PURPOSE OF REVIEWTo review new advances in inclusion body myositis (IBM) and discuss them in light of current knowledge on diagnosis, pathomechanisms, and treatment perspectives.
RECENT FINDINGSIBM ...is a treatment refractory inflammatory myopathy in middle-aged patients that leads to a slow, relentlessly progressive muscle weakness, and atrophy. Recent data collections suggest that mortality in IBM patients is somewhat elevated compared with the general population. One major risk factor for death is severe dysphagia, which can now be determined by a novel real-time MRI technique. Recently, proposed diagnostic criteria with a combination of clinical and histopathological features have improved sensitivity and specificity. cytosolic 5’-nucleotidase 1A antibodies have been characterized in IBM patients and their pathophysiologic role has recently been studied. New inflammatory pathomechanisms have been identified in IBM muscle and may help to design novel treatment strategies. A broad spectrum of immunosuppressive and immunomodulatory trials have been conducted, but – so far– no effective treatment is available. Current therapeutic attempts aim to block the myostatin pathway or restore the protein homeostasis.
SUMMARYThe expanding knowledge of the complex disease, the refinement of diagnostic criteria, and developments in diagnostic procedures are expected to foster the much needed design of new treatment approaches for future clinical trials.
Understanding the spatial distribution of soil organic carbon (SOC) content over different climatic regions will enhance our knowledge of carbon gains and losses due to climatic change. However, ...little is known about the SOC content in the contrasting arid and sub-humid regions of Iran, whose complex SOC–landscape relationships pose a challenge to spatial analysis. Machine learning (ML) models with a digital soil mapping framework can solve such complex relationships. Current research focusses on ensemble ML models to increase the accuracy of prediction. The usual ensemble method is boosting or weighted averaging. This study proposes a novel ensemble technique: the stacking of multiple ML models through a meta-learning model. In addition, we tested the ensemble through rescanning the covariate space to maximize the prediction accuracy. We first applied six state-of-the-art ML models (i.e., Cubist, random forests (RF), extreme gradient boosting (XGBoost), classical artificial neural network models (ANN), neural network ensemble based on model averaging (AvNNet), and deep learning neural networks (DNN)) to predict and map the spatial distribution of SOC content at six soil depth intervals for both regions. In addition, the stacking of multiple ML models through a meta-learning model with/without rescanning the covariate space were tested and applied to maximize the prediction accuracy. Out of six ML models, the DNN resulted in the best modeling accuracies, followed by RF, XGBoost, AvNNet, ANN, and Cubist. Importantly, the stacking of models indicated a significant improvement in the prediction of SOC content, especially when combined with rescanning the covariate space. For instance, the RMSE values for SOC content prediction of the upper 0–5 cm of the soil profiles of the arid site and the sub-humid site by the proposed stacking approaches were 17% and 9% respectively, less than that obtained by the DNN models—the best individual model. This indicates that rescanning the original covariate space by a meta-learning model can extract more information and improve the SOC content prediction accuracy. Overall, our results suggest that the stacking of diverse sets of models could be used to more accurately estimate the spatial distribution of SOC content in different climatic regions.
Triantennary N-acetyl galactosamine (GalNAc, GN3: ), a high-affinity ligand for the hepatocyte-specific asialoglycoprotein receptor (ASGPR), enhances the potency of second-generation gapmer antisense ...oligonucleotides (ASOs) 6-10-fold in mouse liver. When combined with next-generation ASO designs comprised of short S-cEt (S-2'-O-Et-2',4'-bridged nucleic acid) gapmer ASOs, ∼ 60-fold enhancement in potency relative to the parent MOE (2'-O-methoxyethyl RNA) ASO was observed. GN3: -conjugated ASOs showed high affinity for mouse ASGPR, which results in enhanced ASO delivery to hepatocytes versus non-parenchymal cells. After internalization into cells, the GN3: -ASO conjugate is metabolized to liberate the parent ASO in the liver. No metabolism of the GN3: -ASO conjugate was detected in plasma suggesting that GN3: acts as a hepatocyte targeting prodrug that is detached from the ASO by metabolism after internalization into the liver. GalNAc conjugation also enhanced potency and duration of the effect of two ASOs targeting human apolipoprotein C-III and human transthyretin (TTR) in transgenic mice. The unconjugated ASOs are currently in late stage clinical trials for the treatment of familial chylomicronemia and TTR-mediated polyneuropathy. The ability to translate these observations in humans offers the potential to improve therapeutic index, reduce cost of therapy and support a monthly dosing schedule for therapeutic suppression of gene expression in the liver using ASOs.
This paper investigates the performance and fuel-saving effect of a velocity control algorithm on modern 50 cc scooters (Euro 5). The European Parliament has adopted major CO2 emission reductions by ...2030. But modern combustion-powered scooters are inefficiently restricted and emit unnecessary amounts of CO2. Replacing the original restriction method with the system presented in this paper, the engine’s operating point is being improved significantly. A Throttle-by-Wire-System senses the rider’s throttle command and manipulates the throttle valve. A redundant wheel speed sensor measures the precise vehicle velocity using the Hall effect. The entire system is managed by a central ECU, executing the actual velocity control, fail-safe functions, power supply and handling inputs/outputs. For velocity control, an adaptive PI-controller has been simulated, virtually tuned and implemented, limiting the max. velocity regulated by legal constraints (45 km/h). In this way, the environmentally harmful restrictors used today can be bypassed. By implementing a human–machine interface, including a virtual dashboard, the system is capable of interfacing with the rider. For evaluation purposes a measurement box has been developed, logging vehicle orientation, system/control variables and engine parameters. A Peugeot Kisbee 50 4T (Euro 5) is serving as test vehicle. Finally, the system has been evaluated regarding performance and fuel efficiency both through simulation and road testing. Fuel savings of 13.6% in real-world test scenarios were achieved while maintaining vehicle performance.
•Efficiency is increased and the throttle valve opening is reduced by 50%.•The controlled air supply minimizes the fuel injected by up to 25%.•Significant improvements of fuel consumption and CO2 emissions by 14%.•Consistent performance is demonstrated by using energy more effectively.
Zwei Jahrzehnte nach seinem Tod ist das Werk des Soziologen Pierre Bourdieu aus vielen Geistes-, Kultur- und Sozialwissenschaften nicht mehr wegzudenken. Wie aber sieht es mit der Anwendung der ...Bourdieuschen Konzepte und Theorien in der Germanistik aus? Der Band bilanziert den Ertrag der entsprechenden sprach- und literaturwissenschaftlichen Forschung. Zugleich werden die Zukunftspotentiale einer an Bourdieu orientierten Germanistik abgesteckt. Dabei geht es auch um die Frage, inwiefern Bourdieus Arbeiten einen gemeinsamen produktiven Bezugsrahmen für einen stärkeren Austausch zwischen Sprach- und Literaturwissenschaft bieten können.
•Annual soil erosion rates decreased with tree species richness.•Tree diversity reduced soil erosion by affecting tree canopy and biological soil crust development.•Restoring species-rich plantations ...may be beneficial for soil erosion control.
Biodiversity plays a crucial role in forest ecosystem sustainability. However, it is unclear how tree diversity and especially the relationship between diversity and ecosystem functioning affect soil erosion. Based on a forest biodiversity and ecosystem functioning experiment established in subtropical China (BEF China), we measured soil erosion at four tree species richness levels (monocultures, 8 tree species, 16 tree species and 24 species stands) during the rainy seasons from 2013 to 2015. The result showed that mean annual soil erosion rates were detected to decrease with tree species richness significantly over the observed three years. Leaf area index (LAI) and biological soil crusts (BSCs) were the two main factors driving soil erosion within tree stands of different species richness. Positive effects of tree species richness on tree canopy structure and BSCs might drive the reduction of soil erosion in the earlier successional stage after afforestation of tree plantations. Therefore, we highlight the important influence of tree species richness on soil erosion control, hydrologic processes and thus sustainable ecology services.
The paper investigates potentials and challenges during the interpretation of prehistoric settlement dynamics based on large archaeological datasets. Exemplarily, this is carried out using a database ...of 1365 Neolithic sites in the Weiße Elster river catchment in Central Germany located between the southernmost part of the Northern German Plain and the Central Uplands. The recorded sites are systematically pre-processed with regard to their chronology, functional interpretation and spatial delineation. The quality of the dataset is reviewed by analyzing site distributions with respect to field surveys and modern land use. The Random Forests machine learning algorithm is used to examine the impact of terrain covariates on the depth of sites and pottery preservation. Neolithic settlement dynamics are studied using Site Exploitation Territories, and site frequencies per century are used to compare the intensity of land use with adjacent landscapes. The results show that the main trends of the Neolithic settlement dynamics can be derived from the dataset. However, Random Forests analyses indicate poor pottery preservation in the Central Uplands and a superimposition of Neolithic sites in the southernmost part of the Northern German Plain. Throughout the Neolithic the margins between soils on loess and the Weiße Elster floodplain were continuously settled, whereas only Early and Late Neolithic land use also extended into the Central Uplands. These settlement patterns are reflected in the results of the Site Exploitation Territories analyses and explained with environmental economic factors. Similar with adjacent landscapes the Middle Neolithic site frequency is lower compared to earlier and later periods.
Targeted delivery of antisense oligonucleotides (ASO) to hepatocytes via the asialoglycoprotein receptor (ASGR) has improved the potency of ASO drugs ∼30-fold in the clinic (1). In order to fully ...characterize the effect of GalNAc valency, oligonucleotide length, flexibility and chemical composition on ASGR binding, we tested and validated a fluorescence polarization competition binding assay. The ASGR binding, and in vitro and in vivo activities of 1, 2 and 3 GalNAc conjugated single stranded and duplexed ASOs were studied. Two and three GalNAc conjugated single stranded ASOs bind the ASGR with the strongest affinity and display optimal in vitro and in vivo activities. 1 GalNAc conjugated ASOs showed 10-fold reduced ASGR binding affinity relative to three GalNAc ASOs but only 2-fold reduced activity in mice. An unexpected observation was that the ASGR also appears to play a role in the uptake of unconjugated phosphorothioate modified ASOs in the liver as evidenced by the loss of activity of GalNAc conjugated and unconjugated ASOs in ASGR knockout mice. Our results provide insights into how backbone charge and chemical composition assist in the binding and internalization of highly polar anionic single stranded oligonucleotides into cells and tissues.
This paper shows that memory-based learning (MBL) is a very promising approach to deal with complex soil visible and near infrared (vis–NIR) datasets. The main goal of this work was to develop a ...suitable MBL approach for soil spectroscopy. Here we introduce the spectrum-based learner (SBL) which basically is equipped with an optimized principal components distance (oPC-M) and a Gaussian process regression. Furthermore, this approach combines local distance matrices and the spectral features as predictor variables. Our SBL was tested in two soil spectral libraries: a regional soil vis–NIR library of State of São Paulo (Brazil) and a global soil vis–NIR library. We calibrated models of clay content (CC), organic carbon (OC) and exchangeable Ca (Ca++). In order to compare the predictive performance of our SBL with other approaches, the following algorithms were used: partial least squares (PLS) regression, support vector regression machines (SVM), locally weighted PLS regression (LWR) and LOCAL. In all cases our SBL algorithm outperformed the accuracy of the remaining algorithms. Here we show that the SBL presents great potential for predicting soil attributes in large and diverse vis–NIR datasets. In addition we also show that soil vis–NIR distance matrices can be used to further improve the prediction performance of spectral models.
► We developed a new local vis–NIR modeling approach. ► Distance matrices were used as source of additional predictor variables. ► The new approach outperforms other regression algorithms.
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