Baseline MELD score predicts hepatic decompensation during antiviral therapy in patients with chronic hepatitis C and advanced cirrhosis

Background and Aims: In patients with advanced liver cirrhosis due to chronic hepatitis C virus (HCV) infection antiviral therapy with peginterferon and ribavirin is feasible in selected cases only due to potentially life-threatening side effects. However, predictive factors associated with hepatic decompensation during antiviral therapy are poorly defined. Methods: In a retrospective cohort study, 68 patients with HCV-associated liver cirrhosis (mean MELD score 9.18±2.72) were treated with peginterferon and ribavirin. Clinical events indicating hepatic decompensation (onset of ascites, hepatic encephalopathy, upper gastrointestinal bleeding, hospitalization) as well as laboratory data were recorded at baseline and during a follow up period of 72 weeks after initiation of antiviral therapy. To monitor long term sequelae of end stage liver disease an extended follow up for HCC development, transplantation and death was applied (240weeks, ±SD 136weeks). Results: Eighteen patients (26.5%) achieved a sustained virologic response. During the observational period a hepatic decompensation was observed in 36.8%. Patients with hepatic decompensation had higher MELD scores (10.84 vs. 8.23, p14, respectively. Baseline MELD score was significantly associated with the risk for transplantation/death (p<0.001). Conclusions: Our data suggest that the baseline MELD score predicts the risk of hepatic decompensation during antiviral therapy and thus contributes to decision making when antiviral therapy is discussed in HCV patients with advanced liver cirrhosis

Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language

Large foundation models can exhibit unique capabilities depending on the domain of data they are trained on. While these domains are generic, they may only barely overlap. For example, visual-language models (VLMs) are trained on Internet-scale image captions, but large language models (LMs) are further trained on Internet-scale text with no images (e.g. from spreadsheets, to SAT questions). As a result, these models store different forms of commonsense knowledge across different domains. In this work, we show that this model diversity is symbiotic, and can be leveraged to build AI systems with structured Socratic dialogue -- in which new multimodal tasks are formulated as a guided language-based exchange between different pre-existing foundation models, without additional finetuning. In the context of egocentric perception, we present a case study of Socratic Models (SMs) that can provide meaningful results for complex tasks such as generating free-form answers to contextual questions about egocentric video, by formulating video Q&A as short story Q&A, i.e. summarizing the video into a short story, then answering questions about it. Additionally, SMs can generate captions for Internet images, and are competitive with state-of-the-art on zero-shot video-to-text retrieval with 42.8 R@1 on MSR-VTT 1k-A. SMs demonstrate how to compose foundation models zero-shot to capture new multimodal functionalities, without domain-specific data collection. Prototypes are available at socraticmodels.github.io.Comment: https://socraticmodels.github.io

Evaluation of downscaled wind speeds and parameterised gusts for recent and historical windstorms in Switzerland

Assessments of local-scale windstorm hazard require highly resolved spatial information on wind speeds and gusts. In this study, maximum (peak) sustained wind speeds on a 3-km horizontal grid over Switzerland are obtained by dynamical downscaling from the Twentieth Century Reanalysis (20CR) employing the Weather Research and Forecasting (WRF) model. Subsequently, simulated peak gusts are derived using four wind gust parameterizations (WGPs). Evaluations against observations at 63 locations in complex terrain include four high-impact windstorms (occurring in 1919, 1935, 1990, and 1999) and 14 recent windstorms (occurring between 1993 and 2011). Peak sustained wind speeds and directions are generally well simulated, although wind speeds are mostly overestimated. In general, performance and skill measures are best for locations on the Swiss Plateau and inferior for Alpine mountain and valley locations. An independent ERA-Interim WRF downscaling configuration produces overall comparable results, implying that the 20CR ensemble mean is a reliable data set in dynamical downscaling exercises. The four evaluated WGPs largely reproduce the observed gustiness, although the timing and magnitude of the peak gusts are not regularly captured. None of the WGPs stands out as single best for the complex topography of Switzerland. Differences among the WGPs are small compared to the biases inherited from the sustained-wind part in the WGP formulations. All WGPs transform overestimated peak sustained winds into underestimated peak gusts, which points to an underrepresentation of the turbulent part in the WGP formulations. The range of simulated peak gusts from downscaling all 20CR ensemble members does not reliably include the observed peak gust, indicating limited benefit in applying an ensemble approach. Despite the limitations, we infer that with spatial optimisations of the simulation (e.g. by bias correction or adaptation of the WGP schemes), downscaling of 20CR input is an efficient option for high-resolution assessments of windstorm hazard and risk in Switzerland

Fluorescence optical imaging feature selection with machine learning for differential diagnosis of selected rheumatic diseases

Background and objectiveAccurate and fast diagnosis of rheumatic diseases affecting the hands is essential for further treatment decisions. Fluorescence optical imaging (FOI) visualizes inflammation-induced impaired microcirculation by increasing signal intensity, resulting in different image features. This analysis aimed to find specific image features in FOI that might be important for accurately diagnosing different rheumatic diseases.Patients and methodsFOI images of the hands of patients with different types of rheumatic diseases, such as rheumatoid arthritis (RA), osteoarthritis (OA), and connective tissue diseases (CTD), were assessed in a reading of 20 different image features in three phases of the contrast agent dynamics, yielding 60 different features for each patient. The readings were analyzed for mutual differential diagnosis of the three diseases (One-vs-One) and each disease in all data (One-vs-Rest). In the first step, statistical tools and machine-learning-based methods were applied to reveal the importance rankings of the features, that is, to find features that contribute most to the model-based classification. In the second step machine learning with a stepwise increasing number of features was applied, sequentially adding at each step the most crucial remaining feature to extract a minimized subset that yields the highest diagnostic accuracy.ResultsIn total, n = 605 FOI of both hands were analyzed (n = 235 with RA, n = 229 with OA, and n = 141 with CTD). All classification problems showed maximum accuracy with a reduced set of image features. For RA-vs.-OA, five features were needed for high accuracy. For RA-vs.-CTD ten, OA-vs.-CTD sixteen, RA-vs.-Rest five, OA-vs.-Rest eleven, and CTD-vs-Rest fifteen, features were needed, respectively. For all problems, the final importance ranking of the features with respect to the contrast agent dynamics was determined.ConclusionsWith the presented investigations, the set of features in FOI examinations relevant to the differential diagnosis of the selected rheumatic diseases could be remarkably reduced, providing helpful information for the physician

Mobile Air Quality Studies (MAQS) - an international project

Due to an increasing awareness of the potential hazardousness of air pollutants, new laws, rules and guidelines have recently been implemented globally. In this respect, numerous studies have addressed traffic-related exposure to particulate matter using stationary technology so far. By contrast, only few studies used the advanced technology of mobile exposure analysis. The Mobile Air Quality Study (MAQS) addresses the issue of air pollutant exposure by combining advanced high-granularity spatial-temporal analysis with vehicle-mounted, person-mounted and roadside sensors. The MAQS-platform will be used by international collaborators in order 1) to assess air pollutant exposure in relation to road structure, 2) to assess air pollutant exposure in relation to traffic density, 3) to assess air pollutant exposure in relation to weather conditions, 4) to compare exposure within vehicles between front and back seat (children) positions, and 5) to evaluate "traffic zone"- exposure in relation to non-"traffic zone"-exposure. Primarily, the MAQS-platform will focus on particulate matter. With the establishment of advanced mobile analysis tools, it is planed to extend the analysis to other pollutants including including NO2, SO2, nanoparticles, and ozone

Status Of The FAIR Synchrotron Projects SIS18 And SIS100

A large fraction of the program to upgrade the existingheavy ion synchrotron SIS18 as injector for the FAIR synchrotron SIS100 has been successfully completed. With the achieved technical status, a major increase of theaccelerated number of heavy ions could be reached. Thenow available performance especially demonstrates thefeasibility of high intensity beams of medium charge stateheavy ions with a sufficient control of the dynamicvacuum and connected charge exchange loss. Two furtherupgrade measures, the installation of additional magneticalloy (MA) acceleration cavities and the exchange of themain dipole power converter, are presently beingimplemented. For the FAIR synchrotron SIS100, theprocurement of all major components with longproduction times has been started. With the delivery andtesting of several pre-series components, the phase ofoutstanding technical reserach and developments could becompleted and the readiness for series productionachieved

Soluble Serum CD81 Is Elevated in Patients with Chronic Hepatitis C and Correlates with Alanine Aminotransferase Serum Activity

Aim: Cellular CD81 is a well characterized hepatitis C virus (HCV) entry factor, while the relevance of soluble exosomal CD81 in HCV pathogenesis is poorly defined. We performed a case-control study to investigate whether soluble CD81 in the exosomal serum fraction is associated with HCV replication and inflammatory activity. Patients and Methods: Four cohorts were investigated, patients with chronic hepatitis C (n = 37), patients with chronic HCV infection and persistently normal ALT levels (n = 24), patients with long term sustained virologic response (SVR, n = 7), and healthy volunteers (n = 23). Concentration of soluble CD81 was assessed semi-quantitatively after differential centrifugation ranging from 200 g to 100,000 g in the fifth centrifugation fraction by immunoblotting and densitometry. Results: Soluble CD81 was increased in patients with chronic hepatitis C compared to healthy subjects (p = 0.03) and cured patients (p = 0.017). Patients with chronic HCV infection and persistently normal ALT levels and patients with long term SVR had similar soluble CD81 levels as healthy controls (p>0.2). Overall, soluble CD81 levels were associated with ALT levels (r = 0.334, p = 0.016) and severe liver fibrosis (p = 0.027). Conclusion: CD81 is increased in the exosomal serum fraction in patients with chronic hepatitis C and appears to be associated with inflammatory activity and severity of fibrosis

The Three Hundred project: a large catalogue of theoretically modelled galaxy clusters for cosmological and astrophysical applications

We introduce the The Three Hundred project, an endeavour to model 324 large galaxy clusters with full-physics hydrodynamical re-simulations. Here we present the dataset and study the differences to observations for fundamental galaxy cluster properties and scaling relations. We find that the modelled galaxy clusters are generally in reasonable agreement with observations with respect to baryonic fractions and gas scaling relations at redshift z = 0. However, there are still some (model-dependent) differences, such as central galaxies being too massive, and galaxy colours (g − r) being bluer (about 0.2 dex lower at the peak position) than in observations. The agreement in gas scaling relations down to 1013 h−1M⊙ between the simulations indicates that particulars of the sub-grid modelling of the baryonic physics only has a weak influence on these relations. We also include – where appropriate – a comparison to three semi-analytical galaxy formation models as applied to the same underlying dark matter only simulation. All simulations and derived data products are publicly available