Supplementation of iron alone and combined with vitamins improves haematological status, erythrocyte membrane fluidity and oxidative stress in anaemic pregnant women

Pregnancy is a condition exhibiting increased susceptibility to oxidative stress, and Fe plays a central role in generating harmful oxygen species. The objective of the present study is to investigate the changes in haematological status, oxidative stress and erythrocyte membrane fluidity in anaemic pregnant women after Fe supplementation with and without combined vitamins. The study was a 2 months double-blind, randomised trial. Pregnant women (n 164) were allocated to four groups: group C was the placebo control group; group I was supplemented daily with 60 mg Fe (ferrous sulphate) daily; group IF was supplemented daily with Fe plus 400 µg folic acid; group IM was supplemented daily with Fe plus 2 mg retinol and 1 mg riboflavin, respectively. After the 2-month trial, Hb significantly increased by 15·8, 17·3 and 21·8 g/l, and ferritin by 2·8, 3·6 and 11·0 µg/l, in the I, IF and IM groups compared with placebo. Polarisation (¿) and microviscosity (¿) decreased significantly in other groups compared with placebo, indicating an increase in membrane fluidity. Significant decreases of ¿ and ¿ values compared with group C were 0·033 and 0·959 for group I, 0·037 and 1·074 for group IF and 0·064 and 1·865 for group IM, respectively. In addition, significant increases of glutathione peroxidase activities and decreases of malondialdehyde were shown in all treated groups, as well as increases of plasma retinol and urine riboflavin in group IM. The findings show that supplementation with Fe and particularly in combination with vitamins could improve the haematological status as well as oxidative stress and erythrocyte membrane fluidit

An Image Filter Based on Shearlet Transformation and Particle Swarm Optimization Algorithm

Digital image is always polluted by noise and made data postprocessing difficult. To remove noise and preserve detail of image as much as possible, this paper proposed image filter algorithm which combined the merits of Shearlet transformation and particle swarm optimization (PSO) algorithm. Firstly, we use classical Shearlet transform to decompose noised image into many subwavelets under multiscale and multiorientation. Secondly, we gave weighted factor to those subwavelets obtained. Then, using classical Shearlet inverse transform, we obtained a composite image which is composed of those weighted subwavelets. After that, we designed fast and rough evaluation method to evaluate noise level of the new image; by using this method as fitness, we adopted PSO to find the optimal weighted factor we added; after lots of iterations, by the optimal factors and Shearlet inverse transform, we got the best denoised image. Experimental results have shown that proposed algorithm eliminates noise effectively and yields good peak signal noise ratio (PSNR)

Heterogeneity in Surface Sensing Suggests a Division of Labor in Pseudomonas aeruginosa Populations

The second messenger signaling molecule cyclic diguanylate monophosphate (c-di-GMP) drives the transition between planktonic and biofilm growth in many bacterial species. Pseudomonas aeruginosa has two surface sensing systems that produce c-di-GMP in response to surface adherence. Current thinking in the field is that once cells attach to a surface, they uniformly respond by producing c-di-GMP. Here, we describe how the Wsp system generates heterogeneity in surface sensing, resulting in two physiologically distinct subpopulations of cells. One subpopulation has elevated c-di-GMP and produces biofilm matrix, serving as the founders of initial microcolonies. The other subpopulation has low c-di-GMP and engages in surface motility, allowing for exploration of the surface. We also show that this heterogeneity strongly correlates to surface behavior for descendent cells. Together, our results suggest that after surface attachment, P. aeruginosa engages in a division of labor that persists across generations, accelerating early biofilm formation and surface exploration

Interferon gamma (IFN-γ) disrupts energy expenditure and metabolic homeostasis by suppressing SIRT1 transcription

Chronic inflammation impairs metabolic homeostasis and is intimately correlated with the pathogenesis of type 2 diabetes. The pro-inflammatory cytokine IFN-γ is an integral part of the metabolic inflammation circuit and contributes significantly to metabolic dysfunction. The underlying mechanism, however, remains largely unknown. In the present study, we report that IFN-γ disrupts the expression of genes key to cellular metabolism and energy expenditure by repressing the expression and activity of SIRT1 at the transcription level. Further analysis reveals that IFN-γ requires class II transactivator (CIITA) to repress SIRT1 transcription. CIITA, once induced by IFN-γ, is recruited to the SIRT1 promoter by hypermethylated in cancer 1 (HIC1) and promotes down-regulation of SIRT1 transcription via active deacetylation of core histones surrounding the SIRT1 proximal promoter. Silencing CIITA or HIC1 restores SIRT1 activity and expression of metabolic genes in skeletal muscle cells challenged with IFN-γ. Therefore, our data delineate an IFN-γ/HIC1/CIITA axis that contributes to metabolic dysfunction by suppressing SIRT1 transcription in skeletal muscle cells and as such shed new light on the development of novel therapeutic strategies against type 2 diabetes

NUMERICAL NUMERICAL NUMERICAL NUMERICAL RESEARCH RESEARCH RESEARCH RESEARCH ON ON ON ON FORCED FORCED FORCED FORCED RESPONSE RESPONSE RESPONSE RESPONSE OF OF OF OF A A A A COMPRESSOR COMPRESSOR COMPRESSOR COMPRESSOR ROTOR ROTOR ROTOR ROTOR ROW ROW ROW ROW

ABSTRACT ABSTRACT ABSTRACT ABSTRACT Under inlet total pressure distortion, forced response of compressor blades poses a threat to aircraft propulsion system. Research on blade dynamic response is premise and basis for high-cycle fatigue life analysis. Blades of a compressor first rotor row are studied with three dimensional numerical simulation in fluid-structure coupling methods. The inlet distortion's influence on blade aeroelastic dynamic response and flow field characteristics are analyzed. The results demonstrate that circumferential and radial total pressure distortion should be considered together in the phenomenon of actual inlet distortion induced blade vibration response. At the condition of low angle of attacks, radial distortion intensity is weak, the relation between vibration response level of rotor blades and circumferential distortion intensity is proportional. With the angle of attack increases, the vibratory stress under aerodynamic forces grows sufficiently. The radial total pressure distortion near hub increases dynamic response severity of rotor blades

An Adaptive Filtering Algorithm Based on Genetic Algorithm-Backpropagation Network

A new image filtering algorithm is proposed. GA-BPN algorithm uses genetic algorithm (GA) to decide weights in a back propagation neural network (BPN). It has better global optimal characteristics than traditional optimal algorithm. In this paper, we used GA-BPN to do image noise filter researching work. Firstly, this paper uses training samples to train GA-BPN as the noise detector. Then, we utilize the well-trained GA-BPN to recognize noise pixels in target image. And at last, an adaptive weighted average algorithm is used to recover noise pixels recognized by GA-BPN. Experiment data shows that this algorithm has better performance than other filters

A Novel Approach to H

This paper is concerned with the problem of H∞ control of linear neutral systems with time-varying delay. Firstly, by applying a novel Lyapunov-Krasovskii functional which is constructed with the idea of delay partitioning approach, appropriate free-weighting matrices, an improved delay-dependent bounded real lemma (BRL) for neutral systems is established. By using the obtained BRL, a delay-dependent sufficient condition for the existence of a state-feedback controller, which ensures asymptotic stability and a prescribed H∞ performance level of the corresponding closed-loop system, is formulated in terms of linear matrix inequalities. Some numerical examples are given to illustrate the effectiveness of the proposed design method

An Efficient Approach for Identification of the Inlet Distortion of Engine Based on Acoustic Emission Technique

Effective and accurate diagnosis of engine health is key to ensuring the safe operation of engines. Inlet distortion is due to the flow or the pressure variations. In the paper, an acoustic emission (AE) online monitoring technique, which has a faster response time compared with the ordinary vibration monitoring technique, is used to study the inlet distortion of an engine. The results show that with the deterioration of the inlet distortion, the characteristic parameters of AE signals clearly evolve in three stages. Stage I: when the inlet distortion J ≤ 30%, the characteristic parameters of the AE signal increase as J increases and the amplitude saturates at J = 23%, faster than the other three parameters (the strength, the root mean square (RMS), and the average signal level (ASL)). Stage II: when the inlet distortion 30% < J ≤ 43.64%, all the parameters saturate with only slight fluctuations as J increases and the engine works in an unstable statue. Stage III: when the inlet distortion J > 43.64%, the engine is prone to surge. Furthermore, an intelligent recognition method of the engine inlet distortion based on a unit parameter entropy and the back propagation (BP) neural network is constructed. The recognition accuracy is as high as 97.5%, and this method provides a new approach for engine health management