Engineering the Hydrophobic Microenvironment in Polystyrene-Supported Artificial Catalytic Triad Nanocatalysts: An Effective Strategy for Improving Catalytic Performance.

Hydrophobic environments have been identified as one of the main parameters affecting the catalytic performance of artificial catalytic triads but are often ignored as an approach to engineering these catalysts. Here, we have developed a simple yet powerful strategy to engineer the hydrophobic environment in polystyrene-supported artificial catalytic triad (PSACT) nanocatalysts. Hydrophobic copolymers containing either oligo(ethylene glycol) side chains or hydrocarbon side chains were synthesized and used for the preparation of nanocatalysts through nanoprecipitation in aqueous media. By using the hydrolysis of 4-nitrophenyl acetate (4NA) as a model reaction, we studied the influence of chemical structures and effective constituent ratios of hydrophobic copolymers on the catalytic performance of PSACT nanocatalysts. Additionally, PSACT nanocatalysts could catalyze the hydrolysis of a few carboxylic esters, even polymers, and be reused for five consecutive runs without significant loss of catalytic activity. This strategy may open an avenue for engineering other artificial enzymes, and these PSACT nanocatalysts have potential applications for the hydrolysis of carboxylic esters.

Natural polyphenol self-assembled pH-responsive nanoparticles loaded into reversible hydrogel to inhibit oral bacterial activity.

Periodontitis is one of the most prevalent chronic inflammatory diseases and Polyphenols isolated from Turkish gall play a major role in the treatment of inflammatory diseases for their antibacterial, anti-inflammatory and antioxidant activities. In this work, Turkish Galls effective constituent (TGEC, T) was prepared into nanoparticles (T-NPs) by principle of oxidative self-polymerization. The pH-sensitive T-NPs was encapsulated into thermosensitive type in-situ hydrogel, and 42.29 ± 1.12% of effective constituent from T-NPs were continuously released within 96 h under the periodontitis environment. In addition, the weakly alkaline oral micro-environment of patients with periodontitis is more conducive to the sustained release of effective constituent, which is 10.83% more than that of healthy periodontal environment. The bacteriostatic test showed that T-NPs had stronger antibacterial activity on oral pathogens than that of TGEC. Compared with TGEC, the minimum inhibitory concentration (MIC) of T-NPs against P. gingivalis and A. viscosus was reduced by 50% and 25%, respectively. Interestingly, T-NPs induced bacteria lysis by promoting the excessive production of ROS without periodontal tissue damage caused by excessive oxidation reaction. In conclusion, a simple method of preparing microspheres with natural polyphenols was developed, which provides beneficial reference for one-step prepared drug carriers from effective components of natural product, likewise the method offers a green and effective solution to synthesis a new adjuvant therapy drugs for treatment of gingivitis associated with periodontal pockets.

Proteomics analyses of Xiaopi granules in N-methyl-N'-nitro-N-nitrosoguanidine-induced gastric epithelial dysplasia rat model using LC-MS.

Xiaopi granules have been shown to ameliorate gastric epithelial dysplasia in patients. However, the therapeutic mechanism is unclear. Herein, the proteomics method was applied to identify the differentially expressed proteins and related pathways. Sixty male Sprague-Dawley rats were randomly divided into four groups: control (C group, n = 10), model (M group), Xiaopi granules (X group), and vitacoenzyme (V group). The rat gastric epithelial dysplasia model was established by intragastrically administering N-methyl-N'-nitro-N-nitrosoguanidine and ranitidine and by orally administering 0.05% ammonia solution. After 12 weeks, the stomach tissue was analyzed by hematoxylin and eosin staining and proteomics analyses. Western-blot analysis was applied to further validate the proteomics results. Compared to the M group, levels of 326 and 350 proteins were altered significantly in the X and V groups (1.5-fold, p < 0.05), which were significantly enriched in digestion, metabolism, coagulation, and cell apoptosis. CELA2A, GHRL, NDUFB9, and PGC were significantly upregulated (p < 0.0001), whereas CLCA1, PLG, and DAC2 were downregulated (p < 0.001 or 0.0001) in the M group vs. the C group. The change in these proteins could be reversed after the treatment of Xiaopi granules or vitacoenzyme tablets. Xiaopi granules ameliorated gastric epithelial dysplasia by intervening in digestion, metabolism, blood coagulation, cell apoptosis, and other related pathways.

Polyimide-supported Cu/2,2,6,6-tetramethyl-1-piperidine-N-oxyl catalytic systems: Aromatic donor-acceptor interaction-directed cooperative catalysis.

Non-covalent immobilization of multifunctional catalysts onto polymer supports is a promising technique to build highly efficient heterogeneous cooperative catalysts. Here, we present a strategy to build polyimide-supported Cu/2,2,6,6-tetramethyl-1-piperidine-N-oxyl (TEMPO) catalytic systems based on hydrophobic interactions and aromatic donor-acceptor interactions. Pyrene-containing catalytic species and naphthalene diimide (NDI)-based polyimides were chosen for the preparation of nanoparticle catalysts using the nanoprecipitation technique. The cooperative behaviors of catalytic components were evaluated by the catalytic activities of aerobic oxidation of benzyl alcohol (BnOH) in water. We studied the influence of effective constituent ratio of polymers, chain length of monomer, and the incorporation of a second monomer on catalytic activities. The aggregate structures were investigated by X-ray powder diffraction (XRD) patterns and small angle X-ray scattering (SAXS), and speculated to be random distributions of aromatic stacking clusters within nanoparticle catalysts. This strategy will find applications in the construction of other multifunctional heterogeneous catalysts.

Development and Validation of a Prognostic Model for One-year Survival of Cirrhosis Patients with First-ever Spontaneous Bacterial Peritonitis.

BACKGROUND AND AIMS: Spontaneous bacterial peritonitis (SBP) is one of the leading causes of death in patients with liver cirrhosis. We aimed to establish a prognostic model to evaluate the 1-year survival of cirrhosis patients after the first episode of SBP. METHODS: A prognostic model was developed based on a retrospective derivation cohort of 309 cirrhosis patients with first-ever SBP and was validated in a separate validation cohort of 141 patients. We used Uno's concordance, calibration curve, and decision curve (DCA) analysis to evaluate the discrimination, calibration, and clinical net benefit of the model. RESULTS: A total of 59 (19.1%) patients in the derivation cohort and 42 (29.8%) patients in the validation cohort died over the course of 1 year. A prognostic model in nomogram form was developed with predictors including age [hazard ratio (HR): 1.25; 95% confidence interval (CI): 0.92-1.71], total serum bilirubin (HR: 1.66; 95% CI: 1.28-2.14), serum sodium (HR: 0.94; 95% CI: 0.90-0.98), history of hypertension (HR: 2.52; 95% CI: 1.44-4.41) and hepatic encephalopathy (HR: 2.06; 95% CI: 1.13-3.73). The nomogram had a higher concordance (0.79) compared with the model end-stage liver disease (0.67) or Child-Turcotte-Pugh (0.71) score. The nomogram also showed acceptable calibration (calibration slope, 1.12; Bier score, 0.15±0.21) and optimal clinical net benefit in the validation cohort. CONCLUSIONS: This prediction model developed based on characteristics of first-ever SBP patients may benefit the prediction of patients' 1-year survival.

Rapid diagnosis of heavy metal pollution in lake sediments based on environmental magnetism and machine learning.

Environmental magnetism in combination with machine learning can be used to monitor heavy metal pollution in sediments. Magnetic parameters and heavy metal concentrations of sediments from Chaohu Lake (China) were analyzed. The magnetic measurements, high- and low-temperature curves, and hysteresis loops showed the primary magnetic minerals were ferrimagnetic minerals in sediments. For most metals, their concentrations were highest during the wet season and lowest during the medium-water period. Cd, Hg, and Zn were moderately enriched and Cd and Hg posed a considerable ecological risk. A redundancy analysis indicated a relationship between physicochemical indexes and magnetic parameters and heavy metal concentrations. An artificial neural network (ANN) and support vector machine (SVM) were used to construct six models to predict the heavy metal concentrations and ecological risk index. The inclusion of both the physicochemical indexes and magnetic parameters as input factors in the models were significantly ameliorated the simulation accuracy for the majority of heavy metals. The training and test R, for Be, Fe, Pb, Zn, As, Cu, and Cr were > 0.8. The SVM showed better performance and hence it has potential for the efficient and economical long-term tracking and monitoring of heavy metal pollution in lake sediments.

Magnetic properties and its application in the prediction of potentially toxic elements in aquatic products by machine learning.

Magnetic measurement was provided to substitute for time-consuming conventional methods for determination of potentially toxic elements. Both the concentrations of 12 elements and 9 magnetic parameters were determined in 700 muscle tissue samples from the snail Bellamya aeruginosa, shrimp species Exopalaemon modestus and Macrobrachium nipponense, and fish species Hemisalanx prognathous Regan, Coilia ectenes taihuensis, and Culer alburnus Basilewsky collected from Chaohu Lake during different hydrological periods. Spherical and irregular iron oxide particles were observed in the muscle tissues of the studied aquatic products. A field survey of the exposure parameters in humans, such as per capita intake dose of local aquatic products, found no evidence that consumption of the tested species poses a potential health risk. Redundancy analysis revealed different degrees of correlation between the magnetic parameters and concentrations of elements in aquatic products. Back-propagation artificial neural network (BP-ANN) and support vector machine (SVM) models were applied to predict elemental concentrations in aquatic products, using magnetic parameters as input. SVM models performed well in predicting the presence of Cr and Ni, with R and index of agreement values of >0.8 in both training and validation stages as well as relatively low errors. The BP-ANN and SVM models both performed relatively poorly in predicting the presence of Cd and Zn in aquatic products, with R values between 0.333 and 0.718 for Cd and between 0.454 and 0.664 for Zn in training and validation stages. For most of the elements, a better R value was obtained with the SVM than with BP-ANN model. The R of Co, Cr, Cu, Ni, and Ti in the training and validation stages of snail in the SVM model were >0.8. This study is a first step in developing a novel approach allowing the rapid monitoring of potentially toxic elements concentrations in aquatic products.

Rapid monitoring of heavy metal pollution in lake water using nitrogen and phosphorus nutrients and physicochemical indicators by support vector machine.

A novel method of predicting heavy metal concentration in lake water by support vector machine (SVM) model was developed, combined with low-cost, easy to obtain nutrients and physicochemical indicators as input variables. 115 surface water samples were collected from 23 sites in Chaohu Lake, China, during different hydrological periods. The particulate concentrations of heavy metals in water were much higher than the dissolved concentrations. According to Nemerow pollution index (Pi), pollution degrees by Fe, V, Mn and As ranged from heavy (2 ≤ Pi < 4) to serious (Pi ≥ 4). The concentrations of most heavy metals were the highest during the medium-water period and the lowest during the dry season. Non-metric Multidimensional Scaling Analysis confirmed heavy metal concentrations had slight spatial difference but relatively large seasonal variation. Redundancy Analysis indicated the close associations of heavy metals with nutrient and physicochemical indicators. When both nutrient and physicochemical indicators were used as input variables, the simulation effects for most elements in total and particulate were relatively better than those obtained using only nutrient or only physicochemical indicators. The simulation effects for As, Ba, Fe, Ti, V and Zn were generally good, based on their training R values of 0.847, 0.828, 0.856, 0.867, 0.817 and 0.893, respectively, as well as their test R values of 0.811, 0.836, 0.843, 0.873, 0.829 and 0.826, respectively; and meanwhile, in both the training and test stages, these metals also had relatively lower errors. The spatial distribution of heavy metals in Chaohu Lake was then predicted using the fully trained SVM models.

Study on the interaction between ligustrazine and 12-tungstophosphoric acid using resonance Rayleigh scattering and resonance nonlinear scattering spectra, and its analytical applications.

In an HCl medium (pH 1.5), ligustrazine (2,3,5,6-tetramethylpyrazine, TMP) reacted with 12-tungstophosphoric acid (TP) to form a 3 : 1 ion-association complex. As a result, the intensities of resonance Rayleigh scattering (RRS), second-order scattering (SOS) and frequency doubling scattering (FDS) were greatly enhanced and new scattering spectra appeared. The maximum RRS, SOS and FDS wavelengths of the ion-association complexes were located at 379, 738 and 395 nm, respectively. The scattering intensity increments (ΔIRRS , ΔISOS and ΔIFDS ) were directly proportional to the concentration of ligustrazine within certain ranges. The detection limits (3σ) of RRS, SOS and FDS were 1.6, 3.2 and 2.8 ng/mL. Optimal conditions for the RRS method and factors influencing the method were discussed, and the structure of the ion-association complex and the reaction mechanism were investigated. Transmission electron microscopy (TEM) was used to characterize the structures of the ion-association complex. Based on the ion-association reaction and its spectral response, a rapid, simple and sensitive RRS method for the determination of TMP was developed. It was applied to the determination of TMP in tablet and urine samples with satisfactory results.

Huangqi Jianzhong Tang for Treatment of Chronic Gastritis: A Systematic Review of Randomized Clinical Trials.

To assess the clinical effects and safety of Huangqi Jianzhong Tang (HQJZ) for the treatment of chronic gastritis (CG), three English databases and four Chinese databases were searched through the inception to January 2015. In randomized controlled trials (RCTs) comparing HQJZ with placebo, no intervention and western medicine were included. A total of 9 RCTs involving 979 participants were identified. The methodological quality of the included trials was generally poor. Meta-analyses demonstrated that HQJZ plus conventional medicine was more effective in improving overall gastroscopy outcome than western medicine alone for treatment of chronic superficial gastritis with the pooling result of overall improvement [OR 3.78 (1.29,11.06), P = 0.02]. In addition, the combination of HQJZ with antibiotics has higher overall effect rate than antibiotics alone for the treatment of CG [OR 2.60 (1.49,4.54), P = 0.0007]. There were no serious adverse events reported in both the intervention and controlled groups. HQJZ has the potential of improvement of the patients' gastroscopy outcomes, Helicobacter pylori clearance rate, traditional Chinese Medicine syndromes, and overall effect rate alone or in combination use with conventional western medicine for chronic atrophic gastritis. However, due to poor methodological quality, the beneficial effect and safeties of HQJZ for CG could not be confirmed.

Electrochemical sensors using gold submicron particles modified electrodes based on calcium complexes formed with alizarin red S for determination of Ca(2+) in isolated rat heart mitochondria.

A simple glassy carbon electrode (GCE) modified with gold submicron particles (AuSPs), characterized by a mean diameter of about0.15-0.20µm has been developed. Herein, the complexation reaction of Ca(2+) with alizarin red S (ARS), in 0.1M KOH, has been followed by electrochemical methods using the modified electrode which is able to catalyze the electro-reduction of ARS. When the stoichiometry ratio of Ca(2+) and ARS is 1:2, a new reduction peak at a higher negative potential of -0.975V appeared, and the peak of ARS at -0.815V disappeared. The peak current of ARS in alkaline solution is proportional to the concentration of Ca(2+) in the range 6.0×10(-7)-1.2×10(-4)M with a limit of detection (LOD) of 5.1×10(-7)M. Furthermore, the complex site of Ca(2+) with ARS was analysized by the experimental UV-vis and infrared spectrums and those calculated electronic and vibrational spectroscopies with density functional theory (DFT). The good accordance between theoretical and experimental data confirms that chelation of calcium ion preferentially occurs at the deprotonated catechol site. Then, we implemented an electrochemical assay for the investigation of Ca(2+) in preparations of isolated rat heart mitochondria, which demonstrates the submicron particles modified electrode is a simple and rapid sensor for determining the Ca(2+) in the biological samples.

High-resolution multiband polarization epithelial tissue imaging method by sparse representation and fusion.

Multiband polarization epithelial tissue imaging is an effective tool to measure tissue's birefringence and structure for quantitative pathology analysis. To discriminate the pathology accurately, high-resolution multiband polarization images are essential. But it is difficult to acquire high-resolution polarization images because of the limitations of imaging systems. The polarization image calculation process can be regarded as image fusion with fixed rules, and multiband polarization images are intrinsically sparse. In this paper, we propose a novel high-resolution multiband polarization image calculation method by utilizing the sparse representation and image fusion method. The multiband images are first represented in the sparse domain and we further introduce total-variation-regularization terms into the sparse representation framework. Then, polarization parameter images are calculated by simultaneous fusion and reconstruction. Higher quality multiband polarization images can be obtained through additional regularization constraint in the fusion process. Extensive experiments validate that the proposed method achieves much better results than many state-of-the-art algorithms in terms of both peak signal-to-noise-ratio and visual perception.

Dynamic changes in the expression of matrix metalloproteinases and their inhibitors, TIMPs, during hepatic fibrosis induced by alcohol in rats.

AIM: To determine the dynamic changes in the expression of matrix metalloproteinases (MMPs) and the endogenous tissue inhibitors of MMPs inhibitors (TIMPs) during hepatic fibrosis induced by alcohol. METHODS: Male Sprague-Dawley rats were randomly divided into normal, 4 d, 2 wk, 4 wk, 9 wk and 11 wk groups, and the model rats were fed with a mixture of alcohol by gastric infusion at the designed time, respectively, then decollated and their livers were harvested for the examination of MMP-2, MMP-3, MMP-9, MMP-13, TIMP-1 and TIMP-2 by immunohistochemistry, zymograghy and Western blotting, respectively. RESULTS: Normal rats had moderate expression of MMP-2, which was decreased in the model rats except in the 11 wk group, where MMP-2 expression slightly increased. MMP-3 had the similar changing pattern to MMP-2 despite weaker expression. MMP-9 expression decreased in the 4 d and 2 wk groups, rose in the 4 wk group, decreased again in the 9 wk group and returned to normal levels in the 11 wk group. MMP-13 expression decreased in the 4 d and 2 wk groups, and returned to normal levels in the 4 wk, 9 wk and 11 wk groups. TIMP-1 expression decreased in the 4 d and 2 wk groups, but sharply increased in the 4 wk group and sustained at a high level even after modeling was stopped for 2 wk. In normal rats TIMP-2 expression was strong. However, it decreased as soon as modeling began, and then gradually rose, but remained to a level lower than that in normal rats even after modeling was stopped for 2 wk. CONCLUSION: MMP-2 may not always expresses at a high level during hepatic fibrosis. MMP-13 and MMP-3 are acutely affected by TIMP-1. In this model TIMP-1 is the most powerful factor imposed on capillarization and peri-sinusoidal fibrosis. TIMP-2 is the most effective regulator on the metabolism of type IV collagen located in the basement of sinus.

Dynamic changes of capillarization and peri-sinusoid fibrosis in alcoholic liver diseases.

AIM: To investigate the dynamic changes of capillarization and peri-sinusoid fibrosis in an alcoholic liver disease model induced by a new method. METHODS: Male SD rats were randomly divided into 6 groups, namely normal, 4 d, 2 w, 4 w, 9 w and 11 w groups. The animals were fed with a mixture of alcohol for designated days and then decollated, and their livers were harvested to examine the pathological changes of hepatocytes, hepatic stellate cells, sinusoidal endothelial cells, sinusoid, peri-sinusoid. The generation of three kinds of extra cellular matrix was also observed. RESULTS: The injury of hepatocytes became severer as modeling going on. Under electronic microscope, fatty vesicles and swollen mitochondria in hepatocytes, activated hepatic stellate cells with fibrils could been seen near or around it. Fenestrae of sinusoidal endothelial cells were decreased or disappeared, sinusoidal basement was formed. Under light microscopy typical peri-sinusoid fibrosis, gridding-like fibrosis, broaden portal areas, hepatocyte's fatty and balloon denaturation, iron sediment, dot necrosis, congregated lymphatic cells and leukocytes were observed. Type I collagen showed an increasing trend as modeling going on, slightly recovered when modeling stopped for 2 weeks. Meanwhile, type IV collagen decreased rapidly when modeling began and recovered after modeling stopped for 2 weeks. Laminin increased as soon as modeling began and did not recover when modeling stopped for 2 weeks. CONCLUSION: The pathological changes of the model were similar to that of human ALD, but mild in degree. It had typical peri-sinusoid fibrosis, however, capillarization seemed to be instable. It may be related with the reduction of type IV collagen in the basement of sinusoid during modeling.