Antidiabetes and antihypertension potential of commonly consumed carbohydrate sweeteners using in vitro models

Commonly consumed carbohydrate sweeteners derived from sugar cane, palm, and corn (syrups) were investigated to determine their potential to inhibit key enzymes relevant to Type 2 diabetes and hypertension based on the total phenolic content and antioxidant activity using in vitro models. Among sugar cane derivatives, brown sugars showed higher antidiabetes potential than white sugars; nevertheless, no angiotensin I-converting enzyme (ACE) inhibition was detected in both sugar classes. Brown sugar from Peru and Mauritius (dark muscovado) had the highest total phenolic content and 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity, which correlated with a moderate inhibition of yeast alpha-glucosidase without showing a significant effect on porcine pancreatic alpha-amylase activity. In addition, chlorogenic acid quantified by high-performance liquid chromatography was detected in these sugars (128 +/- 6 and 144 +/- 2 mu g/g of sample weight, respectively). Date sugar exhibited high alpha-glucosidase, alpha-amylase, and ACE inhibitory activities that correlated with high total phenolic content and antioxidant activity. Neither phenolic compounds or antioxidant activity was detected in corn syrups, indicating that nonphenolic factors may be involved in their significant ability to inhibit alpha-glucosidase, alpha-amylase, and ACE. This study provides a strong biochemical rationale for further in vivo studies and useful information to make better dietary sweetener choices for Type 2 diabetes and hypertension management.

Plasmodium vivax circumsporozoite genotypes: a limited variation or new subspecies with major biological consequences?

Background: Plasmodium vivax circumsporozoite variants have been identified in several geographical areas. The real implication of the genetic variation in this region of the P. vivax genome has been questioned for a long time. Although previous studies have observed significant association between VK210 and the Duffy blood group, we present here that evidences of this variation are limited to the CSP central portion. Methods: The phylogenetic analyses were accomplished starting from the amplification of conserved domains of 18 SSU RNAr and Cyt B. The antibodies responses against the CSP peptides, MSP-1, AMA-1 and DBP were detected by ELISA, in plasma samples of individuals infected with two P. vivax CS genotypes: VK210 and P. vivax-like. Results: These analyses of the two markers demonstrate high similarity among the P. vivax CS genotypes and surprisingly showed diversity equal to zero between VK210 and P. vivax-like, positioning these CS genotypes in the same clade. A high frequency IgG antibody against the N- and C-terminal regions of the P. vivax CSP was found as compared to the immune response to the R- and V-repetitive regions (p = 0.0005, Fisher's Exact test). This difference was more pronounced when the P. vivax-like variant was present in the infection (p = 0.003, Fisher's Exact test). A high frequency of antibody response against MSP-1 and AMA-1 peptides was observed for all P. vivax CS genotypes in comparison to the same frequency for DBP. Conclusions: This results target that the differences among the P. vivax CS variants are restrict to the central repeated region of the protein, mostly nucleotide variation with important serological consequences.

Chemometric Studies on Natural Products as Potential Inhibitors of the NADH Oxidase from Trypanosoma cruzi Using the VolSurf Approach

Natural products have widespread biological activities, including inhibition of mitochondrial enzyme systems. Some of these activities, for example cytotoxicity, may be the result of alteration of cellular bioenergetics. Based on previous computer-aided drug design (CADD) studies and considering reported data on structure-activity relationships (SAR), an assumption regarding the mechanism of action of natural products against parasitic infections involves the NADH-oxidase inhibition. In this study, chemometric tools, such as: Principal Component Analysis (PCA), Consensus PCA (CPCA), and partial least squares regression (PLS), were applied to a set of forty natural compounds, acting as NADH-oxidase inhibitors. The calculations were performed using the VolSurf+ program. The formalisms employed generated good exploratory and predictive results. The independent variables or descriptors having a hydrophobic profile were strongly correlated to the biological data.

Data collapse, scaling functions, and analytical solutions of generalized growth models

We consider a nontrivial one-species population dynamics model with finite and infinite carrying capacities. Time-dependent intrinsic and extrinsic growth rates are considered in these models. Through the model per capita growth rate we obtain a heuristic general procedure to generate scaling functions to collapse data into a simple linear behavior even if an extrinsic growth rate is included. With this data collapse, all the models studied become independent from the parameters and initial condition. Analytical solutions are found when time-dependent coefficients are considered. These solutions allow us to perceive nontrivial transitions between species extinction and survival and to calculate the transition's critical exponents. Considering an extrinsic growth rate as a cancer treatment, we show that the relevant quantity depends not only on the intensity of the treatment, but also on when the cancerous cell growth is maximum.

Ferromagnetic resonance for the quantification of superparamagnetic iron oxide nanoparticles in biological materials

The aim of the present work is the presentation of a quantification methodology for the control of the amount of superparamagnetic iron oxide nanoparticles (SPIONs) administered in biological materials by means of the ferromagnetic resonance technique (FMR) applied to studies both in vivo and in vitro. The in vivo study consisted in the analysis of the elimination and biodistribution kinetics of SPIONs after intravenous administration in Wistar rats. The results were corroborated by X-ray fluorescence. For the in vitro study, a quantitative analysis of the concentration of SPIONs bound to the specific AC133 monoclonal antibodies was carried out in order to detect the expression of the antigenic epitopes (CD133) in stem cells from human umbilical cord blood. In both studies FMR has proven to be an efficient technique for the SPIONs quantification per volume unit (in vivo) or per labeled cell (in vitro).

Proteomic analysis of total cellular proteins of human neutrophils

Background: Neutrophils are the most abundant leukocytes in peripheral blood and represent one of the most important elements of innate immunity. Recent subcellular proteomic studies have focused on the identification of human neutrophil proteins in various subcellular membrane and granular fractions. Although there are relatively few studies dealing with the analysis of the total extract of human neutrophils, many biological problems such as the role of chemokines, adhesion molecules, and other activating inputs involved in neutrophil responses and signaling can be approached on the basis of the identification of the total cellular proteins. Results: Using gel-LC-MS/MS, 251 total cellular proteins were identified from resting human neutrophils. This is more than ten times the number of proteins identified by an initial proteome analysis of human neutrophils and almost five times the number of proteins identified by the first 2-DE map of extracts of rat polymorphonuclear leukocytes. Most of the proteins identified in the present study are well-known, but some of them, such as neutrophil-secreted proteins and centaurin beta-1, a cytoplasmic protein involved in the regulation of NF-kappa B activity, are described here for the first-time. Conclusion: The present report provides new information about the protein content of human neutrophils. Importantly, our study resulted in the discovery of a series of proteins not previously reported to be associated with human neutrophils. These data are relevant to the investigation of comparative pathological states and models for novel classes of pharmaceutical drugs that could be useful in the treatment of inflammatory disorders in which neutrophils participate.

Possibility for a full optical determination of photodynamic therapy outcome

The efficacy of photodynamic therapy (PDT) depends on a variety of parameters: concentration of the photosensitizer at the time of treatment, light wavelength, fluence, fluence rate, availability of oxygen within the illuminated volume, and light distribution in the tissue. Dosimetry in PDT requires the congregation of adequate amounts of light, drug, and tissue oxygen. The adequate dosimetry should be able to predict the extension of the tissue damage. Photosensitizer photobleaching rate depends on the availability of molecular oxygen in the tissue. Based on photosensitizers photobleaching models, high photobleaching has to be associated with high production of singlet oxygen and therefore with higher photodynamic action, resulting in a greater depth of necrosis. The purpose of this work is to show a possible correlation between depth of necrosis and the in vivo photosensitizer (in this case, Photogem (R)) photodegradation during PDT. Such correlation allows possibilities for the development of a real time evaluation of the photodynamic action during PDT application. Experiments were performed in a range of fluence (0-450 J/cm(2)) at a constant fluence rate of 250 mW/cm(2) and applying different illumination times (0-1800 s) to achieve the desired fluence. A quantity was defined (psi) as the product of fluorescence ratio (related to the photosensitizer degradation at the surface) and the observed depth of necrosis. The correlation between depth of necrosis and surface fluorescence signal is expressed in psi and could allow, in principle, a noninvasive monitoring of PDT effects during treatment. High degree of correlation is observed and a simple mathematical model to justify the results is presented.

Differential expression of microRNAs in mouse pain models

Background: MicroRNAs (miRNAs) are short non-coding RNAs that inhibit translation of target genes by binding to their mRNAs. The expression of numerous brain-specific miRNAs with a high degree of temporal and spatial specificity suggests that miRNAs play an important role in gene regulation in health and disease. Here we investigate the time course gene expression profile of miR-1, -16, and -206 in mouse dorsal root ganglion (DRG), and spinal cord dorsal horn under inflammatory and neuropathic pain conditions as well as following acute noxious stimulation. Results: Quantitative real-time polymerase chain reaction analyses showed that the mature form of miR-1, -16 and -206, is expressed in DRG and the dorsal horn of the spinal cord. Moreover, CFA-induced inflammation significantly reduced miRs-1 and -16 expression in DRG whereas miR-206 was downregulated in a time dependent manner. Conversely, in the spinal dorsal horn all three miRNAs monitored were upregulated. After sciatic nerve partial ligation, miR-1 and -206 were downregulated in DRG with no change in the spinal dorsal horn. On the other hand, axotomy increases the relative expression of miR-1, -16, and 206 in a time-dependent fashion while in the dorsal horn there was a significant downregulation of miR-1. Acute noxious stimulation with capsaicin also increased the expression of miR-1 and -16 in DRG cells but, on the other hand, in the spinal dorsal horn only a high dose of capsaicin was able to downregulate miR-206 expression. Conclusions: Our results indicate that miRNAs may participate in the regulatory mechanisms of genes associated with the pathophysiology of chronic pain as well as the nociceptive processing following acute noxious stimulation. We found substantial evidence that miRNAs are differentially regulated in DRG and the dorsal horn of the spinal cord under different pain states. Therefore, miRNA expression in the nociceptive system shows not only temporal and spatial specificity but is also stimulus-dependent.

A Dynamic Analysis of Tuberculosis Dissemination to Improve Control and Surveillance

Background: Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings: The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance: The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes.

Evaluation of Protective Effect of a Water-In-Oil Microemulsion Incorporating Quercetin Against UVB-Induced Damage in Hairless Mice Skin

Purpose. Histological aspects were considered in order to evaluate the in vivo photoprotective effect of a w/o microemulsion containing quercetin against UVB irradiation-induced dermal damages. The toxicity in cell culture and the potential skin irritation resulting from topical application of this formulation were investigated. Methods. Mouse dorsal surfaces were treated topically with 300 mg of the unloaded and quercetin-loaded (0.3%, w/w) microemulsions before and after exposure to UVB (2.87 J/cm(2)) irradiation. The untreated control groups irradiated and non-irradiated were also evaluated. UVB-induced histopathological changes as well as the photoprotective effect of this formulation were evaluated considering the parameters of infiltration of inflammatory cells, epidermis thickening (basale and spinosum layers) and collagen and elastic fiber contents. The cytotoxicity of the reported formulation was evaluated in L929 mice fibroblasts by MTT assay and the skin irritation was investigated after topical application of both unloaded and quercetin-loaded microemulsions once a day for 15 days. Results. The results demonstrated that the w/o microemulsion containing quercetin reduced the incidence of histological skin alterations, mainly the connective-tissue damage, induced by exposure to UVB irradiation. This suggests that protective effects of this formulation against UV-induced responses are not secondary to the interference of UV transmission (i.e., blocking the UVB radiation from being absorbed by the skin), as is usually implied with UVB absorbers and sunscreens, but is instead due to different biological effects of this flavonoid. Furthermore, by evaluating the cytotoxic effect on L929 cells and histological aspects such as infiltration of inflammatory cells and epidermis thickness of hairless mice, the present study also demonstrated the lack of toxicity of the proposed system. Conclusion. Based on these mice models, a detailed characterization of the w/o microemulsion incorporating quercetin effects as a photochemoprotective agent on human skin is presented.

Additive genetic relationship of longevity with fertility and production traits in Nellore cattle based on bivariate models

Survival or longevity is an economically important trait in beef cattle. The main inconvenience for its inclusion in selection criteria is delayed recording of phenotypic data and the high computational demand for including survival in proportional hazard models. Thus, identification of a longevity-correlated trait that could be recorded early in life would be very useful for selection purposes. We estimated the genetic relationship of survival with productive and reproductive traits in Nellore cattle, including weaning weight (WW), post-weaning growth (PWG), muscularity (MUSC), scrotal circumference at 18 months (SC18), and heifer pregnancy (HP). Survival was measured in discrete time intervals and modeled through a sequential threshold model. Five independent bivariate Bayesian analyses were performed, accounting for cow survival and the five productive and reproductive traits. Posterior mean estimates for heritability (standard deviation in parentheses) were 0.55 (0.01) for WW, 0.25 (0.01) for PWG, 0.23 (0.01) for MUSC, and 0.48 (0.01) for SC18. The posterior mean estimates (95% confidence interval in parentheses) for the genetic correlation with survival were 0.16 (0.13-0.19), 0.30 (0.25-0.34), 0.31 (0.25-0.36), 0.07 (0.02-0.12), and 0.82 (0.78-0.86) for WW, PWG, MUSC, SC18, and HP, respectively. Based on the high genetic correlation and heritability (0.54) posterior mean estimates for HP, the expected progeny difference for HP can be used to select bulls for longevity, as well as for post-weaning gain and muscle score.

Comparison of different models to estimate genetic parameters for carcass traits in a commercial broiler line

The effect of genetic and non-genetic factors for carcass, breast meat and leg weights, and yields of a commercial broiler line were investigated using the restricted maximum likelihood method, considering four different animal models, including or excluding maternal genetic effect with covariance between direct and maternal genetic effects, and maternal permanent environmental effect. The likelihood ratio test was used to determine the most adequate model for each trait. For carcass, breast, and leg weight, and for carcass and breast yield, maternal genetic and permanent environmental effects as well as the covariance between direct and maternal genetic effects were significant. The estimates of direct and maternal heritability were 0.17 and 0.04 for carcass weight, 0.26 and 0.06 for breast weight, 0.22 and 0.02 for leg weight, 0.32 and 0.02 for carcass yield, and 0.52 and 0.04 for breast yield, respectively. For leg yield, maternal permanent environmental effect was important, in addition to direct genetic effects. For that trait, direct heritability and maternal permanent environmental variance as a proportion of the phenotypic variance were 0.43 and 0.02, respectively. The results indicate that ignoring maternal effects in the models, even though they were of small magnitude (0.02 to 0.06), tended to overestimate direct genetic variance and heritability for all traits.

Newtonian perturbations on models with matter creation

Creation of cold dark matter (CCDM) can macroscopically be described by a negative pressure, and, therefore, the mechanism is capable to accelerate the Universe, without the need of an additional dark energy component. In this framework, we discuss the evolution of perturbations by considering a Neo-Newtonian approach where, unlike in the standard Newtonian cosmology, the fluid pressure is taken into account even in the homogeneous and isotropic background equations (Lima, Zanchin, and Brandenberger, MNRAS 291, L1, 1997). The evolution of the density contrast is calculated in the linear approximation and compared to the one predicted by the Lambda CDM model. The difference between the CCDM and Lambda CDM predictions at the perturbative level is quantified by using three different statistical methods, namely: a simple chi(2)-analysis in the relevant space parameter, a Bayesian statistical inference, and, finally, a Kolmogorov-Smirnov test. We find that under certain circumstances, the CCDM scenario analyzed here predicts an overall dynamics (including Hubble flow and matter fluctuation field) which fully recovers that of the traditional cosmic concordance model. Our basic conclusion is that such a reduction of the dark sector provides a viable alternative description to the accelerating Lambda CDM cosmology.

Equation of state for the magnetic-color-flavor-locked phase and its implications for compact star models

Using the solutions of the gap equations of the magnetic-color-flavor-locked (MCFL) phase of paired quark matter in a magnetic field, and taking into consideration the separation between the longitudinal and transverse pressures due to the field-induced breaking of the spatial rotational symmetry, the equation of state of the MCFL phase is self-consistently determined. This result is then used to investigate the possibility of absolute stability, which turns out to require a field-dependent ""bag constant"" to hold. That is, only if the bag constant varies with the magnetic field, there exists a window in the magnetic field vs bag constant plane for absolute stability of strange matter. Implications for stellar models of magnetized (self-bound) strange stars and hybrid (MCFL core) stars are calculated and discussed.

Confronting dark energy models using galaxy cluster number counts

The mass function of cluster-size halos and their redshift distribution are computed for 12 distinct accelerating cosmological scenarios and confronted to the predictions of the conventional flat Lambda CDM model. The comparison with Lambda CDM is performed by a two-step process. First, we determine the free parameters of all models through a joint analysis involving the latest cosmological data, using supernovae type Ia, the cosmic microwave background shift parameter, and baryon acoustic oscillations. Apart from a braneworld inspired cosmology, it is found that the derived Hubble relation of the remaining models reproduces the Lambda CDM results approximately with the same degree of statistical confidence. Second, in order to attempt to distinguish the different dark energy models from the expectations of Lambda CDM, we analyze the predicted cluster-size halo redshift distribution on the basis of two future cluster surveys: (i) an X-ray survey based on the eROSITA satellite, and (ii) a Sunayev-Zeldovich survey based on the South Pole Telescope. As a result, we find that the predictions of 8 out of 12 dark energy models can be clearly distinguished from the Lambda CDM cosmology, while the predictions of 4 models are statistically equivalent to those of the Lambda CDM model, as far as the expected cluster mass function and redshift distribution are concerned. The present analysis suggests that such a technique appears to be very competitive to independent tests probing the late time evolution of the Universe and the associated dark energy effects.