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Maßgeblich unter dem wachsenden externen Druck hat die didaktische Qualifizierung in den medizinischen Fakultäten an Bedeutung gewonnen. Im Rahmen der Professionalisierung der medizinischen Aus-, Fort- und Weiterbildung ist eine pädagogisch-didaktische Ausbildung der Lehrenden unumgänglich. Um Orientierung und Argumentationshilfe zu geben, werden in einer dreiteiligen Artikelfolge Stellenwert der Medizindidaktik, Anforderungsprofil der Angebote und Konzepte zur Implementierung und zur Erfolgsmessung für den deutschsprachigen Raum beleuchtet. In Teil I geben wir eine Bestandsaufnahme zur Medizindidaktik. Aktuell gibt es bundesweit ein breit gefächertes Qualifizierungsangebot. Es reicht von einfachen unstrukturierten Kurzfortbildungen wie zum Beispiel Vorträgen und Seminaren, die inhaltlich, formal und qualitativ eine große Beliebigkeit zeigen, bis hin zu umfassenden mehrjährigen (Aufbau-)Studiengängen mit "Master-Degree". Im internationalen Vergleich fehlt in Deutschland ein allgemein verbindliches "Basis-Programm", das die täglich Lehrenden systematisch auf ihre Ausbildungsaufgaben vorbereitet. Dies ist bisher nur lokal umgesetzt wie zum Beispiel in Baden-Württemberg mit dem ministeriell zertifizierten Programm der Medizindidaktischen Qualifikation I und II. Vergleichbares ist in Nordrhein-Westfalen und Bayern im Aufbau.
Purpose: Scientific and clinical achievements in radiation, medical, and surgical oncology are changing the landscape of interdisciplinary oncology. The German Society for Radiation Oncology (DEGRO) working group of young clinicians and scientists (yDEGRO) and the DEGRO representation of associate and full professors (AKRO) are aware of the essential role of radiation oncology in multidisciplinary treatment approaches. Together, yDEGRO and AKRO endorsed developing a German radiotherapy & radiation oncology vision 2030 to address future challenges in patient care, research, and education. The vision 2030 aims to identify priorities and goals for the next decade in the field of radiation oncology. Methods: The vision development comprised three phases. During the first phase, areas of interest, objectives, and the process of vision development were defined jointly by the yDEGRO, AKRO, and the DEGRO board. In the second phase, a one-day strategy retreat was held to develop AKRO and yDEGRO representatives’ final vision from medicine, biology, and physics. The third phase was dedicated to vision interpretation and program development by yDEGRO representatives. Results: The strategy retreat’s development process resulted in conception of the final vision “Innovative radiation oncology Together – Precise, Personalized, Human.” The first term “Innovative radiation oncology” comprises the promotion of preclinical research and clinical trials and highlights the development of a national committee for strategic development in radiation oncology research. The term “together” underpins collaborations within radiation oncology departments as well as with other partners in the clinical and scientific setting. “Precise” mainly covers technological precision in radiotherapy as well as targeted oncologic therapeutics. “Personalized” emphasizes biology-directed individualization of radiation treatment. Finally, “Human” underlines the patient-centered approach and points towards the need for individual longer-term career curricula for clinicians and researchers in the field. Conclusion: The vision 2030 balances the ambition of physical, technological, and biological innovation as well as a comprehensive, patient-centered, and collaborative approach towards radiotherapy & radiation oncology in Germany.
Glioblastoma multiforme (GBM) is treated by surgical resection followed by radiochemotherapy. Bevacizumab is commonly deployed for anti‐angiogenic therapy of recurrent GBM; however, innate immune cells have been identified as instigators of resistance to bevacizumab treatment. We identified angiopoietin‐2 (Ang‐2) as a potential target in both naive and bevacizumab‐treated glioblastoma. Ang‐2 expression was absent in normal human brain endothelium, while the highest Ang‐2 levels were observed in bevacizumab‐treated GBM. In a murine GBM model, VEGF blockade resulted in endothelial upregulation of Ang‐2, whereas the combined inhibition of VEGF and Ang‐2 leads to extended survival, decreased vascular permeability, depletion of tumor‐associated macrophages, improved pericyte coverage, and increased numbers of intratumoral T lymphocytes. CD206+ (M2‐like) macrophages were identified as potential novel targets following anti‐angiogenic therapy. Our findings imply a novel role for endothelial cells in therapy resistance and identify endothelial cell/myeloid cell crosstalk mediated by Ang‐2 as a potential resistance mechanism. Therefore, combining VEGF blockade with inhibition of Ang‐2 may potentially overcome resistance to bevacizumab therapy.
Purpose: COVID-19 pandemic had multiple influences on the social, industrial, and medical situation in all affected countries. Measures of obligatory medical confinement were suspensions of scheduled non-emergent surgical procedures and outpatients’ clinics as well as overall access restrictions to hospitals and medical practices. The aim of this retrospective study was to assess if the obligatory confinement (lockdown) had an effect on the number of appendectomies (during and after the period of lockdown).
Methods: This retrospective study was based on anonymized nationwide administrative claims data of the German Local General Sickness Fund (AOK). Patients admitted for diseases of the appendix (ICD-10: K35-K38) or abdominal and pelvic pain (ICD-10: R10) who underwent an appendectomy (OPS: 5-470) were included. The study period included 6 weeks of German lockdown (16 March–26 April 2020) as well as 6 weeks before (03 February–15 March 2020) and after (27 April–07 June 2020). These periods were compared to the respective one in 2018 and 2019.
Results: The overall number of appendectomies was significantly reduced during the lockdown time in 2020 compared to that in 2018 and 2019. This decrease affects only appendectomies due to acute simple (ICD-10: K35.30, K35.8) and non-acute appendicitis (ICD-10: K36-K38, R10). Numbers for appendectomies in acute complex appendicitis remained unchanged. Female patients and in the age group 1–18 years showed the strongest decrease in number of cases.
Conclusion: The lockdown in Germany resulted in a decreased number of appendectomies. This affected mainly appendectomies in simple acute and non-acute appendicitis, but not complicated acute appendicitis. The study gives no evidence that the confinement measures resulted in a deterioration of medical care for appendicitis.
The highly infectious disease COVID-19 caused by the Betacoronavirus SARS-CoV-2 poses a severe threat to humanity and demands the redirection of scientific efforts and criteria to organized research projects. The international COVID19-NMR consortium seeks to provide such new approaches by gathering scientific expertise worldwide. In particular, making available viral proteins and RNAs will pave the way to understanding the SARS-CoV-2 molecular components in detail. The research in COVID19-NMR and the resources provided through the consortium are fully disclosed to accelerate access and exploitation. NMR investigations of the viral molecular components are designated to provide the essential basis for further work, including macromolecular interaction studies and high-throughput drug screening. Here, we present the extensive catalog of a holistic SARS-CoV-2 protein preparation approach based on the consortium’s collective efforts. We provide protocols for the large-scale production of more than 80% of all SARS-CoV-2 proteins or essential parts of them. Several of the proteins were produced in more than one laboratory, demonstrating the high interoperability between NMR groups worldwide. For the majority of proteins, we can produce isotope-labeled samples of HSQC-grade. Together with several NMR chemical shift assignments made publicly available on covid19-nmr.com, we here provide highly valuable resources for the production of SARS-CoV-2 proteins in isotope-labeled form.
LICE is one of the four major LHC experiments at CERN. When the accelerator enters the Run 3 data-taking period, starting in 2021, ALICE expects almost 100 times more Pb-Pb central collisions than now, resulting in a large increase of data throughput. In order to cope with this new challenge, the collaboration had to extensively rethink the whole data processing chain, with a tighter integration between Online and Offline computing worlds. Such a system, code-named ALICE O2, is being developed in collaboration with the FAIR experiments at GSI. It is based on the ALFA framework which provides a generalized implementation of the ALICE High Level Trigger approach, designed around distributed software entities coordinating and communicating via message passing.
We will highlight our efforts to integrate ALFA within the ALICE O2 environment. We analyze the challenges arising from the different running environments for production and development, and conclude on requirements for a flexible and modular software framework. In particular we will present the ALICE O2 Data Processing Layer which deals with ALICE specific requirements in terms of Data Model. The main goal is to reduce the complexity of development of algorithms and managing a distributed system, and by that leading to a significant simplification for the large majority of the ALICE users.
Children’s and adolescents’ lives drastically changed during COVID lockdowns worldwide. To compare accident- and injury-related admissions to pediatric intensive care units (PICU) during the first German COVID lockdown with previous years, we conducted a retrospective multicenter study among 37 PICUs (21.5% of German PICU capacities). A total of 1444 admissions after accidents or injuries during the first lockdown period and matched periods of 2017–2019 were reported and standardized morbidity ratios (SMR) were calculated. Total PICU admissions due to accidents/injuries declined from an average of 366 to 346 (SMR 0.95 (CI 0.85–1.05)). Admissions with trauma increased from 196 to 212 (1.07 (0.93–1.23). Traffic accidents and school/kindergarten accidents decreased (0.77 (0.57–1.02 and 0.26 (0.05–0.75)), whereas household and leisure accidents increased (1.33 (1.06–1.66) and 1.34 (1.06–1.67)). Less neurosurgeries and more visceral surgeries were performed (0.69 (0.38–1.16) and 2.09 (1.19–3.39)). Non-accidental non-suicidal injuries declined (0.73 (0.42–1.17)). Suicide attempts increased in adolescent boys (1.38 (0.51–3.02)), but decreased in adolescent girls (0.56 (0.32–0.79)). In summary, changed trauma mechanisms entailed different surgeries compared to previous years. We found no evidence for an increase in child abuse cases requiring intensive care. The increase in suicide attempts among boys demands investigation.
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual’s network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.
Highlights
• Brain connectivity states identified by cofluctuation strength.
• CMEP as new method to robustly predict human traits from brain imaging data.
• Network-identifying connectivity ‘events’ are not predictive of cognitive ability.
• Sixteen temporally independent fMRI time frames allow for significant prediction.
• Neuroimaging-based assessment of cognitive ability requires sufficient scan lengths.
Abstract
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10 min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual's network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.