Selective reporting: a half signalling load algorithm for distributed sensing

Spectrum sensing is a powerful tool of the cognitive cycle to help circumvent the apparent spectrum scarcity faced by wireless transmission systems. To overcome the challenging issues faced by the localized sensing, multiple cognitive radios can cooperate to explore the multiuser diversity and generate a more reliable decision on the presence of a signal in the frequencies of interest. In such a cooperative sensing scenario, a common reporting channel is needed for the transmission of the information of each element. As the number of elements that participate in the sensing operation increases, so does the bandwidth demanded for the reporting channel, quickly becoming the limiting factor in this scenario. To tackle the issue of reducing the sensing report overhead, this paper introduces a new cooperative sensing scheme that introduces silence periods in the reporting and, relying on information theory principles, explores the information present in these periods to reduce by 50% the sensing reporting overhead while maintaining the same performance of standard reporting schemes. Numerical and experimental results confirm the theoretical analysis and show the predicted reduction in reporting overhead and performance preservation

Engineering cooperative tecto–RNA complexes having programmable stoichiometries

High affinity and specificity RNA–RNA binding interfaces can be constructed by combining pairs of GNRA loop/loop–receptor interaction motifs. These interactions can be fused using flexible four-way junction motifs to create divalent, self-assembling scaffolding units (‘tecto-RNA’) that have favorable properties for nanomedicine and other applications. We describe the design and directed assembly of tecto-RNA units ranging from closed, cooperatively assembling ring-shaped complexes of programmable stoichiometries (dimers, trimers and tetramers) to open multimeric structures. The novelty of this work is that tuning of the stoichiometries of self-assembled complexes is achieved by precise positioning of the interaction motifs in the monomer units rather than changing their binding specificities. Structure-probing and transmission electron microscopy studies as well as thermodynamic analysis support formation of closed cooperative complexes that are highly resistant to nuclease digestion. The present designs provide two helical arms per RNA monomer for further functionalization aims

Conjugation of a Ru(II) Arene Complex to Neomycin or to Guanidinoneomycin Leads to Compounds with Differential Cytotoxicities and Accumulation between Cancer and Normal Cells

A straightforward methodology for the synthesis of conjugates between a cytotoxic organometallic ruthenium(II) complex and amino- and guanidinoglycosides, as potential RNA-targeted anticancer compounds, is described. Under microwave irradiation, the imidazole ligand incorporated on the aminoglycoside moiety (neamine or neomycin) was found to replace one triphenylphosphine ligand from the ruthenium precursor [(η6-p-cym)RuCl(PPh3)2]+, allowing the assembly of the target conjugates. The guanidinylated analogue was easily prepared from the neomycin-ruthenium conjugate by reaction with N,N′-di-Boc-N″-triflylguanidine, a powerful guanidinylating reagent that was compatible with the integrity of the metal complex. All conjugates were purified by semipreparative high-performance liquid chromatography (HPLC) and characterized by electrospray ionization (ESI) and matrix-assisted laser desorption-ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) and NMR spectroscopy. The cytotoxicity of the compounds was tested in MCF-7 (breast) and DU-145 (prostate) human cancer cells, as well as in the normal HEK293 (Human Embryonic Kidney) cell line, revealing a dependence on the nature of the glycoside moiety and the type of cell (cancer or healthy). Indeed, the neomycin-ruthenium conjugate (2) displayed moderate antiproliferative activity in both cancer cell lines (IC50 ≈ 80 μM), whereas the neamine conjugate (4) was inactive (IC50 ≈ 200 μM). However, the guanidinylated analogue of the neomycin-ruthenium conjugate (3) required much lower concentrations than the parent conjugate for equal effect (IC50 = 7.17 μM in DU-145 and IC50 = 11.33 μM in MCF-7). Although the same ranking in antiproliferative activity was found in the nontumorigenic cell line (3 2 > 4), IC50 values indicate that aminoglycoside-containing conjugates are about 2-fold more cytotoxic in normal cells (e.g., IC50 = 49.4 μM for 2) than in cancer cells, whereas an opposite tendency was found with the guanidinylated conjugate, since its cytotoxicity in the normal cell line (IC50 = 12.75 μM for 3) was similar or even lower than that found in MCF-7 and DU-145 cancer cell lines, respectively. Cell uptake studies performed by ICP-MS with conjugates 2 and 3 revealed that guanidinylation of the neomycin moiety had a positive effect on accumulation (about 3-fold higher in DU-145 and 4-fold higher in HEK293), which correlates well with the higher antiproliferative activity of 3. Interestingly, despite the slightly higher accumulation in the normal cell than in the cancer cell line (about 1.4-fold), guanidinoneomycin-ruthenium conjugate (3) was more cytotoxic to cancer cells (about 1.8-fold), whereas the opposite tendency applied for neomycin-ruthenium conjugate (2). Such differences in cytotoxic activity and cellular accumulation between cancer and normal cells open the way to the creation of more selective, less toxic anticancer metallodrugs by conjugating cytotoxic metal-based complexes such as ruthenium(II) arene derivatives to guanidinoglycosides

Synthesis of Janus compounds for the recognition of G-U mismatched nucleobase pairs

The design and synthesis of two Janus-type heterocycles with the capacity to simultaneously recognize guanine and uracyl in G-U mismatched pairs through complementary hydrogen bond pairing is described. Both compounds were conveniently functionalized with a carboxylic function and efficiently attached to a tripeptide sequence by using solid-phase methodologies. Ligands based on the derivatization of such Janus compounds with a small aminoglycoside, neamine, and its guanidinylated analogue have been synthesized, and their interaction with Tau RNA has been investigated by using several biophysical techniques, including UV-monitored melting curves, fluorescence titration experiments, and 1H NMR. The overall results indicated that Janus-neamine/guanidinoneamine showed some preference for the +3 mutated RNA sequence associated with the development of some tauopathies, although preliminary NMR studies have not confirmed binding to G-U pairs. Moreover, a good correlation has been found between the RNA binding affinity of such Janus-containing ligands and their ability to stabilize this secondary structure upon complexation

Conformational dynamics and internal friction in homopolymer globules: equilibrium vs. non-equilibrium simulations

We study the conformational dynamics within homopolymer globules by solvent-implicit Brownian dynamics simulations. A strong dependence of the internal chain dynamics on the Lennard-Jones cohesion strength ε and the globule size N [subscript G] is observed. We find two distinct dynamical regimes: a liquid-like regime (for ε ε[subscript s] with slow internal dynamics. The cohesion strength ε[subscript s] of this freezing transition depends on N G . Equilibrium simulations, where we investigate the diffusional chain dynamics within the globule, are compared with non-equilibrium simulations, where we unfold the globule by pulling the chain ends with prescribed velocity (encompassing low enough velocities so that the linear-response, viscous regime is reached). From both simulation protocols we derive the internal viscosity within the globule. In the liquid-like regime the internal friction increases continuously with ε and scales extensive in N [subscript G] . This suggests an internal friction scenario where the entire chain (or an extensive fraction thereof) takes part in conformational reorganization of the globular structure.American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowshi

Accurate classification of RNA structures using topological fingerprints

While RNAs are well known to possess complex structures, functionally similar RNAs often have little sequence similarity. While the exact size and spacing of base-paired regions vary, functionally similar RNAs have pronounced similarity in the arrangement, or topology, of base-paired stems. Furthermore, predicted RNA structures often lack pseudoknots (a crucial aspect of biological activity), and are only partially correct, or incomplete. A topological approach addresses all of these difficulties. In this work we describe each RNA structure as a graph that can be converted to a topological spectrum (RNA fingerprint). The set of subgraphs in an RNA structure, its RNA fingerprint, can be compared with the fingerprints of other RNA structures to identify and correctly classify functionally related RNAs. Topologically similar RNAs can be identified even when a large fraction, up to 30%, of the stems are omitted, indicating that highly accurate structures are not necessary. We investigate the performance of the RNA fingerprint approach on a set of eight highly curated RNA families, with diverse sizes and functions, containing pseudoknots, and with little sequence similarity–an especially difficult test set. In spite of the difficult test set, the RNA fingerprint approach is very successful (ROC AUC \u3e 0.95). Due to the inclusion of pseudoknots, the RNA fingerprint approach both covers a wider range of possible structures than methods based only on secondary structure, and its tolerance for incomplete structures suggests that it can be applied even to predicted structures. Source code is freely available at https://github.rcac.purdue.edu/mgribsko/XIOS_RNA_fingerprint

Approximate Bayesian computation reveals the importance of repeated measurements for parameterising cell-based models of growing tissues.

The growth and dynamics of epithelial tissues govern many morphogenetic processes in embryonic development. A recent quantitative transition in data acquisition, facilitated by advances in genetic and live-imaging techniques, is paving the way for new insights to these processes. Computational models can help us understand and interpret observations, and then make predictions for future experiments that can distinguish between hypothesised mechanisms. Increasingly, cell-based modelling approaches such as vertex models are being used to help understand the mechanics underlying epithelial morphogenesis. These models typically seek to reproduce qualitative phenomena, such as cell sorting or tissue buckling. However, it remains unclear to what extent quantitative data can be used to constrain these models so that they can then be used to make quantitative, experimentally testable predictions. To address this issue, we perform an in silico study to investigate whether vertex model parameters can be inferred from imaging data, and explore methods to quantify the uncertainty of such estimates. Our approach requires the use of summary statistics to estimate parameters. Here, we focus on summary statistics of cellular packing and of laser ablation experiments, as are commonly reported from imaging studies. We find that including data from repeated experiments is necessary to generate reliable parameter estimates that can facilitate quantitative model predictions