Comparative evaluation of the antimicrobial activity of Citrullus colocynthis immature fruit and seed organic extracts

Gastrointestinal problems, dermatological, gynaecological and pulmonary infections produced by micro-organisms are widespread in the entire globe. The treatment of these infections is mainly based on the use of synthetic drugs which have lost, in recent years, their effectiveness, due to the development of resistant strains and the rise of opportunistic fungal infections. Tunisian traditional medicine is a potential source of new remedies namely, Citrullus colocynthis Schrad. (Cucurbitaceae). Lyophilized aqueous and organic extracts from immature fruits and seeds were screened for activity against gram-negative (Escherichia coli, Pseudomonas aeruginosa, Salmonella typhimurium, Vibrio parahaemolyticus and Vibrio alginolyticus) and gram-positive (Enterococcus faecalis, Staphylococcus aureus, Staphylococcus epidermidis, Listeria monocytogenes and Micrococcus luteus) bacteria and various Candida spp. (Candida glabrata, Candida albicans, Candida parapsilosis and Candida kreusei). Minimal inhibition concentrations (MICs) and minimal bactericidal/fungicidal  concentrations (MBCs/MFCs) were used to investigate the antimicrobial activity. Extracts from the two C. colocynthis Schrad. organs, at immature state, inhibited the growth of all the tested strains. The highest antibacterial effects were obtained against E. coli (MIC = 0.006 mg/ml) with the fruit methanol and the seed petroleum extracts. Regarding the anticandidal activity assessment, seed extracts showed the lowest results. This study demonstrated the broad spectrum antimicrobial activity of C. colocynthis immature fruit and seed extracts.Key words: Citrullus colocynthis Schrad, fruits, seeds, organic extracts, antibacterial, anticandidal

antioxidant and anticandidal activities of the tunisian haplophyllum tuberculatum forssk a juss essential oils

Abstract Haplophyllum tuberculatum Forssk. is a medicinal plant growing in Tunisia. It is widely used in traditional medicine against gastro-intestinal problems, fevers, ear infections and rheumatisms. The present investigation evaluated the effects of leaves, stems and leaves + stems essential oils of Haplophyllum tuberculatum Forssk. and of their pure compounds on free radicals as well as their anticandidal activities. Screening for the antioxidant activity of the oils, R-(+)-limonene, S-(−)-limonene and 1-octanol was conducted by DPPH, ABTS and β-carotene/linoleic acid radical scavenging assays. The essentials oils and their compounds were screened for antifungal activity against four Candida species: Candida albicans ATCC 90028; Candida glabrata ATCC 90030; Candida parapsilosis ATCC 27853 and Candida krusei ATCC 6258. When compared with ascorbic acid as standard, it was found that the essential oils have a significant inhibition in scavenging free radicals, resulting in an important IC50. The pure compounds were inactive against the free radicals. The anticandidal test results showed that leaves, stems and leaves + stems oils strongly inhibited the growth of Candida krusei at 30 μg/mL leaves oils and 70 μg/mL for other oils and that moderately of the 3 other Candida species. The pure compound, 1-octanol, was active one against the candida species, with MIC-values between 0.07 and 1.25 mg/mL. In all in vitro assays, a significant correlation existed between the concentrations of the essential oils, the percentage inhibition of free radicals and of the growth inhibitory of tested candida species. The results indicate the essential oils may be applied for treating diseases related to free radicals, potentially to prevent cancer development and as an antifungal agent against Candida

Inhibitory Activity of Leaves Extracts of Citrullus colocynthis Schrad. on HT29 Human Colon Cancer Cells

Aims: Citrullus colocynthis is a plant endemic in Asia, Africa and in the Mediterranean basin. It is used in folk medicine against infections, inflammations and cardiovascular and immune-related diseases. There are further evidences of the use of Citrullus colocynthis Schrad in the treatment of cancer in traditional practices. The present study aimed to determine the potential antiproliferative effects of different Citrullus colocynthis leaf extracts on human cancer cells. Methodology: Antiproliferative and antioxidant effects on HT-29 human colon cancer cells were detected by MTS assay and a modified protocol of the alkaline Comet assay. In vitro antioxidant activities of different leaf extracts were evaluated through DPPH, \u3b2-carotene/linoleic acid and reducing power assays. Results: The leaf chloroform extract exhibited the higher cell growth inhibitory activity without induction of DNA damage; it showed to be able to significantly decrease DNA damage induced by H2O2 (100 M). This antioxidant activity seems to be comparable to that of vitamin C (1 mM). Ethyl acetate, acetone and methanol leaf extracts showed to be the most effective in reducing the stable free DPPH radical (IC50 =113 g/ml), in transforming the Fe3+ to Fe2+ (IC50 = 134 \ub5g/ml) and in inducing linoleic acid oxidation with an inhibition of 31.9 %. Conclusion: Our results confirm the antiproliferative potential of Citrullus colocynthis Schrad. on human cancer cells

Bayesian reconstruction of binary media with unresolved fine-scale spatial structures

We present a Bayesian technique to estimate the fine-scale properties of a binary medium from multiscale observations. The binary medium of interest consists of spatially varying proportions of low and high permeability material with an isotropic structure. Inclusions of one material within the other are far smaller than the domain sizes of interest, and thus are never explicitly resolved. We consider the problem of estimating the spatial distribution of the inclusion proportion, F(x), and a characteristic length-scale of the inclusions, δ, from sparse multiscale measurements. The observations consist of coarse-scale (of the order of the domain size) measurements of the effective permeability of the medium (i.e., static data) and tracer breakthrough times (i.e., dynamic data), which interrogate the fine scale, at a sparsely distributed set of locations. This ill-posed problem is regularized by specifying a Gaussian process model for the unknown field F(x) and expressing it as a superposition of Karhunen–Loève modes. The effect of the fine-scale structures on the coarse-scale effective permeability i.e., upscaling, is performed using a subgrid-model which includes δ as one of its parameters. A statistical inverse problem is posed to infer the weights of the Karhunen–Loève modes and δ, which is then solved using an adaptive Markov Chain Monte Carlo method. The solution yields non-parametric distributions for the objects of interest, thus providing most probable estimates and uncertainty bounds on latent structures at coarse and fine scales. The technique is tested using synthetic data. The individual contributions of the static and dynamic data to the inference are also analyzed.United States. Dept. of Energy. National Nuclear Security Administration (Contract DE-AC04_94AL85000

Surrogate and reduced-order modeling: a comparison of approaches for large-scale statistical inverse problems [Chapter 7]

Solution of statistical inverse problems via the frequentist or Bayesian approaches described in earlier chapters can be a computationally intensive endeavor, particularly when faced with large-scale forward models characteristic of many engineering and science applications. High computational cost arises in several ways. First, thousands or millions of forward simulations may be required to evaluate estimators of interest or to characterize a posterior distribution. In the large-scale setting, performing so many forward simulations is often computationally intractable. Second, sampling may be complicated by the large dimensionality of the input space--as when the inputs are fields represented with spatial discretizations of high dimension--and by nonlinear forward dynamics that lead to multimodal, skewed, and/or strongly correlated posteriors. In this chapter, we present an overview of surrogate and reduced order modeling methods that address these computational challenges. For illustration, we consider a Bayesian formulation of the inverse problem. Though some of the methods we review exploit prior information, they largely focus on simplifying or accelerating evaluations of a stochastic model for the data, and thus are also applicable in a frequentist context.Sandia National Laboratories (Laboratory Directed Research and Development (LDRD) program)United States. Dept. of Energy (Contract DE-AC04-94AL85000)Singapore-MIT Alliance Computational Engineering ProgrammeUnited States. Dept. of Energy (Award Number DE-FG02-08ER25858 )United States. Dept. of Energy (Award Number DESC00025217

Phthalocyanine-based dumbbell-shaped molecule: synthesis, structure and charge transport studies

International audienceWe describe the synthesis of a fully conjugated donor-acceptor-donor triad (ZnPc-BTD-ZnPc) made of zinc phthalocyanine donor fragments (ZnPc) at both ends of a benzothiadiazole-based central dye (BTD). The molecule exhibits a broad absorption in the whole visible range. The introduction of sterically demanding alkoxy chains to the ZnPc fragments is found to limit the molecular organization to a short-range columnar order and the charge-carrier mobility to moderate values, but provides outstanding solubilities in organic solvents

Diffeomorphic random sampling using optimal information transport

In this article we explore an algorithm for diffeomorphic random sampling of nonuniform probability distributions on Riemannian manifolds. The algorithm is based on optimal information transport (OIT)---an analogue of optimal mass transport (OMT). Our framework uses the deep geometric connections between the Fisher-Rao metric on the space of probability densities and the right-invariant information metric on the group of diffeomorphisms. The resulting sampling algorithm is a promising alternative to OMT, in particular as our formulation is semi-explicit, free of the nonlinear Monge--Ampere equation. Compared to Markov Chain Monte Carlo methods, we expect our algorithm to stand up well when a large number of samples from a low dimensional nonuniform distribution is needed.Comment: 8 pages, 3 figure

Meningococcal disease in children in Merseyside, England:a 31 year descriptive study

Meningococcal disease (MCD) is the leading infectious cause of death in early childhood in the United Kingdom, making it a public health priority. MCD most commonly presents as meningococcal meningitis (MM), septicaemia (MS), or as a combination of the two syndromes (MM/MS). We describe the changing epidemiology and clinical presentation of MCD, and explore associations with socioeconomic status and other risk factors. A hospital-based study of children admitted to a tertiary children's centre, Alder Hey Children's Foundation Trust, with MCD, was undertaken between 1977 to 2007 (n = 1157). Demographics, clinical presentations, microbiological confirmation and measures of deprivation were described. The majority of cases occurred in the 1-4 year age group and there was a dramatic fall in serogroup C cases observed with the introduction of the meningococcal C conjugate (MCC) vaccine. The proportion of MS cases increased over the study period, from 11% in the first quarter to 35% in the final quarter. Presentation with MS (compared to MM) and serogroup C disease (compared to serogroup B) were demonstrated to be independent risk factors for mortality, with odds ratios of 3.5 (95% CI 1.18 to 10.08) and 2.18 (95% CI 1.26 to 3.80) respectively. Cases admitted to Alder Hey were from a relatively more deprived population (mean Townsend score 1.25, 95% CI 1.09 to 1.41) than the Merseyside reference population. Our findings represent one of the largest single-centre studies of MCD. The presentation of MS is confirmed to be a risk factor of mortality from MCD. Our study supports the association between social deprivation and MCD

Antioxidant and antimicrobial phenolic compounds from extracts of cultivated and wild-grown Tunisian Ruta chalepensis

The antioxidant and antibacterial activities of phenolic compounds from cultivated and wild Tunisian Ruta chalepensis L. leaves, stems, and flowers were assessed. The leaves and the flowers exhibited high but similar total polyphenol, flavonoid, and tannin content. Moreover, two organs showed strong, although not significantly different, total antioxidant activity, 2,2-diphenyl-1-picrylhydrazyl scavenging ability, and reducing power. Investigation of the phenolic composition showed that vanillic acid and coumarin were the major compounds in the two organs, with higher percentages in the cultivated organs than in the spontaneous organs. Furthermore, R. chalepensis extracts showed marked antibacterial properties against human pathogen strains, and the activity was organ- and origin-dependent. Spontaneous stems had the strongest activity against Pseudomonas aeruginosa. From these results, it was concluded that domestication of Ruta did not significantly affect its chemical composition and consequently the possibility of using R. chalpensis organs as a potential source of natural antioxidants and as an antimicrobial agent in the food industry

An approximate empirical Bayesian method for large-scale linear-Gaussian inverse problems

We study Bayesian inference methods for solving linear inverse problems, focusing on hierarchical formulations where the prior or the likelihood function depend on unspecified hyperparameters. In practice, these hyperparameters are often determined via an empirical Bayesian method that maximizes the marginal likelihood function, i.e., the probability density of the data conditional on the hyperparameters. Evaluating the marginal likelihood, however, is computationally challenging for large-scale problems. In this work, we present a method to approximately evaluate marginal likelihood functions, based on a low-rank approximation of the update from the prior covariance to the posterior covariance. We show that this approximation is optimal in a minimax sense. Moreover, we provide an efficient algorithm to implement the proposed method, based on a combination of the randomized SVD and a spectral approximation method to compute square roots of the prior covariance matrix. Several numerical examples demonstrate good performance of the proposed method