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Abstract Objectives Seeking a noninvasive predictor for BRAF V600E mutation status of pleomorphic xanthoastrocytomas (PXAs) is essential for their prognoses and therapeutic use of BRAF inhibitors. We aimed to noninvasively diagnose BRAF V600E-mutated PXAs using MRI morphologic, DWI and clinical parameters. Methods The clinical findings, anatomical MRI characteristics, and diffusion parameters of 36 pathologically confirmed PXAs were retrospectively analyzed, and BRAF V600E-mutated (n = 16) and wild-type (n = 20) groups were compared. A binary logistic-regression analysis was performed, and a ROC curve was calculated to determine the independent predictors of BRAF V600E mutation status, diagnostic accuracy, and optimal cut-off value. Results A comparison of findings between groups showed that BRAF V600E-mutated PXAs were more frequent in children and young adults (≤ 35 years; P = 0.042) who often had histories of seizures (P = 0.004). Furthermore, BRAF V600E-mutated PXAs generally presented as solitary masses (P = 0.024), superficial locations with meningeal attachment (P

Abstract Soil harbors a vast expanse of unidentified microbes, termed as microbial dark matter, presenting an untapped reservoir of microbial biodiversity and genetic resources, but has yet to be fully explored. In this study, we conduct a large-scale excavation of soil microbial dark matter by reconstructing 40,039 metagenome-assembled genome bins (the SMAG catalogue) from 3304 soil metagenomes. We identify 16,530 of 21,077 species-level genome bins (SGBs) as unknown SGBs (uSGBs), which expand archaeal and bacterial diversity across the tree of life. We also illustrate the pivotal role of uSGBs in augmenting soil microbiome’s functional landscape and intra-species genome diversity, providing large proportions of the 43,169 biosynthetic gene clusters and 8545 CRISPR-Cas genes. Additionally, we determine that uSGBs contributed 84.6% of previously unexplored viral-host associations from the SMAG catalogue. The SMAG catalogue provides an useful genomic resource for further studies investigating soil microbial biodiversity and genetic resources.

Biochar is a very promising material for soil remediation. However, most studies mainly focus on the adsorption ability of biochar on one heavy metal, which is difficult to evaluate the actual remediation effect since soils were contaminated with multiple heavy metals. In order to improve the soil remediation efficiency, we used the joint remediation method of magnetically modified biochar and ryegrass to remediate the soil polluted by compound heavy metals (chromium, nickel, copper, zinc, arsenic and cadmium), and evaluate the effect on the process of organic carbon mineralization in polluted soils. It was found that magnetic biochar and ryegrass together decreased the concentrations of Cr, Ni, Cu, Zn, As, and Cd in soils by 24.12 %, 23.30 %, 22.01 %, 9.98 %, 14.83 %, and 15.08 %, respectively, and reduced the available fractions. Ryegrass roots were the main accumulation part of heavy metals, and the order of enrichment effect was ranked as Zn > As > Cr > Cu > Ni > Cd. In addition, magnetic biochar can maintained the stability of the organic carbon pool, and inhibited the emission of volatile organic compounds from ryegrass. Overall, this study indicates that magnetic biochar spheres combined with ryegrass is an effective method for heavy metals co-contaminated soils, and has the excellent remediation ability for actual co-contaminated soils.

Introduction: Assembly and co-occurrence of the host co-evolved microbiota are essential ecological and evolutionary processes, which is not only crucial for managing individual plant fitness but also ecological function. However, understanding of the microbiome assembly and co-occurrence in higher plants is not well understood. The tea plant was shown to contribute the forest fitness due to the microbiome assembled in the phyllosphere; the landscape of microbiome assembly in the tea plants and its potential implication on phyllosphere homestasis still remains untangled. Objectives: This study aimed to deciphering of the microbiome networks of the tea plants at a continental scale. It would provide fundamental insights into the factors driving the microbiome assembly, with an extended focus on the resilience towards the potential pathogen in the phyllosphere. Methods: We collected 225 samples from 45 locations spanning approximately 2000-km tea growing regions across China. By integration of high-throughput sequencing data, physicochemical properties profiling and bioinformatics analyses, we investigated continental scale microbiome assembly and co-occurrence in the tea plants. Synthetic assemblages, interaction assay and RT-qPCR were further implemented to analyze the microbial interaction indexed in phyllosphere. Results: A trade-off between stochastic and deterministic processes in microbiomes community assembly was highlighted. Assembly processes were dominated by deterministic processes in bulk and rhizosphere soils, and followed by stochastic processes in roots and leaves with amino acids as critical drivers for environmental selection. Sphingobacteria and Proteobacteria ascended from soils to leaves to sustain a core leaf taxa. The core taxa formed a close association with a prevalent foliar pathogen in the co-occurrence network and significantly attenuated the expression of a set of essential virulence genes in pathogen. Conclusion: Our study unveils the mechanism underpinning microbiome assembly in the tea plants, and a potential implication of the microbiome-mediated resilience framework on the phyllosphere homeostasis.

ObjectiveWe designed this study to determine whether there is a link between vitamin D levels and sensitivity to thyroid hormone and to provide a new perspective for studying the relationship between vitamin D and thyroid disease.MethodsOur study included 8,126 participators from the National Health and Nutrition Examination Survey (NHANES) database between 2007 and 2012. We used weighted multiple linear regression models to enquire the connection between serum vitamin D levels and thyroid hormone sensitivity indicators, including the following: Thyroid-stimulating hormone index (TSHI), Free Triiodothyronine/Free thyroxine (FT3/FT4), Thyroid Feedback Quantile-based Index (TFQI), and Thyrotroph Thyroxine Resistance Index (TT4RI). Finally, we used constrained cubic splines to explore possible nonlinear relationships. All data cleaning and statistical analyses were performed using R software.ResultsThe final Results were reached after adjusting for various confounding factors. We found a U-shaped relationship between TFQI and serum vitamin D, and the lowest TFQI appeared when the serum vitamin D concentration was 25.77ng/ml. However, an inverse U-shaped relationship was found between FT3/FT4 and vitamin D levels. When the serum vitamin D concentration was 25.43ng/ml, the ratio of FT3/FT4 was the highest.ConclusionIn the US population, our study concluded that FTQI and FT3/FT4 were U-shaped or inverse-U-shaped with serum vitamin D levels respectively after several adjustments. Therefore, FTQI and FT3/FT4 are considered indicators of the complex relationship between thyroid hormone resistance and vitamin D metabolism. In the future, more complex prospective investigations are needed to confirm these findings and find a causal link between them.

Abstract Lodging resistance is a critical trait in modern maize breeding. This study aimed to examine maize stalk lodging and its related characteristics in response to increasing planting densities in modern hybrids. A two-year field trial was conducted from 2018 to 2019 with two widely grown commercial hybrids (‘Xy335’ and ‘Fm985’) and three planting density treatments of 4.5 × 104 (low density, LD), 6.5 × 104 (medium density, MD), and 8.5 × 104 plants/ha (high density, HD). New hybrid Fm985 had a significantly higher grain yield and lower lodging rate at HD, while there was no significance at LD and MD. Compared to Fm985, old hybrid Xy335 had a significantly high plant height, ear and gravity height, and culm length (CL) across the three planting densities, while opposite stalk bending strength (SBS), dry weight per unit length (DWPU), cross-sectional area, and the cellulose and lignin content in the basal internode were low. Correlation and path analysis revealed that kernel number per ear and lodging rate directly contributed to maize grain yield, while lodging-related traits of SBS, stem lignin, and DWPU had an indirect effect on maize grain yield, suggesting that modern hybrid maize yield enhancement is associated with greater stalk lodging resistance at a high planting density in northeast China.

As a highly developed spatial form of integrated cities, urban agglomeration has become an important fulcrum for promoting economic development and regional growth. Green urban efficiency is the key to achieving green growth in a country. This study propose a slack-based model with undesirable output to evaluate the green urbanization of 18 urban agglomerations in China. Analysis was performed using the integrated barycenter coordinate method, standard deviation ellipses, and the geographic detector model to determine the spatial–temporal characteristics of green urbanization efficiency and the factors that influence urban agglomerations. We found that the green urbanization efficiency of urban agglomerations in China, when plotted, revealed a curve with the shape of “∧,” which increased at first and then decreased. The spatial differentiation characteristics were not obvious as the gap was narrowing. The center of green urbanization efficiency in China’s urban agglomerations has always been located in the Central Plains, with a small overall span and a relatively fixed position. The barycenter coordinates showed a trend of shifting from east to north, but the transfer speed and rhythm were relatively slow. The explanatory power of the various factors influencing the spatial differentiation of green urbanization efficiency of urban agglomerations differed markedly. The magnitude of importance was in the order of: urban population scale > investment growth > technology level > economic development > industrial structure.

BackgroundTongue cancer, as one of the most malignant oral cancers, is highly invasive and has a high risk of recurrence. At present, tongue cancer is not obvious and easy to miss the opportunity for early diagnosis when in the advanced stage. It is important to find markers that can predict the occurrence and progression of tongue cancer.MethodsBioinformatics analysis plays an important role in the acquisition of marker genes. GEO and TCGA data are very important public databases. In addition to expression data, the TCGA database also contains corresponding clinical data. In this study, we screened three GEO data sets that met the standard, which included GSE13601, GSE34105, and GSE34106. These data sets were combined using the SVA package to prepare the data for differential expression analysis, and then the limma package was used to set the standard to p

CD19-targeted chimeric antigen receptor T (anti-CD19 CAR-T) cells have shown good therapeutic results in the treatment of CD19 + B cell acute lymphocytic leukemia and lymphoma. However, severe side reactions and cytotoxicity are great challenges in the application of anti-CD19 CAR-T cell therapy. Cytokine release syndrome (CRS) is the main side effect of CAR-T cell treatment, and interleukin-6 (IL-6) and interferon γ (IFN-γ) are cytokines that play major roles in CRS. Therefore, we investigated double knockdown (KD) of IL-6 and IFN-γ as a potential strategy to manage anti-CD19 CAR-T cell-associated CRS. These improved anti-CD19 CAR-T cells therapy retained the advantages of the original anti-CD19 CAR-T cells and additionally reduced the release of cytokines from CAR-T cells and other immune cells. Moreover, this study presented a novel approach to abrogate CRS through IL-6 and IFN-γ KD, which may potentially inhibit the release of multiple cytokines from CAR-T cells and peripheral blood mononuclear cells (PBMCs), a model of CRS correlate with in vivo features of the CAR-T therapy, thereby reducing the impact of CRS, improving the safety of CAR-T cell treatment, reducing toxicities, and maintaining the function of CAR-T cells.

It is important to capture passengers’ public transit behavior and their mobility to create profiles, which are critical for analyzing human activities, understanding the social and economic structure of cities, improving public transportation, assisting urban planning, and promoting smart cities. In this paper, we develop a generative adversarial machine learning network to characterize the temporal and spatial mobility behavior of public transit passengers, based on massive smart card data and road network data. The Apriori algorithm is extended with spatio-temporal constraints to extract frequent transit mobility patterns of individual passengers based on a reconstructed personal trip dataset. This individual-level pattern information is used to construct personalized feature vectors. For regular and frequent public transit passengers, we identify similar transit mobility groups using spatio-temporal constraints to construct a group feature vector. We develop a generative adversarial network to embed public transit mobility of passengers. The proposed model’s generator consists of an auto-encoder, which extracts a low-dimensional and compact representation of passenger behavior, and a pre-trained sub-generator containing generalization features of public transit passengers. Shenzhen City is taken as the study area in this paper, and experiments were carried out based on smart card data, road network data, and bus GPS data. Clustering analysis of embedding vector representation and estimation of the top K transit destinations were conducted, verifying that the proposed method can profile passenger transit mobility in a comprehensive and compact manner.

Vascular smooth muscle cell (VSMC) migration plays a critical role in the pathogenesis of many cardiovascular diseases. We recently showed that TMEM16A is involved in hypertension-induced cerebrovascular remodeling. However, it is unclear whether this effect is related to the regulation of VSMC migration. Here, we investigated whether and how TMEM16A contributes to migration in basilar artery smooth muscle cells (BASMCs). We observed that AngII increased the migration of cultured BASMCs, which was markedly inhibited by overexpression of TMEM16A. TMEM16A overexpression inhibited AngII-induced RhoA/ROCK2 activation, and myosin light chain phosphatase (MLCP) and myosin light chain (MLC20) phosphorylation. But AngII-induced myosin light chain kinase (MLCK) activation was not affected by TMEM16A. Furthermore, a suppressed activation of integrinβ3/FAK pathway, determined by reduced integrinβ3 expression, FAK phosphorylation and F-actin rearrangement, was observed in TMEM16A-overexpressing BASMCs upon AngII stimulation. Contrary to the results of TMEM16A overexpression, silencing of TMEM16A showed the opposite effects. These in vitro results were further demonstrated in vivo in basilar arteries from VSMC-specific TMEM16A transgenic mice during AngII-induced hypertension. Moreover, we observed that the inhibitory effect of TMEM16A on BASMC migration was mediated by decreasing the activation of WNK1, a Cl−-sensitive serine/threonine kinase. In conclusion, this study demonstrated that TMEM16A suppressed AngII-induced BASMC migration, thus contributing to the protection against cerebrovascular remodeling during AngII-infused hypertension. TMEM16A may exert this effect by suppressing the RhoA/ROCK2/MLCP/MLC20 and integrinβ3/FAK signaling pathways via inhibiting WNK1. Our results suggest that TMEM16A may serve as a novel therapeutic target for VSMC migration-related diseases, such as vascular remodeling.

This longitudinal study explored the changed patterns of structural brain network after radiotherapy (RT) in patients with nasopharyngeal carcinoma (NPC). Diffusion tensor imaging (DTI) data were gathered from 35 patients with NPC at four time points: before RT (baseline), 0∼3 (acute), 6 (early delayed), and 12 months (late-delayed) after RT. The graph theory was used to characterize the dynamic topological properties after RT and the significant changes were detected over time at the global, regional and modular levels. Significantly altered regional metrics (nodal efficiency and degree centrality) were distributed in the prefrontal, temporal, parietal, frontal, and subcortical regions. The module, that exhibited a significantly altered within-module connectivity, had a high overlap with the default mode network (DMN). In addition, the global, regional and modular metrics showed a tendency of progressive decrease at the acute and early delayed stages, and a partial/full recovery at the late-delayed stage. This changed pattern illustrated that the radiation-induced brain damage began at the acute reaction stage and were aggravated at the early-delayed stage, and then partially recovered at the late-delayed stage. Furthermore, the spearman’s correlations between the abnormal nodal metrics and temporal dose were calculated and high correlations were found at the temporal (MTG.R and HES.L), subcortical (INS.R), prefrontal (ORBinf.L and ACG.L), and parietal (IPL.R) indicating that these regions were more sensitive to dose and should be mainly considered in radiotherapy treatment plan.

Obesity-induced metabolic syndrome is a rapidly growing conundrum, reaching epidemic proportions globally. Chronic inflammation in obese adipose tissue plays a key role in metabolic syndrome with a series of local and systemic effects such as inflammatory cell infiltration and inflammatory cytokine secretion. Adipose tissue macrophages (ATM), as one of the main regulators in this process, are particularly crucial for pharmacological studies on obesity-related metabolic syndrome. Ponatinib, a multi-targeted tyrosine kinase inhibitor originally used to treat leukemia, has recently been found to improve dyslipidemia and atherosclerosis, suggesting that it may have profound effect on metabolic syndrome, although the mechanisms underlying have not yet been revealed. Here we discovered that ponatinib significantly improved insulin sensitivity in leptin deficient obese mice. In addition to that, ponatinib treatment remarkably ameliorated high fat diet-induced hyperlipidemia and inhibited ectopic lipid deposition in the liver. Interestingly, although ponatinib did not reduce but increase the weight of white adipose tissue (WAT), it remarkably suppressed the inflammatory response in WAT and preserved its function. Mechanistically, we showed that ponatinib had no direct effect on hepatocyte or adipocyte but attenuated free fatty acid (FFA) induced macrophage transformation from pro-inflammatory to anti-inflammatory phenotype. Moreover, adipocytes co-cultured with FFA-treated macrophages exhibited insulin resistance, while pre-treat these macrophages with ponatinib can ameliorate this process. These results suggested that the beneficial effects of ponatinib on metabolic disorders are achieved by inhibiting the inflammatory phenotypic transformation of ATMs, thereby maintaining the physiological function of adipose tissue under excessive obesity. The data here not only revealed the novel therapeutic function of ponatinib, but also provided a theoretical basis for the application of multi-target tyrosine kinase inhibitors in metabolic diseases.

A typical colorimetric sandwich-type sensor relies on dual antibodies/aptamers to specifically visualize the targets. The requirement of dual antibodies/aptamers and low signal intensity inevitably increases the design difficulty and compromises the sensing sensitivity. In this work, a novel sandwich-type aptasensor was developed using single aptamer-functionalized magnetic nanoparticles as a specific recognition unit to target cancer cells and a bimetallic metal–organic frameworks (MOFs)-based nanozymes as a colorimetric signal amplification unit. The well-defined crystalline structure of UIO-66 MOFs enabled the introduction of Fe/Zr bimetal nodes, which possessed integrated properties of the peroxidase-like nanozyme activity and direct coordinately binding to the cell surface. Such a novel construction strategy of sandwich-type aptasensors achieved simple, sensitive, and specific detection of the target cancer cells, which will inspire the development of biosensors.

Low-molecular-weight organic acids (LMWOAs) are widely distributed in forests. Fresh leaves, litter, humus, and the topsoil layer of representative Rhododendron delavayi (RD), Rhododendron agastum (RA), and Rhododendron irroratum (RI) in the Baili Rhododendron National Forest Park were sampled to explore their seasonal changes. The contents of oxalic, tartaric, malic, citric, acetic, lactic, succinic, and formic acids in samples from different seasons were determined by high-performance liquid chromatography. The results showed that the composition and content of the LMWOAs in the fresh leaves, litter, humus, and topsoil layer of the rhododendrons were affected by the tree species, samples, and season. The main LMWOA was oxalic acid (the average content in the samples was 195.31 µg/g), followed by malic acid (the average content in the samples was 68.55 µg/g) and tartaric acid (the average content in the samples was 59.82 µg/g). Succinic acid had the lowest content; the average content in the samples was 18.40 µg/g. The LMWOAs of the RD were the highest (the average content in the samples was 517.42 µg/g), and the LMWOAs of the RI were the lowest (the average content in the samples was 445.18 µg/g). The LMWOAs in the three rhododendron forests were in the order of fresh leaves > litter > humus > soil layers. This study showed the seasonal distribution characteristics of LMWOAs in three evergreen broadleaf rhododendron forests, and the results provide a reference for ecosystem management and the protection of wild rhododendron forests.

Abstract Background Differentiating glioma recurrence from treatment-related changes can be challenging on conventional imaging. We evaluated the efficacy of quantitative parameters measured by dual-energy spectral computed tomographic (CT) for this differentiation. Methods Twenty-eight patients were examined by dual-energy spectral CT. The effective and normalized atomic number (Zeff and Zeff-N, respectively); spectral Hounsfield unit curve (λHU) slope; and iodine and normalized iodine concentration (IC and ICN, respectively) in the post-treatment enhanced areas were calculated. Pathological results or clinicoradiologic follow-up of ≥2 months were used for final diagnosis. Nonparametric and t-tests were used to compare quantitative parameters between glioma recurrence and treatment-related changes. Sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively), and accuracy were calculated using receiver operating characteristic (ROC) curves. Predictive probabilities were used to generate ROC curves to determine the diagnostic value. Results Examination of pre-contrast λHU, Zeff, Zeff-N, IC, ICN, and venous phase ICN showed no significant differences in quantitative parameters (P > 0.05). Venous phase λHU, Zeff, Zeff-N, and IC in glioma recurrence were higher than in treatment-related changes (P

ObjectivesPhosphatase and tensin homolog (PTEN) mutation is an indicator of poor prognosis of low-grade and high-grade glioma. This study built a reliable model from multi-parametric magnetic resonance imaging (MRI) for predicting the PTEN mutation status in patients with glioma.MethodsIn this study, a total of 244 patients with glioma were retrospectively collected from our center (n = 77) and The Cancer Imaging Archive (n = 167). All patients were randomly divided into a training set (n = 170) and a validation set (n = 74). Three models were built from preoperative MRI for predicting PTEN status, including a radiomics model, a convolutional neural network (CNN) model, and an integrated model based on both radiomics and CNN features. The performance of each model was evaluated by accuracy and the area under the receiver operating characteristic curve (AUC).ResultsThe CNN model achieved an AUC of 0.84 and an accuracy of 0.81, which performed better than did the radiomics model, with an AUC of 0.83 and an accuracy of 0.66. Combining radiomics with CNN will further benefit the predictive performance (accuracy = 0.86, AUC = 0.91).ConclusionsThe combination of both the CNN and radiomics features achieved significantly higher performance in predicting the mutation status of PTEN in patients with glioma than did the radiomics or the CNN model alone.

Background: To develop and validate a deep learning signature (DLS) from diffusion tensor imaging (DTI) for predicting overall survival in patients with infiltrative gliomas, and to investigate the biological pathways underlying the developed DLS. Methods: The DLS was developed based on a deep learning cohort (n = 688). The key pathways underlying the DLS were identified on a radiogenomics cohort with paired DTI and RNA-seq data (n=78), where the prognostic value of the pathway genes was validated in public databases (TCGA, n = 663; CGGA, n = 657). Findings: The DLS was associated with survival (log-rank P < 0.001) and was an independent predictor (P < 0.001). Incorporating the DLS into existing risk system resulted in a deep learning nomogram predicting survival better than either the DLS or the clinicomolecular nomogram alone, with a better calibration and classification accuracy (net reclassification improvement 0.646, P < 0.001). Five kinds of pathways (synaptic transmission, calcium signaling, glutamate secretion, axon guidance, and glioma pathways) were significantly correlated with the DLS. Average expression value of pathway genes showed prognostic significance in our radiogenomics cohort and TCGA/CGGA cohorts (log-rank P < 0.05). Interpretation: DTI-derived DLS can improve glioma stratification by identifying risk groups with dysregulated biological pathways that contributed to survival outcomes. Therapies inhibiting neuron-to-brain tumor synaptic communication may be more effective in high-risk glioma defined by DTI-derived DLS. Funding: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

The manufacturing industry has created a rapid evolution of the economy, but it has also negatively impacted the ecosystem. A better understanding of the manufacturing industry in green growth is crucial to achieving the sustainability goals in China’s high-quality development stage and is better for identifying the impact of scale effect or technological effect in EKC. In this research, a super-efficiency slacks-based measure model is proposed to evaluate the green growth efficiency of 27 manufacturing industries, and a Luenberger index method is adopted to interpret the driving forces of efficiency. The results demonstrate that green growth efficiency in the manufacturing industry shows a fluctuating upward trend, and more than 60% of the industries are in a gray growth state. The growth of green growth efficiency mainly depends on the pulling effect of technological dividends brought by technological progress, rather than the improvement of technical efficiency. As the industry heterogeneity is analyzed, technology-intensive industries still dominate in the process of manufacturing industry and have shown a significant upward trend. Finally, some suggestions are proposed from the perspective of the government and enterprises.

Slug flow as one of the typical two-phase flow patterns occurs widely in industry. The fluctuating phenomenon in slug flow is harmful to the pipeline system and should be suppressed. Flow-pattern modulation by swirl has been widely used to satisfy practical application. In this work, influences of swirl on pressure gradient and interface morphology in a gas–liquid slug flow were studied by visualization experiments. The results showed that slug flow will transform to swirling intermittent flow when the gas and liquid velocity is relatively high. In this case, pressure drop in the slug flow is higher and its fluctuation within a relatively narrow range compared with those in a non-swirl slug flow; the probability density function distribution is more concentrated in the swirling intermittent flow; the slug flow transforms to the flow pattern altering between gas column and gas slug. The slug flow was kept downstream of the swirler when the gas and liquid velocity is relatively low. In this case, effects of swirl on both pressure drop and interface morphology are not obvious. Along the streamwise direction, the morphology interface, fluctuation of pressure drop and pressure signals showed that the swirling intermittent flow gradually transforms to non-swirl slug flow. Finally, the transition boundaries between these flow patterns were proposed and compared with other published transition boundaries in swirling and non-swirling flows.

Patients with hepatitis B virus (HBV)-related cirrhosis (HBV-RC) and minimal hepatic encephalopathy (MHE) exhibit alterations in homotopic inter-hemispheric functional connectivity (FC) and corpus callosum (CC) degeneration. However, the progression of inter-hemispheric dysconnectivity in cirrhotic patients from no MHE (NMHE) to MHE and its association with the progression of diseased-related cognitive impairment remain uncharacterized. We hypothesized that inter-hemispheric dysconnectivity exists in NMHE patients and further deteriorates at the MHE stage, which is associated with performance measured by psychometric hepatic encephalopathy scores (PHES) that can characterize cirrhotic patients with NMHE and MHE. Using inter-hemispheric homotopic FC and CC (and its subfields) volumetric measurements in 31 patients with HBV-RC (17 with NMHE and 14 with MHE) and 37 healthy controls, we verified that MHE patients had significant attenuated inter-hemispheric homotopic FC in the bilateral cuneus, post-central gyrus, inferior parietal lobule, and superior temporal gyms, as well as CC degeneration in total CC, CC2, CC3, and CC4 (each comparison had a corrected P < 0.05). In contrast, NMHE patients had relatively less severe inter-hemispheric homotopic FC and no CC degeneration. In addition, the degeneration of the CC and inter-hemispheric homotopic functional disconnections correlated with poor PHES performances in all cirrhotic patients (NMHE and MHE). Furthermore, impairment of inter-hemispheric homotopic FC partially mediated the association between CC degeneration and worse PHES performance. Notably, a combination of inter-hemispheric homotopic FC and CC volumes had higher discriminative values according to the area under the curve (AUC) score (AUC = 0.908, P < 0.001) to classify patients into MHE or NMHE groups when compared with either alone. Our findings shed light on the progression of inter-hemispheric dysconnectivity in relation to the progression of disease-related cognitive impairment in patients with HBV-RC. Keywords: Corpus callosum, Hepatitis-B-virus-related cirrhosis, Minimal hepatic encephalopathy, Resting-state functional MRI, Structural MRI, Voxel-mirrored homotopic connectivity

Abstract Background The miRNA cluster miR-17-92 is known to act as an oncogene in various cancers. Members of this cluster were also found to be involved in some other pathological process, such as steatosis, which is a pivotal event in the initiation and progression of nonalcoholic fatty liver disease (NAFLD). This study aimed to explore whether miR-17, one of the most functional miRNAs in the miR-17-92 family, participates in the process of steatosis in hepatoma cells. Methods We developed both a miR-17-expressing transgenic mouse model and a miR-17-expressing HepG2 cell model, the latter was established via stable transfection. Real-time PCR and western blot were applied to measure the expression levels of miR-17 and the potential target gene CYP7A1. The luciferase assay was used to confirm direct binding of miR-17 and CYP7A1. The oleic acid induction assay and Oil-Red-O staining were performed to support the determination of steatotic changes in HepG2 cell. Results Extensive steatotic changes were observed in the livers of transgenic mice. Fewer were seen in the wild-type animals. CYP7A1 was confirmed as a target gene of miR-17, and the expression of CYP7A1 was found to be negatively regulated in both the transgenic mice liver cells and the miR-17-expressing HepG2 cells. CYP7A1 was found to participate in miR-17-induced steatosis, as its repressed expression in miR-17 HepG2 cells exacerbated steatotic change. Re-introduction of CYP7A1 into miR-17 HepG2 cell partially alleviated steatosis. Conclusions miR-17 is a novel regulator of CYP7A1 signaling in hepatic lipid metabolism, suggesting a potential therapeutic approach for fatty liver.

Background and purpose: To investigate effects of radiotherapy on normal brain tissue using in vivo neuroimaging in patients with nasopharyngeal carcinoma (NPC). Methods and materials: We used longitudinal MRI to monitor structural brain changes during standard radiotherapy in patients newly diagnosed with NPC. We assessed volumetric measures in 63 patients at 2–3 time points before and after radiotherapy, with 20 NPC-free participants as normal controls. Images were processed using validated software (FreeSurfer). Automated results were inspected visually for accuracy. We examined changes in volume of the whole brain, gray matter, white matter, and ventricles, as well as in cerebral volumes partitioned into temporal, frontal, parietal, and occipital lobes. A linear mixed model was used to evaluate longitudinal changes in these measurements. Statistical significance was evaluated at p

This study aimed to evaluate the diagnostic potential of a novel RFO model in differentiating GBM and SBM with multiparametric MR sequences collected from 244 (131 GBM and 113 SBM) patients. Three basic volume of interests (VOIs) were delineated on the conventional axial MR images (T1WI, T2WI, T2_FLAIR, and CE_T1WI), including volumetric non-enhanced tumor (nET), enhanced tumor (ET), and peritumoral edema (pTE). Using the RFO model, radiomics features extracted from different multiparametric MRI sequence(s) and VOI(s) were fused and the best sequence and VOI, or possible combinations, were determined. A multi-disciplinary team (MDT)-like fusion was performed to integrate predictions from the high-performing models for the final discrimination of GBM vs. SBM. Image features extracted from the volumetric ET (VOIET) had dominant predictive performances over features from other VOI combinations. Fusion of VOIET features from the T1WI and T2_FLAIR sequences via the RFO model achieved a discrimination accuracy of AUC = 0.925, accuracy = 0.855, sensitivity = 0.856, and specificity = 0.853, on the independent testing cohort 1, and AUC = 0.859, accuracy = 0.836, sensitivity = 0.708, and specificity = 0.919 on the independent testing cohort 2, which significantly outperformed three experienced radiologists (p = 0.03, 0.01, 0.02, and 0.01, and p = 0.02, 0.01, 0.45, and 0.02, respectively) and the MDT-decision result of three experienced experts (p = 0.03, 0.02, 0.03, and 0.02, and p = 0.03, 0.02, 0.44, and 0.03, respectively).

Conventional MRI studies showed that radiation-induced brain necrosis in patients with nasopharyngeal carcinoma (NPC) in years after radiotherapy (RT) could involve brain gray matter (GM) and impair brain function. However, it is still unclear the radiation-induced brain morphological changes in NPC patients with normal-appearing GM in the early period after RT. In this study, we acquired high-resolution brain structural MRI data from three groups of patients, 22 before radiotherapy (pre-RT) NPC patients with newly diagnosed but not yet medically treated, 22 NPC patients in the early-delayed stage after radiotherapy (post-RT-ED), and 20 NPC patients in the late-delayed stage after radiotherapy (post-RT-LD), and then analyzed the radiation-induced cortical thickness alteration in NPC patients after RT. Using a vertex-wise surface-based morphometry (SBM) approach, we detected significantly decreased cortical thickness in the precentral gyrus (PreCG) in the post-RT-ED group compared to the pre-RT group. And the post-RT-LD group showed significantly increased cortical thickness in widespread brain regions, including the bilateral inferior parietal, left isthmus of the cingulate, left bank of the superior temporal sulcus and left lateral occipital regions, compared to the pre-RT group, and in the bilateral PreCG compared to the post-RT-ED group. Similar analysis with ROI-wise SBM method also found the consistent results. These results indicated that radiation-induced brain injury mainly occurred in the post-RT-LD group and the cortical thickness alterations after RT were dynamic in different periods. Our findings may reflect the pathogenesis of radiation-induced brain injury in NPC patients with normal-appearing GM and an early intervention is necessary for protecting GM during RT.

Background: Increasing evidence indicates that early radiation-induced subtle cerebral changes may be the precursors to permanent brain dysfunction at the late-delayed (LDS) post-radiotherapy (RT) stage. In this study, we aim to track the RT-related longitudinal brain activity in nasopharyngeal carcinoma (NPC) patients and to determine whether early abnormal brain activity can predict late neurocognitive dysfunction after RT.Methods: Thirty-three NPC patients were finally included and longitudinally followed up at the following time points: prior to treatment initiation, early-delayed stage (EDS, 1–3 months), and LDS (six months) after RT. Fifteen comparable healthy controls (HCs) were finally included and followed up in parallel. Montreal Cognitive Assessment (MoCA) was used to assess the general cognitive function. Brain activity was recorded via resting-state fMRI and regional homogeneity (ReHo). A whole-brain voxel-wise-based one-way repeated-measure analysis of variance (ANOVA) was conducted to evaluate the longitudinal ReHo changes among the three time points for NPC patients and HCs, respectively. Results were reported at the significant level of a threshold of two-tailed voxel-wise P < 0.01 and cluster level P < 0.05 with Gaussian Random Field (GRF) correction. Finally, the efficacies of the aberrant ReHo at EDS for predicting the cognitive impairment at LDS in NPC patients were evaluated.Results: Significant differences were detected in ReHo among the three time points in NPC patients but not in HCs. Aberrant ReHo was distributed in the bilateral cerebellum, the right temporal lobe, and the left insular areas, which showed different dynamic changes patterns over time. Logistic regression model combining the mean ReHo, age, and irradiation dose on the bilateral temporal lobe had the highest diagnostic efficiency according to the area under the curve (AUC) score (AUC = 0.752, P = 0.023).Conclusions: The post-RT brain activity revealed by ReHo in NPC patients was dynamic, complex, and multifactorial. Furthermore, the combination of the aberrant ReHo at EDS, age, and irradiation dose may serve as a potential biomarker of the RT-induced cognitive impairments at LDS.

ABSTRACT Networks encode the interactions between the components in complex systems and play an essential role in understanding complex systems. Microbial ecological networks provide a system-level insight for comprehensively understanding complex microbial interactions, which play important roles in microbial community assembly. However, microbial ecological networks are in their infancy of both network inference and biological interpretation. In this perspective, we articulate the theory gaps and limitations in building and interpreting microbial ecological networks, emphasize developing tools for evaluating the predicted microbial interaction relationships, and predict the potential applications of microbial ecological networks in the long run.

Coastal ecosystems experience some of the most active land–ocean interactions in the world, and they are characterized by high primary productivity and biological diversity in the sediment. Given the roles of microorganisms in soil biogeochemical cycling and their multifaceted influence on soil ecosystems, it is critical to understand the variations and drivers of soil microbial communities across coastal ecosystems. Here, we studied soil bacterial community dynamics at different sites (from seawater to freshwater) in the Yellow River Delta, China. Bacterial community composition and diversity over four seasons were analyzed through 16S rRNA genes. Notably, the bacterial community near the ocean had the lowest alpha-diversity when compared with the other sites. No significant differences in bacterial communities among seasons were found, indicating that seasonal variation in temperature had little influence on bacterial community in the newly formed wetlands in the Yellow River Delta. Bacterial community structure changed substantially along the salinity gradient, revealing a clear ecological replacement along the gradual transformation gradient from freshwater to seawater environment. Redundancy analysis revealed that salinity was the main driver of variations in bacterial community structure and explained 17.5% of the variability. Our study provides a better understanding of spatiotemporally determined bacterial community dynamics in coastal ecosystems.

The processes in construction are more likely than others to breed unsafe behaviors, and the consequences of these actions can be serious. This paper first reviews the research status on unsafe behavior in construction teams. It then analyzes the complex mechanisms that lead to unsafe behavior and constructs a three-layer structural model based on agent-based modeling (ABM) technology. This modeling deals with complexity and elaborates on key points and potential research ideas in the study of unsafe behavior in construction teams. Using the ABM method, the effects of different incentive strategies on the safe behavior of construction teams under different management scenarios were studied. The results showed that when members have a fair perception of the situation, the effect of the excess performance reward distribution, according to the member’s safety awareness level, is better than the average distribution effect. This is the case whether the member’s safety behavior level is positively or negatively related to the member’s safety awareness level. This study proves the feasibility, validity, and universality of the three-layer structural model. It also reaches certain management conclusions and ideas for further development. The purpose of this paper is to provide a reference for research on the containment and prevention of unsafe behavior in construction teams.

Gut microbiota has been implicated as a pivotal contributing factor in diet-related obesity; however, its role in development of disease phenotypes in human genetic obesity such as Prader–Willi syndrome (PWS) remains elusive. In this hospitalized intervention trial with PWS (n = 17) and simple obesity (n = 21) children, a diet rich in non-digestible carbohydrates induced significant weight loss and concomitant structural changes of the gut microbiota together with reduction of serum antigen load and alleviation of inflammation. Co-abundance network analysis of 161 prevalent bacterial draft genomes assembled directly from metagenomic datasets showed relative increase of functional genome groups for acetate production from carbohydrates fermentation. NMR-based metabolomic profiling of urine showed diet-induced overall changes of host metabotypes and identified significantly reduced trimethylamine N-oxide and indoxyl sulfate, host-bacteria co-metabolites known to induce metabolic deteriorations. Specific bacterial genomes that were correlated with urine levels of these detrimental co-metabolites were found to encode enzyme genes for production of their precursors by fermentation of choline or tryptophan in the gut. When transplanted into germ-free mice, the pre-intervention gut microbiota induced higher inflammation and larger adipocytes compared with the post-intervention microbiota from the same volunteer. Our multi-omics-based systems analysis indicates a significant etiological contribution of dysbiotic gut microbiota to both genetic and simple obesity in children, implicating a potentially effective target for alleviation. Research in context: Poorly managed diet and genetic mutations are the two primary driving forces behind the devastating epidemic of obesity-related diseases. Lack of understanding of the molecular chain of causation between the driving forces and the disease endpoints retards progress in prevention and treatment of the diseases. We found that children genetically obese with Prader–Willi syndrome shared a similar dysbiosis in their gut microbiota with those having diet-related obesity. A diet rich in non-digestible but fermentable carbohydrates significantly promoted beneficial groups of bacteria and reduced toxin-producers, which contributes to the alleviation of metabolic deteriorations in obesity regardless of the primary driving forces.

Previous studies suggested that dietary fatty acids could affect blood lipids by interacting with genetic variations in fatty acid desaturase 1 (FADS1). However, little is known about their direct effects on coronary artery disease (CAD). The aim of this study was to evaluate whether dietary n-3 long-chain polyunsaturated fatty acids (LCPUFAs)-eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) could modulate the effect of FADS1 rs174547 polymorphism on CAD.FADS1 single-nucleotide polymorphisms rs174547 genotypes were measured in 440 CAD patients and 838 healthy controls. Dietary EPA and DHA intakes were assessed with a validated quantitative frequency food questionnaire. The association between FADS1 rs174547 and CAD was estimated using logistic regression under both dominant and additive genetic models. The interactions between rs174547 polymorphism and LCPUFAs were analyzed by using multiple logistic regression and the "genotype × n-3 LCPUFAs" interaction term was included into the model.We found that the minor T allele of FADS1 rs174547 increased CAD risk (OR = 1.36, 95%CIs 1.03-1.80), and observed significant interaction between rs174547 and dietary EPA intakes on CAD (P-interaction = 0.028). The T-allele was only associated with higher CAD risk among individuals with lower dietary EPA intakes, but not in those with higher EPA intakes. Similarly, significant interaction was also observed between rs174547 and dietary DHA intakes on CAD (P-interaction = 0.020).Dietary n-3 LCPUFA intakes could modulate the association between FADS1 rs174547 polymorphism and CAD. High dietary n-3 LCPUFA intakes could negate the unfavorable effect of genetic variation in FADS1 on CAD in middle-aged and elderly Chinese population.

This study examined the bacterial and archaeal diversity from a worldwide range of wetlands soils and sediments using a meta-analysis approach. All available 16S rRNA gene sequences recovered from wetlands in public databases were retrieved. In November 2012, a total of 12677 bacterial and 1747 archaeal sequences were collected in GenBank. All the bacterial sequences were assigned into 6383 operational taxonomic units (OTUs 0.03), representing 31 known bacterial phyla, predominant with Proteobacteria (2791 OTUs), Bacteroidetes (868 OTUs), Acidobacteria (731 OTUs), Firmicutes (540 OTUs), and Actinobacteria (418 OTUs). The genus Flavobacterium (11.6% of bacterial sequences) was the dominate bacteria in wetlands, followed by Gp1, Nitrosospira, and Nitrosomonas. Archaeal sequences were assigned to 521 OTUs from phyla Euryarchaeota and Crenarchaeota. The dominating archaeal genera were Fervidicoccus and Methanosaeta. Rarefaction analysis indicated that approximately 40% of bacterial and 83% of archaeal diversity in wetland soils and sediments have been presented. Our results should be significant for well-understanding the microbial diversity involved in worldwide wetlands.

BACKGROUND AND PURPOSE: Cognitive impairment is a well-described phenomenon in end-stage renal disease (ESRD) patients. However, its pathogenesis remains poorly understood. The primary focus of this study was to examine structural and functional brain deficits in ESRD patients. MATERIALS AND METHODS: Thirty ESRD patients on hemodialysis (without clinical neurological disease) and 30 age- and gender-matched control individuals (without renal or neurological problems) were recruited in a prospective, single-center study. High-resolution structural magnetic resonance imaging (MRI) and resting state functional MRI were performed on both groups to detect the subtle cerebral deficits in ESRD patients. Voxel-based morphometry was used to characterize gray matter deficits in ESRD patients. The impact of abnormal morphometry on the cerebral functional integrity was investigated by evaluating the alterations in resting state functional connectivity when brain regions with gray matter volume reduction were used as seed areas. RESULTS: A significant decrease in gray matter volume was observed in ESRD patients in the bilateral medial orbito-prefrontal cortices, bilateral dorsal lateral prefrontal cortices, and the left middle temporal cortex. When brain regions with gray matter volume reduction were used as seed areas, the integration was found to be significantly decreased in ESRD patients in the fronto-cerebellum circuits and within prefrontal circuits. In addition, significantly enhanced functional connectivity was found between the prefrontal cortex and the left temporal cortex and within the prefrontal circuits. CONCLUSIONS: Our study revealed that both the structural and functional cerebral cortices were impaired in ESRD patients on routine hemodialysis.

BACKGROUND: In the past twenty years, codeine-containing cough syrups (CCS) was recognized as a new type of addictive drugs. However, the exact neurobiologic mechanisms underlying CCS-dependence are still ill-defined. The aims of this study are to identify CCS-related modulations of neural activity during the resting-state in CCS-dependent individuals and to investigate whether these changes of neural activity can be related to duration of CCS use, the first age of CCS use and impulse control deficits in CCS-dependent individuals. We also want to observe the impact of gray matter deficits on these functional results. METHODOLOGY/PRINCIPAL FINDINGS: Thirty CCS-dependent individuals and 30 control subjects participated. Resting-state functional MRI was performed by using gradient-echo echo-planar imaging sequence. Regional homogeneity (ReHo) was calculated by using REST software. Voxel-based analysis of the ReHo maps between controls and CCS-dependent groups was performed using two-sample t tests (p

Background. Cardiometabolic risk factors significantly accelerate the progression of coronary artery disease (CAD); however, whether CAD patients in South China are aware of the prevalence of these risk factors is not clear yet. Methods. The study consisted of 2312 in-admission CAD patients from 2008 to 2011 in South China. Disease history including hypertension, dyslipidemia, and diabetes was relied on patients' self-reported records. Physical and clinical examinations were tested to assess the real prevalence of the cardiometabolic risk factors. Results. 57.9% of CAD patients had more than 3 cardiometabolic risk factors in terms of the metabolic syndrome. The self-known and real prevalence of hypertension, diabetes, and dyslipidemia were 56.6%, 28.3%, and 25.1% and 91.3%, 40.9%, and 92.0%, respectively. The awareness rates were 64.4%, 66.3%, and 28.5% for hypertension, diabetes, and dyslipidemia. The prevalence of cardiometabolic risk factors was significantly different among gender and among disease status. Conclusions. Most CAD patients in South China had more than three cardiometabolic risk factors. However, the awareness rate of cardiometabolic diseases was low, especially for dyslipidemia. Strategies of routine physical examination programs are needed for the early detection and treatment of cardiometabolic risk factors in order to prevent CAD progression and prognosis.

BACKGROUND: To investigate the WM microstructure deficits in heroin dependent individuals (HDIs) with different length of heroin dependence, and to investigate whether these WM deficits can be related to the duration of heroin use and to decision-making deficits in HDIs. METHODOLOGY/PRINCIPAL FINDINGS: Thirty-six HDIs [including eighteen sHDIs (duration of heroin dependent is less than 10 years) and eighteen lHDIs (duration of dependent is between 10:20 years)] and sixteen healthy controls participated in this study. Whole brain voxel-wise analysis of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da) and radial diffusivity (Dr) were performed by tract-based spatial statistics (TBSS) to localize abnormal WM regions among groups. TBSS demonstrated that sHDIs had significantly lower FA than controls in right orbito-frontal WM, bilateral temporal WM and right parietal WM. The lHDIs had significantly lower FA throughout the brain compared with the controls and sHDIs. The lHDIs had significantly lower Da than controls in bilateral inferior frontaloccipital fasciculus, bilateral splenium of corpus callosum, left inferior longitudinal fasciculus, and had significantly higher Dr than controls in bilateral uncinatus fasciculus, bilateral inferior frontaloccipital fasciculus and bilateral cortical spinal fasciculus. Volume-of-interest (VOI) analyses detect the changes of diffusivity indices in the regions with FA abnormalities revealed by control vs sHDIs. In most VOIs, FA reductions were caused by the increase in Dr as well as the decrease in Da. Correlation analysis was used to assess the relationship between FA and behavioral measures in HDIs and controls available. Significantly positively correlations were found between the FA values in the right orbital-frontal WM, right parietal WM and IGT performance. CONCLUSIONS: The extent and severity of WM integrity deficits in HDIs was associated with the length of heroin dependent. Furthermore, abnormal WM microstructure may correlate with decision-making impairments in HDIs.