Assessment Performance of 3-Parameter Probability ‎Distributions for At-site Annual Streamflow in the ‎Blue Nile Basin ‎

Many investigators have been applied various probability distributions for flood discharges at-site or region, however, there is no scientific judge about the best distribution to accurate the flood discharge estimations. In practice, different probability distributions are taken into account, and the best distribution is then applied to create the percentile quantiles. This paper introduces the assessment of three probability distributions that have three parameters; Generalized Extreme Value (GEV), Generalized Pareto (GPA) and Generalized Logistic (GLO) using L-moments (LM) method to estimate their parameters using annual peak discharge series of three hydrological stations on Blue River Basin and Atbara River in Sudan. Cunnane plotting position formula is considered to test the applicable probability distribution that gives good estimations in tails. The Q-Q relation with coefficient of determination (R2) is adopted to present the consistency process of the estimates and their corresponding of observed annual peak data. L-moment ratio diagram (LMRD) as suggested by Hosking and Walish (1993) is also performed to measure the discordance of probability distributions. Further, the evaluation performance of probability distributions can be measured by using three comparison criteria; root mean square error (RMSE), mean absolute deviation index (MADI) and relative root mean square error (RRMSE). The results indicated that GLO distribution generally shows the best fit followed by GEV distribution; however the GEV distribution gave more realistic in upper tail than others. It may be recommended as the appropriate probability distribution for annual peak discharge at-site in Blue Nile

Chemical characterisation and the anti-inflammatory, anti-angiogenic and antibacterial properties of date fruit (Phoenix dactylifera L.)

Ethnopharmacological relevance: Date fruit, Phoenix dactylifera L. has traditionally been used as a medicine in many cultures for the treatment of a range of ailments such as stomach and intestinal disorders, fever, oedema, bronchitis and wound healing. Aim of the review: The present review aims to summarise the traditional use and application of Phoenix dactylifera date fruit in different ethnomedical systems, additionally the botany and phytochemistry are identified. Critical evaluation of in vitro and in vitro studies examining date fruit in relation to anti-inflammatory, anti-angiogenic and antimicrobial activities are outlined. Key Findings: The ethnomedical use of Phoenix dactylifera in the treatment of inflammatory disease has been previously identified and reported. Furthermore, date fruit and date fruit co-products such as date syrup are rich sources of polyphenols, anthocyanins, sterols and carotenoids. In vitro studies have demonstrated that date fruit exhibits antibacterial, anti-inflammatory and anti-angiogenic activity. The recent interest in the identification of the numerous health benefits of dates using in vitro and in vivo studies have confirmed that date fruit and date syrup have beneficial health effects that can be attributed to the presence of natural bioactive compounds. Conclusions: Date fruit and date syrup have therapeutic properties, which have the potential to be beneficial to health. However, more investigations are needed to quantify and validate these effects

Infusion of donor feces affects the gut–brain axis in humans with metabolic syndrome

Objective Increasing evidence indicates that intestinal microbiota play a role in diverse metabolic processes via intestinal butyrate production. Human bariatric surgery data suggest that the gut-brain axis is also involved in this process, but the underlying mechanisms remain unknown. Methods We compared the effect of fecal microbiota transfer (FMT) from post-Roux-en-Y gastric bypass (RYGB) donors vs oral butyrate supplementation on (123I-FP-CIT-determined) brain dopamine transporter (DAT) and serotonin transporter (SERT) binding as well as stable isotope-determined insulin sensitivity at baseline and after 4 weeks in 24 male and female treatment-naïve metabolic syndrome subjects. Plasma metabolites and fecal microbiota were also determined at these time points. Results We observed an increase in brain DAT after donor FMT compared to oral butyrate that reduced this binding. However, no effect on body weight and insulin sensitivity was demonstrated after post-RYGB donor feces transfer in humans with metabolic syndrome. Increases in fecal levels of Bacteroides uniformis were significantly associated with an increase in DAT, whereas increases in Prevotella spp. showed an inverse association. Changes in the plasma metabolites glycine, betaine, methionine, and lysine (associated with the S-adenosylmethionine cycle) were also associated with altered striatal DAT expression. Conclusions Although more and larger studies are needed, our data suggest a potential gut microbiota-driven modulation of brain dopamine and serotonin transporters in human subjects with obese metabolic syndrome. These data also suggest the presence of a gut-brain axis in humans that can be modulated

Modeling microbiota-associated human diseases: from minimal models to complex systems

Alterations in the intestinal microbiota are associated with various human diseases of the digestive system, including obesity and its associated metabolic diseases, inflammatory bowel diseases (IBD), and colorectal cancer (CRC). All three diseases are characterized by modifications of the richness, composition, and metabolic functions of the human intestinal microbiota. Despite being multi-factorial diseases, studies in germ-free animal models have unarguably identified the intestinal microbiota as a causal driver of disease pathogenesis. However, for an increased mechanistic understanding of microbial signatures in human diseases, models require detailed refinement to closely mimic the human microbiota and reflect the complexity and range of dysbiosis observed in patients. The transplantation of human fecal microbiota into animal models represents a powerful tool for studying the causal and functional role of the dysbiotic human microbiome in a pathological context. While human microbiota-associated models were initially employed to study obesity, an increasing number of studies have applied this approach in the context of IBD and CRC over the past decade. In this review, we discuss different approaches that allow the functional validation of the bacterial contribution to human diseases, with emphasis on obesity and its associated metabolic diseases, IBD, and CRC. We discuss the utility of simple models, such as in vitro fermentation systems of the human microbiota and ex vivo intestinal organoids, as well as more complex whole organism models. Our focus here lies on human microbiota-associated mouse models in the context of all three diseases, as well as highlighting the advantages and limitations of this approach

Frequency and risk factors of abnormal nerve conduction studies in accidentally diagnosed diabetes

Abstract Background Diabetic peripheral neuropathy (DPN) is one of the major diabetic complication and affects quality of life (QoL).This study aims at assessing the frequency of DPN among accidentally diagnosed diabetic patients, identifying risk factors linked to DPN in those patients, and determine the potential effect on QoL. Results According to nerve conduction study (NCS), 32 patients (44.4%) had polyneuropathy. Polyneuropathy is significantly associated with older age, higher hip and waist measurements, higher weight, and body mass index (BMI). About 53% of patients with polyneuropathy were current smokers versus 25% of non-smokers. Longer duration since the first diagnosis, higher fasting blood sugar (FBG), 2-h post-prandial (2-hPP) glucose, and HbA1c are also associated with peripheral neuropathy (PN) (p < 0.001). Being on insulin was associated with PN (p = 0.002). Increasing BMI, current smoking, and increased HbA1c significantly increase the risk of PN by 1.314, 19.963, and 3.302-folds, respectively. An unhealthy diet is also associated with PN.Hyperlipidemia was also associated with PN (p = 0.028). A significant positive association was found between DQoL scores and symptom scores. Conclusion A significant proportion of type 2 diabetic patients had DPN at the time of diagnosis, which adversely affects QoL. At the time of diagnosis, it is highly suggested that proper screening. procedures be used for DPN. Obesity, smoking, and elevated HbA1c significantly increase the risk of DPN

Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis.

BackgroundPersonalized medicine requires finding relationships between variables that influence a patient's phenotype and predicting an outcome. Sparse generalized canonical correlation analysis identifies relationships between different groups of variables. This method requires establishing a model of the expected interaction between those variables. Describing these interactions is challenging when the relationship is unknown or when there is no pre-established hypothesis. Thus, our aim was to develop a method to find the relationships between microbiome and host transcriptome data and the relevant clinical variables in a complex disease, such as Crohn's disease.ResultsWe present here a method to identify interactions based on canonical correlation analysis. We show that the model is the most important factor to identify relationships between blocks using a dataset of Crohn's disease patients with longitudinal sampling. First the analysis was tested in two previously published datasets: a glioma and a Crohn's disease and ulcerative colitis dataset where we describe how to select the optimum parameters. Using such parameters, we analyzed our Crohn's disease data set. We selected the model with the highest inner average variance explained to identify relationships between transcriptome, gut microbiome and clinically relevant variables. Adding the clinically relevant variables improved the average variance explained by the model compared to multiple co-inertia analysis.ConclusionsThe methodology described herein provides a general framework for identifying interactions between sets of omic data and clinically relevant variables. Following this method, we found genes and microorganisms that were related to each other independently of the model, while others were specific to the model used. Thus, model selection proved crucial to finding the existing relationships in multi-omics datasets

Is Autologous Fecal Microbiota Transfer after Exclusive Enteral Nutrition in Pediatric Crohn’s Disease Patients Rational and Feasible? Data from a Feasibility Test

Background: Exclusive enteral nutrition (EEN) is a highly effective therapy for remission induction in pediatric Crohn’s disease (CD), but relapse rates after return to a regular diet are high. Autologous fecal microbiota transfer (FMT) using stool collected during EEN-induced clinical remission might represent a novel approach to maintaining the benefits of EEN. Methods: Pediatric CD patients provided fecal material at home, which was shipped at 4 °C to an FMT laboratory for FMT capsule generation and extensive pathogen safety screening. The microbial community composition of samples taken before and after shipment and after encapsulation was characterized using 16S rRNA amplicon sequencing. Results: Seven pediatric patients provided fecal material for nine test runs after at least three weeks of nutritional therapy. FMT capsules were successfully generated in 6/8 deliveries, but stool weight and consistency varied widely. Transport and processing of fecal material into FMT capsules did not fundamentally change microbial composition, but microbial richness was <30 genera in 3/9 samples. Stool safety screening was positive for potential pathogens or drug resistance genes in 8/9 test runs. Conclusions: A high pathogen burden, low-diversity microbiota, and practical deficiencies of EEN-conditioned fecal material might render autologous capsule-FMT an unsuitable approach as maintenance therapy for pediatric CD patients

Integrated microbiota and metabolite profiles link Crohn’s disease to sulfur metabolism

International audienceGut microbial and metabolite alterations have been linked to the pathogenesis of inflammatory bowel diseases. Here we perform a multi-omics microbiome and metabolite analysis of a longitudinal cohort of Crohn's disease patients undergoing autologous hematopoietic stem cell transplantation, and investigational therapy that induces drug free remission in a subset of patients. Via comparison of patients who responded and maintained remission, responded but experienced disease relapse and patients who did not respond to therapy, we identify shared functional signatures that correlate with disease activity despite the variability of gut microbiota profiles at taxonomic level. These signatures reflect the disease state when transferred to gnotobiotic mice. Taken together, the integration of microbiome and metabolite profiles from human cohort and mice improves the predictive modelling of disease outcome, and allows the identification of a network of bacteria-metabolite interactions involving sulfur metabolism as a key mechanism linked to disease activity in Crohn's disease