Search

Experiments on ASDEX Upgrade (AUG) in 2021 and 2022 have addressed a number of critical issues for ITER and EU DEMO. A major objective of the AUG programme is to shed light on the underlying physics of confinement, stability, and plasma exhaust in order to allow reliable extrapolation of results obtained on present day machines to these reactor-grade devices. Concerning pedestal physics, the mitigation of edge localised modes (ELMs) using resonant magnetic perturbations (RMPs) was found to be consistent with a reduction of the linear peeling-ballooning stability threshold due to the helical deformation of the plasma. Conversely, ELM suppression by RMPs is ascribed to an increased pedestal transport that keeps the plasma away from this boundary. Candidates for this increased transport are locally enhanced turbulence and a locked magnetic island in the pedestal. The enhanced D-alpha (EDA) and quasi-continuous exhaust (QCE) regimes have been established as promising ELM-free scenarios. Here, the pressure gradient at the foot of the H-mode pedestal is reduced by a quasi-coherent mode, consistent with violation of the high-n ballooning mode stability limit there. This is suggestive that the EDA and QCE regimes have a common underlying physics origin. In the area of transport physics, full radius models for both L- and H-modes have been developed. These models predict energy confinement in AUG better than the commonly used global scaling laws, representing a large step towards the goal of predictive capability. A new momentum transport analysis framework has been developed that provides access to the intrinsic torque in the plasma core. In the field of exhaust, the X-Point Radiator (XPR), a cold and dense plasma region on closed flux surfaces close to the X-point, was described by an analytical model that provides an understanding of its formation as well as its stability, i.e., the conditions under which it transitions into a deleterious MARFE with the potential to result in a disruptive termination. With the XPR close to the divertor target, a new detached divertor concept, the compact radiative divertor, was developed. Here, the exhaust power is radiated before reaching the target, allowing close proximity of the X-point to the target. No limitations by the shallow field line angle due to the large flux expansion were observed, and sufficient compression of neutral density was demonstrated. With respect to the pumping of non-recycling impurities, the divertor enrichment was found to mainly depend on the ionisation energy of the impurity under consideration. In the area of MHD physics, analysis of the hot plasma core motion in sawtooth crashes showed good agreement with nonlinear 2-fluid simulations. This indicates that the fast reconnection observed in these events is adequately described including the pressure gradient and the electron inertia in the parallel Ohm’s law. Concerning disruption physics, a shattered pellet injection system was installed in collaboration with the ITER International Organisation. Thanks to the ability to vary the shard size distribution independently of the injection velocity, as well as its impurity admixture, it was possible to tailor the current quench rate, which is an important requirement for future large devices such as ITER. Progress was also made modelling the force reduction of VDEs induced by massive gas injection on AUG. The H-mode density limit was characterised in terms of safe operational space with a newly developed active feedback control method that allowed the stability boundary to be probed several times within a single discharge without inducing a disruptive termination. Regarding integrated operation scenarios, the role of density peaking in the confinement of the ITER baseline scenario (high plasma current) was clarified. The usual energy confinement scaling ITER98( p,y ) does not capture this effect, but the more recent H20 scaling does, highlighting again the importance of developing adequate physics based models. Advanced tokamak scenarios, aiming at large non-inductive current fraction due to non-standard profiles of the safety factor in combination with high normalised plasma pressure were studied with a focus on their access conditions. A method to guide the approach of the targeted safety factor profiles was developed, and the conditions for achieving good confinement were clarified. Based on this, two types of advanced scenarios (‘hybrid’ and ‘elevated’ q -profile) were established on AUG and characterised concerning their plasma performance.

Graphical AbstractTREM-1 and TREM-2 as Therapeutic Targets: Clinical Challenges and Perspectives.

Wikidata is a free, multilingual, open knowledge-base that stores structured, linked data. It has grown rapidly and as of December 2022 contains over 100 million items and millions of statements, making it the largest semantic knowledge-base in existence. Changing the interaction between people and knowledge, Wikidata offers various learning opportunities, leading to new applications in sciences, technology and cultures. These learning opportunities stem in part from the ability to query this data and ask questions that were difficult to answer in the past. They also stem from the ability to visualize query results, for example on a timeline or a map, which, in turn, helps users make sense of the data and draw additional insights from it. Research on the semantic web as learning platform and on Wikidata in the context of education is almost non-existent, and we are just beginning to understand how to utilize it for educational purposes. This research investigates the Semantic Web as a learning platform, focusing on Wikidata as a prime example. To that end, a methodology of multiple case studies was adopted, demonstrating Wikidata uses by early adopters. Seven semi-structured, in-depth interviews were conducted, out of which 10 distinct projects were extracted. A thematic analysis approach was deployed, revealing eight main uses, as well as benefits and challenges to engaging with the platform. The results shed light on Wikidata's potential as a lifelong learning process, enabling opportunities for improved Data Literacy and a worldwide social impact.

The review on the monograph by Igor V. Kolosov “History of Legal Consequentialism: Effectiveness of Law” analyzes and evaluates the content of the monograph. The review emphasizes and investigates contribution of the monograph to the modern development of historical and theoretical ideas about effectiveness of legal regulation and law enforcement, as well as the main practical conclusions of the monograph. In the modern period, when confrontation of various kinds of interests is evident, profit and result are the main guidelines in practical activities almost everywhere. Due to this, common legal and human values, including the need to ensure equality and justice, as well as issues of general legal and human values are more relevant and significant than ever. This makes us refer to classical thought, requires adaptation of ideas formed throughout the history of legal thought to modern realities to improve the existing legal order.

TREM-1 and TREM-2 as Therapeutic Targets: Clinical Challenges and Perspectives. [ABSTRACT FROM AUTHOR]

BackgroundTraditional food allergy assessment of anaphylaxis remains limited in accuracy and accessibility. Current methods of anaphylaxis risk assessment are costly with low predictive accuracy. The Tolerance Induction Program (TIP) for anaphylactic patients undergoing TIP immunotherapy produced large-scale diagnostic data across biosimilar proteins, which was used to develop a machine learning model for patient-specific and allergen-specific anaphylaxis assessment. In explanation of construct, this work describes the algorithm design for assignment of peanut allergen score as a quantitative measure of anaphylaxis risk. Secondarily, it confirms the accuracy of the machine learning model for a specific cohort of food anaphylactic children.Methods and resultsMachine learning model design for allergen score prediction utilized 241 individual allergy assays per patient. Accumulation of data across total IgE subdivision served as the basis of data organization. Two regression based Generalized Linear Models (GLM) were utilized to position allergy assessment on a linear scale. The initial model was further tested with sequential patient data over time. A Bayesian method was then used to improve outcomes by calculating the adaptive weights for the results of the two GLMs of peanut allergy score prediction. A linear combination of both provided the final hybrid machine learning prediction algorithm. Specific analysis of peanut anaphylaxis within one endotype model is estimated to predict the severity of possible anaphylactic reaction to peanut with a recall of 95.2% on a dataset of 530 juvenile patients with various food allergies, including but not limited to peanut allergy. Receiver Operating Characteristic analysis yielded over 99% AUC (area under curve) results within peanut allergy prediction.ConclusionsMachine learning algorithm design established from comprehensive molecular allergy data produces high accuracy and recall in anaphylaxis risk assessment. Subsequent design of additional food protein anaphylaxis algorithms is needed to improve the precision and efficiency of clinical food allergy assessment and immunotherapy treatment.

Legal utilitarianism is attractive for practice because this field of legal thought and philosophy of law sets out a particular direction of legal policy and statutory regulation (focus on the utility principle in decision-making) that can, under certain reservations, be used to improve people's lives. Most scholars conclude that the first utilitarian was J. Bentham. However, scientific studies prevalently do not involve the analysis of earlier legal doctrines in relation to the use of utility principle. Thus, the relevance and scientific novelty of analysis of the origin of legal utilitarianism is associated with the need to develop a theoretical component of this doctrine that is of current interest for the legal policy and to enlarge the underdeveloped - in our opinion - theoretical framework of legal utilitarianism genesis. The purpose is to identify the first theory in the history of legal thought, which can be classified as legal utilitarianism, and, if such theory is the J. Bentham's utilitarianism, to determine the reasons why earlier theories based on the utility principle cannot be classified as legal utilitarianism. The theoretical basis of the article is materials such as original sources by various thinkers whose works are based on the utility principle and scientific papers of European and the US researchers. For the purpose of the article, the following methodological tools were used: metaphysical (dialectic method), general (analysis and synthesis, deduction and induction, analogy, comparison) and specific (historical and legal-historical) scientific methods. The main outcome of the research is identification of distinct features of pre-Bentham legal thought based on the utility principle and identification of pre-requisites and basis (provisions which had formed the basis) for J. Bentham's utilitarianism, as well as the answer to the question: Was J. Bentham the first legal utilitarian?.

PurposeTo identify potential biomarkers of the renal impairment in lupus nephritis using a multi-parametric renal quantitative MRI (qMRI) protocol including diffusion weighted imaging (DWI), blood oxygen level dependent (BOLD), arterial spin labeling (ASL) and T1rho MRI between a cohort of healthy volunteers and lupus nephritis (LN) patients.Materials and methodsThe renal qMRI protocol was performed twice with repositioning in between on 10 LN patients and 10 matched controls at 1.5 T. Navigator-gated and breath-hold acquisitions followed by non-rigid image registration were used to control respiratory motion. The repeatability of the 4 MRI modalities was evaluated with the intra-class correlation coefficient (ICC) and within-subject coefficient of variation (wsCV). Unpaired t-test and stepwise logistic regression were carried out to evaluate qMRI parameters between the LN and control groups.ResultsThe reproducibility of the 4 qMRI modalities ranged from moderate to good (ICC=0.4-0.91, wsCV≤12%) with a few exceptions. T1rho MRI and ASL renal blood flow (RBF) demonstrated significant differences between the LN and control groups. Stepwise logistic regression yielded only one significant parameter (medullar T1rho) in differentiating LN from control groups with 95% accuracy.ConclusionA reasonable degree of test-retest repeatability and accuracy of a multi-parametric renal qMRI protocol has been demonstrated in healthy volunteers and LN subjects. T1rho and ASL RBF are promising imaging biomarkers of LN.

BackgroundTriggering receptor expressed on myeloid cells (TREM)-1 is a key mediator of innate immunity previously associated with the severity of inflammatory disorders, and more recently, the inferior survival of lung and liver cancer patients. Here, we investigated the prognostic impact and immunological correlates of TREM1 expression in breast tumors.MethodsBreast tumor microarray and RNAseq expression profiles (n=4,364 tumors) were analyzed for associations between gene expression, tumor immune subtypes, distant metastasis-free survival (DMFS) and clinical response to neoadjuvant chemotherapy (NAC). Single-cell (sc)RNAseq was performed using the 10X Genomics platform. Statistical associations were assessed by logistic regression, Cox regression, Kaplan-Meier analysis, Spearman correlation, Student’s t-test and Chi-square test.ResultsIn pre-treatment biopsies, TREM1 and known TREM-1 inducible cytokines (IL1B, IL8) were discovered by a statistical ranking procedure as top genes for which high expression was associated with reduced response to NAC, but only in the context of immunologically “hot” tumors otherwise associated with a high NAC response rate. In surgical specimens, TREM1 expression varied among tumor molecular subtypes, with highest expression in the more aggressive subtypes (Basal-like, HER2-E). High TREM1 significantly and reproducibly associated with inferior distant metastasis-free survival (DMFS), independent of conventional prognostic markers. Notably, the association between high TREM1 and inferior DMFS was most prominent in the subset of immunogenic tumors that exhibited the immunologically hot phenotype and otherwise associated with superior DMFS. Further observations from bulk and single-cell RNAseq analyses indicated that TREM1 expression was significantly enriched in polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) and M2-like macrophages, and correlated with downstream transcriptional targets of TREM-1 (IL8, IL-1B, IL6, MCP-1, SPP1, IL1RN, INHBA) which have been previously associated with pro-tumorigenic and immunosuppressive functions.ConclusionsTogether, these findings indicate that increased TREM1 expression is prognostic of inferior breast cancer outcomes and may contribute to myeloid-mediated breast cancer progression and immune suppression.

Sarah Nanoparticles (SaNPs) are unique multicore iron oxide-based nanoparticles, developed for the treatment of advanced cancer, following standard care, through the selective delivery of thermal energy to malignant cells upon exposure to an alternating magnetic field. For their therapeutic effect, SaNPs need to accumulate in the tumor. Since the potential accumulation and associated toxicity in normal tissues are an important risk consideration, biodistribution and toxicity were assessed in naïve BALB/c mice. Therapeutic efficacy and the effect on survival were investigated in the 4T1 murine model of metastatic breast cancer. Toxicity evaluation at various timepoints did not reveal any abnormal clinical signs, evidence of alterations in organ function, nor histopathologic adverse target organ toxicity, even after a follow up period of 25 weeks, confirming the safety of SaNP use. The biodistribution evaluation, following SaNP administration, indicated that SaNPs accumulate mainly in the liver and spleen. A comprehensive pharmacokinetics evaluation, demonstrated that the total percentage of SaNPs that accumulated in the blood and vital organs was ~78%, 46%, and 36% after 4, 13, and 25 weeks, respectively, suggesting a time-dependent clearance from the body. Efficacy studies in mice bearing 4T1 metastatic tumors revealed a 49.6% and 70% reduction in the number of lung metastases and their relative size, respectively, in treated vs. control mice, accompanied by a decrease in tumor cell viability in response to treatment. Moreover, SaNP treatment followed by alternating magnetic field exposure significantly improved the survival rate of treated mice compared to the controls. The median survival time was 29 ± 3.8 days in the treated group vs. 21.6 ± 4.9 days in the control, p-value 0.029. These assessments open new avenues for generating SaNPs and alternating magnetic field application as a potential novel therapeutic modality for metastatic cancer patients.

Thin porous layers are largely used, but a reliable method to quantify their porosity is missing. Here the authors demonstrate a method, based on quartz crystal microbalance measurements with dissipation monitoring, for accurate assessment of porosity and mechanical properties in thin porous films.