Combined germline and somatic human FADD mutations cause autoimmune lymphoproliferative syndrome.

BACKGROUND: The autoimmune lymphoproliferative syndrome (ALPS) is a noninfectious and nonmalignant lymphoproliferative disease frequently associated with autoimmune cytopenia resulting from defective FAS signaling. We previously described germline monoallelic FAS (TNFRSF6) haploinsufficient mutations associated with somatic events, such as loss of heterozygosity on the second allele of FAS, as a cause of ALPS-FAS. These somatic events were identified by sequencing FAS in DNA from double-negative (DN) T cells, the pathognomonic T-cell subset in ALPS, in which the somatic events accumulated. OBJECTIVE: We sought to identify whether a somatic event affecting the FAS-associated death domain (FADD) gene could be related to the disease onset in 4 unrelated patients with ALPS carrying a germline monoallelic mutation of the FADD protein inherited from a healthy parent. METHODS: We sequenced FADD and performed array-based comparative genomic hybridization using DNA from sorted CD4+ or DN T cells. RESULTS: We found homozygous FADD mutations in the DN T cells from all 4 patients, which resulted from uniparental disomy. FADD deficiency caused by germline heterozygous FADD mutations associated with a somatic loss of heterozygosity was a phenocopy of ALPS-FAS without the more complex symptoms reported in patients with germline biallelic FADD mutations. CONCLUSIONS: The association of germline and somatic events affecting the FADD gene is a new genetic cause of ALPS.

Abnormal biomarkers predict complex FAS or FADD defects missed by exome sequencing.

BACKGROUND: Elevated TCRαß+CD4-CD8- double-negative T cells (DNT) and serum biomarkers help identify FAS mutant patients with autoimmune lymphoproliferative syndrome (ALPS). However, in some patients with clinical features and biomarkers consistent with ALPS, germline or somatic FAS mutations cannot be identified on standard exon sequencing (ALPS-undetermined: ALPS-U). OBJECTIVE: We sought to explore whether complex genetic alterations in the FAS gene escaping standard sequencing or mutations in other FAS pathway-related genes could explain these cases. METHODS: Genetic analysis included whole FAS gene sequencing, copy number variation analysis, and sequencing of FAS cDNA and other FAS pathway-related genes. It was guided by FAS expression analysis on CD57+DNT, which can predict somatic loss of heterozygosity (sLOH). RESULTS: Nine of 16 patients with ALPS-U lacked FAS expression on CD57+DNT predicting heterozygous "loss-of-expression" FAS mutations plus acquired somatic second hits in the FAS gene, enriched in DNT. Indeed, 7 of 9 analyzed patients carried deep intronic mutations or large deletions in the FAS gene combined with sLOH detectable in DNT; 1 patient showed a FAS exon duplication. Three patients had reduced FAS expression, and 2 of them harbored mutations in the FAS promoter, which reduced FAS expression in reporter assays. Three of the 4 ALPS-U patients with normal FAS expression carried heterozygous FADD mutations with sLOH. CONCLUSION: A combination of serum biomarkers and DNT phenotyping is an accurate means to identify patients with ALPS who are missed by routine exome sequencing.

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.

OxyR-dependent formation of DNA methylation patterns in OpvABOFF and OpvABON cell lineages of Salmonella enterica.

Phase variation of the Salmonella enterica opvAB operon generates a bacterial lineage with standard lipopolysaccharide structure (OpvAB(OFF)) and a lineage with shorter O-antigen chains (OpvAB(ON)). Regulation of OpvAB lineage formation is transcriptional, and is controlled by the LysR-type factor OxyR and by DNA adenine methylation. The opvAB regulatory region contains four sites for OxyR binding (OBSA-D), and four methylatable GATC motifs (GATC1-4). OpvAB(OFF) and OpvAB(ON) cell lineages display opposite DNA methylation patterns in the opvAB regulatory region: (i) in the OpvAB(OFF) state, GATC1 and GATC3 are non-methylated, whereas GATC2 and GATC4 are methylated; (ii) in the OpvAB(ON) state, GATC2 and GATC4 are non-methylated, whereas GATC1 and GATC3 are methylated. We provide evidence that such DNA methylation patterns are generated by OxyR binding. The higher stability of the OpvAB(OFF) lineage may be caused by binding of OxyR to sites that are identical to the consensus (OBSA and OBSc), while the sites bound by OxyR in OpvAB(ON) cells (OBSB and OBSD) are not. In support of this view, amelioration of either OBSB or OBSD locks the system in the ON state. We also show that the GATC-binding protein SeqA and the nucleoid protein HU are ancillary factors in opvAB control.

Quantification and identification of aerobic bacteria in holy water samples from a German environment.

Despite its frequent use in many religious institutions, the microbiological quality of holy water is clearly underinvestigated. We analyzed the microbial load of 54 holy water samples, repeatedly taken in five Roman Catholic churches in the greater area of Villingen-Schwenningen, Germany, by means of aerobic colony counting and Matrix-Assisted Laser Desorption/Ionization (MALDI) Biotyping of representative isolates. Over all samples, colony counting indicated an average aerobic microbial load of 5.85 ± 3.98 × 103 colony forming units (CFU) ml-1 (average ± standard error of the mean (SEM)). Urban churches showed significantly higher contaminations than rural churches, probably owing to a greater number of visitors. Out of 145 bacterial isolates, 63 (43%) were identified to genus level and 39 (27%) to species level. The majority of the identified bacteria were typical human skin commensals, mainly affiliated with the genus Staphylococcus. Ten out of 20 (50%) of the identified species were classified as potential pathogens. Appropriate hygiene measures should be taken to control microbial contamination of holy water, e.g., regular water exchange, particularly in highly frequented churches.

The complex methylome of the human gastric pathogen Helicobacter pylori.

The genome of Helicobacter pylori is remarkable for its large number of restriction-modification (R-M) systems, and strain-specific diversity in R-M systems has been suggested to limit natural transformation, the major driving force of genetic diversification in H. pylori. We have determined the comprehensive methylomes of two H. pylori strains at single base resolution, using Single Molecule Real-Time (SMRT®) sequencing. For strains 26695 and J99-R3, 17 and 22 methylated sequence motifs were identified, respectively. For most motifs, almost all sites occurring in the genome were detected as methylated. Twelve novel methylation patterns corresponding to nine recognition sequences were detected (26695, 3; J99-R3, 6). Functional inactivation, correction of frameshifts as well as cloning and expression of candidate methyltransferases (MTases) permitted not only the functional characterization of multiple, yet undescribed, MTases, but also revealed novel features of both Type I and Type II R-M systems, including frameshift-mediated changes of sequence specificity and the interaction of one MTase with two alternative specificity subunits resulting in different methylation patterns. The methylomes of these well-characterized H. pylori strains will provide a valuable resource for future studies investigating the role of H. pylori R-M systems in limiting transformation as well as in gene regulation and host interaction.

Methodological aspects of the highly adaptive testing design for PISA.

This methods paper describes the methodological and statistical underpinnings of the highly adaptive testing design (HAT), which was developed for the Programme for International Student Assessment (PISA). The aim of HAT is to allow for a maximum of adaptivity in selecting items while taking the constraints of PISA into account with appropriate computer algorithms. HAT combines established methods from the area of computerized adaptive testing (a) to improve item selection when items are nested in units, (b) to make use of the correlation between the dimensions measured, (c) to efficiently accomplish constraint management, (d) to control for item position effects, and (e) to foster students' test-taking experience. The algorithm is implemented using the programming language R and readers are provided with the necessary code. This should facilitate future implementations of the HAT design and inspire other adaptive testing designs that aim to maximize adaptivity while meeting constraints.

Benefits of the Curious Behavior of Bayesian Hierarchical Item Response Theory Models-An in-Depth Investigation and Bias Correction.

When using Bayesian hierarchical modeling, a popular approach for Item Response Theory (IRT) models, researchers typically face a tradeoff between the precision and accuracy of the item parameter estimates. Given the pooling principle and variance-dependent shrinkage, the expected behavior of Bayesian hierarchical IRT models is to deliver more precise but biased item parameter estimates, compared to those obtained in nonhierarchical models. Previous research, however, points out the possibility that, in the context of the two-parameter logistic IRT model, the aforementioned tradeoff has not to be made. With a comprehensive simulation study, we provide an in-depth investigation into this possibility. The results show a superior performance, in terms of bias, RMSE and precision, of the hierarchical specifications compared to the nonhierarchical counterpart. Under certain conditions, the bias in the item parameter estimates is independent of the bias in the variance components. Moreover, we provide a bias correction procedure for item discrimination parameter estimates. In sum, we show that IRT models create a unique situation where the Bayesian hierarchical approach indeed yields parameter estimates that are not only more precise, but also more accurate, compared to nonhierarchical approaches. We discuss this beneficial behavior from both theoretical and applied point of views.

Single-cell transcriptomics reveal different maturation stages and sublineage commitment of human thymic invariant natural killer T cells.

Invariant natural killer T cells are a rare, heterogeneous T-cell subset with cytotoxic and immunomodulatory properties. During thymic development, murine invariant natural killer T cells go through different maturation stages differentiating into distinct sublineages, namely, invariant natural killer T1, 2, and 17 cells. Recent reports indicate that invariant natural killer T2 cells display immature properties and give rise to other subsets, whereas invariant natural killer T1 cells seem to be terminally differentiated. Whether human invariant natural killer T cells follow a similar differentiation model is still unknown. To define the maturation stages and assess the sublineage commitment of human invariant natural killer T cells during thymic development, in this study, we performed single-cell RNA sequencing analysis on human Vα24+Vß11+ invariant natural killer T cells isolated from thymocytes. We show that these invariant natural killer T cells displayed heterogeneity, and our unsupervised analysis identified 5 clusters representing different maturation stages, from an immature profile with high expression of genes important for invariant natural killer T cell development and proliferation to a mature, fully differentiated profile with high levels of cytotoxic effector molecules. Evaluation of expression of sublineage-defining gene sets revealed mainly cells with an invariant natural killer T2 signature in the most immature cluster, whereas the more differentiated ones displayed an invariant natural killer T1 signature. Combined analysis with a publicly available single-cell RNA sequencing data set of human invariant natural killer T cells from peripheral blood suggested that the 2 main subsets exist both in thymus and in the periphery, while a third more immature one was restricted to the thymus. Our data point to the existence of different maturation stages of human thymic invariant natural killer T cells and provide evidence for sublineage commitment of invariant natural killer T cells in the human thymus.

AKT activity orchestrates marginal zone B cell development in mice and humans.

The signals controlling marginal zone (MZ) and follicular (FO) B cell development remain incompletely understood. Here, we show that AKT orchestrates MZ B cell formation in mice and humans. Genetic models that increase AKT signaling in B cells or abolish its impact on FoxO transcription factors highlight the AKT-FoxO axis as an on-off switch for MZ B cell formation in mice. In humans, splenic immunoglobulin (Ig) D+CD27+ B cells, proposed as an MZ B cell equivalent, display higher AKT signaling than naive IgD+CD27- and memory IgD-CD27+ B cells and develop in an AKT-dependent manner from their precursors in vitro, underlining the conservation of this developmental pathway. Consistently, CD148 is identified as a receptor indicative of the level of AKT signaling in B cells, expressed at a higher level in MZ B cells than FO B cells in mice as well as humans.

Model-based quality management of groundwater resources - catchment area Liedern, Germany.

Strategies of groundwater protection in agricultural dominated areas are mainly based on a general reduction of the input of nutrients like nitrate. However, preventive measures in different parts of the catchment may provide very different effects on raw water quality. Exemplified on the case study 'Liedern' (BEW GmbH Bocholt, Germany) it is shown that hydrogeochemical processes along the flow path and in the well strongly affect the results of agricultural measures in terms of modality and efficiency. Thus, a reduction of fertilization in the vicinity of the well gallery leads to a decrease of nitrate concentration in the raw water. Whereas agricultural measures in the eastern part of the catchment do not influence nitrate, but cause a reduction of the iron concentration and rate of incrustation in the wells after 18 years. In this study we present a management tool that enables assessment of future trends in raw water quality. The tool is based on a reactive transport model which considers land use dynamics as an instrument to influence groundwater/raw water quality. A thermodynamic equilibrium approach is applied for modelling hydrogeochemical processes between aqueous, solid and gaseous phases. Kinetically controlled reactions like the microbial degradation of organic carbon are expressed by multiplicative Michaelis-Menten equations.

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.

Is diversity harmful?-Mixed-brand cardiac implantable electronic devices undergoing magnetic resonance imaging.

BACKGROUND: Many patients with cardiac implantable electronic devices (CIED) undergo magnetic resonance imaging (MRI); however, a relevant proportion have a CIED system that has not been classified as MRI-conditional because of generators and leads from different brands (mixed-brand group). The available data concerning the outcome of these mixed patients undergoing MRI is limited. METHODS: A retrospective single center study, including all patients with CIEDs undergoing MRI between January 2013 until May 2020, was performed. Primary endpoints were defined as death or any adverse event necessitating hospitalization or CIED revision. Secondary endpoints were the occurrence of any sign for beginning device or lead failure or patient discomfort during MRI. RESULTS: A total of 227 MRI examinations, including 10 thoracic MRIs, were carried out in 158 patients, with 1-9 MRIs per patient. Of the patients 38 underwent 54 procedures in the mixed-brand group and 89 patients underwent 134 MRIs in the MRI-conditional group. Of the patients 31 were excluded since the MRI conditionality could not be determined. No primary endpoints occurred within the mixed-brand group but in 2.2% of the MRI-conditional group (p = 1.000), with 2 patients developing new atrial fibrillation during MRI, of whom one additionally had a transient CIED dysfunction. No secondary endpoints were met in the mixed-brand group compared to 3.4% in the MRI-conditional group (p = 0.554). No complications occurred in the excluded patients. CONCLUSION: The complication rate of CIED patients undergoing MRI was low. Patients with a mixed CIED system showed no signs of increased risk of adverse events compared to patients with MRI-conditional CIED systems.

A Similarity-Weighted Informative Prior Distribution for Bayesian Multiple Regression Models.

Specifying accurate informative prior distributions is a question of carefully selecting studies that comprise the body of comparable background knowledge. Psychological research, however, consists of studies that are being conducted under different circumstances, with different samples and varying instruments. Thus, results of previous studies are heterogeneous, and not all available results can and should contribute equally to an informative prior distribution. This implies a necessary weighting of background information based on the similarity of the previous studies to the focal study at hand. Current approaches to account for heterogeneity by weighting informative prior distributions, such as the power prior and the meta-analytic predictive prior are either not easily accessible or incomplete. To complicate matters further, in the context of Bayesian multiple regression models there are no methods available for quantifying the similarity of a given body of background knowledge to the focal study at hand. Consequently, the purpose of this study is threefold. We first present a novel method to combine the aforementioned sources of heterogeneity in the similarity measure ω. This method is based on a combination of a propensity-score approach to assess the similarity of samples with random- and mixed-effects meta-analytic models to quantify the heterogeneity in outcomes and study characteristics. Second, we show how to use the similarity measure ωas a weight for informative prior distributions for the substantial parameters (regression coefficients) in Bayesian multiple regression models. Third, we investigate the performance and the behavior of the similarity-weighted informative prior distribution in a comprehensive simulation study, where it is compared to the normalized power prior and the meta-analytic predictive prior. The similarity measure ω and the similarity-weighted informative prior distribution as the primary results of this study provide applied researchers with means to specify accurate informative prior distributions.

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.

Metatranscriptomic Analysis of Bacterial Communities on Laundered Textiles: A Pilot Case Study.

Microbially contaminated washing machines and mild laundering conditions facilitate the survival and growth of microorganisms on laundry, promoting undesired side effects such as malodor formation. Clearly, a deeper understanding of the functionality and hygienic relevance of the laundry microbiota necessitates the analysis of the microbial gene expression on textiles after washing, which-to the best of our knowledge-has not been performed before. In this pilot case study, we used single-end RNA sequencing to generate de novo transcriptomes of the bacterial communities remaining on polyester and cotton fabrics washed in a domestic washing machine in mild conditions and subsequently incubated under moist conditions for 72 h. Two common de novo transcriptome assemblers were used. The final assemblies included 22,321 Trinity isoforms and 12,600 Spades isoforms. A large part of these isoforms could be assigned to the SwissProt database, and was further categorized into "molecular function", "biological process" and "cellular component" using Gene Ontology (GO) terms. In addition, differential gene expression was used to show the difference in the pairwise comparison of the two tissue types. When comparing the assemblies generated with the two assemblers, the annotation results were relatively similar. However, there were clear differences between the de novo assemblies regarding differential gene expression.

A distinct CD38+CD45RA+ population of CD4+, CD8+, and double-negative T cells is controlled by FAS.

The identification and characterization of rare immune cell populations in humans can be facilitated by their growth advantage in the context of specific genetic diseases. Here, we use autoimmune lymphoproliferative syndrome to identify a population of FAS-controlled TCRαß+ T cells. They include CD4+, CD8+, and double-negative T cells and can be defined by a CD38+CD45RA+T-BET- expression pattern. These unconventional T cells are present in healthy individuals, are generated before birth, are enriched in lymphoid tissue, and do not expand during acute viral infection. They are characterized by a unique molecular signature that is unambiguously different from other known T cell differentiation subsets and independent of CD4 or CD8 expression. Functionally, FAS-controlled T cells represent highly proliferative, noncytotoxic T cells with an IL-10 cytokine bias. Mechanistically, regulation of this physiological population is mediated by FAS and CTLA4 signaling, and its survival is enhanced by mTOR and STAT3 signals. Genetic alterations in these pathways result in expansion of FAS-controlled T cells, which can cause significant lymphoproliferative disease.

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.

A non-foodborne norovirus outbreak among school children during a skiing holiday, Austria, 2007.

Norovirus is increasingly recognized as a leading cause of outbreaks of foodborne disease. We report on an outbreak in Austria that reached a total of 176 cases, affecting pupils and teachers from four schools on a skiing holiday in a youth hostel in the province of Salzburg in December 2007. A questionnaire was sent to the four schools in order to obtain data from persons attending the school trip on disease status, clinical onset, duration of illness and hospitalization. A cohort study was undertaken to identify the sources of infection. The school trip attendees were interviewed by questionnaire or face-to-face on their exposure to food items from the menu provided by the hostel owner. Of the 284 school holiday-makers, 176 fitted the definition of an outbreak case (attack rate 61.9%). A total of 264 persons on the ski holiday participated in the cohort study (response rate 93%). The day-by-day food-specific analyses did not find any food items served on any of five days (December 8-12) of the holiday to be associated with infection risk. The day-specific risk analyses revealed Monday December 10 (RR: 9.04; 95% CI: 6.02-13.6; P < 0.001) and Tuesday December 11 (RR: 3.37; 95% CI: 2.56-4.43; P < 0.001) as the two most risky days for having being exposed to norovirus. According to the epidemiological investigation, airborne transmission of norovirus originating from the first vomiting case most probably initiated this outbreak; foodborne genesis was excluded. During recent years, norovirus has become increasingly established as the most important causative agent of epidemic gastroenteritis in holiday-makers all over Europe. Tourism is one of the primary industries in Austria. Timely involvement of the relevant public health authorities is essential in any outbreak of norovirus gastroenteritis, irrespective of its genesis.

A foodborne outbreak of Salmonella Enteritidis phage type 6 in Austria, 2008.

In April 2008, a general foodborne outbreak of Salmonella Enteritidis phage type 6 affected nine persons (two households in Salzburg and one household in Tyrol; eight microbiologically confirmed cases and one possible case). Epidemiological investigation revealed that all cases had eaten lunch together at a farm. Homemade bread dumpling loaf, prepared with eggs from the farm, was the most likely vehicle for the pathogen. Six eggs were bacteriologically tested and yielded the outbreak strain on the egg shells. The farm's egg laying flock consisted of 12 hens, which were identified as the source of infection by isolating the outbreak strain from samples of hen fecal material and dust. Molecular subtyping using multiple loci variable number of tandem repeats analysis (MLVA) revealed a pattern unique to isolates from the outbreak, different from nine epidemiologically unrelated isolates tested for comparison. The laying hens were culled and no further cases of salmonellosis were associated with the farm. This example demonstrates the considerable potential of outbreak investigation to elucidate the transmission of infection along the food chain and to provide information essential for implementation of targeted measures for prevention of foodborne illness.