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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.
Background and Objectives: Red blood cell (RBC) transfusions are needed by almost every acute myeloid leukaemia (AML) patient undergoing induction chemotherapy and constitute a cornerstone in supportive measures for cancer patients in general. Randomized controlled trials have shown non‐inferiority or even superiority of restrictive transfusion guidelines over liberal transfusion guidelines in specific clinical situations outside of medical oncology. In this study, we analysed whether more restrictive RBC transfusion reduces blood use without affecting hard outcomes.
Materials and Methods: A total of 352 AML patients diagnosed between 2007 and 2018 and undergoing intensive induction chemotherapy were included in this retrospective analysis. In the less restrictive transfusion group, patients received RBC transfusion for haemoglobin levels below 8 g/dl (2007–2014). In the restrictive transfusion group, patients received RBC transfusion for haemoglobin levels below 7 g/dl (2016–2018). Liberal transfusion triggers were never endorsed.
Results: A total of 268 (76·1%) and 84 (23·9%) AML patients fell into the less restrictive and restrictive transfusion groups, respectively. The less restrictive transfusion group had 1 g/dl higher mean haemoglobin levels, received their first RBC transfusions earlier and needed 1·5 more units of RBC during the hospital stay of induction chemotherapy. Febrile episodes, C‐reactive protein levels, admission to the intensive care unit, length of hospital stay as well as response and survival rates did not differ between the two cohorts.
Conclusion: From our retrospective analysis, we conclude that a more restrictive transfusion trigger does not affect important outcomes of AML patients. The opportunity to test possible effects of the more severe anaemia in the restrictive transfusion group on quality of life was missed.
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.
Kinesins play an important role in many physiological functions including intracellular vesicle transport and mitosis. The emerging role of kinesins in different cancers led us to investigate the expression and functional role of kinesins in meningioma. Therefore, we re-analyzed our previous microarray dataset of benign, atypical, and anaplastic meningiomas (n = 62) and got evidence for differential expression of five kinesins (KIFC1, KIF4A, KIF11, KIF14 and KIF20A). Further validation in an extended study sample (n = 208) revealed a significant upregulation of these genes in WHO°I to °III meningiomas (WHO°I n = 61, WHO°II n = 88, and WHO°III n = 59), which was most pronounced in clinically more aggressive tumors of the same WHO grade. Immunohistochemical staining confirmed a WHO grade-associated upregulated protein expression in meningioma tissues. Furthermore, high mRNA expression levels of KIFC1, KIF11, KIF14 and KIF20A were associated with shorter progression-free survival. On a functional level, knockdown of kinesins in Ben-Men-1 cells and in the newly established anaplastic meningioma cell line NCH93 resulted in a significantly inhibited tumor cell proliferation upon siRNA-mediated downregulation of KIF11 in both cell lines by up to 95% and 71%, respectively. Taken together, in this study we were able to identify the prognostic and functional role of several kinesin family members of which KIF11 exhibits the most promising properties as a novel prognostic marker and therapeutic target, which may offer new treatment options for aggressive meningiomas.
Environmental change impacts on the C- and N-cycle of European forests: a model comparison study
(2013)
Forests are important components of the greenhouse gas balance of Europe. There is considerable uncertainty about how predicted changes to climate and nitrogen deposition will perturb the carbon and nitrogen cycles of European forests and thereby alter forest growth, carbon sequestration and N2O emission. The present study aimed to quantify the carbon and nitrogen balance, including the exchange of greenhouse gases, of European forests over the period 2010–2030, with a particular emphasis on the spatial variability of change. The analysis was carried out for two tree species: European beech and Scots pine. For this purpose, four different dynamic models were used: BASFOR, DailyDayCent, INTEGRATOR and Landscape-DNDC. These models span a range from semi-empirical to complex mechanistic. Comparison of these models allowed assessment of the extent to which model predictions depended on differences in model inputs and structure. We found a European average carbon sink of 0.160 ± 0.020 kgC m−2 yr−1 (pine) and 0.138 ± 0.062 kgC m−2 yr−1 (beech) and N2O source of 0.285 ± 0.125 kgN ha−1 yr−1 (pine) and 0.575 ± 0.105 kgN ha−1 yr−1 (beech). The European average greenhouse gas potential of the carbon sink was 18 (pine) and 8 (beech) times that of the N2O source. Carbon sequestration was larger in the trees than in the soil. Carbon sequestration and forest growth were largest in central Europe and lowest in northern Sweden and Finland, N. Poland and S. Spain. No single driver was found to dominate change across Europe. Forests were found to be most sensitive to change in environmental drivers where the drivers were limiting growth, where changes were particularly large or where changes acted in concert. The models disagreed as to which environmental changes were most significant for the geographical variation in forest growth and as to which tree species showed the largest rate of carbon sequestration. Pine and beech forests were found to have differing sensitivities to environmental change, in particular the response to changes in nitrogen and precipitation, with beech forest more vulnerable to drought. There was considerable uncertainty about the geographical location of N2O emissions. Two of the models BASFOR and LandscapeDNDC had largest emissions in central Europe where nitrogen deposition and soil nitrogen were largest, whereas the two other models identified different regions with large N2O emission. N2O emissions were found to be larger from beech than pine forests and were found to be particularly sensitive to forest growth.
Forests are important components of the greenhouse gas balance of Europe. There is considerable uncertainty about how predicted changes to climate and nitrogen deposition will perturb the carbon and nitrogen cycles of European forests and thereby alter forest growth, carbon sequestration and N2O emission. The present study aimed to quantify the carbon and nitrogen balance, including the exchange of greenhouse gases, of European forests over the period 2010–2030, with a particular emphasis on the spatial variability of change. The analysis was carried out for two tree species: European beech and Scots pine. For this purpose, four different dynamic models were used: BASFOR, DailyDayCent, INTEGRATOR and Landscape-DNDC. These models span a range from semi-empirical to complex mechanistic. Comparison of these models allowed assessment of the extent to which model predictions depended on differences in model inputs and structure. We found a European average carbon sink of 0.160 ± 0.020 kgC m−2 yr−1 (pine) and 0.138 ± 0.062 kgC m−2 yr−1 (beech) and N2O source of 0.285 ± 0.125 kgN ha−1 yr−1 (pine) and 0.575 ± 0.105 kgN ha−1 yr−1 (beech). The European average greenhouse gas potential of the carbon source was 18 (pine) and 8 (beech) times that of the N2O source. Carbon sequestration was larger in the trees than in the soil. Carbon sequestration and forest growth were largest in central Europe and lowest in northern Sweden and Finland, N. Poland and S. Spain. No single driver was found to dominate change across Europe. Forests were found to be most sensitive to change in environmental drivers where the drivers were limiting growth, where changes were particularly large or where changes acted in concert. The models disagreed as to which environmental changes were most significant for the geographical variation in forest growth and as to which tree species showed the largest rate of carbon sequestration. Pine and beech forests were found to have differing sensitivities to environmental change, in particular the response to changes in nitrogen and precipitation, with beech forest more vulnerable to drought. There was considerable uncertainty about the geographical location of N2O emissions. Two of the models BASFOR and LandscapeDNDC had largest emissions in central Europe where nitrogen deposition and soil nitrogen were largest whereas the two other models identified different regions with large N2O emission. N2O emissions were found to be larger from beech than pine forests and were found to be particularly sensitive to forest growth.
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.
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.
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.