Deep-learning analysis of micropattern-based organoids enables high-throughput drug screening of Huntington's disease models.

Organoids are carrying the promise of modeling complex disease phenotypes and serving as a powerful basis for unbiased drug screens, potentially offering a more efficient drug-discovery route. However, unsolved technical bottlenecks of reproducibility and scalability have prevented the use of current organoids for high-throughput screening. Here, we present a method that overcomes these limitations by using deep-learning-driven analysis for phenotypic drug screens based on highly standardized micropattern-based neural organoids. This allows us to distinguish between disease and wild-type phenotypes in complex tissues with extremely high accuracy as well as quantify two predictors of drug success: efficacy and adverse effects. We applied our approach to Huntington's disease (HD) and discovered that bromodomain inhibitors revert complex phenotypes induced by the HD mutation. This work demonstrates the power of combining machine learning with phenotypic drug screening and its successful application to reveal a potentially new druggable target for HD.

Key summary of German national treatment guidance for hospitalized COVID-19 patients : Key pharmacologic recommendations from a national German living guideline using an Evidence to Decision Framework (last updated 17.05.2021).

PURPOSE: This executive summary of a national living guideline aims to provide rapid evidence based recommendations on the role of drug interventions in the treatment of hospitalized patients with COVID-19. METHODS: The guideline makes use of a systematic assessment and decision process using an evidence to decision framework (GRADE) as recommended standard WHO (2021). Recommendations are consented by an interdisciplinary panel. Evidence analysis and interpretation is supported by the CEOsys project providing extensive literature searches and living (meta-) analyses. For this executive summary, selected key recommendations on drug therapy are presented including the quality of the evidence and rationale for the level of recommendation. RESULTS: The guideline contains 11 key recommendations for COVID-19 drug therapy, eight of which are based on systematic review and/or meta-analysis, while three recommendations represent consensus expert opinion. Based on current evidence, the panel makes strong recommendations for corticosteroids (WHO scale 5-9) and prophylactic anticoagulation (all hospitalized patients with COVID-19) as standard of care. Intensified anticoagulation may be considered for patients with additional risk factors for venous thromboembolisms (VTE) and a low bleeding risk. The IL-6 antagonist tocilizumab may be added in case of high supplemental oxygen requirement and progressive disease (WHO scale 5-6). Treatment with nMABs may be considered for selected inpatients with an early SARS-CoV-2 infection that are not hospitalized for COVID-19. Convalescent plasma, azithromycin, ivermectin or vitamin D3 should not be used in COVID-19 routine care. CONCLUSION: For COVID-19 drug therapy, there are several options that are sufficiently supported by evidence. The living guidance will be updated as new evidence emerges.

[Quality of documentation of intraoperative and postoperative complications : improvement of documentation for a nationwide quality assurance program and comparison with routine data]. / Dokumentationsqualität intra- und postoperativer Komplikationen : Verbesserung der Dokumentation für die verpflichtende Qualitätssicherung und Vergleich mit DRG-Routinedaten.

INTRODUCTION: Complications after cholecystectomy are continuously documented in a nationwide database in Germany. Recent studies demonstrated a lack of reliability of these data. The aim of the study was to evaluate the impact of a control algorithm on documentation quality and the use of routine diagnosis coding as an additional validation instrument. METHODS: Completeness and correctness of the documentation of complications after cholecystectomy was compared over a time interval of 12 months before and after implementation of an algorithm for faster and more accurate documentation. Furthermore, the coding of all diagnoses was screened to identify intraoperative and postoperative complications. RESULTS AND DISCUSSION: The sensitivity of the documentation for complications improved from 46 % to 70 % (p = 0.05, specificity 98 % in both time intervals). A prolonged time interval of more than 6 weeks between patient discharge and documentation was associated with inferior data quality (incorrect documentation in 1.5 % versus 15 %, p < 0.05). The rate of case documentation within the 6 weeks after hospital discharge was clearly improved after implementation of the control algorithm. Sensitivity and specificity of screening for complications by evaluating routine diagnoses coding were 70 % and 85 %, respectively. The quality of documentation was improved by implementation of a simple memory algorithm.

[Music--poison and cure]. / Musik--Gift und Heilmittel.

There is no music in nature. Music is a purely human/psychologic phenomenon. Corresponding to the psyche it is bivalent, bipolar, dialectic, good and evil. A paradigm for this is the history of the organ.