Einstein Probe - a small mission to monitor and explore the dynamic X-ray Universe

Einstein Probe is a small mission dedicated to time-domain high-energy astrophysics. Its primary goals are to discover high-energy transients and to monitor variable objects in the $0.5-4~$keV X-rays, at higher sensitivity by one order of magnitude than those of the ones currently in orbit. Its wide-field imaging capability, featuring a large instantaneous field-of-view ($60^\circ \times60^\circ$, $\sim1.1$sr), is achieved by using established technology of micro-pore (MPO) lobster-eye optics, thereby offering unprecedentedly high sensitivity and large Grasp. To complement this powerful monitoring ability, it also carries a narrow-field, sensitive follow-up X-ray telescope based on the same MPO technology to perform follow-up observations of newly-discovered transients. Public transient alerts will be downlinked rapidly, so as to trigger multi-wavelength follow-up observations from the world-wide community. Over three of its 97-minute orbits almost the entire night sky will be sampled, with cadences ranging from 5 to 25 times per day. The scientific objectives of the mission are: to discover otherwise quiescent black holes over all astrophysical mass scales by detecting their rare X-ray transient flares, particularly tidal disruption of stars by massive black holes at galactic centers; to detect and precisely locate the electromagnetic sources of gravitational-wave transients; to carry out systematic surveys of X-ray transients and characterize the variability of X-ray sources. Einstein Probe has been selected as a candidate mission of priority (no further selection needed) in the Space Science Programme of the Chinese Academy of Sciences, aiming for launch around 2020.Comment: accepted to publish in PoS, Proceedings of "Swift: 10 Years of Discovery" (Proceedings of Science; ed. by P. Caraveo, P. D'Avanzo, N. Gehrels and G. Tagliaferri). Minor changes in text, references update

Rapid Screening of Complex DNA Samples by Single-Molecule Amplification and Sequencing

Microbial cloning makes Sanger sequencing of complex DNA samples possible but is labor intensive. We present a simple, rapid and robust method that enables laboratories without special equipment to perform single-molecule amplicon sequencing, although in a low-throughput manner, from sub-picogram quantities of DNA. The method can also be used for quick quality control of next-generation sequencing libraries, as was demonstrated for a metagenomic sample

Discovering patterns in drug-protein interactions based on their fingerprints

<p>Abstract</p> <p>Background</p> <p>The discovering of interesting patterns in drug-protein interaction data at molecular level can reveal hidden relationship among drugs and proteins and can therefore be of paramount importance for such application as drug design. To discover such patterns, we propose here a computational approach to analyze the molecular data of drugs and proteins that are known to have interactions with each other. Specifically, we propose to use a data mining technique called <it>Drug-Protein Interaction Analysis </it>(<it>D-PIA</it>) to determine if there are any commonalities in the fingerprints of the substructures of interacting drug and protein molecules and if so, whether or not any patterns can be generalized from them.</p> <p>Method</p> <p>Given a database of drug-protein interactions, <it>D-PIA </it>performs its tasks in several steps. First, for each drug in the database, the fingerprints of its molecular substructures are first obtained. Second, for each protein in the database, the fingerprints of its protein domains are obtained. Third, based on known interactions between drugs and proteins, an interdependency measure between the fingerprint of each drug substructure and protein domain is then computed. Fourth, based on the interdependency measure, drug substructures and protein domains that are significantly interdependent are identified. Fifth, the existence of interaction relationship between a previously unknown drug-protein pairs is then predicted based on their constituent substructures that are significantly interdependent.</p> <p>Results</p> <p>To evaluate the effectiveness of <it>D-PIA</it>, we have tested it with real drug-protein interaction data. <it>D-PIA </it>has been tested with real drug-protein interaction data including enzymes, ion channels, and protein-coupled receptors. Experimental results show that there are indeed patterns that one can discover in the interdependency relationship between drug substructures and protein domains of interacting drugs and proteins. Based on these relationships, a testing set of drug-protein data are used to see if <it>D-PIA </it>can correctly predict the existence of interaction between drug-protein pairs. The results show that the prediction accuracy can be very high. An AUC score of a ROC plot could reach as high as 75% which shows the effectiveness of this classifier.</p> <p>Conclusions</p> <p><it>D-PIA </it>has the advantage that it is able to perform its tasks effectively based on the fingerprints of drug and protein molecules without requiring any 3D information about their structures and <it>D-PIA </it>is therefore very fast to compute. <it>D-PIA </it>has been tested with real drug-protein interaction data and experimental results show that it can be very useful for predicting previously unknown drug-protein as well as protein-ligand interactions. It can also be used to tackle problems such as ligand specificity which is related directly and indirectly to drug design and discovery.</p

Knockdown of hTERT and Treatment with BIBR1532 Inhibit Cell Proliferation and Invasion in Endometrial Cancer Cells

Telomerase activity and expression of the catalytic protein hTERT are associated with cell proliferation and advanced stage in endometrial cancer. Our objective was to evaluate the effect of inhibition of hTERT by siRNA and BIBR1532 on cell growth, apoptosis and invasion in endometrial cancer cells. Knockdown of hTERT or treatment of the cells with BIBR1532 decreased telomerase activity, inhibited cell proliferation, induced apoptosis, and reduced cell invasion in Ishikawa and ECC-1 cells. Either hTERT siRNA or BIBR1532 in combination with paclitaxel promoted a synergistic inhibitory effect on cell growth through induction of Annexin V expression and a remarkable reduction in cell invasion through reduction of protein expression of MMP9, MMP2, and MMP3. Increased telomerase activity and hTERT protein expression by transfections enhanced the protein expression of MMPs and increased the cell invasion ability. BIBR1532 significantly antagonized cell invasion induced by increased hTERT expression. These findings suggest that telomerase and hTERT facilitate cell invasion via MMP family in human endometrial cancer cells

Understanding how excess lead iodide precursor improves halide perovskite solar cell performance

The presence of excess lead iodide in halide perovskites has been key for surpassing 20% photon-to-power conversion efficiency. To achieve even higher power conversion efficiencies, it is important to understand the role of remnant lead iodide in these perovskites. To that end, we explored the mechanism facilitating this effect by identifying the impact of excess lead iodide within the perovskite film on charge diffusion length, using electron-beam-induced current measurements, and on film formation properties, from grazing-incidence wide-angle X-ray scattering and high-resolution transmission electron microscopy. Based on our results, we propose that excess lead iodide in the perovskite precursors can reduce the halide vacancy concentration and lead to formation of azimuthal angle-oriented cubic alpha-perovskite crystals in-between 0 degrees and 90 degrees. We further identify a higher perovskite carrier concentration inside the nanostructured titanium dioxide layer than in the capping layer. These effects are consistent with enhanced lead iodide-rich perovskite solar cell performance and illustrate the role of lead iodide

Rural-urban differences of neonatal mortality in a poorly developed province of China

<p>Abstract</p> <p>Background</p> <p>The influence of rural-urban disparities in children's health on neonatal death in disadvantaged areas of China is poorly understood. In this study of rural and urban populations in Gansu province, a disadvantaged province of China, we describe the characteristics and mortality of newborn infants and evaluated rural-urban differences of neonatal death.</p> <p>Methods</p> <p>We analyzed all neonatal deaths in the data from the Surveillance System of Child Death in Gansu Province, China from 2004 to 2009. We calculated all-cause neonatal mortality rates (NMR) and cause-specific death rates for infants born to rural or urban mothers during 2004-09. Rural-urban classifications were determined based on the residence registry system of China. Chi-square tests were used to compare differences of infant characteristics and cause-specific deaths by rural-urban maternal residence.</p> <p>Results</p> <p>Overall, NMR fell in both rural and urban populations during 2004-09. Average NMR for rural and urban populations was 17.8 and 7.5 per 1000 live births, respectively. For both rural and urban newborn infants, the four leading causes of death were birth asphyxia, preterm or low birth weight, congenital malformation, and pneumonia. Each cause-specific death rate was higher in rural infants than in urban infants. More rural than urban neonates died out of hospital or did not receive medical care before death.</p> <p>Conclusions</p> <p>Neonatal mortality declined dramatically both in urban and rural groups in Gansu province during 2004-09. However, profound disparities persisted between rural and urban populations. Strategies that address inequalities of accessibility and quality of health care are necessary to improve neonatal health in rural settings in China.</p

Chronic disease prevalence and care among the elderly in urban and rural Beijing, China - a 10/66 Dementia Research Group cross-sectional survey

<p>Abstract</p> <p>Background</p> <p>Demographic ageing is occurring at an unprecedented rate in China. Chronic diseases and their disabling consequences will become much more common. Public policy has a strong urban bias, and older people living in rural areas may be especially vulnerable due to limited access to good quality healthcare, and low pension coverage. We aim to compare the sociodemographic and health characteristics, health service utilization, needs for care and informal care arrangements of representative samples of older people in two Beijing communities, urban Xicheng and rural Daxing.</p> <p>Methods</p> <p>A one-phase cross-sectional survey of all those aged 65 years and over was conducted in urban and rural catchment areas in Beijing, China. Assessments included questionnaires, a clinical interview, physical examination, and an informant interview. Prevalence of chronic diseases, self-reported impairments and risk behaviours was calculated adjusting for household clustering. Poisson working models were used to estimate the independent effect of rural versus urban residence, and to explore the predictors of health services utilization.</p> <p>Results</p> <p>We interviewed 1002 participants in rural Daxing, and 1160 in urban Xicheng. Those in Daxing were more likely to be younger, widowed, less educated, not receiving a pension, and reliant on family transfers. Chronic diseases were more common in Xicheng, when based on self-report rather than clinical assessment. Risk exposures were more common in Daxing. Rural older people were much less likely to access health services, controlling for age and health. Community health services were ineffective, particularly in Daxing, where fewer than 3% of those with hypertension were adequately controlled. In Daxing, care was provided by family, who had often given up work to do so. In Xicheng, 45% of those needing care were supported by paid caregivers. Caregiver strain was higher in Xicheng. Dementia was strongly associated with care needs and caregiver strain, but not with medical helpseeking.</p> <p>Conclusion</p> <p>Apparent better health in Daxing might be explained by under-diagnosis, under-reporting or selective mortality. Far-reaching structural reforms may be needed to improve access and strengthen rural healthcare. The impact of social and economic change is already apparent in Xicheng, with important implications for future long-term care.</p