Children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) usually present minimal symptoms or are asymptomatic. Nevertheless, a subset of children 2-6 weeks after the initial SARS-CoV-2 infection develops a postinfectious SARS-CoV-2-related multisystem inflammatory syndrome in (MIS-C). Recently, transient expansion of TRBV11-2 T cell clonotypes in MIS-C was associated with signatures of inflammation and T cell activation, however, the underlying pathophysiology of MIS-C is not fully understood [1].The purpose of our project is to characterize the complexity of cell populations and capture cellular heterogeneity to uncover the regulatory networks and interactions that are disrupted during MIS-C flare with simultaneous profiling of gene expression and open chromatin regions from the same nuclei.Samples of peripheral blood mononuclear cells from patients with MIS-C diagnosed at the University Children’s Hospital, University Medical Center Ljubljana, were collected during the initial presentation before any treatment and at 6-12 months in remission. The primary aim is to identify which regulatory networks are driving inflammation in MIS-C flare, for which we are performing single cell Multiome ATAC + Gene Expression Sequencing. To enable simultaneous profiling of epigenomic landscape and gene expression from the same nuclei, we are using Chromium Next GEM Single Cell Multiome ATAC + Gene Expression kit from 10X Genomics.We included 32 patients with MIS-C from whom we collected paired blood samples during the initial presentation before treatment and at 6-12 months in remission. In single cell multiomic experiment we included 10 patients with paired samples, with the most viable cell count prior cryopreservation. All samples that are included into multiomic single cell analysis have 75% - 99% viability prior cryopreservation. In the protocol the key is to remove remaining granulocytes causing high mitochondrial RNA burden and extensively optimize the dilution factor of lysis buffer and the length of cell lysis step in order to get intact nuclei with no significant blebbing. Afterward, the single cell ATAC libraries as well as single-cell gene expression libraries are constructed and sequenced. Data are undergoing pairwise analysis to compare the cell population heterogeneity, expression profile and open chromatin landscape in the time of the initial presentation of MIS-C and in the remission, with Cell ranger software as well as with R package scREG [2], and custom scripting. In the second step we will inspect if the resulting altered transcriptomic signature from single-cell experiment is present on larger cohort. In that regard, we will perform bulk transcriptomic profiling on all paired collected samples during the initial presentation of MIS-C before treatment and at 6-12 months in remission.The results of this project are expected to enlighten the underlying pathophysiology of MIS-C flare and thus support clinical decision on more targeted treatment. The identified disrupted networks during MIS-C flare could lead the way to establish an early diagnosis and improve long-term outcome, including prevention of myocardial and neuropsychological impairment. Moreover, a better understanding of the disrupted regulatory networks that are driving inflammation in MIS-C, could lead to new insights into diseases with similar clinical presentations as is Kawasaki Disease.[1]Sacco, K., Castagnoli, R., Vakkilainen, S.et al.Immunopathological signatures in multisystem inflammatory syndrome in children and pediatric COVID-19.Nat Med28, 1050–1062 (2022).[2]Duren, Z., Chang, F., Naqing, F.et al.Regulatory analysis of single cell multiome gene expression and chromatin accessibility data with scREG.Genome Biol23, 114 (2022).This research was supported by Slovenian research agency grant J3-3061 and Interreg ITA-SLO project Cattedra.None Declared.

In Herzegovina table grapes have been grown on smaller private areas. One of the most important factors that affect the yield and quality of vines, grapes and the profit of production are the viruses. The aim of this work is to monitor the occurrence of 4 viruses (GLRaV-1, GLRaV-3, ArMV and GFLV) on 6 table grape varieties: Prima, Black Magic, Cardinal, Demir-kapija, Victoria, Alphonse Lavallée. The research was conducted in the period from November 2019 to September 2020 on one of the larger plantations north of Mostar.Studies have shown different susceptibility of different varieties to these viruses. Of the 60 samples examined, the presence of ArMV virus was not recorded. The presence of GLRaV-1, GLRaV-3 and GFLV viruses was proven by ELISA. The variety Victoria is most susceptible to infection with the GLRaV-3 virus, in which each sample of this variety is infected. The second variety that is most susceptible is Demir kapija with 80% of infected samples, followed by Cardinal with 70% and Alfonso with 50%. The most resistant varieties according to this research are Prima with 30% of infected samples and Black Magic with 10% of infected samples.

The aim of this paper is to predict the positions of the first just noticeable difference (JND) points as optimal levels of compression for images and videos based on simple features derived from the original visual signals. Three image datasets and one video dataset with subjectively defined JNDs were used in the analysis. We show that the position of the first JND point can be successfully predicted on the basis of simple image features. The highest degree of agreement with subjectively assigned JNDs was reached by features based on the gradient magnitude, where on two datasets with JPEG images their correlation is greater than 95%. On the dataset with VVC images, which has a larger number of images and a wider range of image content, the degree of agreement between gradient-based predictions and the results of subjective tests is 84%, while the correlation on the dataset with video sequences is 80%.

This paper provides a comprehensive study on the learning models' power violation, sum-rate performance while taking into consideration power constraint, and computational efficiency in terms of training and execution times over a dynamic wireless channel. We propose a reward shaping method and modify learning models with the output scaling strategy to enforce them to fully respect the power constraints while optimizing the sum-rate performance. The proposed approach reaches close-to-optimal accuracy, i.e., up to 99.15%, while satisfying the predefined power constraint of the base station. Moreover, learning models are shown to be more computationally efficient compared to the traditional algorithm. However, solving the power allocation problem within the Orthogonal Frequency Division Multiplexing (OFDM) symbol duration of $16.7\mu \mathrm{s}$ is a remaining challenge.

This paper presents a comprehensive study on the efficiency and effectiveness of exploration policies for deep reinforcement (DRL) algorithms with applications to the power allocation problem in multi-carrier wireless systems. We propose three distinct exploration functions, i.e., linear, fast and slow, to balance exploration and exploitation in the dynamic wireless environment. We analyze the effect of exploration on the initial training length as well as learning models' sum-rate performance and power violation probabilities. Our results indicate that the DRL algorithms with the proposed exploration functions reach close-to-optimal sum-rate performance within only 1000 training episodes (i.e., equivalent to 8.01 s) while satisfying the predefined power constraint of the base station.

Objectives: vasculitis is a rare disease characterized by inflammation and necrosis of blood vessels. inflammation-induced thrombosis is a hallmark of several autoimmune diseases, such as systemic lupus erythematosus (sle), rheumatoid arthritis (ra), sjögren’s syndrome (ss)

Introduction: Knee osteoarthritis (OA) develops gradually and causes pain, a decrease in range of motion, muscle mass, and strength and leads to a decrease in physical activity and a poor quality of life for the patient. The aim of this study was to investigate the effects of different physiotherapy programs on pain intensity, range of motion, and quality of life in people with knee OA. Methods: The study was designed as a prospective, experimental, and randomized trial. Sixty subjects of both sexes and all ages with OA of the knee were enrolled in the study. In the studied Group I (n = 30), in addition to the standard protocol, high induction electromagnetic stimulation was applied using a Salus Talent device with a strength of 3 T and a frequency of up to 50 Hz for 10 min. In the test Group II (n = 30), in addition to the standard protocol, high-intensity laser therapy (HILT) with a power of 5 J was applied with the help of the Ilux Yag 1064 device for 7 min. The therapy protocol for both test groups lasted 8 weeks, with subjects treated once a week. Results: Analysis of the mean scores on the VAS scale shows that in both groups, the lowest mean scores were recorded in the III measurement (4.35) and the highest in the I measurement (7.96). In all three measurements, there was a difference in the extent of mobility of internal rotation in the form of a higher average range of motion in the test group II, in which HILT was applied. Analysis of the mean scores on the knee injury and osteoarthritis outcome score quality of life scale showed that in both groups, the lowest mean scores were recorded at the first measurement (14.84), with the mean score increasing at the second (32.95) and third measurements (41.08). Conclusion: Both methods showed significant results in reducing pain intensity, improving knee mobility, activities of daily living, and quality of life in people with knee OA. The obtained data do not give preference to any method but indicate them as adequate physiotherapy protocols to improve the function and quality of life of people with knee OA.

Mammalian orthoreovirus (MRV) is a prototypic member of the Spinareoviridae family and has ten double-stranded RNA segments. One copy of each segment must be faithfully packaged into the mature virion, and prior literature suggests that nucleotides (nts) at the terminal ends of each gene likely facilitate their packaging. However, little is known about the precise packaging sequences required or how the packaging process is coordinated. Using a novel approach, we have determined that 200 nts at each terminus, inclusive of untranslated regions (UTR) and parts of the open reading frame (ORF), are sufficient for packaging each S gene segment (S1-S4) individually and together into replicating virus. Further, we mapped the minimal sequences required for packaging the S1 gene segment to 25 5′ nts and 50 3′ nts. The S1 UTRs alone are not sufficient, but are necessary for packaging, as mutations of the 5′ or 3′ UTRs led to a complete loss of virus recovery. Using a second novel assay, we determined that 50 5′nts and 50 3′ nts of S1 are sufficient to package a non-viral gene segment into MRV. The 5′ and 3′ termini of the S1 gene are predicted to form a panhandle structure and specific mutations within the predicted stem of the panhandle region led to a significant decrease in viral recovery. Additionally, mutation of six nts that are conserved in the three major serotypes of MRV and are predicted to form an unpaired loop in the S1 3′UTR, led to a complete loss of viral recovery. Overall, our data provide strong experimental proof that MRV packaging signals lie at the terminal ends of the S gene segments and offer support that the sequence requirements for efficient packaging of the S1 segment include a predicted panhandle structure and specific sequences within an unpaired loop in the 3′ UTR.

This study aimed to compare sprint skating profile characteristics of the different playing positions of junior and senior bandy players. In total, 111 male national-level bandy players (age: 20.7 ± 5.0 years, height: 1.80 ± 0.05 m, body mass: 76.4 ± 0.4 kg, training experience: 13.8 ± 5.0 yrs) were tested on their sprint skating profile over 80 m. The main findings were that no differences between positions were found in sprint skating performance (speed and acceleration), but that elite players were in general heavier (p < 0.05) than junior players (80.0 ± 7.1 vs. 73.1 ± 8.1 kg), they could accelerate faster (2.96 ± 0.22 vs. 2.81 ± 0.28 m/s2), and they reached a higher velocity (10.83 ± 0.37 vs. 10.24 ± 0.42 m/s) earlier over 80 m than the junior players. This implies that junior level players should spend more time in power and sprint training to meet the specific demands of playing at a higher, elite level.

The background for this paper concerns a high frequency of work-related disorders that may result from physical exposure at work being highly sedentary, repetitive–monotonous, or physically demanding. This may result in levels of physical inactivity or strenuous activity impairing health. The aim is to present an evidence-based exercise prescription for the work–life population and beyond. The exercise program is designed to be feasible for use at the workplace and/or during leisure time and to improve health, workability, productivity, sickness absence, etc. The specific concept of Intelligent Physical Exercise Training, IPET, includes the assessment of several health-related variables, including musculoskeletal disorders, physical capacity, and physical exposure at work and/or daily life activity. An algorithm with cut-points for prescribing specific exercises is provided. Exercise programs in praxis are addressed through descriptions of precise executions of various prescribed exercises and possible alternatives to optimize variation and adherence. Finally, perspectives on the significance of introducing IPET and the ongoing, as well as future lines of development, are discussed.

Sweet wormwood (Artemisia annua L.) valorization is gaining importance due to the presence of the health-promoting bioactive compound, artemisinin. Considering the wide possible application of artemisinin drug formulations, new, greener technologies in their production are welcome. In this study, artemisinin was extracted from A. annua leaves using green extraction technologies (ultrasound-assisted extraction, supercritical CO2 extraction, deep eutectic solvent extraction and subcritical water extraction) in combination with green solvents. Artemisinin was present up to 3.21 µg/mgdw. Among the different green extraction techniques, HPLC data revealed supercritical CO2 (SCO2) extracts to exhibit the highest yield of artemisinin due to the solvent non-polar properties. Additionally, the volatile compounds profile of SCO2 extract was determined, with camphor (12.23%), arteannuin b (15.29%) and artemisia ketone (10.97%) as the most abundant compounds. Obtained results encourage the use of green extraction techniques for the separation of artemisinin and are expected to find potential in pharmaceutical, cosmetic and food applications.