In vitro activity of fosfomycin against uropathogen multi-drug resistant (MDR) Pseudomonas aeruginosa and Acinetobacter baumannii

Urinary tract infections caused by multidrug resistant Gram negative bacilli constitute a major global healthcare problem. Fosfomycin is considered the best treatment option for such infections. Urine samples were collected and cultured in a tertiary care hospital (Urology). Identification of these uropathogens and their antibiotic sensitivity screening were performed according to CLSI guidelines. Urine samples (n=436) were selected in which Ps. aeruginosa and Acinetobacter baumannii werefound to be the significant pathogens and treated-exposed to fosfomycin. Sixty six (15%) were identified as Acinetobacter baumannii, Ps. aeruginosa n=370(85%). Forty four percent of all Ps. aeruginosa were found to be multidrug resistant while 48.5% of the Acinetobacter baumannii strains were found multidrug resistant. Polymyxin B was found to be the most effective drug (100%) against all uropathogens and fosfomycin was found effective against 73% of the multidrug resistant Acinetobacter baumannii isolates and 70% of the multidrug resistant Pseudomonas aeruginosa strains. It may be concluded that  antimicrobial  activity (in vitro) of fosfomycin, especially against MDR uropathogens, is very effective.Keywords: Fosfomycin, Multidrug resistant Gram negative bacilli, Urinary tract infections, Ps.  aeruginosa, Acinetobacter baumannii L’ACTIVITE IN VITRO DE LA FOSFOMYCINE CONTRE UROPATHOGEN MULTI-DRUG RESISTANT (MDR)PSEUDOMONAS AERUGINOSA ET ACINETOBACTER BAUMANNIILes infections des voies urinaires causées par les bacilles de multi résistants Gram négatifs, constituent un problème majeur de sante mondiale. Fosfomycine est considéré comme la meilleure option de traitement pour telles infections. Les échantillons d’urine ont été recueillis et cultives dans un hôpital de soins tertiaires. Identification de ces uropathogènes et programmation de leur sensibilité aux  antibiotiques ont été réalisés selon les directives (CLSI). Les échantillons d’urine (n = 436) ont été choisis dans laquelle Ps. aeruginosa et Acinetobacter baumannii se sont trouves être l’agent pathogène important et traités – exposés a Fosfomycine. Soixante – six (15%) ont été identifies comme  Acinetobacter baumannii, Ps. aeruginosa = 370 (85%). Quarante – quatre pourcent de tous les Ps. aeruginosa se sont trouvés être multi résistants et 48,5% des souches Acinetobacter baumannii sesont trouves multi résistants. Polymyxine B a été trouvé d’être le médicament le plus efficace (100%) contre tous les uropathogènes et Fosfomycine a été trouvé efficace contre 73% des isolats de multi résistants Acinetobacter baumannii et 70% des souches de multi résistants Pseudomonas aeruginosa. On peut conclure que l’activité antimicrobienne (in vitro) de Fosfomycine est très efficace, particulièrement contre les uropathogenes MDR.Mots – clés : Fosfomycine, les bacilles de Multi résistants Gram négatifs, les infections des voies urinaires, Ps. aeruginosa, Acinetobacter baumannii.

Designing an augmented reality exhibition: Leonardo's Impossible Machines

This paper discusses the origins, development and results of the animated and augmented reality aspects of the exhibition ‘Leonardo’s Impossible Machines’ that was developed at Ravensbourne University London and Birkbeck, University of London, with support from the Museo Galileo. The exhibition included novel reconstructions and visualisations of Leonardo’s perpetual motion machines from the Codex Forster, and the process is explained here, along with the challenges of mounting a combined physical and AR show

Pharmacokinetic Studies on Metoprolol - Eudragit Matrix Tablets and Bioequivalence Consideration with Mepressor®

Purpose: To investigate the pharmacokinetics of of a developed metoprolol and a reference standard (Mepressor®).Methods: Metoprolol tartrate-loaded Eudragit® FS microparticles were formulated and compressed into tablets. The tablets were tested for their physicochemical properties according to United States Pharmacopoeia (USP) criteria. In vivo studies of the formulations were carried out in 28 young healthy fasting male volunteers based on a randomized open label 4×4 crossover study design with a washout period of 7 days.Results: In vitro tests showed that the developed and reference standard of metoprolol tablets met compendia (USP) requirements. Zero order release of drug was observed from all the tablets. In vivo data demonstrated that there were significant (p < 0.05) differences in tmax, Cmax, MRT, AUC0−t, and AUC0–∞ between the reference and test (developed) formulations. However, the 90 % class interval for the mean ratios of the ln-transformed Cmax, AUC0-t and AUC0-α for the reference, T1, T2, and T3 lied in the bioequivalence range (80 to 125 %) indicating bioequivalence between the compared formulations.                  Conclusion: It can be concluded from this single-dose study that the reference and test (developed) formulations met the predetermined criteria for bioequivalence in young healthy fasting male human subjects as the bioequivalence factor lie in the pre-determined limits for bioequivalence. Thus, the two formulations can be considered bioequivalent.Keywords: Metoprolol tartrate, Eudragit® FS, Microparticles, Bioavailability, Pharmacokinetics

Applicability of organic carbonates as green solvents for membrane preparation

Common polar aprotic solvents, like N,N-dimethylformamide (DMF), 1,4-dioxane, N,N-dimethylacetamide (DMA) and tetrahydrofuran (THF), are excellent for membrane preparation. However, due to their toxicity or volatile nature, it would be useful to replace them by “greener” solvents for environmental and health reasons. In this work, organic carbonates, obtainable through carbon dioxide fixation, were selected as green solvents to find possible use in membrane preparation. Polymer solubility experiments were performed to screen their applicability in the phase inversion process to create porous membrane with appropriate structures and selectivities. Hansen solubility parameters were used to rationalize the solubility results. Membrane morphology and pore structure were characterized using scanning electron microscopy (SEM), while the performance of the membrane was determined by applying a 35 μM aqueous feed solution of rose bengal (RB, MW = 1017 Da) to screen the potential of these polymer/organic carbonate systems toward nanofiltration application

Borane-ctalyzed stereoselective C–H insertion, cyclopropanation, and ring-opening reactions

Lewis acidic boranes have been shown to be effective metal-free catalysts for highly selective reactions of donor-acceptor diazo compounds to a range of substrates. The reactions of α-aryl α-diazoesters with nitrogen heterocycles indole or pyrrole selectively generate C3 and C2 C–H insertion products, respectively, in good to excellent yields even when using unprotected indoles. Alternatively, benzofuran, indene, and alkene substrates give exclusively cyclopropanated products with α-aryl α-diazoesters, whereas the reactions with furans lead to ring-opening. Comprehensive theoretical calculations have been used to explain the differing reactivities and high selectivities of these reactions. Overall, this work demonstrates the selective metal-free catalytic reactions of α-aryl α-diazoesters with (hetero)cycles and alkenes. This simple, mild reaction protocol represents an alternative to the commonly used precious metal systems and may provide future applications in the generation of biologically active compounds

A Comprehensive Insight into Game Theory in relevance to Cyber Security

The progressively ubiquitous connectivity in the present information systems pose newer challenges tosecurity. The conventional security mechanisms have come a long way in securing the well-definedobjectives of confidentiality, integrity, authenticity and availability. Nevertheless, with the growth in thesystem complexities and attack sophistication, providing security via traditional means can beunaffordable. A novel theoretical perspective and an innovative approach are thus required forunderstanding security from decision-making and strategic viewpoint. One of the analytical tools whichmay assist the researchers in designing security protocols for computer networks is game theory. Thegame-theoretic concept finds extensive applications in security at different levels, including thecyberspace and is generally categorized under security games. It can be utilized as a robust mathematicaltool for modelling and analyzing contemporary security issues. Game theory offers a natural frameworkfor capturing the defensive as well as adversarial interactions between the defenders and the attackers.Furthermore, defenders can attain a deep understanding of the potential attack threats and the strategiesof attackers by equilibrium evaluation of the security games. In this paper, the concept of game theoryhas been presented, followed by game-theoretic applications in cybersecurity including cryptography.Different types of games, particularly those focused on securing the cyberspace, have been analysed andvaried game-theoretic methodologies including mechanism design theories have been outlined foroffering a modern foundation of the science of cybersecurity

Diabetes Detection System by Mixing Supervised and Unsupervised Algorithms

Diabetes mellitus is also called gestational diabetes when a woman has high blood sugar while pregnant. It can show up at any time during pregnancy and cause problems for the mother and baby during or after the pregnancy. If the risks are found and dealt with as soon as possible, there is a chance that they can be reduced. The healthcare system is one of the many parts of our daily lives that are being rethought thanks to the creation of intelligent systems by machine learning algorithms. In this article, a hybrid prediction model is suggested to determine if a woman has gestational diabetes. The recommended model reduces the amount of data using the K-means clustering method. Predictions are made using several classification methods, such as decision trees, random forests, SVM, KNN, logistic regression, and naive Bayes. The results show that accuracy increases when clustering and classification are used together