The Feminine Characters in Schiller\u27s Dramas

Woman\u27s role in history shown by the great dramatic productions of the ancient and modern world. Schiller\u27s feminine characters compared with Goethe\u27s

SARS-CoV-2 pandemic as a catalyst? Development of emotional problems of preschool children of mothers with childhood maltreatment experiences in the course of the pandemic–a longitudinal analysis

BackgroundSARS-CoV-2 pandemic have posed great challenges for all families and children. Health risks and fears associated with SARS-CoV-2 negatively affect the parental mental health and perceived stress, which in turn influence parental coping and thereby impairs the mental health and well-being of their children. Additional risk factors within the parents, such as maternal childhood maltreatment (CM) experiences, may increase the risk of children to develop emotional problems during the pandemic.ObjectiveThe purpose of this longitudinal study is to determine whether preschool children of mothers with CM are at higher risk of developing emotional problems during the pandemic than preschool children of mothers without CM.Method74 mothers from a birth cohort examining pathways to resilience or vulnerability in the transgenerational transmission of CM, provided information on emotional problems of their children (aged 3–7 years) at two measurement time points (t1: May 2020, t2: March 2021) as part of an online “SARS-CoV-2 pandemic” survey. In addition, parents were asked for a retrospective assessment of their children's emotional problems before the pandemic at time t1. Children's emotional problems were assessed using the “emotional problems” scale of the German version of the Strengths and Difficulties Questionnaire (SDQ) and linked to previously collected data on mothers' childhood maltreatment experiences, which were collected using the German short version of the Trauma in Childhood Questionnaire (CTQ).ResultsOur analyses showed that children's emotional problems increased significantly over the SARS-CoV-2 pandemic [F(1.86, 116.88) = 3.72, p = 0.030 η2 = 0.06] and were rated significantly higher in the group of children of mothers with CM, than in the group of mothers without CM [F(1, 63) = 126.06, p < 0.001 η2 = 0.67]. Furthermore children's emotional problems of mothers with CM increased significantly more and reached a clinically significant value during the pandemic than for children of mothers without CM [F(1.86, 116.88) = 8.89, p < 0.001, η2 = 0.12].ConclusionsChildren of mothers with CM appear to be at increased risk of developing emotional problems during the pandemic. CM therefore needs to be considered as an additional risk factor in the impact of the pandemic on children

The DNA methylation landscape of the human oxytocin receptor gene (OXTR): data-driven clusters and their relation to gene expression and childhood adversity

The oxytocin receptor gene (OXTR) is of interest when investigating the effects of early adversity on DNA methylation. However, there is heterogeneity regarding the selection of the most promising CpG sites to target for analyses. The goal of this study was to determine functionally relevant clusters of CpG sites within the OXTR CpG island in 113 mother-infant dyads, with 58 of the mothers reporting childhood maltreatment (CM). OXTR DNA methylation was analyzed in peripheral/umbilical blood mononuclear cells. Different complexity reduction approaches were used to reduce the 188 CpG sites into clusters of co-methylated sites. Furthermore, associations between OXTR DNA methylation (cluster- and site-specific level) and OXTR gene expression and CM were investigated in mothers. Results showed that, first, CpG sections differed strongly regarding their statistical utility for research of individual differences in DNA methylation. Second, cluster analyses and Partial Least Squares (PLS) suggested two clusters consisting of intron1/exon2 and the protein-coding region of exon3, respectively, as most strongly associated with outcome measures. Third, cross-validated PLS regression explained 7% of variance in CM, with low cross-validated variance explained for the prediction of gene expression. Fourth, substantial mother-child correspondence was observed in correlation patterns within the identified clusters, but only modest correspondence outside these clusters. This study makes an important contribution to the mapping of the DNA methylation landscape of the OXTR CpG island by highlighting clusters of CpG sites that show desirable statistical properties and predictive value. We provide a Companion Web Application to facilitate the choice of CpG sites

Atypical maternal interaction is associated with elevated levels of hair cortisol in children

The quality of maternal caregiving is an important factor in the healthy development of a child. One consequence of prolonged insensitive and atypical maternal interaction behavior (e.g., withdrawing from interactions with the child and role-reversal, i.e., the takeover of the parental role or parts of it by the child) in mother-child-dyads can cause alteration of the child's stress response system. Higher salivary cortisol concentrations were reported in infants and toddlers directly after negative interactions with their parents. However, no study to date has examined the association between atypical maternal interaction behavior and hair cortisol concentrations (HCC) in infants. Here, we studied the association of maternal interaction behavior with HCC of the child. Mother-child dyads (N = 112) participated in the longitudinal study My Childhood—Your Childhood. The AMBIANCE scale and its subscales were used to assess atypical maternal interaction behavior during the Strange Situation Procedure. Chronic stress levels in the child were assessed by HCC of 3 cm hair strands at the age of 12 months. Maternal educational level (operationalized in highest education level) served as a control variable. Robust multiple linear regression analyses revealed that role/boundary confusion was associated with HCC, i.e., the higher atypical interaction behavior of the mother the higher the HCC in the children. By measuring hair cortisol in this study, it is possible to determine the average long-term activity of the child's stress response system.Thus, atypical maternal interaction behavior could be a risk factor for persistent stress in children, contributing to a higher risk for negative health outcomes in later life. The results of this study highlight the importance of early intervention programs that focus on the relationship between mother and child

The DNA methylation landscape of the human oxytocin receptor gene (OXTR): data-driven clusters and their relation to gene expression and childhood adversity.

The oxytocin receptor gene (OXTR) is of interest when investigating the effects of early adversity on DNA methylation. However, there is heterogeneity regarding the selection of the most promising CpG sites to target for analyses. The goal of this study was to determine functionally relevant clusters of CpG sites within the OXTR CpG island in 113 mother-infant dyads, with 58 of the mothers reporting childhood maltreatment (CM). OXTR DNA methylation was analyzed in peripheral/umbilical blood mononuclear cells. Different complexity reduction approaches were used to reduce the 188 CpG sites into clusters of co-methylated sites. Furthermore, associations between OXTR DNA methylation (cluster- and site-specific level) and OXTR gene expression and CM were investigated in mothers. Results showed that, first, CpG sections differed strongly regarding their statistical utility for research of individual differences in DNA methylation. Second, cluster analyses and Partial Least Squares (PLS) suggested two clusters consisting of intron1/exon2 and the protein-coding region of exon3, respectively, as most strongly associated with outcome measures. Third, cross-validated PLS regression explained 7% of variance in CM, with low cross-validated variance explained for the prediction of gene expression. Fourth, substantial mother-child correspondence was observed in correlation patterns within the identified clusters, but only modest correspondence outside these clusters. This study makes an important contribution to the mapping of the DNA methylation landscape of the OXTR CpG island by highlighting clusters of CpG sites that show desirable statistical properties and predictive value. We provide a Companion Web Application to facilitate the choice of CpG sites

Investigating CTL Mediated Killing with a 3D Cellular Automaton

Cytotoxic T lymphocytes (CTLs) are important immune effectors against intra-cellular pathogens. These cells search for infected cells and kill them. Recently developed experimental methods in combination with mathematical models allow for the quantification of the efficacy of CTL killing in vivo and, hence, for the estimation of parameters that characterize the effect of CTL killing on the target cell populations. It is not known how these population-level parameters relate to single-cell properties. To address this question, we developed a three-dimensional cellular automaton model of the region of the spleen where CTL killing takes place. The cellular automaton model describes the movement of different cell populations and their interactions. Cell movement patterns in our cellular automaton model agree with observations from two-photon microscopy. We find that, despite the strong spatial nature of the kinetics in our cellular automaton model, the killing of target cells by CTLs can be described by a term which is linear in the target cell frequency and saturates with respect to the CTL levels. Further, we find that the parameters describing CTL killing on the population level are most strongly impacted by the time a CTL needs to kill a target cell. This suggests that the killing of target cells, rather than their localization, is the limiting step in CTL killing dynamics given reasonable frequencies of CTL. Our analysis identifies additional experimental directions which are of particular importance to interpret estimates of killing rates and could advance our quantitative understanding of CTL killing

An analytic and systematic framework for estimating metabolic flux ratios from 13C tracer experiments

<p>Abstract</p> <p>Background</p> <p>Metabolic fluxes provide invaluable insight on the integrated response of a cell to environmental stimuli or genetic modifications. Current computational methods for estimating the metabolic fluxes from ¹³<it>C </it>isotopomer measurement data rely either on manual derivation of analytic equations constraining the fluxes or on the numerical solution of a highly nonlinear system of isotopomer balance equations. In the first approach, analytic equations have to be tediously derived for each organism, substrate or labelling pattern, while in the second approach, the global nature of an optimum solution is difficult to prove and comprehensive measurements of external fluxes to augment the ¹³<it>C </it>isotopomer data are typically needed.</p> <p>Results</p> <p>We present a novel analytic framework for estimating metabolic flux ratios in the cell from ¹³<it>C </it>isotopomer measurement data. In the presented framework, equation systems constraining the fluxes are derived automatically from the model of the metabolism of an organism. The framework is designed to be applicable with all metabolic network topologies, ¹³<it>C </it>isotopomer measurement techniques, substrates and substrate labelling patterns.</p> <p>By analyzing nuclear magnetic resonance (NMR) and mass spectrometry (MS) measurement data obtained from the experiments on glucose with the model micro-organisms <it>Bacillus subtilis </it>and <it>Saccharomyces cerevisiae </it>we show that our framework is able to automatically produce the flux ratios discovered so far by the domain experts with tedious manual analysis. Furthermore, we show by <it>in silico </it>calculability analysis that our framework can rapidly produce flux ratio equations – as well as predict when the flux ratios are unobtainable by linear means – also for substrates not related to glucose.</p> <p>Conclusion</p> <p>The core of ¹³<it>C </it>metabolic flux analysis framework introduced in this article constitutes of flow and independence analysis of metabolic fragments and techniques for manipulating isotopomer measurements with vector space techniques. These methods facilitate efficient, analytic computation of the ratios between the fluxes of pathways that converge to a common junction metabolite. The framework can been seen as a generalization and formalization of existing tradition for computing metabolic flux ratios where equations constraining flux ratios are manually derived, usually without explicitly showing the formal proofs of the validity of the equations.</p

Multicountry Prospective Clinical Evaluation of Two Enzyme-Linked Immunosorbent Assays and Two Rapid Diagnostic Tests for Diagnosing Dengue Fever

We evaluated four dengue diagnostic devices from Alere, including the SD Bioline Dengue Duo (nonstructural [NS] 1 Ag and IgG/IgM), the Panbio Dengue Duo Cassette (IgM/IgG) rapid diagnostic tests (RDTs), and the Panbio dengue IgM and IgG capture enzyme-linked immunosorbent assays (ELISAs) in a prospective, controlled, multicenter study in Peru, Venezuela, Cambodia, and the United States, using samples from 1,021 febrile individuals. Archived, well-characterized samples from an additional 135 febrile individuals from Thailand were also used. Reference testing was performed on all samples using an algorithm involving virus isolation, in-house IgM and IgG capture ELISAs, and plaque reduction neutralization tests (PRNT) to determine the infection status of the individual. The primary endpoints were the clinical sensitivities and specificities of these devices. The SD Bioline Dengue Duo had an overall sensitivity of 87.3% (95% confidence interval [CI], 84.1 to 90.2%) and specificity of 86.8% (95% CI, 83.9 to 89.3%) during the first 14 days post-symptom onset (p.s.o.). The Panbio Dengue Duo Cassette demonstrated a sensitivity of 92.1% (87.8 to 95.2%) and specificity of 62.2% (54.5 to 69.5%) during days 4 to 14 p.s.o. The Panbio IgM capture ELISA had a sensitivity of 87.6% (82.7 to 91.4%) and specificity of 88.1% (82.2 to 92.6%) during days 4 to 14 p.s.o. Finally, the Panbio IgG capture ELISA had a sensitivity of 69.6% (62.1 to 76.4%) and a specificity of 88.4% (82.6 to 92.8%) during days 4 to 14 p.s.o. for identification of secondary dengue infections. This multicountry prospective study resulted in reliable real-world performance data that will facilitate data-driven laboratory test choices for managing patient care during dengue outbreaks