julilili42/papers huggingface dataset:
Preparing n-of-1 Antisense Oligonucleotide Treatments for Rare Neurological Diseases in Europe: Genetic, Regulatory, and Ethical Perspectives
2021-09-30

Antisense oligonucleotide (ASO) therapies present a promising disease-modifying treatment approach for rare neurological diseases (RNDs). However, the current focus is on "more common" RNDs, leaving a large share of RND patients still without prospect of disease-modifying treatments. In response to this gap, n-of-1 ASO treatment approaches are targeting ultrarare or even private variants. While highly attractive, this emerging, academia-driven field of ultimately individualized precision medicine is in need of systematic guidance and standards, which will allow global scaling of this approach. We provide here genetic, regulatory, and ethical perspectives for preparing n-of-1 ASO treatments and research programs, with a specific focus on the European context. By example of splice modulating ASOs, we outline genetic criteria for variant prioritization, chart the regulatory field of n-of-1 ASO treatment development in Europe, and propose an ethically informed classification for n-of-1 ASO treatment strategies and level of outcome assessments. To accommodate the ethical requirements of both individual patient benefit and knowledge gain, we propose a stronger integration of patient care and clinical research when developing novel n-of-1 ASO treatments: each single trial of therapy should inherently be driven to generate generalizable knowledge, be registered in a ASO treatment registry, and include assessment of generic outcomes, which allow aggregated analysis across n-of-1 trials of therapy.
Cardiovascular consequences of viral infections: from COVID to other viral diseases
2021-09-30

Abstract Infection of the heart muscle with cardiotropic viruses is one of the major aetiologies of myocarditis and acute and chronic inflammatory cardiomyopathy (DCMi). However, viral myocarditis and subsequent dilated cardiomyopathy is still a challenging disease to diagnose and to treat and is therefore a significant public health issue globally. Advances in clinical examination and thorough molecular genetic analysis of intramyocardial viruses and their activation status have incrementally improved our understanding of molecular pathogenesis and pathophysiology of viral infections of the heart muscle. To date, several cardiotropic viruses have been implicated as causes of myocarditis and DCMi. These include, among others, classical cardiotropic enteroviruses (Coxsackieviruses B), the most commonly detected parvovirus B19, and human herpes virus 6. A newcomer is the respiratory virus that has triggered the worst pandemic in a century, SARS-CoV-2, whose involvement and impact in viral cardiovascular disease is under scrutiny. Despite extensive research into the pathomechanisms of viral infections of the cardiovascular system, our knowledge regarding their treatment and management is still incomplete. Accordingly, in this review, we aim to explore and summarize the current knowledge and available evidence on viral infections of the heart. We focus on diagnostics, clinical relevance and cardiovascular consequences, pathophysiology, and current and novel treatment strategies.
Synthesis and Characterization of a Novel Biocompatible Alloy, Ti-Nb-Zr-Ta-Sn
2021-09-30

Many current-generation biomedical implants are fabricated from the Ti-6Al-4V alloy because it has many attractive properties, such as low density and biocompatibility. However, the elastic modulus of this alloy is much larger than that of the surrounding bone, leading to bone resorption and, eventually, implant failure. In the present study, we synthesized and performed a detailed analysis of a novel low elastic modulus Ti-based alloy (Ti-28Nb-5Zr-2Ta-2Sn (TNZTS alloy)) using a variety of methods, including scanning electron microscopy, transmission electron microscopy, X-ray diffraction, and tensile test. Additionally, the in vitro biocompatibility of the TNZTS alloy was evaluated using SCP-1, SaOs-2, and THP-1 cell lines and primary human osteoblasts. Compared to Ti-6Al-4V, the elastic modulus of TNZTS alloy was significantly lower, while measures of its in vitro biocompatibility are comparable. O2 plasma treatment of the surface of the alloy significantly increased its hydrophilicity and, hence, its in vitro biocompatibility. TNZTS alloy specimens did not induce the release of cytokines by macrophages, indicating that such scaffolds would not trigger inflammatory responses. The present results suggest that the TNZTS alloy may have potential as an alternative to Ti-6Al-4V.
Intracellular Storage Reduces Stoichiometric Imbalances in Soil Microbial Biomass – A Theoretical Exploration
2021-09-30

Microbial intracellular storage is key to defining microbial resource use strategies and could contribute to carbon (C) and nutrient cycling. However, little attention has been devoted to the role of intracellular storage in soil processes, in particular from a theoretical perspective. Here we fill this gap by integrating intracellular storage dynamics into a microbially explicit soil C and nutrient cycling model. Two ecologically relevant modes of storage are considered: reserve storage, in which elements are routed to a storage compartment in proportion to their uptake rate, and surplus storage, in which elements in excess of microbial stoichiometric requirements are stored and limiting elements are remobilized from storage to fuel growth and microbial maintenance. Our aim is to explore with this model how these different storage modes affect the retention of C and nutrients in active microbial biomass under idealized conditions mimicking a substrate pulse experiment. As a case study, we describe C and phosphorus (P) dynamics using literature data to estimate model parameters. Both storage modes enhance the retention of elements in microbial biomass, but the surplus storage mode is more effective to selectively store or remobilize C and nutrients according to microbial needs. Enhancement of microbial growth by both storage modes is largest when the substrate C:nutrient ratio is high (causing nutrient limitation after substrate addition) and the amount of added substrate is large. Moreover, storage increases biomass nutrient retention and growth more effectively when resources are supplied in a few large pulses compared to several smaller pulses (mimicking a nearly constant supply), which suggests storage to be particularly relevant in highly dynamic soil microhabitats. Overall, our results indicate that storage dynamics are most important under conditions of strong stoichiometric imbalance and may be of high ecological relevance in soil environments experiencing large variations in C and nutrient supply.
Automated HW/SW co-design for edge AI
2021-09-30

Gigantic rates of data production in the era of Big Data, Internet of Thing (IoT), and Smart Cyber Physical Systems (CPS) pose incessantly escalating demands for massive data processing, storage, and transmission while continuously interacting with the physical world using edge sensors and actuators. For IoT systems, there is now a strong trend to move the intelligence from the cloud to the edge or the extreme edge (known as TinyML). Yet, this shift to edge AI systems requires to design powerful machine learning systems under very strict resource constraints. This poses a difficult design task that needs to take the complete system stack from machine learning algorithm, to model optimization and compression, to software implementation, to hardware platform and ML accelerator design into account. This paper discusses the open research challenges to achieve such a holistic Design Space Exploration for a HW/SW Co-design for Edge AI Systems and discusses the current state with three currently developed flows: one design flow for systems with tightly-coupled accelerator architectures based on RISC-V, one approach using loosely-coupled, application-specific accelerators as well as one framework that integrates software and hardware optimization techniques to built efficient Deep Neural Network (DNN) systems.
Detection of diabetes from whole-body MRI using deep learning
2021-09-30

Obesity is one of the main drivers of type 2 diabetes, but it is not uniformly associated with the disease. The location of fat accumulation is critical for metabolic health. Specific patterns of body fat distribution, such as visceral fat, are closely related to insulin resistance. There might be further, hitherto unknown, features of body fat distribution that could additionally contribute to the disease. We used machine learning with dense convolutional neural networks to detect diabetes-related variables from 2371 T1-weighted whole-body MRI data sets. MRI was performed in participants undergoing metabolic screening with oral glucose tolerance tests. Models were trained for sex, age, BMI, insulin sensitivity, HbA1c, and prediabetes or incident diabetes. The results were compared with those of conventional models. The area under the receiver operating characteristic curve was 87% for the type 2 diabetes discrimination and 68% for prediabetes, both superior to conventional models. Mean absolute regression errors were comparable to those of conventional models. Heatmaps showed that lower visceral abdominal regions were critical in diabetes classification. Subphenotyping revealed a group with high future diabetes and microalbuminuria risk.Our results show that diabetes is detectable from whole-body MRI without additional data. Our technique of heatmap visualization identifies plausible anatomical regions and highlights the leading role of fat accumulation in the lower abdomen in diabetes pathogenesis.
Challenging German physical education teacher educators’ health-related beliefs through Cooperative Planning
2021-09-30

Abstract Physical education teacher educators’ health-related beliefs can impact public health. An interactive knowledge-to-action approach, such as Cooperative Planning, might challenge the health-related beliefs of physical education teacher educators, thus contributing to innovation in teacher education. We investigated what health-related beliefs physical education teacher educators had before a Cooperative Planning intervention, how these developed throughout the intervention and how teacher educators’ perceptions of Cooperative Planning can explain the identified changes and continuities. We established two Cooperative Planning groups that included physical education teacher educators (university lecturers and teacher trainers), researchers, study course coordinators and prospective teachers. The data of 13 teacher educators were collected before (t0) and after (t1) the Cooperative Planning using two methods: observations of teaching practice and interviews. The data analysis was based on the following categories: (i) epistemic beliefs about health (e.g. salutogenic understanding), (ii) beliefs about the health topic in physical education (e.g. health-related knowledge and understanding), (iii) beliefs about the health topic in physical education teacher education (e.g. health-related pedagogical content knowledge) and (iv) process-related beliefs about Cooperative Planning. The findings revealed that teacher educators’ health-related beliefs were rather stable but could be challenged through a Cooperative Planning intervention. Epistemic beliefs about health remained, whereas more practice-related beliefs about the health topic in physical education and physical education teacher education changed in individual ways. Here, a change in beliefs was more likely when the participants were open to change and when Cooperative Planning offered opportunities to engage in concrete lesson planning.
Body exposure, its forms of delivery and potentially associated working mechanisms: How to move the field forward
2021-09-30

Background Body image disturbance (BID) is a hallmark feature of eating disorders (EDs) and has proven to be involved in their etiology and maintenance. Therefore, the targeting of BID in treatment is crucial, and has been incorporated in various treatment manuals. One of the most common techniques in the treatment of BID is body exposure (BE), the confrontation with one’s own body. BE has been found to be effective in individuals with EDs or high body dissatisfaction. However, BE is applied in a multitude of ways, most of which are based on one or a combination of the hypothesized underlying working mechanisms, with no differential effectiveness known so far. Method The aim of this paper is to selectively review the main hypothesized working mechanisms of BE and their translation into therapeutic approaches. Results and Conclusion Specifically, we underline that studies are needed to pinpoint the proposed mechanisms and to develop an empirically informed theoretical model of BE. We provide a framework for future studies in order to identify working mechanisms and increase effectiveness of BE.
Memory of the U.K.’s 2016 EU referendum: The effects of valence on the long-term measures of a public event.
2021-09-30

Emotional public events, relative to nonemotional ones, are typically remembered more accurately, more vividly, and with more confidence. However, the majority of previous studies investigating this have focused on negative public events and less is known about positive ones. The current study examined whether positive and negative public events were remembered in a similar manner by assessing individuals' memory for the time when they learned the results of the United Kingdom's 2016 Referendum on its European Union (EU) membership. Participants included U.K. participants who voted to <i>leave</i> the EU in the referendum and found the event highly positive, U.K. participants who voted to remain in the EU and found the event highly negative, and U.S. participants who did not vote and found the event neutral. Data from a total of 851 participants were assessed at four time points over the course of 16 months. Growth curve modeling showed that differences in memory between participants in the Remain group (who reported the highest levels of negative emotion) and those in the Leave group (who reported the highest levels of positive emotion) emerged over time. Specifically, Remain participants maintained higher levels of memory consistency than Leave participants, whereas Leave participants maintained higher levels of memory confidence than Remain participants. These results indicate that positive and negative public events are remembered differently, such that negative valence enhances memory accuracy, while positive valence results in overconfidence. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Evidence of weight-based representations of gravitational motion.
2021-09-30

A hypothesis gaining increasing popularity is that laypeople's representations of physical phenomena might be driven by internalized physical laws. In three experiments, we tested if such hypothesis holds true for the representation of gravitational motion. Participants were presented with realistic, real-scale virtual spheres falling vertically downward from about 2 m high. The spheres appeared to be made of either polystyrene or wood. In Experiment 1, participants adjusted the falling motion pattern until it appeared to be natural. In Experiment 2, they compared the perceived naturalness of vertical free falls in a vacuum with the perceived naturalness of more realistic falls characterized by the presence of air drag. In Experiment 3, they estimated the position of the sphere after a variable interval of time from the beginning of the fall. Inconsistently with predictions from physics, results showed that representations of gravitational motion were strongly affected by the implied masses of the falling objects and did not account for air drag. This provides support for the hypothesis of weight-based heuristic representations of gravitational motion against the hypothesis of the internalization of physical laws. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Microscopic evolution of doped Mott insulators from polaronic metal to Fermi liquid
2021-09-30

From polarons to a Fermi liquid Superconductivity in the cuprates emerges by doping an antiferromagnetic “parent” state with holes or electrons. With increased doping, antiferromagnetism gives way to unconventional superconductivity, and the system eventually becomes a Fermi liquid. Koepsell et al . simulated this progression using cold, strongly interacting lithium-6 atoms trapped in an optical lattice. Although the equivalent ordered phases are not yet reachable at the experimentally available temperatures, the researchers were able to measure multipoint spin and hole correlations over a wide range of hole doping. The evolution of these correlators with doping revealed a crossover from a polaronic regime to a Fermi liquid. —JS
Real-time decoding of 5 finger movements from 2 EMG channels for mixed reality human-computer interaction
2021-09-30

Abstract The search for optimized forms of human-computer interaction (HCI) has intensified alongside the growing potential for the combination of biosignals with virtual reality (VR) and augmented reality (AR) to enable the next generation of personal computing. At the core, this requires decoding the user’s biosignals into digital commands. Electromyography (EMG) is a biosensor of particular interest due to the ease of data collection, the relatively high signal-to-noise-ratio, its non-invasiveness, and the ability to interpret the signal as being generated by (intentional) muscle activity. Here, we investigate the potential of using data taken from a simple 2-channel EMG setup to differentiate 5 distinct movements. In particular, EMG was recorded from two bipolar sensors over small hand muscles ( extensor digitorum , flexor digitorum profundus ) while a subject performed 50 trials of dorsal extension and return for each of the five digits. The maximum and the mean values across the trial were determined for each channel and used as features. A k-nearest neighbors (kNN) classification was performed and overall 5-class classification accuracy reached 94% when using the full trial’s time window, while simulated real-time classification reached 90.4% accuracy when using the constructed kNN model (k=3) with a 280ms sliding window. Additionally, unsupervised learning was performed and a homogeneity of 85% was achieved. This study demonstrates that reliable decoding of different natural movements is possible with fewer than one channel per class, even without taking into account temporal features of the signal. The technical feasibility of this approach in a real-time setting was validated by sending real-time EMG data to a custom Unity3D VR application through a Lab Streaming Layer to control a user interface. Further use-cases of gamification and rehabilitation were also examined alongside the integration of eye-tracking and gesture recognition for a sensor fusion approach to HCI and user intent.
EMCA: Explorer of Monte Carlo based Algorithms
2021-09-30

Debugging or analyzing the performance of global illumination algorithms is a challenging task due to the complex path-scene interaction and numerous places where errors and programming bugs can occur. We present a novel, lightweight visualization tool to aid in the understanding of global illumination and the debugging of rendering frameworks. The tool provides detailed information about intersections and light transport paths. Users can add arbitrary data of their choosing to each intersection, based on their specific demands. Aggregate plots allow users to quickly discover and select outliers for further inspection across the globally linked visualization views. That information is further coupled with 3D visualization of the scene where additional aggregated information on the surfaces can be inspected in false colors. These include 3D heat maps such as the density of intersections as well as more advanced colorings such as a diffuse transport approximation computed from local irradiance samples and diffuse material approximations. The necessary data for the 3D coloring is collected as a side-product of quickly rendering the image at low sample counts without significantly slowing down the rendering process. It requires almost no precomputation and very little storage compared to point cloud-based approaches. We present several use cases of how novices and advanced rendering researchers can leverage the presented tool to speed up their research.
(R.) Bett (trans.) Sextus Empiricus. How to Keep an Open Mind. An Ancient Guide to Thinking Like a Skeptic. Pp. l + 225. Princeton and Oxford: Princeton University Press, 2021. Cased, £13.99, US$16.95. ISBN: 978-0-691-20604-2.
2021-09-30

(R.) Bett (trans.) Sextus Empiricus. How to Keep an Open Mind. An Ancient Guide to Thinking Like a Skeptic. Pp. l + 225. Princeton and Oxford: Princeton University Press, 2021. Cased, £13.99, US$16.95. ISBN: 978-0-691-20604-2. - Volume 72 Issue 1
Reduction of radiation exposure in scoliosis monitoring using flat detector and pulsed fluoroscopy technology
2021-09-30

A new flat detector and pulsed fluoroscopy technology is available to further reduce radiation exposure in radiological monitoring during scoliosis treatment in children and adolescents. The aim of this study is to compare different settings of the system (opening area(OA) and image quality settings (IQS)) in order to find the optimal parameters with high image quality and the lowest possible radiation exposure. Therefore, we examined four cadaver spines (T1 to sacrum) with the flat detector technique using digital pulsed fluoroscopy and simulated the abdominal soft tissues. The images were merged and evaluated by three different investigators using an established scoring system. For comparison, we used digital radiography images of the cadaver spines. The values for the DAP increased from the small OA (33% ; 0.56 μGy·m2) to the maximum OA (100% ; 0.82 μGy·m2) by 45% (p = .003) and from the low image quality setting (0.57 μGy·m2) to the high setting (0.84 μGy·m2) by 48% (p = .028). Despite the low DAP, the setting 33% OA achieved the best point values for image quality, therefore this setting is clearly preferred. Using a digital fluoroscopy system allows a significant reduction of radiation exposure by a factor of 7.5 (3.88μGy·m2 to 0.5μGy·m2) compared to slot- scanning x-ray (EOS). Due to this success, the flat detector and pulsed fluoroscopy technology can be an alternative to established methods such as X-ray and EOS in clinical use.