The transition from a liquid to a glass remains one of the most poorly understood phenomena in condensed matter physics, and still no fully microscopic theory exists that can describe the dynamics of ...supercooled liquids in a quantitative manner over all relevant time scales. Here, we present a theoretical framework that yields near-quantitative accuracy for the time-dependent correlation functions of a glass-forming system over a broad density range. Our approach requires only simple static structural information as input and is based entirely on first principles. Owing to its ab initio nature, the framework offers a unique platform to study the relation between structure and dynamics in glass-forming matter, and paves the way towards a systematically correctable and ultimately fully quantitative theory of microscopic glassy dynamics.
The coupling of active, self-motile particles to topological constraints can give rise to novel non-equilibrium dynamical patterns that lack any passive counterpart. Here we study the behavior of ...self-propelled rods confined to a compact spherical manifold by means of Brownian dynamics simulations. We establish the state diagram and find that short active rods at sufficiently high density exhibit a glass transition toward a disordered state characterized by persistent self-spinning motion. By periodically melting and revitrifying the spherical spinning glass, we observe clear signatures of time-dependent aging and rejuvenation physics. We quantify the crucial role of activity in these non-equilibrium processes, and rationalize the aging dynamics in terms of an absorbing-state transition toward a more stable active glassy state. Our results demonstrate both how concepts of passive glass phenomenology can carry over into the realm of active matter, and how topology can enrich the collective spatiotemporal dynamics in inherently non-equilibrium systems.
The enhancement and detection of elongated structures in noisy image data are relevant for many biomedical imaging applications. To handle complex crossing structures in 2D images, 2D orientation ...scores
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. First, we construct the orientation score from a given dataset, which is achieved by an invertible coherent state type of transform. For this transformation we introduce 3D versions of the 2D cake wavelets, which are complex wavelets that can simultaneously detect oriented structures and oriented edges. Here we introduce two types of cake wavelets: the first uses a discrete Fourier transform, and the second is designed in the 3D generalized Zernike basis, allowing us to calculate analytical expressions for the spatial filters. Second, we propose a nonlinear diffusion flow on the 3D roto-translation group: crossing-preserving coherence-enhancing diffusion via orientation scores (CEDOS). Finally, we show two applications of the orientation score transformation. In the first application we apply our CEDOS algorithm to real medical image data. In the second one we develop a new tubularity measure using 3D orientation scores and apply the tubularity measure to both artificial and real medical data.
Soft particles such as microgels can undergo significant and anisotropic deformations when adsorbed to a liquid interface. This, in turn, leads to a complex phase behavior upon compression. To date, ...experimental efforts have predominantly provided phenomenological links between microgel structure and resulting interfacial behavior, while simulations have not been entirely successful in reproducing experiments or predicting the minimal requirements for the desired phase behavior. Here, we develop a multiscale framework to link the molecular particle architecture to the resulting interfacial morphology and, ultimately, to the collective interfacial phase behavior. To this end, we investigate interfacial morphologies of different poly(N-isopropylacrylamide) particle systems using phase-contrast atomic force microscopy and correlate the distinct interfacial morphology with their bulk molecular architecture. We subsequently introduce a new coarse-grained simulation method that uses augmented potentials to translate this interfacial morphology into the resulting phase behavior upon compression. The main novelty of this method is the possibility to efficiently encode multibody interactions, the effects of which are key to distinguishing between heterostructural (anisotropic collapse) and isostructural (isotropic collapse) phase transitions. Our approach allows us to qualitatively resolve existing discrepancies between experiments and simulations. Notably, we demonstrate the first in silico account of the two-dimensional isostructural transition, which is frequently found in experiments but elusive in simulations. In addition, we provide the first experimental demonstration of a heterostructural transition to a chain phase in a single-component system, which has been theoretically predicted decades ago. Overall, our multiscale framework provides a phenomenological bridge between physicochemical soft-particle characteristics at the molecular scale and nanoscale and the collective self-assembly phenomenology at the macroscale, serving as a stepping stone toward an ultimately more quantitative and predictive design approach.
Primary antibody deficiencies (PADs) without an identified monogenetic origin form the largest and most heterogeneous group of primary immunodeficiencies. These patients often remain undiagnosed for ...years and many present to medical attention in adulthood after several infections risking structural complications. Not much is known about their treatment, comorbidities, or prognosis, nor whether the various immunological forms (decreased total IgG, IgG subclass(es), IgM, IgA, specific antibody responses, alone or in combination(s)) should be considered as separate, clearly definable subgroups. The unclassified primary antibody deficiency (unPAD) study aims to describe in detail all PAD patients without an identified specific monogenetic defect regarding their demographical, clinical, and immunological characteristics at presentation and during follow-up. In constructing these patterns, the unPAD study aims to reduce the number of missed and unidentified PAD patients in the future. In addition, this study will focus on subclassifying unPAD to support the identification of patients at higher risk for infection or immune dysregulation related complications, enabling the development of personalized follow-up and treatment plans.
We present a protocol for a multicenter observational cohort study using the ESID online Registry. Patients of all ages who have given informed consent for participation in the ESID online Registry and fulfill the ESID Clinical Working Definitions for 'unclassified antibody deficiency', 'deficiency of specific IgG', 'IgA with IgG subclass deficiency', 'isolated IgG subclass deficiency', 'selective IgM deficiency', 'selective IgA deficiency' or 'common variable immunodeficiency' will be included. For all patients, basic characteristics can be registered at first registration and yearly thereafter in level 1 forms. Detailed characteristics of the patients can be registered in level 2 forms. Consecutive follow-up forms can be added indefinitely. To ensure the quality of the collected data, all data will be fully monitored before they are exported from the ESID online Registry for analysis. Outcomes will be the clinical and immunological characteristics of unPAD at presentation and during follow-up. Subgroup analyses will be made based on demographical, clinical and immunological characteristics.
The worldwide incidence of prediabetes/type 2 has continued to rise the last 40 years. In the same period, the mean daily energy intake has increased, and the quality of food has significantly ...changed. The chronic exposure of pancreatic β-cells to calorie excess (excessive energy intake) and food additives may increase pancreatic insulin secretion, decrease insulin pulses and/or reduce hepatic insulin clearance, thereby causing chronic hyperinsulinemia and peripheral insulin resistance. Chronic calorie excess and hyperinsulinemia may promote lipogenesis, inhibit lipolysis and increase lipid storage in adipocytes. In addition, calorie excess and hyperinsulinemia can induce insulin resistance and contribute to progressive and excessive ectopic fat accumulation in the liver and pancreas by the conversion of excess calories into fat. The personal fat threshold hypothesis proposes that in susceptible individuals, excessive ectopic fat accumulation may eventually lead to hepatic insulin receptor resistance, the loss of pancreatic insulin secretion, hyperglycemia and the development of frank type 2 diabetes. Thus, type 2 diabetes seems (partly) to be caused by hyperinsulinemia-induced excess ectopic fat accumulation in the liver and pancreas. Increasing evidence further shows that interventions (hypocaloric diet and/or bariatric surgery), which remove ectopic fat in the liver and pancreas by introducing a negative energy balance, can normalize insulin secretion and glucose tolerance and induce the sustained biochemical remission of type 2 diabetes. This pathophysiological insight may have major implications and may cause a paradigm shift in the management of type 2 diabetes: avoiding/reducing ectopic fat accumulation in the liver and pancreas may both be essential to prevent and cure type 2 diabetes.
Abstract Objective We compared popular methods to handle missing data with multiple imputation (a more sophisticated method that preserves data). Study Design and Setting We used data of 804 patients ...with a suspicion of deep venous thrombosis (DVT). We studied three covariates to predict the presence of DVT: d -dimer level, difference in calf circumference, and history of leg trauma. We introduced missing values (missing at random) ranging from 10% to 90%. The risk of DVT was modeled with logistic regression for the three methods, that is, complete case analysis, exclusion of d -dimer level from the model, and multiple imputation. Results Multiple imputation showed less bias in the regression coefficients of the three variables and more accurate coverage of the corresponding 90% confidence intervals than complete case analysis and dropping d -dimer level from the analysis. Multiple imputation showed unbiased estimates of the area under the receiver operating characteristic curve (0.88) compared with complete case analysis (0.77) and when the variable with missing values was dropped (0.65). Conclusion As this study shows that simple methods to deal with missing data can lead to seriously misleading results, we advise to consider multiple imputation. The purpose of multiple imputation is not to create data, but to prevent the exclusion of observed data.
Government agencies are becoming more data-driven and need high-quality data to fulfill their roles in society. In the past, each agency organized its own data exchange system according to its own ...needs. Today, data is distributed over many organizations, and government agencies need to adopt an ecosystem approach for data exchange. Fundamental in the ecosystem approach is the dependence on other parties for the execution of stewardship strategies. Data-driven government agencies increasingly depend on other organizations for high-quality data and data stewardship across organizations is becoming more critical. While there is ample research on data stewardship within organizations, little is known about data stewardship in ecosystems. More specifically, it is unclear which data stewardship strategies government agencies can employ in ecosystems. The main goal of this explorative paper is to identify and compare data stewardship strategies used in empirical government-business ecosystems. Following an explorative case study approach, this paper reveals three different configurations of inter-organizational data stewardship: 1) the government-led ecosystem, 2) the government-business-led ecosystem, and 3) the regulation-led ecosystem. The case studies expose a wide array of data stewardship strategies across ecosystems. While the ecosystem approach provides advantages such as cost-sharing and innovation by private parties, government agencies become increasingly dependent on private parties to gain high-quality data and provide distributed infrastructure components. Maximizing the benefits and minimizing the risks of the ecosystem approach requires government agencies to be cautious when selecting a specific ecosystem configuration.
•We developed an analytical framework to analyze different empirical data stewardship configurations and data strategies.•Centralized digital infrastructures are replaced by a negotiated framework of data exchange agreements.•Government agencies become increasingly dependent on market parties.•In these frameworks governments need to focus on data stewardship and form a data stewardship strategy.•Data stewardship must be extended to include governance and system quality.
Abstract
Artificial intelligence (AI) is entering into daily life and has the potential to play a significant role in healthcare. Aim was to investigate the perspectives (knowledge, experience, and ...opinion) on AI in healthcare among patients with gastrointestinal (GI) disorders, gastroenterologists, and GI-fellows. In this prospective questionnaire study 377 GI-patients, 35 gastroenterologists, and 45 GI-fellows participated. Of GI-patients, 62.5% reported to be familiar with AI and 25.0% of GI-physicians had work-related experience with AI. GI-patients preferred their physicians to use AI (mean 3.9) and GI-physicians were willing to use AI (mean 4.4, on 5-point Likert-scale). More GI-physicians believed in an increase in quality of care (81.3%) than GI-patients (64.9%, χ
2
(2) = 8.2,
p
= 0.017). GI-fellows expected AI implementation within 6.0 years, gastroenterologists within 4.2 years (t(76) = − 2.6,
p
= 0.011), and GI-patients within 6.1 years (t(193) = − 2.0,
p
= 0.047). GI-patients and GI-physicians agreed on the most important advantages of AI in healthcare: improving quality of care, time saving, and faster diagnostics and shorter waiting times. The most important disadvantage for GI-patients was the potential loss of personal contact, for GI-physicians this was insufficiently developed IT infrastructures. GI-patients and GI-physicians hold positive perspectives towards AI in healthcare. Patients were significantly more reserved compared to GI-fellows and GI-fellows were more reserved compared to gastroenterologists.
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