Maligní melanom je jedním z nejzávažnějších kožních nádorů u lidí i zvířat. Je vysoce odolný vůči konvenčním terapiím a i přes velké úsilí při vývoji nových imunoterapií došlo jen k jejich drobným vylepšením. Proto se jako ideální směr dalšího výzkumu jeví možnost vývoje imunoterapií, které by byly schopné navodit kompletní regresi nádoru, což je ideální výsledek při léčbě jakéhokoliv nádor. Bohužel podmínky potřebné k dosažení úplné regrese nejsou dosud dobře známé. V laboratoři biologie nádorů v Ústavu živočišné fyziologie a genetiky AV ČR je k dispozici model melanomu u miniaturních prasat, u kterého dochází k spontánní regresi nádorů po období progrese spojené s metastázami především do sleziny, plic a lymfatických uzlin, kdy dojde k vyléčení většiny zvířat a pouze asi 5 % umírá na progresi nádoru nebo přidružené komplikace. Další výzkum MeLiM modelu umožní získat nové poznatky o spontánní regresi melanomu a nabídne nové možnosti pro tvorbu účinnějších imunoterapií.
Malignant melanoma is one of the most serious skin cancer diseases in humans and animals. It is highly resistant to conventional therapies and despite major efforts in development of novel immunotherapies there have been only minor improvements. Therefore, an ideal further research should be led towards developing immunotherapies that would be capable of inducing a complete tumor regression. This is the ideal result of the treatment of all tumor. Unfortunately, the conditions required to achieve complete regressions are not well known yet. In the laboratory of tumor biology at the Institute of Animal Physiology and Genetics AS CR an animal model of melanoma is being researched, ie melanoma bearing Libechov minipigs, in which spontaneous tumor regression occurs after a period of progression associated with organ metastases - mainly in the spleen, lungs and lymph nodes. Most animals are completelycured, but around 10 % die of tumor progression or associated complications. Further research of MeLiM model will provide new knowledge about the spontaneous regression of melanoma and offer new possibilities for creating more effective immunotherapy.
- MeSH
- Cyprinodontiformes MeSH
- Humans MeSH
- Melanoma * MeSH
- Swine, Miniature * genetics MeSH
- Disease Models, Animal MeSH
- Mice MeSH
- Neoplasm Regression, Spontaneous MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Mice MeSH
- Animals MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
... CONTENTS -- 1 Introduction to the Logistic Regression Model -- 1.1 Introduction, 1 -- 1.2 Fitting the ... ... Logistic Regression Model, 33 -- 2.4 Testing for the Significance of the Model, 36 -- 2.5 Confidence ... ... Model, 188 -- Exercises, 200 -- 6 Application of Logistic Regression with Different -- Sampling Models ... ... Logistic Regression Model, 280 -- 8.2 Ordinal Logistic Regression Models, 288 -- 8.2.1 Introduction ... ... Strategies for Ordinal Logistic Regression Models, 305 -- 8.3 Logistic Regression Models for the Analysis ...
Wiley series in probability and statistics
2nd ed. xii, 375 s.
Springer series in statistics
1st ed. 568 s.
The aims of this study were to create a regression model of the relationship between load and muscle power output and to determine an optimal load for maximum power output during a countermovement squat and a bench press. 55 males and 48 females performed power testing at 0, 10, 30, 50, 70, 90, and 100% of their individual one-repetition maximum (1-RM) in the countermovement squat and bench press exercises. Values for the maximum dynamic strength and load for each lift were used to develop a regression model in which the ratio of power was predicted from the ratio of the load for each type of lift. By optimizing the regression model, we predicted the optimal load for maximum muscle power. For the bench press and the countermovement squat, the mean optimal loads for maximum muscle output ranged from 50 to 70% of maximum dynamic strength. Optimal load in the acceleration phase of the upward movement of the two exercises appeared to be more important than over the full range of the movement. This model allows for specific determination of the optimal load for a pre-determined power output.
- MeSH
- Models, Biological MeSH
- Adult MeSH
- Physical Endurance physiology MeSH
- Muscle, Skeletal physiology MeSH
- Humans MeSH
- Computer Simulation MeSH
- Energy Transfer physiology MeSH
- Regression Analysis MeSH
- Models, Statistical MeSH
- Muscle Contraction physiology MeSH
- Weight-Bearing physiology MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
V simulační studii (ve výukovém referátu) je po stručném fyziologickém úvodu popsán lineární model izometrické kontrakce kosterního svalu pomocí mechanické analógie. Model se skládá z bloků, z nichž první, generující sílu, představuje kontraktilní aparát a další modelují plastické a elastické vlastnosti svalu na základě pružin a elementů viskozního třeni Platnost modelu je omezena pouze na okolí pracovního bodu činnosti svalu. Výsledky simulace vyjadřují grafy, charakterizující průběh koncentrace vápníkových iontů ve svalu, průběh síly generované svalem a srovnání průběhů této silypři různých periodách budicího signálu. Simulace probíhá v simulačním prostředí MATLAB - SIMULINK, jež tvoří základ výukového simulačního systému, využívaného při výuce předmětu Biokybernetika na katedře kybernetiky FEL, ČVU T v Praze.
After a brief physiological introduction a skeletal nuscle isometric contraction linear model using mezhanical analogy is described in the simulation study. The model consists of blocks; the first of them generaIng force, represents contractile apparatus and the text ones model plastic and elastic muscle qualities on the basis of springs and viscous friction elements. Model validity is limited only on muscle activity working point enviroment The simulation results are presented by graphs characterizing calcium ions in the nuscle concentration course, force generated by muscle course and comparizon of this force courses during various periods of exciting signal The simulation is performed in the MATLAB - SIMULINK environment making the bases of the educational simulation system used by teaching the subject Biocybernetics on the Department of Cybernetics of the Faculty of Electrical Engineering Czech Technical University in Prague.
... Regression Models for Survival Data 67 -- 3.1 Introduction, 67 -- 3.2 Semi-Parametric Regression Models ... ... Regression Model, 87 -- Exercises, 90 vii viii -- CONTENTS -- 4. ... ... Parametric Regression Models 244 -- 8.1 Introduction, 244 -- 8.2 The Exponential Regression Model, 246 ... ... -- 8.3 The Weibull Regression Model, 260 -- 8.4 The Log-Logistic Regression Model, 273 -- 8.5 Other ... ... Parametric Regression Models, 283 Exercises, 283 -- 9. ...
Wiley series in probability and statistics
Second edition xiii, 392 stran : ilustrace, tabulky, grafy ; 24 cm.
- Conspectus
- Kombinatorika. Teorie grafů. Matematická statistika. Operační výzkum. Matematické modelování
- NML Fields
- přírodní vědy
- NML Publication type
- kolektivní monografie
In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique.
- MeSH
- Fuzzy Logic * MeSH
- Humans MeSH
- Linear Models * MeSH
- Recycling * statistics & numerical data MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Survival analysis is commonly conducted in medical and public health research to assess the association of an exposure or intervention with a hard end outcome such as mortality. The Cox (proportional hazards) regression model is probably the most popular statistical tool used in this context. However, when the exposure includes compositional covariables (that is, variables representing a relative makeup such as a nutritional or physical activity behaviour composition), some basic assumptions of the Cox regression model and associated significance tests are violated. Compositional variables involve an intrinsic interplay between one another which precludes results and conclusions based on considering them in isolation as is ordinarily done. In this work, we introduce a formulation of the Cox regression model in terms of log-ratio coordinates which suitably deals with the constraints of compositional covariates, facilitates the use of common statistical inference methods, and allows for scientifically meaningful interpretations. We illustrate its practical application to a public health problem: the estimation of the mortality hazard associated with the composition of daily activity behaviour (physical activity, sitting time and sleep) using data from the U.S. National Health and Nutrition Examination Survey (NHANES).
