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Background: Network science provides powerful access to essential organizational principles of the brain. The aim of this study was to investigate longitudinal evolution of gray matter networks in early relapsing–remitting MS (RRMS) compared with healthy controls (HCs) and contrast network dynamics with conventional atrophy measurements.
Methods: For our longitudinal study, we investigated structural cortical networks over 1 year derived from 3T MRI in 203 individuals (92 early RRMS patients with mean disease duration of 12.1 ± 14.5 months and 101 HCs). Brain networks were computed based on cortical thickness inter-regional correlations and fed into graph theoretical analysis. Network connectivity measures (modularity, clustering coefficient, local efficiency, and transitivity) were compared between patients and HCs, and between patients with and without disease activity. Moreover, we calculated longitudinal brain volume changes and cortical atrophy patterns.
Results: Our analyses revealed strengthening of local network properties shown by increased modularity, clustering coefficient, local efficiency, and transitivity over time. These network dynamics were not detectable in the cortex of HCs over the same period and occurred independently of patients’ disease activity. Most notably, the described network reorganization was evident beyond detectable atrophy as characterized by conventional morphometric methods.
Conclusion: In conclusion, our findings provide evidence for gray matter network reorganization subsequent to clinical disease manifestation in patients with early RRMS. An adaptive cortical response with increased local network characteristics favoring network segregation could play a primordial role for maintaining brain function in response to neuroinflammation.
Background: Available data on the incidence and outcome of invasive fungal diseases (IFD) in children with hematological malignancies or after allogeneic hematopoietic stem cell transplantation (HSCT) are mostly based on monocenter, retrospective studies or on studies performed prior to the availability of newer triazoles or echinocandins.
Procedure: We prospectively collected clinical data on incidence, diagnostic procedures, management and outcome of IFD in children treated for hematological malignancies or undergoing HSCT in three major European pediatric cancer centers.
Results: A total of 304 children (median age 6.0 years) who underwent 360 therapies (211 chemotherapy treatments, 138 allogeneic HSCTs and/or 11 investigational chemotherapeutic treatments) were included in the analysis. Nineteen children developed proven/probable IFD, mostly due to Aspergillus (n = 10) and Candida spp. (n = 5), respectively. In patients receiving chemotherapy, 11 IFDs occurred, all during induction or re-induction therapy. None of these patients died due to IFD, whereas IFD was lethal in 3 of the 8 HSCT recipients with IFD. Significant differences among centers were observed with regard to the use of imaging diagnostics and the choice, initiation and duration of antifungal prophylaxis.
Conclusion: This prospective multicenter study provides information on the current incidence and outcome of IFD in the real life setting. Practice variation between the centers may help to ultimately improve antifungal management in children at highest risk for IFDs.
Background: Germinal center-derived B cell lymphomas are tumors of the lymphoid tissues representing one of the most heterogeneous malignancies. Here we characterize the variety of transcriptomic phenotypes of this disease based on 873 biopsy specimens collected in the German Cancer Aid MMML (Molecular Mechanisms in Malignant Lymphoma) consortium. They include diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt’s lymphoma, mixed FL/DLBCL lymphomas, primary mediastinal large B cell lymphoma, multiple myeloma, IRF4-rearranged large cell lymphoma, MYC-negative Burkitt-like lymphoma with chr. 11q aberration and mantle cell lymphoma.
Methods: We apply self-organizing map (SOM) machine learning to microarray-derived expression data to generate a holistic view on the transcriptome landscape of lymphomas, to describe the multidimensional nature of gene regulation and to pursue a modular view on co-expression. Expression data were complemented by pathological, genetic and clinical characteristics.
Results: We present a transcriptome map of B cell lymphomas that allows visual comparison between the SOM portraits of different lymphoma strata and individual cases. It decomposes into one dozen modules of co-expressed genes related to different functional categories, to genetic defects and to the pathogenesis of lymphomas. On a molecular level, this disease rather forms a continuum of expression states than clearly separated phenotypes. We introduced the concept of combinatorial pattern types (PATs) that stratifies the lymphomas into nine PAT groups and, on a coarser level, into five prominent cancer hallmark types with proliferation, inflammation and stroma signatures. Inflammation signatures in combination with healthy B cell and tonsil characteristics associate with better overall survival rates, while proliferation in combination with inflammation and plasma cell characteristics worsens it. A phenotypic similarity tree is presented that reveals possible progression paths along the transcriptional dimensions. Our analysis provided a novel look on the transition range between FL and DLBCL, on DLBCL with poor prognosis showing expression patterns resembling that of Burkitt’s lymphoma and particularly on "double-hit" MYC and BCL2 transformed lymphomas.
Conclusions: The transcriptome map provides a tool that aggregates, refines and visualizes the data collected in the MMML study and interprets them in the light of previous knowledge to provide orientation and support in current and future studies on lymphomas and on other cancer entities.
Background & Aims: We investigated the effect of albumin treatment (20% solution) on hypoalbuminemia, cardiocirculatory dysfunction, portal hypertension, and systemic inflammation in patients with decompensated cirrhosis with and without bacterial infections.
Methods: We performed a prospective study to assess the effects of long-term (12 weeks) treatment with low doses (1 g/kg body weight every 2 weeks) and high doses (1.5 g/kg every week) of albumin on serum albumin, plasma renin, cardiocirculatory function, portal pressure, and plasma levels of cytokines, collecting data from 18 patients without bacterial infections (the Pilot-PRECIOSA study). We also assessed the effect of short-term (1 week) treatment with antibiotics alone vs the combination of albumin plus antibiotics (1.5 g/kg on day 1 and 1 g/kg on day 3) on plasma levels of cytokines in biobanked samples from 78 patients with bacterial infections included in a randomized controlled trial (INFECIR-2 study).
Results: Circulatory dysfunction and systemic inflammation were extremely unstable in many patients included in the Pilot-PRECIOSA study; these patients had intense and reversible peaks in plasma levels of renin and interleukin 6. Long-term high-dose albumin, but not low-dose albumin, was associated with normalization of serum level of albumin, improved stability of the circulation and left ventricular function, and reduced plasma levels of cytokines (interleukin 6, granulocyte colony-stimulating factor, interleukin 1 receptor antagonist, and vascular endothelial growth factor) without significant changes in portal pressure. The immune-modulatory effects of albumin observed in the Pilot-PRECIOSA study were confirmed in the INFECIR-2 study. In this study, patients given albumin had significant reductions in plasma levels of cytokines.
Conclusions: In an analysis of data from 2 trials (Pilot-PRECIOSA study and INFECIR-2 study), we found that albumin treatment reduced systemic inflammation and cardiocirculatory dysfunction in patients with decompensated cirrhosis. These effects might be responsible for the beneficial effects of albumin therapy on outcomes of patients with decompensated cirrhosis. ClinicalTrials.gov, Numbers: NCT00968695 and NCT03451292.
Replacement therapy in severe hemophilia A leads to factor VIII (FVIII) inhibitors in 30% of patients. Factor VIII gene (F8) mutation type, a family history of inhibitors, ethnicity and intensity of treatment are established risk factors, and were included in two published prediction tools based on regression models. Recently investigated immune regulatory genes could also play a part in immunogenicity. Our objective is to identify bio-clinical and genetic markers for FVIII inhibitor development, taking into account potential genetic high order interactions. The study population consisted of 593 and 79 patients with hemophilia A from centers in Bonn and Frankfurt respectively. Data was collected in the European ABIRISK tranSMART database. A subset of 125 severely affected patients from Bonn with reliable information on first treatment was selected as eligible for risk stratification using a hybrid tree-based regression model (GPLTR). In the eligible subset, 58 (46%) patients developed FVIII inhibitors. Among them, 49 (84%) were “high risk” F8 mutation type. 19 (33%) had a family history of inhibitors. The GPLTR model, taking into account F8 mutation risk, family history of inhibitors and product type, distinguishes two groups of patients: a high-risk group for immunogenicity, including patients with positive HLA-DRB1*15 and genotype G/A and A/A for IL-10 rs1800896, and a low-risk group of patients with negative HLA-DRB1*15 / HLA-DQB1*02 and T/T or G/T for CD86 rs2681401. We show associations between genetic factors and the occurrence of FVIII inhibitor development in severe hemophilia A patients taking into account for high-order interactions using a generalized partially linear tree-based approach.
The volume under review is the result of a conference on historical graffiti held at the Ludwig-Maximilians-University of Munich in 2017. The aim of this book is to analyse — for the first time — graffiti from the ancient, medieval and modern periods in their historical and geographical contexts from an interdisciplinary point of view. Following this comparative approach the authors show the tremendous potential of this nascent area of research by investigating epigraphic material that has been neglected and underestimated by scholars for a long time. ...
While prediction errors (PE) have been established to drive learning through adaptation of internal models, the role of model-compliant events in predictive processing is less clear. Checkpoints (CP) were recently introduced as points in time where expected sensory input resolved ambiguity regarding the validity of the internal model. Conceivably, these events serve as on-line reference points for model evaluation, particularly in uncertain contexts. Evidence from fMRI has shown functional similarities of CP and PE to be independent of event-related surprise, raising the important question of how these event classes relate to one another. Consequently, the aim of the present study was to characterise the functional relationship of checkpoints and prediction errors in a serial pattern detection task using electroencephalography (EEG). Specifically, we first hypothesised a joint P3b component of both event classes to index recourse to the internal model (compared to non-informative standards, STD). Second, we assumed the mismatch signal of PE to be reflected in an N400 component when compared to CP. Event-related findings supported these hypotheses. We suggest that while model adaptation is instigated by prediction errors, checkpoints are similarly used for model evaluation. Intriguingly, behavioural subgroup analyses showed that the exploitation of potentially informative reference points may depend on initial cue learning: Strict reliance on cue-based predictions may result in less attentive processing of these reference points, thus impeding upregulation of response gain that would prompt flexible model adaptation. Overall, present results highlight the role of checkpoints as model-compliant, informative reference points and stimulate important research questions about their processing as function of learning und uncertainty.
The expression of thrombospondin-4 correlates with disease severity in osteoarthritic knee cartilage
(2019)
Osteoarthritis (OA) is a progressive joint disease characterized by a continuous degradation of the cartilage extracellular matrix (ECM). The expression of the extracellular glycoprotein thrombospondin-4 (TSP-4) is known to be increased in injured tissues and involved in matrix remodeling, but its role in articular cartilage and, in particular, in OA remains elusive. In the present study, we analyzed the expression and localization of TSP-4 in healthy and OA knee cartilage by reverse transcription polymerase chain reaction (RT-PCR), immunohistochemistry, and immunoblot. We found that TSP-4 protein expression is increased in OA and that expression levels correlate with OA severity. TSP-4 was not regulated at the transcriptional level but we detected changes in the anchorage of TSP-4 in the altered ECM using sequential protein extraction. We were also able to detect pentameric and fragmented TSP-4 in the serum of both healthy controls and OA patients. Here, the total protein amount was not significantly different but we identified specific degradation products that were more abundant in sera of OA patients. Future studies will reveal if these fragments have the potential to serve as OA-specific biomarkers.
Cardiovascular disease (CVD) remains the leading cause of cardiac morbidity and mortality in the entire world population. Heart failure (HF) is the fastest growing cardiac diagnosis, with an annual incidence of 10 cases per 1000 people in individuals older than 65 [1]. This is partly a reflection of an aging population and success of treatment of acute coronary syndromes with reduced premature mortality due to ischaemic heart disease (IHD), as well as increasing ability to recognise non-ischaemic - intrinsic myocardial processes- due to advances in genetics and imaging. The conventional imaging predictors of outcome in CVD patients primarily include left ventricular ejection fraction (LVEF) and late gadolinium enhancement (LGE) using cardiovascular magnetic resonance (CMR). LVEF represents the main universal, as well as the multimodality biomarker of risk stratification. ...
We study the information flow from the ECB on policy dates since its inception, using tick data. We show that three factors capture about all of the variation in the yield curve but that these are different factors with different variance shares in the window that contains the policy decision announcement and the window that contains the press conference. We also show that the QE-related policy factor has been dominant in the recent period and that Forward Guidance and QE effects have been very persistent on the longer-end of the yield curve. We further show that broad and banking stock indices' responses to monetary policy surprises depended on the perceived nature of the surprises. We find no evidence of asymmetric responses of financial markets to positive and negative surprises, in contrast to the literature on asymmetric real effects of monetary policy. Lastly, we show how to implement our methodology for any policy-related news release, such as policymaker speeches. To carry out the analysis, we construct the Euro Area Monetary Policy Event- Study Database (EA-MPD). This database, which contains intraday asset price changes around the policy decision announcement as well as around the press conference, is a contribution on its own right and we expect it to be the standard in monetary policy research for the euro area.