Abstract
An emerging diversity of computational platforms offers many different approaches to adopting the paradigm of artificial intelligence to the study of electron-ion collisions. Here we review ...several leading candidates in this computational frontier and their workflows for experimental applications of artificial intelligence that may impact the future Electron-Ion Collider. We discuss the motivation for exploring novel methods to solve artificial intelligence and machine learning problems including with customized devices, quantum simulation, and heterogeneous computing systems. These technologies offer promising approaches to address some of the leading concerns of future computing that may impact the Electron-Ion Collider but they will require further development and testing in order to support future planning efforts.
Hemophagocytic lymphohistiocytosis (HLH) is a rare syndrome of uncontrolled immune activation that has gained increasing attention during the last decade. The diagnosis of HLH is based on a ...constellation of clinical and laboratory abnormalities, including elevated serum ferritin levels. In the pediatric population, marked hyperferritinemia is specific for HLH. To determine what conditions are associated with profoundly elevated ferritin in the adult population, we performed a retrospective analysis in a large academic health care system. We identified 113 patients with serum ferritin levels higher than 50 000 µg/L. The most frequently observed conditions included renal failure, hepatocellular injury, infections, and hematologic malignancies. Our results suggest that marked hyperferritinemia can be seen in a variety of conditions and is not specific for HLH in adults.
•Highly elevated ferritin is not specific for hemophagocytic lymphohistiocytosis in adults.•Marked hyperferritinemia in adults most often occurs in the setting of renal failure, hepatocellular injury, infection, or malignancy.
The Belle II experiment at KEK is preparing for first collisions in 2017. Processing the large amounts of data that will be produced will require conditions data to be readily available to systems ...worldwide in a fast and efficient manner that is straightforward for both the user and maintainer. The Belle II conditions database was designed with a straightforward goal: make it as easily maintainable as possible. To this end, HEP-specific software tools were avoided as much as possible and industry standard tools used instead. HTTP REST services were selected as the application interface, which provide a high-level interface to users through the use of standard libraries such as curl. The application interface itself is written in Java and runs in an embedded Payara-Micro Java EE application server. Scalability at the application interface is provided by use of Hazelcast, an open source In-Memory Data Grid (IMDG) providing distributed in-memory computing and supporting the creation and clustering of new application interface instances as demand increases. The IMDG provides fast and efficient access to conditions data via in-memory caching.
Summary
Haemophagocytic lymphohistiocytosis (HLH) is a syndrome of uncontrolled immune activation that has gained increasing attention over the past decade. Although classically known as a familial ...disorder of children caused by mutations that affect cytotoxic T‐cell function, an acquired form of HLH in adults is now widely recognized. This is often seen in the setting of malignancy, infection or rheumatological disorders. We performed a retrospective review across 3 tertiary care centres and identified 68 adults with HLH. The average age was 53 years (range 18–77 years) and 43 were male (63%). Underlying disorders included malignancy in 33 patients (49%), infection in 22 (33%), autoimmune disease in 19 (28%) and idiopathic HLH in 15 (22%). Patients were treated with disease‐specific therapy and immunomodulatory agents. After a median follow‐up of 32·2 months, 46 patients had died (69%). The median overall survival was 4 months (95% CI: 0·0–10·2 months). Patients with malignancy had a worse prognosis compared to those without (median survival 2·8 months versus 10·7 months, P = 0·007). HLH is a devastating disorder with a high mortality. Further research is needed to improve treatment and outcomes.
Abstract Type 2 diabetes mellitus (T2DM) has been associated with an increased risk of fractures, despite normal to increased bone mineral density (BMD). Insulin use is one of the factors linked to ...this increased fracture risk. However, direct negative effects of insulin on bone quality are not expected since insulin is thought to be anabolic to bone. In this cross-sectional study the association between insulin use and volumetric BMD (vBMD), bone micro-architecture and bone strength of the distal radius, as measured with HR-pQCT, was examined. Data from 50 participants with T2DM of The Maastricht Study (mean age 62 ± 7.5 years, 44% women) was used. Participants were classified as insulin user (n = 13) or non-insulin user (n = 37) based on prescription data. Linear regression analysis was used to estimate the association between current insulin use and HR-pQCT derived parameters. After adjustment for age, sex, body mass index, glycated hemoglobin A1c and T2DM duration, insulin use was associated with lower total vBMD (standardized beta (β):− 0.56 (95% CI:− 0.89 to − 0.24)), trabecular vBMD (β:− 0.58 (95% CI:− 0.87 to − 0.30)), trabecular thickness (β:− 0.55 (95% CI:− 0.87 to − 0.23)), cortical thickness (β:− 0.41 (95% CI:− 0.74 to − 0.08)), log cortical pore volume (β:− 0.43 (95% CI:− 0.73 to − 0.13)), bone stiffness (β:− 0.39 (95% CI:− 0.62 to − 0.17)) and failure load (β:− 0.39 (95% CI:− 0.60 to − 0.17)) when compared to the non-insulin users. Insulin use was not associated with cortical vBMD, trabecular number, trabecular separation, cortical porosity and cortical pore diameter. This study indicates that insulin use is negatively associated with bone density, bone micro-architectural and bone strength parameters. These findings may partly explain the previously observed increased fracture risk in insulin users, although there may be residual confounding by other factors related to disease severity in insulin users.
Understanding a tumor's detailed molecular profile has become increasingly necessary to deliver the standard of care for patients with advanced cancer. Innovations in both tumor genomic sequencing ...technology and the development of drugs that target molecular alterations have fueled recent gains in genome-driven oncology care. "Basket studies," or histology-agnostic clinical trials in genomically selected patients, represent one important research tool to continue making progress in this field. We review key aspects of genome-driven oncology care, including the purpose and utility of basket studies, biostatistical considerations in trial design, genomic knowledgebase development, and patient matching and enrollment models, which are critical for translating our genomic knowledge into clinically meaningful outcomes.
Ploidy abnormalities are a hallmark of cancer, but their impact on the evolution and outcomes of cancers is unknown. Here, we identified whole-genome doubling (WGD) in the tumors of nearly 30% of ...9,692 prospectively sequenced advanced cancer patients. WGD varied by tumor lineage and molecular subtype, and arose early in carcinogenesis after an antecedent transforming driver mutation. While associated with TP53 mutations, 46% of all WGD arose in TP53-wild-type tumors and in such cases was associated with an E2F-mediated G1 arrest defect, although neither aberration was obligate in WGD tumors. The variability of WGD across cancer types can be explained in part by cancer cell proliferation rates. WGD predicted for increased morbidity across cancer types, including KRAS-mutant colorectal cancers and estrogen receptor-positive breast cancers, independently of established clinical prognostic factors. We conclude that WGD is highly common in cancer and is a macro-evolutionary event associated with poor prognosis across cancer types.
The cyclotron radiation emission spectroscopy (CRES) technique pioneered by Project 8 measures electromagnetic radiation from individual electrons gyrating in a background magnetic field to construct ...a highly precise energy spectrum for beta decay studies and other applications. The detector, magnetic trap geometry and electron dynamics give rise to a multitude of complex electron signal structures which carry information about distinguishing physical traits. With machine learning models, we develop a scheme based on these traits to analyze and classify CRES signals. Proper understanding and use of these traits will be instrumental to improve cyclotron frequency reconstruction and boost the potential of Project 8 to achieve world-leading sensitivity on the tritium endpoint measurement in the future.
Background
Atopic dermatitis (AD or eczema) is a most common chronic skin disease. Designing personalised treatment strategies for AD based on patient stratification is of high clinical relevance, ...given a considerable variation in the clinical phenotype and responses to treatments among patients. It has been hypothesised that the measurement of biomarkers could help predict therapeutic responses for individual patients.
Objective
We aim to assess whether serum biomarkers can predict the outcome of systemic immunosuppressive therapy in adult AD patients.
Methods
We developed a statistical machine learning model using the data of an already published longitudinal study of 42 patients who received azathioprine or methotrexate for over 24 weeks. The data contained 26 serum cytokines and chemokines measured before the therapy. The model described the dynamic evolution of the latent disease severity and measurement errors to predict AD severity scores (Eczema Area and Severity Index, (o)SCORing of AD and Patient Oriented Eczema Measure) two‐weeks ahead. We conducted feature selection to identify the most important biomarkers for the prediction of AD severity scores.
Results
We validated our model in a forward chaining setting and confirmed that it outperformed standard time‐series forecasting models. Adding biomarkers did not improve predictive performance.
Conclusions
In this study, biomarkers had a negligible and non‐significant effect for predicting the future AD severity scores and the outcome of the systemic therapy.
Type 2 diabetes mellitus is associated with cognitive decrements. Specifically affected cognitive domains are learning and memory, for which the hippocampus plays an essential role. The ...pathophysiological mechanism remains to be revealed. The present study examined whether local hippocampal microstructure and white matter connectivity are related to type 2 diabetes and memory performance. Forty participants with type 2 diabetes and 38 participants without type 2 diabetes underwent detailed cognitive assessment and 3‐Tesla diffusion magnetic resonance imaging (MRI). Diffusion MRI was performed to assess microstructure (fractional anisotropy and mean diffusivity) and white matter connectivity (tract volume) of the hippocampus, which were compared between participants with and without type 2 diabetes. No differences in hippocampal microstructure were observed. Participants with type 2 diabetes had fewer white matter connections between the hippocampus and frontal lobe (P = 0.017). Participants who scored lower on memory function, regardless of type 2 diabetes, had fewer white matter connections between the hippocampus and temporal lobe (P = 0.017). Taken together, type 2 diabetes and memory decrements appear to be associated with altered hippocampal white matter connectivity.
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