Graphene oxide decorated with gold enables efficient biophotovolatic cells incorporating photosystem I.

This paper describes the use of reduced graphene oxide decorated with gold nanoparticles as an efficient electron transfer layer for solid-state biophotovoltic cells containing photosystem I as the sole photo-active component. Together with polytyrosine-polyaniline as a hole transfer layer, this device architecture results in an open-circuit voltage of 0.3 V, a fill factor of 38% and a short-circuit current density of 5.6 mA cm-2 demonstrating good coupling between photosystem I and the electrodes. The best-performing device reached an external power conversion efficiency of 0.64%, the highest for any solid-state photosystem I-based photovoltaic device that has been reported to date. Our results demonstrate that the functionality of photosystem I in the non-natural environment of solid-state biophotovoltaic cells can be improved through the modification of electrodes with efficient charge-transfer layers. The combination of reduced graphene oxide with gold nanoparticles caused tailoring of the electronic structure and alignment of the energy levels while also increasing electrical conductivity. The decoration of graphene electrodes with gold nanoparticles is a generalizable approach for enhancing charge-transfer across interfaces, particularly when adjusting the levels of the active layer is not feasible, as is the case for photosystem I and other biological molecules.

Fullerenes Enhance Self-Assembly and Electron Injection of Photosystem I in Biophotovoltaic Devices.

This paper describes the fabrication of microfluidic devices with a focus on controlling the orientation of photosystem I (PSI) complexes, which directly affects the performance of biophotovoltaic devices by maximizing the efficiency of the extraction of electron/hole pairs from the complexes. The surface chemistry of the electrode on which the complexes assemble plays a critical role in their orientation. We compared the degree of orientation on self-assembled monolayers of phenyl-C61-butyric acid and a custom peptide on nanostructured gold electrodes. Biophotovoltaic devices fabricated with the C61 fulleroid exhibit significantly improved performance and reproducibility compared to those utilizing the peptide, yielding a 1.6-fold increase in efficiency. In addition, the C61-based devices were more stable under continuous illumination. Our findings show that fulleroids, which are well-known acceptor materials in organic photovoltaic devices, facilitate the extraction of electrons from PSI complexes without sacrificing control over the orientation of the complexes, highlighting this combination of traditional organic semiconductors with biomolecules as a viable approach to coopting natural photosynthetic systems for use in solar cells.

Chitosan-heparin nanoparticle coating on anodized NiTi for improvement of blood compatibility and biocompatibility.

The aim of this study was to simultaneously improve blood compatibility and corrosion resistance of nitinol via two-step process; anodizing and consequently coating with chitosans-heparin nanoparticles. Moreover, the role of these surface modification processes on the heparin release kinetic and blood compatibility was investigated. Finally, the interaction between human umbilical vein endothelial cells (HUVECs) and surface modified samples was investigated. Electrochemical characterization revealed that while Ni ions released from the anodized sample (9 ppb), chitosan-heparin nanoparticle coatings prohibited from Ni ion release form NiTi substrate. Moreover, the controlled release of heparin was found from chitosan-heparin nanoparticle coating deposited on the nanotubes, leading to significant improvement of blood compatibility. Finally, HUVECs were attached and proliferated on the chitosan-heparin nanoparticle coated samples confirming the cell compatibility of samples. In summary, results proved that two-step anodizing process and heparin release could promote both endothelial cell compatibility and blood compatibility to nitinol surface which might be appropriate for coronary stent application.

SECIMTools: a suite of metabolomics data analysis tools.

BACKGROUND: Metabolomics has the promise to transform the area of personalized medicine with the rapid development of high throughput technology for untargeted analysis of metabolites. Open access, easy to use, analytic tools that are broadly accessible to the biological community need to be developed. While technology used in metabolomics varies, most metabolomics studies have a set of features identified. Galaxy is an open access platform that enables scientists at all levels to interact with big data. Galaxy promotes reproducibility by saving histories and enabling the sharing workflows among scientists. RESULTS: SECIMTools (SouthEast Center for Integrated Metabolomics) is a set of Python applications that are available both as standalone tools and wrapped for use in Galaxy. The suite includes a comprehensive set of quality control metrics (retention time window evaluation and various peak evaluation tools), visualization techniques (hierarchical cluster heatmap, principal component analysis, modular modularity clustering), basic statistical analysis methods (partial least squares - discriminant analysis, analysis of variance, t-test, Kruskal-Wallis non-parametric test), advanced classification methods (random forest, support vector machines), and advanced variable selection tools (least absolute shrinkage and selection operator LASSO and Elastic Net). CONCLUSIONS: SECIMTools leverages the Galaxy platform and enables integrated workflows for metabolomics data analysis made from building blocks designed for easy use and interpretability. Standard data formats and a set of utilities allow arbitrary linkages between tools to encourage novel workflow designs. The Galaxy framework enables future data integration for metabolomics studies with other omics data.

Cognitive Machine-Learning Algorithm for Cardiac Imaging: A Pilot Study for Differentiating Constrictive Pericarditis From Restrictive Cardiomyopathy.

BACKGROUND: Associating a patient's profile with the memories of prototypical patients built through previous repeat clinical experience is a key process in clinical judgment. We hypothesized that a similar process using a cognitive computing tool would be well suited for learning and recalling multidimensional attributes of speckle tracking echocardiography data sets derived from patients with known constrictive pericarditis and restrictive cardiomyopathy. METHODS AND RESULTS: Clinical and echocardiographic data of 50 patients with constrictive pericarditis and 44 with restrictive cardiomyopathy were used for developing an associative memory classifier-based machine-learning algorithm. The speckle tracking echocardiography data were normalized in reference to 47 controls with no structural heart disease, and the diagnostic area under the receiver operating characteristic curve of the associative memory classifier was evaluated for differentiating constrictive pericarditis from restrictive cardiomyopathy. Using only speckle tracking echocardiography variables, associative memory classifier achieved a diagnostic area under the curve of 89.2%, which improved to 96.2% with addition of 4 echocardiographic variables. In comparison, the area under the curve of early diastolic mitral annular velocity and left ventricular longitudinal strain were 82.1% and 63.7%, respectively. Furthermore, the associative memory classifier demonstrated greater accuracy and shorter learning curves than other machine-learning approaches, with accuracy asymptotically approaching 90% after a training fraction of 0.3 and remaining flat at higher training fractions. CONCLUSIONS: This study demonstrates feasibility of a cognitive machine-learning approach for learning and recalling patterns observed during echocardiographic evaluations. Incorporation of machine-learning algorithms in cardiac imaging may aid standardized assessments and support the quality of interpretations, particularly for novice readers with limited experience.

Effect of Co-planted Purslane (Portulaca Oleracea L.) on Cd Accumulation by Sunflower in Different Levels of Cd Contamination and Salinity: A Pot Study.

Heavy metal bioaccumulation can be affected by various crop-weed interactions that potentially exist in agroecosystems. A pot experiment was conducted to evaluate the role of rhizosphere interaction of sunflower and purslane (Portulaca oleracea L.) weed on cadmium (Cd) uptake and its allocation to sunflower grains. The experimental treatments consisted of two cropping systems (mono and mixed culture), two adjusted salinity levels (0 and 0.5% NaCl) and three artificial levels of Cd in soil (Control, 3 and 6 mg kg(-1)). The results showed that the growth of sunflower in the presence of purslane in comparison to mono culture of sunflower led to change of total Cd content and Cd allocated to grains only in saline conditions. Promoting effects of salinity on Cd concentration of grain were alleviated where sunflower was co-planted with purslane. Besides, supply of Zn in grains of co-planted sunflower was strongly affected by salinity. Results of this study revealed that although co-planted purslane could alter conditions in the shared rhizosphere, it had no effect on enhancing Cd uptake by neighboring sunflower directly.

Topological edge properties of C60+12 n fullerenes.

A molecular graph M is a simple graph in which atoms and chemical bonds are the vertices and edges of M, respectively. The molecular graph M is called a fullerene graph, if M is the molecular graph of a fullerene molecule. It is well-known that such molecules exist for even integers n ≥ 24 or n = 20. The aim of this paper is to investigate the topological properties of a class of fullerene molecules containing 60 + 12n carbon atoms.

Chiral spin waves in Fermi liquids with spin-orbit coupling.

We predict the existence of chiral spin waves-collective modes in a two-dimensional Fermi liquid with the Rashba or Dresselhaus spin-orbit coupling. Starting from the phenomenological Landau theory, we show that the long-wavelength dynamics of magnetization is governed by the Klein-Gordon equations. The standing-wave solutions of these equations describe ''particles" with effective masses, whose magnitudes and signs depend on the strength of the electron-electron interaction. The spectrum of the spin-chiral modes for arbitrary wavelengths is determined from the Dyson equation for the interaction vertex. We propose to observe spin-chiral modes via microwave absorption by standing waves confined by an in-plane profile of the spin-orbit splitting.

Shell-polynomials and cluj-tehran index in tori t(4,4)s[5,n].

Weighted Hosoya polynomials have been developed by Diudea, in ref. Studia Univ. "Babes-Bolyai", 2002, 47, 131-139. Among various weighting schemes, those polynomials obtained by using Diudea's Shell matrix operator are far more interesting. We present here the Shell-Distance and Shell-Degree-Distance polynomials and close formulas to calculate them and derived Cluj-Tehran CT index in the family of square tiled tori T(4,4)S[5,n]. Applications of the proposed descriptors are also presented.

Symmetry properties of tetraammine platinum(II) with C2v and C4v point groups.

Let G be a weighted graph with adjacency matrix A=[a(ij)]. An Euclidean graph associated with a molecule is defined by a weighted graph with adjacency matrix D=[d(ij)], where for i not = j, d(ij) is the Euclidean distance between the nuclei i and j. In this matrix d(ii) can be taken as zero if all the nuclei are equivalent. Otherwise, one may introduce different weights for different nuclei. Balasubramanian (1995) computed the Euclidean graphs and their automorphism groups for benzene, eclipsed and staggered forms of ethane and eclipsed and staggered forms of ferrocene. This paper describes a simple method, by means of which it is possible to calculate the automorphism group of weighted graphs. We apply this method to compute the symmetry of tetraammine platinum(II) with C2v and C4v point groups.

Construction of some hypergroups from combinatorial structures.

Jajcay's studies (1993; 1994) on the automorphism groups of Cayley maps yielded a new product of groups, which he called, rotary product. Using this product, we define a hyperoperation [symbol: see text] on the group Syme(G), the stabilizer of the identity e [symbol: see text] G in the group Sym(G). We prove that (Syme(G), [symbol: see text]) is a hypergroup and characterize the subhypergroups of this hypergroup. Finally, we show that the set of all subhypergroups of Syme(G) constitute a lattice under ordinary join and meet and that the minimal elements of order two of this lattice is a subgroup of Aut(G).