Preliminary expression profile of cytokines in brain tissue of BALB/c mice with Angiostrongylus cantonensis infection

BACKGROUND: Angiostrongylus cantonensis (A. cantonensis) infection can result in increased risk of eosinophilic meningitis. Accumulation of eosinophils and inflammation can result in the A. cantonensis infection playing an important role in brain tissue injury during this pathological process. However, underlying mechanisms regarding the transcriptomic responses during brain tissue injury caused by A. cantonensis infection are yet to be elucidated. This study is aimed at identifying some genomic and transcriptomic factors influencing the accumulation of eosinophils and inflammation in the mouse brain infected with A. cantonensis. METHODS: An infected mouse model was prepared based on our laboratory experimental process, and then the mouse brain RNA Libraries were constructed for deep Sequencing with Illumina Genome Analyzer. The raw data was processed with a bioinformatics’ pipeline including Refseq genes expression analysis using cufflinks, annotation and classification of RNAs, lncRNA prediction as well as analysis of co-expression network. The analysis of Refseq data provides the measure of the presence and prevalence of transcripts from known and previously unknown genes. RESULTS: This study showed that Cys-Cys (CC) type chemokines such as CCL2, CCL8, CCL1, CCL24, CCL11, CCL7, CCL12 and CCL5 were elevated significantly at the late phase of infection. The up-regulation of CCL2 indicated that the worm of A. cantonensis had migrated into the mouse brain at an early infection phase. CCL2 could be induced in the brain injury during migration and CCL2 might play a major role in the neuropathic pain caused by A. cantonensis infection. The up-regulated expression of IL-4, IL-5, IL-10, and IL-13 showed Th2 cell predominance in immunopathological reactions at late infection phase in response to infection by A. cantonensis. These different cytokines can modulate and inhibit each other and function as a network with the specific potential to drive brain eosinophilic inflammation. The increase of ATF-3 expression at 21 dpi suggested the injury of neuronal cells at late phase of infection. 1217 new potential lncRNA were candidates of interest for further research. CONCLUSIONS: These cytokine networks play an important role in the development of central nervous system inflammation caused by A. cantonensis infection. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13071-015-0939-6) contains supplementary material, which is available to authorized users

Fusobacterium nucleatum induces colon anastomosis leak by activating epithelial cells to express MMP9

BackgroundDespite advances in anastomotic techniques and perioperative care, the incidence of anastomotic leak (AL) has not substantially decreased over time. Although it is known that AL etiology is multifactorial and the mechanisms involved remain unclear, there is accumulating evidence pointing at AL related to gut microbiota.MethodWe firstly performed a clinical study to analyze the gut microbiota between colorectal cancer patients who developed AL and those who did not (nAL) using 16S-rRNA sequencing and quantitative real-time PCR to identify AL risk bacterial taxa. Then we built a rat anastomosis model and performed a bacteria transplantation to ensure the cause-effect relationship. The anastomotic healing score was used to evaluate the healing of anastomosis. In addition, we assessed the adhesion ability of bacteria by staining with fluorescein isothiocyanate and attachment assay. The expression of matrix metalloproteinase 9 (MMP9) was detected by western blot, and the activity was detected by gelatin zymography.ResultsWe found that the abundance and positive rate of Fusobacterium nucleatum (Fn) were higher in the AL patients. Exposure of the rat’s colon anastomosis to Fn contributes to the loss of submucosa collagen I and III, leading to AL’s pathogenesis. Fn can attach to the gut epithelial cells and stimulate intestinal MMP9 expression in vitro and in vivo. We further confirmed that these effects of Fn depended on the E-cadherin/β-catenin signaling pathway.ConclusionThis work demonstrates that Fn attaches and then stimulates the expression of epithelial cells MMP9 by the E-cadherin/β-catenin signaling pathway. These effects contribute to collagen break down in the intestinal tissue, finally leading to AL

Age over sex: evaluating gut microbiota differences in healthy Chinese populations

Age and gender have been recognized as two pivotal covariates affecting the composition of the gut microbiota. However, their mediated variations in microbiota seem to be inconsistent across different countries and races. In this study, 613 individuals, whom we referred to as the “healthy” population, were selected from 1,018 volunteers through rigorous selection using 16S rRNA sequencing. Three enterotypes were identified, namely, Escherichia–Shigella, mixture (Bacteroides and Faecalibacterium), and Prevotella. Moreover, 11 covariates that explain the differences in microbiota were determined, with age being the predominant factor. Furthermore, age-related differences in alpha diversity, beta diversity, and core genera were observed in our cohort. Remarkably, after adjusting for 10 covariates other than age, abundant genera that differed between age groups were demonstrated. In contrast, minimal differences in alpha diversity, beta diversity, and differentially abundant genera were observed between male and female individuals. Furthermore, we also demonstrated the age trajectories of several well-known beneficial genera, lipopolysaccharide (LPS)-producing genera, and short-chain fatty acids (SCFAs)-producing genera. Overall, our study further elucidated the effects mediated by age and gender on microbiota differences, which are of significant importance for a comprehensive understanding of the gut microbiome spectrum in healthy individuals

Second virial coefficients for a Fermi gas trapped in an anisotropic harmonic potential

We study the virial expansion of an interacting Fermi gas trapped in an anisotropic harmonic potential and calculate the second virial coefficients for both cigar-shaped and pancake-shaped traps across a wide range of interaction and for various temperatures. At unitarity, we observe a universal behavior regardless of the trapping geometry and temperature. With these results, we calculate the interaction energy and entropy of a trapped gas at unitarity and obtain the pressure and compressibility for a homogeneous Fermi gas

Interaction between tns and β-lactoglobulin

The major bovine milk protein β-lactoglobulin (β-LG), a member of the lipocalin superfamily, can bind a wide range of ligands and act as a specific transporter. In the present study, the combination of the hydrophobic molecule 2-(p-toluidino)-6-naphthalenesulfonic acid sodium salt (tns) with β-LG was analyzed using fluorescence spectroscopy and autodock modeling to discern the major binding sites of the protein and to determine the capacity of other small ligands to bind with β-LG by utilizing tns as a reference. The experimental data indicate that in a neutral pH environment, tns is located in the hydrophobic domain of the β-LG protein, 2.5 nm away from the Trp19 residues of β-LG. The binding constant of tns to β-LG is (3.30±0.32)10The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Estimate Forest Aboveground Biomass of Mountain by ICESat-2/ATLAS Data Interacting Cokriging

Compared with the previous full-waveform data, the new generation of ICESat-2/ATLAS (Advanced Terrain Laser Altimeter System) has a larger footprint overlap density and a smaller footprint area. This study used ATLAS data to estimate forest aboveground biomass (AGB) in a high-altitude, ecologically fragile area. The paper used ATLAS data as the main information source and a typical mountainous area in Shangri-La, northwestern Yunnan Province, China, as the study area. Then, we combined biomass data from 54 ground samples to obtain the estimated AGB of 74,873 footprints using a hyperparametric optimized random forest (RF) model. The total AGB was estimated by combining the best variance function model in geostatistics with the slope that is the covariates. The results showed that among the 50 index parameters and three topographic variables extracted based on ATLAS, six variables showed a significant correlation with AGB. They were, in order, number of canopy photons, Landsat percentage canopy, canopy photon rate, slope, number of photons, and apparent surface reflectance. The optimized random forest model was used to estimate the AGB within the footprints. The model accuracy was the coefficient of determination (R2) = 0.93, the root mean square error (RMSE) = 10.13 t/hm2, and the population estimation accuracy was 83.3%. The optimized model has a good estimation effect and can be used for footprint AGB estimation. The spatial structure analysis of the variance function of footprint AGB showed that the spherical model had the largest fitting accuracy (R2 = 0.65, the residual sum of squares (RSS) = 2.65 × 10−4), the nugget (C0) was 0.21, and the spatial structure ratio was 94.0%. It showed that the AGB of footprints had strong spatial correlation and could be interpolated by kriging. Finally, the slope in the topographic variables was selected as the co-interpolation variable, and cokriging spatial interpolation was performed. Furthermore, a continuous map of AGB spatial distribution was obtained, and the total AGB was 6.07 × 107 t. The spatial distribution of AGB showed the same trend as the distribution of forest stock. The absolute accuracy of the estimation was 82.6%, using the statistical value of the forest resource planning and design survey as a reference. The ATLAS data can improve the accuracy of AGB estimation in mountain forests

Borehole stability in naturally fractured rocks with drilling mud intrusion and associated fracture strength weakening: A coupled DFN-DEM approach

Borehole instability in naturally fractured rocks poses significant challenges to drilling. Drilling mud invades the surrounding formations through natural fractures under the difference between the wellbore pressure (Pw) and pore pressure (Pp) during drilling, which may cause wellbore instability. However, the weakening of fracture strength due to mud intrusion is not considered in most existing borehole stability analyses, which may yield significant errors and misleading predictions. In addition, only limited factors were analyzed, and the fracture distribution was oversimplified. In this paper, the impacts of mud intrusion and associated fracture strength weakening on borehole stability in fractured rocks under both isotropic and anisotropic stress states are investigated using a coupled DEM (distinct element method) and DFN (discrete fracture network) method. It provides estimates of the effect of fracture strength weakening, wellbore pressure, in situ stresses, and sealing efficiency on borehole stability. The results show that mud intrusion and weakening of fracture strength can damage the borehole. This is demonstrated by the large displacement around the borehole, shear displacement on natural fractures, and the generation of fracture at shear limit. Mud intrusion reduces the shear strength of the fracture surface and leads to shear failure, which explains that the increase in mud weight may worsen borehole stability during overbalanced drilling in fractured formations. A higher in situ stress anisotropy exerts a significant influence on the mechanism of shear failure distribution around the wellbore. Moreover, the effect of sealing natural fractures on maintaining borehole stability is verified in this study, and the increase in sealing efficiency reduces the radial invasion distance of drilling mud. This study provides a directly quantitative prediction method of borehole instability in naturally fractured formations, which can consider the discrete fracture network, mud intrusion, and associated weakening of fracture strength. The information provided by the numerical approach (e.g. displacement around the borehole, shear displacement on fracture, and fracture at shear limit) is helpful for managing wellbore stability and designing wellbore-strengthening operations

Effects of curcumin-coated nanomicelles on cerebral ischemia injury in rats by regulating lncRNA GAS5 and NF-κB signalling pathways

AbstractThis work aimed to investigate the effects of curcumin (Cur) encapsulated in triblock copolymer nanomicelles on lncRNA GAS5 expression and NF-κB signalling pathway in ischemic stroke rats. Using polycaprolactone (PCL), polyethylene (mPEG), polyglutamic acid (PLG), and Cur as raw materials, Cur-PLG-mPEG-PCL nanoparticles were prepared. Its morphology, particle size, and Zeta potential were analyzed. Then seventy-two SD rats were randomly divided into control (Ctrl) group, model group, model + blank nanomicelles (M + BNM) group, model +80 mg/mL Cur (M + C) group, model +40 mg/mL Cur-nanomicelles (M + CNM (40 mg/mL)) group, and model +80 mg/mL Cur nanomicelle (M + CNM (80 mg/mL)) group. The results showed that mean particle size of Cur-PLG-mPEG-PCL was (148.27 ± 27.44) nm, and mean Zeta potential was (−1.97 ± 0.21) mV. The evaluation time of intelligent optimization algorithm based on Single Shot MultiBox Detector (SSD) was significantly shortened, and average EEG power spectrum of ischemic cerebral pawns was significantly lower than that of the control group at θ, α, β, and γ bands for 4h (p < 0.01). These results indicate that the computer intelligent algorithm can be used to evaluate the behaviour of rats, EEG can reflect the changes of cerebral cortical function, and Cur-PLG-mPEG-PCL can improve neurological function and degree of brain injury