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Background: Early medical complications are potentially modifiable factors influencing in-hospital outcome. We investigated the influence of acute complications on mortality and poor outcome 3 months after ischemic stroke.
Methods: Data were obtained from patients admitted to one of 13 stroke units of the Berlin Stroke Registry (BSR) who participated in a 3-months-follow up between June 2010 and September 2012. We examined the influence of the cumulative number of early in-hospital complications on mortality and poor outcome (death, disability or institutionalization) 3 months after stroke using multivariable logistic regression analyses and calculated attributable fractions to determine the impact of early complications on mortality and poor outcome.
Results: A total of 2349 ischemic stroke patients alive at discharge from acute care were included in the analysis. Older age, stroke severity, pre-stroke dependency and early complications were independent predictors of mortality 3 months after stroke. Poor outcome was independently associated with older age, stroke severity, pre-stroke dependency, previous stroke and early complications. More than 60% of deaths and poor outcomes were attributed to age, pre-stroke dependency and stroke severity and in-hospital complications contributed to 12.3% of deaths and 9.1% of poor outcomes 3 months after stroke.
Conclusion: The majority of deaths and poor outcomes after stroke were attributed to non-modifiable factors. However, early in-hospital complications significantly affect outcome in patients who survived the acute phase after stroke, underlining the need to improve prevention and treatment of complications in hospital.
Optimal open-loop control, i.e. the application of an analytically derived control rule, is demonstrated for nanooptical excitations using polarization-shaped laser pulses. Optimal spatial near-field localization in gold nanoprisms and excitation switching is realized by applying a shift to the relative phase of the two polarization components. The achieved near-field switching confirms theoretical predictions, proves the applicability of predefined control rules in nanooptical light–matter interaction and reveals local mode interference to be an important control mechanism.
Multiple myeloma (MM) is a plasma cell malignancy with a significant heritable basis. Genome-wide association studies have transformed our understanding of MM predisposition, but individual studies have had limited power to discover risk loci. Here we perform a meta-analysis of these GWAS, add a new GWAS and perform replication analyses resulting in 9,866 cases and 239,188 controls. We confirm all nine known risk loci and discover eight new loci at 6p22.3 (rs34229995, P=1.31 × 10−8), 6q21 (rs9372120, P=9.09 × 10−15), 7q36.1 (rs7781265, P=9.71 × 10−9), 8q24.21 (rs1948915, P=4.20 × 10−11), 9p21.3 (rs2811710, P=1.72 × 10−13), 10p12.1 (rs2790457, P=1.77 × 10−8), 16q23.1 (rs7193541, P=5.00 × 10−12) and 20q13.13 (rs6066835, P=1.36 × 10−13), which localize in or near to JARID2, ATG5, SMARCD3, CCAT1, CDKN2A, WAC, RFWD3 and PREX1. These findings provide additional support for a polygenic model of MM and insight into the biological basis of tumour development.
Transient receptor potential channels are important mediators of thermal and mechanical stimuli and play an important role in neuropathic pain. The contribution of hereditary variants in the genes of transient receptor potential channels to neuropathic pain is unknown. We investigated the frequency of transient receptor potential ankyrin 1, transient receptor potential melastin 8 and transient receptor potential vanilloid 1 single nucleotide polymorphisms and their impact on somatosensory abnormalities in neuropathic pain patients. Within the German Research Network on Neuropathic Pain (Deutscher Forscbungsverbund Neuropathischer Schmerz) 371 neuropathic pain patients were phenotypically characterized using standardized quantitative sensory testing. Pyrosequencing was employed to determine a total of eleven single nucleotide polymorphisms in transient receptor potential channel genes of the neuropathic pain patients and a cohort of 253 German healthy volunteers. Associations of quantitative sensory testing parameters and single nucleotide polymorphisms between and within groups and subgroups, based on sensory phenotypes, were analyzed. Single nucleotide polymorphisms frequencies did not differ between both the cohorts. However, in neuropathic pain patients transient receptor potential ankyrin 1 710G>A (rs920829, E179K) was associated with the presence of paradoxical heat sensation (p=0.03), and transient receptor potential vanilloid 1 1911A>G (rs8065080, I585V) with cold hypoalgesia (p=0.0035). Two main subgroups characterized by preserved (1) and impaired (2) sensory function were identified. In subgroup 1 transient receptor potential vanilloid 1 1911A>G led to significantly less heat hyperalgesia, pinprick hyperalgesia and mechanical hypaesthesia (p=0.006, p=0.005 and p<0.001) and transient receptor potential vanilloid 1 1103C>G (rs222747, M315I) to cold hypaesthesia (p=0.002), but there was absence of associations in subgroup 2. In this study we found no evidence that genetic variants of transient receptor potential channels are involved in the expression of neuropathic pain, but transient receptor potential channel polymorphisms contributed significantly to the somatosensory abnormalities of neuropathic pain patients.
Multidrug-resistant bacteria represent one of the most important health care problems worldwide. While there are numerous drugs available for standard therapy, there are only a few compounds capable of serving as a last resort for severe infections. Therefore, approaches to control multidrug-resistant bacteria must be implemented. Here, a strategy of reactivating the established glycopeptide antibiotic vancomycin by structural modification with polycationic peptides and subsequent fatty acid conjugation to overcome the resistance of multidrug-resistant bacteria was followed. This study especially focuses on the structure–activity relationship, depending on the modification site and fatty acid chain length. The synthesized conjugates showed high antimicrobial potential on vancomycin-resistant enterococci. We were able to demonstrate that the antimicrobial activity of the vancomycin-lipopeptide conjugates depends on the chain length of the attached fatty acid. All conjugates showed good cytocompatibility in vitro and in vivo. Radiolabeling enabled the in vivo determination of pharmacokinetics in Wistar rats by molecular imaging and biodistribution studies. An improved biodistribution profile in comparison to unmodified vancomycin was observed. While vancomycin is rapidly excreted by the kidneys, the most potent conjugate shows a hepatobiliary excretion profile. In conclusion, these results demonstrate the potential of the structural modification of already established antibiotics to provide highly active compounds for tackling multidrug-resistant bacteria.
Radiationless energy transfer is at the core of diverse phenomena, such as light harvesting in photosynthesis\(^1\), energy-transfer-based microspectroscopies\(^2\), nanoscale quantum entanglement\(^3\) and photonic-mode hybridization\(^4\). Typically, the transfer is efficient only for separations that are much shorter than the diffraction limit. This hampers its application in optical communication and quantum information processing, which require spatially selective addressing. Here, we demonstrate highly efficient radiationless coherent energy transfer over a distance of twice the excitation wavelength by combining localized and delocalized\(^5\) plasmonic modes. Analogous to the Tavis-Cummings model, two whispering-gallery-mode antennas\(^6\) placed in the foci of an elliptical plasmonic cavity\(^7\) fabricated from single-crystal gold plates act as a pair of oscillators coupled to a common cavity mode. Time-resolved two-photon photoemission electron microscopy (TR 2P-PEEM) reveals an ultrafast long-range periodic energy transfer in accordance with the simulations. Our observations open perspectives for the optimization and tailoring of mesoscopic energy transfer and long-range quantum emitter coupling.
Multidrug‐resistant bacteria represent one of the biggest challenges facing modern medicine. The increasing prevalence of glycopeptide resistance compromises the efficacy of vancomycin, for a long time considered as the last resort for the treatment of resistant bacteria. To reestablish its activity, polycationic peptides were conjugated to vancomycin. By site‐specific conjugation, derivatives that bear the peptide moiety at four different sites of the antibiotic were synthesized. The most potent compounds exhibited an approximately 1000‐fold increased antimicrobial activity and were able to overcome the most important types of vancomycin resistance. Additional blocking experiments using d‐Ala‐d‐Ala revealed a mode of action beyond inhibition of cell‐wall formation. The antimicrobial potential of the lead candidate FU002 for bacterial infection treatments could be demonstrated in an in vivo study. Molecular imaging and biodistribution studies revealed that conjugation engenders superior pharmacokinetics.
Background
Germline mutations in the BRIP1 gene have been described as conferring a moderate risk for ovarian cancer (OC), while the role of BRIP1 in breast cancer (BC) pathogenesis remains controversial.
Methods
To assess the role of deleterious BRIP1 germline mutations in BC/OC predisposition, 6341 well-characterized index patients with BC, 706 index patients with OC, and 2189 geographically matched female controls were screened for loss-of-function (LoF) mutations and potentially damaging missense variants. All index patients met the inclusion criteria of the German Consortium for Hereditary Breast and Ovarian Cancer for germline testing and tested negative for pathogenic BRCA1/2 variants.
Results
BRIP1 LoF mutations confer a high OC risk in familial index patients (odds ratio (OR) = 20.97, 95% confidence interval (CI) = 12.02–36.57, P < 0.0001) and in the subgroup of index patients with late-onset OC (OR = 29.91, 95% CI = 14.99–59.66, P < 0.0001). No significant association of BRIP1 LoF mutations with familial BC was observed (OR = 1.81 95% CI = 1.00–3.30, P = 0.0623). In the subgroup of familial BC index patients without a family history of OC there was also no apparent association (OR = 1.42, 95% CI = 0.70–2.90, P = 0.3030). In 1027 familial BC index patients with a family history of OC, the BRIP1 mutation prevalence was significantly higher than that observed in controls (OR = 3.59, 95% CI = 1.43–9.01; P = 0.0168). Based on the negative association between BRIP1 LoF mutations and familial BC in the absence of an OC family history, we conclude that the elevated mutation prevalence in the latter cohort was driven by the occurrence of OC in these families. Compared with controls, predicted damaging rare missense variants were significantly more prevalent in OC (P = 0.0014) but not in BC (P = 0.0693) patients.
Conclusions
To avoid ambiguous results, studies aimed at assessing the impact of candidate predisposition gene mutations on BC risk might differentiate between BC index patients with an OC family history and those without. In familial cases, we suggest that BRIP1 is a high-risk gene for late-onset OC but not a BC predisposition gene, though minor effects cannot be excluded.
As multidrug-resistant bacteria represent a concerning burden, experts insist on the need for a dramatic rethinking on antibiotic use and development in order to avoid a post-antibiotic era. New and rapidly developable strategies for antimicrobial substances, in particular substances highly potent against multidrug-resistant bacteria, are urgently required. Some of the treatment options currently available for multidrug-resistant bacteria are considerably limited by side effects and unfavorable pharmacokinetics. The glycopeptide vancomycin is considered an antibiotic of last resort. Its use is challenged by bacterial strains exhibiting various types of resistance. Therefore, in this study, highly active polycationic peptide-vancomycin conjugates with varying linker characteristics or the addition of PEG moieties were synthesized to optimize pharmacokinetics while retaining or even increasing antimicrobial activity in comparison to vancomycin. The antimicrobial activity of the novel conjugates was determined by microdilution assays on susceptible and vancomycin-resistant bacterial strains. VAN1 and VAN2, the most promising linker-modified derivatives, were further characterized in vivo with molecular imaging and biodistribution studies in rodents, showing that the linker moiety influences both antimicrobial activity and pharmacokinetics. Encouragingly, VAN2 was able to undercut the resistance breakpoint in microdilution assays on vanB and vanC vancomycin-resistant enterococci. Out of all PEGylated derivatives, VAN:PEG1 and VAN:PEG3 were able to overcome vanC resistance. Biodistribution studies of the novel derivatives revealed significant changes in pharmacokinetics when compared with vancomycin. In conclusion, linker modification of vancomycin-polycationic peptide conjugates represents a promising strategy for the modulation of pharmacokinetic behavior while providing potent antimicrobial activity.
Multiple myeloma (MM) represents a haematological cancer characterized by the pathological hyper proliferation of antibody-producing B-lymphocytes. Patients typically suffer from kidney malfunction and skeletal disorders. In the context of MM, the transforming growth factor β (TGFβ) member Activin A was recently identified as a promoter of both accompanying symptoms. Because studies have shown that bone morphogenetic protein (BMP)-2-mediated activities are counteracted by Activin A, we analysed whether BMP2, which also binds to the Activin A receptors ActRII and ActRIIB but activates the alternative SMAD-1/5/8 pathway, can be used to antagonize Activin A activities, such as in the context of MM. Therefore three BMP2 derivatives were generated with modified binding activities for the type II (ActRIIB) and/or type I receptor (BMPRIA) showing either increased or decreased BMP2 activity. In the context of MM these BMP2 muteins show two functionalities since they act as a) an anti-proliferative/apoptotic agent against neoplastic B-cells, b) as a bone-formation promoting growth factor. The molecular basis of both activities was shown in two different cellular models to clearly rely on the properties of the investigated BMP2 muteins to compete for the binding of Activin A to the Activin type II receptors. The experimental outcome suggests new therapeutic strategies using BMP2 variants in the treatment of MM-related pathologies.
Background: Dendritic cells (DCs) rendered suppressive by treatment with mitomycin C and loaded with the autoantigen myelin basic protein demonstrated earlier their ability to prevent experimental autoimmune encephalomyelitis (EAE), the animal model for multiple sclerosis (MS). This provides an approach for prophylactic vaccination against autoimmune diseases. For clinical application such DCs are difficult to generate and autoantigens hold the risk of exacerbating the disease.
Methods: We replaced DCs by peripheral mononuclear cells and myelin autoantigens by glatiramer acetate (Copaxone ®), a drug approved for the treatment of MS. Spleen cells were loaded with Copaxone®, incubated with mitomycin C (MICCop) and injected into mice after the first bout of relapsing-remitting EAE. Immunosuppression mediated by MICCop was investigated in vivo by daily assessment of clinical signs of paralysis and in in vitro restimulation assays of peripheral immune cells. Cytokine profiling was performed by enzyme-linked immunosorbent assay (ELISA). Migration of MICCop cells after injection was examined by biodistribution analysis of 111Indium-labelled MICCop. The number and inhibitory activity of CD4+CD25+FoxP3+ regulatory T cells were analysed by histology, flow cytometry and in vitro mixed lymphocyte cultures. In order to assess the specificity of MICCop-induced suppression, treated EAE mice were challenged with the control protein ovalbumin. Humoral and cellular immune responses were then determined by ELISA and in vitro antigen restimulation assay.
Results: MICCop cells were able to inhibit the harmful autoreactive T-cell response and prevented mice from further relapses without affecting general immune responses. Administered MICCop migrated to various organs leading to an increased infiltration of the spleen and the central nervous system with CD4+CD25+FoxP3+ cells displaying a suppressive cytokine profile and inhibiting T-cell responses.
Conclusion: We describe a clinically applicable cell therapeutic approach for controlling relapses in autoimmune encephalomyelitis by specifically silencing the deleterious autoimmune response.
Background
Imaging results are frequently considered as hallmarks of disease by spine surgeons to plan their future treatment strategy. Numerous classification systems have been proposed to quantify or grade lumbar magnetic resonance imaging (MRI) scans and thus objectify imaging findings. The clinical impact of the measured parameters remains, however, unclear. To evaluate the pathological significance of imaging findings in patients with multisegmental degenerative findings, clinicians can perform image-guided local infiltrations to target defined areas such as the facet joints.
The aim of the present retrospective study was to evaluate the correlation of MRI facet joint degeneration and spinal stenosis measurements with improvement obtained by image-guided intraarticular facet joint infiltration.
Methods
Fifty MRI scans of patients with chronic lumbar back pain were graded radiologically using a wide range of classification and measurement systems. The reported effect of facet joint injections at the site was recorded, and a comparative analysis performed.
Results
When we allocated patients according to their reported pain relief, 27 showed no improvement (0–30%), 16 reported good improvement (31–75%) and 7 reported excellent improvement (> 75%). MRI features assessed in this study did, however, not show any relevant correlation with reported pain after facet joint infiltration: Values for Kendall’s tau ranged from \(\tau\) = − 0.190 for neuroforaminal stenosis grading as suggested by Lee, to \(\tau\) = 0.133 for posterior disc height as proposed by Hasegawa.
Conclusion
Despite the trend in evidence-based medicine to provide medical algorithms, our findings underline the continuing need for individualised spine care that, along with imaging techniques or targeted infiltrations, includes diagnostic dimensions such as good patient history and clinical examination to formulate a diagnosis.
Trial registration
ClinicalTrials.gov, NCT03308149, retrospectively registered October 2017
Automation in Software Performance Engineering Based on a Declarative Specification of Concerns
(2019)
Software performance is of particular relevance to software system design, operation, and evolution because it has a significant impact on key business indicators. During the life-cycle of a software system, its implementation, configuration, and deployment are subject to multiple changes that may affect the end-to-end performance characteristics. Consequently, performance analysts continually need to provide answers to and act based on performance-relevant concerns. To ensure a desired level of performance, software performance engineering provides a plethora of methods, techniques, and tools for measuring, modeling, and evaluating performance properties of software systems. However, the answering of performance concerns is subject to a significant semantic gap between the level on which performance concerns are formulated and the technical level on which performance evaluations are actually conducted. Performance evaluation approaches come with different strengths and limitations concerning, for example, accuracy, time-to-result, or system overhead. For the involved stakeholders, it can be an elaborate process to reasonably select, parameterize and correctly apply performance evaluation approaches, and to filter and interpret the obtained results. An additional challenge is that available performance evaluation artifacts may change over time, which requires to switch between different measurement-based and model-based performance evaluation approaches during the system evolution. At model-based analysis, the effort involved in creating performance models can also outweigh their benefits.
To overcome the deficiencies and enable an automatic and holistic evaluation of performance throughout the software engineering life-cycle requires an approach that: (i) integrates multiple types of performance concerns and evaluation approaches, (ii) automates performance model creation, and (iii) automatically selects an evaluation methodology tailored to a specific scenario. This thesis presents a declarative approach —called Declarative Performance Engineering (DPE)— to automate performance evaluation based on a humanreadable specification of performance-related concerns. To this end, we separate the definition of performance concerns from their solution. The primary scientific contributions presented in this thesis are:
A declarative language to express performance-related concerns and a corresponding processing framework:
We provide a language to specify performance concerns independent of a concrete performance evaluation approach. Besides the specification of functional aspects, the language allows to include non-functional tradeoffs optionally. To answer these concerns, we provide a framework architecture and a corresponding reference implementation to process performance concerns automatically. It allows to integrate arbitrary performance evaluation approaches and is accompanied by reference implementations for model-based and measurement-based performance evaluation.
Automated creation of architectural performance models from execution traces:
The creation of performance models can be subject to significant efforts outweighing the benefits of model-based performance evaluation. We provide a model extraction framework that creates architectural performance models based on execution traces, provided by monitoring tools.The framework separates the derivation of generic information from model creation routines. To derive generic information, the framework combines state-of-the-art extraction and estimation techniques. We isolate object creation routines specified in a generic model builder interface based on concepts present in multiple performance-annotated architectural modeling formalisms. To create model extraction for a novel performance modeling formalism, developers only need to write object creation routines instead of creating model extraction software from scratch when reusing the generic framework.
Automated and extensible decision support for performance evaluation approaches:
We present a methodology and tooling for the automated selection of a performance evaluation approach tailored to the user concerns and application scenario. To this end, we propose to decouple the complexity of selecting a performance evaluation approach for a given scenario by providing solution approach capability models and a generic decision engine. The proposed capability meta-model enables to describe functional and non-functional capabilities of performance evaluation approaches and tools at different granularities. In contrast to existing tree-based decision support mechanisms, the decoupling approach allows to easily update characteristics of solution approaches as well as appending new rating criteria and thereby stay abreast of evolution in performance evaluation tooling and system technologies.
Time-to-result estimation for model-based performance prediction:
The time required to execute a model-based analysis plays an important role in different decision processes. For example, evaluation scenarios might require the prediction results to be available in a limited period of time such that the system can be adapted in time to ensure the desired quality of service. We propose a method to estimate the time-to-result for modelbased performance prediction based on model characteristics and analysis parametrization. We learn a prediction model using performancerelevant features thatwe determined using statistical tests. We implement the approach and demonstrate its practicability by applying it to analyze a simulation-based multi-step performance evaluation approach for a representative architectural performance modeling formalism.
We validate each of the contributions based on representative case studies. The evaluation of automatic performance model extraction for two case study systems shows that the resulting models can accurately predict the performance behavior. Prediction accuracy errors are below 3% for resource utilization and mostly less than 20% for service response time. The separate evaluation of the reusability shows that the presented approach lowers the implementation efforts for automated model extraction tools by up to 91%. Based on two case studies applying measurement-based and model-based performance evaluation techniques, we demonstrate the suitability of the declarative performance engineering framework to answer multiple kinds of performance concerns customized to non-functional goals. Subsequently, we discuss reduced efforts in applying performance analyses using the integrated and automated declarative approach. Also, the evaluation of the declarative framework reviews benefits and savings integrating performance evaluation approaches into the declarative performance engineering framework. We demonstrate the applicability of the decision framework for performance evaluation approaches by applying it to depict existing decision trees. Then, we show how we can quickly adapt to the evolution of performance evaluation methods which is challenging for static tree-based decision support systems. At this, we show how to cope with the evolution of functional and non-functional capabilities of performance evaluation software and explain how to integrate new approaches. Finally, we evaluate the accuracy of the time-to-result estimation for a set of machinelearning algorithms and different training datasets. The predictions exhibit a mean percentage error below 20%, which can be further improved by including performance evaluations of the considered model into the training data. The presented contributions represent a significant step towards an integrated performance engineering process that combines the strengths of model-based and measurement-based performance evaluation. The proposed performance concern language in conjunction with the processing framework significantly reduces the complexity of applying performance evaluations for all stakeholders. Thereby it enables performance awareness throughout the software engineering life-cycle. The proposed performance concern language removes the semantic gap between the level on which performance concerns are formulated and the technical level on which performance evaluations are actually conducted by the user.