Exploring Outliers in Crowdsourced Ranking for QoE

Outlier detection is a crucial part of robust evaluation for crowdsourceable assessment of Quality of Experience (QoE) and has attracted much attention in recent years. In this paper, we propose some simple and fast algorithms for outlier detection and robust QoE evaluation based on the nonconvex optimization principle. Several iterative procedures are designed with or without knowing the number of outliers in samples. Theoretical analysis is given to show that such procedures can reach statistically good estimates under mild conditions. Finally, experimental results with simulated and real-world crowdsourcing datasets show that the proposed algorithms could produce similar performance to Huber-LASSO approach in robust ranking, yet with nearly 8 or 90 times speed-up, without or with a prior knowledge on the sparsity size of outliers, respectively. Therefore the proposed methodology provides us a set of helpful tools for robust QoE evaluation with crowdsourcing data.Comment: accepted by ACM Multimedia 2017 (Oral presentation). arXiv admin note: text overlap with arXiv:1407.763

Combined intervention with pioglitazone and n-3 fatty acids in metformin-treated type 2 diabetic patients: improvement of lipid metabolism

Background: The marine n-3 fatty acids, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) exert numerous beneficial effects on health, but their potency to improve treatment of type 2 diabetic (T2D) patients remains poorly characterized. We aimed to evaluate the effect of a combination intervention using EPA?+?DHA and the insulin-sensitizing drug pioglitazone in overweight/obese T2D patients already treated with metformin.Methods: In a parallel-group, four-arm, randomized trial, 69 patients (66 % men) were assigned to 24-week-intervention using: (i) corn oil (5 g/day; Placebo), (ii) pioglitazone (15 mg/day; Pio), (iii) EPA?+?DHA concentrate (5 g/day, containing ~2.8 g EPA?+?DHA; Omega-3), or (iv) pioglitazone and EPA?+?DHA concentrate (Pio&amp; Omega-3). Data from 60 patients were used for the final evaluation. At baseline and after intervention, various metabolic markers, adiponectin and cytokines were evaluated in serum using standard procedures, EPA?+?DHA content in serum phospholipids was evaluated using shotgun lipidomics and mass spectrometry, and hyperinsulinemic-euglycemic clamp and meal test were also performed. Indirect calorimetry was conducted after the intervention. Primary endpoints were changes from baseline in insulin sensitivity evaluated using hyperinsulinemic-euglycemic clamp and in serum triacylglycerol concentrations in fasting state. Secondary endpoints included changes in fasting glycemia and glycated hemoglobin (HbA1c), changes in postprandial glucose, free fatty acid and triacylglycerol concentrations, metabolic flexibility assessed by indirect calorimetry, and inflammatory markers.Results: Omega-3 and Pio&amp; Omega-3 increased EPA?+?DHA content in serum phospholipids. Pio and Pio&amp; Omega-3 increased body weight and adiponectin levels. Both fasting glycemia and HbA1c were increased by Omega-3, but were unchanged by Pio&amp; Omega-3. Insulin sensitivity was not affected by Omega-3, while it was improved by Pio&amp; Omega-3. Fasting triacylglycerol concentrations and inflammatory markers were not significantly affected by any of the interventions. Lipid metabolism in the meal test and metabolic flexibility were additively improved by Pio&amp; Omega-3.Conclusion: Besides preventing a modest negative effect of n-3 fatty acids on glycemic control, the combination of pioglitazone and EPA?+?DHA can be used to improve lipid metabolism in T2D patients on stable metformin therapy.Trial registration: EudraCT number 2009-011106-42.<br/

Intracellular Targeting Specificity of Novel Phthalocyanines Assessed in a Host-Parasite Model for Developing Potential Photodynamic Medicine

Photodynamic therapy, unlikely to elicit drug-resistance, deserves attention as a strategy to counter this outstanding problem common to the chemotherapy of all diseases. Previously, we have broadened the applicability of this modality to photodynamic vaccination by exploiting the unusual properties of the trypanosomatid protozoa, Leishmania, i.e., their innate ability of homing to the phagolysosomes of the antigen-presenting cells and their selective photolysis therein, using transgenic mutants endogenously inducible for porphyrin accumulation. Here, we extended the utility of this host-parasite model for in vitro photodynamic therapy and vaccination by exploring exogenously supplied photosensitizers. Seventeen novel phthalocyanines (Pcs) were screened in vitro for their photolytic activity against cultured Leishmania. Pcs rendered cationic and soluble (csPcs) for cellular uptake were phototoxic to both parasite and host cells, i.e., macrophages and dendritic cells. The csPcs that targeted to mitochondria were more photolytic than those restricted to the endocytic compartments. Treatment of infected cells with endocytic csPcs resulted in their accumulation in Leishmania-containing phagolysosomes, indicative of reaching their target for photodynamic therapy, although their parasite versus host specificity is limited to a narrow range of csPc concentrations. In contrast, Leishmania pre-loaded with csPc were selectively photolyzed intracellularly, leaving host cells viable. Pre-illumination of such csPc-loaded Leishmania did not hinder their infectivity, but ensured their intracellular lysis. Ovalbumin (OVA) so delivered by photo-inactivated OVA transfectants to mouse macrophages and dendritic cells were co-presented with MHC Class I molecules by these antigen presenting cells to activate OVA epitope-specific CD8+T cells. The in vitro evidence presented here demonstrates for the first time not only the potential of endocytic csPcs for effective photodynamic therapy against Leishmania but also their utility in photo-inactivation of Leishmania to produce a safe carrier to express and deliver a defined antigen with enhanced cell-mediated immunity

Is Paromomycin an Effective and Safe Treatment against Cutaneous Leishmaniasis? A Meta-Analysis of 14 Randomized Controlled Trials

Millions of people worldwide are suffering from cutaneous leishmaniasis that is caused by parasites of the genus Leishmania. Although pentavalent antimony compounds are the treatment of choice, their use is limited by high cost, poor compliance, and systemic toxicity. Paromomycin was developed to overcome such limitations. However, there is no consensus on its efficacy. This meta-analysis assessed the efficacy and safety of paromomycin compared with placebo and pentavalent antimony compounds. Fourteen randomized controlled trials, including 1,221 patients, met our selection criteria. Topical paromomycin appeared to have therapeutic activity against the old world and new world cutaneous leishmaniasis, with increased local reactions, when combined with methylbenzethonium chloride. Topical paromomycin was not significantly different from intralesional pentavalent antimony compounds in treating the old world form, whereas it was inferior to parenteral pentavalent antimony compounds in treating the new world form. However, a similar efficacy was found between parenteral paromomycin and pentavalent antimony compounds in treating the new world form. Fewer systemic side effects were observed with topical and parenteral paromomycin than pentavalent antimony compounds. These results suggest that topical paromomycin with methylbenzethonium chloride could be a therapeutic alternative to pentavalent antimony compounds for selected cases of the old world cutaneous leishmaniasis

Normalization techniques for PARAFAC modeling of urine metabolomic data

Introduction One of the body fluids often used in metabolomics studies is urine. The concentrations of metabolites in urine are affected by hydration status of an individual, resulting in dilution differences. This requires therefore normalization of the data to correct for such differences. Two normalization techniques are commonly applied to urine samples prior to their further statistical analysis. First, AUC normalization aims to normalize a group of signals with peaks by standardizing the area under the curve (AUC) within a sample to the median, mean or any other proper representation of the amount of dilution. The second approach uses specific end-product metabolites such as creatinine and all intensities within a sample are expressed relative to the creatinine intensity. Objectives Another way of looking at urine metabolomics data is by realizing that the ratios between peak intensities are the information-carrying features. This opens up possibilities to use another class of data analysis techniques designed to deal with such ratios: compositional data analysis. The aim of this paper is to develop PARAFAC modeling of three-way urine metabolomics data in the context of compositional data analysis and compare this with standard normalization techniques. Methods In the compositional data analysis approach, special coordinate systems are defined to deal with the ratio problem. In essence, it comes down to using other distance measures than the Euclidian Distance that is used in the conventional analysis of metabolomic data. Results We illustrate using this type of approach in combination with three-way methods (i.e. PARAFAC) of a longitudinal urine metabolomics study and two simulations. In both cases, the advantage of the compositional approach is established in terms of improved interpretability of the scores and loadings of the PARAFAC model. Conclusion For urine metabolomics studies, we advocate the use of compositional data analysis approaches. They are easy to use, well established and proof to give reliable results

Oxidized phosphatidylcholines suggest oxidative stress in patients with medium-chain acyl-CoA dehydrogenase deficiency

Inborn errors of metabolism encompass a large group of diseases caused by enzyme deficiencies and are therefore amenable to metabolomics investigations. Medium chain acyl-CoA dehydrogenase deficiency (MCADD) is a defect in β-oxidation of fatty acids, and is one of the most well understood disorders. We report here the use of liquid chromatography–mass spectrometry (LC–MS) based untargeted metabolomics and targeted flow injection analysis–tandem mass spectrometry (FIA–TMS) that lead to discovery of novel compounds of oxidative stress. Dry blood spots of controls (n=25) and patient samples (n=25) were extracted by methanol/water (1/1, v/v) and these supernatants were analyzed by LC–MS method with detection by an Orbitrap Elite MS. Data were processed by XCMS and CAMERA followed by dimension reduction methods. Patients were clearly distinguished from controls in PCA. S-plot derived from OPLS-DA indicated that medium-chain acylcarnitines (octanoyl, decenoyl and decanoyl carnitines) as well as three phosphatidylcholines (PC(16:0,9:0(COOH))), PC(18:0,5:0(COOH)) and PC(16:0,8:0(COOH)) were important metabolites for differentiation between patients and healthy controls. In order to biologically validate these discriminatory molecules as indicators for oxidative stress, a second cohort of individuals were analyzed, including MCADD (n=25) and control (n=250) samples. These were measured by a modified newborn screening method using FIA–TMS (API 4000) in MRM mode. Calculated p-values for PC(16:0,9:0(COOH)), PC(18:0,5:0(COOH)) and PC(16:0,8:0(COOH)) were 1.927×10−14, 2.391×10−15 and 3.354×10−15 respectively. These elevated oxidized phospholipids indeed show an increased presence of oxidative stress in MCADD patients as one of the pathophysiological mechanisms of the disease

Normalization techniques for PARAFAC modeling of urine metabolomic data

Introduction One of the body fluids often used in metabolomics studies is urine. The concentrations of metabolites in urine are affected by hydration status of an individual, resulting in dilution differences. This requires therefore normalization of the data to correct for such differences. Two normalization techniques are commonly applied to urine samples prior to their further statistical analysis. First, AUC normalization aims to normalize a group of signals with peaks by standardizing the area under the curve (AUC) within a sample to the median, mean or any other proper representation of the amount of dilution. The second approach uses specific end-product metabolites such as creatinine and all intensities within a sample are expressed relative to the creatinine intensity. Objectives Another way of looking at urine metabolomics data is by realizing that the ratios between peak intensities are the information-carrying features. This opens up possibilities to use another class of data analysis techniques designed to deal with such ratios: compositional data analysis. The aim of this paper is to develop PARAFAC modeling of three-way urine metabolomics data in the context of compositional data analysis and compare this with standard normalization techniques. Methods In the compositional data analysis approach, special coordinate systems are defined to deal with the ratio problem. In essence, it comes down to using other distance measures than the Euclidian Distance that is used in the conventional analysis of metabolomic data. Results We illustrate using this type of approach in combination with three-way methods (i.e. PARAFAC) of a longitudinal urine metabolomics study and two simulations. In both cases, the advantage of the compositional approach is established in terms of improved interpretability of the scores and loadings of the PARAFAC model. Conclusion For urine metabolomics studies, we advocate the use of compositional data analysis approaches. They are easy to use, well established and proof to give reliable results