Electrocatalysis in confined space

The complex interplay of restricted mass transport leading to local accumulation or depletion of educts, intermediates, products, counterions and co-ions influences the reactions at the active sites of electrocatalysts when electrodes are rough, three-dimensionally mesoporous or nanoporous. This influence is important with regard to activity, and even more to selectivity, of electrocatalytic reactions. The underlying principles are discussed based on the growing awareness of these considerations over recent years

A thermodynamic approach to designing structure-free combinatorial DNA word sets

An algorithm is presented for the generation of sets of non-interacting DNA sequences, employing existing thermodynamic models for the prediction of duplex stabilities and secondary structures. A DNA ‘word’ structure is employed in which individual DNA ‘words’ of a given length (e.g. 12mer and 16mer) may be concatenated into longer sequences (e.g. four tandem words and six tandem words). This approach, where multiple word variants are used at each tandem word position, allows very large sets of non-interacting DNA strands to be assembled from combinations of the individual words. Word sets were generated and their figures of merit are compared to sets as described previously in the literature (e.g. 4, 8, 12, 15 and 16mer). The predicted hybridization behavior was experimentally verified on selected members of the sets using standard UV hyperchromism measurements of duplex melting temperatures (T(m)s). Additional experimental validation was obtained by using the sequences in formulating and solving a small example of a DNA computing problem

Combining Nanoconfinement in Ag Core/Porous Cu Shell Nanoparticles with Gas Diffusion Electrodes for Improved Electrocatalytic Carbon Dioxide Reduction

Bimetallic silver-copper electrocatalysts are promising materials for electrochemical CO2 reduction reaction (CO2RR) to fuels and multi-carbon molecules. Here, we combine Ag core/porous Cu shell particles, which entrap reaction intermediates and thus facilitate the formation of C2+ products at low overpotentials, with gas diffusion electrodes (GDE). Mass transport plays a crucial role in the product selectivity in CO2RR. Conventional H-cell configurations suffer from limited CO2 diffusion to the reaction zone, thus decreasing the rate of the CO2RR. In contrast, in the case of GDE-based cells, the CO2RR takes place under enhanced mass transport conditions. Hence, investigation of the Ag core/porous Cu shell particles at the same potentials under different mass transport regimes reveals: (i) a variation of product distribution including C3 products, and (ii) a significant change in the local OH- activity under operation

Is Cu instability during the CO<inf>2</inf>reduction reaction governed by the applied potential or the local CO concentration?

Cu-based catalysts have shown structural instability during the electrochemical CO2reduction reaction (CO2RR). However, studies on monometallic Cu catalysts do not allow a nuanced differentiation between the contribution of the applied potential and the local concentration of CO as the reaction intermediate since both are inevitably linked. We first use bimetallic Ag-core/porous Cu-shell nanoparticles, which utilise nanoconfinement to generate high local CO concentrations at the Ag core at potentials at which the Cu shell is still inactive for the CO2RR. Usingoperandoliquid cell TEM in combination withex situTEM, we can unequivocally confirm that the local CO concentration is the main source for the Cu instability. The local CO concentration is then modulated by replacing the Ag-core with a Pd-core which further confirms the role of high local CO concentrations. Product quantification during CO2RR reveals an inherent trade-off between stability, selectivity and activity in both systems

Synthesis and characterization of ZnO nanopowder by non-basic

Nanocrystalline ZnO particles were prepared from methanolic solutions of zinc acetate dihydrate without using base such as NaOH or LiOH through a colloid process carried out at a low temperature of 60 o C. The precipitate obtained after 12-72h contained ZnO, covered with polymeric species of zinc hydroxo acetate. The reaction course was studied by mass spectrometry means. To complete the hydrolysis process, up to pure ZnO, it was necessarily to reflux the white precipitate separate from methanolic solution, in water at 80 o C. We found that reaction time in the presence of methanol primarily influenced the size of the particles, while the reaction time in the presence of water mainly influenced the ZnO purity

RNA secondary structure prediction from multi-aligned sequences

It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.Comment: A preprint of an invited review manuscript that will be published in a chapter of the book `Methods in Molecular Biology'. Note that this version of the manuscript may differ from the published versio

Free energy estimation of short DNA duplex hybridizations

<p>Abstract</p> <p>Background</p> <p>Estimation of DNA duplex hybridization free energy is widely used for predicting cross-hybridizations in DNA computing and microarray experiments. A number of software programs based on different methods and parametrizations are available for the theoretical estimation of duplex free energies. However, significant differences in free energy values are sometimes observed among estimations obtained with various methods, thus being difficult to decide what value is the accurate one.</p> <p>Results</p> <p>We present in this study a quantitative comparison of the similarities and differences among four published DNA/DNA duplex free energy calculation methods and an extended Nearest-Neighbour Model for perfect matches based on triplet interactions. The comparison was performed on a benchmark data set with 695 pairs of short oligos that we collected and manually curated from 29 publications. Sequence lengths range from 4 to 30 nucleotides and span a large GC-content percentage range. For perfect matches, we propose an extension of the Nearest-Neighbour Model that matches or exceeds the performance of the existing ones, both in terms of correlations and root mean squared errors. The proposed model was trained on experimental data with temperature, sodium and sequence concentration characteristics that span a wide range of values, thus conferring the model a higher power of generalization when used for free energy estimations of DNA duplexes under non-standard experimental conditions.</p> <p>Conclusions</p> <p>Based on our preliminary results, we conclude that no statistically significant differences exist among free energy approximations obtained with 4 publicly available and widely used programs, when benchmarked against a collection of 695 pairs of short oligos collected and curated by the authors of this work based on 29 publications. The extended Nearest-Neighbour Model based on triplet interactions presented in this work is capable of performing accurate estimations of free energies for perfect match duplexes under both standard and non-standard experimental conditions and may serve as a baseline for further developments in this area of research.</p

SYNTHESIS, MECHANICAL AND STRUCTURAL PROPERTIES AND BIOLOGICAL ACTIVITY OF SOME NANOSTRUCTURED BONE SCAFFOLDS

Three new biodegradable and bioactive scaffolds based on hydroxyapatite (HAP), β tricalcium phosphate (β-TCP) and a composite HAP+β-TCP are studied in this paper. Their mechanical, structural properties and long term behaviour in simulated body fluid (SBF) were analysed. Also, these scaffolds were subjected to in vitro evaluation of cell behaviour. The open porosity from 16.41% to 34.26% it resulted. The compression resistance (2-3 MPa) is very close to the cancellous bone. It resulted that simultaneously with the dissolution, on the surface of materials were deposited calcium and phosphorous ions, namely, these materials are favourable to the bone formation. The scaffold morphology showed a dense polycrystalline structure with cavities (porosity), junctions and interconnections that can facilitate the cell proliferation. SEM micrographs revealed that, after 2100 immersion hours in SBF, the scaffolds coated with a layer of micro-sized grains. The in vitro results proved that hFOB 1.19 cells are able to attach, migrate in the interior of scaffolds, proliferate, synthesize and extracellularly assemble ECM molecules

Prediction of RNA secondary structure by maximizing pseudo-expected accuracy

<p>Abstract</p> <p>Background</p> <p>Recent studies have revealed the importance of considering the entire distribution of possible secondary structures in RNA secondary structure predictions; therefore, a new type of estimator is proposed including the maximum expected accuracy (MEA) estimator. The MEA-based estimators have been designed to maximize the expected accuracy of the base-pairs and have achieved the highest level of accuracy. Those methods, however, do not give the single best prediction of the structure, but employ parameters to control the trade-off between the sensitivity and the positive predictive value (PPV). It is unclear what parameter value we should use, and even the well-trained default parameter value does not, in general, give the best result in popular accuracy measures to each RNA sequence.</p> <p>Results</p> <p>Instead of using the expected values of the popular accuracy measures for RNA secondary structure prediction, which is difficult to be calculated, the <it>pseudo</it>-expected accuracy, which can easily be computed from base-pairing probabilities, is introduced. It is shown that the pseudo-expected accuracy is a good approximation in terms of sensitivity, PPV, MCC, or F-score. The pseudo-expected accuracy can be approximately maximized for each RNA sequence by stochastic sampling. It is also shown that well-balanced secondary structures between sensitivity and PPV can be predicted with a small computational overhead by combining the pseudo-expected accuracy of MCC or F-score with the γ-centroid estimator.</p> <p>Conclusions</p> <p>This study gives not only a method for predicting the secondary structure that balances between sensitivity and PPV, but also a general method for approximately maximizing the (pseudo-)expected accuracy with respect to various evaluation measures including MCC and F-score.</p