The goal in the present paper was to examine the combined and relative impact of fine motor ability, auditory working memory, and processing speed on fluid intelligence in a sample of early elementary school students. Our participant sample was 145 children (Mage = 9.1 years, SD = 1.1; 80 boys, 65 girls). We used the Raven’s Colored Progressive Matrices Test as a measure of fluid intelligence and five other measures to represent the three predictor variables: the Grooved Pegboard Test as a measure of fine motor skills, Digit Span Forwards and Digit Span Backwards tests as measures of working memory, and Rapid Automatized Naming and Letter-Digit Substitution tasks as measures of processing speed. Regression analyses indicated that only two of these measures had a statistically significant association with the fluid intelligence test scores, namely, scores on the Grooved Pegboard (fine motor skills) and Digit Span Backwards (working memory) tests, with these two measures explaining 35% of the variance in the fluid intelligence test scores. Thus, fine motor skills and working memory were correlated with fluid intelligence in early elementary-grade students. Until the directions of these relationships are better understood, we might assume that interventions aiming to increase young children’s fluid intelligence, or at least their intelligence scores, might partly target working memory and fine motor skills.

Driven by co‐evolution with pathogens, host immunity continuously adapts to optimize defence against pathogens within a given environment. Recent advances in genetics, genomics and transcriptomics have enabled a more detailed investigation into how immunogenetic variation shapes the diversity of immune responses seen across domestic and wild animal species. However, a deeper understanding of the diverse molecular mechanisms that shape immunity within and among species is still needed to gain insight into—and generate evolutionary hypotheses on—the ultimate drivers of immunological differences. Here, we discuss current advances in our understanding of molecular evolution underpinning jawed vertebrate immunity. First, we introduce the immunome concept, a framework for characterizing genes involved in immune defence from a comparative perspective, then we outline how immune genes of interest can be identified. Second, we focus on how different selection modes are observed acting across groups of immune genes and propose hypotheses to explain these differences. We then provide an overview of the approaches used so far to study the evolutionary heterogeneity of immune genes on macro and microevolutionary scales. Finally, we discuss some of the current evidence as to how specific pathogens affect the evolution of different groups of immune genes. This review results from the collective discussion on the current key challenges in evolutionary immunology conducted at the ESEB 2021 Online Satellite Symposium: Molecular evolution of the vertebrate immune system, from the lab to natural populations.

Many large-scale systems are composed of subsystems operated by decentralized controllers, which are fixed in their structure, yet have parameters to tune. Initial tuning or subsequent adjustments dof those parameters ue to varying operating conditions or changes in the network of interconnected systems, while ensuring stability, performance, and security, pose a challenging task due to the overall complexity and size. Subsystems may not be willing or allowed to expose detailed information for safety and privacy reasons. In some cases, a comprehensive system model might not be available for global tuning, or the resulting problem might be computationally infeasible. To enable meaningful global parameter tuning while allowing for data privacy and security, we propose that the subsystems themselves should provide reduced-order models. These models capture the parametric dependency of the subsystem dynamics on the controller parameters. Specifically, we present a method to construct a region in the subsystems’ parameter space in which the deviation of the subsystem and the reduced-order model stays below a specified error bound and in which both systems are stable. A necessary and sufficient condition for such regions is derived using robust control theory. Notably, sufficiency can be expressed in terms of a linear matrix inequality. We demonstrate the approach by considering the temperature control of a large-scale building complex.

This paper explores the use of semantic knowledge inherent in the cyber-physical system (CPS) being studied in order to minimize the use of explicit communication, which refers to the use of physical radio resources to transmit potentially informative data. It is assumed that the acquired data have a function in the system, usually related to its state estimation, which may trigger control actions. We propose a semantic-functional approach that can leverage semantic-enabled implicit communication while ensuring the system maintains its required functionality and performance. We illustrate the potential of this proposal through simulations of a swarm of drones jointly performing remote sensing in a given area. Our numerical results demonstrate that the proposed method offers the best design option regarding the ability to accomplish a previously established task—remote sensing in the addressed case—while minimizing the use of explicit communication by controlling the trade-offs that jointly determine the performance and effectiveness of the CPS in terms of resource utilization. In this sense, we establish a fundamental relationship among energy, communication, and functionality, considering a specific end application.

Obesity, a highly prevalent disorder and central diagnosis of the metabolic syndrome, is linked to mental health by clinical observations and biological pathways. Patients with a diagnosis of obesity may show long-lasting increases in risk for receiving psychiatric co-diagnoses. Austrian national registry data of inpatient services from 1997 to 2014 were analyzed to detect associations between a hospital diagnosis of obesity (ICD-10: E66) and disorders grouped by level-3 ICD-10 codes. Data were stratified by age decades and associations between each pair of diagnoses were computed with the Cochran-Mantel-Haenszel method, providing odds ratios (OR) and p values corrected for multiple testing. Further, directions of the associations were assessed by calculating time-order-ratios. Receiving a diagnosis of obesity significantly increased the odds for a large spectrum of psychiatric disorders across all age groups, including depression, psychosis-spectrum, anxiety, eating and personality disorders (all p _corr < 0.01, all OR > 1.5). For all co-diagnoses except for psychosis-spectrum, obesity was significantly more often the diagnosis received first. Further, significant sex differences were found for most disorders, with women showing increased risk for all disorders except schizophrenia and nicotine addiction. In addition to the well-recognized role in promoting disorders related to the metabolic syndrome and severe cardiometabolic sequalae, obesity commonly precedes severe mental health disorders. Risk is most pronounced in young age groups and particularly increased in female patients. Consequently, thorough screening for mental health problems in patients with obesity is urgently called for to allow prevention and facilitate adequate treatment.

Epigenetic modifications play a vital role in the preservation of genome integrity and in the regulation of gene expression. DNA methylation, one of the key mechanisms of epigenetic control, impacts growth, development, stress response and adaptability of all organisms, including plants. The detection of DNA methylation marks is crucial for understanding the mechanisms underlying these processes and for developing strategies to improve productivity and stress resistance of crop plants. There are different methods for detecting plant DNA methylation, such as bisulfite sequencing, methylation-sensitive amplified polymorphism, genome-wide DNA methylation analysis, methylated DNA immunoprecipitation sequencing, reduced representation bisulfite sequencing, MS and immuno-based techniques. These profiling approaches vary in many aspects, including DNA input, resolution, genomic region coverage, and bioinformatics analysis. Selecting an appropriate methylation screening approach requires an understanding of all these techniques. This review provides an overview of DNA methylation profiling methods in crop plants, along with comparisons of the efficacy of these techniques between model and crop plants. The strengths and limitations of each methodological approach are outlined, and the importance of considering both technical and biological factors are highlighted. Additionally, methods for modulating DNA methylation in model and crop species are presented. Overall, this review will assist scientists in making informed decisions when selecting an appropriate DNA methylation profiling method.

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.

Juvenile systemic sclerosis (jSSc) is an orphan disease with a prevalence of 3 in 1 000 000 children. In adult patients there are significant differences between the clinical presentation of diffuse and limited subtypes. We reviewed clinical differences in presentation of subtypes in patients in the juvenile systemic scleroderma inception cohort (jSScC).To study the clinical presentation of jSSc patients with diffuse (djSSc) and limited (ljSSc) subtypes.We reviewed the baseline clinical characteristics of the patients, who were recruited to the jSScC till December 2022. jSScC is a prospective cohort of jSSc patients, who developed the first non-Raynaud´s symptom before the age of 16 years and are under the age of 18 years at the time of inclusion.The JSScC included 232 patients, 68% (n=159) had diffuse subtype. The median age at onset of Raynaud phenomenon was 10.4 years (7.3-12.9), at the first non-Raynaud symptom 10.9 years (7.3-13.0) and median disease duration 2.5 years (1.0-4.6). The female/male ratio was significantly lower in the djSSc subtype (3:1 versus 5:1, p<0.001). Antibody profile was similar, with the exception of a significantly higher number of anticentromere positive patients in the ljSSc. Decreased FVC<80% was found in approximately 30% and decreased DLCO<80% was found in around 40% in both subtypes. Abnormal HRCT findings were found in 44% of patients. Pulmonary hypertension assessed by ultrasound occurred in approximately 5% in both groups and gastrointestinal involvement in 43% of djSSc and 36% in ljSSc (p=0.303). Patients with djSSc had significantly higher modified Rodnan Skin Score, more frequently sclerodactyly, a history of digital ulceration active ulceration, telangiectasia, a decreased Body Mass Index z score ≤ -2 and decreased joint range of motion. Patients with ljSSc had significantly higher rate of cardiac involvement. Regarding patient related outcomes assessed by VAS 0-100 djSSc patients had more severe disease also physician related outcome assessed by VAS 0-100 were significantly higher in djSSc (see Table 1).Table 1.Comparison of subtypes at time of inclusion in the cohortWhole Group N=232Diffuse Subtype N=159Limited Subtype N=73P value Anticentromere5% (7/156)2% (2/106)10% (5/50)0.022 MRSS, median (IQR)10 (4 – 20)16 (8 - 27)4 (0 – 8)0.001 Gottron Papules26% (59/228)31% (48/155)15% (11/73)0.011 Sclerodactyly75% (165/219)85% (127/150)55% (38/69)<0.001 Telangiectasia37% (77/209)44%(62/141)22% (15/68)0.002 History of ulceration52% (119/229)62% (98/158)30% (21/71)<0.001 Active ulceration17% (39/229)21% (33/158)8% (6/71)0.021 Only Cardiac involvement5% (12/232)3% (4/159)11% (8/73)0.007 BMI<- 2 z score15% (33/217)20% (29/148)6% (4/69)0.008 Joints with decreased range59% (136/231)64% (101/158)48% (35/73)0.022Physician Reported (Median, IQR) Physician global disease activity30 (20 – 45)n=19735 (20– 50)n=13820 (10 – 30)n=590.001 Physician global disease damage30 (15 – 40)n=19530 (20 – 45)n=13820 (5 – 30)n=570.004 Physician ulceration activity0 (0 – 16)n=2165 (0 – 20)n=1540 (0 – 0)n=620.018Patient Reported (Median, IQR) Patient global disease activity40 (20 – 50)n=17840 (20 – 50)n=12930 (15 – 55)n=490.024 Patient global disease damage30 (15 – 60)n=17740 (20 – 60)n=12825 (5 – 55)n=490.001 Patient Raynaud activity30 (10 – 60)n=20230 (10 – 60)n=14515 (0 – 55)n=570.001 Patient ulceration activity0 (0 – 30)n=20310 (0 – 30)n=1450 (0 – 20)n=580.001In the largest jSSc cohort in the world, djSSc patients have a significantly more severe disease. Patients and physician related outcomes were significantly more severe in djSSc group. Interestingly, we found no differences regarding interstitial lung disease, pulmonary hypertension or gastrointestinal involvement, although the number of patients with decreased BMI ≤ -2 z score was significantly higher in the djSSc patients.NIL.NIL.None Declared.

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.

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%.

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)