We have developed a method to longitudinally classify subjects into two or more prognostic groups using longitudinally observed values of markers related to the prognosis. We assume the availability of a training data set where the subjects' allocation into the prognostic group is known. The proposed method proceeds in two steps as described earlier in the literature. First, multivariate linear mixed models are fitted in each prognostic group from the training data set to model the dependence of markers on time and on possibly other covariates. Second, fitted mixed models are used to develop a discrimination rule for future subjects. Our method improves upon existing approaches by relaxing the normality assumption of random effects in the underlying mixed models. Namely, we assume a heteroscedastic multivariate normal mixture for random effects. Inference is performed in the Bayesian framework using the Markov chain Monte Carlo methodology. Software has been written for the proposed method and it is freely available. The methodology is applied to data from the Dutch Primary Biliary Cirrhosis Study.

• MeSH
• biliární cirhóza farmakoterapie   MeSH
• biologické markery analýza   MeSH
• cholagoga a choleretika terapeutické užití   MeSH
• diskriminační analýza * MeSH
• interpretace statistických dat * MeSH
• kyselina ursodeoxycholová terapeutické užití   MeSH
• lidé MeSH
• lineární modely * MeSH
• longitudinální studie MeSH
• počítačová simulace MeSH
• progrese nemoci MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• biologické markery MeSH
• cholagoga a choleretika MeSH
• kyselina ursodeoxycholová MeSH

Plants adapt to continual changes in environmental conditions throughout their life spans. High-throughput phenotyping methods have been developed to noninvasively monitor the physiological responses to abiotic/biotic stresses on a scale spanning a long time, covering most of the vegetative and reproductive stages. However, some of the physiological events comprise almost immediate and very fast responses towards the changing environment which might be overlooked in long-term observations. Additionally, there are certain technical difficulties and restrictions in analyzing phenotyping data, especially when dealing with repeated measurements. In this study, a method for comparing means at different time points using generalized linear mixed models combined with classical time series models is presented. As an example, we use multiple chlorophyll time series measurements from different genotypes. The use of additional time series models as random effects is essential as the residuals of the initial mixed model may contain autocorrelations that bias the result. The nature of mixed models offers a viable solution as these can incorporate time series models for residuals as random effects. The results from analyzing chlorophyll content time series show that the autocorrelation is successfully eliminated from the residuals and incorporated into the final model. This allows the use of statistical inference.

• Klíčová slova
• ARIMA, Arabidopsis, linear mixed models, time series analysis,
• Publikační typ
• časopisecké články MeSH

Random-regression models (RRM) are used in national genetic evaluations for longitudinal traits. The outputs of RRM are an index based on random-regression coefficients and its reliability. The reliabilities are obtained from the inverse of the coefficient matrix of mixed model equations (MME). The reliabilities must be approximated for large datasets because it is impossible to invert the MME. There is no extensive literature on methods to approximate the reliabilities of RRM when genomic information is included by single-step GBLUP. We developed an algorithm to approximate such reliabilities. Our method combines the reliability of the index without genomic information with the reliability of a GBLUP model in terms of effective record contributions. We tested our algorithm in the 3-lactation model for milk yield from the Czech Republic. The data had 30 million test-day records, 2.5 million animals in the pedigree, and 54,000 genotyped animals. The correlation between our approximation and the reliabilities obtained from the inversion of the MME was 0.98, and the slope and intercept of the regression were 0.91 and 0.02, respectively. The elapsed time to approximate the reliabilities for the Czech data was 21 min.

• Publikační typ
• časopisecké články MeSH

AIMS: Abiraterone treatment requires regular drug intake under fasting conditions due to pronounced food effect, which may impact patient adherence. The aim of this prospective study was to evaluate adherence to abiraterone treatment in patients with prostate cancer. To achieve this aim, an abiraterone population pharmacokinetic model was developed and patients' adherence has been estimated by comparison of measured levels of abiraterone with population model-based simulations. METHODS: A total of 1469 abiraterone plasma levels from 83 healthy volunteers collected in a bioequivalence study were analysed using a nonlinear mixed-effects model. Monte Carlo simulation was used to describe the theoretical distribution of abiraterone pharmacokinetic profiles at a dose of 1000 mg once daily. Adherence of 36 prostate cancer patients treated with abiraterone was then evaluated by comparing the real abiraterone concentration measured in each patient during follow-up visit with the theoretical distribution of profiles based on simulations. Patients whose abiraterone levels were ˂5th or ˃95th percentile of the distribution of simulated profiles were considered to be non-adherent. RESULTS: Based on this evaluation, 13 patients (36%) have been classified as non-adherent. We observed significant association (P = .0361) between richness of the breakfast and rate of non-adherence. Adherent patients reported significantly better overall condition in self-assessments (P = .0384). A trend towards a higher occurrence of adverse effects in non-adherent patients was observed. CONCLUSIONS: We developed an abiraterone population pharmacokinetic model and proposed an advanced approach to medical adherence evaluation. Due to the need for administration under fasting conditions, abiraterone therapy is associated with a relatively high rate of non-adherence.

• Klíčová slova
• Monte Carlo simulation, abiraterone acetate, anti‐androgen, compliance, non‐linear mixed‐effects modelling, therapeutic drug monitoring,
• MeSH
• androsteny * farmakokinetika   aplikace a dávkování   terapeutické užití   MeSH
• biologické modely * MeSH
• dospělí MeSH
• hodnocení adherence k farmakoterapii * MeSH
• interakce mezi potravou a léky MeSH
• lidé středního věku MeSH
• lidé MeSH
• metoda Monte Carlo MeSH
• nádory prostaty * farmakoterapie   MeSH
• omezení příjmu potravy MeSH
• prospektivní studie MeSH
• protinádorové látky farmakokinetika   aplikace a dávkování   MeSH
• senioři MeSH
• terapeutická ekvivalence MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• abiraterone MeSH Prohlížeč
• androsteny * MeSH
• protinádorové látky MeSH

OBJECTIVE: To compare several methods of missing data imputation for function (Health Assessment Questionnaire) and for disease activity (Disease Activity Score-28 and Clinical Disease Activity Index) in rheumatoid arthritis (RA) patients. METHODS: One thousand RA patients from observational cohort studies with complete data for function and disease activity at baseline, 6, 12 and 24 months were selected to conduct a simulation study. Values were deleted at random or following a predicted attrition bias. Three types of imputation were performed: (1) methods imputing forward in time (last observation carried forward; linear forward extrapolation); (2) methods considering data both forward and backward in time (nearest available observation-NAO; linear extrapolation; polynomial extrapolation); and (3) methods using multi-individual models (linear mixed effects cubic regression-LME3; multiple imputation by chained equation-MICE). The performance of each estimation method was assessed using the difference between the mean outcome value, the remission and low disease activity rates after imputation of the missing values and the true value. RESULTS: When imputing missing baseline values, all methods underestimated equally the true value, but LME3 and MICE correctly estimated remission and low disease activity rates. When imputing missing follow-up values at 6, 12, or 24 months, NAO provided the least biassed estimate of the mean disease activity and corresponding remission rate. These results were not affected by the presence of attrition bias. CONCLUSION: When imputing function and disease activity in large registers of active RA patients, researchers can consider the use of a simple method such as NAO for missing follow-up data, and the use of mixed-effects regression or multiple imputation for baseline data.

• Klíčová slova
• DAS28, disease activity, epidemiology, outcomes research, rheumatoid arthritis,
• MeSH
• algoritmy MeSH
• indukce remise MeSH
• interpretace statistických dat * MeSH
• kohortové studie MeSH
• lidé MeSH
• lineární modely MeSH
• následné studie MeSH
• počítačová simulace MeSH
• revmatoidní artritida epidemiologie   MeSH
• stupeň závažnosti nemoci MeSH
• výzkumný projekt statistika a číselné údaje   MeSH
• zkreslení výsledků (epidemiologie) MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• pozorovací studie MeSH
• práce podpořená grantem MeSH
• srovnávací studie MeSH

In this work, we have investigated retention of maltooligosaccharides and their fluorescent derivatives in hydrophilic interaction liquid chromatography using four different stationary phases. The non-derivatized maltooligosaccharides (maltose to maltoheptaose) and their derivatives with 2-aminobenzoic acid, 2-aminobenzamide, 2-aminopyridine and 8-aminonaphthalene-1,3,6-trisulfonic acid were analyzed on silica gel, aminopropyl silica, amide (carbamoyl-bonded silica) and ZIC-HILIC zwitterionic sulfobetain bonded phase. The partitioning of the analytes between the bulk mobile phase and adsorbed water-rich layer, polar and ionic interactions of analytes with stationary phase have been evaluated and compared. The effects of the mobile phase additives (0.1% (v/v) of acetic acid and ammonium acetate in concentration range 5-30 mmol L(-1)) on retention were described. The suitability of different models for prediction of retention was tested including linear solvent strength model, quadratic model, mixed-mode model, and empirical Neue-Kuss model. The mixed-mode model was extended to the parameter describing the contribution of monomeric glucose unit to the retention of non-derivatized and derivatized maltooligosaccharides, which was used for evaluation of contribution of both, oligosaccharide backbone and end-group to retention.

• Klíčová slova
• Fluorescent derivatives, Hydrophilic interaction liquid chromatography, Liquid chromatography/mass spectrometry, Oligosaccharides, Retention,
• MeSH
• 1-naftylamin chemie   MeSH
• adsorpce MeSH
• aminopyridiny chemie   MeSH
• chemické modely * MeSH
• chemické techniky analytické * MeSH
• chromatografie kapalinová * MeSH
• hydrofobní a hydrofilní interakce MeSH
• oligosacharidy chemie   izolace a purifikace   MeSH
• ortoaminobenzoáty chemie   MeSH
• oxid křemičitý chemie   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• 1-naftylamin MeSH
• alpha-aminopyridine MeSH Prohlížeč
• aminopyridiny MeSH
• anthranilamide MeSH Prohlížeč
• anthranilic acid MeSH Prohlížeč
• maltooligosaccharides MeSH Prohlížeč
• oligosacharidy MeSH
• ortoaminobenzoáty MeSH
• oxid křemičitý MeSH

INTRODUCTION: Sepsis is the main cause of morbidity and mortality in intensive care units and its early diagnosis is not straightforward. Many studies have evaluated the usefulness of various markers of infection, including C-reactive protein (CRP), which is the most accessible and widely used. CRP is of weak diagnostic value because of its low specificity; a better understanding of patterns of CRP levels associated with a particular form of infection may improve its usefulness as a sepsis marker. In the present article, we apply multilevel modeling techniques and mixed linear models to CRP-related data to assess the time course of CRP blood levels in association with clinical outcome in children with different septic conditions. METHODS: We performed a retrospective analysis of 99 patients with systemic inflammatory response syndrome, sepsis, or septic shock who were admitted to the Pediatric Critical Care Unit at the University Hospital, Brno. CRP blood levels were monitored for 10 days following the onset of the septic condition. The effect of different septic conditions and of the surgical or nonsurgical diagnosis on CRP blood levels was statistically analyzed using mixed linear models with a multilevel modeling approach. RESULTS: A significant effect of septic condition and diagnosis on the course of CRP levels was identified. In patients who did not progress to septic shock, CRP blood levels decreased rapidly after reaching peak values - in contrast to the values in patients with septic shock in whom CRP protein levels decreased slowly. Moreover, CRP levels in patients with a surgical diagnosis were higher than in patients with a nonsurgical condition. The magnitude of this additional elevation in surgical patients did not depend on the septic condition. CONCLUSION: Understanding the pattern of change in levels of CRP associated with a particular condition may improve its diagnostic and prognostic value in children with sepsis.

• MeSH
• analýza přežití MeSH
• biologické markery krev   MeSH
• C-reaktivní protein metabolismus   MeSH
• dítě MeSH
• kojenec MeSH
• komorbidita MeSH
• lidé MeSH
• lineární modely MeSH
• mladiství MeSH
• novorozenec MeSH
• předškolní dítě MeSH
• rány a poranění epidemiologie   MeSH
• retrospektivní studie MeSH
• sepse krev   epidemiologie   MeSH
• Check Tag
• dítě MeSH
• kojenec MeSH
• lidé MeSH
• mladiství MeSH
• mužské pohlaví MeSH
• novorozenec MeSH
• předškolní dítě MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Česká republika epidemiologie   MeSH
• Názvy látek
• biologické markery MeSH
• C-reaktivní protein MeSH

BACKGROUND AND AIMS: Spotted knapweed (Centaurea stoebe s.l., Asteraceae) is native to Europe, where it occurs as a diploid (2xEU) and tetraploid cytotype (4xEU), but so far only the tetraploid has been reported in the introduced range in North America (4xNA). In previous studies, significant range shifts have been found towards drier climates in 4xEU compared with 2xEU, and in 4xNA when compared with the native range. In addition, 4x plants showed thicker leaves and reduced specific leaf area compared with 2x plants, suggesting higher drought tolerance in 4x plants. It is thus hypothesized that the 4x cytotype might be better pre-adapted to drought than the 2x, and the 4xNA better adapted than the 4xEU due to post-introduction selection. METHODS: Plants of the three geocytotypes (2xEU, 4xEU and 4xNA ), each represented by six populations, were subjected to three water treatments over 6 weeks in a greenhouse experiment. Plasticity and reaction norms of above- and below-ground biomasses and their ratio, survival rate, stomatal conductance and carbon isotope discrimination were analysed using linear and generalized linear mixed effect models. KEY RESULTS AND CONCLUSIONS: Above-ground and total biomasses of European tetraploids were slightly less affected by drought than those of European diploids, and 4xEU plants maintained higher levels of stomatal conductance under moderate drought than 4xNA plants, thus supporting the pre-adaptation but not the post-introduction evolution hypothesis. Plasticity indexes for most of the traits were generally higher in 2xEU and 4xNA than in 4xEU plants, but these differences were not or were only marginally significant. Interestingly, the effect of population origin and its interaction with treatment was more important than the effects of geocytotype and range. Population means for the control treatment showed several significant associations either with latitude or some aspect of climatic data, suggesting evolution of local adaptations, especially within the 2xEU and 4xEU geocytotypes.

• Klíčová slova
• Biological invasions, Centaurea stoebe, biomass partitioning, carbon isotope discrimination, drought tolerance, local adaptations, plasticity, polyploidy, spotted knapweed, water use efficiency,
• MeSH
• biomasa MeSH
• Centaurea fyziologie   MeSH
• fyziologická adaptace * MeSH
• lineární modely MeSH
• období sucha * MeSH
• podnebí MeSH
• populační dynamika MeSH
• regresní analýza MeSH
• voda MeSH
• zavlečené druhy * MeSH
• zeměpis MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• voda MeSH

The future performance of the widely abundant European beech (Fagus sylvatica L.) across its ecological amplitude is uncertain. Although beech is considered drought-sensitive and thus negatively affected by drought events, scientific evidence indicating increasing drought vulnerability under climate change on a cross-regional scale remains elusive. While evaluating changes in climate sensitivity of secondary growth offers a promising avenue, studies from productive, closed-canopy forests suffer from knowledge gaps, especially regarding the natural variability of climate sensitivity and how it relates to radial growth as an indicator of tree vitality. Since beech is sensitive to drought, we in this study use a drought index as a climate variable to account for the combined effects of temperature and water availability and explore how the drought sensitivity of secondary growth varies temporally in dependence on growth variability, growth trends, and climatic water availability across the species' ecological amplitude. Our results show that drought sensitivity is highly variable and non-stationary, though consistently higher at dry sites compared to moist sites. Increasing drought sensitivity can largely be explained by increasing climatic aridity, especially as it is exacerbated by climate change and trees' rank progression within forest communities, as (co-)dominant trees are more sensitive to extra-canopy climatic conditions than trees embedded in understories. However, during the driest periods of the 20th century, growth showed clear signs of being decoupled from climate. This may indicate fundamental changes in system behavior and be early-warning signals of decreasing drought tolerance. The multiple significant interaction terms in our model elucidate the complexity of European beech's drought sensitivity, which needs to be taken into consideration when assessing this species' response to climate change.

• Klíčová slova
• Climate sensitivity, Dendroecology, Drought, Fagus sylvatica, Forests, Linear mixed-effects models,
• MeSH
• buk (rod) * růst a vývoj   fyziologie   MeSH
• klimatické změny * MeSH
• lesy MeSH
• období sucha * MeSH
• stromy růst a vývoj   fyziologie   MeSH
• Publikační typ
• časopisecké články MeSH

The major quantitative trait loci associated with bunch weight and its component traits in the East African highland banana-breeding population are located on chromosome 3. Bunch weight increase is one of the major objectives of banana improvement programs, but little is known about the loci controlling bunch weight and its component traits. Here we report for the first time some genomic loci associated with bunch weight and its component traits in banana as revealed through a genome-wide association study. A banana-breeding population of 307 genotypes varying in ploidy was phenotyped in three locations under different environmental conditions, and data were collected on bunch weight, number of hands and fruits; fruit length and circumference; and diameter of both fruit and pulp for three crop cycles. The population was genotyped with genotyping by sequencing and 27,178 single nucleotide polymorphisms (SNPs) were generated. The association between SNPs and the best linear unbiased predictors of traits was performed with TASSEL v5 using a mixed linear model accounting for population structure and kinship. Using Bonferroni correction, false discovery rate, and long-range linkage disequilibrium (LD), 25 genomic loci were identified with significant SNPs and most were localized on chromosome 3. Most SNPs were located in genes encoding uncharacterized and hypothetical proteins, but some mapped to transcription factors and genes involved in cell cycle regulation. Inter-chromosomal LD of SNPs was present in the population, but none of the SNPs were significantly associated with the traits. The clustering of significant SNPs on chromosome 3 supported our hypothesis that fruit filling in this population was under control of a few quantitative trait loci with major effects.

• MeSH
• banánovník genetika   MeSH
• fenotyp MeSH
• genetické asociační studie MeSH
• genetické markery MeSH
• genotyp MeSH
• jednonukleotidový polymorfismus MeSH
• lineární modely MeSH
• lokus kvantitativního znaku * MeSH
• ovoce růst a vývoj   MeSH
• šlechtění rostlin * MeSH
• vazebná nerovnováha MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• východní Afrika MeSH
• Názvy látek
• genetické markery MeSH