Using Linguistic Features to Estimate Suicide Probability of Chinese Microblog Users

If people with high risk of suicide can be identified through social media like microblog, it is possible to implement an active intervention system to save their lives. Based on this motivation, the current study administered the Suicide Probability Scale(SPS) to 1041 weibo users at Sina Weibo, which is a leading microblog service provider in China. Two NLP (Natural Language Processing) methods, the Chinese edition of Linguistic Inquiry and Word Count (LIWC) lexicon and Latent Dirichlet Allocation (LDA), are used to extract linguistic features from the Sina Weibo data. We trained predicting models by machine learning algorithm based on these two types of features, to estimate suicide probability based on linguistic features. The experiment results indicate that LDA can find topics that relate to suicide probability, and improve the performance of prediction. Our study adds value in prediction of suicidal probability of social network users with their behaviors

Viral integration drives multifocal HCC during the occult HBV infection

© 2019 The Author(s). Background & Aims: Although the prognosis of patients with occult hepatitis B virus (HBV) infection (OBI) is usually benign, a small portion may undergo cirrhosis and subsequently hepatocellular carcinoma (HCC). We studied the mechanism of life-long Integration of virus DNA into OBI host's genome, of which may induce hepatocyte transformation. Methods: We applied HBV capture sequencing on single cells from an OBI patient who, developed multiple HCC tumors and underwent liver resection in May 2013 at Tongji Hospital in China. Despite with the undetectable virus DNA in serum, we determined the pattern of viral integration in tumor cells and adjacent non-tumor cells and obtained the details of the viral arrangement in host genome, and furthermore the HBV integrated region in cancer genome. Results: HBV captured sequencing of tissues and individual cells revealed that samples from multiple tumors shared two viral integration sites that could affect three host genes, including CSMD2 on chr1 and MED30/EXT1 on chr8. Whole genome sequencing further indicated one hybrid chromosome formed by HBV integrations between chr1 and chr8 that was shared by multiple tumors. Additional 50 poorly differentiated liver tumors and the paired adjacent non-tumors were evaluated and functional studies suggested up-regulated EXT1 expression promoted HCC growth. We further observed that the most somatic mutations within the tumor cell genome were common among the multiple tumors, suggesting that HBV associated, multifocal HCC is monoclonal in origin. Conclusion: Through analyzing the HBV integration sites in multifocal HCC, our data suggested that the tumor cells were monoclonal in origin and formed in the absence of active viral replication, whereas the affected host genes may subsequently contribute to carcinogenesis

Nanofluids Research: Key Issues

Nanofluids are a new class of fluids engineered by dispersing nanometer-size structures (particles, fibers, tubes, droplets) in base fluids. The very essence of nanofluids research and development is to enhance fluid macroscopic and megascale properties such as thermal conductivity through manipulating microscopic physics (structures, properties and activities). Therefore, the success of nanofluid technology depends very much on how well we can address issues like effective means of microscale manipulation, interplays among physics at different scales and optimization of microscale physics for the optimal megascale properties. In this work, we take heat-conduction nanofluids as examples to review methodologies available to effectively tackle these key but difficult problems and identify the future research needs as well. The reviewed techniques include nanofluids synthesis through liquid-phase chemical reactions in continuous-flow microfluidic microreactors, scaling-up by the volume averaging and constructal design with the constructal theory. The identified areas of future research contain microfluidic nanofluids, thermal waves and constructal nanofluids

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

MicroRNA-21 regulates breast cancer invasion partly by targeting tissue inhibitor of metalloproteinase 3 expression

<p>Abstract</p> <p>Background</p> <p>MicroRNAs are non-coding RNA molecules that posttranscriptionally regulate expression of target genes and have been implicated in the progress of cancer proliferation, differentiation and apoptosis. The aim of this study was to determine whether microRNA-21 (miR-21), a specific microRNA implicated in multiple aspects of carcinogenesis, impacts breast cancer invasion by regulating the tissue inhibitor of metalloproteinase 3 (TIMP3) gene.</p> <p>Methods</p> <p>miR-21 expression was investigated in 32 matched breast cancer and normal breast tissues, and in four human breast cancer cell lines, by Taqman quantitative real-time PCR. Cell invasive ability was determined by matrigel invasion assay in vitro, in cells transfected with miR-21 or anti-miR-21 oligonucleotides. In addition, the regulation of tissue inhibitor of metalloproteinase 3 (TIMP3) by miR-21 was evaluated by western blotting and luciferase assays.</p> <p>Results</p> <p>Of the 32 paired samples analyzed, 25 breast cancer tissues displayed overexpression of miR-21 in comparison with matched normal breast epithelium. Additionally, incidence of lymph node metastasis closely correlated with miR-21 expression, suggesting a role for miR-21 in metastasis. Similarly, each of the four breast cancer cell lines analyzed overexpressed miR-21, to varied levels. Further, cells transfected with miR-21 showed significantly increased matrigel invasion compared with control cells, whereas transfection with anti-miR-21 significantly decreased cell invasion. Evaluation of TIMP3 protein levels, a peptidase involved in extarcellular matrix degredation, inversely correlated with miR-21 expression.</p> <p>Conclusion</p> <p>As knockdown of miR-21 increased TIMP3 protein expression and luciferase reporter activity, our data suggests that miR-21 could promote invasion in breast cancer cells via its regulation of TIMP3.</p

Multifunctional graphene woven fabrics

Tailoring and assembling graphene into functional macrostructures with well-defined configuration are key for many promising applications. We report on a graphene-based woven fabric (GWF) prepared by interlacing two sets of graphene micron-ribbons where the ribbons pass each other essentially at right angles. By using a woven copper mesh as the template, the GWF grown from chemical vapour deposition retains the network configuration of the copper mesh. Embedded into polymer matrices, it has significant flexibility and strength gains compared with CVD grown graphene films. The GWFs display both good dimensional stability in both the warp and the weft directions and the combination of film transparency and conductivity could be optimized by tuning the ribbon packing density. The GWF creates a platform to integrate a large variety of applications, e.g., composites, strain sensors and solar cells, by taking advantages of the special structure and properties of graphene

High Accordance in Prognosis Prediction of Colorectal Cancer across Independent Datasets by Multi-Gene Module Expression Profiles

A considerable portion of patients with colorectal cancer have a high risk of disease recurrence after surgery. These patients can be identified by analyzing the expression profiles of signature genes in tumors. But there is no consensus on which genes should be used and the performance of specific set of signature genes varies greatly with different datasets, impeding their implementation in the routine clinical application. Instead of using individual genes, here we identified functional multi-gene modules with significant expression changes between recurrent and recurrence-free tumors, used them as the signatures for predicting colorectal cancer recurrence in multiple datasets that were collected independently and profiled on different microarray platforms. The multi-gene modules we identified have a significant enrichment of known genes and biological processes relevant to cancer development, including genes from the chemokine pathway. Most strikingly, they recruited a significant enrichment of somatic mutations found in colorectal cancer. These results confirmed the functional relevance of these modules for colorectal cancer development. Further, these functional modules from different datasets overlapped significantly. Finally, we demonstrated that, leveraging above information of these modules, our module based classifier avoided arbitrary fitting the classifier function and screening the signatures using the training data, and achieved more consistency in prognosis prediction across three independent datasets, which holds even using very small training sets of tumors