Serological Prevalence of Schistosoma japonicum in Mobile Populations in Previously Endemic but Now Non-Endemic Regions of China: A Systematic Review and Meta-Analysis.

Background: Schistosomiasis japonica has been resurging in certain areas of China where its transmission was previously well controlled or interrupted. Several factors may be contributing to this, including mobile populations, which if infected, may spread the disease. A wide range of estimates have been published for S. japonicum infections in mobile populations, and a synthesis of these data will elucidate the relative risk presented from these groups. Methods: A literature search for publications up to Oct 31, 2014 on S. japonicum infection in mobile populations in previously endemic but now non-endemic regions was conducted using four bibliographic databases: China National Knowledge Infrastructure, WanFang, VIP Chinese Journal Databases, and PubMed. A meta-analysis was conducted by pooling one arm binary data with MetaAnalyst Beta 3.13. The protocol is available on PROSPERO (No. CRD42013005967). Results: A total of 41 studies in Chinese met the inclusion criteria, covering seven provinces of China. The time of post-interruption surveillance ranged from the first year to the 31st year. After employing a random-effects model, from 1992 to 2013 the pooled seroprevalence ranged from 0.9% (95% CI: 0.5-1.6%) in 2003 to 2.3% (95% CI: 1.5-3.4) in 1995; from the first year after the disease had been interrupted to the 31st year, the pooled seroprevalence ranged from 0.6% (95% CI: 0.2-2.1%) in the 27th year to 4.0% (95%CI: 1.3-11.3%) in the second year. The pooled seroprevalence in mobile populations each year was significantly lower than among the residents of endemic regions, whilst four papers reported a lower level of infection in the mobile populations than in the local residents out of only 13 papers which included this data. Conclusions: The re-emergence of S. japonicum in areas which had previously interrupted transmission might be due to other factors, although risk from re-introduction from mobile populations could not be excluded

Sequence variation in TgROP7 gene among Toxoplasma gondii isolates from different hosts and geographical regions

Toxoplasma gondii can infect a wide range of hosts including mammals and birds, causing toxoplasmosis which is one of the most common parasitic zoonoses worldwide. The present study examined sequence variation in rhoptry 7 (ROP7) gene among different T. gondii isolates from different hosts and geographical localities. Phylogenetic analysis of the examined T. gondii isolates was conducted using the maximum likelihood (ML) method. Sequence analysis revealed that 60 nucleotide positions were variable in the ROP7 gene sequences among the 19 examined T. gondii isolates, corresponding to sequence variations of 0 to 1.7%, which occurred at the first, second and third codons. Phylogenetic analysis indicated that sequence variation in ROP7 gene was low among the examined T. gondii isolates from different hosts and geographical localities, and that the ROP7 sequence was not suitable as genetic marker for the differentiation of T. gondii isolates. The results of the present study suggest that ROP7 gene may be a suitable vaccine candidate.Key words: Sequence variation, rhoptry 7 (ROP7) gene, Toxoplasma gondii, toxoplasmosis, phylogenetic analysis

Gated Diffusion-controlled Reactions

The binding and active sites of proteins are often dynamically occluded by motion of the nearby polypeptide. A variety of theoretical and computational methods have been developed to predict rates of ligand binding and reactivity in such cases. Two general approaches exist, "protein centric" approaches that explicitly treat only the protein target, and more detailed dynamical simulation approaches in which target and ligand are both treated explicitly. This mini-review describes recent work in this area and some of the biological implications

Entropic Tension in Crowded Membranes

Unlike their model membrane counterparts, biological membranes are richly decorated with a heterogeneous assembly of membrane proteins. These proteins are so tightly packed that their excluded area interactions can alter the free energy landscape controlling the conformational transitions suffered by such proteins. For membrane channels, this effect can alter the critical membrane tension at which they undergo a transition from a closed to an open state, and therefore influence protein function \emph{in vivo}. Despite their obvious importance, crowding phenomena in membranes are much less well studied than in the cytoplasm. Using statistical mechanics results for hard disk liquids, we show that crowding induces an entropic tension in the membrane, which influences transitions that alter the projected area and circumference of a membrane protein. As a specific case study in this effect, we consider the impact of crowding on the gating properties of bacterial mechanosensitive membrane channels, which are thought to confer osmoprotection when these cells are subjected to osmotic shock. We find that crowding can alter the gating energies by more than $2\;k_BT$ in physiological conditions, a substantial fraction of the total gating energies in some cases. Given the ubiquity of membrane crowding, the nonspecific nature of excluded volume interactions, and the fact that the function of many membrane proteins involve significant conformational changes, this specific case study highlights a general aspect in the function of membrane proteins.Comment: 20 pages (inclduing supporting information), 4 figures, to appear in PLoS Comp. Bio

Climate changes reconstructed from a glacial lake in High Central Asiaover the past two millennia

Climatic changes in Arid Central Asia (ACA) over the past two millennia have been widely concerned. However, less attention has been paid to those in the High Central Asia (HCA), where the Asian water tower nurtures the numerous oases by glacier and/or snow melt. Here, we present a new reconstruction of the temperature and precipitation change over the past two millennia based on grain size of a well-dated glacial lake sediment core in the central of southern Tianshan Mountains. The results show that the glacial lake catchment has experienced cold-wet climate conditions during the Dark Age Cold Period (&sim;300&ndash;600 AD; DACP) and the Little Ice Age (&sim;1300&ndash;1870 AD; LIA), whereas warm-dry conditions during the Medieval Warm Period (&sim;700&ndash;1270 AD; MWP). Integration of our results with those of previously published lake sediment records, stalagmite &delta;18O records, ice core net accumulation rates, tree-ring based temperature reconstructions, and mountain glacier activities suggest that there has a broadly similar hydroclimatic pattern over the HCA areas on centennial time scale during the past two millennia. Comparison between hydroclimatic pattern of the HCA and that of the ACA areas suggests a prevailing &#39;warm-dry and cold-wet&#39; hydroclimatic pattern over the whole westerlies-dominated central Asia areas during the past two millennia. We argue that the position and intensity of the westerlies, which are closely related to the phase of the North Atlantic Oscillation (NAO), and the strength of the Siberian High pressure (SH), could have jointly modulated the late Holocene central Asia hydroclimatic changes.<br /

At the crossroads of biomacromolecular research: highlighting the interdisciplinary nature of the field

Due to their complexity and wide-ranging utility, biomacromolecular research is an especially interdisciplinary branch of chemistry. It is my goal that the Biomacromolecules subject area of Chemistry Central Journal will parallel this richness and diversity. In this inaugural commentary, I attempt to set the stage for achieving this by highlighting several areas where biomacromolecular research overlaps more traditional chemistry sub-disciplines. Specifically, it is discussed how Materials Science and Biotechnology, Analytical Chemistry, Cell Biology and Chemical Theory are each integral to modern biomacromolecular research. Investigators with reports in any of these areas, or any other dealing with biomacromolecules, are encouraged to submit their research papers to Chemistry Central Journal

Clusters of spatial, temporal, and space-time distribution of hemorrhagic fever with renal syndrome in Liaoning Province, Northeastern China

<p>Abstract</p> <p>Background</p> <p>Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by Hantavirus, with characteristics of fever, hemorrhage, kidney damage, and hypotension. HFRS is recognized as a notifiable public health problem in China, and Liaoning Province is one of the most seriously affected areas with the most cases in China. It is necessary to investigate the spatial, temporal, and space-time distribution of confirmed cases of HFRS in Liaoning Province, China for future research into risk factors.</p> <p>Methods</p> <p>A cartogram map was constructed; spatial autocorrelation analysis and spatial, temporal, and space-time cluster analysis were conducted in Liaoning Province, China over the period 1988-2001.</p> <p>Results</p> <p>When the number of permutation test was set to 999, Moran's I was 0.3854, and was significant at significance level of 0.001. Spatial cluster analysis identified one most likely cluster and four secondary likely clusters. Temporal cluster analysis identified 1998-2001 as the most likely cluster. Space-time cluster analysis identified one most likely cluster and two secondary likely clusters.</p> <p>Conclusions</p> <p>Spatial, temporal, and space-time scan statistics may be useful in supervising the occurrence of HFRS in Liaoning Province, China. The result of this study can not only assist health departments to develop a better prevention strategy but also potentially increase the public health intervention's effectiveness.</p

Interaction site prediction by structural similarity to neighboring clusters in protein-protein interaction networks

<p>Abstract</p> <p>Background</p> <p>Recently, revealing the function of proteins with protein-protein interaction (PPI) networks is regarded as one of important issues in bioinformatics. With the development of experimental methods such as the yeast two-hybrid method, the data of protein interaction have been increasing extremely. Many databases dealing with these data comprehensively have been constructed and applied to analyzing PPI networks. However, few research on prediction interaction sites using both PPI networks and the 3D protein structures complementarily has explored.</p> <p>Results</p> <p>We propose a method of predicting interaction sites in proteins with unknown function by using both of PPI networks and protein structures. For a protein with unknown function as a target, several clusters are extracted from the neighboring proteins based on their structural similarity. Then, interaction sites are predicted by extracting similar sites from the group of a protein cluster and the target protein. Moreover, the proposed method can improve the prediction accuracy by introducing repetitive prediction process.</p> <p>Conclusions</p> <p>The proposed method has been applied to small scale dataset, then the effectiveness of the method has been confirmed. The challenge will now be to apply the method to large-scale datasets.</p