Thrombotic microangiopathies and acute kidney injury induced by artificial termination of pregnancy

Thrombotic microangiopathy (TMA) is a rare, but potentially lethal condition requiring rapid recognition, diagnosis and initiation of therapy. Here, we present two cases of women with hemolytic anemia, thrombocytopenia and acute kidney injury shortly after surgical termination of pregnancy. Histological examination of their kidneys revealed endothelial cell swelling and luminal stenosis or fibrin.containing thrombi in the glomeruli and arterioles, which support the diagnosis of TMA. The patients were treated with hemodialysis, plasma infusion and corticosteroids with or without  immunosuppressive agents. Three weeks after treatment, one patient was cured and symptoms of the other patient markedly improved. Reporting of more cases of TMA associated with surgical termination of pregnancy will provide further insights into this rare disease, possibly aiding in identifying risk factors and improving time to clinical diagnosis, treatment and  prognosis.Key words: Acute renal failure, case studies, induced abortion, pregnancy, thrombotic microangiopath

Light hadron, Charmonium(-like) and Bottomonium(-like) states

Hadron physics represents the study of strongly interacting matter in all its manifestations and the understanding of its properties and interactions. The interest on this field has been revitalized by the discovery of new light hadrons, charmonium- and bottomonium-like states. I review the most recent experimental results from different experiments.Comment: Presented at Lepton-Photon 2011, Mumbai, India; 21 pages, 18 figures; add more references; some correctio

Self-assembly of DNA nanogels with endogenous microRNA toehold self-regulating switches for targeted gene regulation therapy

Herein, a smart nanohydrogel with endogenous microRNA-21 toehold is developed to encapsulate gemcitabine-loaded mesoporous silica nanoparticles for targeted pancreatic cancer therapy. This toehold mediated strand displacement method can simultaneously achieve specific drug release and miRNA-21 silencing, resulting in the up-regulation of the expression of tumor suppressor genes PTEN and PDCD4

A Multi-Label Predictor for Identifying the Subcellular Locations of Singleplex and Multiplex Eukaryotic Proteins

Subcellular locations of proteins are important functional attributes. An effective and efficient subcellular localization predictor is necessary for rapidly and reliably annotating subcellular locations of proteins. Most of existing subcellular localization methods are only used to deal with single-location proteins. Actually, proteins may simultaneously exist at, or move between, two or more different subcellular locations. To better reflect characteristics of multiplex proteins, it is highly desired to develop new methods for dealing with them. In this paper, a new predictor, called Euk-ECC-mPLoc, by introducing a powerful multi-label learning approach which exploits correlations between subcellular locations and hybridizing gene ontology with dipeptide composition information, has been developed that can be used to deal with systems containing both singleplex and multiplex eukaryotic proteins. It can be utilized to identify eukaryotic proteins among the following 22 locations: (1) acrosome, (2) cell membrane, (3) cell wall, (4) centrosome, (5) chloroplast, (6) cyanelle, (7) cytoplasm, (8) cytoskeleton, (9) endoplasmic reticulum, (10) endosome, (11) extracellular, (12) Golgi apparatus, (13) hydrogenosome, (14) lysosome, (15) melanosome, (16) microsome, (17) mitochondrion, (18) nucleus, (19) peroxisome, (20) spindle pole body, (21) synapse, and (22) vacuole. Experimental results on a stringent benchmark dataset of eukaryotic proteins by jackknife cross validation test show that the average success rate and overall success rate obtained by Euk-ECC-mPLoc were 69.70% and 81.54%, respectively, indicating that our approach is quite promising. Particularly, the success rates achieved by Euk-ECC-mPLoc for small subsets were remarkably improved, indicating that it holds a high potential for simulating the development of the area. As a user-friendly web-server, Euk-ECC-mPLoc is freely accessible to the public at the website http://levis.tongji.edu.cn:8080/bioinfo/Euk-ECC-mPLoc/. We believe that Euk-ECC-mPLoc may become a useful high-throughput tool, or at least play a complementary role to the existing predictors in identifying subcellular locations of eukaryotic proteins

Dynamic liquefaction of shear zones in intact loess during simulated earthquake loading

The 2010-2011 Canterbury earthquake sequence in New Zealand exposed loess-mantled slopes in the area to very high levels of seismic excitation (locally measured as >2 g). Few loess slopes showed permanent local downslope deformation, and most of these showed only limited accumulated displacement. A series of innovative dynamic back pressured shear-box tests were undertaken on intact and remoulded loess samples collected from one of the recently active slopes replicating field conditions under different simplified horizontal seismic excitations. During each test, the strength reduction and excess pore water pressures generated were measured as the sample failed. Test results suggest that although dynamic liquefaction could have occurred, a key factor was likely to have been that the loess was largely unsaturated at the times of the large earthquake events. The failure of intact loess samples in the tests was complex and variable due to the highly variable geotechnical characteristics of the material. Some loess samples failed rapidly as a result of dynamic liquefaction as seismic excitation generated an increase in pore-water pressure, triggering rapid loss of strength and thus of shear resistance. Following initial failure, pore pressure dissipated with continued seismic excitation and the sample consolidated, resulting in partial shear-strength recovery. Once excess pore-water pressures had dissipated, deformation continued in a critical effective stress state with no further change in volume. Remoulded and weaker samples, however, did not liquefy, and instead immediately reduced in volume with an accompanying slower and more sustained increase in pore pressure as the sample consolidated. Thereafter excess pressures dissipated and deformation continued at a critical state. The complex behaviour explained why, despite exceptionally strong ground shaking, there was only limited displacement and lack of run-out: dynamic liquefaction was unlikely to occur in the freely draining slopes. Dynamic liquefaction however remained a plausible mechanism to explain loess failure in some of the low-angle toe slopes, where a permanent water table was present in the loess

Observation of a ppb mass threshoud enhancement in \psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p}) decay

The decay channel $\psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p})$ is studied using a sample of $1.06\times 10^8$ $\psi^\prime$ events collected by the BESIII experiment at BEPCII. A strong enhancement at threshold is observed in the $p\bar{p}$ invariant mass spectrum. The enhancement can be fit with an $S$-wave Breit-Wigner resonance function with a resulting peak mass of $M=1861^{+6}_{-13} {\rm (stat)}^{+7}_{-26} {\rm (syst)} {\rm MeV/}c^2$ and a narrow width that is $\Gamma<38 {\rm MeV/}c^2$ at the 90% confidence level. These results are consistent with published BESII results. These mass and width values do not match with those of any known meson resonance.Comment: 5 pages, 3 figures, submitted to Chinese Physics

Comparison of Artificial Neural Network and Logistic Regression Models for Predicting In-Hospital Mortality after Primary Liver Cancer Surgery

BACKGROUND: Since most published articles comparing the performance of artificial neural network (ANN) models and logistic regression (LR) models for predicting hepatocellular carcinoma (HCC) outcomes used only a single dataset, the essential issue of internal validity (reproducibility) of the models has not been addressed. The study purposes to validate the use of ANN model for predicting in-hospital mortality in HCC surgery patients in Taiwan and to compare the predictive accuracy of ANN with that of LR model. METHODOLOGY/PRINCIPAL FINDINGS: Patients who underwent a HCC surgery during the period from 1998 to 2009 were included in the study. This study retrospectively compared 1,000 pairs of LR and ANN models based on initial clinical data for 22,926 HCC surgery patients. For each pair of ANN and LR models, the area under the receiver operating characteristic (AUROC) curves, Hosmer-Lemeshow (H-L) statistics and accuracy rate were calculated and compared using paired T-tests. A global sensitivity analysis was also performed to assess the relative significance of input parameters in the system model and the relative importance of variables. Compared to the LR models, the ANN models had a better accuracy rate in 97.28% of cases, a better H-L statistic in 41.18% of cases, and a better AUROC curve in 84.67% of cases. Surgeon volume was the most influential (sensitive) parameter affecting in-hospital mortality followed by age and lengths of stay. CONCLUSIONS/SIGNIFICANCE: In comparison with the conventional LR model, the ANN model in the study was more accurate in predicting in-hospital mortality and had higher overall performance indices. Further studies of this model may consider the effect of a more detailed database that includes complications and clinical examination findings as well as more detailed outcome data

Genome-wide profiling of G protein-coupled receptors in cerebellar granule neurons using high-throughput, real-time PCR

<p>Abstract</p> <p>Background</p> <p>G protein-coupled receptors (GPCRs) are major players in cell communication, regulate a whole range of physiological functions during development and throughout adult life, are affected in numerous pathological situations, and constitute so far the largest class of drugable targets for human diseases. The corresponding genes are usually expressed at low levels, making accurate, genome-wide quantification of their expression levels a challenging task using microarrays.</p> <p>Results</p> <p>We first draw an inventory of all endo-GPCRs encoded in the murine genome. To profile GPCRs genome-wide accurately, sensitively, comprehensively, and cost-effectively, we designed and validated a collection of primers that we used in quantitative RT-PCR experiments. We experimentally validated a statistical approach to analyze genome-wide, real-time PCR data. To illustrate the usefulness of this approach, we determined the repertoire of GPCRs expressed in cerebellar granule neurons and neuroblasts during postnatal development.</p> <p>Conclusions</p> <p>We identified tens of GPCRs that were not detected previously in this cell type; these GPCRs represent novel candidate players in the development and survival of cerebellar granule neurons. The sequences of primers used in this study are freely available to those interested in quantifying GPCR expression comprehensively.</p

Studying user income through language, behaviour and affect in social media

Automatically inferring user demographics from social media posts is useful for both social science research and a range of downstream applications in marketing and politics. We present the first extensive study where user behaviour on Twitter is used to build a predictive model of income. We apply non-linear methods for regression, i.e. Gaussian Processes, achieving strong correlation between predicted and actual user income. This allows us to shed light on the factors that characterise income on Twitter and analyse their interplay with user emotions and sentiment, perceived psycho-demographics and language use expressed through the topics of their posts. Our analysis uncovers correlations between different feature categories and income, some of which reflect common belief e.g. higher perceived education and intelligence indicates higher earnings, known differences e.g. gender and age differences, however, others show novel findings e.g. higher income users express more fear and anger, whereas lower income users express more of the time emotion and opinions