• MeSH
• Breast Neoplasms prevention & control   MeSH
• Mass Screening MeSH
• Socialism MeSH
• Geographicals
• Historical Geographic Locations MeSH

• MeSH
• Discriminant Analysis MeSH
• Air Pollutants analysis   MeSH
• Environmental Monitoring MeSH
• Data Collection MeSH
• Cluster Analysis MeSH
• Air Pollution MeSH
• Publication type
• Database MeSH

• MeSH
• Biometry MeSH
• Statistics as Topic MeSH

• Conspectus
• Statistika
• NML Fields
• statistika, zdravotnická statistika
• management, organizace a řízení zdravotnictví

• MeSH
• Multivariate Analysis MeSH

• MeSH
• Survival MeSH
• Regression Analysis MeSH
• Research statistics & numerical data   MeSH

• Conspectus
• Kombinatorika. Teorie grafů. Matematická statistika. Operační výzkum. Matematické modelování
• NML Fields
• přírodní vědy
• NML Publication type
• kolektivní monografie

• Keywords
• bioinformatika, zdravotnická elektronická dokumentace, eHealth,
• MeSH
• Databases as Topic trends   utilization   MeSH
• Financing, Organized MeSH
• Humans MeSH
• Evidence-Based Medicine MeSH
• Meta-Analysis as Topic MeSH
• Molecular Biology methods   trends   MeSH
• Hospital Information Systems trends   utilization   MeSH
• Registries MeSH
• Data Collection methods   utilization   MeSH
• Statistics as Topic MeSH
• Medical Order Entry Systems trends   utilization   MeSH
• Medical Informatics Applications MeSH
• Records MeSH
• Check Tag
• Humans MeSH

A test-statistic typically employed in the gene set enrichment analysis (GSEA) prevents this method from being genuinely multivariate. In particular, this statistic is insensitive to changes in the correlation structure of the gene sets of interest. The present paper considers the utility of an alternative test-statistic in designing the confirmatory component of the GSEA. This statistic is based on a pertinent distance between joint distributions of expression levels of genes included in the set of interest. The null distribution of the proposed test-statistic, known as the multivariate N-statistic, is obtained by permuting group labels. Our simulation studies and analysis of biological data confirm the conjecture that the N-statistic is a much better choice for multivariate significance testing within the framework of the GSEA. We also discuss some other aspects of the GSEA paradigm and suggest new avenues for future research.

• MeSH
• Phenotype MeSH
• Financing, Organized MeSH
• Models, Genetic MeSH
• Multivariate Analysis MeSH
• Oligonucleotide Array Sequence Analysis statistics & numerical data   MeSH
• Gene Expression Profiling statistics & numerical data   MeSH
• Computational Biology MeSH

CONTEXT: Mucoadhesive oral films, with their prolonged residence time at the site of application, offer a promising approach for protection of the oral lesion surface. The addition of sodium hyaluronate of different molecular weights as a second mucoadhesive polymer into the film matrix could positively influence the physico-mechanical and mucoadhesive properties of films. OBJECTIVE: The aim of this study was to investigate the formulation of a monolayered film matrix containing varying amounts of sodium hyaluronate and to test the properties of such matrices by applying different characterization methods. MATERIALS AND METHODS: Film matrix was composed of two mucoadhesive polymers, carmellose sodium and sodium hyaluronate, plasticized with glycerol. Resulting films were characterized with regard to their viscosity and physico-mechanical properties. RESULTS AND DISCUSSION: Multivariate data analysis was employed to evaluate the influence of varying amounts of mucoadhesive polymers on the main mucoadhesive oral films' properties. The lower content of sodium hyaluronate caused improvements in mechanical properties and residence time on the artificial oral mucosa, both of which are the main characteristics that determine the quality of the final product. CONCLUSIONS: The best results were obtained by samples containing carmellose sodium with a small amount of sodium hyaluronate (about 0.5% in casting dispersion).

• MeSH
• Adhesives chemistry   metabolism   MeSH
• Adhesiveness MeSH
• Glycerol chemistry   metabolism   MeSH
• Hyaluronic Acid chemistry   metabolism   MeSH
• Drug Delivery Systems methods   MeSH
• Humans MeSH
• Multivariate Analysis MeSH
• Oral Mucosal Absorption MeSH
• Tensile Strength MeSH
• Polymers MeSH
• Carboxymethylcellulose Sodium chemistry   metabolism   MeSH
• Mouth Mucosa metabolism   MeSH
• Drug Liberation MeSH
• Viscosity MeSH
• Plasticizers chemistry   metabolism   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

Differences among lipidomic profiles of healthy volunteers, obese people and three groups of cardiovascular disease (CVD) patients are investigated with the goal to differentiate individual groups based on the multivariate data analysis (MDA) of lipidomic data from plasma, erythrocytes and lipoprotein fractions of more than 50 subjects. Hydrophilic interaction liquid chromatography on ultrahigh-performance liquid chromatography (HILIC-UHPLC) column coupled with electrospray ionization mass spectrometry (ESI-MS) is used for the quantitation of four classes of polar lipids (phosphatidylethanolamines, phosphatidylcholines, sphingomyelins and lysophosphatidylcholines), normal-phase UHPLC-atmospheric pressure chemical ionization MS (NP-UHPLC/APCI-MS) is applied for the quantitation of five classes of nonpolar lipids (cholesteryl esters, triacylglycerols, sterols, 1,3-diacylglycerols and 1,2-diacylglycerols) and the potential of matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is tested for the fast screening of all lipids without a chromatographic separation. Obtained results are processed by unsupervised (principal component analysis) and supervised (orthogonal partial least squares) MDA approaches to highlight the largest differences among individual groups and to identify lipid molecules with the highest impact on the group differentiation.

• MeSH
• Adult MeSH
• Cardiovascular Diseases blood   MeSH
• Cohort Studies MeSH
• Middle Aged MeSH
• Humans MeSH
• Lipids blood   chemistry   classification   MeSH
• Lipoproteins blood   chemistry   classification   MeSH
• Least-Squares Analysis MeSH
• Multivariate Analysis MeSH
• Obesity MeSH
• Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization methods   MeSH
• Computational Biology MeSH
• Chromatography, High Pressure Liquid methods   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

• Keywords
• Statistika,

• Conspectus
• Statistika
• NML Fields
• statistika, zdravotnická statistika