• MeSH
• Biomedical Research MeSH
• Hemodynamics MeSH
• Lung Diseases, Obstructive complications   MeSH
• Hypertension, Pulmonary diagnosis   MeSH
• Respiratory Function Tests MeSH

• MeSH
• Discriminant Analysis MeSH
• Radiation Injuries, Experimental MeSH
• Forecasting MeSH
• Survival MeSH
• Prognosis methods   MeSH
• Dogs MeSH
• Radiobiology methods   MeSH
• Animals MeSH
• Check Tag
• Dogs MeSH
• Animals MeSH

Recent techniques of image analysis brought the possibility to recognize subjects based on discriminative image features. We performed a magnetic resonance imaging (MRI)-based classification study to assess its usefulness for outcome prediction of first-episode schizophrenia patients (FES). We included 39 FES patients and 39 healthy controls (HC) and performed the maximum-uncertainty linear discrimination analysis (MLDA) of MRI brain intensity images. The classification accuracy index (CA) was correlated with the Positive and Negative Syndrome Scale (PANSS) and the Global Assessment of Functioning scale (GAF) at 1-year follow-up. The rate of correct classifications of patients with poor and good outcomes was analyzed using chi-square tests. MLDA classification was significantly better than classification by chance. Leave-one-out accuracy was 72%. CA correlated significantly with PANSS and GAF scores at the 1-year follow-up. Moreover, significantly more patients with poor outcome than those with good outcome were classified correctly. MLDA of brain MR intensity features is, therefore, able to correctly classify a significant number of FES patients, and the discriminative features are clinically relevant for clinical presentation 1 year after the first episode of schizophrenia. The accuracy of the current approach is, however, insufficient to be used in clinical practice immediately. Several methodological issues need to be addressed to increase the usefulness of this classification approach.

• MeSH
• Discriminant Analysis MeSH
• Adult MeSH
• Humans MeSH
• Linear Models MeSH
• Magnetic Resonance Imaging methods   MeSH
• Brain Mapping MeSH
• Young Adult MeSH
• Brain pathology   MeSH
• Image Processing, Computer-Assisted methods   MeSH
• Psychiatric Status Rating Scales MeSH
• Schizophrenia diagnosis   MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Publication type
• Journal Article MeSH

Východiska: Rozvoj nádorového onemocnění tlustého střeva je mimo jiné charakterizován abnormalitami v syntéze a metabolizmu lipidů, ovlivňujícími energetickou rovnováhu, strukturu a funkci biologických membrán, produkci specifických mediátorů a buněčné signálování. Změny buněčného lipidového profilu a metabolizmu (lipidomu) zásadně ovlivňují chování buněk i jejich odpověď na terapii. K lepšímu pochopení problematiky na buněčné a molekulární úrovni jsou využívány permanentní linie epiteliálních buněk tlustého střeva různého stupně nádorového rozvoje. Naše práce vycházela z předpokladu, že detailní analýza lipidomu různých buněčných linií tlustého střeva může odhalit takové rozdíly v množství a profilu specifických tříd/typů lipidů, které se mohou podílet na jejich rozdílné odpovědi k různým podnětům. Materiál a metody: Z buněk šesti lidských epiteliálních linií tlustého střeva odvozených z tkáně v různém stupni nádorového rozvoje byly izolovány lipidy a podrobeny LC/MS/MS (kapalinová chromatografie s tandemovou hmotnostní spektrometrií) analýze. Bylo stanoveno množství a hmotnostní profily všech tříd fosfolipidů (PL), lysofosfolipidů (lysoPL) a sfingolipidů. Tato data byla matematicky vyhodnocena (shluková a diskriminační analýza) s ohledem na vzájemné srovnání linií a na významně diskriminující typy lipidů. Výsledky: Výsledky shlukové analýzy seřadily buněčné linie dle stupně jejich nádorové transformace (normální buňky, adenom, karcinom, lymfatická metastáza). Výsledky diskriminačních analýz odhalily nejvíce rozlišující typy lipidů i odlišnosti v poměru PL: lysoPL. Ukázaly se zejména významné korelace zastoupení a profilu některých specifických tříd lysoPL a sfingolipidů se stupněm nádorové transformace buněk. Podobné přístupy jsou nyní aplikovány při srovnání lipidomu střevních epiteliálních buněk izolovaných z nádorové vs. nenádorové tkáně pacientů s nádory tlustého střeva. Závěr: Naše výsledky ukázaly, že a) vybrané buněčné linie jsou vhodným modelem pro lipidomické studie a mohou sloužit jako základ k navazujícímu klinickému výzkumu, b) analýza buněčného lipidomu by mohla přispět k rozlišení nádorových a nenádorových buněk také u klinických vzorků, u nichž by specifické typy lipidů mohly být využity jako biomarkery.

Backgrounds: Colon cancer development is often characterized by abnormalities in lipid synthesis and metabolism, which may influence energetic balance, structure and function of biological membranes, or production of specific mediators and cell signalling. The changes in lipid profile and metabolism (lipidome) may significantly affect cell behaviour and response to therapy. Permanent epithelial cell lines at various stages of cancer development are used for better understanding of this topic on cellular and molecular levels. In our study, we hypothesized that detailed analyses of colon cancer cell line lipidomes may help to identify major alterations in the amount and profile of specific lipid classes/species, which can contribute to their different response to various stimuli. Material and Methods: Cellular lipids were isolated from six human epithelial cell lines derived from tissues at various stages of tumour development. Liquid chromatography coupled with tandem mass spectometry analyses were performed in order to determine amount and mass profiles of all phospholipid (PL), lysophospholipid (lysoPL) and sphingolipid classes. The data was statistically evaluated (cluster and discrimination analyses) with respect to mutual comparison of cell lines and to significantly discriminating lipid types. Results: The results of cluster analysis arranged cell lines in order corresponding to their level of transformation (normal cells, adenoma, carcinoma and lymph node metastasis). The results of discrimination analyses revealed the most discriminating lipid types and distinction in PL: lysoPL ratios. Particularly, significant correlation of the amount and profiles of both specific lysoPL and sphingolipid classes with cell transformation level were observed. Similar approaches are now applied to compare lipidomes of colon epithelial cells isolated from tumour vs. non-tumour samples of colon cancer patients. Conclusion: Our results indicate that a) selected cancer cell lines are suitable model for lipidomic studies that can serve as a basis for subsequent clinical research, b) cellular lipidome analyses may help to discriminate tumour and non-tumour cells in clinical samples, where specific types of lipids could serve as biomarkers.

• MeSH
• Adenoma pathology   metabolism   MeSH
• Chromatography, Liquid MeSH
• Discriminant Analysis MeSH
• Phospholipids metabolism   MeSH
• Carcinoma pathology   metabolism   MeSH
• Humans MeSH
• Lymphatic Metastasis pathology   metabolism   MeSH
• Lysophospholipids metabolism   MeSH
• Lipid Metabolism * MeSH
• Cell Transformation, Neoplastic * MeSH
• Biomarkers, Tumor MeSH
• Cell Line, Tumor MeSH
• Colonic Neoplasms * metabolism   pathology   MeSH
• Sphingolipids metabolism   MeSH
• Cluster Analysis MeSH
• Tandem Mass Spectrometry MeSH
• Check Tag
• Humans MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH

• MeSH
• Discriminant Analysis MeSH
• Rodentia anatomy & histology   MeSH
• Myocardial Infarction diagnosis   physiopathology   MeSH
• Rats anatomy & histology   MeSH
• Magnetic Resonance Imaging methods   instrumentation   utilization   MeSH
• Models, Animal MeSH
• Image Processing, Computer-Assisted MeSH
• Software MeSH
• Models, Theoretical MeSH
• Check Tag
• Rats anatomy & histology   MeSH

The p53 tumor suppressor protein is a transcription factor that mediates the cell's response to various kinds of stress by preventing cell division and/or inducing apoptosis. p53 gene mutations have been detected in nearly 50% of human cancers. These gene aberrations are mostly missense point mutations located predominantly in the central DNA-binding domain. In addition to the classical inactivating mutations, there are also dominant-negative, gain-of-function, temperature-sensitive, and cold-sensitive, discriminating, superactive p53 mutations, and some mutations that do not inactivate p53 activity. Several approaches have been developed for detection and analyses of p53 mutations: first, immunochemical methods have been developed to detect p53 protein levels; second, molecular analyses targeting changes in DNA structure are utilized; and third, functional assays are used to explore the biological properties of the p53 protein. Functional analysis of separated alleles in yeast targets the transactivation capability of the p53 protein expressed in yeast cells. This method uses p53 mRNA isolated from cells and tissues to produce a p53 product by RT-PCR. This method has undergone continuous improvement and now serves as a powerful tool for distinguishing various functional types of p53 mutations. Understanding the exact impact of p53 mutation on its function is an important prerequisite for establishment of efficient anti-cancer therapies.

• MeSH
• Financing, Organized MeSH
• Genes, p53 MeSH
• Humans MeSH
• Mutation MeSH
• DNA Mutational Analysis methods   MeSH
• Tumor Suppressor Protein p53 analysis   physiology   genetics   MeSH
• Saccharomyces cerevisiae genetics   MeSH
• Tissue Distribution MeSH
• Check Tag
• Humans MeSH

• MeSH
• Pulmonary Disease, Chronic Obstructive * diagnosis   complications   MeSH
• Discriminant Analysis * MeSH
• Middle Aged MeSH
• Humans MeSH
• Sick Leave * MeSH
• Respiratory Function Tests MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH

• MeSH
• Diastole MeSH
• Echocardiography, Doppler MeSH
• Ventricular Dysfunction, Left MeSH
• Coronary Disease diagnosis   MeSH
• Humans MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Female MeSH

251 patients with coronary heart disease (CHD) and a control group of 32 normal persons were examined with the purpose of establishing the determinants of the left ventricular function and comparing these determinants with the functional significance of coronary stenosis. The subjects were divided into four groups: I--controls; II--patients with normal left ventricular function (EF more than 60%); III--patients with impaired LV function (EF less than 60%) and Group IV--patients with left ventricular aneurysm. Nine parameters were obtained by multivariate discriminant analysis, which characterize and classify the left ventricular function: the ejection fraction (EF), angina pectoris, exercise ECG, left ventricular end-diastolic pressure, mean velocity of circumferential fibre shortening, left ventricular functional index, longitudinal shortening, LV systolic pressure/systolic volume ratio, and coronary index. On the basis of these parameters, all the normal persons, 88% of Group II, 92% of Group III and 72% of Group IV were classified correctly. The study proves that there is a good correlation between the EF and the haemodynamic and angiocardiographic parameters. The complex left ventricular function index facilitates the prognosis of surgical results. Abnormalities in left ventricular function cannot be reliably assessed by the coronary index values alone.

• MeSH
• Angina Pectoris physiopathology   MeSH
• Adult MeSH
• Coronary Disease physiopathology   MeSH
• Middle Aged MeSH
• Humans MeSH
• Ventricular Function MeSH
• Heart physiopathology   MeSH
• Heart Ventricles physiopathology   MeSH
• Constriction, Pathologic physiopathology   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Publication type
• Journal Article MeSH
• Comparative Study MeSH

• Keywords
• Analýza dat, Analýza statistická, Regrese,

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