Diabetes is usually associated with inflammation. Inflammation contributes to the development of diabetes. Traditional Chinese medicines (TCM) play an important role in lowering blood glucose and ...controlling inflammation. Many studies show that TCM with hypoglycaemic effects, for example Radix Astragali, Radix Rehmanniae, Radix Trichosanthis, Panax Ginseng, Fructus Schisandrae, Radix Ophiopogonis, Rhizoma Anemarrhenae, Radix Puerariae, Fructus Lycii, Poria, Rhizoma Coptidis, Rhizoma Dioscoreae, Rhizoma Polygonati, Radix Salviae Miltiorrhizae, Radix Glycyrrhizae, Semen Trigonellae, Momordica charantia, Allium sativum, Opuntia stricta, Aloe vera, Cortex Cinnamomi, Rhizoma Curcumae Longae, and so on, have nearly independent anti-inflammatory action. Antihyperglycaemic compounds, for example berberine, puerarin, quercetin, ferulic acid, astragaloside IV, curcumin, epigallocatechin gallate, resveratrol, tetrandrine, glycyrrhizin, emodin and baicalin, used in TCM also have anti-inflammatory effects. These studies suggest that TCM might exert hypoglycaemic effects that are partly mediated by the anti-inflammatory mechanisms. However, small amounts of TCM with potent anti-inflammatory action does not have any hypoglycaemic effect. This indirectly indicates that diabetes may be a low-grade inflammatory disease and potent regulation of inflammatory mediators may not be required. Studies of TCM add new evidences, which indicate that diabetes may be an inflammatory disease and slight or moderate inhibition of inflammation might be useful to prevent the development of diabetes. Through this review, we aim to develop more perspectives to indicate that diabetes may be an inflammatory disease and diverse TCM may share a common antidiabetic property: anti-inflammatory action. Further studies should focus on and validate inflammation-regulating targets of TCM that may be involved in inhibiting the development of diabetes.
Clustering is a fundamental data analysis method. It is widely used for pattern recognition, feature extraction, vector quantization (VQ), image segmentation, function approximation, and data mining. ...As an unsupervised classification technique, clustering identifies some inherent structures present in a set of objects based on a similarity measure. Clustering methods can be based on statistical model identification (
McLachlan & Basford, 1988) or competitive learning. In this paper, we give a comprehensive overview of competitive learning based clustering methods. Importance is attached to a number of competitive learning based clustering neural networks such as the self-organizing map (SOM), the learning vector quantization (LVQ), the neural gas, and the ART model, and clustering algorithms such as the
C
-means, mountain/subtractive clustering, and fuzzy
C
-means (FCM) algorithms. Associated topics such as the under-utilization problem, fuzzy clustering, robust clustering, clustering based on non-Euclidean distance measures, supervised clustering, hierarchical clustering as well as cluster validity are also described. Two examples are given to demonstrate the use of the clustering methods.
This comprehensive textbook reviews the most popular neural-network methods and associated techniques. Each chapter describes important research results of the respective neural-network methods. ...Useful for those working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence.
Summary
Classical swine fever (CSF) is a devastating infectious disease of pigs caused by classical swine fever virus (CSFV). In China, CSF has been under control owing to extensive vaccination with ...the lapinized attenuated vaccine (C‐strain) since 1950s, despite sporadic or endemic in many regions. However, recently, CSF outbreaks occurred in a large number of swine herds in China. Here, we isolated 15 CSFV strains from diverse C‐strain‐vaccinated pig farms in China and characterized the genetic variations and antigenicity of the new isolates. The new strains showed unique variations in the E2 protein and were clustered to the subgenotype 2.1d of CSFV recently emerging in China in the phylogenetic tree. Cross‐neutralization test showed that the neutralizing titres of porcine anti‐C‐strain sera against the new isolates were substantially lower than those against both the highly virulent Shimen strain and the subgenotype 2.1b strains that were isolated in China in 2006 and 2009, respectively. In addition, experimental animal infection showed that the HLJZZ2014 strain‐infected pigs displayed lower mortality and less severe clinical signs and pathological changes compared with the Shimen strain‐infected pigs. The HLJZZ2014 strain was defined to be moderately virulent based on a previously established assessment system for CSFV virulence evaluation, and the virus shedding and the viral load in various tissues of the CSFV HLJZZ2014 strain‐infected pigs were significantly lower than those of the Shimen strain‐infected pigs. Taken together, the subgenotype 2.1d isolate of CSFV is a moderately virulent strain with molecular variations and antigenic alterations.
Background and Purpose
Functional dyspepsia (FD) is a gastrointestinal disorder of unknown etiology. Although micro‐inflammation appears to be important in the pathogenesis, studies evaluating immune ...activation in FD have been inconsistent. A systematic review of literature and meta‐analysis was performed to compare immunologic cell counts and cytokine levels in the mucosa and peripheral blood of individuals with FD and healthy controls. PubMed, Embase, and the Cochrane library were searched. Data on immunologic cell counts and cytokines levels among individuals with FD and control groups were extracted and compared by calculating standard mean differences (SMD). Thirty‐seven studies met the inclusion criteria. Mast cell (SMD = 0.94, 95%CI 0.26‐1.62, P = .007) and eosinophil counts (SMD = 0.36, 95%CI 0.06‐0.68, P = .03) in the stomach were increased, among individuals with FD compared to controls. Similarly, mast cell (SMD = 0.66, 95%CI 0.20‐1.13, P = 0.005) and eosinophil (SMD = 0.95, 95%CI 0.66‐1.24; P < .001) counts in the duodenum were also increased in those with FD compared to controls. In a subgroup analysis, elevated eosinophil counts in the duodenum were observed in both post‐prandial distress syndrome (SMD = 0.97, 95%CI 0.46‐1.47, P = .0002) and epigastric pain syndrome subtypes (SMD = 1.16, 95%CI 0.48‐1.83, P = .0008). No differences in mucosal intraepithelial lymphocyte, enterochromaffin cell, and neutrophil counts, as well as, peripheral interlukin‐6 (IL‐6) and IL‐10 levels were observed among individuals with FD and controls. Micro‐inflammation in the form of local immune cell infiltration, particularly eosinophils and mast cells, characterizes the pathogenesis of FD.
A systematic review and meta‐analysis of 37 studies evaluating peripheral and mucosal immune cytokines and cells were performed. Gastroduodenal eosinophils and mast cells were increased in individuals with FD compared to healthy controls.
Dysbiotic oral microbiota has been associated with multiple sclerosis. However, the role and mechanism of oral microbiota in the development of multiple sclerosis are still elusive. Here, we ...demonstrated that ligature-induced periodontitis (LIP) aggravated experimental autoimmune encephalomyelitis (EAE) in mice, and this was likely dependent on the expansion of T helper 17 (Th17) cells. LIP increased the splenic richness of Enterobacter sp., which was able to induce the expansion of splenic Th17 cells and aggravate EAE in mice. LIP also led to enrichment of Erysipelotrichaceae sp. in the gut and increased Th17 cells in the large intestinal lamina propria of EAE mice. Fecal microbiota transplantation from EAE mice with LIP also promoted EAE symptoms. In conclusion, periodontitis exacerbates EAE, likely through ectopic colonization of oral pathobionts and expansion of Th17 cells.
The effect of heating rate on the mechanism of reverse transformation from martensite to austenite during continuous heating process was studied in a cold-rolled 304 stainless steel, and the ...corresponding mechanical properties were analyzed. It indicated that the reverse transformation occurred diffusionally at slow heating rate range (< 10 °C/s). However, rapid heating rates (> 40 °C/s) resulted the reverse transformation to occur via martensitic shear-type. At medium heating rates (10–40 °C/s), the reversion mechanism gradually changed from diffusional to shear-type. The diffusional reversed austenite was characterized by equiaxed, defect-free, nano/ultrafine grains with grain size of 100–500 nm, while the martensitic shear-type reversed austenite exhibited lath-type/banded grains with high defects density. At 100 °C/s, an excellent combination of high-strength and high-ductility with significant work hardening ability was obtained. Moreover, the product of strength and ductility was enhanced over three times from 11.14 GPa (at 2 °C/s) to 35.78 GPa (at 100 °C/s). The strain gradient due to the heterostructure, the glide of preexisting mobile dislocations and the controlled release from TRIP effect contributed to the improved mechanical properties. The study also indicated that reversion mechanism had no effect on austenite texture.
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Sinigrin is a class of glucosinolates found naturally in plants of the Brassicaceae family. Lately, studies have shown that sinigrin possesses anticancer, antibacterial and ...anti-inflammatory activities. Since its efficacy has not been explored on wound healing, we examined the effect of sinigrin on HaCaT cells. We also aimed at formulating sinigrin into phytosome to form a sinigrin–phytosome complex and study the wound healing and cytotoxic activities on A-375 and HaCaT cells. Sinigrin was efficiently formulated into the phytosome with an average particle size of 153±39nm, zeta potential of 10.09±0.98mV and complex efficiency of 69.5±5%. The formation of the sinigrin–phytosome complex was confirmed by DSC and FTIR analysis. The sinigrin–phytosome complex significantly exhibited wound healing effects when compared to sinigrin alone. After 42h, the phytosome complex completely healed the wound, whereas sinigrin alone showed only 71% wound closure. The sinigrin–phytosome complex displayed minimal toxicity towards HaCaT cells and at higher concentrations, it showed potent activity towards A-375. The results indicated that sinigrin–phytosome complex augmented the therapeutic potential of sinigrin towards the wound healing activity and this approach should be explored further for cancerous wound treatment.
Due to the limitation in the prediction of the foundation pit settlement, this paper proposed a new methodology which takes advantage of the grey Verhulst model and a genetic algorithm. In the ...previous study, excavation times are often the only factor to predict the settlement, which is mainly because the correspondence between real-time excavation depth and the excavation time is hard to determine. To solve this issue, the supporting times are precisely recorded and the excavation depth rate can be obtained through the excavation time length and excavation depth between two adjacent supports. After the correspondence between real-time excavation depth and the excavation time is obtained, the internal friction angle, cohesion, bulk density, Poisson’s ratio, void ratio, water level changes, permeability coefficient, number of supports, and excavation depth, which can influence the settlement, are taken to be considered in this study. For the application of the methodology, the settlement monitoring point of D4, which is near the bridge pier of the highway, is studied in this paper. The predicted values of the BP neural network, GA-BP neural network, BP neural network optimized by the grey Verhulst model, and GA-BP neural network optimized by the grey Verhulst model are detailed compared with the measured values. And the evaluation indexes of RMSE, MAE, MSE, MAPE, and R2 are calculated for these models. The results show that the grey Verhulst model can greatly improve the consistency between predicted values and measured values, while the accuracy and resolution is still low. The genetic algorithm (GA) can greatly improve the accuracy of the predicted values, while the GA-BP neural network shows low reflection to the fluctuation of measured values. The GA-BP neural network optimized by the grey Verhulst model, which has taken the advantages of GA and the grey Verhulst model, has extremely high accuracy and well consistency with the measured values.
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