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Contemporary education is being undeniably shaped by datafication, and while new algorithmic and automated decision-making processes can have educational benefits, they also raise issues about children's digital rights and education policy responses to these rights. This study mapped how children's digital right to privacy and related human rights concepts are present in education policy documents of Australia's three largest state government departments of education. A children's rights coding framework was developed from the United Nation's 'General comment No. 25 (2021) on children's rights in relation to the digital environment' and used to code the dataset. Two levels of analysis were then undertaken. Level 1 involved code and subcode frequency analyses of concepts related to children's digital rights in policy documents. Level 2 was a descriptive qualitative analysis designed to understand how digital rights were expressed in policy. The study found that although all state government departments of education reflected some elements of children's digital rights, some states had a more complex, sustained and public-facing commitment to expressing these in policy. The study concluded that Australian government departments of education should work towards providing more transparent public-facing policy on children's digital rights that can empower students and their families to make informed decisions within a rapidly shifting digital environment.

"Lesson study" has garnered considerable attention from educational researchers and practitioners as a promising method for improving instruction. At its core, lesson study reflects a collaborative inquiry process, grounded in cycles of planning, enacting, and reflecting, that promotes teacher learning through active engagement in lesson refinement. In this article, we leverage lesson study as an exemplar case to foreground an examination and application of theory-based evaluation. We overview a novel evaluation framework contextualized to this multidimensional instructional program and draw out the contributions of theory-based evaluation to the study of program effects. To ground the description of this framework, we summarize representative findings from our ongoing evaluation of a lesson study-based instructional program and discuss processes for selecting, using, and managing evidence sources as well as determining causal strands supporting program outcomes. We conclude by discussing lessons learned and implications for theory-based evaluation of complex programs.

Abstract The WD repeat-containing protein 4 (WDR4) has repeatedly been associated with primary microcephaly, a condition of impaired brain and skull growth. Often, faulty centrosomes cause microcephaly, yet aberrant cilia may also be involved. Here, we show using a combination of approaches in human fibroblasts, zebrafish embryos and patient-derived cells that WDR4 facilitates cilium formation. Molecularly, we associated WDR4 loss-of-function with increased protein synthesis and concomitant upregulation of proteasomal activity, while ubiquitin precursor pools are reduced. Inhibition of proteasomal activity as well as supplementation with free ubiquitin restored normal ciliogenesis. Proteasome inhibition ameliorated microcephaly phenotypes. Thus, we propose that WDR4 loss-of-function impairs head growth and neurogenesis via aberrant cilia formation, initially caused by disturbed protein and ubiquitin homeostasis.

Abstract Copper chaperones of the ATX1 family are found in a wide range of organisms where these essential soluble carriers strictly control the transport of monovalent copper across the cytoplasm to various targets in diverse cellular compartments thereby preventing detrimental radical formation catalyzed by the free metal ion. Notably, the ATX1 family in plants contains two distinct forms of the cellular copper carrier. In addition to ATX1 having orthologs in other species, they also contain the copper chaperone CCH. The latter features an extra C-terminal extension whose function is still unknown. The secondary structure of this extension was predicted to be disordered in previous studies, although this has not been experimentally confirmed. Solution NMR studies on purified CCH presented in this study disclose that this region is intrinsically disordered regardless of the chaperone’s copper loading state. Further biophysical analyses of the purified metallochaperone provide evidence that the C-terminal extension stabilizes chaperone dimerization in the copper-free and copper-bound states. A variant of CCH lacking the C-terminal extension, termed CCHΔ, shows weaker dimerization but similar copper binding. Computational studies further corroborate the stabilizing role of the C-terminal extension in chaperone dimerization and identify key residues that are vital to maintaining dimer stability.

Abstract Background To address the declining numbers of general practitioners (GPs) in rural areas and a lack of medical students pursuing a career in primary care, a general practice-based curriculum coupled with additional university admissions for students has been established at three universities in Hesse, Germany. This study aims to analyze potential topics which students striving to become a GP will benefit from. Teaching such topics will prepare them for their chosen career and working in rural areas. We aimed to explore the views of both specialists and GPs on chief topics and necessary skills in primary care. Methods In our study we used semi-structured interviews with outpatient specialists and specialists in clinical practice and semi-structured group interviews with GPs in training. The topic guide addressed contents of the curriculum for medical students with an extracurricular focus (addressing additional topics) on primary care. Data analysis was carried out using qualitative content analysis according to Mayring. Results GPs in training and specialists agreed on the importance of knowledge in the fields of medical history, physical examination, communication as well as common diseases in primary care. Essential competences mentioned were: inducing medical treatment, decision-making and triage, conducting structured conversations, having patient knowledge (hard skills) as well as an interest in continuous learning, empathy, personal commitment, listening and down-to-earthness (soft skills). Case reports, symptom-based learning, practical training, lessons with simulated patients and the integration of role models were regarded as useful teaching methods. Conclusions General practice-based curriculums should not only focus on the transfer of knowledge. Equally important is the training of soft and hard skills to prepare future GPs for their work in primary care. Special teaching methods as well as practical training should be the heart of a newly established curriculum.

Learning to interpret data in context is an important educational outcome. To assess students' attainment of this outcome, it is necessary to examine the interplay between their contextual and statistical reasoning. We describe a research method designed to do so. The method draws upon Toulmin's (1958, 2003) model of argumentation for the first stage of qualitative data analysis and the Structure of the Observed Learning Outcome (SOLO) (Biggs & Collis, 1991) model for the second stage. Toulmin analyses help identify the justifications and expressions of uncertainty students provide in their interpretive arguments. Subsequent analyses based on the multi-modal conceptualization of SOLO help characterize the quality of student arguments relative to one another. Existing literature and an empirical example are drawn upon to explain how the Toulmin and SOLO models can be used in tandem to analyze students' interpretations of contextualized data. We also explain how pairing Toulmin and SOLO can address theoretical and practical limitations that arise when using just one of the two models on its own.

Recent developments in condition-based maintenance (CBM) have helped make it a promising approach to maintenance cost avoidance in engineering systems. By performing maintenance based on conditions of the component with regards to failure or time, there is potential to avoid the large costs of system shutdown and maintenance delays. However, CBM requires a large investment cost compared to other available maintenance strategies. The investment cost is required for research, development, and implementation. Despite the potential to avoid significant maintenance costs, the large investment cost of CBM makes decision makers hesitant to implement. This study is the first in the literature that attempts to address the problem of conducting a cost-benefit analysis (CBA) for implementing CBM concepts for unmanned systems. This paper proposes a method for conducting a CBA to determine the return on investment (ROI) of potential CBM strategies. The CBA seeks to compare different CBM strategies based on the differences in the various maintenance requirements associated with maintaining a multi-component, unmanned system. The proposed method uses modular dynamic fault tree analysis (MDFTA) with Monte Carlo simulations (MCS) to assess the various maintenance requirements. The proposed method is demonstrated on an unmanned surface vessel (USV) example taken from the literature that consists of 5 subsystems and 71 components. Following this USV example, it is found that selecting different combinations of components for a CBM strategy can have a significant impact on maintenance requirements and ROI by impacting cost avoidances and investment costs.

Part of the reason many districts fail to achieve the promise of high-quality professional learning is that they operate with what the authors call a "PD mindset." This mindset manifests in sporadic, one-time events, inservice sessions, guest speakers, webinars, and workshops that are not part of a larger plan or vision. The authors believe that education leaders and learning designers need to shift from this "PD mindset" to a "professional learning mindset," in which professional learning and growth are centered around accelerating personal and collective learning and closing the knowing-doing gap for leaders and teachers. This article discusses how to make that shift.

Aleksander Robert Stawowski,1 Joanna Konopińska,2 Sylwester Szymon Stawowski,3 Justyna Adamczuk,4 Monika Groth,5 Anna Moniuszko-Malinowska,4 Piotr Czupryna4 1Department of Ophthalmology, University Clinical Hospital in Bialystok, Bialystok, Poland; 2Department of Ophthalmology, Medical University of Bialystok, Bialystok, Poland; 3Non-Public Health Care Facility MEDIX, Bialystok, Poland; 4Department of Infectious Diseases and Neuroinfectious, Medical University of Bialystok, Bialystok, Poland; 5Department of Allergology and Internal Diseases, University Clinical Hospital in Bialystok, Bialystok, PolandCorrespondence: Aleksander Robert Stawowski, Department of Ophthalmology, University Clinical Hospital in Bialystok, Bialystok, Poland, Tel +48-668101778, Email aleksanderstawowski@wp.plAbstract: The COVID-19 pandemic caused by SARS-CoV-2 had a significant impact on the health of the global human population, affecting almost every human organ, including the organ of vision. Research focus on understanding the pathophysiology, identifying symptoms and complications of the disease. Eye-related pathologies are important foci of research due to the potential for direct impact of the virus. Ophthalmologists around the world are reporting various symptoms of eye infections and ocular pathologies associated with SARS-CoV-2. The review of ophthalmic symptoms was conducted to help physicians of various specialties recognize possible ophthalmic manifestations of this viral disease. A literature review was conducted from January 2020 to July 2023 in the PubMed, MEDLINE, Science Direct, Scopus, Scielo and Google Scholar databases. The review of the literature showed that conjunctivitis is the most common ophthalmic symptom observed during the course of COVID-19 and can occur at any stage of the disease. Changes in the eye may result from the direct effect of the virus, immune response, prothrombotic states, comorbidities, and medications used. Symptoms related to the organ of vision can be divided into: changes affecting the protective apparatus of the eye, the anterior eye segment, the posterior eye segment, neuro-ophthalmic, and orbital changes. Ocular symptoms may suggest COVID-19 infection or appear several weeks after recovery. Following COVID-19 vaccinations, a diverse range of ophthalmic symptoms was observed in various locations and at different times, mirroring the ocular symptoms experienced throughout the course of the COVID-19 illness. It is important for physicians of all specialties to be aware of possible potential connections between eye diseases and SARS-CoV-2, in order to effectively diagnose and treat patients.Keywords: COVID-19, SARS-CoV-2, ocular symptoms

Abstract Background Diabetes in pregnancy is associated with increased risk of long-term metabolic disease in the offspring, potentially mediated by in utero epigenetic variation. Previously, we identified multiple differentially methylated single CpG sites in offspring of women with gestational diabetes mellitus (GDM), but whether stretches of differentially methylated regions (DMRs) can also be identified in adolescent GDM offspring is unknown. Here, we investigate which DNA regions in adolescent offspring are differentially methylated in blood by exposure to diabetes in pregnancy. The secondary aim was to characterize the RNA expression of the identified DMR, which contained the nc886 non-coding RNA. Methods To identify DMRs, we employed the bump hunter method in samples from young (9–16 yr, n = 92) offspring of women with GDM (O-GDM) and control offspring (n = 94). Validation by pyrosequencing was performed in an adult offspring cohort (age 28–33 years) consisting of O-GDM (n = 82), offspring exposed to maternal type 1 diabetes (O-T1D, n = 67) and control offspring (O-BP, n = 57). RNA-expression was measured using RT-qPCR in subcutaneous adipose tissue and skeletal muscle. Results One significant DMR represented by 10 CpGs with a bimodal methylation pattern was identified, located in the nc886/VTRNA2-1 non-coding RNA gene. Low methylation status across all CpGs of the nc886 in the young offspring was associated with maternal GDM. While low methylation degree in adult offspring in blood, adipose tissue, and skeletal muscle was not associated with maternal GDM, adipose tissue nc886 expression was increased in O-GDM compared to O-BP, but not in O-T1D. In addition, adipose tissue nc886 expression levels were positively associated with maternal pre-pregnancy BMI (p = 0.006), but not with the offspring’s own adiposity. Conclusions Our results highlight that nc886 is a metastable epiallele, whose methylation in young offspring is negatively correlated with maternal obesity and GDM status. The physiological effect of nc886 may be more important in adipose tissue than in skeletal muscle. Further research should aim to investigate how nc886 regulation in adipose tissue by exposure to GDM may contribute to development of metabolic disease.

Abstract Although DNA methylation data yields highly accurate age predictors, little is known about the dynamics of this quintessential epigenomic biomarker during lifespan. To narrow the gap, we investigate the methylation trajectories of male mouse colon at five different time points of aging. Our study indicates the existence of sudden hypermethylation events at specific stages of life. Precisely, we identify two epigenomic switches during early-to-midlife (3-9 months) and mid-to-late-life (15-24 months) transitions, separating the rodents’ life into three stages. These nonlinear methylation dynamics predominantly affect genes associated with the nervous system and enrich in bivalently marked chromatin regions. Based on groups of nonlinearly modified loci, we construct a clock-like classifier STageR (STage of aging estimatoR) that accurately predicts murine epigenetic stage. We demonstrate the universality of our clock in an independent mouse cohort and with publicly available datasets.

Abstract Background Gastrointestinal eosinophilic sclerosing fibroplasia (GESF) in cats presents as mass(es) associated with the gastrointestinal tract, mesentery, and abdominal lymph nodes. Hypothesis/Objectives To report the clinicopathological findings, treatment, and outcome of cats with GESF. Animals Sixty client‐owned cats diagnosed with GESF. Methods Retrospective review of medical records of cats with histopathologically confirmed GESF. Results The median age was 5.4 years (interquartile range [IQR], 3.3‐8.9.); 30% were Domestic Shorthairs and 12% were Domestic Longhair cats, with the most prevalent pedigree breeds being Ragdolls (25%), Exotic Shorthair (10%) and Persian (8%) cats. The median duration of clinical signs was 90 days (IQR, 17.5‐247.0); the most common clinical signs were weight loss (60%), hyporexia/anorexia (55%), chronic vomiting (37%), lethargy (35%) and chronic diarrhea (27%). Masses were located in the small intestine (32%), stomach (27%), ileocolic junction (15%), colon (10%), lymph node (8%) and mesentery (8%) and 15% of cats had >1 mass. Eosinophilia was present in 50% and hypoalbuminemia in 28% of cats. The mass was removed surgically in 37% of cases. Most cats (98%) were treated with corticosteroids. Survival was not statistically different between cats treated with surgical resection and cats treated with medical therapy alone, 88% of the cats were still alive at the time of writing. Conclusions and Clinical Importance GESF is an important differential diagnosis for abdominal masses in cats, and has a much better prognosis than previously reported.

Abstract Skeletal muscle function crucially depends on innervation while repair of skeletal muscle relies on resident muscle stem cells (MuSCs). However, it is poorly understood how innervation affects MuSC properties and thereby regeneration of skeletal muscle. Here, we report that loss of innervation causes precocious activation of MuSCs concomitant with the expression of markers of myogenic differentiation. This aberrant activation of MuSCs after loss of innervation is accompanied by profound alterations on the mRNA and protein level. Combination of muscle injury with loss of innervation results in impaired regeneration of skeletal muscle including shifts in myogenic populations concomitant with delayed maturation of regenerating myofibers. We further demonstrate that loss of innervation leads to alterations in myofibers and their secretome, which then affect MuSC behavior. In particular, we identify an increased secretion of Osteopontin and transforming growth factor beta 1 (Tgfb1) by myofibers isolated from mice which had undergone sciatic nerve transection. The altered secretome results in the upregulation of early activating transcription factors, such as Junb, and their target genes in MuSCs. However, the combination of different secreted factors from myofibers after loss of innervation is required to cause the alterations observed in MuSCs after loss of innervation. These data demonstrate that loss of innervation first affects myofibers causing alterations in their secretome which then affect MuSCs underscoring the importance of proper innervation for MuSC functionality and regeneration of skeletal muscle.

This work introduces the Queen's University Agent-Based Outbreak Outcome Model (QUABOOM). This tool is an agent-based Monte Carlo simulation for modelling epidemics and informing public health policy. We illustrate the use of the model by examining capacity restrictions during a lockdown. We find that public health measures should focus on the few locations where many people interact, such as grocery stores, rather than the many locations where few people interact, such as small businesses. We also discuss a case where the results of the simulation can be scaled to larger population sizes, thereby improving computational efficiency.

Analysis of comparable discharges fuelled by either deuterium or protium reveals a clear relationship between the isotope mass and the H-mode density limit. Notably, the density limit is significantly lower in protium, showing a reduction of up to 35 % compared to identical deuterium plasma conditions. Within mixed H-mode density limit (HDL) plasmas, the maximum achievable density, or H-mode density limit, decreases with increasing protium concentration, denoted as cH. For instance, the highest corresponding maximum Greenwald fraction (fGW) of about 1.02 was observed in the pulse with the lowest cH value of 4.4 %. This fGW decreases to 0.96 at cH = 48 %. The average atomic mass, A¯, of the plasma species decreases in these pulses from the value of 1.96 (cH = 4.4 %) down to 1.52 (cH = 48 %). Interestingly, the maximum achievable density appears to be largely unaffected by the applied power value, regardless of whether deuterium or protium is used, as well as under mixed H/D fuelling conditions.Additionally, the measured Greenwald fractions are agreed with a heuristic model based on the SOL pressure threshold of an MHD instability, as proposed by Goldston. This comparison, especially concerning the model’s dependence on isotopic mass, shows full consistency between the measured and predicted Greenwald fractions.

Radiation transport simulations of the deuterium Lyman line series using EIRENE predict a factor of 2 increase of Balmer-α emission in the JET-ILW low confinement divertor plasmas in high-recycling and detached conditions caused by the re-absorption of Lyman-β emission. The photon tracing model in the EIRENE code is applied to SOLPS-ITER pure deuterium plasma solutions of JET-ILW to evaluate the contribution of Lyman-β capture towards the population density of D(p=3) and, consequently, the Balmer-α emission. The local population escape factors of Lyman-α and Lyman-β lines in the JET-ILW divertor show steep spatial gradients and indicate local regions with high opacity in high-recycling and detached conditions. The relative contribution of Lyman-β capture towards the population density of D(p=3) is significant in high-recycling and detached conditions. This observation is further corroborated by line-integrated calculations using Balmer-α diagnostic line-of-sights.

ABSTRACTBooster vaccinations against SARS-CoV-2 are recommended 6–12 months after the last dose or infection in elderly and high-risk groups. The present analysis aims to evaluate whether an interval shorter than 12 months is required in multiple sclerosis patients receiving ofatumumab. Neutralizing antibody status over 1 year in patients receiving booster vaccination in the non-interventional, multicenter KYRIOS study under continued ofatumumab treatment was analyzed. Fifteen patients were included. At the time of the first booster vaccination, ten patients were seropositive for neutralizing antibodies, four patients were seronegative, and for one patient, no baseline levels were available. All patients who were seropositive at baseline showed >2-fold increase in neutralizing antibody titers after the first booster and two patients (20%) showed a >10-fold increase. Among seronegative patients, three (75%) had a >10-fold increase in neutralizing antibody titers. Seropositivity was maintained in almost all patients until month 12. One initially seronegative patient had less than 2-fold increase in neutralizing antibody titers after the booster vaccination and can be considered a non-responder. Most patients with continued ofatumumab treatment are able to maintain permanent seropositivity and therefore presumably constant protection against severe courses of COVID-19 if repeated booster vaccinations are applied.

ABSTRACTThere has been growing interest in the role of B cells in antitumour immunity and potential use in adoptive cellular therapies. To date, the success of such therapies is limited. The intrinsic capacity of B cells to specifically activate tumour-specific CD4+ T cells in vivo via TCR-dependent interactions remains poorly defined. We have developed an in vivo tumour model that utilizes MHCII I-E restriction which limits antigen presentation to tumour-specific CD4 T cells to either tumour-specific B cells or host myeloid antigen presenting cells (APCs) in lymphopenic RAG-/-mice. We have previously shown that these naive tumour-specific CD4+ T cells can successfully eradicate established tumours in this model when activated by host APCs. When naïve tumour-specific B cells are the only source of I-E+ APC, very limited proliferation of naïve CD4+ T cells is observed, whereas host I-E+ APCs are potent T cell activators. B cells pre-activated with an anti-CD40 agonistic antibody in vivo support increased T cell proliferation, although far less than host APCs. CD4+ T cells that have already differentiated to an effector/central memory phenotype proliferate more readily in response to naïve B cells, although still 100-fold less than in response to host APCs. This study demonstrates that even in a significantly lymphopenic environment, myeloid APCs are the dominant primary activators of tumour-specific T cells, in contrast to the very limited capacity of tumour-specific B cells. This suggests that future anti-tumour therapies that incorporate activated B cells should also include mechanisms that activate host APCs.

The St. Nicolas House Analysis (SNHA) is a new graph estimation method for detection of extensive interactions among variables. It operates by ranking absolute bivariate correlation coefficients in descending order thereby creating hierarchic association chains. The latter characterizes dependence structures of interacting variables which can be visualized in a corresponding network graph as a chain of end-to-end connected edges representing direct relationships between the connected nodes. The important advantage of this relatively new approach is that it produces less false positive edges resulting from indirect or transitive associations than expected with standard correlation or linear model-based approaches. Here we aim to improve the detection of ramifications in graphs by addition of different data processing layers to SNHA. They include the combinations of the extensions R-squared gaining(RSG) and linear model check(LMC). SNHA together with these so-called extensions were benchmarked against default SNHA and other reference methods available for the programming language R. In the end combinations of RSG, LMC and Bootstrapping improve SNHA performance across different network types, albeit at the cost of longer computation time.