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There are complex interactions between the gut and the brain. With increasing research on the relationship between gut microbiota and brain function, accumulated clinical and preclinical evidence suggests that gut microbiota is intimately involved in the pathogenesis of neurodegenerative diseases (NDs). Increasingly studies are beginning to focus on the association between gut microbiota and central nervous system (CNS) degenerative pathologies to find potential therapies for these refractory diseases. In this review, we summarize the changes in the gut microbiota in Alzheimer's disease, Parkinson's disease, multiple sclerosis, and amyotrophic lateral sclerosis and contribute to our understanding of the function of the gut microbiota in NDs and its possible involvement in the pathogenesis. We subsequently discuss therapeutic approaches targeting gut microbial abnormalities in these diseases, including antibiotics, diet, probiotics, and fecal microbiota transplantation (FMT). Furthermore, we summarize some completed and ongoing clinical trials of interventions with gut microbes for NDs, which may provide new ideas for studying NDs. [ABSTRACT FROM AUTHOR]

In this paper, an improved 4H-SiC metal semiconductor field effect transistor with a partially undoped region and tortuous channel (URTC MESFET) is proposed. Based on the drain side-recessed p-buffer structure (DS-RPB MESFET), the URTC MESFET introduces a recessed region in the gate-source side channel and an undoped region in the gate-drain side channel, also, the recessed regions in the p-buffer layer are optimized. Simulation results demonstrate that the URTC MESFET achieves a 63% increase in breakdown voltage compared to the double recessed structure (DR MESFET), with the saturation current increasing from 458.13 mA/mm to 485.05 mA/mm. Furthermore, the maximum output power improves from 4.31 W/mm to 7.71 W/mm, representing a 79% enhancement. Additionally, the cut-off frequency increases from 22.4 GHz to 23.29 GHz. The power added efficiency increases from 56% in the DR structure to 67%. Therefore, the URTC structure exhibits significant improvements in DC characteristics, AC characteristics, and power added efficiency, showing great potential for applications in high-power, RF, and high-efficiency domains. [ABSTRACT FROM AUTHOR]

A very important cause of the frustration with drug therapy for central nervous system (CNS) diseases is the failure of drug delivery. The blood–brain barrier (BBB) prevents most therapeutic molecules from entering the brain while maintaining CNS homeostasis. Scientists are keen to develop new brain drug delivery systems to solve this dilemma. Extracellular vesicles (EVs), as a class of naturally derived nanoscale vesicles, have been extensively studied in drug delivery due to their superior properties. This review will briefly present current brain drug delivery strategies, including invasive and non-invasive techniques that target the brain, and the application of nanocarriers developed for brain drug delivery in recent years, especially EVs. The cellular origin of EVs affects the surface protein, size, yield, luminal composition, and other properties of EVs, which are also crucial in determining whether EVs are useful as drug carriers. Stem cell-derived EVs, which inherit the properties of parental cells and avoid the drawbacks of cell therapy, have always been favored by researchers. Thus, in this review, we will focus on the application of stem cell-derived EVs for drug delivery in the CNS. Various nucleic acids, proteins, and small-molecule drugs are loaded into EVs with or without modification and undergo targeted delivery to the brain to achieve their therapeutic effects. In addition, the challenges facing the clinical application of EVs as drug carriers will also be discussed. The directions of future efforts may be to improve drug loading efficiency and precise targeting. [ABSTRACT FROM AUTHOR]

Acid mine drainage (AMD) is usually acidic (pH < 4) and contains high concentrations of dissolved metals and metalloids, making AMD a typical representative of extreme environments. Recent studies have shown that microbes play a key role in AMD bioremediation, and secondary metabolite biosynthetic gene clusters (smBGCs) from AMD microbes are important resources for the synthesis of antibacterial and anticancer drugs. Here, 179 samples from 13 mineral types were used to analyze the putative novel microorganisms and secondary metabolites in AMD environments. Among 7,007 qualified metagenome-assembled genomes (MAGs) mined from these datasets, 6,340 MAGs could not be assigned to any GTDB species representative. Overall, 11,856 smBGCs in eight categories were obtained from 7,007 qualified MAGs, and 10,899 smBGCs were identified as putative novel smBGCs. We anticipate that these datasets will accelerate research in the field of AMD bioremediation, aid in the discovery of novel secondary metabolites, and facilitate investigation into gene functions, metabolic pathways, and CNPS cycles in AMD. Measurement(s) Metagenome Technology Type(s) Next Generation Sequencing Sample Characteristic - Environment acid mine drainage Sample Characteristic - Location Guizhou Province • Marsberg • Municipality of Canaa dos Carajas • North Wales • Town of Vershire • State of Washington • Guangdong Province • Germany • County (Sweden) • Commonwealth of Pennsylvania • Province of Ontario • Hunan Province • Jiangxi Province • Guangxi Zhuang Autonomous Region • Anhui Province • Fujian Province [ABSTRACT FROM AUTHOR]

Stroke, a lethal neurological disease, accounts for a grave economic burden on society. Despite extensive basic and clinical studies on stroke prevention, a precise effective treatment approach for stroke at this stage remains unavailable. The majority of our body's gut microbiota plays a vital role in food digestion, immune regulation, and nervous system development, which is highly associated with the development of some diseases. Multiple clinical studies have documented variation in the composition of gut microbiota between stroke patients and healthy counterparts. Moreover, the intervention of intestinal symbiotic microorganisms via several mechanisms plays an active role in stroke prognosis. In the prevention and treatment of stroke, the gut microbiota gives off a seductive glow, this is a promising therapeutic target. This paper summarizes the current knowledge of stroke and gut microbiota, and systematically describes the possible mechanisms of interaction between stroke and gut microbiota, the relationship between stroke-related risk factors and gut microbiota, and the treatment of gut flora using microorganisms. Thus, it could valuably elucidate the correlation of gut microbiota with stroke incidence, providing stroke researchers with a new strategy for stroke prevention and treatment by regulating gut microbiota. [ABSTRACT FROM AUTHOR]

Physical models used to forecast the temporal occurrence of rainfall-induced shallow landslides are based on deterministic laws. Owing to the existing measuring technology and our knowledge of the physical laws controlling landslide initiation, model uncertainties are due to an inability to accurately quantify the model input parameters and rainfall forcing data. An uncertainty analysis of slope instability prediction provides a rationale for refining the geotechnical models. The Transient Rainfall Infiltration and Grid-based Regional Slope Stability-Probabilistic (TRIGRS-P) model adopts a probabilistic approach to compute the changes in the Factor of Safety (FS) due to rainfall infiltration. Slope Infiltration Distributed Equilibrium (SLIDE) is a simplified physical model for landslide prediction. The new code (SLIDE-P) is also modified by adopting the same probabilistic approach to allow values of the SLIDE model input parameters to be sampled randomly. This study examines the relative importance of rainfall variability and the uncertainty in the other variables that determine slope stability. The precipitation data from weather stations, China Meteorological Administration Land Assimilation System 2.0 (CLDAS2.0), China Meteorological Forcing Data set precipitation (CMFD), and China geological hazard bulletin are used to drive TRIGRS, SLIDE, TRIGRS-P and SLIDE-P models. The TRIGRS-P and SLIDE-P models are used to generate the input samples and to calculate the values of FS. The outputs of several model runs with varied input parameters and rainfall forcings are analyzed statistically. A comparison suggests that there are significant differences in the simulations of the TRIGRS-P and SLIDE-P models. Although different precipitation data sets are used, the simulation results of TRIGRS-P are more concentrated. This study can inform the potential use of numerical models to forecast the spatial and temporal occurrence of regional rainfall-induced shallow landslides. [ABSTRACT FROM AUTHOR]

The probability of quantitative precipitation forecast (PQPF) of three Bayesian Model Averaging (BMA) models based on three raw super ensemble prediction schemes (i. e., A, B, and C) are established, which through calibration of their parameters using 1–3 day precipitation ensemble prediction systems (EPSs) from the China Meteorological Administration (CMA), the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) and observation during land-falling of three typhoons in south-east China in 2013. The comparison of PQPF shows that the performance is better in the BMA than that in raw ensemble forecasts. On average, the mean absolute error (MAE) of 1 day lead time forecast is reduced by 12.4%, and its continuous ranked probability score (CRPS) of 1–3 day lead time forecast is reduced by 26.2%, respectively. Although the amount of precipitation prediction by the BMA tends to be underestimated, but in view of the perspective of probability prediction, the probability of covering the observed precipitation by the effective forecast ranges of the BMA are increased, which is of great significance for the early warning of torrential rain and secondary disasters induced by it. [ABSTRACT FROM AUTHOR]

Hydrological processes exert enormous influences on the land surface water and energy balance, and have a close relationship with human society. We have developed a new hydrological runoff parameterization called XXT to improve the performance of a coupled land surface-atmosphere modeling system. The XXT parameterization, which is based upon the Xinanjiang hydrological model and TOPMODEL, includes an optimized function of runoff calculation with a new soil moisture storage capacity distribution curve (SMSCC). We then couple XXT with the Global/Regional Assimilation Prediction System (GRAPES) and compare it to GRAPES coupled with a simple water balance model (SWB). For the model evaluation and comparison, we perform 72-h online simulations using GRAPES-XXT and GRAPES-SWB during two torrential events in August 2007 and July 2008, respectively. The results show that GRAPES can reproduce the rainfall distribution and intensity fairly well in both cases. Differences in the representation of feedback processes between surface hydrology and the atmosphere result in differences in the distributions and amounts of precipitation simulated by GRAPES-XXT and GRAPES-SWB. The runoff simulations are greatly improved by the use of XXT in place of SWB, particularly with respect to the distribution and amount of runoff. The average runoff depth is nearly doubled in the rainbelt area, and unreasonable runoff distributions simulated by GRAPES-SWB are made more realistic by the introduction of XXT. Differences in surface soil moisture between GRAPES-XXT and GRAPES-SWB show that the XXT model changes infiltration and increases surface runoff. We also evaluate river flood discharge in the Yishu River basin. The peak values of flood discharge calculated from the output of GRAPES-XXT agree more closely with observations than those calculated from the output of GRAPES-SWB. [ABSTRACT FROM AUTHOR]

Having provided an overview of the ideas of developing user-oriented interactive forecast system (UIFS) emerging in recent years, the authors proposed an idealized framework of the new-generation meteorological system, which includes the initial user-end module for configuring the forecast target, the physical predictive and downscaling components, and an incessant assessing module in association with decision-making at the user-end. A case study was carried out with a focus on applying the TIGGE (THORPEX Interactive Grand Global Ensemble; THORPEX stands for The Observing System Research and Predictability Experiment) precipitation forecasts for the hydrological users in Linyi, a region richest in rivers and reservoirs in eastern China. The preliminary results exhibited great potential of improvement in applications of weather forecasts by combining the user-end information. Although the TIGGE results provided by existing national/ international operating models were independent from the user-end, the case study enlightened ways of establishing an iteratively self-improving UIFS involving user-orientation throughout the forecast process. [ABSTRACT FROM AUTHOR]

A coupled atmospheric-hydrologic-hydraulic ensemble flood forecasting model, driven by The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data, has been developed for flood forecasting over the Huaihe River. The incorporation of numerical weather prediction (NWP) information into flood forecasting systems may increase forecast lead time from a few hours to a few days. A single NWP model forecast from a single forecast center, however, is insufficient as it involves considerable non-predictable uncertainties and leads to a high number of false alarms. The availability of global ensemble NWP systems through TIGGE offers a new opportunity for flood forecast. The Xinanjiang model used for hydrological rainfall-runoff modeling and the one-dimensional unsteady flow model applied to channel flood routing are coupled with ensemble weather predictions based on the TIGGE data from the Canadian Meteorological Centre (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF), the UK Met Office (UKMO), and the US National Centers for Environmental Prediction (NCEP). The developed ensemble flood forecasting model is applied to flood forecasting of the 2007 flood season as a test case. The test case is chosen over the upper reaches of the Huaihe River above Lutaizi station with flood diversion and retarding areas. The input flood discharge hydrograph from the main channel to the flood diversion area is estimated with the fixed split ratio of the main channel discharge. The flood flow inside the flood retarding area is calculated as a reservoir with the water balance method. The Muskingum method is used for flood routing in the flood diversion area. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE ensemble forecasts. The results demonstrate satisfactory flood forecasting with clear signals of probability of floods up to a few days in advance, and show that TIGGE ensemble forecast data are a promising tool for forecasting of flood inundation, comparable with that driven by raingauge observations. [ABSTRACT FROM AUTHOR]

Based on the precipitation and temperature data obtained from THORPEX (The Observing System Research and Predictability Experiment) Interactive Grand Global Ensemble (TIGGE)-China Meteorological Administration (CMA) archiving center and the raingauge data, the three-layer variable infiltration capacity (VIC-3L) land surface model was employed to carry out probabilistic hydrological forecast experiments over the upper Huaihe River catchment from 20 July to 3 August 2008. The results show that the performance of the ensemble probabilistic prediction from each ensemble prediction system (EPS) is better than that of the deterministic prediction. Especially, the 72-h prediction has been improved obviously. The ensemble spread goes widely with increasing lead time and more observed discharge is bracketed in the 5th-99th quantile. The accuracy of river discharge prediction driven by the European Centre (EC)-EPS is higher than that driven by the CMA-EPS and the US National Centers for Environmental Prediction (NCEP)-EPS, and the grand-ensemble prediction is the best for hydrological prediction using the VIC model. With regard to Wangjiaba station, all predictions made with a single EPS are close to the observation between the 25th and 75th quantile. The onset of the flood ascending and the river discharge thresholds are predicted well, and so is the second rising limb. Nevertheless, the flood recession is not well predicted. [ABSTRACT FROM AUTHOR]

The probability distribution of precipitation in the Huaihe basin (HB) is analyzed with the shape and scale parameters of a Gamma distribution. The summer daily precipitation records of 158 meteorological raingauges are applied over the HB during the period of 1980-2007, and the precipitation samples are classified into unconditional rainy days and conditional rainy days which have a dry or wet preceding day over the years. The Kolmogorov-Smirnov (K-S) test and the comparison between the Gamma distribution probability density function and the sample frequency of daily precipitation records of five representative stations are conducted and analyzed. The results show that the HB is a 'scale-dominated' region characterized with large scale parameters of the Gamma distribution, where rainfall is likely to exhibit large variability leading to extreme wet or dry conditions. Further analysis shows that the confluence area of Sha River and Ying River within the stream between Wangjiaba dam and Bengbu station, the eastern branch of the Huaihe River (HR) between Bengbu station and the Hongze Lake, and the downstream area below the Hongze Lake, are all the areas with a high probability of large precipitation under the condition that the rainy day has a dry preceding day. The eastern part of the Yishu River watershed and the region near Wangjiaba dam are the center of a high probability of large precipitation under the condition that the rainy day has a wet preceding day. Moreover, the day following a dry preceding day has a greater probability of small rainfall. The probability distribution of summer daily precipitation of the HB is significantly skewed. The probability distribution could be more applicable if the rainy days are preceded by a dry or wet day. [ABSTRACT FROM AUTHOR]

We isolated a clone, named Si69, from a foxtail millet immature seed cDNA library. The protein encoded by Si69 contains a conserved Wali7 (wheat aluminum induced protein 7) domain and shares high-level homology with aluminum-induced proteins from other species including rice and Arabidopsis. The Si69 gene presents as a single locus In foxtail millet genome and is globally expressed in all tissues examined. Its expression is up-regulated by aluminum. The sequence feature and expression pattern suggest that the Si69 gene is involved in aluminum tolerance or detoxification. To confirm its biological functions, Si69 controlled by the CaMV35S promoter was introduced into Arabidopsis. Transgenic plants did not show any visible morphological changes compared to wild-type plants under normal growth conditions. However, when treated with 20 or 50 μmol/L Aluminum (Al), the root apices of wild-type plants were heavily stained by hematoxylin, whereas those of Si69 transgenic plants were not stained when treated with 20 μmol/L Al and slightly stained when treated with 50 μmoI/L Al. Scanning electron microscopy (SEM) results further demonstrated that the damage of the root apices was severer in wild-type plants than in transgenic plants. Inhibition of root growth and accumulation of malondialdehyde (MDA), an indicator of lipid peroxidation, were lower in transgenic plants than in wild-type plants. The results show that overexpression of Si69 may increase Al tolerance in transgenic plants, indicating that a series of Wali7-containing genes may play similar roles in Al tolerance/detoxification. [ABSTRACT FROM AUTHOR]

Similar to the SNP (single nucleotide polymorphism) data, there is non-random association of the DNA methylation level (we call it methylation disequilibrium, MD) between neighboring methylation loci. For the case-control study of complex diseases, it is important to identify the association between methylation levels combination types (we call it methylecomtype) and diseases/phenotypes. We extended the classical framework of SNP haplotype-based association study in population genetics to DNA methylation level data, and developed a software EWAS to identify the disease-related methylecomtypes. EWAS can provide the following basic functions: (1) calculating the DNA methylation disequilibrium coefficient between two CpG loci; (2) identifying the MD blocks across the whole genome; (3) carrying out case-control association study of methylecomtypes and identifying the disease-related methylecomtypes. For a DNA methylation level data set including 689 samples (354 cases and 335 controls) and 473864 CpG loci, it takes only about 25 min to complete the full scan. EWAS v1.0 can rapidly identify the association between combinations of methylation levels (methylecomtypes) and diseases. EWAS v1.0 is freely available at: http://www.ewas.org.cn or http://www.bioapp.org/ewas. [ABSTRACT FROM AUTHOR]