Polymer-stabilized blue phase liquid crystal with a negative Kerr constant

A polymer-stabilized blue-phase liquid crystal (BPLC) with a negative Kerr constant is reported. In a voltage-on state, the double-twist BPLC molecules within the lattice cylinders are reoriented perpendicular to the applied electric field because of their negative dielectric anisotropy. As a result, the induced birefringence has a negative value, which leads to a negative Kerr constant. The negative sign of Kerr constant is experimentally validated by using a quarter-wave plate and a vertical field switching cell. Such a BPLC shows a negligible (similar to 1%) hysteresis and fast response time (similar to 1ms) at the room temperature, although its Kerr constant is relatively small because the employed host has a small Delta epsilon

Genomic analysis of oesophageal squamous-cell carcinoma identifies alcohol drinking-related mutation signature and genomic alterations

Approximately half of the world's 500,000 new oesophageal squamous-cell carcinoma (ESCC) cases each year occur in China. Here, we show whole-genome sequencing of DNA and RNA in 94 Chinese individuals with ESCC. We identify six mutational signatures (E1–E6), and Signature E4 is unique in ESCC linked to alcohol intake and genetic variants in alcohol-metabolizing enzymes. We discover significantly recurrent mutations in 20 protein-coding genes, 4 long non-coding RNAs and 10 untranslational regions. Functional analyses show six genes that have recurrent copy-number variants in three squamous-cell carcinomas (oesophageal, head and neck and lung) significantly promote cancer cell proliferation, migration and invasion. The most frequently affected genes by structural variation are LRP1B and TTC28. The aberrant cell cycle and PI3K-AKT pathways seem critical in ESCC. These results establish a comprehensive genomic landscape of ESCC and provide potential targets for precision treatment and prevention of the cancer

Leakage current simulations of Low Gain Avalanche Diode with improved Radiation Damage Modeling

We report precise TCAD simulations of IHEP-IME-v1 Low Gain Avalanche Diode (LGAD) calibrated by secondary ion mass spectroscopy (SIMS). Our setup allows us to evaluate the leakage current, capacitance, and breakdown voltage of LGAD, which agree with measurements' results before irradiation. And we propose an improved LGAD Radiation Damage Model (LRDM) which combines local acceptor removal with global deep energy levels. The LRDM is applied to the IHEP-IME-v1 LGAD and able to predict the leakage current well at -30 $^{\circ}$C after an irradiation fluence of $\Phi_{eq}=2.5 \times 10^{15} ~n_{eq}/cm^{2}$. The charge collection efficiency (CCE) is under development

Integrative analysis of gene expression profiles reveals specific signaling pathways associated with pancreatic duct adenocarcinoma

Abstract Background Pancreatic duct adenocarcinoma (PDAC) remains a major health problem because conventional cancer treatments are relatively ineffective against it. Microarray studies have linked many genes to pancreatic cancer, but the available data have not been extensively mined for potential insights into PDAC. This study attempted to identify PDAC-associated genes and signaling pathways based on six microarray-based profiles of gene expression in pancreatic cancer deposited in the gene expression omnibus database. Methods Pathway network methods were used to analyze core pathways in six publicly available pancreatic cancer gene (GSE71989, GSE15471, GSE16515, GSE32676, GSE41368 and GSE28735) expression profiles. Genes potentially linked to PDAC were assessed for potential impact on survival time based on data in The Cancer Genome Atlas and International Cancer Genome Consortium databases, and the expression of one candidate gene (CKS2) and its association with survival was examined in 102 patients with PDAC from our hospital. Effects of CKS2 knockdown were explored in the PDAC cell lines BxPC-3 and CFPAC-1. Results The KEGG signaling pathway called “pathway in cancer” may play an important role in pancreatic cancer development and progression. Five genes (BIRC5, CKS2, ITGA3, ITGA6 and RALA) in this pathway were significantly associated with survival time in patients with PDAC. CKS2 was overexpressed in PDAC samples from our hospital, and higher CKS2 expression in these patients was associated with shorter survival time. CKS2 knockdown substantially inhibited PDAC cell proliferation in vitro. Conclusions Analysis integrating existing microarray datasets allowed identification of the “pathway in cancer” as an important signaling pathway in PDAC. This integrative approach may be powerful for identifying genes and pathways involved in cancer

CASB: a concanavalin A‐based sample barcoding strategy for single‐cell sequencing

Abstract Sample multiplexing facilitates single‐cell sequencing by reducing costs, revealing subtle difference between similar samples, and identifying artifacts such as cell doublets. However, universal and cost‐effective strategies are rather limited. Here, we reported a concanavalin A‐based sample barcoding strategy (CASB), which could be followed by both single‐cell mRNA and ATAC (assay for transposase‐accessible chromatin) sequencing techniques. The method involves minimal sample processing, thereby preserving intact transcriptomic or epigenomic patterns. We demonstrated its high labeling efficiency, high accuracy in assigning cells/nuclei to samples regardless of cell type and genetic background, and high sensitivity in detecting doublets by three applications: 1) CASB followed by scRNA‐seq to track the transcriptomic dynamics of a cancer cell line perturbed by multiple drugs, which revealed compound‐specific heterogeneous response; 2) CASB together with both snATAC‐seq and scRNA‐seq to illustrate the IFN‐γ‐mediated dynamic changes on epigenome and transcriptome profile, which identified the transcription factor underlying heterogeneous IFN‐γ response; and 3) combinatorial indexing by CASB, which demonstrated its high scalability

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Additional file 5: Table S5. Hazard ratio (HR) of death for genes in the pathway in cancer that are differentially expressed in pancreatic cancer, based on data in two databases

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Additional file 9: Figure S3. CKS2 expression across multiple types of cancer and corresponding normal tissues. The numbers of studies reporting up- or down-regulation is indicated, respectively, in red or blue boxes. Color intensity reflects the best gene rank percentile for analyses within the box. The following settings were used for the analysis: P=0.05, fold change=all, gene rank=all, and data type=mRNA ( http://www.oncomine.org )

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Additional file 8: Figure S2. CKS2 expression in different types of cancer cell lines, based on data from the CCLE database ( https://portals.broadinstitute.org/ccle/home )

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Additional file 6: Table S6. Genes associated with CKS2 expression level in pancreatic cancer tissues, based on data in The Cancer Genome Atlas

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Additional file 2: Table S2. Short interfering RNA (siRNA) sequences used in this study