2014
NON-INVASIVE SAMPLING AND SUBSEQUENT CAPILLARY ELECTROPHORETIC ANALYSIS OF SWEAT AND SALIVA IN CLINICAL DIAGNOSIS OF CYSTIC FIBROSIS
ĎURČ, Pavol, Michal GREGUŠ, Júlia LAČNÁ, Eva POKOJOVÁ, Jana SKŘIČKOVÁ et. al.Základní údaje
Originální název
NON-INVASIVE SAMPLING AND SUBSEQUENT CAPILLARY ELECTROPHORETIC ANALYSIS OF SWEAT AND SALIVA IN CLINICAL DIAGNOSIS OF CYSTIC FIBROSIS
Autoři
ĎURČ, Pavol (703 Slovensko, domácí), Michal GREGUŠ (703 Slovensko, domácí), Júlia LAČNÁ (703 Slovensko, domácí), Eva POKOJOVÁ (203 Česká republika, domácí), Jana SKŘIČKOVÁ (203 Česká republika, domácí), František FORET (203 Česká republika, domácí) a Petr KUBÁŇ (203 Česká republika, domácí)
Vydání
BRNO, CECE 2014: 11TH INTERNATIONAL INTERDISCIPLINARY MEETING ON BIOANALYSIS, od s. 182-186, 5 s. 2014
Nakladatel
INST ANALYTICAL CHEMISTRY ASCR, V V I-IAC
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
10406 Analytical chemistry
Stát vydavatele
Česká republika
Utajení
není předmětem státního či obchodního tajemství
Forma vydání
tištěná verze "print"
Kód RIV
RIV/00216224:14310/14:00083393
Organizační jednotka
Přírodovědecká fakulta
ISBN
978-80-904959-2-0
UT WoS
000354547400061
Klíčová slova anglicky
Capillary electrophoresis
Změněno: 26. 4. 2016 10:06, Ing. Andrea Mikešková
Anotace
V originále
Capillary electrophoresis (CE) with double opposite end injection (DOEI) and contactless conductivity detection (C4D) was used in a novel approach for diagnosis of cystic fibrosis (CF). A simple, fast and inexpensive "skin wipe" technique for sweat sampling was developed as a time-saving substitute for conventional, iontophoretic sweat sampling. Saliva sample was also obtained. A number of major target analytes (inorganic/organic anions and inorganic cations) were quantified simultaneously in these samples. By applying principal component analysis (PCA) to ion concentration ratios, rather than to individual ion concentrations, more accurate diagnostic tool for CF was obtained. We demonstrate that by using the developed approach and comparing a group of healthy individuals to patients diagnosed with CF, two clearly distinguished clusters can be observed without any data overlap. This approach may thus set a basis for a new method to diagnose CF more reliably.