Improving the Efficacy of Conventional Therapy by Adding Andrographolide Sulfonate in the Treatment of Severe Hand, Foot, and Mouth Disease: A Randomized Controlled Trial

Background. Herb-derived compound andrographolide sulfonate (called Xiyanping injection) recommended control measure for severe hand, foot, and mouth disease (HFMD) by the Ministry of Health (China) during the 2010 epidemic. However, there is a lack of good quality evidence directly comparing the efficacy of Andrographolide Sulfonate combination therapy with conventional therapy. Methods. 230 patients were randomly assigned to 7–10 days of Andrographolide Sulfonate 5–10 mg/Kg/day and conventional therapy, or conventional therapy alone. Results. The major complications occurred less often after Andrographolide Sulfonate (2.6% versus 12.1%; risk difference [RD], 0.94; 95% CI, 0.28–1.61; P=0.006). Median fever clearance times were 96 hours (CI, 80 to 126) for conventional therapy recipients and 48 hours (CI, 36 to 54) for Andrographolide Sulfonate combination-treated patients (χ2=16.57, P<0.001). The two groups did not differ in terms of HFMD-cause mortality (P=1.00) and duration of hospitalization (P=0.70). There was one death in conventional therapy group. No important adverse event was found in Andrographolide Sulfonate combination therapy group. Conclusions. The addition of Andrographolide Sulfonate to conventional therapy reduced the occurrence of major complications, fever clearance time, and the healing time of typical skin or oral mucosa lesions in children with severe HFMD

Molecular epidemiology of measles viruses in China, 1995–2003

This report describes the genetic characterization of 297 wild-type measles viruses that were isolated in 24 provinces of China between 1995 and 2003. Phylogenetic analysis of the N gene sequences showed that all of the isolates belonged to genotype H1 except 3 isolates, which were genotype A. The nucleotide sequence and predicted amino acid homologies of the 294-genotype H1 strains were 94.7%–100% and 93.3%–100%, respectively. The genotype H1 isolates were divided into 2 clusters, which differed by approximately 2.9% at the nucleotide level. Viruses from both clusters were distributed throughout China with no apparent geographic restriction and multiple co-circulating lineages were present in many provinces. Even though other measles genotypes have been detected in countries that border China, this report shows that genotype H1 is widely distributed throughout the country and that China has a single, endemic genotype. This important baseline data will help to monitor the progress of measles control in China

SDAE-BP Based Octane Number Soft Sensor Using Near-infrared Spectroscopy in Gasoline Blending Process

As the most important properties in the gasoline blending process, octane number is difficult to be measured in real time. To address this problem, a novel deep learning based soft sensor strategy, by using the near-infrared (NIR) spectroscopy obtained in the gasoline blending process, is proposed. First, as a network structure with hidden layer as symmetry axis, input layer and output layer as symmetric, the denosing auto-encoder (DAE) realizes the advanced expression of input. Additionally, the stacked DAE (SDAE) is trained based on unlabeled NIR and the weights in each DAE is recorded. Then, the recorded weights are used as the initial parameters of back propagation (BP) with the reason that the SDAE trained initial weights can avoid local minimums and realizes accelerate convergence, and the soft sensor model is achieved with labeled NIR data. Finally, the achieved soft sensor model is used to estimate the real time octane number. The performance of the method is demonstrated through the NIR dataset of gasoline, which was collected from a real gasoline blending process. Compared with PCA-BP (the dimension of datasets of BP reduced by principal component analysis) soft sensor model, the prediction accuracy was improved from 86.4% of PCA-BP to 94.8%, and the training time decreased from 20.1 s to 16.9 s. Therefore, SDAE-BP is proposed as a novel method for rapid and efficient determination of octane number in the gasoline blending process

Rapid determination of acetaminophen and p-aminophenol in pharmaceutical formulations using miniaturized capillary electrophoresis with amperometric detection

Capability of fast analysis of a novel miniaturized capillary electrophoresis with carbon disk electrode amperometric detection (mini-CE-AD) system was demonstrated by determining acetaminophen and p-aminophenol in dosage forms. Factors influencing the separation and detection processes were examined and optimized. Under the optimum conditions, the end-capillary 300 μm carbon disc electrode amperometric detector offered favorable signal-to-noise characteristics at a relatively low potential (+600 mV versus Ag/AgCl) for detecting acetaminophen and p-aminophenol. Two analytes can been separated within 150 s in a 8.5 cm length capillary at a separation voltage of 2000 V using a Na₂B₄O₇–KH₂PO₄ running buffer (pH 7.2). Acetaminophen and p-aminophenol could be detected down to the 1.4 × 10⁻⁶–5.9 × 10⁻⁷ mol L⁻¹ level with linearity up to the 1.0 × 10⁻³ mol L⁻¹ level examined. The inter-day repeatability for analytes in peak current (R.S.D. ≤ 2.3%) and migration times (R.S.D. ≤ 1.3%) were excellent. The proposed mini-CE-AD system should find a wide range of analytical applications in pharmaceutical formulations as an alternative to conventional CE and μ-CE.6 page(s

Application of capillary electrophoresis to study phenolic profiles of honeybee-collected pollen

Honeybee-collected pollen is promoted as a health food with a wide range of nutritional and therapeutic properties. A high-performance capillary electrophoresis with amperometric detection method has been developed for the simultaneous determination of bioactive ingredients in 10 samples of honeybee-collected pollen in this work. Under the optimum conditions, 13 phenolic components can be well-separated or nearly baseline-separated (apigenin and vanillic acid peaks) within 29 min at the separation voltage of 14 kV in a 50 mM borax running buffer (pH 9.0), and adequate extraction was obtained with ethanol for the determination of the above 13 compounds. Recovery (94.1–104.0%), repeatability of the peak current (<5.4%), and detection limits (6.9 × 10⁻⁷−6.4 × 10⁻⁹ g mL⁻¹) for the method were evaluated. This procedure was successfully used for the analysis and comparison of the phenolic content of honeybee-collected pollen samples originating from different floral origins based on their electropherograms or “phenolic profiles”.6 page(s

POSITIVITY-PRESERVING LOCAL DISCONTINUOUS GALERKIN METHOD FOR PATTERN FORMATION DYNAMICAL MODEL IN POLYMERIZING ACTIN FLOCKS\u3csup\u3e*\u3c/sup\u3e

In this paper, we apply local discontinuous Galerkin (LDG) methods for pattern formation dynamical model in polymerizing actin flocks. There are two main difficulties in designing effective numerical solvers. First of all, the density function is non-negative, and zero is an unstable equilibrium solution. Therefore, negative density values may yield blow-up solutions. To obtain positive numerical approximations, we apply the positivity-preserving (PP) techniques. Secondly, the model may contain stiff source. The most commonly used time integration for the PP technique is the strong-stability-preserving Runge-Kutta method. However, for problems with stiff source, such time discretizations may require strictly limited time step sizes, leading to large computational cost. Moreover, the stiff source any trigger spurious filament polarization, leading to wrong numerical approximations on coarse meshes. In this paper, we combine the PP LDG methods with the semi-implicit Runge-Kutta methods. Numerical experiments demonstrate that the proposed method can yield accurate numerical approximations with relatively large time steps

A local discontinuous Galerkin method for pattern formation dynamical model in polymerizing action flocks

In this paper, we apply local discontinuous Galerkin methods to the pattern formation dynamical model in polymerizing action flocks. Optimal error estimates for the density and filament polarization in different norms are established. We use a semi-implicit spectral deferred correction time method for time discretization, which allows a relative large time step and avoids computation of a Jacobian matrix. Numerical experiments are presented to verify the theoretical analysis and to show the capability for simulations of action wave formation