The rates for the MISO channel, with <i>T</i> = 4, <i>P</i> = 10, <i>σ</i>² = 1, <i>ϵ</i> = 10⁻⁶.

The rates for the MISO channel, with T = 4, P = 10, σ2 = 1, ϵ = 10−6.</p

The rates for the MIMO channel, with <i>T</i> = 4, <i>M</i> = 4, <i>P</i> = 10, <i>σ</i>² = 1, <i>ϵ</i> = 10⁻⁶.

The rates for the MIMO channel, with T = 4, M = 4, P = 10, σ2 = 1, ϵ = 10−6.</p

Notations.

Ultra-reliable low-latency communication (URLLC) is a key technology in future wireless communications, and finite blocklength (FBL) coding is the core of the URLLC. In this paper, FBL coding schemes for the wireless multi-antenna channels are proposed, which are based on the classical Schalkwijk-Kailath scheme for the point-to-point additive white Gaussian noise channel with noiseless feedback. Simulation examples show that the proposed feedback-based schemes almost approach the corresponding channel capacities.</div

The rates for the SIMO channel, with <i>M</i> = 4, <i>P</i> = 10, <i>σ</i>² = 1, <i>ϵ</i> = 10⁻⁶.

The rates for the SIMO channel, with M = 4, P = 10, σ2 = 1, ϵ = 10−6.</p

The SISO/SIMO/MISO/MIMO systems (<i>T</i> ≥ 1, <i>M</i> ≥ 1) with noiseless feedback.

The SISO/SIMO/MISO/MIMO systems (T ≥ 1, M ≥ 1) with noiseless feedback.</p

The rates for the SISO channel, with <i>P</i> = 10, <i>σ</i>² = 1, <i>ϵ</i> = 10⁻⁶.

The rates for the SISO channel, with P = 10, σ2 = 1, ϵ = 10−6.</p

Data_Sheet_1.XLSX

<p>We previously identified microRNA (miRNA) from Nosema ceranae and found that knockdowns of transcripts for the parasite protein Dicer greatly reduce parasite reproduction. In order to study parasitic miRNA functions and identify candidate target genes, we fed honey bees infected with N. ceranae with small interfering RNA (siRNA) targeting the N. ceranae gene Dicer. We then deep-sequenced honey bee and N. ceranae miRNAs daily across a full 6-day proliferation cycle. We found seven honey bee and five N. ceranae miRNAs that were significantly differently expressed between the infection and siRNA-Dicer groups. N. ceranae miRNA showed potentially strong impacts on the N. ceranae transcriptome, where over 79% of the total protein coding genes were significantly correlated with one or more miRNAs. N. ceranae miRNAs also can regulate honey bee metabolism and immune response, given parasitic miRNAs were secreted into the cytoplasm. Our results suggest that N. ceranae miRNAs regulate both parasite and host gene expression, providing new insights for microsporidia parasitism evolution.</p

A D-Optimal Design for Estimation of Parameters of an Exponential-Linear Growth Curve of Nanostructures

<div><p>We consider the problem of determining an optimal experimental design for estimation of parameters of a class of complex curves characterizing nanowire growth that is partially exponential and partially linear. Locally D-optimal designs for some of the models belonging to this class are obtained by using a geometric approach. Further, a Bayesian sequential algorithm is proposed for obtaining D-optimal designs for models with a closed-form solution, and for obtaining efficient designs in situations where theoretical results cannot be obtained. The advantages of the proposed algorithm over traditional approaches adopted in recently reported nanoexperiments are demonstrated using Monte Carlo simulations. The computer code implementing the sequential algorithm is available as supplementary materials.</p></div

Presentation_1_Circular RNA Signature Predicts Gemcitabine Resistance of Pancreatic Ductal Adenocarcinoma.PDF

<p>Gemcitabine resistance is currently the main problem of chemotherapy for advanced pancreatic cancer patients. The resistance is thought to be caused by altered drug metabolism or reduced apoptosis of cancer cells. However, the underlying mechanism of Gemcitabine resistance in pancreatic cancer remains unclear. In this study, we established Gemcitabine resistant PANC-1 (PANC-1-GR) cell lines and compared the circular RNAs (circRNAs) profiles between PANC-1 cells and PANC-1-GR cells by RNA sequencing. Differentially expressed circRNAs were demonstrated using scatter plot and cluster heatmap analysis. Gene ontology and pathway analysis were performed to systemically map the genes which are functionally associated to those differentially expressed circRNAs identified from our data. The expression of the differentially expressed circRNAs picked up by RNAseq in PANC-1-GR cells was further validated by qRT-PCR and two circRNAs were eventually identified as the most distinct targets. Consistently, by analyzing plasma samples form pancreatic ductal adenocarcinoma (PDAC) patients, the two circRNAs showed more significant expression in the Gemcitabine non-responsive patients than the responsive ones. In addition, we found that silencing of the two circRNAs could restore the sensitivity of PANC-1-GR cells to Gemcitabine treatment, while over-expression of them could increase the resistance of normal PANC-1 and MIA PACA-2 cells, suggesting that they might serve as drug targets for Gemcitabine resistance. Furthermore, the miRNA interaction networks were also explored based on the correlation analysis of the target microRNAs of these two circRNAs. In conclusion, we successfully established new PANC-1-GR cells, systemically characterized the circRNA and miRNA profiles, and identified two circRNAs as novel biomarkers and potential therapeutic targets for Gemcitabine non-responsive PDAC patients.</p

X‑ray Crystal Structure of Phosphodiesterase 2 in Complex with a Highly Selective, Nanomolar Inhibitor Reveals a Binding-Induced Pocket Important for Selectivity

To better understand the structural origins of inhibitor selectivity of human phosphodieasterase families (PDEs 1–11), here we report the X-ray crystal structure of PDE2 in complex with a highly selective, nanomolar inhibitor (BAY60-7550) at 1.9 Å resolution, and the structure of apo PDE2 at 2.0 Å resolution. The crystal structures reveal that the inhibitor binds to the PDE2 active site by using not only the conserved glutamine-switch mechanism for substrate binding, but also a binding-induced, hydrophobic pocket that was not reported previously. <i>In silico</i> affinity profiling by molecular docking indicates that the inhibitor binding to this pocket contributes significantly to the binding affinity and thereby improves the inhibitor selectivity for PDE2. Our results highlight a structure-based design strategy that exploits the potential binding-induced pockets to achieve higher selectivity in the PDE inhibitor development