Jan Evangelista Purkyně University in Ústí nad Labem
Recent publications
While extensive research addresses the working conditions of international Ph.D. students in Western countries, only little explores their experiences within Central and Eastern European (CEE) countries. CEE countries favour masculine values, hierarchical structures and conservatism, and English does not serve as a primary language in both academic and non‐academic contexts. This study, involving seventeen international Ph.D. students in the Czech Republic, aimed to elucidate their experiences through in‐depth phenomenological interviews. Inductive analysis uncovered common challenges of international Ph.D. students, including language barriers, cultural misunderstandings, discrimination by university staff and gender biases. Participants also highlighted gaps in support and unclear career prospects, which contributed to increased uncertainty. To remain resilient, the participants emphasised the need for self‐care, intrinsic motivation and self‐regulation. The study suggests that enhancing university language access, equity policies, mental health services and career development programming could dramatically improve inclusiveness.
Background Sulodexide is a glycosaminoglycan-based drug prescribed to patients with angiopathy. We performed a pilot study to investigate whether sulodexide positively modulates the endothelial glycocalyx (EG) layer and the microcirculation in a porcine model of EG enzymatic damage. The EG is a sugar-based endothelial lining that is involved in the physiology of the capillary wall and the pathogenesis of many diseases. Methods EG damage was induced in eight piglets by hyaluronidase III and heparanase I given intravenously. Four animals received sulodexide 600 IU intravenously before the enzymes and four animals after the enzymes were administered. Four animals constituted a control group. Sublingual microcirculation by side-stream dark field imaging and plasmatic concentration of syndecan-1 by ELISA were measured at baseline, 20 min after intervention, and at the 40th, and 60th minute onwards. The statistics were performed with a one-way ANOVA test with Turkey's correction for multiple comparisons testing. Timepoint comparison was performed by Student t-test or Mann-Whitney test. Results At baseline, there were no statistically significant differences between the animal groups. After the intervention, the levels of syndecan-1 were significantly lower in the control group. While there were no differences between the two intervention groups. The sublingual microcirculation analysis showed that the DeBacker score was significantly higher in the control group. At 60 min, there was also a statistically significant difference in DeBacker score between the groups (8.1 ± 1.6 mm ⁻¹ in the group with enzymes given first and 11 ± 0.92 mm ⁻¹ in the group with sulodexide given first, p = 0.03). The analysis of the proportion of perused vessels did not show any statistically significant differences. Conclusion The results of the study demonstrated a working model of EG damage but no specific action of sulodexide on EG modulation. In the sublingual microcirculation analysis, the sulodexide reduced the fall in absolute tissue perfusion in 60 min.
Background The ischemia-reperfusion injury (IRI) is unavoidable in vascular surgery. Damage to the microcirculation and endothelial glycocalyx might set up a shock with loss of circulatory coherence and organ failure. Sulodexide may help to protect endothelial glycocalyx and alleviate the ischemia-reperfusion injury. Methods Twenty female piglets underwent surgery with a 30-min-long suprarenal aortic clamp, followed by two hours of reperfusion. Ten piglets received sulodexide before the clamp, and 10 received normal saline. Blood and urine samples were taken at baseline and in 20-min intervals until the 120 th minute to analyze the serum syndecan-1, E-selectin, and thrombomodulin. Albumin and glycosaminoglycans were examined in the urine. The kidney biopsies before and after the protocol were examined by light microscopy with hematoxylin-eosin staining. The sublingual microcirculation was recorded by side-stream dark field imaging at the time as blood and urine. Results Based on the 2-way ANOVA testing, there was no statistically significant difference in the parameters of sublingual microcirculation. Serum markers of endothelial cell activation and damage (E-selectin and thrombomodulin) did not show any statistically significant difference either. Syndecan-1, a marker of glycocalyx damage, showed statistically significantly higher values based on the 2-way ANOVA testing (p < 0.0001) with the highest difference in the 80 th minute: 7.8 (3.9–44) ng/mL in the control group and 1.8 (0.67–2.8) ng/mL in the sulodexide group. In the urine, the albuminuria was higher in the control group, although not statistically significant. Glycosaminoglycans were statistically significantly higher in the sulodexide group based on the mixed-effect analysis due to the intervention itself. Histological analysis of the renal biopsies showed necrosis in both groups after reperfusion. Conclusion Administering sulodexide significantly reduced the level of endothelial markers of IRI. The study results support further research into using preemptive administration of sulodexide to modulate IRI in clinical medicine.
The care of German tombs and graves remains a sensitive and complex issue in Central Europe, particularly in the Czech Republic. This study adopts a historical–geographical approach to explore German cemeteries and graves as significant memory landscapes. Specifically, it investigates the current state of German cemeteries in the Czech Republic, identifies forms of devastation, and examines the tools available to burial ground operators for their maintenance. The theoretical framework draws upon the concepts of lieux de mémoire (sites of memory) and a metaphorical understanding of memory landscapes. Empirically, the study involves on-site visits to cemeteries and the implementation of semi-structured interviews in three case study regions within the country. The findings contribute to a proposal for measures aimed at preserving and caring for abandoned German cemeteries, taking into account ongoing scholarly debates on the geography and politics of memory. Among the key recommendations is the establishment of a subsidy programme to support, even symbolically, the rehabilitation of graves of significant historical figures. Additionally, the development of a methodological guide is proposed to assist mayors and other burial ground operators in addressing practical challenges related to the care and restoration of these graves.
Proximally sensed laser scanning presents new opportunities for automated forest ecosystem data capture. However, a gap remains in deriving ecologically pertinent information, such as tree species, without additional ground data. Artificial intelligence approaches, particularly deep learning (DL), have shown promise towards automation. Progress has been limited by the lack of large, diverse, and, most importantly, openly available labelled single‐tree point cloud datasets. This has hindered both (1) the robustness of the DL models across varying data types (platforms and sensors) and (2) the ability to effectively track progress, thereby slowing the convergence towards best practice for species classification. To address the above limitations, we compiled the FOR‐species20K benchmark dataset, consisting of individual tree point clouds captured using proximally sensed laser scanning data from terrestrial (TLS), mobile (MLS) and drone laser scanning (ULS). Compiled collaboratively, the dataset includes data collected in forests mainly across Europe, covering Mediterranean, temperate and boreal biogeographic regions. It includes scattered tree data from other continents, totaling over 20,000 trees of 33 species and covering a wide range of tree sizes and forms. Alongside the release of FOR‐species20K, we benchmarked seven leading DL models for individual tree species classification, including both point cloud (PointNet++, MinkNet, MLP‐Mixer, DGCNNs) and multi‐view 2D‐based methods (SimpleView, DetailView, YOLOv5). 2D Image‐based models had, on average, higher overall accuracy (0.77) than 3D point cloud‐based models (0.72). Notably, the performance was consistently >0.8 across scanning platforms and sensors, offering versatility in deployment. The top‐scoring model, DetailView, demonstrated robustness to training data imbalances and effectively generalized across tree sizes. The FOR‐species20K dataset represents an important asset for developing and benchmarking DL models for individual tree species classification using proximally sensed laser scanning data. As such, it serves as a crucial foundation for future efforts to classify accurately and map tree species at various scales using laser scanning technology, as it provides the complete code base, dataset, and an initial baseline representative of the current state‐of‐the‐art of point cloud tree species classification methods.
In order to canvass the state of the art of research on Okun’s law, the paper surveys 84 articles published in Web of Science™ journals between 1995 and 2020 occupied with estimating the relationship between unemployment and output in the spirit of an approach proposed by Okun (1962). A bibliometric analysis is conducted to identify the most influential works and authors, to establish links between them, and to outline research fronts with main paths of knowledge diffusion. Under a content analysis, the articles included in the survey are further classified by their leitmotif and research agenda as well as by their geographical scope. The basal methodological choices of the articles are overviewed and their temporal patterns are studied. An emphasis is put on the stylized facts constituting the research agenda of 57 of the surveyed applications of Okun’s law (such as instability over time, asymmetries, or age and gender specificity). A majority of studies estimated Okun’s law on the basis of a regression equation that may suggest that it is unemployment that responds to fluctuations in output and adopted the difference version of Okun’s law. In estimating the gap version, the Hodrick-Prescott filter has continued to be a preferred choice despite its well-known flawed statistical properties. Lotka’s law indicates an above-average level of research productivity of authors in this field. The findings provide insights into the intellectual structure of the empirics of Okun’s law and act as guidance for future research on cyclical unemployment-output fluctuations.
We compared the applicability of 3D fibrous scaffolds, produced by our patented centrifugal spinning technology, in soft tissue engineering. The scaffolds were prepared from four different biocompatible and biodegradable thermoplastics, namely, polylactide (PLA), polycaprolactone (PCL), poly(3-hydroxybutyrate) (PHB), and poly(1,4-butylene succinate) (PBS) and their blends. The combined results of SEM and BET analyses revealed an internal hierarchically organized porosity of the polymeric micro/nanofibers. Both nanoporosity and capillary effect are crucial for the water retention capacity of scaffolds designed for tissue engineering. The increased surface area provided by nanoporosity enhances water retention, while the capillary effect facilitates the movement of water and nutrients within the scaffolds. When the scaffolds were seeded with adipose-derived stem cells (ASCs), the ingrowth of these cells was the deepest in the PLA/PCL 13.5/4 (w/w) composite scaffolds. This result is consistent with the relatively large pore size in the fibrous networks, the high internal porosity, and the large specific surface area found in these scaffolds, which may therefore be best suited as a component of adipose tissue substitutes that could reduce postoperative tissue atrophy. Adipose tissue constructs produced in this way could be used in the future instead of conventional fat grafts, for example, in breast reconstruction following cancer ablation.
The current utilization of wheat dust (WD) and hexane-extracted rapeseed scrap (RS) in Central Europe is inefficient and non-ecological. Therefore, it is necessary to identify an appropriate waste treatment that supports the principles of the circular economy. For this reason, the aforementioned wastes were pyrolyzed, resulting in the production of biochars, which are commonly used as absorbents or soil amendments. These biochars were then steam activated, characterized, and evaluated for potential further suitable and sustainable utilization. The structure, porosity, specific surface area, and composition of bound functional groups, nutrients, toxic elements, cation exchange capacity (CEC), and pH were analyzed as important parameters for biochar applications. RS biochar contained high concentrations of nutrients (N 75.9, P 21.5, K 15.1, C 603, Ca 14.3, Mg 8.31, S 5.40 g·kg⁻¹ wt. all). The CEC was remarkably high 87.0 cmol·kg⁻¹ for the RS biochar. The SSA value increased in fivefold in both samples upon activation (11.0 m²·g⁻¹ for WD biochar and 0.8 m²·g⁻¹ for RS biochar). The pore depth increased in accordance with activation temperature. Alkanes, aromatics, and oxygenated groups were detected on the biochars surfaces, yet more evident in WD. WD biochar could be used as an adsorbent for organic pollutants because its structure, surface area, and representation of functional group predict high adsorption efficiency, especially after activation. Raw RS biochar is more suited to utilization as a soil amendment, due to its high concentration of nutrients. These utilizations of biochar support the circular economy, eliminate pollution, improve soil properties, and reduce the need for industrially produced fertilizers and sorbents. Graphical abstract
Changes in climate patterns have a significant impact on agricultural production. A comprehensive understanding of weather changes in arable farming is essential to ensure practical and effective strategies for farmers. Our research aimed to investigate how different fertilization interacts with environmental factors, examine their effects on wheat yield and varietal response over time, minimize nitrogen (N) fertilizer using alfalfa as a proceeding crop, and recommend an optimum N dose based on the latest weather conditions. A long-term experiment including 15 seasons (1961–2022) was studied, where a wheat crop followed alfalfa with different N applications. Our results indicated that the average temperature in the Caslav region has increased by 0.045°C per year, more significantly since 1987. Moreover, precipitation slightly decreased by 0.247 mm, but not significantly. The average November temperatures are gradually rising, positively affecting wheat grain yield. July precipitation negatively impacted grain yield only in years with extraordinary rainfall. Additionally, new wheat varieties (Contra, Mulan, Julie) yielded statistically more than the old variety (Slavia). Effectively managing nitrogen under various climate conditions is essential for promoting plant growth and reducing environmental N losses. The optimal N dosage was determined at 65 kg/ha N, resulting in an average yield of 9.1 t/ha following alfalfa as a preceding crop. Alfalfa reduces the need for N fertilization and contributes to sustainable conventional agriculture. Our findings will serve as a foundation for designing future climate change adaptation strategies to sustain wheat production.
Surface modification of various polymer foils was achieved by UV activation and chemical grafting with cysteamine to improve surface properties and antimicrobial efficacy. UVC activation at 254 nm led to changes in surface wettability and charge density, which allowed the introduction of amino and thiol functional groups by cysteamine grafting. X-ray photoelectron spectroscopy (XPS) confirmed increased nitrogen and sulfur content on the modified surfaces. SEM analysis revealed that UV activation and cysteamine grafting resulted in distinct surface roughness and texturing, which are expected to enhance microbial interactions. Antimicrobial tests showed increased resistance to algal growth (inhibition test) and bacterial colonization (drop plate method), with significant improvement observed for polyethylene terephthalate (PET) and polyetheretherketone (PEEK) foils. The important factors influencing the efficacy included UV exposure time and cysteamine concentration, with longer exposure and higher concentrations leading to bacterial reduction of up to 45.7% for Escherichia coli and 55.6% for Staphylococcus epidermidis. These findings highlight the potential of combining UV activation and cysteamine grafting as an effective method for developing polymeric materials with enhanced antimicrobial function, offering applications in industries such as healthcare and packaging.
Hepatocellular carcinoma (HCC) cells critically depend on PARP1 and CHK1 activation for survival. Combining the PARP inhibitor (PARPi) olaparib with a CHK1 inhibitor (MK-8776, CHK1i) produced a synergistic effect, reducing cell viability and inducing marked oxidative stress and DNA damage, particularly in the HepG2 cells. This dual treatment significantly increased apoptosis markers, including γH2AX and caspase-3/7 activity. Both HCC cell lines exhibited heightened sensitivity to the combined treatment. The effect of drugs on the expression of proliferation markers in an olaparib-resistant patient-derived xenograft (PDX) model of ovarian cancer was also investigated. Ovarian tumors displayed reduced tissue growth, as reflected by a drop in proliferation marker Ki-67 levels in response to PARPi combined with CHK1i. No changes were observed in corresponding liver tissues using Ki-67 and pCHK staining, which indicates the absence of metastases and a hepatotoxic effect. Thus, our results indicate that the dual inhibition of PARP and CHK1 may prove to be a promising therapeutic approach in the treatment of primary HCC as well as OC tumors without the risk of liver metastases, especially in patients with olaparib-resistant tumor profiles.
Introduction Initial evidence suggests that engaging with accepting communities on social media such as Instagram may inform sexual minority youths' sense of stigma and well‐being. However, as existing research has predominately drawn upon cross‐sectional or qualitative designs, it is currently unclear whether the positive experiences identified in previous research accumulate, endure, or evolve over time. We also know relatively little about whether engagement with accepting online communities is primarily a compensatory or enhancing behavior. Thus, drawing upon minority stress theory and broaden‐and‐build theory, this study explores the longitudinal reciprocal relationships between perceived stigma, well‐being, and engagement with accepting Instagram communities. Method Three‐wave panel data were collected from 460 sexual minority youth in the United States and Poland (M age = 18.58, SD = 1.64), and data were analyzed using a random intercept cross‐lagged panel model. Results At the between‐person level, engagement with accepting Instagram communities was positively associated with perceived stigma and negatively associated with well‐being. No significant within‐person associations emerged between perceived stigma and engagement with accepting Instagram networks. However, a positive reciprocal relationship was found between well‐being and engagement with accepting Instagram communities. Cultural context had no moderating effect on the hypothesized model. Conclusions Results suggest that whilst the interrelations between perceived stigma and engaging with accepting online networks may be short‐lived, engaging with supportive Instagram communities may contribute to an upward spiral of positive emotions. Findings therefore extend the existing literature regarding the potential benefits of social media use amongst sexual minority youth.
Finding a way to increase the amount of recycled waste tyres is a current global challenge. Among others, the production of ground tyre rubber (GTR) and its application in a new rubber compound looks as a perspective way. However, the compatibility of GTR and rubber matrix is limited, leading to insufficient properties of the new material. To improve them, it is suitable to activate the GTR prior to mixing. In this paper, GTR obtained by water jet process was activated with microwave irradiation (i) in a household oven at 400 W and 800 W for 1 and 3 min, and (ii) in an industrial device at 500 W, 1000 W, 1500 W and 1750 W for 1, 3 and 5 min. A total of 7% (w/w) of the irradiated GTR was incorporated into a carbon black-filled rubber compound based on styrene-butadiene rubber (SBR), natural rubber (NR) and butadiene rubber (BR), with a formulation for off-road tyre treads. Most compounds containing microwave-treated GTR showed comparable or better properties than the reference with untreated GTR (tensile strength, 14.9 MPa; elongation at break, 437%; modulus at 300% elongation, 8.97 MPa; hardness, 65.6 Shore A). The industrial microwave device offered better results and the possibility of use of higher variation in conditions than the home microwave oven.
This study investigates the determinants influencing the labour market integration of former clients of rehabilitation centres, with a focus on past clients of Europe Teen Challenge (ETC). The research aims to examine the impact of economic, social and personal factors on the likelihood of successful labour market integration and the motivation to maintain employment among former ETC rehab clients. The study utilizes a questionnaire encompassing sections on employment, demographics, work experience, societal and personal elements related to motivation theories and substance usage. The results indicate that poor relations with superiors significantly reduce the duration of job retention. Experience exhibits a beneficial impact on labour market involvement, and previous users of hallucinogens demonstrate higher job retention rates. Salary, commute to work, prior alcohol addiction, workplace discrimination due to past substance abuse and limited opportunities for education or certification also play crucial roles in labour market integration. The study emphasizes the importance of supportive work environments and tailored strategies to enhance labour market outcomes for individuals with a history of substance abuse. These findings contribute to a better understanding of the complexities surrounding labour market integration for former rehab clients and offer implications for policy and practice in the field of rehabilitation and workforce integration.
This study focuses on selecting a suitable 3D printer and defining experimental methods to gather the necessary data for determining the optimal filament material for printing components of the VEX GO and VEX IQ robotic kits. The aim is to obtain the required data to identify an appropriate filament material and set 3D printing parameters to achieve the desired mechanical properties of the parts while maintaining cost-effectiveness. Another key objective is achieving optimal operational functionality, ensuring the required part performance with minimal printing costs. It is desirable for the modeled and printed parts to exhibit the required mechanical properties while maintaining economic efficiency. Another crucial aspect is achieving optimal functionality of the produced parts with minimal printing costs. This will be assessed by analyzing the impact of key 3D printing technology parameters, focusing in this research phase on material selection. The criteria for selecting filament materials include ease of printability under the conditions of primary and secondary schools, simplicity of printing, minimal need for post-processing, and adequate mechanical properties verified through experimental measurements and destructive tests on original parts from VEX GO and VEX IQ kits. The study analyzed various filaments regarding their mechanical properties, printability, and cost-effectiveness. The most significant practical contribution of this study is selecting a suitable filament material tested through a set of destructive tests, emphasizing maintaining the mechanical properties required for the real-life application of the parts. This includes repetitive assembly and disassembly of various robotic model constructions and their activation for demonstration purposes and applications of STEM/STEAM/STREAM methods in the educational process to achieve the properties of original components. Additionally, the study aims to set up 3D printing such that even a beginner-level operator, such as a primary or secondary school student under the supervision of their teacher or a teacher with minimal knowledge and experience in 3D printing, can successfully execute it. Further ongoing research focuses on evaluating the effects of characteristic 3D printing parameters, such as infill and perimeter, on the properties of 3D-printed parts through additional measurements and analyses.
The manuscript details the outcomes of a comprehensive study on the application of cluster-bicluster analysis, gene ontology analysis, and convolutional neural network (CNN) for diagnosing cancer and Alzheimer’s disease using gene expression data derived from both DNA microarray experiments and mRNA sequencing. It outlines a conceptual framework and provides a block diagram of the stepwise procedure for analyzing gene expression data, aiming to enhance the accuracy and objectivity of disease diagnosis. The research methodology involves initial gene ontology analysis, followed by the application of the Self Organizing Tree Algorithm (SOTA) for clustering gene expression profiles, an ensemble algorithm for data biclustering, and CNN for sample classification. Bayesian optimization method was employed to determine the optimal hyperparameters for all models. The analysis of simulation results demonstrates the high efficacy of the proposed approach. Specifically, for Alzheimer’s data, the number of genes analyzed was reduced from 44,662 to 4,004. Subsequent cluster-bicluster analysis divided this data into two subsets containing 1,158 and 2,846 genes, respectively. Classification accuracy for samples within these subsets reached 89.8% and 91.8%. In cancer data analysis, the gene count was reduced from 60,660 to 10,422, with 3,955 and 6,467 genes in the first and second clusters, respectively. The classification accuracy for these subsets was 97.4% and 97.6%, respectively. To our mind, the implementation of this model promises to significantly improve the efficacy of early diagnosis systems for complex diseases.
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Hynek Tippelt
  • Department of Political Science and Philosophy
Yaroslav Bazaikin
  • Department of Mathematics
Inna Kalita
  • The Department of Bohemistic Studies
Jan Klečka
  • Department of Biology
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Ústí nad Labem, Czechia
Head of institution
Doc. RNDr. Martin Balej, Ph.D.