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Abstract One of the global problems of our time is food waste that is most significant at the household level. There is a lack of research that focus on the food-wasting behavior of the main breadwinner groups in society, generations Y and X. To fill this gap, the purpose of this study is to analyse the factors that influence the food-wasting behavior of these groups. From data of a representative sample of 1,665 respondents by using structural equation modeling it is shown that the intention of reducing food waste is positively influenced by attitudes, health-, price and environmental consciousness, planning routines and ecological motives. The results show that influences from the immediate environment and the media are not effective, therefore programs dealing with the future of the Earth, children and sustainability, which strengthen environmental and ecological awareness and planning routines in generations X and Y are recommended. more...

Abstract Despite the growing consumer interest in local and artisanal foods over the past decades, there have still been few empirical studies on consumer behavior toward crafted food. This study aims to be the first to investigate consumer behavior towards craft bakery products by using the Theory of Planned Behavior model. Data were collected in Hungary, the sample of 418 respondents was weighted by gender and age group to ensure representativeness. Covariance-based structural equation modeling was used as the data analyzing method. The results showed that positive consumer attitudes and the effects of perceived behavioral control explained consumer intention and behavior towards craft bakery products well, but the influence of the consumer’s environment was not confirmed. Based on the results, the main activities proposed to the stakeholders of craft bakery products are those that highlight the availability and affordability of craft bakery products, while raising awareness of sustainability and health aspects. It is worth organizing festivals and events where the consumption of artisan baked goods is combined with pleasant stimuli and aromas. The results of the study provide a good starting point for further research, in which adding more factors to the model would increase its explanatory power. more...

Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and human coronavirus HKU1 (HCoV-HKU1) are two forms of human coronaviruses known to cause respiratory tract symptoms. A co-infection with both viruses is rare, particularly in the United States. Case description: An 85-year-old male presented to the Emergency Department with recurrent falls, diarrhoea and cough, and whose viral panel was positive for both SARS-COV-2 and HCoV-HKU1. The patient developed bacterial pneumonia and was treated with antibacterial agents and glucocorticoids. His past medical history of atrial fibrillation required careful monitoring and subsequent discontinuation of remdesivir, a medication known to cause adverse cardiovascular effects in COVID-19 patients. The length of stay was also prolonged due to delirium and deconditioning. Ultimately, the patient required an urgent ablation followed by the placement of a permanent pacemaker, and anticoagulation therapy was initiated before discharge. The patient had a favourable outcome given the rarity of this case. Discussion: COVID-19 patients co-infected with other human coronaviruses should be monitored for disease progression and superimposed bacterial infections. Providers should be cautious with the use of remdesivir in cases of co-infection and in severely ill COVID-19 patients who have a history of atrial fibrillation. more...

Abstract Introduction Combination use of atogepant and onabotulinumtoxinA has the potential to be more effective than either alone for the preventive treatment of chronic migraine (CM) due to their complementary mechanisms of action. This analysis collected real-world data to evaluate the safety, tolerability, and effectiveness of adding atogepant to onabotulinumtoxinA as a combination preventive treatment for CM. Methods This retrospective, longitudinal, multicenter chart review included adults with CM who received ≥ 2 consecutive cycles of onabotulinumtoxinA before ≥ 1 month of onabotulinumtoxinA and atogepant combination treatment. Charts at atogepant prescription (index date) and two subsequent onabotulinumtoxinA treatment visits (~ 3 and ~ 6 months post-index) were reviewed for change from baseline in monthly headache days (MHDs), ≥ 50% reduction in MHDs, discontinuation rates, and adverse events (AEs). Results Of the 55 charts that met safety analysis criteria, 31 had data on headache days at index and first post-index visit and were eligible for effectiveness analysis (mean age 46.7 years, 94.5% female). For those with data available prior to onabotulinumtoxinA treatment (n = 25), the mean MHD was 24.0 days, reduced by 8.15 days after onabotulinumtoxinA treatment. After atogepant was added, MHD was incrementally reduced by 4.53 days and 8.75 days from index date to the first (N = 31) and second (N = 23) post-index onabotulinumtoxinA treatment visit, respectively. A ≥ 50% reduction in MHDs was achieved by 45.2% of patients ~ 3 months post-index. Atogepant and onabotulinumtoxinA were discontinued by 16.1% and 6.5% of patients, respectively. In the safety population, 32.7% of patients experienced ≥ 1 AE. No serious AEs were reported. Conclusions This real-world study of patients with CM demonstrated that adding atogepant to onabotulinumtoxinA as a combination preventive treatment for CM was effective by providing an additional reduction in MHDs over ~ 3 and ~ 6 months of combination treatment. Safety results were consistent with the known safety profiles of onabotulinumtoxinA and atogepant, with no new safety signals identified. more...

Candida auris occupies similar niches in various infections as Pseudomonas aeruginosa; however, the details of their interspecies communication remain largely unknown. To gain deeper insights into this relationship, phenotypic and transcriptomic analyses were conducted in the presence of the primary P. aeruginosa quorum-sensing molecule, N-(3-oxododecanoyl)-l-homoserine lactone (HSL), against C. auris, with the results compared to those of C. albicans. Our findings indicate that HSL-induced effects are not specific to C. albicans; additionally, several characteristics are present in C. auris but not in C. albicans following HSL exposure. Significant HSL-induced reduction was observed in growth and adhesion of C. auris cells in time -and concentration-dependent way (p more...

In agriculture, computer vision and image processing are essential for monitoring crops and controlling robots and actuators. In this work, the detection of ripe tomato fruit was the main aim. During the tomato-ripping process, the green tomato turns to red in several color stages (Ambrus et al., 2024). While the chlorophyll concentration decreases, the lycopene concentration increases. The sugar and the acid increase parallel to lycopene. The RGB camera can capture the process but needs to convert HSV color space to identify the tomato. The successful identification depends on the direct illumination volume. The experiment contains 4 ripe tomatoes and 15 different artificial illumination levels. The measurements show that the results are similar to or constantly above 3,000 lx illumination. However, under 3,000 lx, the detected size of tomatoes looks smaller and smaller depending on the weakness of illumination. Around 1,600 lx, it is possible to measure only half of the real size of the tomato. It shows that using the right amount of light is crucial to precise measurement in HSV color space. This research highlights the critical importance of proper illumination in ensuring accurate image analysis for tasks like industrial tomato segmentation. It emphasizes the need for adaptable lighting solutions, particularly in varying weather conditions, and the balance between adequate light and energy efficiency. more...

In this study, we investigated the individual and combined toxic effects of a glyphosate-containing herbicide (Amega Up) and a tau-fluvalinate-containing insecticide (Mavrik 24 EW) on pheasant embryos, after immersion treatment of eggs. The emulsions of Amega Up with a concentration of 4.0% (360 g/l glyphosate) and Mavrik 24 EW (240 g/l tau-fluvalinate) with a concentration of 0.05% were used as test materials. The immersion treatment was performed on the first day of incubation, and the pheasant eggs were processed on day 21 of incubation. During the necropsy, the following parameters were recorded: body weight, the beak-hoof range, embryonic mortality and type and frequency of macroscopic developmental abnormalities. In the group treated with 4.0% Amega Up emulsion, the body weight values were lower and the beak-hoof range was shorter. The changes were significantly different as compared to the control. As a result of Mavrik 24 EW treatment, embryonic body weight and beak-hoof range decreased and embryonic mortality increased, however, the differences were not significant. During the study of the combined toxic effect with the test materials, a significant decrease in embryonic body weight and a statistically justified decrease also in the beak-hoof range were observed compared to the control group. The frequency of macroscopic developmental malformations increased to a statistically justified extent. The combined administration of the test materials increased the embryotoxicity compared to the individual toxicity tests which was presumably manifested as an additive toxic interaction. more...

Abstract Context The landscape provides not only a living space for all life forms, including humans, but also a spatial base and set of resources for the implementation of individual human activities. Inappropriate implementation of human activities, disrespecting the properties of the landscape's natural resources, causes the degradation of natural resources and, consequently, the human living. Objectives The aim of this paper is to develop new methodological procedures and algorithms for effective assessment of natural capital based on the geosystem approach. Methods Each territorial unit (geosystem) represents a unique combination of natural assets that create a certain potential for the development of individual activities and eco-stabilization functions. In this study, we developed a new approach and algorithms to assess the natural capital of landscapes for sustainable use. This involves selecting indicators and their functional interpretation, as well as collecting available spatial data and statistics for GIS analysis, synthesis, and modeling. Results The methodological procedure consists of the determination of indicators for natural capital assessment, the determination of their functional values and weighting coefficients, the determination of the suitability of the geosystem for the implementation of individual activities based on the value of natural capital, and the determination of restrictions and limiting factors. The set of data on landscape assets can be categorized into abiotic, land cover and biotic, and socio-economic indicators, which can either support human activities or limit them. Options for sustainable use of natural capital were split into two groups of potential activities: (I) natural capital for landscape planning activities and (II) specific activities or functions (e.g., natural capital for energy use, recreation, regulation services). The modeling of eco-stabilizing natural capital in Trnava LTSER pointed to low spatial ecological stability, mainly in the central part of the district. Discussion Discussion pointed to strength, novelty and opportunities of implementing methodological approach to natural capital assessment. Conclusions As an output of this methodological approach, a comprehensive digital spatial database of landscape-ecological data for the assessment of natural capital and the suitability of its use for socio-economic activities has been created in Slovakia. The database represents a set of consistent spatial information on natural capital assets and other indicators, including land cover and socio-ecological indicators. The methodological approach can be applicable to any territory on the basis of a modification. more...

High blood cholesterol is one of the most important risk factors of atherosclerosis. Currently, four groups of drugs (statins, ezetimibe, PCSK9 inhibitors and bempedoic acid) have large clinical trials proving that the frequency of cardiovascular events can be significantly improved by lowering LDL-cholesterol (LDL-C). According to the lipid guidelines, the reduction of LDL-C should begin as early as possible and should be done as lower as possible for a long term. It should also be borne in mind that the greater the risk, the greater the cardiovascular benefit. Taking this into account, using the new domestic health insurance regulations, we should pay great attention to starting PCSK9 inhibitor treatment as soon as possible in our very high-risk patients, if high-intensity statin and ezetimibe combination therapy is not sufficient. Currently, evolocumab given every two weeks and inclisiran given every 6 months are available. A randomized clinical end-point study with a large number of patients has not yet been completed with the latter, but studies have been conducted with this drug so far, and since this mechanism of action with PCSK9 inhibitor monoclonal antibodies has already been proven in clinical studies and Mendelian randomization studies, there is expert consensus that anticipating trust, inclisiran can be given safely and effectively. Pooled post hoc analyzes demonstrated an LDL-C-lowering effect of 45-55%, and analysis of 9,982 patient-years of 3,576 patients compared with placebo showed no difference in reported treatment-emergent adverse events and discontinuation of therapy. more...

γ Persei is a long-period ( P ≈ 14.6 yr) eclipsing binary system. Its period makes it a difficult target to fully understand: so far, only two primary eclipses are known in the literature, from 1990 and from 2019, whereas the 2005 one was missed due to its closeness to the Sun at the time. We aimed to fill in this gap by processing the quasi-continuous photometry collected by the Solar Mass Ejection Imager (SMEI) between 2003 and 2011, which was ideally positioned to observe such a bright targets. In order to do that, we first determined a color-dependent conversion formula from the SMEI measurements into Gaia G magnitudes. We applied various corrections to the photometry and provide the longest continuous light curve of γ Persei. We successfully detected the 2005 primary eclipse of the system, with the yearly observations ending during the egress of the companion. We predicted the position of a possible secondary eclipse by forward modeling the binary system with PHOEBE, and successfully recovered the secondary eclipse in the 2006 SMEI observations. The existence of the secondary eclipse puts strong constraints on the orbital configuration, which will be an important constraint for future studies of the system. more...

Saturation processes occur in almost every theoretical and practical field, e.g. liquid uptake within fibrous composite reinforcements. These processes require appropriate mathematical functions to model them and use them for design purposes. This includes assessing the saturation level, especially in microfluidic processes of fibrous composite reinforcements. This paper proposes a mathematical approach that uses a simple and well-known saturation function with modification through variable transformations and/ or linear combinations. When the initial asymptotic behavior is numerically known, this modified function provides a tailored and robust approximation of the measured saturation process and makes it possible to assess the asymptotic saturation level as well. A saturation function based on micro-tensiometer measurements and a simple exponential function was applied to validate this method. The mathematical approach was validated by test results based on distilled water uptake in polyester yarns and unsaturated polyester (UP) resin absorption within fiberglass chopped strand mats. In both cases, a good correlation was found between the experimental results and the applied mathematical approach, where the determination coefficients were higher than 0.989. [ABSTRACT FROM AUTHOR] more...

In this study, we examined the chemical changes occurring in ground tire rubber (GTR) and on its surface as a result of gamma irradiation in water, with low doses of 5, 10, 15, 20, 25, and 30 kGy. To better distinguish the changes the radiation caused in the GTR and the surface activation of the GTR caused by the irradiated water, we also performed radiation treatments in an inert atmosphere. We mixed the treated GTRs with fresh rubber, and after vulcanization, investigated the mechanical properties and conducted dose optimization. The chemical changes occurring in GTR were characterized by Soxhlet-extraction and cross-link density measurements. Changes on the surface were investigated by Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). In water irradiation, cross-link density decreased (∼10 %), while in an inert atmosphere, new bonds formed between the chains (∼10 %), with negligible degradation (∼2 %) in both cases. Based on the FTIR spectra, new oxygen-containing groups appeared on the GTR surface in water treatment, while this was not observed in a nitrogen atmosphere. The increase in surface oxygen content was confirmed by XPS, showing a ∼10 % increase as a result of water treatment, while it remained unchanged in the inert atmosphere. We achieved a 30 % increase in tensile strength (5 kGy) without a decrease in elongation properties and a 32 % increase in tear strength (20 kGy) for vulcanizates containing surface-activated GTR. Mechanical properties did not improve with treatments in an inert atmosphere. The oxidizing agents formed during the radiolysis of water activated the surface of the GTR, helping to establish a better connection with the matrix. more...

Abstract This study analyzes the optical properties of TiO2 films grown via atomic layer deposition (ALD) using Tetrakis(dimethylamino)titanium with oxidizing agents such as H2O, H2O2, O3, and O2‐plasma. TiO2‐H2O exhibited Ti3+ states and oxygen vacancies characteristic of black TiO2, enhancing visible‐NIR light absorption. This effect increased with more ALD cycles due to the surface memory effect, leading to a decreased growth rate. In contrast, films grown with H2O2, O3, and O2‐plasma are more stoichiometric, has fewer defects, and show no visible‐NIR absorption due to the absence of Ti3+. TiO2 films deposited with H2O also show increased surface roughness and hydrophobicity, while films grown with other oxidizing agents exhibited higher roughness but decreased hydrophobicity. Ellipsometry and UV–vis spectroscopy confirmed that TiO2 films grown with H2O has an increased refractive index and extinction coefficient in the visible range, along with a bandgap widening due to the Moss‐Burstein effect. Conversely, films grown with other oxidizing agents showed a decreased bandgap with increasing thickness and an increased refractive index but a zero extinction coefficient below the bandgap. Mid‐IR ellipsometry measurements revealed the dielectric response, highlighting the critical role of the oxidizing agent in tailoring the properties of TiO2 films for energy and environmental applications. more...

Hereditary breast and ovarian cancer is a well-known genetic condition, inherited mainly in an autosomal dominant way, which elevates the risk of developing malignancies at a young age in heterozygous carriers. Advances in new generation sequencing have enabled medical professionals to determine whether a patient is harbouring mutations in moderate- or high penetrance susceptibility genes. We conducted a retrospective analysis among 275 patients who underwent genetic counselling and multigene panel testing for hereditary breast and ovarian cancer syndrome in our department. From these patients 74.5% (205/275) were affected by some type of malignancy, while the remaining 25.5% (70/275) had a positive family history of different cancers, suggesting a genetic predisposition. These tests confirmed a genetic variant in 29.8% and 28.6% of these patient groups respectively. The results also mirrored our general knowledge concerning the genetic background of hereditary breast and ovarian cancer, as variants in either one of the BRCA1 and BRCA2 genes proved to be the most common cause among our patients with 41.5%. Our test also detected a novel mutation in the CDH1 gene and three patients with double heterozygosity in two different susceptibility genes. This study demonstrates the relevance of genetic counselling and non-BRCA gene sequencing among cancer patients and patients who fulfil the criteria for genetic testing, while also providing important details about the genetic profile of Hungarian patients. more...

Summary: Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B∗15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B∗15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the United States (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B∗15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections studied, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified. more...

Abstract In Hungary, as part of a nationwide, climatically balanced survey for a next-generation sequencing-based study of the honey bee (Apis mellifera) gut microbiome, repeated sampling was carried out during the honey production season (March and May 2019). Among other findings, the presence of Apis mellifera filamentous virus (AmFV) was detected in all samples, some at very high levels. AmFV-derived reads were more abundant in the March samples than in the May samples. In March, a higher abundance of AmFV-originated reads was identified in samples collected from warmer areas compared to those collected from cooler areas. A lower proportion of AmFV-derived reads were identified in samples collected in March from the wetter areas than those collected from the drier areas. AmFV-read abundance in samples collected in May showed no significant differences between groups based on either environmental temperature or precipitation. The AmFV abundance correlated negatively with Bartonella apihabitans, Bartonella choladocola, and positively with Frischella perrara, Gilliamella apicola, Gilliamella sp. ESL0443, Lactobacillus apis, Lactobacillus kullabergensis, Lactobacillus sp. IBH004. De novo metagenome assembly of four samples resulted in almost the complete AmFV genome. According to phylogenetic analysis based on DNA polymerase, the Hungarian strains are closest to the strain CH-05 isolated in Switzerland. more...

The pollen beetle (Brassicogethes aeneus Fabricius, 1775) is one of the most harmful pests of winter oilseed rape. Resistant populations have already appeared and spread in Europe due to the misuse of pyrethroid insecticides. Therefore, lambda-cyhalothrin resistance tests were performed on adult beetles collected in four Hungarian habitats according to the coated glass vial assay of the Insecticide Resistance Action Committee (IRAC) in 2018 and 2019. According to the results, all tested individuals were classified into the resistant category, as the mortality at the concentration of 0.075 μg/cm² of the active ingredient, which corresponds to the typical field rate, was only 52–55%. From the cumulated data of the two consecutive years and four sampling sites, the L.D. 50 (0.047 μg/cm²) and the L.D. 90 (0.148 μg/cm²) values of lambda-cyhalothrin were also determined. Total mortality was observed only for the 150% (0.113 μg/cm²) and 200% (0.15 μg/cm²) treatments. Preventing the further spread of pyrethroid-resistant pollen beetle populations and controlling them has become essential in Hungary; therefore, additional monitoring of pollen beetles is critical in developing strategies to address insecticide resistance. more...

Abstract Background Collagen type IV alpha 1 chain (COL4A1) in the basement membrane is an important component during lung development, as suggested from animal models where COL4A1 has been shown to regulate alveolarization and angiogenesis. Less is known about its role in human lung development. Our aim was to study COL4A1 expression in preterm infants with different lung maturational and clinical features. Methods COL4A1 expression in 115 lung samples from newborn infants (21-41 weeks’ gestational age; 0-228 days’ postnatal age [PNA]) was studied by immunohistochemistry combined with digital image analysis. Cluster analysis was performed to find subgroups according to immunohistologic and clinical data. Results Patients were automatically categorized into 4 Groups depending on their COL4A1 expression. Expression of COL4A1 was mainly extracellular in Group 1, low in Group 2, intracellular in Group 3, and both extra- and intracellular in Group 4. Intracellular/extracellular ratio of COL4A1 expression related to PNA showed a distinctive postnatal maturational pattern on days 1-7, where intracellular expression of COL4A1 was overrepresented in extremely preterm infants. Conclusions COL4A1 expression seems to be highly dynamic during the postnatal life due to a possible rapid remodeling of the basement membrane. Intracellular accumulation of COL4A1 in the lungs of extremely premature infants occurs more frequently between 1 and 7 postnatal days than during the first 24 hours. In view of the lung arrest described in extremely preterm infants, the pathological and/or developmental role of postnatally increased intracellular COL4A1 as marker for basement membrane turnover, needs to be further investigated. more...

The advent of cloud computing and advanced processing technologies has elevated deep learning (DL) as a leading method for hyperspectral imaging (HSI) classification. Classifying crops accurately is vital for generating precise agricultural data to support informed decision-making. This study introduces a DL framework, called HypsLiDNet, tailored for remote sensing activities. This model processes HSI in conjunction with innovative, comprehensive light detection and ranging (LiDAR) data from Hungary to conduct thorough examinations of the Earth's surface. Integrating LiDAR attributes with HSI is anticipated to enhance classification accuracy beyond HSI-only techniques. LiDAR integration provides a significant advantage by adding structural details to spectral data, aiding in the correct identification of objects with similar spectral characteristics but different shapes.The HypsLiDNet method utilizes morphological operations on LiDAR data to extract features indicative of the land's shape and texture. These features are then combined with HSI data through an attention mechanism that selectively highlights key features from both data types, improving the model's accuracy in predictions. This is particularly beneficial for complex environmental assessments, such as distinguishing between plant species. The attention mechanism also refines the feature selection process, prioritizing relevant information, which boosts computational efficiency and reduces the use of resources. Moreover, this method requires a smaller number of training samples. HypsLiDNet showcases its ability to classify with precision by harnessing the combined power of HSI and LiDAR data. Experimental results show a significant improvement in classification outcomes, outperforming traditional machine learning approaches by more than 14% and recent DL techniques by approximately 1%–3%. more...

This study aimed to develop a new method for combining Sentinel-2 and PlanetScope (PS) imagery. The normalized difference vegetation indices (NDVI) data were retrieved from the Earth observation satellites S2 Level-2A and PS Level-3 surface reflectance during the soybean growing phase. The proposed method utilizes the Python implementation of data mining sharpener algorithm, which is a decision-tree-based technique for enhancing low- and high-resolution images with information from large-scale images. The robustness and flexibility of a multidimensional data fusion, deep neural network, and machine-learning-based yield estimation model were analyzed based on the within-field variability in soybean yield. A comparative analysis revealed that the fusion data with 1.5–2.5 tons significantly outperformed individual predictions, demonstrating higher accuracy and fewer errors. The fusion data used to predict yields showed relatively small error ranges of 0.5–0.2 t/ha. In contrast, the PS and S2 datasets showed higher prediction errors. The study employed vegetation indices, and during validation, crop forecasts were compared using an NDVI map. The effectiveness of artificial neural networks in predicting crop yields was highlighted, demonstrating superior performance across diverse datasets compared with other algorithms. This novel fusion technique is essential for monitoring crop health and growth, improving agricultural practices, such as fertilization and water management, and improving yield forecast accuracy. This study provides valuable insights into phenology monitoring, image fusion accuracy, and the effectiveness of machine-learning algorithms in predicting crop yields, emphasizing the benefits of fused imagery. more...

Background: Accuracy of baseline ACTH for the diagnosis of PPID in horses varies between studies. Objectives: To estimate the diagnostic accuracy of ACTH as a biomarker for PPID in adult horses and appraise potential causes of heterogeneity. Study design: Systematic review and meta‐analysis. Methods: A literature review identified studies reporting diagnostic accuracy data for extraction. Risk of bias was evaluated using QUADAS‐2. Two random‐effects models, the hierarchical summary receiver operating curve (HSROC) and the bivariate binomial normal model (BBN) were used to pool accuracy measurements. We performed meta‐regression using study‐level variables. The impact of diagnostic test accuracy on the frequency of false‐positive and false‐negative results at various pretest probabilities was calculated using the BBN model's accuracy results. Results: Patient selection and index test evaluation demonstrated significant risk of bias. Mean and 95% confidence intervals for sensitivity and specificity for all studies (n = 11) based upon the HSROC model were (0.72, 95% CI: 0.62 to 0.82) and (0.88, 95% CI: 0.79 to 0.93), respectively. When studies with a common positivity threshold of 35 pg/mL ACTH were evaluated (n = 6), sensitivity and specificity were (0.66, 95% CI:0.54 to 0.77) and (0.87, 95% CI: 0.74 to 0.94). In a hypothetical group of one thousand horses with PPID prevalence of 2%, 20%, and 90%, the frequency of resulting false‐positive and false‐negatives would be (127 and 7), (104 and 68) and (13 and 306), respectively. Factors leading to increased accuracy were case‐control design, clinical reference standard and data‐driven choice of ACTH threshold. Main limitations: A small number of primary studies (n = 11) were available, demonstrating significant biases. Conclusions: Less biased studies examining diagnostic accuracy of ACTH are needed. In horses with a high pretest probability of PPID, ACTH may be a functional "rule‐in" test. Baseline ACTH is not recommended for screening purposes or use in horses without clinical signs of PPID. [ABSTRACT FROM AUTHOR] more...

Our primary objective was to assess the effectiveness of detailed cardiovascular ultrasound screening during the first trimester, which was performed by obstetricians with intermediate experience. We collected first-trimester fetal cardiac screening data from an unselected pregnant population at RMC-Fetal Medicine Center during a study period spanning from 1 January 2010, to 31 January 2015, in order to analyze our learning curve. A pediatric cardiologist performed a follow-up assessment in cases where the examining obstetrician determined that the fetal cardiac screening results were abnormal or high-risk. Overall, 42 (0.88%) congenital heart abnormalities were discovered prenatally out of 4769 fetuses from 4602 pregnant women who had at least one first-trimester cardiac ultrasonography screening. In total, 89.2% of the major congenital heart abnormalities (27 of 28) in the following fetuses were discovered (or at least highly suspected) at the first-trimester screening and subsequent fetal echocardiography by the pediatric cardiology specialist. Of these, 96.4% were diagnosed prenatally. According to our results, the effectiveness of first-trimester fetal cardiovascular ultrasound screening conducted by moderately experienced obstetricians in an unselected (’routine’) pregnant population may reach as high as 90% in terms of major congenital heart defects, provided that equipment, quality assurance, and motivation are appropriate. more...

Background: Monomicrobial Enterobacterales necrotizing fasciitis is associated with exceedingly high mortality rates. Although effective antimicrobial therapy is an important part of treatment, the traditional microbiological diagnostic methods are not fast enough to meaningfully influence early therapeutic decisions. Methods: Here, we report the application of the BioMérieux Biofire Filmarray Joint Infection Panel (BFJIP) for the rapid detection of the causative agent and susceptibility prediction in such a case. Aside from the BFJIP-based rapid diagnostic approach and culturing, the whole genome sequencing (WGS) of the causative agent was performed using Illumina MiSeq and Oxford Nanopore MinION platforms. Results: The BFJIP indicated the presence of K. pneumoniae, without KPC, VIM, IMP, NDM, OXA-48 carbapenemase genes, and CTX-M-type extended-spectrum beta-lactamases. Based on the WGS data, the isolate belonged to the K1-capsule-type ST23, harboured a pNTUH-2044-like plasmid, and was positive for all the virulence factors associated with this lineage. The conventional susceptibility results were also in accordance with the BFJIP results; the isolate lacked any of these acquired resistance mechanisms. Conclusions: Despite this being the first case of the successful identification of pathogenic bacteria in necrotising fasciitis using this assay, the BFJIP may become a useful tool for rapid identification of pathogens in necrotising fasciitis cases and guiding antimicrobial therapy for better clinical outcomes. more...

In this study, five different time-dependent incompressible non-Newtonian boundary layer models in two dimensions are investigated with the self-similar Ansatz, including external magnetic field effects. The power-law, the Casson fluid, the Oldroyd-B model, the Walter fluid B model, and the Williamson fluid are analyzed. For the first two models, analytical results are given for the velocity and pressure distributions, which can be expressed by different types of hypergeometric functions. Depending on the parameters involved in the analytical solutions of the nonlinear ordinary differential equation obtained by the similarity transformation, a vast range of solution types is presented. It turned out that the last three models lack self-similar symmetry; therefore, no analytic solutions can be derived. more...

In this paper, we define and investigate a system of coupled regular diffusion equations in which each concentration acts as a driving term in the next diffusion equation. Such systems can be understood as a kind of cascade process which appear in different fields of physics like diffusion and reaction processes or turbulence. As a solution, we apply the time-dependent self-similar Ansatz method, the obtained solutions can be expressed as the product of a Gaussian and a Kummer’s function. This model physically means that the first diffusion works as a catalyst in the second diffusion system. The coupling of these diffusion systems is only one way. In the second part of the study we investigate mutually coupled diffusion equations which also have the self-similar trial function. The derived solutions show some similarities to the former one. To make our investigation more complete, different kinds of couplings were examined like the linear, the power-law, and the Lorentzian. Finally, a special coupling was investigated which is capable of describing isomerization with temporal decay. more...

editorial

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. more...

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. more...

Abstract The bacterial growth rate is important for pathogenicity and food safety. Therefore, the study of bacterial growth rate over time can provide important data from a medical and veterinary point of view. We trained convolutional neural networks (CNNs) on manually annotated solid medium cultures to detect bacterial colonies as accurately as possible. Predictions of bacterial colony size and growth rate were estimated from image sequences of independent Staphylococcus aureus cultures using trained CNNs. A simple linear model for control cultures with less than 150 colonies estimated that the mean growth rate was 60.3 $$\mu m/h$$ μ m / h for the first 24 h. Analyzing with a mixed effect model that also takes into account the effect of culture, smaller values of change in colony size were obtained (control: 51.0 $$\mu m/h$$ μ m / h , rifampicin pretreated: 36.5 $$\mu m/h$$ μ m / h ). An increase in the number of neighboring colonies clearly reduces the colony growth rate in the control group but less typically in the rifampicin-pretreated group. Based on our results, CNN-based bacterial colony detection and the subsequent analysis of bacterial colony growth dynamics might become an accurate and efficient tool for bacteriological work and research. more...