| 1. |
- Ghorbanzad‘e, Mehdi, et al.
(författare)
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Quantitative and qualitative prediction of corneal permeability for drug-like compounds
- 2011
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Ingår i: Talanta. - : Elsevier BV. - 0039-9140 .- 1873-3573. ; 85:5, s. 2686-2694
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Tidskriftsartikel (refereegranskat)abstract
- A set of 69 drug-like compounds with corneal permeability was studied using quantitative and qualitative modeling techniques. Multiple linear regression (MLR) and multilayer perceptron neural network (MLP-NN) were used to develop quantitative relationships between the corneal permeability and seven molecular descriptors selected by stepwise MLR and sensitivity analysis methods. In order to evaluate the models, a leave many out cross-validation test was performed, which produced the statistic Q2 = 0.584 and SPRESS = 0.378 for MLR and Q2 = 0.774 and SPRESS = 0.087 for MLP-NN. The obtained results revealed the suitability of MLP-NN for the prediction of corneal permeability. The contribution of each descriptor to MLP-NN model was evaluated. It indicated the importance of the molecular volume and weight. The pattern recognition methods principal component analysis (PCA) and hierarchical clustering analysis (HCA) have been employed in order to investigate the possible qualitative relationships between the molecular descriptors and the corneal permeability. The PCA and HCA results showed that, the data set contains two groups. Then, the same descriptors used in quantitative modeling were considered as inputs of counter propagation neural network (CPNN) to classify the compounds into low permeable (LP) and very low permeable (VLP) categories in supervised manner. The overall classification non error rate was 95.7% and 95.4% for the training and prediction test sets, respectively. The results revealed the ability of CPNN to correctly recognize the compounds belonging to the categories. The proposed models can be successfully used to predict the corneal permeability values and to classify the compounds into LP and VLP ones. Highlights ► Linear and nonlinear prediction of corneal permeability using molecular descriptors. ► MLP-NN model was found to be more successful than MLR equation. ► Molecular volume and molecular weight were identified as the most important descriptors. ► Categorizing drugs in two low permeable and very low permeable compounds groups. ► CPNN model can correctly recognize objects belonging to the groups.
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| 2. |
- Ghorbanzadeh, Mehdi, et al.
(författare)
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Modeling the cellular uptake of magnetofluorescent nanoparticles in pancreatic cancer cells : a quantitative structure activity relationship study
- 2012
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Ingår i: Industrial & Engineering Chemistry Research. - : American Chemical Society (ACS). - 0888-5885 .- 1520-5045. ; 51:32, s. 10712-10718
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Tidskriftsartikel (refereegranskat)abstract
- An artificial neural network was employed to predict the cellular uptake of 109 magnetofluorescent nanoparticles (NPs) in pancreatic cancer cells on the basis of quantitative structure activity relationship method. Six descriptors chosen by combining self organizing map and stepwise multiple linear regression (MLR) techniques were used to correlate the nanostructure of the studied particles with their bioactivity using MLR and multilayered perceptron neural network (MLP-NN) modeling techniques. For the MLR and MLP-NN models, the correlation coefficient was 0.769 and 0.934, and the root-mean-square error was 0.364 and 0.150, respectively. The results obtained after a leave-many-out cross-validation test revealed the credibility of MLP-NN for the prediction of cellular uptake of NPs. In addition, sensitivity analysis of MLP-NN model indicated that the number of hydrogen-bond donor sites in the organic coating of a NP is the predominant factor responsible for cellular uptake.
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| 3. |
- Gouveia-Figueira, Sandra C., et al.
(författare)
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Mass spectrometry profiling reveals altered plasma levels of monohydroxy fatty acids and related lipids in healthy humans after controlled exposure to biodiesel exhaust
- 2018
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Ingår i: Analytica Chimica Acta. - : Elsevier. - 0003-2670 .- 1873-4324. ; 1018, s. 62-69
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Tidskriftsartikel (refereegranskat)abstract
- Experimental human exposure studies are an effective tool to study adverse health effects from acute inhalation of particulate matter and other constituents of air pollution. In this randomized and double-blinded crossover study, we investigated the systemic effect on bioactive lipid metabolite levels after controlled biodiesel exhaust exposure of healthy humans and compared it to filtered air at a separate exposure occasion. Eicosanoids and other oxylipins, as well as endocannabinoids and related lipids, were quantified in plasma from 14 healthy volunteers at baseline and at three subsequent time points (2, 6, and 24 h) after 1 h exposure sessions. Protocols based on liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS) methods were developed to detect temporal changes in circulating levels after biodiesel exhaust exposure. The exhaust was generated by a diesel engine fed with an undiluted rapeseed methyl ester fuel. Among the 51 analyzed lipid metabolites, PGF(2 alpha), 9,10-DiHOME, 9-HODE, 5-HETE, 11-HETE, 12-HETE, and DEA displayed significant responsiveness to the biodiesel exhaust exposure as opposed to filtered air. Of these, 9-HODE and 5-HETE at 24 h survived the 10% false discovery rate cutoff (p < 0.003). Hence, the majority of the responsive lipid metabolites were monohydroxy fatty acids. We conclude that it is possible to detect alterations in circulating bioactive lipid metabolites in response to biodiesel exhaust exposure using LC-MS/MS, with emphasis on metabolites with inflammation related properties and implications on cardiovascular health and disease. These observations aid future investigations on air pollution effects, especially with regard to cardiovascular outcomes.
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| 4. |
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| 5. |
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| 6. |
- Gouveia-Figueira, Sandra, et al.
(författare)
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Mass spectrometry profiling of oxylipins, endocannabinoids, and N-acylethanolamines in human lung lavage fluids reveals responsiveness of prostaglandin E2 and associated lipid metabolites to biodiesel exhaust exposure
- 2017
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Ingår i: Analytical and Bioanalytical Chemistry. - : SPRINGER HEIDELBERG. - 1618-2642 .- 1618-2650. ; 409:11, s. 2967-2980
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Tidskriftsartikel (refereegranskat)abstract
- The adverse effects of petrodiesel exhaust exposure on the cardiovascular and respiratory systems are well recognized. While biofuels such as rapeseed methyl ester (RME) biodiesel may have ecological advantages, the exhaust generated may cause adverse health effects. In the current study, we investigated the responses of bioactive lipid mediators in human airways after biodiesel exhaust exposure using lipidomic profiling methods. Lipid mediator levels in lung lavage were assessed following 1-h biodiesel exhaust (average particulate matter concentration, 159 mu g/m(3)) or filtered air exposure in 15 healthy individuals in a double-blinded, randomized, controlled, crossover study design. Bronchoscopy was performed 6 h post exposure and lung lavage fluids, i.e., bronchial wash (BW) and bronchoalveolar lavage (BAL), were sequentially collected. Mass spectrometry methods were used to detect a wide array of oxylipins (including eicosanoids), endocannabinoids, Nacylethanolamines, and related lipid metabolites in the collected BWand BAL samples. Six lipids in the human lung lavage samples were altered following biodiesel exhaust exposure, three from BAL samples and three from BW samples. Of these, elevated levels of PGE2, 12,13-DiHOME, and 13-HODE, all of which were found in BAL samples, reached Bonferroni-corrected significance. This is the first study in humans reporting responses of bioactive lipids following biodiesel exhaust exposure and the most pronounced responses were seen in the more peripheral and alveolar lung compartments, reflected by BAL collection. Since the responsiveness and diagnostic value of a subset of the studied lipid metabolites were established in lavage fluids, we conclude that our mass spectrometry profiling method is useful to assess effects of human exposure to vehicle exhaust.
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| 7. |
- Karimpour, Masoumeh, 1986-
(författare)
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Multi-platform metabolomics assays to study the responsiveness of the human plasma and lung lavage metabolome
- 2016
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Konstnärligt arbete (övrigt vetenskapligt/konstnärligt)abstract
- Metabolomics as a field has been used to track changes and perturbations in the human body by investigating metabolite profiles indicating the change of metabolite levels over time and in response to different challenges. In this thesis work, the main focus was on applying multiplatform-metabolomics to study the human metabolome following exposure to perturbations, such as diet (in the form of a challenge meal) and exhaust emissions (air pollution exposure in a controlled setting). The cutting-edge analytical platforms used for this purpose were nuclear magnetic resonance (NMR), as well as gas chromatography (GC) and liquid chromatography (LC) coupled to mass spectrometry (MS). Each platform offered unique characterization features, allowing detection and identification of a specific range of metabolites. The use of multiplatform-metabolomics was found to enhance the metabolome coverage and to provide complementary findings that enabled a better understanding of the biochemical processes reflected by the metabolite profiles. Using non-targeted analysis, a wide range of unknown metabolites in plasma were identified during the postprandial stage after a well-defined challenge meal (in Paper I). In addition, a considerable number of metabolites were detected and identified in lung lavage fluid after biodiesel exhaust exposure compared to filtered air exposure (in Paper II). In parallel, using targeted analysis, both lung lavage and plasma fatty acid metabolites were detected and quantified in response to filtered air and biodiesel exhaust exposure (in Paper III and IV).Data processing of raw data followed by data analysis, using both univariate and multivariate methods, enabled changes occurring in metabolites levels to be screened and investigated. For the initial pilot postprandial study, the aim was to investigate the plasma metabolome response after a well-defined meal during the postprandial stage for two types of diet. It was found that independent of the background diet type, levels of metabolites returned to their baseline levels after three hours. This finding was taken into consideration for the biodiesel exhaust exposures studies, designed to limit the impact of dietary effects. Both targeted and non-targeted approaches resulted in important findings. For instance, different metabolite profiles were detected in bronchial wash (BW) compared to bronchoalveolar lavage (BAL) fluid with mainly NMR and LC-MS. Furthermore, biodiesel exhaust exposure resulted in different metabolite profiles as observed by GC-MS, especially in BAL. In addition, fatty acid metabolites in BW, BAL, and plasma were shown to be responsive to biodiesel exhaust exposure, as measured by a targeted LC-MS/MS protocol. In summary, the new analytical methods developed to investigate the responsiveness of the human plasma and lung lavage metabolome proved to be useful in an analytical perspective, and provided important biological findings. However, further studies are needed to validate these results.
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| 8. |
- Karimpour, Masoumeh, et al.
(författare)
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Postprandial metabolomics : A pilot mass spectrometry and NMR study of the human plasma metabolome in response to a challenge meal
- 2016
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Ingår i: Analytica Chimica Acta. - Elsevier : Elsevier BV. - 0003-2670 .- 1873-4324. ; 908, s. 121-131
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Tidskriftsartikel (refereegranskat)abstract
- The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms – gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) – to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1–86% for GC-MS and 0.9–42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2–97% for the positive and 4–69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a multi-platform metabolomics approach followed by multivariate and univariate data analysis for a broad-scale screen of the individual metabolome, particularly for studies using repeated measures to determine dietary response phenotype.
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| 9. |
- Larsson, Nirina, et al.
(författare)
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Lipid mediator profiles differ between lung compartments in asthmatic and healthy humans
- 2014
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Ingår i: European Respiratory Journal. - : European Respiratory Society (ERS). - 0903-1936 .- 1399-3003. ; 43:2, s. 453-463
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Tidskriftsartikel (refereegranskat)abstract
- Oxylipins are oxidised fatty acids that can exert lipid mediator functions in inflammation, and several oxylipins derived from arachidonic acid are linked to asthma. This study quantified oxylipin profiles in different regions of the lung to obtain a broad-scale characterisation of the allergic asthmatic inflammation in relation to healthy individuals. Bronchoalveolar lavage fluid (BALF), bronchial wash fluid and endobronchial mucosal biopsies were collected from 16 healthy and 16 mildly allergic asthmatic individuals. Inflammatory cell counts, immunohistochemical staining and oxylipin profiling were performed. Univariate and multivariate statistics were employed to evaluate compartment-dependent and diagnosis-dependent oxylipin profiles in relation to other measured parameters. Multivariate modelling showed significantly different bronchial wash fluid and BALF oxylipin profiles in both groups ((RY)-Y-2[cum]=0.822 and Q(2)[cum]=0.759). Total oxylipin concentrations and five individual oxylipins, primarily from the lipoxygenase (LOX) pathway of arachidonic and linoleic acid, were elevated in bronchial wash fluid from asthmatics compared to that from healthy controls, supported by immunohistochemical staining of 15-LOX-1 in the bronchial epithelium. No difference between the groups was found among BALF oxylipins. In conclusion, bronchial wash fluid and BALF contain distinct oxylipin profiles, which may have ramifications for the study of respiratory diseases. Specific protocols for sampling proximal and distal airways separately should be employed for lipid mediator studies.
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| 10. |
- Sahebi, Golnaz, et al.
(författare)
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SEECC : A Secure and Efficient Elliptic Curve Cryptosystem for E-health Applications
- 2016
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Ingår i: 2016 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING & SIMULATION (HPCS 2016). - : IEEE. - 9781509020881 ; , s. 492-500
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Konferensbidrag (refereegranskat)abstract
- Security is an essential factor in wireless sensor networks especially for E-health applications. One of the common mechanisms to satisfy the security requirements is cryptography. Among the cryptographic methods, elliptic curve cryptography is well-known, as by having a small key length it provides the same security level in comparison with the other public key cryptosystems. The small key sizes make ECC very interesting for devices with limited processing power or memory such as wearable devices for E-health applications. It is vitally important that elliptic curves are protected against all kinds of attacks concerning the security of elliptic curve cryptography. Selection of a secure elliptic curve is a mathematically difficult problem. In this paper, an efficient elliptic curve selection framework, called SEECC, is proposed to select a secure and efficient curve front all the available elliptic curves. This method enhances the security and efficiency of elliptic curve cryptosystems by using a parallel genetic algorithm.
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