Protective effects of a chemically characterized extract from solanum torvum leaves on acetaminophen-induced liver injury.

Distinct parts of Solanum torvum Swartz. (Solanaceae) are popularly used for a variety of therapeutic purposes. This study determined the phytochemical composition of a phenolic fraction of S. torvum leaf aqueous extract and investigated its antioxidant and liver-protective properties. A phenolic compound-enriched fraction, or phenolic fraction (STLAE-PF) of an infusion (STLAE) of S. torvum leaves, was tested in vitro (antagonism of H2O2 in cytotoxicity and DCF assays with HepG2/C3A cells), and in vivo for antioxidant activity and protective effects against acetaminophen (APAP)-induced liver injury in mice. Thirty-eight compounds (flavonoids, esters of hydroxycinnamic acid, and chlorogenic acid isomers) were tentatively identified (high-performance liquid chromatography coupled to high-resolution electrospray mass spectrometry) in the STLAE-PF fraction. In vitro assays in HepG2/C3A cells showed that STLAE-PF and some flavonoids contained in this phenolic fraction, at noncytotoxic levels, antagonized in a concentration-dependent manner the effects of a powerful oxidant agent (H2O2). In C57BL/6 mice, oral administration of STLAE (600 and 1,200 mg/kg bw) or STLAE-PF (300 mg/kg bw) prevented the rise in serum transaminases (ALT and AST), depletion of reduced glutathione (GSH) and elevation of thiobarbituric acid reactive species (TBARs) levels in the liver caused by APAP (600 mg/kg bw, i.p.). The hepatoprotective effects of STLAE-PF (300 mg/kg bw) against APAP-caused liver injury were comparable to those of N-acetyl-cysteine (NAC 300 or 600 mg/kg bw i.p.). These findings indicate that a phenolic fraction of S. torvum leaf extract (STLAE-PF) is a new phytotherapeutic agent potentially useful for preventing/treating liver injury caused by APAP overdosing.

Lifelog Retrieval From Daily Digital Data: Narrative Review.

BACKGROUND: Over the past decade, the wide availability and small size of different types of sensors, together with the decrease in pricing, have allowed the acquisition of a substantial amount of data about a person's life in real time. These sensors can be incorporated into personal electronic devices available at a reasonable cost, such as smartphones and small wearable devices. They allow the acquisition of images, audio, location, physical activity, and physiological signals among other data. With these data, usually denoted as lifelog data, we can then analyze and understand personal experiences and behaviors. This process is called lifelogging. OBJECTIVE: The objective of this paper was to present a narrative review of the existing literature about lifelogging over the past decade. To achieve this goal, we analyzed lifelogging applications used to retrieve relevant information from daily digital data, some of them with the purpose of monitoring and assisting people with memory issues and others designed for memory augmentation. We aimed for this review to be used by researchers to obtain a broad idea of the type of data used, methodologies, and applications available in this research field. METHODS: We followed a narrative review methodology to conduct a comprehensive search for relevant publications in Google Scholar and Scopus databases using lifelog topic-related keywords. A total of 411 publications were retrieved and screened. Of these 411 publications, 114 (27.7%) publications were fully reviewed. In addition, 30 publications were manually included based on our bibliographical knowledge of this research field. RESULTS: From the 144 reviewed publications, a total of 113 (78.5%) were selected and included in this narrative review based on content analysis. The findings of this narrative review suggest that lifelogs are prone to become powerful tools to retrieve memories or increase knowledge about an individual's experiences or behaviors. Several computational tools are already available for a considerable range of applications. These tools use multimodal data of different natures, with visual lifelogs being one of the most used and rich sources of information. Different approaches and algorithms to process these data are currently in use, as this review will unravel. Moreover, we identified several open questions and possible lines of investigation in lifelogging. CONCLUSIONS: The use of personal lifelogs can be beneficial to improve the quality of our life, as they can serve as tools for memory augmentation or for providing support to people with memory issues. Through the acquisition and analysis of lifelog data, lifelogging systems can create digital memories that can be potentially used as surrogate memory. Through this narrative review, we understand that contextual information can be extracted from lifelogs, which provides an understanding of the daily life of a person based on events, experiences, and behaviors.

Characterization of the Antinociceptive Activity from Stevia serrata Cav.

BACKGROUND: Stevia serrata Cav. (Asteraceae), widely found in Guatemala, is used to treat gastrointestinal problems. The aim of this study was to demonstrate the antinociceptive and anti-inflammatory effects of the essential oil (EO) and the mechanism of action. METHODS: EO was tested in chemical (capsaicin- and glutamate-induced licking response) or thermal (hot plate) models of nociception at 10, 30 or 100 mg/kg doses. The mechanism of action was evaluated using two receptor antagonists (naloxone, atropine) and an enzyme inhibitor (L-NAME). The anti-hyperalgesic effect was evaluated using carrageenan-induced nociception and evaluated in the hot plate. RESULTS: All three doses of EO reduced licking response induced by glutamate, and higher doses reduced capsaicin-induced licking. EO also increased area under the curve, similar to the morphine-treated group. The antinociceptive effect induced by EO was reversed by pretreatment of mice with naloxone (1 mg/kg, ip), atropine (1 mg/kg, ip) or L-NAME (3 mg/kg, ip). EO also demonstrated an anti-hyperalgesic effect. The 100 mg/kg dose increased the latency time, even at 1 h after oral administration and this effect has been maintained until the 96th hour, post-administration. CONCLUSIONS: Our data suggest that essential oil of S. serrata presents an antinociceptive effect mediated, at least in part, through activation of opioid, cholinergic and nitrergic pathways.

Spatiotemporal analysis of the relationship between socioeconomic factors and stroke in the Portuguese mainland population under 65 years old.

Stroke risk has been shown to display varying patterns of geographic distribution amongst countries but also between regions of the same country. Traditionally a disease of older persons, a global 25% increase in incidence instead was noticed between 1990 and 2010 in persons aged 20-≤64 years, particularly in low- and medium-income countries. Understanding spatial disparities in the association between socioeconomic factors and stroke is critical to target public health initiatives aiming to mitigate or prevent this disease, including in younger persons. We aimed to identify socioeconomic determinants of geographic disparities of stroke risk in people <65 years old, in municipalities of mainland Portugal, and the spatiotemporal variation of the association between these determinants and stroke risk during two study periods (1992-1996 and 2002-2006). Poisson and negative binomial global regression models were used to explore determinants of disease risk. Geographically weighted regression (GWR) represents a distinctive approach, allowing estimation of local regression coefficients. Models for both study periods were identified. Significant variables included education attainment, work hours per week and unemployment. Local Poisson GWR models achieved the best fit and evidenced spatially varying regression coefficients. Spatiotemporal inequalities were observed in significant variables, with dissimilarities between men and women. This study contributes to a better understanding of the relationship between stroke and socioeconomic factors in the population <65 years of age, one age group seldom analysed separately. It can thus help to improve the targeting of public health initiatives, even more in a context of economic crisis.

MAFCO: a compression tool for MAF files.

In the last decade, the cost of genomic sequencing has been decreasing so much that researchers all over the world accumulate huge amounts of data for present and future use. These genomic data need to be efficiently stored, because storage cost is not decreasing as fast as the cost of sequencing. In order to overcome this problem, the most popular general-purpose compression tool, gzip, is usually used. However, these tools were not specifically designed to compress this kind of data, and often fall short when the intention is to reduce the data size as much as possible. There are several compression algorithms available, even for genomic data, but very few have been designed to deal with Whole Genome Alignments, containing alignments between entire genomes of several species. In this paper, we present a lossless compression tool, MAFCO, specifically designed to compress MAF (Multiple Alignment Format) files. Compared to gzip, the proposed tool attains a compression gain from 34% to 57%, depending on the data set. When compared to a recent dedicated method, which is not compatible with some data sets, the compression gain of MAFCO is about 9%. Both source-code and binaries for several operating systems are freely available for non-commercial use at: http://bioinformatics.ua.pt/software/mafco.

Van der Waals heterostructure of phosphorene and graphene: tuning the Schottky barrier and doping by electrostatic gating.

In this Letter, we study the structural and electronic properties of single-layer and bilayer phosphorene with graphene. We show that both the properties of graphene and phosphorene are preserved in the composed heterostructure. We also show that via the application of a perpendicular electric field, it is possible to tune the position of the band structure of phosphorene with respect to that of graphene. This leads to control of the Schottky barrier height and doping of phosphorene, which are important features in the design of new devices based on van der Waals heterostructures.

Tuning the thermoelectric properties of a single-molecule junction by mechanical stretching.

We theoretically investigate, as a function of the stretching, the behaviour of the thermoelectric properties - the Seebeck coefficient (S), the electronic heat conductance (κel) and the figure of merit (ZT) - of a molecule-based junction composed of a benzene-1,4-dithiolate molecule (BDT) coupled to Au(111) surfaces at room temperature. We show that the thermoelectric properties of a single molecule junction can be tuned by mechanic stretching. The Seebeck coefficient is positive, indicating that it is dominated by the HOMO. Furthermore, it increases as the HOMO level, which is associated to the sulphur atom, tends towards energies close to the Fermi energy. By modelling the transmission coefficient of the system as a single Lorentzian peak, we propose a scheme to obtain the maximum ZT of any molecular junction.

Electronic transport in patterned graphene nanoroads.

Graphane, hydrogenated graphene, can be patterned into electronic devices by selectively removing hydrogen atoms. The most simple of such devices is the so-called nanoroad, analogous to the graphene nanoribbon, where confinement-and the opening of a gap-is obtained without the need for breaking the carbon bonds. In this work we address the electronic transport properties of such systems considering different hydrogen impurities within the conduction channel. We show, using a combination of density functional theory and non-equilibrium Green's functions, that hydrogen leads to significant changes in the transport properties and in some cases to current polarization.

Efetividade de três soluções na descontaminação de cones de guta-percha e de resilo / Effectiveness of three solutions in disinfection of gutta-percha and resilon pellets

O objetivo deste trabalho foi verificar a efetividade na descontaminação de cones de guta-percha e de resilon com os seguintes grupos: hipoclorito de sódio 5,25% durante 1 minuto; hipoclorito de sódio 2,5% durante 1 minuto; clorexidina 2% durante 1 minuto; glicerina fenicada durante 24 horas. Os agentes apresentaram-se eficazes, sem diferença estatística significativa, embora a clorexidina a 2% tenha apresentado um percentual de 20% de amostras positivas tanto na guta-percha como no resilon, o que pode ser considerado relevante clinicamente. Concluiu-se que o hipoclorito de sódio e a glicerina fenicada podem ser indicados para a descontaminação de ambos os tipos de cone, nas duas concentrações testadas.

The aim of this study was to assess the effectiveness in decontamination of gutta-percha and Resilon with the following groups: 5.25% sodium hypochlorite for 1 minute; 2.5% sodium hypochlorite for 1 minute, 2% chlorhexidine during 1 minute; glycerin fenicada for 24 hours. The agents had been effective, not statistically significant, although the 2% chlorhexidine presented a higher percentage of 20% of positive samples in both the gutta-percha and Resilon in what can be considered clinically relevant. It was concluded that sodium hypochlorite and glycerin fenicada may be indicated for the decontamination of both types of cone, at the concentrations tested.

Confinement effects and why carbon nanotube bundles can work as gas sensors.

Carbon nanotubes have been at the forefront of nanotechnology, leading not only to a better understanding of the basic properties of charge transport in one dimensional materials, but also to the perspective of a variety of possible applications, including highly sensitive sensors. Practical issues, however, have led to the use of bundles of nanotubes in devices, instead of isolated single nanotubes. From a theoretical perspective, the understanding of charge transport in such bundles, and how it is affected by the adsorption of molecules, has been very limited, one of the reasons being the sheer size of the calculations. A frequent option has been the extrapolation of knowledge gained from single tubes to the properties of bundles. In the present work we show that such procedure is not correct, and that there are qualitative differences in the effects caused by molecules on the charge transport in bundles versus isolated nanotubes. Using a combination of density functional theory and recursive Green's function techniques we show that the adsorption of molecules randomly distributed onto the walls of carbon nanotube bundles leads to changes in the charge density and consequently to significant alterations in the conductance even in pristine tubes. We show that this effect is driven by confinement which is not present in isolated nanotubes. Furthermore, a low concentration of dopants randomly adsorbed along a two-hundred nm long bundle drives a change in the transport regime; from ballistic to diffusive, which can account for the high sensitivity to different molecules.

Molecular and electronic structure of the peptide subunit of Geobacter sulfurreducens conductive pili from first principles.

The respiration of metal oxides by the bacterium Geobacter sulfurreducens requires the assembly of a small peptide (the GS pilin) into conductive filaments termed pili. We gained insights into the contribution of the GS pilin to the pilus conductivity by developing a homology model and performing molecular dynamics simulations of the pilin peptide in vacuo and in solution. The results were consistent with a predominantly helical peptide containing the conserved α-helix region required for pilin assembly but carrying a short carboxy-terminal random-coiled segment rather than the large globular head of other bacterial pilins. The electronic structure of the pilin was also explored from first principles and revealed a biphasic charge distribution along the pilin and a low electronic HOMO-LUMO gap, even in a wet environment. The low electronic band gap was the result of strong electrostatic fields generated by the alignment of the peptide bond dipoles in the pilin's α-helix and by charges from ions in solution and amino acids in the protein. The electronic structure also revealed some level of orbital delocalization in regions of the pilin containing aromatic amino acids and in spatial regions of high resonance where the HOMO and LUMO states are, which could provide an optimal environment for the hopping of electrons under thermal fluctuations. Hence, the structural and electronic features of the pilin revealed in these studies support the notion of a pilin peptide environment optimized for electron conduction.

On the representability of complete genomes by multiple competing finite-context (Markov) models.

A finite-context (Markov) model of order k yields the probability distribution of the next symbol in a sequence of symbols, given the recent past up to depth k. Markov modeling has long been applied to DNA sequences, for example to find gene-coding regions. With the first studies came the discovery that DNA sequences are non-stationary: distinct regions require distinct model orders. Since then, Markov and hidden Markov models have been extensively used to describe the gene structure of prokaryotes and eukaryotes. However, to our knowledge, a comprehensive study about the potential of Markov models to describe complete genomes is still lacking. We address this gap in this paper. Our approach relies on (i) multiple competing Markov models of different orders (ii) careful programming techniques that allow orders as large as sixteen (iii) adequate inverted repeat handling (iv) probability estimates suited to the wide range of context depths used. To measure how well a model fits the data at a particular position in the sequence we use the negative logarithm of the probability estimate at that position. The measure yields information profiles of the sequence, which are of independent interest. The average over the entire sequence, which amounts to the average number of bits per base needed to describe the sequence, is used as a global performance measure. Our main conclusion is that, from the probabilistic or information theoretic point of view and according to this performance measure, multiple competing Markov models explain entire genomes almost as well or even better than state-of-the-art DNA compression methods, such as XM, which rely on very different statistical models. This is surprising, because Markov models are local (short-range), contrasting with the statistical models underlying other methods, where the extensive data repetitions in DNA sequences is explored, and therefore have a non-local character.

Disorder-based graphene spintronics.

The use of the spin of the electron as the ultimate logic bit-in what has been dubbed spintronics-can lead to a novel way of thinking about information flow. At the same time single-layer graphene has been the subject of intense research due to its potential application in nanoscale electronics. While defects can significantly alter the electronic properties of nanoscopic systems, the lack of control can lead to seemingly deleterious effects arising from the random arrangement of such impurities. Here we demonstrate, using ab initio density functional theory and non-equilibrium Green's functions calculations, that it is possible to obtain perfect spin selectivity in doped graphene nanoribbons to produce a perfect spin filter. We show that initially unpolarized electrons entering the system give rise to 100% polarization of the current due to random disorder. This effect is explained in terms of different localization lengths for each spin channel which leads to a new mechanism for the spin filtering effect that is disorder-driven.

Tight-binding model for carbon nanotubes from ab initio calculations.

Here we present a parametrized tight-binding (TB) model to calculate the band structure of single-wall carbon nanotubes (SWNTs). On the basis of ab initio calculations we fit the band structure of nanotubes of different radii with results obtained with an orthogonal TB model to third neighbors, which includes the effects of orbital hybridization by means of a reduced set of parameters. The functional form for the dependence of these parameters on the radius of the tubes can be used to interpolate appropriate TB parameters for different SWNTs and to study the effects of curvature on their electronic properties. Additionally, we have shown that the model gives an appropriate description of the optical spectra of SWNTs, which can be useful for a proper assignation of SWNTs' specific chirality from optical absorption experiments.

Lossless compression of microarray images using image-dependent finite-context models.

The use of microarray expression data in state-of-the-art biology has been well established. The widespread adoption of this technology, coupled with the significant volume of data generated per experiment, in the form of images, has led to significant challenges in storage and query retrieval. In this paper, we present a lossless bitplane-based method for efficient compression of microarray images. This method is based on arithmetic coding driven by image-dependent multibitplane finite-context models. It produces an embedded bitstream that allows progressive, lossy-to-lossless decoding. We compare the compression efficiency of the proposed method with three image compression standards (JPEG2000, JPEG-LS, and JBIG) and also with the two most recent specialized methods for microarray image coding. The proposed method gives better results for all images of the test sets and confirms the effectiveness of bitplane-based methods and finite-context modeling for the lossless compression of microarray images.

Theoretical investigation of Hf and Zr defects in c-Ge.

The introduction of high-permittivity gate dielectric materials into complementary metal oxide semiconductor technology has reopened the interest in Ge as a channel material mainly due to its high hole mobility. Since HfO(2) and ZrO(2) are two of the most promising dielectric candidates, it is important to investigate if Hf and Zr may diffuse into the Ge channel. Therefore, using ab initio density functional theory calculations, we have studied substitutional and interstitial Hf and Zr impurities in c-Ge,looking for neutral defects. We find that (i) substitutional Zr and Hf defects are energetically more favorable than interstitial defects; (ii) under oxygen-rich conditions, neither Zr nor Hf migration towards the channel is likely to occur; (iii) either under Hf- or Zr-rich conditions it is very likely, particularly for Zr, that defects will be incorporated in the channel.

Fat-free mass, strength, and sarcopenia are related to bone mineral density in older women.

This study examined the association between fat-free mass (FFM) and muscle strength with bone mineral density (BMD), and compared the BMD values between sarcopenic and nonsarcopenic older women. After the exclusion criteria were applied, a total of 246 volunteers (age: 66.51+/-6.37 yr) participated in the analysis. Subjects underwent FFM and BMD evaluation by dual-energy X-ray absorptiometry and quadriceps strength by an isokinetic dynamometer. To address the potential for confounding by height, FFM values were considered relative to body height squared. For fat mass correction, fat-adjusted FFM was calculated. Individuals were classified as sarcopenic if their appendicular FFM was less than 5.45 kg/m2. All the evaluated FFM indexes were significantly correlated with the measured BMD sites. Sarcopenic individuals presented significantly lower whole body and trochanter BMD, and were significantly more prone to have low BMD. Muscle strength was also correlated with BMD sites; however, when it was expressed relative to body weight, the significance disappeared. Nevertheless, volunteers with low relative strength had higher risk of having low trochanter BMD. It can be concluded, in older women, that FFM is significantly correlated with BMD independently of height and fat mass. Muscle strength was also correlated with BMD, although the correlation was weaker when corrected for body weight. Finally, sarcopenic elderly women were more likely to have low BMD and muscle strength.

sigma- and pi-defects at graphene nanoribbon edges: building spin filters.

The presence of certain kinds of defects at the edges of monohydrogenated zigzag graphene nanoribbons changes dramatically the charge transport properties inducing a spin-polarized conductance. Using an approach based on density functional theory and nonequilibrium Green's function formalism to calculate the transmittance, we classify the defects in different classes depending on their distinct transport properties: (i) sigma-defects, which do not affect the transmittance close to the Fermi energy (EF); and (ii) pi-defects, which cause a spin polarization of the transmittance and that can be further divided into either electron or hole defects if the spin transport polarization results in larger transmittance for the up or down spin channel, respectively.

Symmetry controlled spin polarized conductance in au nanowires.

The fact that the resistance of propagating electrons in solids depends on their spin orientation has led to a new field called spintronics. With the parallel advances in nanoscience, it is now possible to talk about nanospintronics. Many works have focused on the study of charge transport along nanosystems, such as carbon nanotubes, graphene nanoribbons, or metallic nanowires, and spin dependent transport properties at this scale may lead to new behaviors due to the manipulation of a small number of spins. Metal nanowires have been studied as electric contacts where atomic and molecular insertions can be constructed. Here we describe what might be considered the ultimate spin device, namely, a Au thin nanowire with one Co atom bridging its two sides. We show that this system has strong spin dependent transport properties and that its local symmetry can dramatically change them, leading to a significant spin polarized conductance.

Designing real nanotube-based gas sensors.

Using a combination of density functional theory and recursive Green's functions techniques, we present a full description of a large scale sensor, accounting for disorder and different coverages. Here, we use this method to demonstrate the functionality of nitrogen-rich carbon nanotubes as ammonia sensors as an example. We show how the molecules one wishes to detect bind to the most relevant defects on the nanotube, describe how these interactions lead to changes in the electronic transport properties of each isolated defect, and demonstrate that there are significative resistance changes even in the presence of disorder, elucidating how a realistic nanosensor works.