Martin Hostovský

Martin Hostovský


Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2014
Verified
Journal Article
Closed access
MHMartin Hostovský
Martin Hostovský
Jana BlahovaJana Blahova
Jana Blahova
LPLucie Plhalova
Lucie Plhalova
VKVladimir Kopriva
Vladimir Kopriva
ZSZdenka Svobodova
Zdenka Svobodova

3 October 2024 in Acta Veterinaria Brno
Verified
Journal Article
Open access
PDF file
LHLucie Hostovská
Lucie Hostovská
MHMartin Hostovský
Martin Hostovský
KNKatarina Nenadović
Katarina Nenadović
EVEva VoslářOvá
Eva VoslářOvá
VVVladimír Večerek
Vladimír Večerek
The aim of this study was to investigate the biochemical indices in the saliva of leisure and sport horses undergoing different levels of workload. The experiment was conducted on 40 horses (4–28 years): sport horses (n = 20), and leisure horses (n = 20). The saliva samples were collected non-invasively 15 min before riding (A), 1 min before riding (B), 1 min after riding (C) and 15 min after riding (D). Albumin (Alb), alkaline phosphatase (ALP), α-amylase (AMY), creatine kinase (CK), creatinine (Crea), glucose (Glc), lactate (Lac), triacylglycerols (TG), total protein (TP), urea and lipid peroxidation (TBARS) were measured in saliva. Riding caused a significant change in many biochemical indices (Alb, CK, Glc, Lac, TBARS and urea) compared to baseline values in leisure horses ( P < 0.05) but only in a few indices (Glc, Crea and TBARS) in sport horses. On the other hand, when comparing groups of leisure and sport horses, higher concentrations of Alb, Glc, TG and urea were found in sport horses whereas raised concentrations of CK and Crea were found in leisure horses. The obtained results indicate the adaptation of trained horses to physical effort. Moreover, this study confirms other possibilities of using salivary biochemical properties for physical stress assessment. Other more detailed comparative studies of load response in horses may provide useful information to quantify the reference range of individual stress indices.

23 February 2020 in Foods
Verified
Journal Article
Open access
PDF file
LKLudmila Kalcakova
Ludmila Kalcakova
Bohuslava TremlováBohuslava Tremlová
Bohuslava Tremlová
MPMatej Pospiech
Matej Pospiech
MHMartin Hostovský
Martin Hostovský
Dani DordevicDani Dordevic
Dani Dordevic
MBMarie Bartlová
Marie Bartlová
The aim of the study was to analytically evaluate quantum dots in immunohistofluorescence (IHF-QD) microscopic imaging as detectors of food allergens—peanut and wheat. The experiment was designed as two in silico experiments or simulations: (a) models of pastry samples were prepared with the addition of allergenic components (peanut and wheat protein components) and without the addition of allergenic components, and (b) positive and negative commercial samples underwent food allergen detection. The samples from both simulations were tested by the ELISA and IHF-QD microscopic methods. The primary antibodies (secondary antibodies to a rabbit Fc fragment with labeled CdSe/ZnS QD) were labelled at 525, 585, and 655 nm emissions. The use of quantum dots (QDs) has expanded to many science areas and they are also finding use in food allergen detection, as shown in the study. The study indicated that differences between the ELISA and IHF-QD microscopic methods were not observable among experimentally produced pastry samples with and without allergenic components, although differences were observed among commercial samples. The important value of the study is certainly the differences found in the application of different QD conjugates (525, 585, and 655). The highest contrast was found in the application of 585 QD conjugates that can serve for the possible quantification of present food allergens—peanuts and wheat. The study clearly emphasized that QD can be used for the qualitative detection of food allergens and can represent a reliable analytical method for food allergen detection in different food matrixes.

1 January 2013
Verified
Journal Article
Closed access
LZLenka Zelníckova
Lenka Zelníckova
Jana BlahovaJana Blahova
Jana Blahova
PMPetr Marsalek
Petr Marsalek
MHMartin Hostovský
Martin Hostovský
MSMarie Sevcikova
Marie Sevcikova
ZSZdenka Svobodova
Zdenka Svobodova

1 January 2015
Verified
Journal Article
Closed access
VSVlasta Stancova
Vlasta Stancova
LPLucie Plhalova
Lucie Plhalova
FTFrantisek Tichy
Frantisek Tichy
VDVeronika Doubkova
Veronika Doubkova
PMPetr Marsalek
Petr Marsalek
ZSZdenka Svobodova
Zdenka Svobodova

1 January 2012
Verified
Journal Article
Closed access
LPLucie Plhalova
Lucie Plhalova
SSStanislava Stepanova
Stanislava Stepanova
Jana BlahovaJana Blahova
Jana Blahova
EPEva Praskova
Eva Praskova
MHMartin Hostovský
Martin Hostovský
IBIveta Bedanova
Iveta Bedanova