Background and aim Striving for harmonisation of specialty training and excellence of care in rheumatology, the European League Against Rheumatism (EULAR) established a task force to develop points to consider (PtCs) for the assessment of competences during rheumatology specialty training. Methods A systematic literature review on the performance of methods for the assessment of competences in rheumatology specialty training was conducted. This was followed by focus groups in five selected countries to gather information on assessment practices and priorities. Combining the collected evidence with expert opinion, the PtCs were formulated by the multidisciplinary task force, including rheumatologists, medical educationalists, and people with rheumatic and musculoskeletal diseases. The level of agreement (LoA) for each PtC was anonymously voted online. Results Four overarching principles and 10 PtCs were formulated. The overarching principles highlighted the importance of assessments being closely linked to the rheumatology training programme and protecting sufficient time and resources to ensure effective implementation. In the PtCs, two were related to overall assessment strategy (PtCs 1 and 5); three focused on formative assessment and portfolio (PtCs 2–4); three focused on the assessment of knowledge, skills or professionalism (PtCs 6–8); one focused on trainees at risk of failure (PtC 9); and one focused on training the trainers (PtC 10). The LoA (0–10) ranged from 8.75 to 9.9. Conclusion These EULAR PtCs provide European guidance on assessment methods throughout rheumatology training programmes. These can be used to benchmark current practices and to develop future strategies, thereby fostering continuous improvement in rheumatology learning and, ultimately, in patient care.

The purpose of this paper is to analyze and compare two different business models called business to business and business to consumer. The first model -business to business or B2B is defined as the transfer of goods and services between businesses or firms without the interference of consumers. The second model, business to consumer or B2C is customer-oriented in which the goods and services are sold immediately to customers in the market. This research focuses on the performance of these two business models in North Macedonia and Serbia. Our analysis tries to provide information regarding the countries’ development in different sectors within B2B and B2C models that are affected by specific indicators such as net salaries, total employment level, investment and exports, and research&innovation. Furthermore, besides the analysis of these indicators separately for each country, the paper will show the results and compare the performance differences among listed developing countries.

Recurrent copy number variations (CNVs) are common causes of neurodevelopmental disorders (NDDs) and associated with a range of psychiatric traits. These CNVs occur at defined genomic regions that are particularly prone to recurrent deletions and duplications and often exhibit variable expressivity and incomplete penetrance. Robust estimates of the population prevalence and inheritance pattern of recurrent CNVs associated with neurodevelopmental disorders (NDD CNVs) are lacking. Here we perform array-based CNV calling in 12,252 mother–father–child trios from the Norwegian Mother, Father, and Child Cohort Study (MoBa) and analyse the inheritance pattern of 26 recurrent NDD CNVs in 13 genomic regions. We estimate the total prevalence of recurrent NDD CNVs (duplications and deletions) in live-born children to 0.48% (95% C.I.: 0.37–0.62%), i.e., ~1 in 200 newborns has either a deletion or duplication in these NDDs associated regions. Approximately a third of the newborn recurrent NDD CNVs (34%, N  = 20/59) are de novo variants. We provide prevalence estimates and inheritance information for each of the 26 NDD CNVs and find higher prevalence than previously reported for 1q21.1 deletions (~1:2000), 15q11.2 duplications (~1:4000), 15q13.3 microdeletions (~1:2500), 16p11.2 proximal microdeletions (~1:2000) and 17q12 deletions (~1:4000) and lower than previously reported prevalence for the 22q11.2 deletion (~1:12,000). In conclusion, our analysis of an unselected and representative population of newborns and their parents provides a clearer picture of the rate of recurrent microdeletions/duplications implicated in neurodevelopmental delay. These results will provide an important resource for genetic diagnostics and counseling.

Recurrent copy number variations (CNVs) are common causes of neurodevelopmental disorders (NDDs) and associated with a range of psychiatric traits. These CNVs occur at defined genomic regions that are particularly prone to recurrent deletions and duplications and often exhibit variable expressivity and incomplete penetrance. Robust estimates of the population prevalence and inheritance pattern of recurrent CNVs associated with neurodevelopmental disorders (NDD CNVs) are lacking. Here we perform array-based CNV calling in 12,252 mother–father–child trios from the Norwegian Mother, Father, and Child Cohort Study (MoBa) and analyse the inheritance pattern of 26 recurrent NDD CNVs in 13 genomic regions. We estimate the total prevalence of recurrent NDD CNVs (duplications and deletions) in live-born children to 0.48% (95% C.I.: 0.37–0.62%), i.e., ~1 in 200 newborns has either a deletion or duplication in these NDDs associated regions. Approximately a third of the newborn recurrent NDD CNVs (34%, N = 20/59) are de novo variants. We provide prevalence estimates and inheritance information for each of the 26 NDD CNVs and find higher prevalence than previously reported for 1q21.1 deletions (~1:2000), 15q11.2 duplications (~1:4000), 15q13.3 microdeletions (~1:2500), 16p11.2 proximal microdeletions (~1:2000) and 17q12 deletions (~1:4000) and lower than previously reported prevalence for the 22q11.2 deletion (~1:12,000). In conclusion, our analysis of an unselected and representative population of newborns and their parents provides a clearer picture of the rate of recurrent microdeletions/duplications implicated in neurodevelopmental delay. These results will provide an important resource for genetic diagnostics and counseling.

Based on the strong-field approximation, we report results for high-order harmonic generation by bi-elliptical orthogonally polarized two-color (BEOTC) fields with frequency ratios of 2:1 and 3:1 and fundamental wavelengths of 800 and 1800 nm. A BEOTC field denotes the superposition of two copropagating counter-rotating elliptically polarized fields with different wavelengths and orthogonal semimajor axes. Its two limiting cases are the bicircular field and the linearly polarized orthogonal two-color field [D. B. Milo\ifmmode \check{s}\else \v{s}\fi{}evi\ifmmode \acute{c}\else \'{c}\fi{} and W. Becker, Phys. Rev. A 100, 031401(R) (2019)]. A detailed analysis of the high-order harmonic intensities and ellipticities as functions of the harmonic order, the ellipticity, and the relative phase between the two driving-field components is presented. Regions of the parameter space are identified where the harmonic ellipticities are very high. Surprisingly, this can be the case already for very small ellipticity (as small as $\ensuremath{\varepsilon}=0.01$) of the driving field. This can be important for practical applications. In the opposite limit where the BEOTC field is close to bicircular, the selection rules that govern the latter case can also be very quickly invalidated. For the 2:1 case, this can result in an apparent shift of the selection rules by one harmonic order.

Background: Alzheimer’s disease is a complex disorder of unclear etiology that develops in the elderly population. It is a debilitating, progressive neurodegeneration for which disease-modifying therapies do not exist. Previous studies have suggested that, for a subset of patients, dysregulation in hemostasis might be one of the molecular mechanisms that ultimately leads to the development of neurodegeneration resulting in cognitive decline that represents the most prominent symptomatic characteristic of Alzheimer’s disease. Objective: To examine a relationship between factors that are part of coagulation and anticoagulation pathways with cognitive decline that develops during Alzheimer’s disease. Methods: SOMAscan assay was used to measure levels of coagulation/anticoagulation factors V, VII, IX, X, Xa, XI, antithrombin III, protein S, protein C, and activated protein C in plasma samples obtained from three groups of subjects: 1) subjects with stable cognitively healthy function, 2) subjects with stable mild cognitive impairment, and 3) subjects diagnosed with probable Alzheimer’s disease. Results: Our results show that protein levels of coagulation factor XI are significantly increased in patients who are diagnosed with probable Alzheimer’s disease compared with cognitively healthy subjects or patients diagnosed with mild cognitive impairment. Furthermore, our results demonstrate that significant predictors of Alzheimer’s-type diagnosis are factors IX and XI—an increase in both factors is associated with a reduction in cognitive function. Conclusion: Our study justifies further investigations of biological pathways involving coagulation/anticoagulation factors in relation to dementia, including dementia resulting from Alzheimer’s-type neurodegeneration.

Diesel exhaust is carcinogenic and exposure to diesel particles cause health effects. We investigated the toxicity of diesel exhaust particles designed to have varying physicochemical properties in order to attribute health effects to specific particle characteristics. Particles from three fuel types were compared at 13% engine intake O2 concentration: MK1 ultra low sulfur diesel (DEP13) and the two renewable diesel fuels hydrotreated vegetable oil (HVO13) and rapeseed methyl ester (RME13). Additionally, diesel particles from MK1 ultra low sulfur diesel were generated at 9.7% (DEP9.7) and 17% (DEP17) intake O2 concentration. We evaluated physicochemical properties and histopathological, inflammatory and genotoxic responses on day 1, 28, and 90 after single intratracheal instillation in mice compared to reference diesel particles and carbon black. Moderate variations were seen in physical properties for the five particles: primary particle diameter: 15–22 nm, specific surface area: 152–222 m2/g, and count median mobility diameter: 55–103 nm. Larger differences were found in chemical composition: organic carbon/total carbon ratio (0.12–0.60), polycyclic aromatic hydrocarbon content (1–27 μg/mg) and acid-extractable metal content (0.9–16 μg/mg). Intratracheal exposure to all five particles induced similar toxicological responses, with different potency. Lung particle retention was observed in DEP13 and HVO13 exposed mice on day 28 post-exposure, with less retention for the other fuel types. RME exposure induced limited response whereas the remaining particles induced dose-dependent inflammation and acute phase response on day 1. DEP13 induced acute phase response on day 28 and inflammation on day 90. DNA strand break levels were not increased as compared to vehicle, but were increased in lung and liver compared to blank filter extraction control. Neutrophil influx on day 1 correlated best with estimated deposited surface area, but also with elemental carbon, organic carbon and PAHs. DNA strand break levels in lung on day 28 and in liver on day 90 correlated with acellular particle-induced ROS. We studied diesel exhaust particles designed to differ in physicochemical properties. Our study highlights specific surface area, elemental carbon content, PAHs and ROS-generating potential as physicochemical predictors of diesel particle toxicity.

Beer production includes the formation of different by-products such as wastewater, spent grains, spent hops, and yeast. In addition to these well-known by-products, it is necessary to mention germ/rootlets, which also remain after the malting process. Given that a huge amount of beer is produced annually worldwide, by-products are available in large quantities throughout the year. Spent grains, spent hops, and spent yeasts are high-energy raw materials that possess a great potential for application in the branch of biotechnology, and the food industry, but these by-products are commonly used as livestock feed, disposed of in the fields, or incinerated. Breweries by-products can be utilized for microalgae production, biofuel production, extraction of proteins, polyphenolic, antioxidative substances, etc. This paper aims to address each of these by-products with an emphasis on their possible application in biotechnology and other industries.

Prompt identification of acute coronary syndrome is a challenge in clinical practice. The 12-lead electrocardiogram (ECG) is readily available during initial patient evaluation, but current rule-based interpretation approaches lack sufficient accuracy. Here we report machine learning-based methods for the prediction of underlying acute myocardial ischemia in patients with chest pain. Using 554 temporal-spatial features of the 12-lead ECG, we train and test multiple classifiers on two independent prospective patient cohorts (n = 1244). While maintaining higher negative predictive value, our final fusion model achieves 52% gain in sensitivity compared to commercial interpretation software and 37% gain in sensitivity compared to experienced clinicians. Such an ultra-early, ECG-based clinical decision support tool, when combined with the judgment of trained emergency personnel, would help to improve clinical outcomes and reduce unnecessary costs in patients with chest pain. Diagnosing a heart attack requires excessive testing and prolonged observation, which frequently requires hospital admission. Here the authors report a machine learning-based system based exclusively on ECG data that can help clinicians identify 37% more heart attacks during initial screening.