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Parabens and sorbic acid are commonly used as food preservatives due to their antimicrobial effect. However, their use in foods for infants and young children is not permitted in the European Union. Previous studies found these compounds in some gel-filled baby teethers, whereby parabens, which are well-known as endocrine disruptors, were identified in the polymer-based chewing surface consisting of ethylene-vinyl acetate (EVA). To assess the exposure of infants and young children to these products, the application of parabens in teethers should be thoroughly investigated. Therefore, the present study aimed to apply a representative migration test procedure combined with an accurate analytical method to examine gel-filled baby teethers without elaborate sample preparation, high costs, and long processing times. Accordingly, solid-phase extraction (SPE), in combination with a stable isotope dilution assay (SIDA) and subsequent gas chromatography–mass spectrometry (GC–MS) for analysis of methyl-, ethyl-, and n-propylparaben (MeP, EtP, and n-PrP), was found to be well-suited, with recoveries ranging from 93 to 99%. The study compared the release of these parabens from intact teether surfaces into water and saliva simulant under real-life conditions, with total amounts of detected parabens found to be in the range of 101–162 µg 100 mL−1 and 57–148 µg 100 mL−1, respectively. Furthermore, as a worst-case scenario, the release into water was examined using a long-term migration study.
2-Aminobenzimidazole 10, although a weak catalyst in the monomeric state, is a successful building block for effective artificial ribonucleases. In an effort to identify new building blocks with improved catalytic potential, RNA cleavage by a variety of heterocyclic amidines and guanidines has been studied. In addition to pKa values and steric effects, the energy difference between tautomeric forms seems to be another important parameter for catalysis. This information is available from quantum chemical calculations on higher levels, but semiempirical methods are sufficient to get a first estimate. According to this assumption, imidazoimidazol 18, characterized by isoenergetic tautomeric forms, is superior to 2-aminoimidazol 6, the best candidate among the simple compounds. By far the largest effects are seen with 2-aminoperimidine 24, which rapidly cleaves RNA even in the micromolar concentration range. The impressive reactivity, however, is related to a tendency of compound 24 to form polycationic aggregates which are the actual catalysts.
2-Aminobenzimidazole 10, although a weak catalyst in the monomeric state, is a successful building block for effective artificial ribonucleases. In an effort to identify new building blocks with improved catalytic potential, RNA cleavage by a variety of heterocyclic amidines and guanidines has been studied. In addition to pKa values and steric effects, the energy difference between tautomeric forms seems to be another important parameter for catalysis. This information is available from quantum chemical calculations on higher levels, but semiempirical methods are sufficient to get a first estimate. According to this assumption, imidazoimidazol 18, characterized by isoenergetic tautomeric forms, is superior to 2-aminoimidazol 6, the best candidate among the simple compounds. By far the largest effects are seen with 2-aminoperimidine 24, which rapidly cleaves RNA even in the micromolar concentration range. The impressive reactivity, however, is related to a tendency of compound 24 to form polycationic aggregates which are the actual catalysts.
Ecological speciation assumes reproductive isolation to be the product of ecologically based divergent selection. Beside natural selection, sexual selection via phenotype-assortative mating is thought to promote reproductive isolation. Using the neotropical fish Poecilia mexicana from a system that has been described to undergo incipient ecological speciation in adjacent, but ecologically divergent habitats characterized by the presence or absence of toxic H2S and darkness in cave habitats, we demonstrate a gradual change in male body colouration along the gradient of light/darkness, including a reduction of ornaments that are under both inter- and intrasexual selection in surface populations. In dichotomous choice tests using video-animated stimuli, we found surface females to prefer males from their own population over the cave phenotype. However, female cave fish, observed on site via infrared techniques, preferred to associate with surface males rather than size-matched cave males, likely reflecting the female preference for better-nourished (in this case: surface) males. Hence, divergent selection on body colouration indeed translates into phenotype-assortative mating in the surface ecotype, by selecting against potential migrant males. Female cave fish, by contrast, do not have a preference for the resident male phenotype, identifying natural selection against migrants imposed by the cave environment as the major driver of the observed reproductive isolation.
Background: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods: A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results: 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions: Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.
