The analysis of functional magnetic resonance imaging (fMRI) data involves multiple stages of data pre-processing before the activation can be statistically detected. Spatial smoothing is a very common pre-processing step in the analysis of functional brain imaging data. This study presents a broad perspective on the influence of spatial smoothing on fMRI group activation results. The data obtained from 20 volunteers during a visual oddball task were used for this study. Spatial smoothing using an isotropic gaussian filter kernel with full width at half maximum (FWHM) sizes 2 to 30 mm with a step of 2 mm was applied in two levels - smoothing of fMRI data and/or smoothing of single-subject contrast files prior to general linear model random-effects group analysis generating statistical parametric maps. Five regions of interest were defined, and several parameters (coordinates of nearest local maxima, t value, corrected threshold, effect size, residual values, etc.) were evaluated to examine the effects of spatial smoothing. The optimal filter size for group analysis is discussed according to various criteria. For our experiment, the optimal FWHM is about 8 mm. We can conclude that for robust experiments and an adequate number of subjects in the study, the optimal FWHM for single-subject inference is similar to that for group inference (about 8 mm, according to spatial resolution). For less robust experiments and fewer subjects in the study, a higher FWHM would be optimal for group inference than for single-subject inferences.

• MeSH
• algoritmy MeSH
• artefakty MeSH
• design vybavení MeSH
• dospělí MeSH
• financování organizované MeSH
• kontrastní látky MeSH
• lidé MeSH
• magnetická rezonanční tomografie metody   MeSH
• mapování mozku metody   přístrojové vybavení   MeSH
• mozek patologie   MeSH
• normální rozdělení MeSH
• počítačové zpracování obrazu MeSH
• reprodukovatelnost výsledků MeSH
• statistické modely MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH

The bacterial endosymbiont Wolbachia has been used to control insect pests owing to its ability to manipulate their life history and suppress infectious diseases. Therefore, knowledge on Wolbachia dynamics in natural populations is fundamental. The European cherry fruit fly, Rhagoletis cerasi, is infected with the Wolbachia strain wCer2, mainly present in southern and central European populations, and is currently spreading into wCer2-uninfected populations driven by high unidirectional cytoplasmic incompatibility. Here, we describe the distribution of wCer2 along two transition zones where the infection is spreading into wCer2-uninfected R. cerasi populations. Fine-scale sampling of 19 populations in the Czech Republic showed a smooth decrease of wCer2 frequency from south to north within a distance of less than 20 km. Sampling of 12 Hungarian populations, however, showed a sharp decline of wCer2 infection frequency within a few kilometres. We fitted a standard wave equation to our empirical data and estimated a Wolbachia wave speed of 1.9 km yr-1 in the Czech Republic and 1.0 km yr-1 in Hungary. Considering the univoltine life cycle and limited dispersal ability of R. cerasi, our study highlights a rapid Wolbachia spread in natural host populations.

• MeSH
• prostorová analýza * MeSH
• Tephritidae mikrobiologie   MeSH
• Wolbachia fyziologie   MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Česká republika MeSH
• Maďarsko MeSH

In epidemiology, it is very important to estimate the baseline incidence of infectious diseases. From this baseline, the epidemic threshold can be derived as a clue to recognize an excess incidence, i.e. to detect an epidemic by mathematical methods. Nevertheless, a problem is posed by the fact that the incidence may vary during the year, as a rule, in a season dependent manner. To model the incidence of a disease, some authors use seasonal trend models. For instance, Serfling applies the sine function with a phase shift and amplitude. A similar model based on the analysis of variance with kernel smoothing and Serfling's higher order models, i.e. models composed of multiple sine-cosine function pairs with a variably long period, will be presented below. Serfling's model uses a long-term linear trend, but the linearity may not be always acceptable. Therefore, a more complex, long-term trend estimation will also be addressed, using different smoothing methods. In addition, the issue of the time unit (mostly a week) used in describing the incidence is discussed.

• MeSH
• epidemiologické metody MeSH
• epidemiologie * MeSH
• incidence MeSH
• lidé MeSH
• roční období * MeSH
• statistické modely * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

PURPOSE: We reviewed the survival time for patients with primary brain tumors undergoing treatment with stereotactic radiation methods at the Masaryk Memorial Cancer Institute Brno. We also identified risk factors and characteristics, and described their influence on survival time. METHODS: In summarizing survival data, there are two functions of principal interest, namely, the survival function and the hazard function. In practice, both of them can depend on some characteristics. We focused on nonparametric methods, propose a method based on kernel smoothing, and compared our estimates with the results of the Cox regression model. The hazard function is conditional to age and gross tumor volume and visualized as a color-coded surface. A multivariate Cox model was also designed. RESULTS: There were 88 patients with primary brain cancer, treated with stereotactic radiation. The median survival of our patient cohort was 47.8 months. The estimate of the hazard function has two peaks (about 10 months and about 40 months). The survival time of patients was significantly different for various diagnoses (p≪0.001), KI (p = 0.047) and stereotactic methods (p = 0.033). Patients with a greater GTV had higher risk of death. The suitable threshold for GTV is 20 cm3. Younger patients with a survival time of about 50 months had a higher risk of death. In the multivariate Cox regression model, the selected variables were age, GTV, sex, diagnosis, KI, location, and some of their interactions. CONCLUSION: Kernel methods give us the possibility to evaluate continuous risk variables and based on the results offer risk-prone patients a different treatment, and can be useful for verifying assumptions of the Cox model or for finding thresholds of continuous variables.

• MeSH
• dospělí MeSH
• Kaplanův-Meierův odhad MeSH
• lidé středního věku MeSH
• lidé MeSH
• meningeom mortalita   patologie   chirurgie   MeSH
• mladiství MeSH
• mladý dospělý MeSH
• nádory mozku mortalita   patologie   chirurgie   MeSH
• prognóza MeSH
• proporcionální rizikové modely MeSH
• radiochirurgie MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• tumor burden MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• srovnávací studie MeSH

V rutinních systémech sledování nemocnosti na jednotlivé diagnózy je jedním z důležitých problé-mů analýza časového vývoje například týdenních počtů hlášení. Tento článek se zabývá metodikouuvedené problematiky. V praxi se ukazuje, že počty výskytů mnohých onemocnění jsou závislé naroční době. Samozřejmě je nutno vzít v úvahu i dlouhodobý vývoj počtu onemocnění. V článku sediskutuje o dvou často používaných přístupech. Jde jednak o Boxovu-Jenkinsovu analýzu časovýchřad, která modeluje „náhodnou chybu“, a jednak o metodu dekompozice trendu, která se pokoušírozložit pozorovaný počet případů na systematické složky (dlouhodobý trend a sezonní složku)a náhodné kolísání. V článku je popsána možnost vyhlazení odhadu časové řady pomocí modifi-kovaného jádrového odhadu. Pro ilustraci obou metod jsou použity týdenní údaje o celorepubliko-vých počtech nemocných s hepatitidou A, zarděnkami a salmonelózou.

In routine systems investigating the morbidity according to diagnosis it is very useful to analysethe development in time (for example the development of weekly reports). This paper is concernedwith the methodology of such analyses. In practice it appears that the number of cases depends onseason. It stands to reason, that it is necessary to consider also long-therm trends. In this paper twodifferent approaches are discussed – the Box-Jenkins analysis, which describes the random errorand the Method of Trend Decomposition which spread the number of cases into the systematiccomponent (long term trend and seasonal effect) and random variability. The authors describe themethod of smoothing the estimate of the time series by kernel estimate. In both approaches theyuse weekly reports from the whole Czech Republic of diagnoses viral hepatitis A, rubella andsalmonellosis.

• MeSH
• časové faktory MeSH
• epidemiologické metody MeSH
• morbidita trendy   MeSH
• statistické modely MeSH

BACKGROUND: Socioeconomic inequalities are increasingly recognised as an important public health issue, although their role in the leading causes of mortality in urban areas in Europe has not been fully evaluated. In this study, we used data from the INEQ-CITIES study to analyse inequalities in cause-specific mortality in 15 European cities at the beginning of the 21st century. METHODS: A cross-sectional ecological study was carried out to analyse 9 of the leading specific causes of death in small areas from 15 European cities. Using a hierarchical Bayesian spatial model, we estimated smoothed Standardized Mortality Ratios, relative risks and 95% credible intervals for cause-specific mortality in relation to a socioeconomic deprivation index, separately for men and women. RESULTS: We detected spatial socioeconomic inequalities for most causes of mortality studied, although these inequalities differed markedly between cities, being more pronounced in Northern and Central-Eastern Europe. In the majority of cities, most of these causes of death were positively associated with deprivation among men, with the exception of prostatic cancer. Among women, diabetes, ischaemic heart disease, chronic liver diseases and respiratory diseases were also positively associated with deprivation in most cities. Lung cancer mortality was positively associated with deprivation in Northern European cities and in Kosice, but this association was non-existent or even negative in Southern European cities. Finally, breast cancer risk was inversely associated with deprivation in three Southern European cities. CONCLUSIONS: The results confirm the existence of socioeconomic inequalities in many of the main causes of mortality, and reveal variations in their magnitude between different European cities.

• MeSH
• Bayesova věta MeSH
• chudoba MeSH
• disparity zdravotního stavu * MeSH
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• příčina smrti trendy   MeSH
• prostorová analýza MeSH
• průřezové studie MeSH
• sociální determinanty zdraví * MeSH
• socioekonomické faktory MeSH
• stupeň vzdělání MeSH
• velkoměsta ekonomika   statistika a číselné údaje   MeSH
• zdraví ve městech ekonomika   statistika a číselné údaje   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Evropa MeSH
• velkoměsta ekonomika   statistika a číselné údaje   MeSH

• MeSH
• longitudinální studie MeSH
• sociální vědy metody   MeSH
• výzkum MeSH
• výzkumný projekt MeSH
• Publikační typ
• monografie MeSH

• Konspekt
• Sociologie
• NLK Obory
• sociologie

Cíle. Cílem práce bylo zjistit psychometrické vlastnosti české verze Dotazníku obecné self--efficacy (General Self-Efficacy Scale – GSES) u populace hospitalizovaných pacientů.Vzorek a metodika. Sledovaný soubor činil 386 respondentů hospitalizovaných ve Fakultní ne-mocnici Hradec Králové. Byla použita česká verze dotazníku General Self-Efficacy Scale.Statistická analýza. Veškeré analýzy byly pro-vedeny v prostředí R. Faktorová struktura byla ověřována s využitím teorie odpovědi na polož-ku (Item Response Theory), a to pomocí dvou-parametrového Graded Response Modelu. Tento byl použit i pro ověření invariance měření mezi muži a ženami. Pro hodnocení vztahu obecné self-efficacy s demografickými proměnnými byla použita lineární regrese a t-testy. Percen-tilové normy byly sestrojeny pomocí vyhlazené kumulativní distribuční funkce pro muže a ženy zvláště.Výsledky. Celkový skór škály se pohyboval v rozmezí 15–40 bodů s průměrem M = 30,86 (SD = 6,05). Psychometrické vlastnosti české verze dotazníku GSES jsou dobré, vnitřní kon-zistence je vysoká (Cronbachovo α = 0,924; ωt = 0,938). Struktura dotazníku je spíše dvou-dimenzionální, korelace obou faktorů je však velmi vysoká. Je tedy smysluplné pracovat s je-diným celkovým skórem dotazníku. Ze všech sledovaných proměnných pouze pohlaví mělo statisticky významný vliv na vnímanou self--efficacy (SE), škála byla pro obě pohlaví in-variantní. Rozdíly mezi klinikami byly velmi malé, pouze respondenti z psychiatrické kliniky dosahovali statisticky významně nižšího skóru oproti respondentům z ostatních klinik.Limity studie. Limity studie vyplývají z jejího průřezového charakteru a skutečnosti, že výběr respondentů nebyl reprezentativní. Data jsou založena na subjektivních výpovědích; jedná se o respondenty hospitalizované s různými zdra-votními potížemi.

Objectives. The aim of this study was to analyze the psychometric properties of the Czech version of the General Self-Efficacy Scale (GSES) in the group of hospitalized patients. Sample and setting. The sample contained 386 respondents hospitalized in the Faculty hospital Hradec Kralove. The Czech version of GSES was used. Statistical analysis. All the analyses were performed in the R environment. Factor structure was tested using Item Response Theory (IRT), namely two‑parameters Graded Response model. This model was used also for testing measurement invariance for men and women. We used t‑tests and linear model to test relation between GSES and demographical variables. Percentile norms were constructed using kernel smoothed cumulative distribution for men and women separately. Results. The score of the scale ranged from 15 to 40 points with an average of M = 30,86 (SD = 6,05). Our results suggest that the Czech version of the GSES has satisfactory psychometric properties, the internal consistency is on high level (Cronbach α = 0,924; ωt = 0,938). Even though the analysis of the structure of the questionnaire showed to be slightly twodimensional, the correlation of the two factors is quite high. This implies the potential of working with one universal questionnaire score. Of all monitored variables, only gender had statistically significant influence over the perceived self-efficacy, the scale was invariant for both genders. The differences between clinics were very small, only the respondents from psychiatric clinic achieved statistically significant lower score. Study limitations. The limits of the study come from its cross-sectional character and the fact that the choise of respondents was not representative. Data are based on subjective statements coming from respondents hospitalized with various health problems.

• MeSH
• vzorkové studie MeSH

• Konspekt
• Statistika
• NLK Obory
• statistika, zdravotnická statistika

• MeSH
• matematické výpočty počítačové MeSH
• matematika MeSH
• numerická analýza pomocí počítače * MeSH
• Publikační typ
• monografie MeSH

• Konspekt
• Počítačová věda. Výpočetní technika. Informační technologie
• NLK Obory
• přírodní vědy
• přírodní vědy