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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.
More recently, it became clear that conclusions drawn from traditional ecological theory may be altered substantially if the spatial dimension of species interactions is considered explicitly. Regardless of the details of these models, spatially explicit simulations of ecological processes have nearly universally shown that spatial or spatio-temporal patterns in species distributions can emerge even from homogeneous starting conditions; limited dispersal is one of the key factors responsible for the development of such aggregated and patchy distributions (cf., Pacala 1986, Holmes et al. 1994, Molofsky 1994, Tilman 1994, Bascompte and Sole 1995, 1997, 1998, Jeltsch et al. 1999). In line with these ideas, we wish to draw attention to the fact that in heterogeneous landscapes differences in characteristic dispersal distances between species are a sufficient precondition for the emergence of a successional pattern. We will use a simple, spatially explicit simulation program to demonstrate the validity of this statement. We will also show that the speed of the successional progress depends on scale and heterogeneity in the distribution of suitable habitat.
Background
The aim of this study was to quantify the variability in spinal radiosurgery (SRS) planning practices between five international institutions, all member of the Elekta Spine Radiosurgery Research Consortium.
Methods
Four institutions provided one representative patient case each consisting of the medical history, CT and MR imaging. A step-wise planning approach was used where, after each planning step a consensus was generated that formed the basis for the next planning step. This allowed independent analysis of all planning steps of CT-MR image registration, GTV definition, CTV definition, PTV definition and SRS treatment planning. In addition, each institution generated one additional SRS plan for each case based on intra-institutional image registration and contouring, independent of consensus results.
Results
Averaged over the four cases, image registration variability ranged between translational 1.1 mm and 2.4 mm and rotational 1.1° and 2.0° in all three directions. GTV delineation variability was 1.5 mm in axial and 1.6 mm in longitudinal direction averaged for the four cases. CTV delineation variability was 0.8 mm in axial and 1.2 mm in longitudinal direction. CTV-to-PTV margins ranged between 0 mm and 2 mm according to institutional protocol. Delineation variability was 1 mm in axial directions for the spinal cord. Average PTV coverage for a single fraction18 Gy prescription was 87 ± 5 %; Dmin to the PTV was 7.5 ± 1.8 Gy averaged over all cases and institutions. Average Dmax to the PRV_SC (spinal cord + 1 mm) was 10.5 ± 1.6 Gy and the average Paddick conformity index was 0.69 ± 0.06.
Conclusions
Results of this study reflect the variability in current practice of spine radiosurgery in large and highly experienced academic centers. Despite close methodical agreement in the daily workflow, clinically significant variability in all steps of the treatment planning process was demonstrated. This may translate into differences in patient clinical outcome and highlights the need for consensus and established delineation and planning criteria.
Background
Although 5-HTTLPR has been shown to influence the risk of life stress-induced depression in the majority of studies, others have produced contradictory results, possibly due to weak effects and/or sample heterogeneity.
Methods
In the present study we investigated how age, type and intensity of life-stressors modulate the effect of 5-HTTLPR on depression and anxiety in a European population cohort of over 2300 subjects. Recent negative life events (RLE), childhood adversity (CHA), lifetime depression, Brief Symptoms Inventory (BSI) depression and anxiety scores were determined in each subject. Besides traditional statistical analysis we calculated Bayesian effect strength and relevance of 5-HTTLPR genotypes in specified models.
Results
The short (s) low expressing allele showed association with increased risk of depression related phenotypes, but all nominally significant effects would turn to non-significant after correction for multiple testing in the traditional analysis. Bayesian effect strength and relevance analysis, however, confirmed the role of 5-HTTLPR. Regarding current (BSI) and lifetime depression 5-HTTLPR-by-RLE interactions were confirmed. Main effect, with other words direct association, was supported with BSI anxiety. With more frequent RLE the prevalence or symptoms of depression increased in ss carriers. Although CHA failed to show an interaction with 5-HTTLPR, in young subjects CHA sensitized towards the depression promoting effect of even mild RLE. Furthermore, the direct association of anxiety with the s allele was driven by young (\(\leq\)30) individuals.
Limitations
Our study is cross-sectional and applies self-report questionnaires.
Conclusions
Albeit 5-HTTLPR has only weak/moderate effects, the s allele is directly associated with anxiety and modulates development of depression in homogeneous subgroups.
Objectives
To determine sleep bruxism (SB) behavior during five consecutive nights and to identify correlations between SB episodes per hour (SB index) and sleep-time masseter-muscle activity (sMMA).
Material and methods
Thirty-one participants were included in the study. Of these, 10 were classified as sleep bruxers (group SB-1) and nine as non-sleep bruxers (group non-SB). The bruxism status of these 19 patients was identified by means of questionnaires, an assessment of clinical symptoms, and electromyographic/electrocardiographic data (Bruxoff® device). The remaining 12 participants were also identified as bruxers, but based exclusively on data from the Bruxoff device (group SB-2). Data analysis included descriptive statistics and Spearman’s correlation to assess the relationship between the SB index and sMMA.
Results
Participants in group SB-1 showed an overall mean SB index of 3.1 ± 1.6 and a mean total sMMA per night of 62.9 ± 38.3. Participants in group SB-2 had an overall mean SB index of 2.7 ± 1.5 and a mean total sMMA of 56.0 ± 29.3. In the non-SB group, participants showed an overall mean SB index of 0.8 ± 0.5 and a mean total sMMA of 56.8 ± 30.3. Spearman’s correlation yielded values of − 0.27 to 0.71 for the correlation between sMMA and SB index.
Conclusions
The data revealed variable SB activity and the absence of a reliable correlation between sMMA and the SB index.
Clinical relevance
The high variation in SB activity and lack of correlation between sMMA and the SB index should be considered when diagnosing SB.
Trial registration
Clinical Trials [NIH], clinical trial no. NCT03039985.
Floral nectar is considered the most important floral reward for attracting pollinators. It contains large amounts of carbohydrates besides variable concentrations of amino acids and thus represents an important food source for many pollinators. Its nutrient content and composition can, however, strongly vary within and between plant species. The factors driving this variation in nectar quality are still largely unclear.
We investigated factors underlying interspecific variation in macronutrient composition of floral nectar in 34 different grassland plant species. Specifically, we tested for correlations between the phylogenetic relatedness and morphology of plants and the carbohydrate (C) and total amino acid (AA) composition and C:AA ratios of nectar.
We found that compositions of carbohydrates and (essential) amino acids as well as C:AA ratios in nectar varied significantly within and between plant species. They showed no clear phylogenetic signal. Moreover, variation in carbohydrate composition was related to family‐specific structural characteristics and combinations of morphological traits. Plants with nectar‐exposing flowers, bowl‐ or parabolic‐shaped flowers, as often found in the Apiaceae and Asteraceae, had nectar with higher proportions of hexoses, indicating a selective pressure to decelerate evaporation by increasing nectar osmolality.
Our study suggests that variation in nectar nutrient composition is, among others, affected by family‐specific combinations of morphological traits. However, even within species, variation in nectar quality is high. As nectar quality can strongly affect visitation patterns of pollinators and thus pollination success, this intra‐ and interspecific variation requires more studies to fully elucidate the underlying causes and the consequences for pollinator behaviour.
This doctoral thesis is concerned with the mathematical modeling of magnetoelastic materials and the analysis of PDE systems describing these materials and obtained from a variational approach.
The purpose is to capture the behavior of elastic particles that are not only magnetic but exhibit a magnetic domain structure which is well described by the micromagnetic energy and the Landau-Lifshitz-Gilbert equation of the magnetization. The equation of motion for the material’s velocity is derived in a continuum mechanical setting from an energy ansatz. In the modeling process, the focus is on the interplay between Lagrangian and Eulerian coordinate systems to combine elasticity and magnetism in one model without the assumption of small deformations.
The resulting general PDE system is simplified using special assumptions. Existence of weak solutions is proved for two variants of the PDE system, one including gradient flow dynamics on the magnetization, and the other featuring the Landau-Lifshitz-Gilbert equation. The proof is based on a Galerkin method and a fixed point argument. The analysis of the PDE system with the Landau-Lifshitz-Gilbert equation uses a more involved approach to obtain weak solutions based on G. Carbou and P. Fabrie 2001.
Many modern statistically efficient methods come with tremendous computational challenges, often leading to large-scale optimisation problems. In this work, we examine such computational issues for recently developed estimation methods in nonparametric regression with a specific view on image denoising. We consider in particular certain variational multiscale estimators which are statistically optimal in minimax sense, yet computationally intensive. Such an estimator is computed as the minimiser of a smoothness functional (e.g., TV norm) over the class of all estimators such that none of its coefficients with respect to a given multiscale dictionary is statistically significant. The so obtained multiscale Nemirowski-Dantzig estimator (MIND) can incorporate any convex smoothness functional and combine it with a proper dictionary including wavelets, curvelets and shearlets. The computation of MIND in general requires to solve a high-dimensional constrained convex optimisation problem with a specific structure of the constraints induced by the statistical multiscale testing criterion. To solve this explicitly, we discuss three different algorithmic approaches: the Chambolle-Pock, ADMM and semismooth Newton algorithms. Algorithmic details and an explicit implementation is presented and the solutions are then compared numerically in a simulation study and on various test images. We thereby recommend the Chambolle-Pock algorithm in most cases for its fast convergence. We stress that our analysis can also be transferred to signal recovery and other denoising problems to recover more general objects whenever it is possible to borrow statistical strength from data patches of similar object structure.
Acceleration is a central aim of clinical and technical research in magnetic resonance imaging (MRI) today, with the potential to increase robustness, accessibility and patient comfort, reduce cost, and enable entirely new kinds of examinations. A key component in this endeavor is image reconstruction, as most modern approaches build on advanced signal and image processing. Here, deep learning (DL)-based methods have recently shown considerable potential, with numerous publications demonstrating benefits for MRI reconstruction. However, these methods often come at the cost of an increased risk for subtle yet critical errors. Therefore, the aim of this thesis is to advance DL-based MRI reconstruction, while ensuring high quality and fidelity with measured data. A network architecture specifically suited for this purpose is the variational network (VN). To investigate the benefits these can bring to non-Cartesian cardiac imaging, the first part presents an application of VNs, which were specifically adapted to the reconstruction of accelerated spiral acquisitions. The proposed method is compared to a segmented exam, a U-Net and a compressed sensing (CS) model using qualitative and quantitative measures. While the U-Net performed poorly, the VN as well as the CS reconstruction showed good output quality. In functional cardiac imaging, the proposed real-time method with VN reconstruction substantially accelerates examinations over the gold-standard, from over 10 to just 1 minute. Clinical parameters agreed on average.
Generally in MRI reconstruction, the assessment of image quality is complex, in particular for modern non-linear methods. Therefore, advanced techniques for precise evaluation of quality were subsequently demonstrated.
With two distinct methods, resolution and amplification or suppression of noise are quantified locally in each pixel of a reconstruction. Using these, local maps of resolution and noise in parallel imaging (GRAPPA), CS, U-Net and VN reconstructions were determined for MR images of the brain. In the tested images, GRAPPA delivers uniform and ideal resolution, but amplifies noise noticeably. The other methods adapt their behavior to image structure, where different levels of local blurring were observed at edges compared to homogeneous areas, and noise was suppressed except at edges. Overall, VNs were found to combine a number of advantageous properties, including a good trade-off between resolution and noise, fast reconstruction times, and high overall image quality and fidelity of the produced output. Therefore, this network architecture seems highly promising for MRI reconstruction.