmonic mean difference. Based on the above new method, in this paper, the multiscale permutation entropy (MPE) was used to extract fault features, linear discriminant analysis (LDA) was used to reduce the dimension of fault features, and the proposed HMDSOF was further used to classify the features. At the end of this paper, the proposed fault diagnosis method was applied to the diagnosis examples of two groups of different rolling bearings. The results verify the superiority and generalization of the proposed fault diagnosis method.

Modified Singular Spectrum Decomposition and Its Application to Composite Fault Diagnosis of Gearboxes.

Under the strong noise environment, the composite fault signal of gearbox is weak, which makes it difficult to extract fault features. For this problem, based on noise-assisted method, we propose a novel method called Modified Singular Spectrum Decomposition (MSSD). Singular Spectrum Decomposition (SSD) has many advantages such as high decomposition precision and strong ability to restrain mode mixing, etc. However, the ability of SSD to extract a weak signal is not ideal, the decomposition results usually contain a lot of redundant noise and mode mixing caused by intermittency, which is also a troubling problem. In order to improve the decomposition efficiency and make up for the defects of SSD, the new method MSSD adds an adaptive and particular noise in every SSD decomposition stage for each trial, and in addition, whenever the input signal is decomposed to obtain an intrinsic module function (IMF), a unique residual is obtained. After multiple decomposition, the average value of the residual is used as input to the next stage, until the residual cannot continue to decompose, which means that the residual component has, at most, one extreme value. Finally, analyzing simulated signals to explain the advantages of MSSD compared to ensemble empirical mode decomposition (EEMD) and complete ensemble local mean decomposition with adaptive noise (CEEMDAN). In order to further prove the effectiveness of MSSD, this new method, MSSD, is applied to the fault diagnosis of an engineering gearbox test stand in an actual engineer project case. The final results show that MSSD can extract more fault feature information, and mode mixing has been improved and suffers less interference compared to SSD.

AntDAS: Automatic Data Analysis Strategy for UPLC-QTOF-Based Nontargeted Metabolic Profiling Analysis.

High-quality data analysis methodology remains a bottleneck for metabolic profiling analysis based on ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. The present work aims to address this problem by proposing a novel data analysis strategy wherein (1) chromatographic peaks in the UPLC-QTOF data set are automatically extracted by using an advanced multiscale Gaussian smoothing-based peak extraction strategy; (2) a peak annotation stage is used to cluster fragment ions that belong to the same compound. With the aid of high-resolution mass spectrometer, (3) a time-shift correction across the samples is efficiently performed by a new peak alignment method; (4) components are registered by using a newly developed adaptive network searching algorithm; (5) statistical methods, such as analysis of variance and hierarchical cluster analysis, are then used to identify the underlying marker compounds; finally, (6) compound identification is performed by matching the extracted peak information, involving high-precision m/z and retention time, against our compound library containing more than 500 plant metabolites. A manually designed mixture of 18 compounds is used to evaluate the performance of the method, and all compounds are detected under various concentration levels. The developed method is comprehensively evaluated by an extremely complex plant data set containing more than 2000 components. Results indicate that the performance of the developed method is comparable with the XCMS. The MATLAB GUI code is available from http://software.tobaccodb.org/software/antdas .

Valproic acid ameliorates coxsackievirus-B3-induced viral myocarditis by modulating Th17/Treg imbalance.

BACKGROUND: Viral myocarditis, which is often caused by coxsackievirus B3 (CVB3), is a serious clinical disorder characterized by excessive myocardial inflammation. Valproic acid (VPA) is described as a histone deacetylase inhibitor that has anti-inflammatory effects in several inflammatory diseases. However, the role and the detailed mechanism of VPA in viral myocarditis remain unclear. METHODS: Experimental CVB3-induced myocarditis was induced in mice by intraperitoneally (i.p.) infected with CVB3. VPA was i.p. administered from day 0 to day 7. The survival, body weight loss, and myocarditis severity of mice were recorded. Th17 and Treg cells in spleen were analyzed by flow cytometry. Th17/Treg cell-related cytokine expressions were quantified by ELISA. The effect of VPA on Th17 and Treg cells differentiation was examined in vitro and in vivo. RESULTS: Administration of VPA significantly attenuated the clinical severity of myocarditis, and the overall mortality from CVB3-induced myocarditis. The infiltration of Th17 and Treg cells, as well as the serum level of related cytokines (IL-17A and IL-10), were increased in CVB3 infected mice. In addition, VPA decreased the percentage of splenic Th17 cells while increased the percentage of Treg cells. Moreover, VPA downregulated the expression of IL-17A and upregulated IL-10 in serum and heart tissues of CVB3 infected mice. Additionally, VPA directly inhibited the differentiation of Th17 cells and promoted both the differentiation and suppressive function of Treg cells in vitro and in vivo. CONCLUSIONS: Our results suggest that VPA may thus be a promising strategy in the therapy of viral myocarditis.

Effect of Hypoxia on DDR1 Expression in Pituitary Adenomas.

BACKGROUND: Pituitary adenoma is a common intracranial tumor in neurosurgery. Some pituitary adenomas have the characteristics of invasive growth make them unable to be removed completely by surgery leading to easy relapse. Discoidin domain receptor l (DDR1) is a new kind of tyrosine kinase receptor on the cell surface. DDR1 can be activated by tumor microenvironment signal in tumorigenesis, increasing MMP-2/9 expression and promoting the invasive ability of tumor cells. Anoxia can promote tumor growth and metastasis. This study investigated the impact of anoxic environment DDR1 expression in pituitary adenoma. MATERIAL AND METHODS: A primary hypoxia pituitary adenoma cell model was established and treated with DDR1 inhibitor nilotinib. Real-time PCR and Western blot were used to detect DDR1 mRNA and protein expression. ELISA was used to detect MMP-2/9 changes. MTT method was used to detect pituitary adenoma cell proliferation. We used a transwell chamber to determine pituitary adenoma cell invasion ability. RESULTS: DDR1 mRNA and protein were significantly overexpressed under hypoxia (P<0.05). MMP-2 and MMP-9 expression was obviously increased in supernatant (P<0.05). Pituitary adenoma cell proliferation and invasive ability improved markedly under hypoxia (P<0.05). Nilotinib could reduce DDR1 expression, decrease MMP-2 and MMP-9 expression, and inhibit pituitary adenoma cells proliferation and invasion. CONCLUSIONS: Hypoxia can increase DDR1 expression in pituitary adenoma cells, leading to improved MMP-2 and MMP-9 secretion, and promoting pituitary adenoma cell proliferation and invasion.