Parallel detection of multiple biomarkers in a point-of-care-competent device for the prediction of exacerbations in chronic inflammatory lung disease.

Sudden aggravations of chronic inflammatory airway diseases are difficult-to-foresee life-threatening episodes for which advanced prognosis-systems are highly desirable. Here we present an experimental chip-based fluidic system designed for the rapid and sensitive measurement of biomarkers prognostic for potentially imminent asthma or COPD exacerbations. As model biomarkers we chose three cytokines (interleukin-6, interleukin-8, tumor necrosis factor alpha), the bacterial infection marker C-reactive protein and the bacterial pathogen Streptococcus pneumoniae-all relevant factors in exacerbation episodes. Assay protocols established in laboratory environments were adapted to 3D-printed fluidic devices with emphasis on short processing times, low reagent consumption and a low limit of detection in order to enable the fluidic system to be used in point-of-care settings. The final device demonstrator was validated with patient sample material for its capability to detect endogenous as well as exogenous biomarkers in parallel.

The Dual Role of the Airway Epithelium in Asthma: Active Barrier and Regulator of Inflammation.

Chronic airway inflammation is the cornerstone on which bronchial asthma arises, and in turn, chronic inflammation arises from a complex interplay between environmental factors such as allergens and pathogens and immune cells as well as structural cells constituting the airway mucosa. Airway epithelial cells (AECs) are at the center of these processes. On the one hand, they represent the borderline separating the body from its environment in order to keep inner homeostasis. The airway epithelium forms a multi-tiered, self-cleaning barrier that involves an unstirred, discontinuous mucous layer, the dense and rigid mesh of the glycocalyx, and the cellular layer itself, consisting of multiple, densely interconnected cell types. On the other hand, the airway epithelium represents an immunologically highly active tissue once its barrier has been penetrated: AECs play a pivotal role in releasing protective immunoglobulin A. They express a broad spectrum of pattern recognition receptors, enabling them to react to environmental stressors that overcome the mucosal barrier. By releasing alarmins-proinflammatory and regulatory cytokines-AECs play an active role in the formation, strategic orientation, and control of the subsequent defense reaction. Consequently, the airway epithelium is of vital importance to chronic inflammatory diseases, such as asthma.

Determinants of higher education teachers' intention to use technology-based exams.

The replacement of existing technology or the introduction of novel technology into the day-to-day routines of higher education institutions is not a trivial task. Currently, many higher education institutions are faced with the challenge of replacing existing procedures for administering written exams with e-exams. To guide this process, this paper proposes the novel technology-based exams acceptance model (TEAM) and empirically evaluates its model structure and usefulness from the perspective of higher education teachers. The model can be used to guide the transition from paper-based exams to e-exams and the implementation of innovative (e.g., adaptive) e-exam formats. The model includes perceived usefulness, computer self-efficacy, computer anxiety, prior experience, facilitating conditions, and subjective norm as predictors of the behavioral intention to use e-exams. To test the model empirically, the responses of 992 teachers at 63 German universities to a standardized online questionnaire were analyzed using structural equation modeling. The model fit was acceptable. With 77% (conventional e-exams) and 82% (adaptive e-exams), a large proportion of the variance of the intention to use these types of exams was explained. With TEAM, a highly predictive model for explaining the behavioral intention to use e-exams is now available. It offers a theoretical basis that can be used for the successful implementation of e-exams in higher education.

Robustness of the performance of the optimized hierarchical two-parameter logistic IRT model for small-sample item calibration.

Hierarchical Bayesian modeling is beneficial when complex models with many parameters of the same type, such as item response theory (IRT) models, are to be estimated with sparse data. Recently, Koenig et al. (Applied Psychological Measurement, 44, 311-326, 2020) illustrated in an optimized hierarchical Bayesian two-parameter logistic model (OH2PL) how to avoid bias due to unintended shrinkage or degeneracies of the posterior, and how to benefit from this approach in small samples. The generalizability of their findings, however, is limited because they investigated only a single specification of the hyperprior structure. Consequently, in a comprehensive simulation study, we investigated the robustness of the performance of the novel OH2PL in several specifications of their hyperpriors under a broad range of data conditions. We show that the novel OH2PL in the half-Cauchy or Exponential configuration yields unbiased (in terms of bias) model parameter estimates in small samples of N = 50. Moreover, it outperforms (especially in terms of the RMSE of the item discrimination parameters) marginal maximum likelihood (MML) estimation and its nonhierarchical counterpart. This further corroborates the possibility that hierarchical Bayesian IRT models behave differently than general hierarchical Bayesian models. We discuss these results regarding the applicability of complex IRT models in small-scale situations typical in psychological research, and illustrate the extended applicability of the 2PL IRT model with an empirical example.

COVID-19 Pandemic and Student Reading Achievement: Findings From a School Panel Study.

Since 2020, the COVID-19 pandemic had an impact on education worldwide. There is increased discussion of possible negative effects on students' learning outcomes and the need for targeted support. We examined fourth graders' reading achievement based on a school panel study, representative on the student level, with N = 111 elementary schools in Germany (total: N = 4,290 students, age: 9-10 years). The students were tested with the Progress in International Reading Literacy Study instruments in 2016 and 2021. The analysis focused on (1) total average differences in reading achievement between 2016 and 2021, (2) average differences controlling for student composition, and (3) changes in achievement gaps between student subgroups (i.e., immigration background, socio-cultural capital, and gender). The methodological approach met international standards for the analysis of large-scale assessments (i.e., multiple multi-level imputation, plausible values, and clustered mixed-effect regression). The results showed a substantial decline in mean reading achievement. The decline corresponds to one-third of a year of learning, even after controlling for changes in student composition. We found no statistically significant changes of achievement gaps between student subgroups, despite numerical tendencies toward a widening of achievement gaps between students with and without immigration background. It is likely that this sharp achievement decline was related to the COVID-19 pandemic. The findings are discussed in terms of further research needs, practical implications for educating current student cohorts, and educational policy decisions regarding actions in crises such as the COVID-19 pandemic.

How are apprentice satisfaction and concerns changing as a consequence of the coronavirus pandemic?

For more than a year, the coronavirus pandemic has severely restricted everyday life. This has had an impact on the economy, on working life and on the organisation of school routines. Apprentices in dual vocational training have been doubly challenged as they have had to cope with changes both at work and at vocational school. Therefore, it is worthwhile to explore what psychosocial consequences the coronavirus pandemic has had on apprentices. However, little research has been conducted on the impact of the pandemic on the worries and life satisfaction for apprentices in general. This mixed-methods study fills this research gap by using data from 167 apprentices (16-35 years old) in technical and commercial trade apprenticeships in Southern Germany. When designing the survey, particular attention was paid to a visual presentation of Likert scales suitable for adolescents to assess their worries and satisfaction during and prior to the coronavirus pandemic. Explicit questions were asked about their satisfaction with work, social contacts and life in general, as well as their concerns about their financial situation, job loss and health. Furthermore, these aspects are analysed with respect to gender differences based on the assumption that the coronavirus pandemic has a different impact on the satisfaction and worries of women and men. The results show that apprentices' worries significantly increased with their satisfaction decreasing and that women were particularly affected.

Artificial Evolutionary Optimization Process to Improve the Functionality of Cell Penetrating Peptides.

Crossing cellular membranes is a versatile molecular property that allows for a wide variety of peptides with cell penetrating capabilities. This broadness complicates identification of candidates suited best for a specific application. To facilitate the screening of this enormous molecular space in a supervised manner we here present a method to "breed" the desired molecules by applying the rules of Darwinian evolution. With this mate-and-check protocol, which combines an in silico evolution step with an in vitro performance test, cell penetrating peptides that are optimized for a specific task can be achieved in a few rounds of breeding. The procedure is simple and straightforward on the synthetic site but requires robust, highly reproducible and close-to-reality biological assays to yield realistic functional output. With this technology even top-performing peptides can be further improved and functionally adjusted.

Effects of COVID-19-Related School Closures on Student Achievement-A Systematic Review.

The COVID-19 pandemic led to numerous governments deciding to close schools for several weeks in spring 2020. Empirical evidence on the impact of COVID-19-related school closures on academic achievement is only just emerging. The present work aimed to provide a first systematic overview of evidence-based studies on general and differential effects of COVID-19-related school closures in spring 2020 on student achievement in primary and secondary education. Results indicate a negative effect of school closures on student achievement, specifically in younger students and students from families with low socioeconomic status. Moreover, certain measures can be identified that might mitigate these negative effects. The findings are discussed in the context of their possible consequences for national educational policies when facing future school closures.

IgE Epitope Profiling for Allergy Diagnosis and Therapy - Parallel Analysis of a Multitude of Potential Linear Epitopes Using a High Throughput Screening Platform.

Immunoglobulin E (IgE) is pivotal for manifestation and persistence of most immediate-type allergies and some asthma phenotypes. Consequently, IgE represents a crucial target for both, diagnostic purposes as well as therapeutic approaches. In fact, allergen-specific immunotherapy - aiming to re-route an IgE-based inflammatory response into an innocuous immune reaction against the allergen - is the only curative approach for IgE-mediated allergic diseases known so far. However, this requires the cognate allergen to be known. Unfortunately, even in well-characterized allergics or asthmatics, often just a small fraction of total IgE can be assigned to specific target allergens. To overcome this knowledge gap, we have devised an analytical platform for unbiased IgE target epitope detection. The system relies on chemically produced random peptide libraries immobilized on polystyrene beads ("one-bead-one-compound (OBOC) libraries") capable to present millions of different peptide motifs simultaneously to immunoglobulins from biological samples. Beads binding IgE are highlighted with a fluorophore-labeled anti-IgE antibody allowing fluorescence-based detection and isolation of positives, which then can be characterized by peptide sequencing. Setting-up this platform required an elaborate optimization process including proper choice of background suppressants, secondary antibody and fluorophore label as well as incubation conditions. For optimal performance our procedure involves a sophisticated pre-adsorption step to eliminate beads that react nonspecifically with anti-IgE secondary antibodies. This step turned out to be important for minimizing detection of "false positive" motifs that otherwise would erroneously be classified as IgE epitopes. In validation studies we were able to retrieve artificial test-peptide beads spiked into our library by using IgE directed against those test-peptides at physiological concentrations (≤20 IU/ml of specific IgE), and disease-relevant bead-bound epitopes of the major peanut allergen Ara h 2 by screening with sera from peanut allergics. Thus, we established a platform with which one can find and validate new immunoglobulin targets using patient material which displays a largely unknown immunoglobulin repertoire.

An Optimized Bayesian Hierarchical Two-Parameter Logistic Model for Small-Sample Item Calibration.

Accurate item calibration in models of item response theory (IRT) requires rather large samples. For instance, N > 500 respondents are typically recommended for the two-parameter logistic (2PL) model. Hence, this model is considered a large-scale application, and its use in small-sample contexts is limited. Hierarchical Bayesian approaches are frequently proposed to reduce the sample size requirements of the 2PL. This study compared the small-sample performance of an optimized Bayesian hierarchical 2PL (H2PL) model to its standard inverse Wishart specification, its nonhierarchical counterpart, and both unweighted and weighted least squares estimators (ULSMV and WLSMV) in terms of sampling efficiency and accuracy of estimation of the item parameters and their variance components. To alleviate shortcomings of hierarchical models, the optimized H2PL (a) was reparametrized to simplify the sampling process, (b) a strategy was used to separate item parameter covariances and their variance components, and (c) the variance components were given Cauchy and exponential hyperprior distributions. Results show that when combining these elements in the optimized H2PL, accurate item parameter estimates and trait scores are obtained even in sample sizes as small as N = 100 . This indicates that the 2PL can also be applied to smaller sample sizes encountered in practice. The results of this study are discussed in the context of a recently proposed multiple imputation method to account for item calibration error in trait estimation.

More Than Just a Barrier: The Immune Functions of the Airway Epithelium in Asthma Pathogenesis.

Allergic bronchial asthma is a chronic disease of the airways that is characterized by symptoms like respiratory distress, chest tightness, wheezing, productive cough, and acute episodes of broncho-obstruction. This symptom-complex arises on the basis of chronic allergic inflammation of the airway wall. Consequently, the airway epithelium is central to the pathogenesis of this disease, because its multiple abilities directly have an impact on the inflammatory response and thus the formation of the disease. In turn, its structure and functions are markedly impaired by the inflammation. Hence, the airway epithelium represents a sealed, self-cleaning barrier, that prohibits penetration of inhaled allergens, pathogens, and other noxious agents into the body. This barrier is covered with mucus that further contains antimicrobial peptides and antibodies that are either produced or specifically transported by the airway epithelium in order to trap these particles and to remove them from the body by a process called mucociliary clearance. Once this first line of defense of the lung is overcome, airway epithelial cells are the first cells to get in contact with pathogens, to be damaged or infected. Therefore, these cells release a plethora of chemokines and cytokines that not only induce an acute inflammatory reaction but also have an impact on the alignment of the following immune reaction. In case of asthma, all these functions are impaired by the already existing allergic immune response that per se weakens the barrier integrity and self-cleaning abilities of the airway epithelium making it more vulnerable to penetration of allergens as well as of infection by bacteria and viruses. Recent studies indicate that the history of allergy- and pathogen-derived insults can leave some kind of memory in these cells that can be described as imprinting or trained immunity. Thus, the airway epithelium is in the center of processes that lead to formation, progression and acute exacerbation of asthma.

Polyethylene glycol-conjugated alkylamines - A novel class of surfactants for the saturation of immunoassay solid phase surfaces.

All solid-phase immunoassay techniques depend on so-called blocking reagents to suppress the background that is caused by unwanted adhesion of assay system components to the solid support. Commonly used blocking reagents based on biological materials bear severe inherent drawbacks such as heterogeneity and cross-reactivity, while synthetic alternatives often show insufficient background prevention. In this study, polyethylene glycol-conjugated alkylamines were synthesized via a versatile building block approach and were studied as novel blocking reagent candidates in immunoassays. The newly developed substances outperformed commonly used blocking reagents in two different ELISA setups, enabling both, excellent prevention of non-specific binding and particularly high assay sensitivity. This class of surfactants therefore may contribute significantly to the field of assay technology.

Evaluating Different Equating Setups in the Continuous Item Pool Calibration for Computerized Adaptive Testing.

The increasing digitalization in the field of psychological and educational testing opens up new opportunities to innovate assessments in many respects (e.g., new item formats, flexible test assembly, efficient data handling). In particular, computerized adaptive testing provides the opportunity to make tests more individualized and more efficient. The newly developed continuous calibration strategy (CCS) from Fink et al. (2018) makes it possible to construct computerized adaptive tests in application areas where separate calibration studies are not feasible. Due to the goal of reporting on a common metric across test cycles, the equating is crucial for the CCS. The quality of the equating depends on the common items selected and the scale transformation method applied. Given the novelty of the CCS, the aim of the study was to evaluate different equating setups in the CCS and to derive practical recommendations. The impact of different equating setups on the precision of item parameter estimates and on the quality of the equating was examined in a Monte Carlo simulation, based on a fully crossed design with the factors common item difficulty distribution (bimodal, normal, uniform), scale transformation method (mean/mean, mean/sigma, Haebara, Stocking-Lord), and sample size per test cycle (50, 100, 300). The quality of the equating was operationalized by three criteria (proportion of feasible equatings, proportion of drifted items, and error of transformation constants). The precision of the item parameter estimates increased with increasing sample size per test cycle, but no substantial difference was found with respect to the common item difficulty distribution and the scale transformation method. With regard to the feasibility of the equatings, no differences were found for the different scale transformation methods. However, when using the moment methods (mean/mean, mean/sigma), quite extreme levels of error for the transformation constants A and B occurred. Among the characteristic curve method the performance of the Stocking-Lord method was slightly better than for the Haebara method. Thus, while no clear recommendation can be made with regard to the common item difficulty distribution, the characteristic curve methods turned out to be the most favorable scale transformation methods within the CCS.

Modeling Multiple Item Context Effects With Generalized Linear Mixed Models.

Item context effects refer to the impact of features of a test on an examinee's item responses. These effects cannot be explained by the abilities measured by the test. Investigations typically focus on only a single type of item context effects, such as item position effects, or mode effects, thereby ignoring the fact that different item context effects might operate simultaneously. In this study, two different types of context effects were modeled simultaneously drawing on data from an item calibration study of a multidimensional computerized test (N = 1,632) assessing student competencies in mathematics, science, and reading. We present a generalized linear mixed model (GLMM) parameterization of the multidimensional Rasch model including item position effects (distinguishing between within-block position effects and block position effects), domain order effects, and the interactions between them. Results show that both types of context effects played a role, and that the moderating effect of domain orders was very strong. The findings have direct consequences for planning and applying mixed domain assessment designs.

Breeding Cell Penetrating Peptides: Optimization of Cellular Uptake by a Function-Driven Evolutionary Process.

In nature, building block-based biopolymers can adapt to functional and environmental demands by recombination and mutation of the monomer sequence. We present here an analogous, artificial evolutionary optimization process which we have applied to improve the functionality of cell-penetrating peptide molecules. The "evolution" consisted of repeated rounds of in silico peptide sequence alterations using a genetic algorithm followed by in vitro peptide synthesis, experimental analysis, and ranking according to their "fitness" (i.e., their ability to carry the cargo carboxyfluorescein into cultured cells). The genetic algorithm-based optimization method was customized and adapted from former successful applications in the lab to realize an early convergence and a minimum number of in vitro and in silico processing steps by configured settings derived from empirical in silico simulation. We started out with 20 "lead peptides" which we had previously identified as top performers regarding their ability to enter cultured cells. Ten breeding rounds comprising 240 peptides each yielded a peptide population of which the top 10 candidates displayed a 6-fold (median values) increase in its cell-penetration capability compared with the top 10 lead peptides, and two consensus sequences emerged which represent local fitness optima. In addition, the cell-penetrating potential could be proven independently of the carboxyfluorescein cargo in an alternative setting. Our results demonstrate that we have established a powerful optimization technology that can be used to further improve peptides with known functionality and adapt them to specific applications.

Scaling properties of pain intensity ratings in paediatric populations using the Faces Pain Scale-revised: Secondary analyses of published data based on the item response theory.

BACKGROUND: The Faces Pain Scale-revised (FPS-r) has been developed as an interval scale. For other pain measurement instruments, several studies found evidence for and against an interval level of measurement. OBJECTIVES: The primary aim of the current study was to evaluate the scale properties of the FPS-r using an item response theory approach. DESIGN: Secondary analysis of published data. SETTING: Three studies; Study 1 and study 2: One university hospital; Study 3: international pain registry. PARTICIPANTS: Study 1: n = 246, female: 41%, age: 11-18 years, 3 pain items; Study 2: n = 240, female: 43%, age: 11-18 years, 9 pain items; Study 3: n = 2266, female: 41%, age: 4-18 years, 3 pain items. METHODS: The rating scale model (interval scale), the graded response model (no interval scale, ordered response categories) and the partial credit model (no interval scale) were used to scale the data. RESULTS: In all three studies, the rating scale model was outperformed by the graded response model or the partial credit model in terms of model fit. Overlapping response categories were found in items associated with less pain. Response category widths were wider for categories associated with low pain intensity and smaller for categories associated with high pain intensities. Smallest response categories were 1%-67% smaller compared to the widest response category of the same item. CONCLUSION: According to these findings, the interval scale properties of the FPS-r may be questioned. Item response theory methods may help to solve the problem of missing linearity in pain intensity ratings using FPS-r.

Cell penetrating peptides: a comparative transport analysis for 474 sequence motifs.

Delivering reagents into cells is a key demand in molecular medicine. The vehicle of choice is often cell penetrating peptides (CPPs), which can ferry conjugated cargo across membranes. Although numerous peptides have been shown to promote such uptake events, there has been no comprehensive comparison of individual performance under standardized conditions. We have devised a method to rapidly analyze the ability of a multitude of CPP conjugates to carry a model cargo into HeLa cells. Sequence information for 474 CPPs was collected from literature sources, and the respective peptides were synthesized and modified with carboxyfluorescein (FAM) as model cargo. All candidates were evaluated in an identical uptake test, and transport was quantified using cellular fluorescence intensities. Substantial differences in the ability to carry the fluorophore into the cells were observed, with transport performance differing by a factor of 70 between the best CPP investigated and cargo alone. Strong correlations were observed between uptake efficiency and both sequence length and the presence of positive net charge. A compilation of the 20 top performers with regard to cargo delivery performance and cell compatibility is provided.