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Die weltweite Vernetzung von Märkten, Kapital und Produktion lässt Entwicklungs- und Schwellenländer der Versuchung des »social dumping« erliegen: Das ohnehin niedrige arbeitsrechtliche Niveau senken sie noch weiter ab, um im globalen Wettbewerb mithalten zu können. Davon betroffen sind Länder in Afrika, Asien und Lateinamerika ebenso wie in Mittel- und Osteuropa. Doch bedroht sind auch die sozialen Errungenschaften in fortgeschrittenen Industrieländern, da die Produktion immer häufiger in Länder mit geringeren Arbeitskosten verlagert wird. Eine Abwärtsspirale ist in Gang gesetzt, der viel beschworene »race to the bottom« erscheint unaufhaltsam. Deshalb soll hier der Frage nachgegangen werden, welche Konzepte der Gegensteuerung sich auf globaler Ebene ausmachen lassen, wie deren Effektivität einzuschätzen ist und welche Zukunftsperspektiven sich aus den bisherigen Erfahrungen gewinnen lassen.
Der Beitrag ruft die zentralen Überlegungen Hugo Sinzheimers zur sozialen Selbstbestimmung, zur Arbeitsverfassung, zum Arbeitsrecht als ein die Grenzen zwischen Zivilrecht und öffentlichem Recht sprengenden Rechtsgebiet sui generis und zur Rechtssoziologie ins Gedächtnis, um daraus einige Folgerungen für die Arbeitsrechtswissenschaft am Fachbereich Rechtswissenschaft der Goethe Universität abzuleiten.
The mechanism by which the enzyme pyruvate decarboxylase from yeast is activated allosterically has been elucidated. A total of seven three-dimensional structures of the enzyme, of enzyme variants or of enzyme complexes from two yeast species (three of them reported here for the first time) provide detailed atomic resolution snapshots along the activation coordinate. The prime event is the covalent binding of the substrate pyruvate to the side chain of cysteine 221, thus forming a thiohemiketal. This reaction causes the shift of a neighbouring amino acid, which eventually leads to the rigidification of two otherwise flexible loops, where one of the loops provides two histidine residues necessary to complete the enzymatically competent active site architecture. The structural data are complemented and supported by kinetic investigations and binding studies and provide a consistent picture of the structural changes, which occur upon enzyme activation.
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.
Epigenetic neural glioblastoma enhances synaptic integration and predicts therapeutic vulnerability
(2023)
Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is nascent. We present an epigenetically defined neural signature of glioblastoma that independently affects patients survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals high abundance of stem cell-like malignant cells classified as oligodendrocyte precursor and neural precursor cell-like in high-neural glioblastoma. High-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature associates with decreased survival as well as increased functional connectivity and can be detected via DNA analytes and brain-derived neurotrophic factor in plasma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant.
Introduction: The German PID-NET registry was founded in 2009, serving as the first national registry of patients with primary immunodeficiencies (PID) in Germany. It is part of the European Society for Immunodeficiencies (ESID) registry. The primary purpose of the registry is to gather data on the epidemiology, diagnostic delay, diagnosis, and treatment of PIDs.
Methods: Clinical and laboratory data was collected from 2,453 patients from 36 German PID centres in an online registry. Data was analysed with the software Stata® and Excel.
Results: The minimum prevalence of PID in Germany is 2.72 per 100,000 inhabitants. Among patients aged 1–25, there was a clear predominance of males. The median age of living patients ranged between 7 and 40 years, depending on the respective PID. Predominantly antibody disorders were the most prevalent group with 57% of all 2,453 PID patients (including 728 CVID patients). A gene defect was identified in 36% of patients. Familial cases were observed in 21% of patients. The age of onset for presenting symptoms ranged from birth to late adulthood (range 0–88 years). Presenting symptoms comprised infections (74%) and immune dysregulation (22%). Ninety-three patients were diagnosed without prior clinical symptoms. Regarding the general and clinical diagnostic delay, no PID had undergone a slight decrease within the last decade. However, both, SCID and hyper IgE- syndrome showed a substantial improvement in shortening the time between onset of symptoms and genetic diagnosis. Regarding treatment, 49% of all patients received immunoglobulin G (IgG) substitution (70%—subcutaneous; 29%—intravenous; 1%—unknown). Three-hundred patients underwent at least one hematopoietic stem cell transplantation (HSCT). Five patients had gene therapy.
Conclusion: The German PID-NET registry is a precious tool for physicians, researchers, the pharmaceutical industry, politicians, and ultimately the patients, for whom the outcomes will eventually lead to a more timely diagnosis and better treatment.