Antimicrobial effects of folk medicinal plants from the North of Iran against Mycobacterium tuberculosis

Background: Medicinal plants have been used traditionally in Golestan province (north of Iran), against Mycobacterium tuberculosis or the clinical signs of tuberculosis (TB). Objectives: This study aimed to define the inhibitory effects of ethanolic extracts of six of these medicinal plants against Mycobacterium tuberculosis. Materials and Methods: Peganum harmala (seed extract), Punica granatum (peel extract), Digitalis sp. (leaf extract), fruit extract of Citrus lemon, Rosa canina and Berberis vulgaris were extracted in ethanol and their activity against M. tuberculosis isolates were determined by the agar diffusion method. The zone of inhibition (at 200 to 1.6 mg/mL) was measured and the results were compared with isoniazid and rifampin as standard positive controls. Also the concentration of vitamin C of each the extracts was evaluated. Results: The ethanolic extract of Peganum harmala seed and Punica granatum peel exhibited potential activity against all M. tuberculosis isolates with mean inhibitory zone of 18.7 and 18.8 mm, at 200 mg/mL concentration. The mean inhibitory zone around isoniazid and rifampinwere 19.2 and 18.8 mm. Ethanolic extract of Citrus lemon showed moderate inhibitory activity only against sensitive (non MDR; non multi drug resistant) strains of M. tuberculosis, and Digitalis sp. showed inhibitory effects on five isolates. Ascorbic acid content was 43.3 mg/dL in Punica granatum and Digitalis sp. and only 9.1 mg/dL in ethanolic extract of Peganum harmala. Conclusions: The highest content of vitamin C was observed in the extract of Punica granatum, which was observed to be highly active against Mycobacterium tuberculosis, while the P. harmala must have contained other phytochemical constituents that contributed to the anti-tuberculosis effects of this plant. Our findings showed that ethanolic extracts of P. granatum and P. harmala had anti-TB effects comparable to isoniazid and rifampin and can be good candidates for novel and safe natural products against tuberculosis. © 2015, Pediatric Infections Research Center

EFFECT OF CALCINATION TEMPERATURE OF TUNISIAN CLAYS ON THE PROPERTIES OF GEOPOLYMERS

Geopolymers are amorphous three dimensional aluminosilicate materials that may be synthesized at room or slightly higher temperature by alkaline activation of aluminosilicates obtained from industrial wastes, calcined clays and natural minerals. Among the different family of geopolymers, two Tunisian clays (a kaolinite clay from Tabarka and illito/kaolinitic clay from Medenine) are tested for their feasibility of geopolymers at low temperature. The unfired and calcined clays were dissolved in strongly alkaline solution in order to produce consolidated materials whose pastes were characterized by their compressive strength. Hardened geopolymer samples were also submitted to X-Ray diffraction, FTIR spectroscopy and scanning electron microscopy analyses. The geopolymer strength is related to the structure and reactivity of the clay generated by thermal treatment and to the role of associated minerals in clays. The amorphous character of obtained geopolymers and the displacement of the IR wavenumber are signature of geopolymerisation reaction

How Accurate Are Blood (or Breath) Tests for Identifying Self-Reported Heavy Drinking Among People with Alcohol Dependence?

AIMS: Managing patients with alcohol dependence includes assessment for heavy drinking, typically by asking patients. Some recommend biomarkers to detect heavy drinking but evidence of accuracy is limited. METHODS: Among people with dependence, we assessed the performance of disialo-carbohydrate-deficient transferrin (%dCDT, ≥1.7%), gamma-glutamyltransferase (GGT, ≥66 U/l), either %dCDT or GGT positive, and breath alcohol (> 0) for identifying 3 self-reported heavy drinking levels: any heavy drinking (≥4 drinks/day or >7 drinks/week for women, ≥5 drinks/day or >14 drinks/week for men), recurrent (≥5 drinks/day on ≥5 days) and persistent heavy drinking (≥5 drinks/day on ≥7 consecutive days). Subjects (n = 402) with dependence and current heavy drinking were referred to primary care and assessed 6 months later with biomarkers and validated self-reported calendar method assessment of past 30-day alcohol use. RESULTS: The self-reported prevalence of any, recurrent and persistent heavy drinking was 54, 34 and 17%. Sensitivity of %dCDT for detecting any, recurrent and persistent self-reported heavy drinking was 41, 53 and 66%. Specificity was 96, 90 and 84%, respectively. %dCDT had higher sensitivity than GGT and breath test for each alcohol use level but was not adequately sensitive to detect heavy drinking (missing 34-59% of the cases). Either %dCDT or GGT positive improved sensitivity but not to satisfactory levels, and specificity decreased. Neither a breath test nor GGT was sufficiently sensitive (both tests missed 70-80% of cases). CONCLUSIONS: Although biomarkers may provide some useful information, their sensitivity is low the incremental value over self-report in clinical settings is questionable

Sr0.9_{0.9}K0.1_{0.1}Zn1.8_{1.8}Mn0.2_{0.2}As2_{2}: a ferromagnetic semiconductor with colossal magnetoresistance

A bulk diluted magnetic semiconductor (Sr,K)(Zn,Mn)$_{2}$As$_{2}$ was synthesized with decoupled charge and spin doping. It has a hexagonal CaAl$_{2}$Si$_{2}$-type structure with the (Zn,Mn)$_{2}$As$_{2}$ layer forming a honeycomb-like network. Magnetization measurements show that the sample undergoes a ferromagnetic transition with a Curie temperature of 12 K and \revision{magnetic moment reaches about 1.5 $\mu_{B}$/Mn under $\mu_0H$ = 5 T and $T$ = 2 K}. Surprisingly, a colossal negative magnetoresistance, defined as $[\rho(H)-\rho(0)]/\rho(0)$, up to $-$38\% under a low field of $\mu_0H$ = 0.1 T and to $-$99.8\% under $\mu_0H$ = 5 T, was observed at $T$ = 2 K. The colossal magnetoresistance can be explained based on the Anderson localization theory.Comment: Accepted for publication in EP

Potential Role of Ultrafine Particles in Associations between Airborne Particle Mass and Cardiovascular Health

Numerous epidemiologic time-series studies have shown generally consistent associations of cardiovascular hospital admissions and mortality with outdoor air pollution, particularly mass concentrations of particulate matter (PM) ≤2.5 or ≤10 μm in diameter (PM(2.5), PM(10)). Panel studies with repeated measures have supported the time-series results showing associations between PM and risk of cardiac ischemia and arrhythmias, increased blood pressure, decreased heart rate variability, and increased circulating markers of inflammation and thrombosis. The causal components driving the PM associations remain to be identified. Epidemiologic data using pollutant gases and particle characteristics such as particle number concentration and elemental carbon have provided indirect evidence that products of fossil fuel combustion are important. Ultrafine particles < 0.1 μm (UFPs) dominate particle number concentrations and surface area and are therefore capable of carrying large concentrations of adsorbed or condensed toxic air pollutants. It is likely that redox-active components in UFPs from fossil fuel combustion reach cardiovascular target sites. High UFP exposures may lead to systemic inflammation through oxidative stress responses to reactive oxygen species and thereby promote the progression of atherosclerosis and precipitate acute cardiovascular responses ranging from increased blood pressure to myocardial infarction. The next steps in epidemiologic research are to identify more clearly the putative PM casual components and size fractions linked to their sources. To advance this, we discuss in a companion article (Sioutas C, Delfino RJ, Singh M. 2005. Environ Health Perspect 113:947–955) the need for and methods of UFP exposure assessment

Identification of illustrators

This paper is motivated by a book in which artists and illustrators from all over the world offer their personal interpretations of the declaration of human rights in pictures [1]. It was enthusiastic for a young reader to see an illustration of an artist that he already knows from his books . The characters were different, the topic was irrelevant, but still it was easy to identify the illustrators based on the style of the illustration. Inspired by the human's ability to identify illustrators, in this study we propose a method that can automatically learn to distinguish illustrations of different illustrators using computer vision techniques. © 2012 Springer-Verlag

Dental Education Economics: Challenges and Innovative Strategies

This article reviews current dental education economic challenges such as increasing student tuition and debt, decreasing funds for faculty salaries and the associated faculty shortage, and the high cost of clinic operations and their effect on the future of dentistry. Management tactics to address these issues are also reviewed. Despite recent efforts to change the clinical education model, implementation of proposed faculty recruitment and compensation programs, and creation of education- corporate partnerships, the authors argue that the current economics of public dental education is not sustainable. To remain viable, the dental education system must adopt transformational actions to re-engineer the program for long-term stability. The proposed re-engineering includes strategies in the following three areas: 1) educational process redesign, 2) reduction and redistribution of time in dental school, and 3) development of a regional curriculum. The intent of these strategies is to address the financial challenges, while educating adequate numbers of dentists at a reasonable cost to both the student and the institution in addition to maintaining dental education within research universities as a learned profession

Sampling-based Algorithms for Optimal Motion Planning

During the last decade, sampling-based path planning algorithms, such as Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness. However, little effort has been devoted to the formal analysis of the quality of the solution returned by such algorithms, e.g., as a function of the number of samples. The purpose of this paper is to fill this gap, by rigorously analyzing the asymptotic behavior of the cost of the solution returned by stochastic sampling-based algorithms as the number of samples increases. A number of negative results are provided, characterizing existing algorithms, e.g., showing that, under mild technical conditions, the cost of the solution returned by broadly used sampling-based algorithms converges almost surely to a non-optimal value. The main contribution of the paper is the introduction of new algorithms, namely, PRM* and RRT*, which are provably asymptotically optimal, i.e., such that the cost of the returned solution converges almost surely to the optimum. Moreover, it is shown that the computational complexity of the new algorithms is within a constant factor of that of their probabilistically complete (but not asymptotically optimal) counterparts. The analysis in this paper hinges on novel connections between stochastic sampling-based path planning algorithms and the theory of random geometric graphs.Comment: 76 pages, 26 figures, to appear in International Journal of Robotics Researc