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To date, reports of reading interventions for students at risk for emotional/behavioral disorders (E/BD) that have been published in refereed journals have involved sustained support by university or school-site personnel. This study examined the efficacy and feasibility of a reading intervention that 2 general education teachers implemented in inclusive settings to support 7 first-grade students at risk for E/BD and reading difficulties. Results of a multiple baseline design revealed lasting improvements in reading fluency for all students, accompanied by decreases in variability of academic engagement for 4 students. Although intervention goals, procedures, and outcomes exceeded teacher expectations, social validity ratings for some students declined between the onset and the conclusion of the intervention. This article presents limitations, future directions, and educational implications., Educators have long recognized that students with emotional/ behavioral disorders (E/BD) and those who are at risk for such problems have social and behavioral patterns that impede instruction. For example, [...]

BackgroundWearable sensors have been used successfully to characterize bradykinetic gait in patients with Parkinson disease (PD), but most studies to date have been conducted in highly controlled laboratory environments. ObjectiveThis paper aims to assess whether sensor-based analysis of real-life gait can be used to objectively and remotely monitor motor fluctuations in PD. MethodsThe Parkinson@Home validation study provides a new reference data set for the development of digital biomarkers to monitor persons with PD in daily life. Specifically, a group of 25 patients with PD with motor fluctuations and 25 age-matched controls performed unscripted daily activities in and around their homes for at least one hour while being recorded on video. Patients with PD did this twice: once after overnight withdrawal of dopaminergic medication and again 1 hour after medication intake. Participants wore sensors on both wrists and ankles, on the lower back, and in the front pants pocket, capturing movement and contextual data. Gait segments of 25 seconds were extracted from accelerometer signals based on manual video annotations. The power spectral density of each segment and device was estimated using Welch’s method, from which the total power in the 0.5- to 10-Hz band, width of the dominant frequency, and cadence were derived. The ability to discriminate between before and after medication intake and between patients with PD and controls was evaluated using leave-one-subject-out nested cross-validation. ResultsFrom 18 patients with PD (11 men; median age 65 years) and 24 controls (13 men; median age 68 years), ≥10 gait segments were available. Using logistic LASSO (least absolute shrinkage and selection operator) regression, we classified whether the unscripted gait segments occurred before or after medication intake, with mean area under the receiver operator curves (AUCs) varying between 0.70 (ankle of least affected side, 95% CI 0.60-0.81) and 0.82 (ankle of most affected side, 95% CI 0.72-0.92) across sensor locations. Combining all sensor locations did not significantly improve classification (AUC 0.84, 95% CI 0.75-0.93). Of all signal properties, the total power in the 0.5- to 10-Hz band was most responsive to dopaminergic medication. Discriminating between patients with PD and controls was generally more difficult (AUC of all sensor locations combined: 0.76, 95% CI 0.62-0.90). The video recordings revealed that the positioning of the hands during real-life gait had a substantial impact on the power spectral density of both the wrist and pants pocket sensor. ConclusionsWe present a new video-referenced data set that includes unscripted activities in and around the participants’ homes. Using this data set, we show the feasibility of using sensor-based analysis of real-life gait to monitor motor fluctuations with a single sensor location. Future work may assess the value of contextual sensors to control for real-world confounders.

Twenty-two Bachelor of Science in Nursing (BSN) graduates shared their perceptions one year after graduation on two practice education models they experienced during years three and four of their nursing education. The two models evaluated were collaborative learning units (CLU) and preceptorship. The participants described what was most important about each of these models in preparing them for graduate practice. While the preceptorship model has been researched for decades, the CLU data are previously unexplored information. The CLU data revealed the themes of working with many and making practice their own, while the themes of working with one and consolidation of nursing practice emerged from the preceptorship data. The participants suggest that both models offer different yet complementary paths for learning and enhanced professional development and practice. There is also confirmation that both are relevant and perhaps necessary to accomplish the complexities of preparing students for professional nursing practice. [ABSTRACT FROM AUTHOR]

Most nurse educators fulfill dual roles of clinical practitioner and teacher and thus have to achieve a balance between these two challenging sets of competencies. The authors discuss the obligation and expectation that nurse educators are concurrently experts in clinical practice and education. Is this dual competence a feasible and sustainable goal? To begin to explore this issue, the meanings of 'expert practice' and 'practice competence,' derived from the nursing education literature, are reviewed. Current professional practice competency requirements related to the nurse educator role are discussed. Questions are raised regarding support for and barriers to achieving these competencies. The potential challenges and rewards of this endeavour are presented and illustrated by two nurse educators who share their stories of achieving a balance in teaching and clinical practice competence. Finally, implications for nurse educators and directions for future research into this issue are proposed. [ABSTRACT FROM AUTHOR]

BackgroundParkinson’s disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. ObjectiveTo assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson’s Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. MethodsOnline self-reported data was validated against the gold standard Parkinson’s Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom severity. The average magnitude of fluctuations versus time since diagnosis was modeled by using a gamma generalized linear model. ResultsDistributions of ages at diagnosis and UPDRS in the PLM and PD-DOC databases were broadly consistent. The PLM patients were systematically younger than the PD-DOC patients and showed increased symptom severity in the PD off state. The average fluctuation in symptoms (UPDRS Parts I and II) was 2.6 points at the time of diagnosis, rising to 5.9 points 16 years after diagnosis. This fluctuation exceeds the estimated minimal and moderate clinically important differences, respectively. Not all patients conformed to the current clinical picture of gradual, smooth changes: many patients had regimes where symptom severity varied in an unpredictable manner, or underwent large rapid changes in an otherwise more stable progression. ConclusionsThis information about short-term PD symptom dynamics contributes new scientific understanding about the disease progression, currently very costly to obtain without self-administered Internet-based reporting. This understanding should have implications for the optimization of clinical trials into new treatments and for the choice of treatment decision timescales.

The incorporation of photoresponsive groups into porous materials is attractive as it offers potential advantages in controlling the pore size and selectivity to guest molecules. A combination of computational modeling and experiment resulted in the synthesis of two azobenzene-derived organic cages based on building blocks identified in a computational screen. Both cages incorporate three azobenzene moieties, and are therefore capable of 3-fold isomerization, using either ditopic or tetratopic aldehydes containing diazene functionality. The ditopic aldehyde forms a Tri 2 Di 3 cage via a 6-fold imine condensation and the tritopic aldehyde forms a Tet 3 Di 6 cage via a 12-fold imine condensation. The relative energies and corresponding intrinsic cavities of each isomeric state were computed, and the photoswitching behavior of both cages was studied by UV-Vis and 1 H NMR spectroscopy, including a detailed kinetic analysis of the thermal isomerization for each of the EEZ , EZZ and ZZZ metastable isomers of the Tet 3 Di 6 cage. Both cages underwent photoisomerization, where a photostationary state of up to 77% of the cis -isomer and overall thermal half-life of 110 h was identified for the Tet 3 Di 6 species. Overall, this work demonstrates the potential of computational modeling to inform the design of photoresponsive materials and highlights the contrasting effects on the photoswitching properties of the azobenzene moieties on incorporation into the different cage species.

Background: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis is a heterogenous autoimmune disease. While traditionally stratified into two conditions, granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA), the subclassification of ANCA-associated vasculitis is subject to continued debate. Here we aim to identify phenotypically distinct subgroups and develop a data-driven subclassification of ANCA-associated vasculitis, using a large real-world dataset., Methods: In the collaborative data reuse project FAIRVASC (Findable, Accessible, Interoperable, Reusable, Vasculitis), registry records of patients with ANCA-associated vasculitis were retrieved from six European vasculitis registries: the Czech Registry of ANCA-associated vasculitis (Czech Republic), the French Vasculitis Study Group Registry (FVSG; France), the Joint Vasculitis Registry in German-speaking Countries (GeVas; Germany), the Polish Vasculitis Registry (POLVAS; Poland), the Irish Rare Kidney Disease Registry (RKD; Ireland), and the Skåne Vasculitis Cohort (Sweden). We performed model-based clustering of 17 mixed-type clinical variables using a parsimonious mixture of two latent Gaussian variable models. Clinical validation of the optimal cluster solution was made through summary statistics of the clusters' demography, phenotypic and serological characteristics, and outcome. The predictive value of models featuring the cluster affiliations were compared with classifications based on clinical diagnosis and ANCA specificity. People with lived experience were involved throughout the FAIRVASVC project., Findings: A total of 3868 patients diagnosed with ANCA-associated vasculitis between Nov 1, 1966, and March 1, 2023, were included in the study across the six registries (Czech Registry n=371, FVSG n=1780, GeVas n=135, POLVAS n=792, RKD n=439, and Skåne Vasculitis Cohort n=351). There were 2434 (62·9%) patients with GPA and 1434 (37·1%) with MPA. Mean age at diagnosis was 57·2 years (SD 16·4); 2006 (51·9%) of 3867 patients were men and 1861 (48·1%) were women. We identified five clusters, with distinct phenotype, biochemical presentation, and disease outcome. Three clusters were characterised by kidney involvement: one severe kidney cluster (555 [14·3%] of 3868 patients) with high C-reactive protein (CRP) and serum creatinine concentrations, and variable ANCA specificity (SK cluster); one myeloperoxidase (MPO)-ANCA-positive kidney involvement cluster (782 [20·2%]) with limited extrarenal disease (MPO-K cluster); and one proteinase 3 (PR3)-ANCA-positive kidney involvement cluster (683 [17·7%]) with widespread extrarenal disease (PR3-K cluster). Two clusters were characterised by relative absence of kidney involvement: one was a predominantly PR3-ANCA-positive cluster (1202 [31·1%]) with inflammatory multisystem disease (IMS cluster), and one was a cluster (646 [16·7%]) with predominantly ear-nose-throat involvement and low CRP, with mainly younger patients (YR cluster). Compared with models fitted with clinical diagnosis or ANCA status, cluster-assigned models demonstrated improved predictive power with respect to both patient and kidney survival., Interpretation: Our study reinforces the view that ANCA-associated vasculitis is not merely a binary construct. Data-driven subclassification of ANCA-associated vasculitis exhibits higher predictive value than current approaches for key outcomes., Funding: European Union's Horizon 2020 research and innovation programme under the European Joint Programme on Rare Diseases., Competing Interests: Declaration of interests PL has received grants or contracts from the German Research Society, Federal Ministry of Education and Research, German Society for Rheumatology, John Grube Foundation, and Vifor Pharma; consulting fees from AbbVie, AstraZeneca, GSK, Novartis, UCB, and Vifor Pharma; payment or honoraria for lectures, presentations, speakers, bureaus, manuscript writing, or educational events from AstraZeneca, Boehringer Ingelheim, GSK, Janssen, Novartis, Rheumaakademie, UCB, and Vifor Pharma; support for attending meetings or travel from Vifor Pharma; and has participated on Data Safety Monitoring Boards or Advisory Boards of AbbVie, AstraZeneca, GSK, and Vifor Pharma. XP has received grants as an investigator of academic studies of ANCA-associated vasculitis for which rituximab was provided by Roche Pharma. MS has received consulting fees from Vifor Pharma, Otsuka, and Hansa Biopharma. BT has received consulting fees from Novartis, AstraZeneca, CSL Vifor, GSK, and Boehringer Ingelheim; payment or honoraria for lectures, presentations, speakers, bureaus, manuscript writing, or educational events from Novartis, AstraZeneca, CSL Vifor, GSK, and Boehringer Ingelheim; support for attending meetings or travel from GSK, AstraZeneca, and Novartis; and participates on the Advisory Board for Amgen. KW is a member of the Advisory Board at CSL Vifor. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Introduction: High rates of tobacco use persist in the U.S. military, with 18.4% of service members smoking cigarettes in 2018. The Department of Defense's (DoD) 2017 policy required that tobacco retailers on military installations set tobacco product prices equal to the most common community price, including tax, but there is limited evidence confirming whether local retailers are adhering to this policy. We examined tobacco product pricing in tobacco retailers on- and off-post at the largest U.S. Army installation, Fort Liberty, and Cumberland County, North Carolina., Aims and Methods: Between June and August 2021, we collected data on tobacco product availability, price, and promotions from retailers on Fort Liberty (n = 14) and a random sample of off-post retailers within 10 miles of installation gates (n = 52). We calculated the mode, mean, and median price of each product, plus the difference in these prices at on- and off-post retailers. We used Welch's t-test to test differences in mean prices between on- versus off-post retailers., Results: The mode, mean, and median prices of cigarette packs and cartons were lower on-post than off-post (eg, $0.51-$0.55 cheaper for Marlboro cigarette packs on-post). However, the mode, mean, and median prices of smokeless tobacco products and little cigars were higher on-post than off-post (eg, $0.82-$0.89 more costly for Swisher Sweets 2-packs on-post)., Conclusions: Results highlight the need for continued enforcement to ensure compliance with the 2017 DoD policy. Comprehensive policy action to reduce tobacco price disparities on- and off-post is critical to reducing high rates of tobacco use among service members., Implications: Despite the implementation of the 2017 DoD pricing policy, some tobacco products remain cheaper at tobacco retailers on-post compared to off-post retailers. Our results highlight the need for greater routine surveillance to increase implementation of the policy-particularly for cigarettes-to reduce high rates of tobacco use among service members., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Objective: Identification of those at high and low risk of disease relapse is a major unmet need in the management of patients with ANCA-associated vasculitis (AAV). Precise stratification would allow tailoring of immunosuppressive medication. We profiled the autoantibody repertoire of AAV patients in remission to identify novel autoantibodies associated with relapse risk., Methods: Plasma samples collected from 246 AAV patients in remission were screened for novel autoantibodies using in-house generated protein arrays including 42 000 protein fragments representing 18 000 unique human proteins. Patients were categorized based on the occurrence and frequency of relapses. We modelled the association between these antibodies and relapse occurrence using descriptive and high dimensional regression approaches., Results: We observed nine autoantibodies at higher frequency in samples from AAV patients experiencing multiple relapses compared with patients in long-term remission off therapy (LTROT). LASSO analysis identified six autoantibodies that exhibited an association with relapse occurrence after sample collection. Antibodies targeting HFE and SYT5 were identified as associated with relapse in both analyses., Conclusion: Through a broad protein array-based autoantibody screening, we identified two novel autoantibodies directed against HFE and SYT5 as candidate biomarkers of relapse in AAV., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Environmental factors amplified by climate change contribute significantly to the global burden of disease, disproportionately impacting vulnerable populations, such as individuals with rare diseases. Researchers require innovative, dynamic data linkage methods to enable the development of risk prediction models, particularly for diseases like vasculitis with unknown aetiology but potential environmental triggers. In response, we present the Semantic Environmental and Rare Disease Data Integration Framework (SERDIF). SERDIF was evaluated with researchers studying climate-related health hazards of vasculitis disease activity across European countries (N P1  = 10, N P2  = 17, N P3  = 23). Usability metrics consistently improved, indicating SERDIF's effectiveness in linking complex environmental and health datasets. Furthermore, SERDIF-enabled epidemiologists to study environmental factors in a pregnancy cohort in Lombardy, showcasing its versatility beyond rare diseases. This framework offers for the first time a user-friendly, FAIR-compliant design for environment-health data linkage with export capabilities enabling data analysis to mitigate health risks posed by climate change., (© 2024. The Author(s).)

Objective: Pulmonary infection is one of the leading causes of death in patients with ANCA-associated vasculitis (AAV). It is sometimes difficult to differentiate pulmonary infection from pulmonary involvement of vasculitis in AAV patients. Fiberoptic bronchoscopy and bronchoalveolar lavage fluid (BALF) assays are useful diagnostic methods. In addition to conventional microbiological tests (CMTs), metagenomic next-generation sequencing (mNGS) facilitates rapid and sensitive detection of various pathogens. The current study aimed to evaluate the advantages of additional BALF mNGS in the management of pulmonary infection in AAV patients., Methods: 27 patients with active AAV and suspected pulmonary infection whose BALF samples were tested by mNGS and CMTs and 17 active AAV patients whose BALF were tested by CMTs alone were retrospectively recruited. The results of microbiological tests, and adjustments of treatment following BALF mNGS, were described. The durations of antimicrobial treatment and in-hospital mortality in patients were compared., Results: Among the 27 patients whose BALF samples were tested by mNGS, 25.9% of patients did not have evidence of pathogenic microorganism in their BALF samples, 55.6% had polymicrobial infections, including bacteria, fungi and viruses. Of these 27 patients, 40.7% did not have evidence of pathogenic microorganism in their BALF or serum samples according to CMTs. Patients in the BALF mNGS/CMT group received a significantly shorter duration of antibacterial and total antimicrobial treatment than patients in the CMT alone group (17.3 ± 14.7 vs. 27.9 ± 19.0 days, P = 0.044; 18.9 ± 15.0 vs. 29.5 ± 17.7 days, P = 0.040, respectively). Fewer patients in the BALF mNGS/CMT group died than in the CMT alone group (4/27 vs. 7/17, P = 0.049)., Conclusion: Compared with CMT alone, additional mNGS tests may shorten the duration of antimicrobial treatment and possibly decrease death from severe infection by providing precise and quick diagnosis of infection., (© 2024. The Author(s).)

Neutrophilia occurs in patients infected with SARS-CoV-2 (COVID-19) and is predictive of poor outcomes. Here, we link heterogenous neutrophil populations to disease severity in COVID-19. We identified neutrophils with features of cellular aging and immunosuppressive capacity in mild COVID-19 and features of neutrophil immaturity and activation in severe disease. The low-density neutrophil (LDN) number in circulating blood correlated with COVID-19 severity. Many of the divergent neutrophil phenotypes in COVID-19 were overrepresented in the LDN fraction and were less detectable in normal-density neutrophils. Functionally, neutrophils from patients with severe COVID-19 displayed defects in neutrophil extracellular trap formation and reactive oxygen species production. Soluble factors secreted by neutrophils from these patients inhibited T cell proliferation. Neutrophils from patients with severe COVID-19 had increased expression of arginase-1 protein, a feature that was retained in convalescent patients. Despite this increase in intracellular expression, there was a reduction in arginase-1 release by neutrophils into serum and culture supernatants. Furthermore, neutrophil-mediated T cell suppression was independent of arginase-1. Our results indicate the presence of dysfunctional, activated, and immature neutrophils in severe COVID-19.