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Abstract In this paper, we examine children’s ethnic discrimination in access to sport. We conducted two field experiments to test whether Roma applicants get greater rejection rates when applying to sport clubs and whether this rate is higher in case Roma applicants have a lower-class background. Basketball, volleyball, and soccer coaches were contacted by e-mail using Roma and non-Roma sounding names, requesting to participate in a trial practice. Previous findings show persistent discrimination of Roma people in Central and Eastern Europe in the labor and housing market and in access to various public services. Our findings in the field of sport in Hungary show that there is significant ethnic discrimination only when a stereotype about Roma people being lower class is activated. Further, gender was found to have a significant effect, with higher positive response rates for mothers applying for a trial session for a daughter, than for a son, regardless of their ethnicity. Our findings suggest a prevailing intersection of class and ethnicity, though our data does not allow for the separation of these two effects. These differences are discussed to better understand the role of intersectionality in discrimination within sport.

Abstract The antiarrhythmic and cardiac electrophysiological effects of SZV-2649 that contains a 2,6-diiodophenoxy moiety but lacks the benzofuran ring system present in amiodarone, were studied in mammalian cell line, rat and dog cardiac preparations. SZV-2649 exerted antiarrhythmic effects against coronary artery occlusion/reperfusion induced ventricular arrhythmias in rats and in acetylcholine- and burst stimulation induced atrial fibrillation in dogs. SZV-2649 inhibited hERG and GIRK currents in HEK cells (IC50: 342 and 529 nM, respectively). In canine ventricular myocytes, SZV-2649 (10 µM) decreased the densities of IKr, and Ito outward and INaL and ICaL inward currents. The compound (2.5–10 µM) elicited Class IB type Vmax reducing and Class III type action potential duration prolonging effects in dog right ventricular muscle preparations. In canine atrial muscle, SZV-2629 (2.5–10 µM) moderately prolonged action potential duration and this effect was greatly augmented in preparations pretreated with 1 µM carbachol. In conclusion, SZV-2649, has antiarrhythmic effects based on its multiple ion channel blocking properties. Since its chemical structure substantially differs from that of amiodarone, it is expected that SZV-2649 would exhibit fewer adverse effects than the currently used most effective multichannel inhibitor drug amiodarone and may be a promising molecule for further development.

Abstract Among malignant diseases, lung cancer has one of the highest mortality and incidence. Most epidemiological studies conclude that Hungary faces the most severe burden in association with this disease. However, for various reasons estimates and population-based studies show discrepancies. In this study, an intense data cleansing was performed on lung cancer cases that were reported to the Hungarian National Cancer Registry in 2018, and the major clinico-pathological parameters as well as survival characteristics were described. Our population-based figures were compared to the European estimates. As a result of our thorough revision, the corrected incidence of lung cancer has fallen below the number of cases that were reported to the Registry from 11,746 to 9,519. We also demonstrate that Hungary did not show the highest incidence and mortality in Europe, but it is still among the ones with the worst raking countries, with 92.9 and 50.6 age standardized rate per 100 thousand capita among males and females, respectively. Analysis of the annually reported case numbers revealed a gender-specific difference in incidence trends: while from 2001 to 2019 it slightly decreased among males, it increased among females. The most dominant subtype was adenocarcinoma, which was more frequent among female patients. Unfortunately, most of the newly diagnosed cases were in advanced stage; thus, 5 year overall survival was 14.8%. We anticipate that in the longer term, a decrease in incidence and improvement in survival rates may be expected as a result of the development of primary and secondary prevention programs in the country.

The role of soil organic carbon (SOC) is crucial not only for numerous soil functions and processes but also for addressing various environmental crises and challenges we face. Consequently, the demand for information on the spatiotemporal variability of SOC is increasing, posing new methodological challenges, such as the need for information on SOC and SOC changes with quantified uncertainty across a wide variety of spatial scales and temporal periods. Our objective was to present a methodology based on a combination of machine learning and space–time geostatistics to predict the spatiotemporal variability of SOC stock with quantified uncertainty at various spatial supports (i.e., point support, 1 × 1 km, 5 × 5 km, 10 × 10 km, 25 × 25 km, counties, and the entire country) for Hungary, between 1992 and 2016. The role of geostatistics is pivotal, as it accounts for the spatiotemporal correlation of the interpolation errors, which is essential for reliably quantifying the uncertainty associated with spatially aggregated SOC stock and SOC stock change predictions. Five times repeated 10-fold leave-location-out cross-validation was used to evaluate the point support predictions and uncertainty quantifications, yielding acceptable results for both SOC stock (ME = −0.897, RMSE = 19.358, MEC = 0.321, and G = 0.912) and SOC stock change (ME = 0.414, RMSE = 16.626, MEC = 0.160, and G = 0.952). We compiled a series of maps of SOC stock predictions between 1992 and 2016 for each support, along with the quantified uncertainty, which is unprecedented in Hungary. It was demonstrated that the larger the support, the smaller the prediction uncertainty, which facilitates the identification and delineation of larger areas with statistically significant SOC stock changes. Moreover, the methodology can overcome the limitations of recent approaches in the spatiotemporal modelling of SOC, allowing the prediction of SOC and SOC changes, with quantified uncertainty, for any year, time period, and spatial scale. This methodology is capable of meeting the current and anticipated demands for dynamic information on SOC at both national and international levels.

Abstract Aims The aim of the study was to assess the incidence and predictive factors of the development of heart failure with improved ejection fraction (HFimpEF) category during a 1 year follow‐up period in a heart failure with reduced ejection fraction (HFrEF) patient population managed in a heart failure outpatient clinic. Methods and results The study evaluated data from patients enrolled in the Hungarian Heart Failure Registry (HHFR). The incidence and predictive factors of the development of the HFimpEF category after 1 year follow‐up were assessed in the group of patients who had HFrEF at baseline. We evaluated the incidence and predictors of the development of HFimpEF after a 1 year follow‐up in relation to time since diagnosis of HFrEF in patients diagnosed within 3 months, between 3 months and 1 year, and beyond 1 year. The predictive factors of the development of HFimpEF were analysed using univariate and multivariate logistic regression analysis. Of the 833 HFrEF patients enrolled in the HHFR, the development of HFimpEF was observed in 162 patients (19.5%) during 1 year follow‐up. In the whole patient population, independent predictors of the development of HFimpEF were female gender [odds ratio (OR): 1.73; 95% confidence interval (CI): 1.01–2.96; P

Abstract Based on computer simulations of a realistic discrete element model we demonstrate that shrinkage induced cracking of thin layers of heterogeneous materials, generating spectacular crack patterns, proceeds in bursts. These crackling pulses are characterized by scale free distributions of size and duration, however, with non-universal exponents depending on the system size and shrinking rate. On the contrary, local avalanches composed of micro-cracking events with temporal and spatial correlation are found to obey a universal power law statistics. Most notably, we demonstrate that the observed non-universality of the integrated signal is the consequence of the temporal superposition of the underlying local avalanches, which pop up in an uncorrelated way in homogeneous systems. Our results provide an explanation of recent acoustic emission measurements on drying induced shrinkage cracking and may have relevance for the acoustic monitoring of the electro-mechanical degradation of battery electrodes.

Respiratory sensitization is a complex immunological process eventually leading to hypersensitivity following re-exposure to the chemical. A frequent consequence is occupational asthma, which may occur after long latency periods. Although chemical-induced respiratory hypersensitivity has been known for decades, there are currently no comprehensive and validated approaches available for the prospective identification of chemicals that induce respiratory sensitization, while the expectations of new approach methodologies (NAMs) are high. A great hope is that due to a better understanding of the molecular key events, new methods can be developed now. However, this is a big challenge due to the different chemical classes to which respiratory sensitizers belong, as well as because of the complexity of the response and the late manifestation of symptoms. In this review article, the current information on respiratory sensitization related processes is summarized by introducing it in the available adverse outcome pathway (AOP) concept. Potentially useful models for prediction are discussed. Knowledge gaps and gaps of regulatory concern are identified.

Esters of kynurenic acid, a known neuroprotective agent were reacted with cyclic amino acids to yield novel alkoxymethylated products under optimized reaction conditions. The importance of amino acid based (primary, secondary, biogenic and synthetic) organic additives was proven by the conduction of numerous test reactions. Thoroughly extended investigations, directly focusing on amino acid catalysis, which is an emerging and up-to-date field of catalysis and green chemical processes, have been conducted. The mechanism of the alkoxymethylation reaction was proposed and later the findings supported the hypothesis of the first retro-Mannich step (formation of the ortho-quinone methide intermediate) and subsequent formation of the alkoxymethylated derivatives. As a preparative result, two novel kynurenic acid derivatives bearing an alkoxymethyl moiety and two additional derivatives having amino acid residues at the site C-3 were synthesized, thus setting the scope and limitations of the modified Mannich reaction of kynurenic acid derivatives using amino acid nucleophiles. The mechanistic investigations highlighted the significant physicochemical effects of used nucleophiles on the amino-acid driven one-pot retro-Mannich initiated alkoxylation of kynurenic acid.

Objective: The Prolapse and Incontinence Knowledge Questionnaire (PIKQ) is a self-administered, reliable and valid instrument which assess knowledge regarding urinary incontinence and pelvic organ prolapse. There is no validated Hungarian version of this questionnaire; therefore the aim of this study was to develop a reliable, valid and culturally sensitive Hungarian version of the PIKQ. Study design: A cross-sectional study was conducted from March to October 2022 with a sample of 459 women. The PIKQ, which consists of the urinary incontinence and pelvic organ prolapse scales, was translated into Hungarian in accordance with international guidelines. The validity and reliability of the final version of the Hungarian PIKQ was evaluated using construct validity, comparison with known-groups, internal consistency and test-retest reliability. Results: Regarding construct validity, all fit indices were found acceptable. Healthcare workers had significantly higher knowledge about urinary incontinence and pelvic organ prolapse (p

Abstract Continuous intra-jejunal infusion of levodopa-carbidopa intestinal gel (LCIG) is a long-term proven and effective treatment in advanced Parkinson’s Disease (APD). Efficacy and safety of 16-h administration of LCIG has already been established. Additional benefits of 24-h LCIG administration have been reported in several case series and small clinical studies. The aim of this retrospective study was to compare the characteristics of patients who needed 24-h LCIG from the beginning of the DAT (device-aided treatment) with those who remained with the standard 16-h LCIG treatment and to identify particular motives if any. We initiated LCIG in 150 patients out of which in case of 62 patients (41,3%) due to unsatisfactory initial clinical benefits continuous 24-h LCIG was deemed necessary. Despite the subjective complaints and more severe clinical condition, at baseline evaluation we found statistically significant differences between 16-h LCIG cohort and 24-h LCIG cohort only in case of incidence of freezing (47% vs 65%, p = 0.03) and sudden off (32% vs 48%, p = 0.04). Wake hours/daytime LCIG does not always sufficiently improve the patient's quality of life in some patients due to persistent nighttime troublesome symptoms. Instead of labeling the patient as a non-responder, it is worth trying the 24-h LCIG dosage in a carefully selected group of patients, as there is currently no consensus on reliable criteria that serve the decision in these patients.

Abstract Freshwater lakes in most inhabited areas of the world are threatened by water quality issues. Standard water conservation measures have shown efficiency in the past; however, polluted lakes have only partially recovered from eutrophication. Our knowledge is still incomplete about the sensitivity of these lakes to different anthropogenic sources and to the changes in their internal processes due to global warming. In this article, we present a database comprising sediment data from Lake Balaton (Hungary), which can facilitate further analysis helping to better understand the internal processes and changes occurring in the lake. The published dataset includes the following parameters measured in 4211 lake bed sediment samples: pHKCl, calcium carbonate (CaCO3), organic carbon (Corg), total nitrogen (Ntotal), soluble phosphorus (AL-P2O5) and soluble potassium (AL-K2O), magnesium (Mg2+), zinc (Zn2+), copper (Cu2+) and manganese (Mn2+). We are confident that our database serves as a strong basis for further research relating to freshwater lakes influenced by human activities.

Crop yield forecasting is critical in modern agriculture to ensure food security, economic stability, and effective resource management. The main goal of this study was to combine historical multisource satellite and environmental datasets with a deep learning (DL) model for soybean yield forecasting in the United States’ Corn Belt. The following Moderate Resolution Imaging Spectroradiometer (MODIS) products were aggregated at the county level. The crop data layer (CDL) in Google Earth Engine (GEE) was used to mask the data so that only soybean pixels were selected. Several machine learning (ML) models were trained by using 5 years of data from 2012 to 2016: random forest (RF), least absolute shrinkable and selection operator (LASSO) regression, extreme gradient boosting (XGBoost), and decision tree regression (DTR) as well as DL-based one-dimensional convolutional neural network (1D-CNN). The best model was determined by comparing their performances at forecasting the soybean yield in 2017–2021 at the county scale. The RF model outperformed all other ML models with the lowest RMSE of 0.342 t/ha, followed by XGBoost (0.373 t/ha), DTR (0.437 t/ha), and LASSO (0.452 t/ha) regression. However, the 1D-CNN model showed the highest forecasting accuracy for the 2018 growing season with RMSE of 0.280 t/ha. The developed 1D-CNN model has great potential for crop yield forecasting because it effectively captures temporal dependencies and extracts meaningful input features from sequential data.

Satellite images are widely used for crop yield estimation, but their coarse spatial resolution means that they often fail to provide detailed information at the field scale. Recently, a new generation of high-resolution satellites and CubeSat platforms has been launched. In this study, satellite data sources including PlanetScope and Sentinel-2 were combined with topographic and climatic variables, and the improvement in wheat yield estimation was evaluated. Wheat yield data from a combine harvester were used to train and validate a yield estimation model based on random forest regression. Nine vegetation indices (NDVI, GNDVI, MSAVI2, MTVI2, MTCI, reNDVI, SAVI, EVI and WDVI) and spectral bands were tested. During the model training, the Sentinel-2 data realized a slightly higher estimation accuracy than the PlanetScope data. However, combining environmental data with the PlanetScope data realized the highest estimation accuracy. For the validated models, adding the topographic and climatic datasets to the satellite data sources improved the estimation accuracy, and the results were slightly better with the Sentinel-2 data than with the PlanetScope data. Observation data of the milk and dough stages provided the highest estimation accuracy of the wheat yield at 210–225 days after sowing.

The reaction between glycine-type aminonaphthol derivatives substituted with 2- or 1-naphthol and indole or 7-azaindole has been tested. Starting from 2-naphthol as a precursor, the reaction led to the formation of ring-closed products, while in the case of a 1-naphthol-type precursor, the desired biaryl ester was isolated. The synthesis of a bifunctional precursor starting from 5-chloro-8-hydroxyquinoline, morpholine, and ethyl glyoxylate via modified Mannich reaction is reported. The formed Mannich base 10 was subjected to give bioconjugates with indole and 7-azaindole. The effect of the aldehyde component and the amine part of the Mannich base on the synthetic pathway was also investigated. In favor of having a preliminary overview of the structure-activity relationships, the derivatives have been tested on cancer and normal cell lines. In the case of bioconjugate 16, as the most powerful scaffold in the series bearing indole and a 5-chloro-8-hydroxyquinoline skeleton, a potent toxic activity against the resistant Colo320 colon adenocarcinoma cell line was observed. Furthermore, this derivative was selective towards cancer cell lines showing no toxicity on non-tumor fibroblast cells.

As a complex system governing and interconnecting numerous functions within the human body, the immune system is unsurprisingly susceptible to the impact of toxic chemicals. Toxicants can influence the immune system through a multitude of mechanisms, resulting in immunosuppression, hypersensitivity, increased risk of autoimmune diseases and cancer development. At present, the regulatory assessment of the immunotoxicity of chemicals relies heavily on rodent models and a limited number of Organisation for Economic Co-operation and Development (OECD) test guidelines, which only capture a fraction of potential toxic properties. Due to this limitation, various authorities, including the World Health Organization and the European Food Safety Authority have highlighted the need for the development of novel approaches without the use of animals for immunotoxicity testing of chemicals. In this paper, we present a concise overview of ongoing efforts dedicated to developing and standardizing methodologies for a comprehensive characterization of the immunotoxic effects of chemicals, which are performed under the EU-funded Partnership for the Assessment of Risk from Chemicals (PARC).

In neonatal screening, amino acids have a significant diagnostic role. Determination of their values may identify abnormal conditions. Early diagnosis and continuous monitoring of amino acid disorders results in a better disease outcome. An easy and simple LC-MS/MS method was developed for the quantitation of underivatized amino acids. Amino acids were separated using a normal-phase HPLC column having a totally porous silica stationary phase and using classical reversed-phase eluents. Mass spectrometry in multiple reaction monitoring mode was used for the analysis, providing high selectivity and sensitivity. A standard addition calibration model was applied for quantitation using only one isotope-labeled internal standard for all amino acids. Five calibration points were used for quantitation, and the method was successfully validated. The slopes of the calibration curves of the individual amino acids in parallel measurements were found to be similar. Since the measured slopes were reproducible, one serum sample could represent every series of serum samples of a given day. The method was tested on human serum samples and adequate results were obtained. This new method can be easily applied in clinical laboratories.