111 research outputs found

    Development of biodegradable, cellulose-based, essential oil and chitosan drug delivery systems for cosmetic mask applications

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    The goal of this research was the development of cellulose-based biodegradable drug delivery systems solutions for cosmetic mask applications. Cellulose-based materials derived from natural renewable sources provide a sustainable alternative to nonwoven cosmetic masks derived from nondegradable fossil-based raw materials. An experimental design was executed to assemble the 3D cellulose fibres matrix and the water in oil emulsion comprising the active molecules from Mentha piperita L. Two types of biopolymeric additives were used, one derived from a nano/micro fibrillated cellulose pulp and another one including chitosan. A 3D computational simulation study was performed to enhance porosity and strength properties. The results indicated that the cosmetic face mask optimized prototypes, made from a biodegradable 3D matrix of cellulose fibres and active molecules, are suitable for dermic usePostprint (published version

    A characterization of the multivariate excess wealth ordering

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    In this paper, some new properties of the upper-corrected orthant of a random vector are proved. The univariate right-spread or excess wealth function, introduced by Fernández-Ponce et al. (1996), is extended to multivariate random vectors, and some properties of this multivariate function are studied. Later, this function was used to define the excess wealth ordering by Shaked and Shanthikumar (1998) and Fernández-Ponce et al. (1998). The multivariate excess wealth function enable us to define a new stochastic comparison which is weaker than the multivariate dispersion orderings. Also, some properties relating the multivariate excess wealth order with stochastic dependence are describe

    Stimulation of the beta-2-adrenergic receptor with salbutamol activates human brown adipose tissue

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    While brown adipose tissue (BAT) is activated by the beta-3-adrenergic receptor (ADRB3) in rodents, in human brown adipocytes, the ADRB2 is dominantly present and responsible for noradrenergic activation. Therefore, we performed a randomized double-blinded crossover trial in young lean men to compare the effects of single intravenous bolus of the ADRB2 agonist salbutamol without and with the ADRB1/2 antago-nist propranolol on glucose uptake by BAT, assessed by dynamic 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography-computed tomography scan (i.e., primary outcome). Salbutamol, compared with salbutamol with propranolol, increases glucose uptake by BAT, without affecting the glucose uptake by skeletal muscle and white adipose tissue. The salbutamol-induced glucose uptake by BAT positively asso-ciates with the increase in energy expenditure. Notably, participants with high salbutamol-induced glucose uptake by BAT have lower body fat mass, waist-hip ratio, and serum LDL-cholesterol concentration. In conclusion, specific ADRB2 agonism activates human BAT, which warrants investigation of ADRB2 activation in long-term studies (EudraCT: 2020-004059-34).NWO091506191007

    Azithromycin to Prevent Pertussis in Household Contacts, Catalonia and Navarre, Spain, 2012-2013

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    We retrospectively assessed the effectiveness of azithromycin in preventing transmission of pertussis to a patient's household contacts. We also considered the duration between symptom onset in the primary patient and azithromycin administration. We categorized contacts into 4 groups: those treated within 21 days after illness onset in the primary patient. We studied 476 primary index patients and their 1,975 household contacts, of whom 4.5% were later identified as having pertussis. When contacts started chemoprophylaxis within 14 days after primary patient's symptom onset was less effective. We recommend that contacts of persons with pertussis begin chemoprophylaxis within <14 days after primary patient's symptom onset

    FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium

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    Background:Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium. Methods:Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression. Results:Little evidence of association with breast cancer risk was observed for SNPs in the FGF receptor genes. The strongest evidence in European women was for rs743682 in FGFR3; the estimated per-allele odds ratio was 1.05 (95 confidence interval=1.02-1.09, P=0.0020), which is substantially lower than that observed for SNPs in FGFR2. Conclusion:Our results suggest that common variants in the other FGF receptors are not associated with risk of breast cancer to the degree observed for FGFR2. © 2014 Cancer Research UK

    Low Complexity Regularization of Linear Inverse Problems

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    Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of 2\ell^2-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

    Statistical Outliers and Dragon-Kings as Bose-Condensed Droplets

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    A theory of exceptional extreme events, characterized by their abnormal sizes compared with the rest of the distribution, is presented. Such outliers, called "dragon-kings", have been reported in the distribution of financial drawdowns, city-size distributions (e.g., Paris in France and London in the UK), in material failure, epileptic seizure intensities, and other systems. Within our theory, the large outliers are interpreted as droplets of Bose-Einstein condensate: the appearance of outliers is a natural consequence of the occurrence of Bose-Einstein condensation controlled by the relative degree of attraction, or utility, of the largest entities. For large populations, Zipf's law is recovered (except for the dragon-king outliers). The theory thus provides a parsimonious description of the possible coexistence of a power law distribution of event sizes (Zipf's law) and dragon-king outliers.Comment: Latex file, 16 pages, 1 figur

    ARGONAUT II study of the in vitro activity of plazomicin against carbapenemase-producing klebsiella pneumoniae

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    Plazomicin was tested against 697 recently acquired carbapenemresistant Klebsiella pneumoniae isolates from the Great Lakes region of the United States. Plazomicin MIC50 and MIC90 values were 0.25 and 1 mg/liter, respectively; 680 isolates (97.6%) were susceptible (MICs of ≤2 mg/liter), 9 (1.3%) intermediate (MICs of 4 mg/liter), and 8 (1.1%) resistant (MICs of>32 mg/liter). Resistance was associated with rmtF-, rmtB-, or armA-encoded 16S rRNA methyltransferases in all except 1 isolate
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