Chromosome homologies of the highly rearranged karyotypes of four Akodon species (Rodentia, Cricetidae) resolved by reciprocal chromosome painting: the evolution of the lowest diploid number in rodents

Traditionally comparative cytogenetic studies are based mainly on banding patterns. Nevertheless, when dealing with species with highly rearranged genomes, as in Akodon species, or with other highly divergent species, cytogenetic comparisons of banding patterns prove inadequate. Hence, comparative chromosome painting has become the method of choice for genome comparisons at the cytogenetic level since it allows complete chromosome probes of a species to be hybridized in situ onto chromosomes of other species, detecting homologous genomic regions between them. In the present study, we have explored the highly rearranged complements of the Akodon species using reciprocal chromosome painting through species-specific chromosome probes obtained by chromosome sorting. The results revealed complete homology among the complements of Akodon sp. n. (ASP), 2n = 10; Akodon cursor (ACU), 2n = 15; Akodon montensis (AMO), 2n = 24; and Akodon paranaensis (APA), 2n = 44, and extensive chromosome rearrangements have been detected within the species with high precision. Robertsonian and tandem rearrangements, pericentric inversions and/or centromere repositioning, paracentric inversion, translocations, insertions, and breakpoints, where chromosomal rearrangements, seen to be favorable, were observed. Chromosome painting using the APA set of 21 autosomes plus X and Y revealed eight syntenic segments that are shared with A. montensis, A. cursor, and ASP, and one syntenic segment shared by A. montensis and A. cursor plus five exclusive chromosome associations for A. cursor and six for ASP chromosome X, except for the heterochromatin region of ASP X, and even chromosome Y shared complete homology among the species. These data indicate that all those closely related species have experienced a recent extensive process of autosomal rearrangement in which, except for ASP, there is still complete conservation of sex chromosomes homologies.

Effect of 830 nm low-level laser therapy applied before high-intensity exercises on skeletal muscle recovery in athletes

Our aim was to investigate the immediate effects of bilateral, 830 nm, low-level laser therapy (LLLT) on high-intensity exercise and biochemical markers of skeletal muscle recovery, in a randomised, double-blind, placebo-controlled, crossover trial set in a sports physiotherapy clinic. Twenty male athletes (nine professional volleyball players and eleven adolescent soccer players) participated. Active LLLT (830 nm wavelength, 100 mW, spot size 0.0028 cm(2), 3-4 J per point) or an identical placebo LLLT was delivered to five points in the rectus femoris muscle (bilaterally). The main outcome measures were the work performed in the Wingate test: 30 s of maximum cycling with a load of 7.5% of body weight, and the measurement of blood lactate (BL) and creatine kinase (CK) levels before and after exercise. There was no significant difference in the work performed during the Wingate test (P > 0.05) between subjects given active LLLT and those given placebo LLLT. For volleyball athletes, the change in CK levels from before to after the exercise test was significantly lower (P = 0.0133) for those given active LLLT (2.52 U l(-1) +/- 7.04 U l(-1)) than for those given placebo LLLT (28.49 U l(-1) +/- 22.62 U l(-1)). For the soccer athletes, the change in blood lactate levels from before exercise to 15 min after exercise was significantly lower (P < 0.01) in the group subjected to active LLLT (8.55 mmol l(-1) +/- 2.14 mmol l(-1)) than in the group subjected to placebo LLLT (10.52 mmol l(-1) +/- 1.82 mmol l(-1)). LLLT irradiation before the Wingate test seemed to inhibit an expected post-exercise increase in CK level and to accelerate post-exercise lactate removal without affecting test performance. These findings suggest that LLLT may be of benefit in accelerating post-exercise recovery.

Regression Models with Heteroscedasticity using Bayesian Approach

In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

Two-level network design with intermediate facilities: An application to electrical distribution systems

We consider the two-level network design problem with intermediate facilities. This problem consists of designing a minimum cost network respecting some requirements, usually described in terms of the network topology or in terms of a desired flow of commodities between source and destination vertices. Each selected link must receive one of two types of edge facilities and the connection of different edge facilities requires a costly and capacitated vertex facility. We propose a hybrid decomposition approach which heuristically obtains tentative solutions for the vertex facilities number and location and use these solutions to limit the computational burden of a branch-and-cut algorithm. We test our method on instances of the power system secondary distribution network design problem. The results show that the method is efficient both in terms of solution quality and computational times. (C) 2010 Elsevier Ltd. All rights reserved.

NMR Chemical Shielding and Spin-Spin Coupling Constants of Liquid NH(3): A Systematic Investigation using the Sequential QM/MM Method

The NMR spin coupling parameters, (1)J(N,H) and (2)J(H,H), and the chemical shielding, sigma((15)N), of liquid ammonia are studied from a combined and sequential QM/MM methodology. Monte Carlo simulations are performed to generate statistically uncorrelated configurations that are submitted to density functional theory calculations. Two different Lennard-Jones potentials are used in the liquid simulations. Electronic polarization is included in these two potentials via an iterative procedure with and without geometry relaxation, and the influence on the calculated properties are analyzed. B3LYP/aug-cc-pVTZ-J calculations were used to compute the V(N,H) constants in the interval of -67.8 to -63.9 Hz, depending on the theoretical model used. These can be compared with the experimental results of -61.6 Hz. For the (2)J(H,H) coupling the theoretical results vary between -10.6 to -13.01 Hz. The indirect experimental result derived from partially deuterated liquid is -11.1 Hz. Inclusion of explicit hydrogen bonded molecules gives a small but important contribution. The vapor-to-liquid shifts are also considered. This shift is calculated to be negligible for (1)J(N,H) in agreement with experiment. This is rationalized as a cancellation of the geometry relaxation and pure solvent effects. For the chemical shielding, U(15 N) Calculations at the B3LYP/aug-pcS-3 show that the vapor-to-liquid chemical shift requires the explicit use of solvent molecules. Considering only one ammonia molecule in an electrostatic embedding gives a wrong sign for the chemical shift that is corrected only with the use of explicit additional molecules. The best result calculated for the vapor to liquid chemical shift Delta sigma((15)N) is -25.2 ppm, in good agreement with the experimental value of -22.6 ppm.

Effect of low-level laser irradiation on odontoblast-like cells

Low-level laser therapy (LLLT), also referred to as therapeutic laser, has been recommended for a wide array of clinical procedures, among which the treatment of dentinal hypersensitivity. However, the mechanism that guides this process remains unknown. Therefore, the objective of this study was to evaluate in vitro the effects of LLL irradiation on cell metabolism (MTT assay), alkaline phosphatase (ALP) expression and total protein synthesis. The expression of genes that encode for collagen type-1 (Col-1) and fibronectin (FN) was analyzed by RT-PCR. For such purposes, oclontoblast-like cell line (MDPC-23) was previously cultured in Petri dishes (15000 cells/cm(2)) and submitted to stress conditions during 12 h. Thereafter, 6 applications with a monochromatic near infrared radiation (GaAlAs) set at predetermined parameters were performed at 12-h intervals. Non-irradiated cells served as a control group. Neither the MTT values nor the total protein levels of the irradiated group differed significantly from those of the control group (Mann-Whitney test; p > 0.05). On the other hand, the irradiated cells showed a decrease in ALP activity (Mann-Whitney test; p < 0.05). RT-PCR results demonstrated a trend to a specific reduction in gene expression after cell irradiation, though not significant statistically (Mann-Whitney test; p > 0.05). It may be concluded that, under the tested conditions, the LLLT parameters used in the present study did not influence cell metabolism, but reduced slightly the expression of some specific proteins.

Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimization

Augmented Lagrangian methods for large-scale optimization usually require efficient algorithms for minimization with box constraints. On the other hand, active-set box-constraint methods employ unconstrained optimization algorithms for minimization inside the faces of the box. Several approaches may be employed for computing internal search directions in the large-scale case. In this paper a minimal-memory quasi-Newton approach with secant preconditioners is proposed, taking into account the structure of Augmented Lagrangians that come from the popular Powell-Hestenes-Rockafellar scheme. A combined algorithm, that uses the quasi-Newton formula or a truncated-Newton procedure, depending on the presence of active constraints in the penalty-Lagrangian function, is also suggested. Numerical experiments using the Cute collection are presented.

Bayesian inference for a skew-normal IRT model under the centred parameterization

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is interest in studying latent variables. These latent variables are directly considered in the Item Response Models (IRM) and they are usually called latent traits. A usual assumption for parameter estimation of the IRM, considering one group of examinees, is to assume that the latent traits are random variables which follow a standard normal distribution. However, many works suggest that this assumption does not apply in many cases. Furthermore, when this assumption does not hold, the parameter estimates tend to be biased and misleading inference can be obtained. Therefore, it is important to model the distribution of the latent traits properly. In this paper we present an alternative latent traits modeling based on the so-called skew-normal distribution; see Genton (2004). We used the centred parameterization, which was proposed by Azzalini (1985). This approach ensures the model identifiability as pointed out by Azevedo et al. (2009b). Also, a Metropolis Hastings within Gibbs sampling (MHWGS) algorithm was built for parameter estimation by using an augmented data approach. A simulation study was performed in order to assess the parameter recovery in the proposed model and the estimation method, and the effect of the asymmetry level of the latent traits distribution on the parameter estimation. Also, a comparison of our approach with other estimation methods (which consider the assumption of symmetric normality for the latent traits distribution) was considered. The results indicated that our proposed algorithm recovers properly all parameters. Specifically, the greater the asymmetry level, the better the performance of our approach compared with other approaches, mainly in the presence of small sample sizes (number of examinees). Furthermore, we analyzed a real data set which presents indication of asymmetry concerning the latent traits distribution. The results obtained by using our approach confirmed the presence of strong negative asymmetry of the latent traits distribution. (C) 2010 Elsevier B.V. All rights reserved.

RNA Isolation method for polysaccharide rich algae: agar producing Gracilaria tenuistipitata (Rhodophyta)

RNA isolation is essential to study gene expression at the molecular level. However, RNA isolation is difficult in organisms (plants and algae) that contain large amounts of polysaccharides, which co-precipitate with RNA. Currently, there is no commercial kit available, specifically for the isolation of high-quality RNA from these organisms. Furthermore, because of the large amounts of polysaccharides, the common protocols for RNA isolation usually result in poor yields when applied to algae. Here we describe a simple method for RNA isolation from the marine red macroalga Gracilaria tenuistipitata var. liui Zhang et Xia (Rhodophyta), which can be applied to other plants and algae.

Predicting and characterizing new molecular species at a high-level theoretical approach: HSeCl, HClSe, and SeCl

New molecular species HSeCl, HClSe, and SeCl were investigated at a high level of theory, CCSD(T), with a series of correlation consistent basis sets with extrapolation to the CBS limit. Account has been taken for valence-only and core-valence correlation effects, and of anharmonic effects on the vibrational frequencies. HSeCl is 43.25 kcal mol (1) more stable than HClSe. A barrier (Delta G(#)) of 47.20 kcal mol (1) separates these species. Internuclear distances are generally overestimated by 0.008 angstrom in the valence-only correlation calculations. Inclusion of anharmonicity leads to much improved vibrational frequencies. For SeCl, we estimate Delta H(f) (0 K) = 23.96 and Delta H(f) (298.15 K) = 24.64 kcal mol (1); for HSeCl, we had 4.20 and 4.97 kcal mol (1), respectively. (C) 2010 Elsevier B.V. All rights reserved.

Development of a sequential injection-square wave voltammetry method for determination of paraquat in water samples employing the hanging mercury drop electrode

This work describes the development and optimization of a sequential injection method to automate the determination of paraquat by square-wave voltammetry employing a hanging mercury drop electrode. Automation by sequential injection enhanced the sampling throughput, improving the sensitivity and precision of the measurements as a consequence of the highly reproducible and efficient conditions of mass transport of the analyte toward the electrode surface. For instance, 212 analyses can be made per hour if the sample/standard solution is prepared off-line and the sequential injection system is used just to inject the solution towards the flow cell. In-line sample conditioning reduces the sampling frequency to 44 h(-1). Experiments were performed in 0.10 M NaCl, which was the carrier solution, using a frequency of 200 Hz, a pulse height of 25 mV, a potential step of 2 mV, and a flow rate of 100 mu L s(-1). For a concentration range between 0.010 and 0.25 mg L(-1), the current (i(p), mu A) read at the potential corresponding to the peak maximum fitted the following linear equation with the paraquat concentration (mg L(-1)): ip = (-20.5 +/- 0.3) Cparaquat -(0.02 +/- 0.03). The limits of detection and quantification were 2.0 and 7.0 mu g L(-1), respectively. The accuracy of the method was evaluated by recovery studies using spiked water samples that were also analyzed by molecular absorption spectrophotometry after reduction of paraquat with sodium dithionite in an alkaline medium. No evidence of statistically significant differences between the two methods was observed at the 95% confidence level.

Calculating Flash Point Numbers from Molecular Structure: An Improved Method for Predicting the Flash Points of Acyclic Alkanes

We report a novel method for calculating flash points of acyclic alkanes from flash point numbers, N(FP), which can be calculated from experimental or calculated boiling point numbers (Y(BP)) with the equation N(FP) = 1.020Y(BP) - 1.083 Flash points (FP) are then determined from the relationship FP(K) = 23.369N(FP)(2/3) + 20.010N(FP)(1/3) + 31.901 For it data set of 102 linear and branched alkanes, the correlation of literature and predicted flash points has R(2) = 0.985 and an average absolute deviation of 3.38 K. N(FP) values can also be estimated directly from molecular structure to produce an even closer correspondence of literature and predicted FP values. Furthermore, N(FP) values provide a new method to evaluate the reliability of literature flash point data.

Isomers on the [H, S(2), Cl] potential energy surface: A high level investigation

This study reports a systematic state-of-the-art characterization of new sulfur-chlorine species on the [H, S(2), Cl] potential energy surface. Coupled cluster theory singles and doubles with perturbative contributions of connected triples, using the series of correlation consistent basis sets with extrapolations to the complete basis set limit (CBS), were employed to quantify the energetic quantities involved in the isomerization processes on this surface. The structures and vibrational frequencies are unique for some species and represent the most accurate investigation to date. These molecules are potentially a new route of coupling the sulfur and chlorine chemistries in the atmosphere, and conditions of high concentration of H(2)S (HS) like in volcanic eruptions might contribute to their formation. Also an assessment of the MP2/CBS approach relative to CCSD(T)/CBS provides insights on the expected performance of MP2/CBS on the characterization of polysulfides, and also of more complex systems containing disulfide bridges. (C) 2009 Elsevier B.V. All rights reserved.

A method for Ca, Fe, Ga, Na, Si and Zn determination in alumina by inductively coupled plasma optical emission spectrometry after aluminum precipitation

In this present work a method for the determination of Ca, Fe, Ga, Na, Si and Zn in alumina (Al(2)O(3)) by inductively coupled plasma optical emission spectrometry (ICP OES) with axial viewing is presented. Preliminary studies revealed intense aluminum spectral interference over the majority of elements and reaction between aluminum and quartz to form aluminosilicate, reducing drastically the lifetime of the torch. To overcome these problems alumina samples (250 mg) were dissolved with 5 mL HCl + 1.5 mLH(2)SO(4) + 1.5 mL H(2)O in a microwave oven. After complete dissolution the volume was completed to 20 mL and aluminum was precipitated as Al(OH)(3) with NH(3) (by bubbling NH(3) into the solution up to a pH similar to 8, for 10 min). The use of internal standards (Fe/Be, Ga/Dy, Zn/In and Na/Sc) was essential to obtain precise and accurate results. The reliability of the proposed method was checked by analysis of alumina certified reference material (Alumina Reduction Grade-699, NIST). The found concentrations (0.037%w(-1) CaO, 0.013% w w(-1) Fe(2)O(3), 0.012%w w(-1)Ga(2)O(3), 0.49% w w(-1) Na(2)O, 0.014% w w(-1) SiO(2) and 0.013% w w(-1) ZnO) presented no statistical differences compared to the certified values at a 95% confidence level. (C) 2011 Elsevier B.V. All rights reserved.

Simple Method to Evaluate and to Predict Flash Points of Organic Compounds

Flash points (T(FP)) of organic compounds are calculated from their flash point numbers, N(FP), with the relationship T(FP) = 23.369N(FP)(2/3) + 20.010N(FP)(1/3) + 31.901. In turn, the N(FP) values can be predicted from boiling point numbers (Y(BP)) and functional group counts with the equation N(FP) = 0.974Y(BP) + Sigma(i)n(i)G(i) + 0.095 where G(i) is a functional group-specific contribution to the value of N(FP) and n(i) is the number of such functional groups in the structure. For a data set consisting of 1000 diverse organic compounds, the average absolute deviation between reported and predicted flash points was less than 2.5 K.