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
• fenotyp MeSH
• modely genetické MeSH
• multivariační analýza MeSH
• sekvenční analýza hybridizací s uspořádaným souborem oligonukleotidů statistika a číselné údaje   MeSH
• stanovení celkové genové exprese statistika a číselné údaje   MeSH
• výpočetní biologie MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH

SUMMARY: The package MorphoTools2 is intended for multivariate analyses of morphological data. Commonly used tools are missing or scattered across several R packages. The new package, in order to make the workflow convenient and fast, wraps available statistical and graphical tools and provides a comprehensive framework for checking and manipulating input data, core statistical analyses and a wide palette of functions designed to visualize results. AVAILABILITY AND IMPLEMENTATION: Stable version is available from CRAN: https://cran.r-project.org/package=MorphoTools2. The development version is available from the following GitHub repository: https://github.com/MarekSlenker/MorphoTools2. The software is distributed under the GNU General Public Licence (v.3). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

• MeSH
• multivariační analýza MeSH
• průběh práce MeSH
• software * MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

The pharmaceutical industry has to tackle the explosion of high amounts of poorly soluble APIs. This phenomenon leads to numerous sophisticated solutions. These include the use of multifactorial data analysis identifying correlations between the components and dosage form properties, laboratory and production process parameters with respect to the API liberation Example of such API is bicalutamide. Improved liberation is achieved by particle size reduction. Laboratory batches, with different PSD of API, were filled into gelatinous capsules and consequently granulated for tablet compression. Comparative dissolution profiles with Casodex 150 mg (Astra Zeneca) were performed. The component analysis was used for the statistical evaluation of f1 and f2 factors and D(v,0.9) and D[4,3] parameters of PSD to identify optimal PSD values. Suitable PSD limits for API were statistically confirmed in laboratory and in commercial scale with respect to optimized tablet properties. The tablets were bioequivalent with originator (n = 20; 90% CI for ln AUC0-120: 99.8-111.9%; 90% CI for ln cmax: 101.1-112.9%). In conclusion, the micronisation of the API is still an efficient and inexpensive method improving the bioavailability, although there are more complicated and expensive methods available. Statistical multifactorial methods improved the safety and reproducibility of production.

• Klíčová slova
• Bicalutamide, bioequivalence, dissolution, multivariate statistics, particle size,
• MeSH
• anilidy chemická syntéza   metabolismus   MeSH
• biologická dostupnost MeSH
• farmaceutická chemie metody   MeSH
• multivariační analýza MeSH
• nitrily chemická syntéza   metabolismus   MeSH
• tablety MeSH
• terapeutická ekvivalence MeSH
• tosylové sloučeniny chemická syntéza   metabolismus   MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• anilidy MeSH
• bicalutamide MeSH Prohlížeč
• nitrily MeSH
• tablety MeSH
• tosylové sloučeniny MeSH

The visual evaluation of data derived from screening and optimization experiments in the development of new analytical methods poses a considerable time investment and introduces the risk of subjectivity. This study presents a novel approach to processing such data, based on factor analysis of mixed data and hierarchical clustering - multivariate techniques implemented in the R programming language. The methodology is demonstrated in the early-stage screening and optimization of the chromatographic separation of 15 structurally diverse drugs that affect the central nervous system, using a custom R Language script. The presented explorative approach enabled the identification of key parameters affecting the separation and significantly reduced the time required to evaluate the comprehensive dataset from the screening experiments. Based on the data analysis results, the optimal combination of stationary phase and mobile phase composition was selected, considering retention, overall resolution, and peak shape of compounds. Additionally, compounds vulnerable to changes in selected chromatographic conditions were identified. As a complement to the presented R Language script, a web-based application ChromaFAMDeX has been developed to offer an intuitive interface that enhances the accessibility of the used statistical methods. Accompanying the publication, the R script and the link to the standalone application are provided, enabling replication and adaptation of the methodology.

• Klíčová slova
• Factor analysis of mixed data, Hierarchical clustering, Liquid chromatography, Optimization, R Language,
• MeSH
• chromatografie kapalinová metody   MeSH
• multivariační analýza MeSH
• programovací jazyk * MeSH
• shluková analýza MeSH
• software MeSH
• Publikační typ
• časopisecké články 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.

• Klíčová slova
• Cardiovascular diseases, Lipidomics, Lipids, Lipoprotein fractions, Multivariate data analysis, UHPLC/MS,
• MeSH
• dospělí MeSH
• kardiovaskulární nemoci krev   MeSH
• kohortové studie MeSH
• lidé středního věku MeSH
• lidé MeSH
• lipidy krev   chemie   klasifikace   MeSH
• lipoproteiny krev   chemie   klasifikace   MeSH
• metoda nejmenších čtverců MeSH
• multivariační analýza MeSH
• obezita MeSH
• spektrometrie hmotnostní - ionizace laserem za účasti matrice metody   MeSH
• výpočetní biologie MeSH
• vysokoúčinná kapalinová chromatografie metody   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• lipidy MeSH
• lipoproteiny MeSH

AIM: Current diagnostics of bone metastatic disease is not satisfactory for early detection or regular process monitoring. The combination of biomarkers and the multiparametric approach was described as effective in other oncology diagnoses. The aim of the study was to improve the difference diagnostics between bone-metastatic disease and solid tumors using mutivariate logistic regression model. METHODS: We assessed the group of 131 patients with the following diagnoses: prostate cancer, breast cancer, lung cancer, and colorectal cancer. According to the results of scintigraphy, the cohort was divided into 2 groups based on the occurrence of bone metastases. Group 0 was a control group of 75 patients with no signs of bone metastases and group 1 included 56 patients with bone metastases. RESULTS: We used stepwise selection multivariate logistic regression for choosing the multimarker formula for calculation of risk score for bone metastases diagnostics. For detection of bone metastasis, it was shown to be most effective measurement of 3 biomarkers: procollagen type 1 N-terminal propeptide, growth differentiation factor-15, and osteonectin and combining with calculation of risk score by designating measured concentrations in mathematical formula: bone risk score = procollagen type 1 N-terminal propeptide × 0.0500 + growth differentiation factor-15 × 1.4179 + osteonectin × 0.00555. CONCLUSION: We identified growth differentiation factor-15 as the best individual marker for bone metastasis diagnostics. The best formula for risk score includes levels of 3 biomarkers-procollagen type 1 N-terminal propeptide, growth differentiation factor-15, and osteonectin. The new score has better performance described by higher area under the curve than individual biomarkers. A further study is necessary to confirm these findings incorporating a larger number of patients.

• Klíčová slova
• biomarkers, bone metastasis, cancer, multivariate analysis, scintigraphy,
• MeSH
• dospělí MeSH
• kohortové studie MeSH
• kosti a kostní tkáň metabolismus   patologie   MeSH
• lidé středního věku MeSH
• lidé MeSH
• multivariační analýza MeSH
• nádorové biomarkery metabolismus   MeSH
• nádory kostí metabolismus   patologie   sekundární   MeSH
• osteonektin metabolismus   MeSH
• radioisotopová scintigrafie metody   MeSH
• růstový diferenciační faktor 15 metabolismus   MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• nádorové biomarkery MeSH
• osteonektin MeSH
• růstový diferenciační faktor 15 MeSH

INTRODUCTION: It is often questioned whether to perform replantation or revision amputation for amputation injuries in elderly patients and smokers. According to the current indication criteria, neither old age nor smoking in the absence of other risk factors are considered to be risk factors for replantation failure. However, many microsurgeons still may make the decision not to perform digital replantation based solely on these factors. MATERIAL AND METHODS: In order to evaluate the influence of both factors, we provided univariate and multivariate analyses of patients who underwent replantation at our centre during a 10-year period. We divided patients in two groups according to age (< and ≥ 60 years) and smoking status. RESULTS: In the univariate analysis, there were no differences in immediate results between the two age groups. In the multivariate analysis, no statistical difference was found in neither long-term nor short-term results between the two age groups and between smokers and non-smokers. CONCLUSION: Smoking and age should not be considered the only risk factors when deciding whether to perform digital replantation.

• MeSH
• amputace MeSH
• kouření tabáku * MeSH
• kouření * škodlivé účinky   epidemiologie   MeSH
• lidé středního věku MeSH
• lidé MeSH
• multivariační analýza MeSH
• replantace MeSH
• senioři MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• senioři MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Patients with bipolar disorder (BD) and major depressive disorder (MDD) exhibit depressive episodes with similar symptoms despite having different and poorly understood underlying neurobiology, often leading to misdiagnosis and improper treatment. This exploratory study examined whole-brain functional connectivity (FC) using FC multivariate pattern analysis (fc-MVPA) to identify the FC patterns with the greatest ability to distinguish between currently depressed patients with BD type I (BD I) and those with MDD. METHODOLOGY: In a cross-sectional design, 41 BD I, 40 MDD patients and 63 control participants completed resting state functional magnetic resonance imaging scans. Data-driven fc-MVPA, as implemented in the CONN toolbox, was used to identify clusters with differential FC patterns between BD patients and MDD patients. The identified cluster was used as a seed in a post hoc seed-based analysis (SBA) to reveal associated connectivity patterns, followed by a secondary ROI-to-ROI analysis to characterize differences in connectivity between these patterns among BD I patients, MDD patients and controls. RESULTS: FC-MVPA identified one cluster located in the right frontal pole (RFP). The subsequent SBA revealed greater FC between the RFP and posterior cingulate cortex (PCC) and between the RFP and the left inferior/middle temporal gyrus (LI/MTG) and lower FC between the RFP and the left precentral gyrus (LPCG), left lingual gyrus/occipital cortex (LLG/OCC) and right occipital cortex (ROCC) in MDD patients than in BD patients. Compared with the controls, ROI-to-ROI analysis revealed lower FC between the RFP and the PCC and greater FC between the RFP and the LPCG, LLG/OCC and ROCC in BD patients; in MDD patients, the analysis revealed lower FC between the RFP and the LLG/OCC and ROCC and greater FC between the RFP and the LI/MTG. CONCLUSIONS: Differences in the RFP FC patterns between currently depressed patients with BD and those with MDD suggest potential neuroimaging markers that should be further examined. Specifically, BD patients exhibit increased FC between the RFP and the motor and visual networks, which is associated with psychomotor symptoms and heightened compensatory frontoparietal FC to counter distractibility. In contrast, MDD patients exhibit increased FC between the RFP and the default mode network, corresponding to sustained self-focus and rumination.

• Klíčová slova
• Bipolar disorder, Functional connectivity, Major depressive disorder, Multivariate pattern analysis, Resting state,
• MeSH
• bipolární porucha * patofyziologie   diagnostické zobrazování   MeSH
• depresivní porucha unipolární * patofyziologie   diagnostické zobrazování   MeSH
• dospělí MeSH
• konektom metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• magnetická rezonanční tomografie * metody   MeSH
• mapování mozku metody   MeSH
• mozek patofyziologie   diagnostické zobrazování   MeSH
• multivariační analýza MeSH
• nervová síť diagnostické zobrazování   patofyziologie   MeSH
• nervové dráhy patofyziologie   diagnostické zobrazování   MeSH
• průřezové studie MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Automated head-space solid-phase microextraction (HS-SPME)-based sampling procedure, coupled to gas chromatography-time-of-flight mass spectrometry (GC-TOFMS), was developed and employed for obtaining of fingerprints (GC profiles) of beer volatiles. In total, 265 speciality beer samples were collected over a 1-year period with the aim to distinguish, based on analytical (profiling) data, (i) the beers labelled as Rochefort 8; (ii) a group consisting of Rochefort 6, 8, 10 beers; and (iii) Trappist beers. For the chemometric evaluation of the data, partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and artificial neural networks with multilayer perceptrons (ANN-MLP) were tested. The best prediction ability was obtained for the model that distinguished a group of Rochefort 6, 8, 10 beers from the rest of beers. In this case, all chemometric tools employed provided 100% correct classification. Slightly worse prediction abilities were achieved for the models "Trappist vs. non-Trappist beers" with the values of 93.9% (PLS-DA), 91.9% (LDA) and 97.0% (ANN-MLP) and "Rochefort 8 vs. the rest" with the values of 87.9% (PLS-DA) and 84.8% (LDA) and 93.9% (ANN-MLP). In addition to chromatographic profiling, also the potential of direct coupling of SPME (extraction/pre-concentration device) with high-resolution TOFMS employing a direct analysis in real time (DART) ion source has been demonstrated as a challenging profiling approach.

• MeSH
• multivariační analýza MeSH
• pivo analýza   MeSH
• řízení kvality MeSH
• těkavé organické sloučeniny analýza   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• těkavé organické sloučeniny MeSH

Biorelevant dissolution instruments represent an important tool for pharmaceutical research and development. These instruments are designed to simulate the dissolution of drug formulations in conditions most closely mimicking the gastrointestinal tract. In this work, we focused on the optimization of dissolution compartments/vessels for an updated version of the biorelevant dissolution apparatus-Golem v2. We designed eight compartments of uniform size but different inner geometry. The dissolution performance of the compartments was tested using immediate release caffeine tablets and evaluated by standard statistical methods and principal component analysis. Based on two phases of dissolution testing (using 250 and 100 mL of dissolution medium), we selected two compartment types yielding the highest measurement reproducibility. We also confirmed a statistically ssignificant effect of agitation rate and dissolution volume on the extent of drug dissolved and measurement reproducibility.

• Klíčová slova
• Golem, biorelevant, caffeine, dissolution, multivariate data analysis,
• MeSH
• biologické modely * MeSH
• design vybavení MeSH
• farmaceutická chemie * MeSH
• farmakokinetika * MeSH
• gastrointestinální absorpce MeSH
• gastrointestinální trakt metabolismus   MeSH
• multivariační analýza MeSH
• počítačová simulace MeSH
• rozpustnost * MeSH
• Publikační typ
• časopisecké články MeSH