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Science learning is an important part of the K-12 educational experience, as well as in the lives of students. This study considered students' science learning as they engaged in the instruction of scientific issues with social relevance. With classroom environments radically changing during the COVID-19 pandemic, our study adapted to teachers and students as they were forced to change from more traditional, in-person instructional settings to virtual, online instruction settings. In the present study, we considered science learning during a scaffold-facilitated process, where secondary students evaluated the connections between lines of scientific evidence and alternative explanations about fossil fuels and climate change and gauged the plausibility of each explanation. Our investigation focused on the relations between students' levels of evaluations, shifts in plausibility judgments, and knowledge gains, and examined whether there were differences in these relations between in-person classroom settings and virtual classroom settings. The results revealed that the indirect relational pathway linking higher levels of evaluation, plausibility shifts toward a more scientific stance, and greater knowledge gains was meaningful and more robust than the direct relational pathway linking higher levels of evaluation to greater knowledge gains. The results also showed no meaningful difference between the two instructional settings, suggesting the potential adaptiveness and effectiveness of properly-designed, scaffolded science instruction.

Abstract While significant advances have been made in understanding renal pathophysiology, less is known about the role of glycosphingolipid (GSL) metabolism in driving organ dysfunction. Here, we used a small molecule inhibitor of glucosylceramide synthase to modulate GSL levels in three mouse models of distinct renal pathologies: Alport syndrome (Col4a3 KO), polycystic kidney disease (Nek8 jck ), and steroid-resistant nephrotic syndrome (Nphs2 cKO). At the tissue level, we identified a core immune-enriched transcriptional signature that was shared across models and enriched in human polycystic kidney disease. Single nuclei analysis identified robust transcriptional changes across multiple kidney cell types, including epithelial and immune lineages. To further explore the role of GSL modulation in macrophage biology, we performed in vitro studies with homeostatic and inflammatory bone marrow-derived macrophages. Cumulatively, this study provides a comprehensive overview of renal dysfunction and the effect of GSL modulation on kidney-derived cells in the setting of renal dysfunction.

Abstract Background Serum creatinine is used as initial test to derive eGFR and confirmatory testing with serum cystatin C is recommended when creatinine‐based eGFR is considered less accurate due to deviant muscle mass. Low muscle mass is associated with increased risk of premature mortality. However, the associations of serum creatinine and cystatin C with muscle mass and mortality remain unclear and require further investigation to better inform clinical decision‐making. Methods We included 8437 community‐dwelling adults enrolled in the Dutch PREVEND study and 5033 in the US NHANES replication cohort. Associations of serum creatinine and/or cystatin C with muscle mass surrogates and mortality were quantified with linear and Cox proportional hazards regression, respectively. Missing observations in covariates were multiply imputed using Substantive Model Compatible Fully Conditional Specification. Results Mean (SD) age of PREVEND and NHANES participants (50% and 48% male) were 49.8 (12.6) and 48.7 (18.7) years, respectively. Median (Q1–Q3) serum creatinine and cystatin C were 71 (61–80) and 80 (62–88) μmol/L and 0.87 (0.78–0.98) and 0.91 (0.80–1.10) mg/L, respectively. Higher serum creatinine was associated with greater muscle mass, while serum cystatin C was not associated with muscle mass. Adjusting both markers for each other strengthened the positive relationship between serum creatinine and muscle mass and revealed an inverse association between serum cystatin C and muscle mass. In the PREVEND cohort, 1636 (19%) deaths were registered over a median follow‐up of 12.9 (5.8–16.3) years with a 10‐year mortality rate (95% CI) of 7.6% (7.1–8.2%). In the NHANES, 1273 (25%) deaths were registered over a median follow‐up of 17.9 (17.3–18.5) years with a 10‐year mortality rate of 13.8% (12.8–14.7%). Both markers were associated with increased mortality. Notably, when adjusted for each other, higher serum creatinine was associated with decreased mortality, while the association between serum cystatin C and increased mortality strengthened. The shapes of the associations in the PREVEND study and NHANES were almost identical. Conclusions The strong association between serum creatinine and muscle mass challenges its reliability as GFR marker, necessitating a more cautious approach in its clinical use. The minimal association between serum cystatin C and muscle mass supports its increased use as a more reliable alternative in routine clinical practice.

Abstract The resonance-stabilization of the propargyl radical (C3H3) makes it among the most important reactive intermediates in extreme environments and grants it a long enough lifetime to recombine in both terrestrial combustion media and cold molecular clouds in space. This makes the propargyl self-reaction a pivotal step in the formation of benzene, the first aromatic ring, to eventually lead to polycyclic aromatic hydrocarbons in a variety of environments. In this work, by producing propargyl radicals in a flow tube where propyne reacted with F atoms and probing the reaction products by mass-selected threshold-photoelectron spectroscopy (TPES), we identified eight C6H6 products in total, including benzene. On top of providing the first comprehensive measurements of the branching ratios of the eight identified C6H6 isomers in the propargyl self reaction products (4 mbar, 298 K conditions), this study also highlights the advantages and disadvantages of using isomer-selective TPES to identify and quantify reaction products.

Abstract Background Informal care is an essential part of support provided in the homecare setting. To ensure effective healthcare provision, good communication and collaboration between informal and formal care providers are crucial. To achieve this aim, it is necessary to have a clear understanding of the perspectives of all stakeholders. In the scientific literature, limited knowledge is available regarding family members’ opinions about their involvement in care. To date, no instruments have been developed that accurately measure these opinions. This study aims to elucidate the opinions of family members about their involvement in nursing care. Methods A cross-sectional survey approach was employed. The methodological steps in this study were (1) convert the Families’ Importance in Nursing Care–Nurses’ Attitudes (FINC-NA) from a nurses’ perspective to a family perspective and thus develop the Families’ Importance in Nursing Care–Families’ Opinions (FINC-FO) and (2) measure families’ opinions regarding their involvement in home nursing care. The questionnaire was sent to 3,800 patients with activated patient portals, which accounts for about 17% of the total patient base. Responses were received from 1,339 family members, a response rate of 35%. Results The developed FINC-FO questionnaire showed homogeneity and internal consistency. The results of the questionnaire indicate that family members consider it important to be involved in care and that they wish to be acknowledged as participants in discussions about care (planning) but are less inclined to actively participate in the provision of care by nurses. Family members expressed less explicit opinions about their own support needs. Factors such as level of education, type of partnership, and amount of care provided are seemingly associated with these opinions. Conclusions Family members in the homecare setting wish to be involved in discussions about care (planning). The transition in care from primarily formal to more informal care necessitates an awareness and clear definition—on part of both healthcare professionals and families—of their respective roles in the provision of care. Communication about wishes, expectations, and the need for support in care is essential to ensure quality of care and that the family can sustain caregiving.

The model  is designed to estimate the impacts of various elements of the ACA on employer decisions to offer insurance coverage and individual decisions to obtain coverage in California.

Non-IgE immune-mediated gastrointestinal disorders constitute a heterogeneous group of enigmatic conditions that are on the rise. This category encompasses entities like food protein-induced enterocolitis syndrome (FPIES), food protein-induced allergic proctocolitis (FPIAP), and food protein-induced enteropathy (FPE). These are immune-mediated reactions to certain foods without the involvement of allergen-specific IgE in their pathogenesis. Eosinophilic esophagitis (EoE) is also included in this group, acknowledged for its mixed IgE and non-IgE-mediated characteristics. The diagnostic landscape is fraught with challenges, given the poorly understood nature of these disorders and their propensity to manifest with varying and overlapping clinical presentations, typically emerging in infancy with common potential triggers such as cow’s milk and soy. Presently, confirmatory testing for most of these conditions is limited and invasive, emphasizing the pivotal role of a thorough history and physical examination in reaching a diagnosis. Notably, there are limited guidelines for diagnosis and management for most of these disorders. This article elucidates the key distinctions among these disorders, provides an overview of existing diagnostic and therapeutic approaches, and addresses existing knowledge and research gaps. The considerable impact on the quality of life of non-IgE immune-mediated allergic disorders of the gastrointestinal tract, which can result in debilitating complications such as nutritional deficiencies, mental health disorders, and eating disorders, underscores the urgency for comprehensive exploration and management strategies.

Primary immune regulatory disorders (PIRDs) constitute a subset of inborn errors of immunity and are characterized by lymphoproliferation, autoimmunity, malignancy, and infection. Unlike classical primary immune deficiencies, initial symptoms of PIRDs can manifest as autoimmunity such as cytopenias or enteropathy, which can often prove resistant to conventional treatments and occur years prior to the onset of infectious complications. Raising awareness about PIRDs among specialists and adopting a multidisciplinary approach is crucial for early diagnosis, intervention, and potential prevention of severe organ damage. Significant progress has been made in identifying several PIRDs, which has contributed to a more comprehensive comprehension of their underlying immunological mechanisms. This knowledge has paved the way for targeted therapies focusing on specific molecules, which tend to offer superior disease control compared to traditional immunosuppressants. This review, informed by the latest literature, explores prevalent PIRDs, detailing their clinical manifestations and recent advancements in treatment modalities.

Functional analyses are the main method to classify mismatch repair (MMR) gene variants of uncertain significance (VUSs). However, the pathogenicity remains unclear for many variants because of conflicting results between clinical, molecular, and functional data. In this study, we evaluated whether whole exome sequencing (WES) could add another layer of evidence to elucidate the pathogenicity of MMR variants with conflicting interpretations. WES was performed on formalin-fixed paraffin-embedded tumor tissue of eight patients with a constitutional MMR VUS (seven families), including eight colorectal and two endometrial carcinomas and one ovarian carcinoma. Cell-free CIMRA assays were performed to assign Odds of Pathogenicity to these VUSs. In four families, seven tumors showed MMR deficiency-associated mutational signatures, supporting the pathogenicity of the VUS. Moreover, somatic (second) MMR hits identified in the WES data were found to explain MMR staining patterns when the MMR staining was discordant with the reported germline MMR gene variant. In conclusion, WES did not significantly reclassify VUS in these cases but clarified some phenotypic aspects such as age of onset and explanations in case of discordant MMR stainings.

BackgroundDisability progression is a key milestone in the disease evolution of people with multiple sclerosis (PwMS). Prediction models of the probability of disability progression have not yet reached the level of trust needed to be adopted in the clinic. A common benchmark to assess model development in multiple sclerosis is also currently lacking.MethodsData of adult PwMS with a follow-up of at least three years from 146 MS centers, spread over 40 countries and collected by the MSBase consortium was used. With basic inclusion criteria for quality requirements, it represents a total of 15, 240 PwMS. External validation was performed and repeated five times to assess the significance of the results. Transparent Reporting for Individual Prognosis Or Diagnosis (TRIPOD) guidelines were followed. Confirmed disability progression after two years was predicted, with a confirmation window of six months. Only routinely collected variables were used such as the expanded disability status scale, treatment, relapse information, and MS course. To learn the probability of disability progression, state-of-the-art machine learning models were investigated. The discrimination performance of the models is evaluated with the area under the receiver operator curve (ROC-AUC) and under the precision recall curve (AUC-PR), and their calibration via the Brier score and the expected calibration error. All our preprocessing and model code are available at https://gitlab.com/edebrouwer/ms_benchmark, making this task an ideal benchmark for predicting disability progression in MS.FindingsMachine learning models achieved a ROC-AUC of 0⋅71 ± 0⋅01, an AUC-PR of 0⋅26 ± 0⋅02, a Brier score of 0⋅1 ± 0⋅01 and an expected calibration error of 0⋅07 ± 0⋅04. The history of disability progression was identified as being more predictive for future disability progression than the treatment or relapses history.ConclusionsGood discrimination and calibration performance on an external validation set is achieved, using only routinely collected variables. This suggests machine-learning models can reliably inform clinicians about the future occurrence of progression and are mature for a clinical impact study.

While the growth rate of atmospheric CO2 mole fractions can be measured with high accuracy, there are still large uncertainties in its attribution to specific regions and diverse anthropogenic and natural sources and sinks. A major source of uncertainty is the net flux of carbon dioxide from the biosphere to the atmosphere, the net ecosystem exchange (NEE). There are two major approaches to quantifying NEE: top-down approaches that typically use atmospheric inversions and bottom-up estimates that rely on process-based or data-driven models or inventories. Both top-down and bottom-up approaches have known strengths and limitations. Atmospheric inversions (e.g., those used in global carbon budgets) produce estimates of NEE that are consistent with the atmospheric CO2 growth rate at regional and global scales but are highly uncertain at smaller scales. Bottom-up data-driven models based on eddy-covariance measurements (e.g., FLUXCOM) match local observations of NEE and their spatial variability but have difficulty in accurately upscaling to a reliable global estimate. In this study, we propose combining the two approaches to produce global NEE estimates, with the goal of capitalizing on each approach's strengths and mitigating their limitations. We do this by constraining the data-driven FLUXCOM model with regional estimates of NEE derived from an ensemble of atmospheric inversions from the Global Carbon Budget 2021. To do this, we need to overcome a series of scientific and technical challenges when combining information about diverse physical variables, which are influenced by different processes at different spatial and temporal scales. We design a modeling structure that optimizes NEE by considering both the model's performance at the in situ level, based on eddy-covariance measurements, and at the level of large regions, based on atmospheric inversion estimates of NEE and their uncertainty. This resulting “dual-constraint” data-driven flux model improves on information based on single constraints (either top down or bottom up), producing robust locally resolved and globally consistent NEE spatio-temporal fields. Compared to reference estimates of the global land sink from the literature, e.g., Global Carbon Budgets, our double-constraint inferred global NEE shows a considerably smaller bias in global and tropical NEE compared to the underlying bottom-up data-driven model estimates (i.e., single constraint). The mean seasonality of our double-constraint inferred global NEE is also more consistent with the Global Carbon Budget and atmospheric inversions. At the same time, our model allows for more robustly spatially resolved NEE. The improved performance of the double-constraint model across spatial and temporal scales demonstrates the potential for adding a top-down constraint to a bottom-up data-driven flux model.

Soft robots are increasingly gaining popularity as a preferred choice for designing medical devices due to their inherently compliant and adaptable nature. As research continues to advance in this field, soft robots are poised to revolutionize healthcare by providing safer, more patient-centric solutions. This paper presents the design of a novel soft corrugated actuator to create a system for positioning the head during head and neck cancer radiation therapy. Simulation and experimental data show that the presented actuator design can achieve linear expansion with respect to pressure in both free and under loading conditions. A machine learning model of the single actuator is created using experimental data (pressure, expansion, and weight) to predict the required pressure. The single actuator model’s validity is confirmed by using four actuators to achieve head flexion at a specific angle, illustrating its potential for implementation in a multi-actuator system. The preliminary design of the multi-actuator head and neck positioning system demonstrates its capability to achieve four degrees of freedom.

Engineering ethics education typically focuses on decisions by individual engineers and case studies of disasters. This does not reflect the everyday decisions that practicing engineers must make, and neglects the fact that most engineers work on teams rather than alone. The focus on safety and disaster prevention leaves little time for discussing pervasive social impacts of engineering and technology. Our research seeks to fill these gaps by determining how ethical decision making occurs in team settings, how it can be influenced by ethics-focused team members, and to what extent a social context influence consideration of social impacts. Over three years, we observed ethics discussions among teams of engineering students. First, we observed undergraduates during their Capstone Design project. We contrasted typical teams and teams with an additional team member trained and educated in engineering ethics. Second, we observed university research laboratory groups composed of undergraduate students, graduate students and postdocs in their spontaneous and regular conversations. Data analysis suggests that engineering students have a narrow understanding of engineering ethics, and that their explicit and implicit understanding can be in conflict. We also observed that an engineering expert can improve the breadth and depth of conversations. We also observe that engineering students rarely--if ever--discuss ethical or social implications of their work during routine activities. This also points to the benefits of facilitated discussions.

The role of Real-Time PCR assays for surveillance and rapid screening for pathogens is garnering more and more attention because of its versatility and ease of adoption. The goal of this study was to design, test, and evaluate Real-Time TaqMan PCR assays for the detection of botulinum neurotoxin (bont/A-G) genes from currently recognized BoNT subtypes. Assays were computationally designed and then laboratory tested for sensitivity and specificity using DNA preparations containing bont genes from 82 target toxin subtypes, including nine bivalent toxin types; 31 strains representing other clostridial species; and an extensive panel that consisted of DNA from a diverse set of prokaryotic (bacterial) and eukaryotic (fungal, protozoan, plant, and animal) species. In addition to laboratory testing, the assays were computationally evaluated using in silico analysis for their ability to detect bont gene sequences from recently identified toxin subtypes. Seventeen specific assays (two for each of the bont/C, bont/D, bont/E, and bont/G subtypes and three for each of the bont/A, bont/B, and bont/F subtypes) were designed and evaluated for their ability to detect bont genes encoding multiple subtypes from all seven serotypes. These assays could provide an additional tool for the detection of botulinum neurotoxins in clinical, environmental and food samples that can complement other existing methods used in clinical diagnostics, regulatory, public health, and research laboratories.

Continuous glucose monitoring (CGM) usage has been shown to improve disease outcomes in people living with diabetes by facilitating better glycemic management. However, previous research has suggested that access to these devices can be influenced by nonmedical factors such as socioeconomic status and ethnicity. It is critical that equitable access to CGM devices is ensured as people from those groups experience poorer diabetes-related health outcomes. In this narrative review, we provide an overview of the various healthcare systems worldwide and how socioeconomic status, social context, and ethnicity shape device usage and the associated health outcomes. In general, we found that having a lower socioeconomic status and belonging to an ethnic minority group negatively impact CGM usage. While financial means proved to be an important mediator in this process, it was not the sole driver as disparities persisted even after adjustment for factors such as income and insurance status. Recommendations to increase CGM usage for people of a lower socioeconomic status and ethnic minorities include increasing the availability of financial, administrative, and educational support, for both patients and healthcare providers. However, recommendations will vary due to local country-specific circumstances, such as reimbursement criteria and healthcare ecosystems.

Abstract Background The food and beverages served in family childcare homes (FCCHs) may play an important role in the development of childhood overweight and obesity. This analysis examines whether children’s diet quality mediates the relationship between foods and beverages served in FCCHs and preschool-aged children’s weight status. Methods Trained and certified staff conducted observations for two days in each FCCH, using the Environment and Policy Assessment and Observation (EPAO) measure to determine the foods and beverages served to children (N = 370) in FCCHs (N = 120). They also used the Dietary Observation in Child Care (DOCC) protocol to assess children’s food and beverage intake during childcare, from which we calculated the Healthy Eating Index-2015 (HEI), a measure of diet quality. Height and weight were measured for each child with parent consent from which the child’s body mass index (BMI) z-scores were calculated. A multilevel mediation analysis was conducted to indicate whether children’s diet quality mediates the relations between food and beverage served in FCCHs and preschool-aged children’s weight status. Results Children’s total HEI scores significantly mediated the relationship between the EPAO subscale Food Provided and children’s BMI z-scores (B=-0.01, p

Introduction. Electrical resistivity is an important material characteristic in the field of electrical engineering and material science. There are several methods that can be used to measure resistance, like the 4-wire method which relates the resistance to a voltage drop at a given current flow, but to define the resistivity from the resistance value requires an analytical expression for the given system which requires a sufficient mathematical apparatus for describing complicated shapes. Therefore we use finite element method computations to compute the resistivity of a metal material. This approach has been already used for different materials like concrete and aluminum in the past. We then compare this method with an analytical expression that due to intuition could approximate the solution sufficiently. After that, the same material is used again to test the electrical isotropy of the sample. Novelty. A method is developed by combining the results of experimental studies and the results of mathematical modelling of the process of determining the electrical conductivity of metals. The goal is to describe and employ a method of measuring the electrical resistivity of metal objects of random shapes. Using this method, it is possible to measure the resistivity of materials without the need to manufacture them into wires or ribbons. Methods. The solution to the problem was carried out by the finite element method via the COMSOL Multiphysics 5.6 simulation program in a cartesian coordinate system and the resistance between two points of the metal sample was measured by the 4-wire method. Results. A similar resistance value was obtained when the measuring terminals were placed in different places. The difference between them was within 1,5 % and the obtained values were close to the values given by the literature for the electrical resistivity of electrical steels. Terminal size influences the measured conductivity and a max error of 5,2 % was estimated. Practical value. A method of estimating the resistivity of materials without the need to manufacture them into specific shapes, like wires or ribbons, for which analytical expressions between resistivity and resistance are easily derived.

Abstract Background The management and care of older patients with multiple health problems is demanding and complex. Interprofessional and intraprofessional collaboration has the potential to improve both the efficiency and the quality of care for these patients. However, it has proven difficult to demonstrate the efficacy of this approach in terms of objective patient-related outcomes. Recently, a care model with interprofessional and intraprofessional care was started, the Intensive Collaboration Ward (ICW). This ward combines interprofessional care and intraprofessional care for older patients with multiple health problems. The aim of this study was to evaluate the effects of ICW care in older patients with multiple health problems. Methods This retrospective cohort study evaluated the effects on patients outcomes. This was done by comparing patients of the new model, the ICW (ICW group), to a historical cohort of comparable patients who would have been eligible for the ICW (control group). Outcomes were medical consultations, allied health professional consultations, radiological procedures, waiting time for radiological procedures, change in primary treating specialty, length of hospital stay, readmission rate, and mortality rate. Linear and logistic regression analyses were performed, adjusted for baseline differences. Results The ICW group required significantly fewer medical consultations than the control group. Calls to specialists from the emergency room decreased significantly, but there was no change in in-person consultations on the ER. 51% of control patients had ≥ 1 in-hospital consultation compared to 21% of ICW patients (p