QSAR Modeling of a Set of Pyrazinoate Esters as Antituberculosis Prodrugs

Tuberculosis is an infection caused mainly by Mycobacterium tuberculosis. A first-line antimycobacterial drug is pyrazinamide (PZA), which acts partially as a prodrug activated by a pyrazinamidase releasing the active agent, pyrazinoic acid (POA). As pyrazinoic acid presents some difficulty to cross the mycobacterial cell wall, and also the pyrazinamide-resistant strains do not express the pyrazinamidase, a set of pyrazinoic acid esters have been evaluated as antimycobacterial agents. In this work, a QSAR approach was applied to a set of forty-three pyrazinoates against M. tuberculosis ATCC 27294, using genetic algorithm function and partial least squares regression (WOLF 5.5 program). The independent variables selected were the Balaban index (I), calculated n-octanol/water partition coefficient (ClogP), van-der-Waals surface area, dipole moment, and stretching-energy contribution. The final QSAR model (N = 32, r(2) = 0.68, q(2) = 0.59, LOF = 0.25, and LSE = 0.19) was fully validated employing leave-N-out cross-validation and y-scrambling techniques. The test set (N = 11) presented an external prediction power of 73%. In conclusion, the QSAR model generated can be used as a valuable tool to optimize the activity of future pyrazinoic acid esters in the designing of new antituberculosis agents.

Molecular modeling as a promising tool to study dendrimer prodrugs delivery

Molecular modeling methodologies were applied to perform preliminary studies concerning the release of active agents from potentially antichagasic and antileishmanial dendrimer prodrugs. The dendrimer was designed having myo-inositol as a core, L-malic acid as a spacer group, and hydroxymethylnitrofurazone (NFOH), 3-hydroxyflavone or quercetin, as active compounds. Each dendrimer presented a particular behavior concerning to the following investigated properties: spatial hindrance, map of electrostatic potential (MEP), and the lowest unoccupied molecular orbital energy (E(LUMO)). Additionally, the findings suggested that the carbonyl group next to the active agent seems to be the most promising ester breaking point. (C) 2009 Elsevier B.V. All rights reserved.

Molecular modeling and QSAR studies of a set of indole and benzimidazole derivatives as H(4) receptor antagonists

Histamine is an important biogenic amine, which acts with a group of four G-protein coupled receptors (GPCRs), namely H(1) to H(4) (H(1)R - H(4)R) receptors. The actions of histamine at H(4)R are related to immunological and inflammatory processes, particularly in pathophysiology of asthma, and H(4)R ligands having antagonistic properties could be helpful as antiinflammatory agents. In this work, molecular modeling and QSAR studies of a set of 30 compounds, indole and benzimidazole derivatives, as H(4)R antagonists were performed. The QSAR models were built and optimized using a genetic algorithm function and partial least squares regression (WOLF 5.5 program). The best QSAR model constructed with training set (N = 25) presented the following statistical measures: r (2) = 0.76, q (2) = 0.62, LOF = 0.15, and LSE = 0.07, and was validated using the LNO and y-randomization techniques. Four of five compounds of test set were well predicted by the selected QSAR model, which presented an external prediction power of 80%. These findings can be quite useful to aid the designing of new anti-H(4) compounds with improved biological response.

Host-guest complexation of a nitroheterocyclic compound with cyclodextrins: a spectrofluorimetric and molecular modeling study

Nitroheterocyclic compounds (NC) were candidate drugs proposed for Chagas disease chemotherapy. In this study, we investigated the complexation of hydroxymethylnitrofurazone (NFOH), a potential antichagasic compound, with alpha-cyclodextrin (alpha-CD), beta-cyclodextrin (beta-CD), Hydroxypropyl-beta-cyclodextrin (HP-beta-CD), Dimethyl-beta-cyclodextrin (DM-beta-CD) and gamma-cyclodextrin (gamma-CD) by fluorescence spectroscopy and molecular modeling studies. Hildebrand-Benesi equation was used to calculate the formation constants of NFOH with cyclodextrins based on the fluorescence differences in the CDs solution. The complexing capacity of NFOH with different CDs was compared through the results of association constant according to the following order: DM-beta-CD > beta-CD > alpha-CD > HP-beta-CD > gamma-CD. Molecular modeling studies give support for the experimental assignments, in favor of the formation of an inclusion complex between cyclodextrins with NFOH. This is an important study to investigate the effects of different kinds of cyclodextrins on the inclusion complex formation with NFOH and to better characterize a potential formulations to be used as therapeutic options for the oral treatment of Chagas disease.

Design, synthesis, antimicrobial activity and molecular modeling studies of novel benzofuroxan derivatives against Staphylococcus aureus

Molecular modi. cation is a quite promising strategy in the design and development of drug analogs with better bioavailability, higher intrinsic activity and less toxicity. In the search of new leads with potential antimicrobial activity, a new series of 14 4-substituted [N`-(benzofuroxan-5-yl) methylene] benzohydrazides, nifuroxazide derivatives, were synthesized and tested against standard and multidrug-resistant Staphylococcus aureus strains. The selection of the substituent groups was based on physicochemical properties, such as hydrophobicity and electronic effect. These properties were also evaluated through the lipophilic and electrostatic potential maps, respectively, considering the compounds with better biological pro. le. Twelve compounds exhibited similar bacteriostatic activity against standard and multidrug-resistant strains. The most active compound was the 4-CF(3) substituted derivative, which presented a minimum inhibitory concentration (MIC) value of 14.6-13.1 mu g/mL, and a ClogP value of 1.87. The results highlight the benzofuroxan derivatives as potential leads for designing new future antimicrobial drug candidates. (C) 2009 Elsevier Ltd. All rights reserved.

Molecular modeling studies and in vitro bioactivity evaluation of a set of novel 5-nitro-heterocyclic derivatives as anti-T. cruzi agents

In this study, in vitro anti-T. cruzi activity assays of nifuroxazide (NX) analogues, such as 5-nitro-2-furfuryliden and 5-nitro-2-theniliden derivatives, were performed. A molecular modeling approach was also carried out to relate the lipophilicity potential ( LP) property and biological activity data. The majority of the NX derivatives showed increased anti-T. cruzi activity in comparison to the reference drug, benznidazole (BZN). Additionally, the 5-nitro-2-furfuryliden derivatives presented better pharmacological profile than the 5-nitro-2-theniliden analogues. The LP maps and corresponding ClogP values indicate that there is an optimum lipophilicity value, which must be observed in the design of new potential anti-T. cruzi agents. (c) 2009 Elsevier Ltd. All rights reserved.

Synthesis, antichagasic in vitro evaluation, cytotoxicity assays, molecular modeling and SAR/QSAR studies of a 2-phenyl-3-(1-phenyl-1H-pyrazol-4-yl)-acrylic acid benzylidene-carbohydrazide series

Chagas disease (American trypanosomiasis) is one of the most important parasitic diseases with serious social and economic impacts mainly on Latin America. This work reports the synthesis, in vitro trypanocidal evaluation, cytotoxicity assays, and molecular modeling and SAR/QSAR studies of a new series of N-phenylpyrazole benzylidene-carbohydrazides. The results pointed 6k (X = H, Y = p-NO(2), pIC(50) = 4.55 M) and 6l (X = F, Y = p-CN, pIC(50) = 4.27 M) as the most potent derivatives compared to crystal violet (pIC(50) = 3.77 M). The halogen-benzylidene-carbohydrazide presented the lowest potency whereas 6l showed the most promising pro. le with low toxicity (0% of cell death). The best equation from the 4D-QSAR analysis (Model 1) was able to explain 85% of the activity variability. The QSAR graphical representation revealed that bulky X-substituents decreased the potency whereas hydrophobic and hydrogen bond acceptor Y-substituents increased it. (C) 2008 Elsevier Ltd. All rights reserved.

RFID adoption: framework and survey in large Brazilian companies

Purpose - The purpose of this paper is to provide a framework for radio frequency identification (RFID) technology adoption considering company size and five dimensions of analysis: RFID applications, expected benefits business drivers or motivations barriers and inhibitors, and organizational factors. Design/methodology/approach - A framework for RFID adoption derived from literature and the practical experience on the subject is developed. This framework provides a conceptual basis for analyzing a survey conducted with 114 companies in Brazil. Findings - Many companies have been developing RFID initiatives in order to identify potential applications and map benefits associated with their implementation. The survey highlights the importance business drivers in the RFID implementation stage, and that companies implement RFID focusing on a few specific applications. However, there is a weak association between expected benefits and business challenges with the current level of RFID technology adoption in Brazil. Research limitations/implications - The paper is not exhaustive, since RFID adoption in Brazil is at early stages during the survey timeline. Originality/value - The main contribution of the paper is that it yields a framework for analyzing RFID technology adoption. The authors use this framework to analyze RFID adoption in Brazil, which proved to be a useful one for identifying key issues for technology adoption. The paper is useful to any researchers or practitioners who are focused on technology adoption, in particular, RFID technology.

Forward-looking versus recursive-dynamic modeling in climate policy analysis: A comparison

This paper develops a multi-regional general equilibrium model for climate policy analysis based on the latest version of the MIT Emissions Prediction and Policy Analysis (EPPA) model. We develop two versions so that we can solve the model either as a fully inter-temporal optimization problem (forward-looking, perfect foresight) or recursively. The standard EPPA model on which these models are based is solved recursively, and it is necessary to simplify some aspects of it to make inter-temporal solution possible. The forward-looking capability allows one to better address economic and policy issues such as borrowing and banking of GHG allowances, efficiency implications of environmental tax recycling, endogenous depletion of fossil resources, international capital flows, and optimal emissions abatement paths among others. To evaluate the solution approaches, we benchmark each version to the same macroeconomic path, and then compare the behavior of the two versions under a climate policy that restricts greenhouse gas emissions. We find that the energy sector and CO(2) price behavior are similar in both versions (in the recursive version of the model we force the inter-temporal theoretical efficiency result that abatement through time should be allocated such that the CO(2) price rises at the interest rate.) The main difference that arises is that the macroeconomic costs are substantially lower in the forward-looking version of the model, since it allows consumption shifting as an additional avenue of adjustment to the policy. On the other hand, the simplifications required for solving the model as an optimization problem, such as dropping the full vintaging of the capital stock and fewer explicit technological options, likely have effects on the results. Moreover, inter-temporal optimization with perfect foresight poorly represents the real economy where agents face high levels of uncertainty that likely lead to higher costs than if they knew the future with certainty. We conclude that while the forward-looking model has value for some problems, the recursive model produces similar behavior in the energy sector and provides greater flexibility in the details of the system that can be represented. (C) 2009 Elsevier B.V. All rights reserved.

Modeling volatile organic compounds (voc`s) adsorption onto cup-stacked carbon nanotubes (cscnt) using the linear driving force model

Modeling volatile organic compounds (voc`s) adsorption onto cup-stacked carbon nanotubes (cscnt) using the linear driving force model. Volatile organic compounds (VOC`s) are an important category of air pollutants and adsorption has been employed in the treatment (or simply concentration) of these compounds. The current study used an ordinary analytical methodology to evaluate the properties of a cup-stacked nanotube (CSCNT), a stacking morphology of truncated conical graphene, with large amounts of open edges on the outer surface and empty central channels. This work used a Carbotrap bearing a cup-stacked structure (composite); for comparison, Carbotrap was used as reference (without the nanotube). The retention and saturation capacities of both adsorbents to each concentration used (1, 5, 20 and 35 ppm of toluene and phenol) were evaluated. The composite performance was greater than Carbotrap; the saturation capacities for the composite was 67% higher than Carbotrap (average values). The Langmuir isotherm model was used to fit equilibrium data for both adsorbents, and a linear driving force model (LDF) was used to quantify intraparticle adsorption kinetics. LDF was suitable to describe the curves.

Local delivery of EGF-liposome mediated bone modeling in orthodontic tooth movement by increasing RANKL expression

Aims: It has long been demonstrated that epidermal growth factor (EGF) has catabolic effects oil bone. Thus. we examined the role of EGF in regulating mechanically induced bone modeling in a rat model of orthodontic tooth movement. Main methods: The maxillary first molars of rats were moved mesially using an orthodontic appliance attached to the maxillary incisor teeth. Rats were randomly divided into 4 groups: (G1) administration of PBS (Phosphate buffer saline Solution (n = 24); (G2) administration of empty liposomes (it = 24): (Q) administration 20 rig of EGF Solution (n = 24): and (G4) 20 ng of EGF-liposomes Solution (it = 24). Each Solution was injected in the mucosa of the left first molar adjacent to the appliance. At days 5, 10, 14 and 2 1 after drug administration. 6 animals of each group were sacrificed. Histomorphometric analysis was used to quantify osteoclasts (Tartrate-resistant acid phosphatase (TRAP) + cells) and tooth movement. Using immunohistochemistry assay we evaluated the RANKL (receptor activator of nuclear factor kappa B ligand) and epidermal growth factor receptor (EGFR) expression. Key findings: The EGF-liposome administration showed an increased tooth movement and osteoclast numbers compared to controls (p<0.05). This was correlated with intense RANKL expression. Both osteoblasts and osteoclasts expressed EGFR. Significance: Local delivery of EGF-liposome stimulates, osteoclastogenesis and tooth movement. (C) 2009 Elsevier Inc. All rights reserved.

Massage for Low Back Pain An Updated Systematic Review Within the Framework of the Cochrane Back Review Group

Study Design. Systematic Review. Objectives. To assess the effects of massage therapy for nonspecific low back pain. Summary of Background Data. Low back pain is one of the most common and costly musculoskeletal problems in modern society. Proponents of massage therapy claim it can minimize pain and disability, and speed return to normal function. Methods. We searched MEDLINE, EMBASE, CINAHL from their beginning to May 2008. We also searched the Cochrane Central Register of Controlled Trials (The Cochrane Library 2006, issue 3), HealthSTAR and Dissertation abstracts up to 2006. There were no language restrictions. References in the included studies and in reviews of the literature were screened. The studies had to be randomized or quasi-randomized trials investigating the use of any type of massage (using the hands or a mechanical device) as a treatment for nonspecific low back pain. Two review authors selected the studies, assessed the risk of bias using the criteria recommended by the Cochrane Back Review Group, and extracted the data using standardized forms. Both qualitative and meta-analyses were performed. Results. Thirteen randomized trials were included. Eight had a high risk and 5 had a low risk of bias. One study was published in German and the rest in English. Massage was compared to an inert therapy (sham treatment) in 2 studies that showed that massage was superior for pain and function on both short- and long-term follow-ups. In 8 studies, massage was compared to other active treatments. They showed that massage was similar to exercises, and massage was superior to joint mobilization, relaxation therapy, physical therapy, acupuncture, and self-care education. One study showed that reflexology on the feet had no effect on pain and functioning. The beneficial effects of massage in patients with chronic low back pain lasted at least 1 year after the end of the treatment. Two studies compared 2 different techniques of massage. One concluded that acupuncture massage produces better results than classic (Swedish) massage and another concluded that Thai massage produces similar results to classic (Swedish) massage. Conclusion. Massage might be beneficial for patients with subacute and chronic nonspecific low back pain, especially when combined with exercises and education. The evidence suggests that acupuncture massage is more effective than classic massage, but this need confirmation. More studies are needed to confirm these conclusions, to assess the impact of massage on return-to-work, and to determine cost-effectiveness of massage as an intervention for low back pain.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

A NEUROECONOMIC MODELING OF ATTENTION-DEFICIT/HYPERACTIVITY DISORDER (ADHD)

In this paper we present a new neuroeconomics model for decision-making applied to the Attention-Deficit/Hyperactivity Disorder (ADHD). The model is based on the hypothesis that decision-making is dependent on the evaluation of expected rewards and risks assessed simultaneously in two decision spaces: the personal (PDS) and the interpersonal emotional spaces (IDS). Motivation to act is triggered by necessities identified in PDS or IDS. The adequacy of an action in fulfilling a given necessity is assumed to be dependent on the expected reward and risk evaluated in the decision spaces. Conflict generated by expected reward and risk influences the easiness (cognitive effort) and the future perspective of the decision-making. Finally, the willingness (not) to act is proposed to be a function of the expected reward (or risk), adequacy, easiness and future perspective. The two most frequent clinical forms are ADHD hyperactive (AD/HDhyp) and ADHD inattentive (AD/HDdin). AD/HDhyp behavior is hypothesized to be a consequence of experiencing high rewarding expectancies for short periods of time, low risk evaluation, and short future perspective for decision-making. AD/HDin is hypothesized to be a consequence of experiencing high rewarding expectancies for long periods of time, low risk evaluation, and long future perspective for decision-making.

A Dynamical Modeling to Study the Adaptive Immune System and the Influence of Antibodies in the Immune Memory

Immunological systems have been an abundant inspiration to contemporary computer scientists. Problem solving strategies, stemming from known immune system phenomena, have been successfully applied to chall enging problems of modem computing. Simulation systems and mathematical modeling are also beginning use to answer more complex immunological questions as immune memory process and duration of vaccines, where the regulation mechanisms are not still known sufficiently (Lundegaard, Lund, Kesmir, Brunak, Nielsen, 2007). In this article we studied in machina a approach to simulate the process of antigenic mutation and its implications for the process of memory. Our results have suggested that the durability of the immune memory is affected by the process of antigenic mutation.and by populations of soluble antibodies in the blood. The results also strongly suggest that the decrease of the production of antibodies favors the global maintenance of immune memory.