Cadmium-Induced Oxidative Stress and Apoptotic Changes in the Testis of Freshwater Crab, Sinopotamon henanense

Cadmium (Cd), one of the most toxic environmental and industrial pollutants, is known to exert gonadotoxic and spermiotoxic effects. In the present study, we examined the toxic effect of Cd on the testis of freshwater crab, Sinopotamon henanense. Crabs were exposed to different Cd concentrations (from 0 to 116.00 mg·L−1) for 7 d. Oxidative stress and apoptotic changes in the testes were detected. The activities of SOD, GPx and CAT initially increased and subsequently decreased with increasing Cd concentrations, which was accompanied with the increase in malondialdehyde (MDA) and H2O2 content in a concentration-dependent manner. Typical morphological characteristic and physiological changes of apoptosis were observed using a variety of methods (HE staining, AO/EB double fluorescent staining, Transmission Electron Microscope observation and DNA fragmentation analysis), and the activities of caspase-3 and caspase-9 were increased in a concentration-dependent manner after Cd exposure. These results led to the conclusion that Cd could induced oxidative damage as well as apoptosis in the testis, and the apoptotic processes may be mediated via mitochondria-dependent apoptosis pathway by regulating the activities of caspase-3 and caspase-9

A comparison of approximation techniques for variance-based sensitivity analysis of biochemical reaction systems

<p>Abstract</p> <p>Background</p> <p>Sensitivity analysis is an indispensable tool for the analysis of complex systems. In a recent paper, we have introduced a thermodynamically consistent variance-based sensitivity analysis approach for studying the robustness and fragility properties of biochemical reaction systems under uncertainty in the standard chemical potentials of the activated complexes of the reactions and the standard chemical potentials of the molecular species. In that approach, key sensitivity indices were estimated by Monte Carlo sampling, which is computationally very demanding and impractical for large biochemical reaction systems. Computationally efficient algorithms are needed to make variance-based sensitivity analysis applicable to realistic cellular networks, modeled by biochemical reaction systems that consist of a large number of reactions and molecular species.</p> <p>Results</p> <p>We present four techniques, derivative approximation (DA), polynomial approximation (PA), Gauss-Hermite integration (GHI), and orthonormal Hermite approximation (OHA), for <it>analytically </it>approximating the variance-based sensitivity indices associated with a biochemical reaction system. By using a well-known model of the mitogen-activated protein kinase signaling cascade as a case study, we numerically compare the approximation quality of these techniques against traditional Monte Carlo sampling. Our results indicate that, although DA is computationally the most attractive technique, special care should be exercised when using it for sensitivity analysis, since it may only be accurate at low levels of uncertainty. On the other hand, PA, GHI, and OHA are computationally more demanding than DA but can work well at high levels of uncertainty. GHI results in a slightly better accuracy than PA, but it is more difficult to implement. OHA produces the most accurate approximation results and can be implemented in a straightforward manner. It turns out that the computational cost of the four approximation techniques considered in this paper is orders of magnitude smaller than traditional Monte Carlo estimation. Software, coded in MATLAB^®, which implements all sensitivity analysis techniques discussed in this paper, is available free of charge.</p> <p>Conclusions</p> <p>Estimating variance-based sensitivity indices of a large biochemical reaction system is a computationally challenging task that can only be addressed via approximations. Among the methods presented in this paper, a technique based on orthonormal Hermite polynomials seems to be an acceptable candidate for the job, producing very good approximation results for a wide range of uncertainty levels in a fraction of the time required by traditional Monte Carlo sampling.</p

Prediction of protein binding sites in protein structures using hidden Markov support vector machine

<p>Abstract</p> <p>Background</p> <p>Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. Recent research on protein binding site prediction has been mainly based on widely known machine learning techniques, such as artificial neural networks, support vector machines, conditional random field, etc. However, the prediction performance is still too low to be used in practice. It is necessary to explore new algorithms, theories and features to further improve the performance.</p> <p>Results</p> <p>In this study, we introduce a novel machine learning model hidden Markov support vector machine for protein binding site prediction. The model treats the protein binding site prediction as a sequential labelling task based on the maximum margin criterion. Common features derived from protein sequences and structures, including protein sequence profile and residue accessible surface area, are used to train hidden Markov support vector machine. When tested on six data sets, the method based on hidden Markov support vector machine shows better performance than some state-of-the-art methods, including artificial neural networks, support vector machines and conditional random field. Furthermore, its running time is several orders of magnitude shorter than that of the compared methods.</p> <p>Conclusion</p> <p>The improved prediction performance and computational efficiency of the method based on hidden Markov support vector machine can be attributed to the following three factors. Firstly, the relation between labels of neighbouring residues is useful for protein binding site prediction. Secondly, the kernel trick is very advantageous to this field. Thirdly, the complexity of the training step for hidden Markov support vector machine is linear with the number of training samples by using the cutting-plane algorithm.</p

First finds of Prunus domestica L. in Italy from the Phoenician and Punic periods (6th-2nd centuries BC)

Abstract During the archaeological excavations in the Phoenician and Punic settlement of Santa Giusta (Oristano, Sardinia, Italy), dating back to the 6th–2nd centuries bc, several Prunus fruitstones (endocarps) inside amphorae were recovered. The exceptional state of preservation of the waterlogged remains allowed morphometric measurements to be done by image analysis and statistical comparisons made with modern cultivated and wild Prunus samples collected in Sardinia. Digital images of modern and archaeological Prunus fruitstones were acquired with a flatbed scanner and analysed by applying image analysis techniques to measure 26 morphometric features. By applying stepwise linear discriminant analysis, a morphometric comparison was made between the archaeological fruitstones of Prunus and the modern ones collected in Sardinia. These analyses allowed identification of 53 archaeological fruitstones as P. spinosa and 11 as P. domestica. Moreover, the archaeological samples of P. spinosa showed morphometric similarities in 92.5% of the cases with the modern P. spinosa samples currently growing near the Phoenician and Punic site. Likewise, the archaeological fruitstones identified as P. domestica showed similarities with the modern variety of P. domestica called Sanguigna di Bosa which is currently cultivated near the village of Bosa. Currently, these findings represent the first evidence of P. domestica in Italy during the Phoenician and Punic periods. Keywords Archaeobotany · Image analysis · Morphometric features · Prunus · Sardini

Prevalence and trend of hepatitis C virus infection among blood donors in Chinese mainland: a systematic review and meta-analysis

<p>Abstract</p> <p>Background</p> <p>Blood transfusion is one of the most common transmission pathways of hepatitis C virus (HCV). This paper aims to provide a comprehensive and reliable tabulation of available data on the epidemiological characteristics and risk factors for HCV infection among blood donors in Chinese mainland, so as to help make prevention strategies and guide further research.</p> <p>Methods</p> <p>A systematic review was constructed based on the computerized literature database. Infection rates and 95% confidence intervals (95% CI) were calculated using the approximate normal distribution model. Odds ratios and 95% CI were calculated by fixed or random effects models. Data manipulation and statistical analyses were performed using STATA 10.0 and ArcGIS 9.3 was used for map construction.</p> <p>Results</p> <p>Two hundred and sixty-five studies met our inclusion criteria. The pooled prevalence of HCV infection among blood donors in Chinese mainland was 8.68% (95% CI: 8.01%-9.39%), and the epidemic was severer in North and Central China, especially in Henan and Hebei. While a significant lower rate was found in Yunnan. Notably, before 1998 the pooled prevalence of HCV infection was 12.87% (95%CI: 11.25%-14.56%) among blood donors, but decreased to 1.71% (95%CI: 1.43%-1.99%) after 1998. No significant difference was found in HCV infection rates between male and female blood donors, or among different blood type donors. The prevalence of HCV infection was found to increase with age. During 1994-1995, the prevalence rate reached the highest with a percentage of 15.78% (95%CI: 12.21%-19.75%), and showed a decreasing trend in the following years. A significant difference was found among groups with different blood donation types, Plasma donors had a relatively higher prevalence than whole blood donors of HCV infection (33.95% <it>vs </it>7.9%).</p> <p>Conclusions</p> <p>The prevalence of HCV infection has rapidly decreased since 1998 and kept a low level in recent years, but some provinces showed relatively higher prevalence than the general population. It is urgent to make efficient measures to prevent HCV secondary transmission and control chronic progress, and the key to reduce the HCV incidence among blood donors is to encourage true voluntary blood donors, strictly implement blood donation law, and avoid cross-infection.</p