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Early-childhood body mass index and its association with the COVID-19 pandemic, containment measures and islet autoimmunity in children with increased risk for type 1 diabetes

Aims/hypothesis: The aim of this study was to determine whether BMI in early childhood was affected by the COVID-19 pandemic and containment measures, and whether it was associated with the risk for islet autoimmunity. Methods: Between February 2018 and May 2023, data on BMI and islet autoimmunity were collected from 1050 children enrolled in the Primary Oral Insulin Trial, aged from 4.0 months to

Risk of subsequent gliomas and meningiomas among 69,460 5-year survivors of childhood and adolescent cancer in Europe : the PanCareSurFup study

Background: Childhood cancer survivors are at risk of subsequent gliomas and meningiomas, but the risks beyond age 40 years are uncertain. We quantified these risks in the largest ever cohort. Methods: Using data from 69,460 5-year childhood cancer survivors (diagnosed 1940–2008), across Europe, standardized incidence ratios (SIRs) and cumulative incidence were calculated. Results: In total, 279 g

Reconfiguration of cognitive control networks during a long-duration flanker task

Continuous task engagement generally leads to vigilance decrement and deteriorates task performance. However, how conflict effect is modulated by vigilance decrement has no consistent evidence, and little is known about the underlying neural mechanisms. Here we adopted an electroencephalogram dataset collected during a prolonged flanker task to examine the interactions between vigilance and congru

Population-Based Validation of the MIA and MSKCC Tools for Predicting Sentinel Lymph Node Status

Importance: Patients with melanoma are selected for sentinel lymph node biopsy (SLNB) based on their risk of a positive SLN. To improve selection, the Memorial Sloan Kettering Cancer Center (MSKCC) and Melanoma Institute Australia (MIA) developed predictive models, but the utility of these models remains to be tested. Objective: To determine the clinical utility of the MIA and MSKCC models. Design

A feasibility study of applying generative deep learning models for map labeling

The automation of map labeling is an ongoing research challenge. Currently, the map labeling algorithms are based on rules defined by experts for optimizing the placement of the text labels on maps. In this paper, we investigate the feasibility of using well-labeled map samples as a source of knowledge for automating the labeling process. The basic idea is to train deep learning models, specifical

Numerical Reconstruction of Proton Exchange Membrane Fuel Cell Gas Diffusion Layers

Stochastic reconstruction is widely employed for effective and flexible imitation of Gas Diffusion Layers (GDLs), e.g., to facilitate the study of their properties. However, the reconstruction often overlooks crucial factors such as fiber curvature, fiber stack arrangement, and fiber anisotropy. Consequently, the impact of these structural characteristics remains poorly understood. In this study,

Structural basis of Cfr-mediated antimicrobial resistance and mechanisms to evade it

The bacterial ribosome is an essential drug target as many clinically important antibiotics bind and inhibit its functional centers. The catalytic peptidyl transferase center (PTC) is targeted by the broadest array of inhibitors belonging to several chemical classes. One of the most abundant and clinically prevalent resistance mechanisms to PTC-acting drugs in Gram-positive bacteria is C8-methylat

On Metrics for Information Value Quantification

In this paper, we aggregate, analyze, and exemplify several metrics for the information value. The metrics vary by absolute value, normalizations, or full probabilistic quantification. The normalization of the information value encompasses the division by (1) the expected and maximized utility of the base scenario (usually without additional information), (2) by the system performance, or (3) by t

Risk of Alzheimer's Disease and Related Dementias in Persons with Glaucoma : A National Cohort Study

Purpose: Glaucoma is a heterogeneous group of optic neuropathies that potentially may be associated with other cerebral neurodegenerative processes leading to dementia. However, prior studies have been inconsistent. We examined dementia risks after glaucoma diagnosis in a large population-based cohort. Design: National matched cohort study. Participants: A total of 324 730 persons diagnosed with g

Retrospective validation study of an artificial neural network-based preoperative decision-support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer (ISRCTN14341750)

Background: Surgical sentinel lymph node biopsy (SLNB) is routinely used to reliably stage axillary lymph nodes in early breast cancer (BC). However, SLNB may be associated with postoperative arm morbidities. For most patients with BC undergoing SLNB, the findings are benign, and the procedure is currently questioned. A decision-support tool for the prediction of benign sentinel lymph nodes based

Can the presence of specialized addiction staff in primary health care increase the number of alcohol-related medical consultations – A controlled intervention study

Background: Few individuals with alcohol use disorders receive treatment. Primary care has been suggested as an arena for early treatment for these disorders. Aim: To evaluate whether the presence of a specialized addiction nurse can increase alcohol-related physician consultations in a primary care setting. Method: This controlled intervention study included one intervention and one control prima

Ground geophysical measurements made on mine-tailings in Sweden. Case studies and lessons learnt

Ground-based geophysical surveys were conducted at eight mine-tailings repositories during 2021 and 2022 to help preparing an inventory of potential sources of critical raw materials in mine-waste. Geophysical methods included ERT, DCIP, RMT, and tTEM. In this study, we show results obtained on two of the sites as an example. Integration of models of electrical properties, geological observations,

Financing an accelerated shift to zero emission vehicles by deploying High-Capacity Transport with Intelligent Access by 2024

The paper explores synergies by bundling High-Capacity Transport - Intelligent Access - Zero Emission Vehicle reforms. State of the art is analyzed, and research questions are formulated. One joint policy framework is proposed and applied to three use cases: one vehicle, one real use case, and one scenario for the whole of EU. In the later, the cost savings 2024 to 2028 from allowing longer and/or

Evolution of the structure of lipid nanoparticles for nucleic acid delivery : From in situ studies of formulation to colloidal stability

The development of lipid nanoparticle (LNP) based therapeutics for delivery of RNA has triggered the advance of new strategies for formulation, such as high throughput microfluidics for precise mixing of components into well-defined particles. In this study, we have characterised the structure of LNPs throughout the formulation process using in situ small angle x-ray scattering in the microfluidic

Optimal Phasors for Wideband RIS Transmissions

Configuring reconfigurable intelligent surfaces (RISs) based on a practical RIS model is a fundamental problem in RIS-assisted wireless transmission. In this work, we propose a concept named optimal phasor (OP), a latent quantity that can considerably help the practical model-based RIS configuration. Under such a concept, we can design versatile algorithms that are applicable to different RIS mode

Changes in T-Peak-to-T-End Morphology Measured by Time-Warping are Associated with Ischemia-Induced Ventricular Fibrillation in a Porcine Model

In this work, we use a time-warping-based morphology variation index, d_{w}, computed between the peak and the end of the T-wave, and assess its association with the occurrence of ventricular fibrillation (VF) episodes in ischemic conditions. ECG recordings from 26 pigs under-going a 40-minute coronary occlusion were analyzed. The d_{w} series was obtained by quantifying the morphological differen

Elective one-minute full brain multi-contrast MRI versus brain CT in pediatric patients : a prospective feasibility study

Background: Brain CT can be used to evaluate pediatric patients with suspicion of cerebral pathology when anesthetic and MRI resources are scarce. This study aimed to assess if pediatric patients referred for an elective brain CT could endure a diagnostic fast brain MRI without general anesthesia using a one-minute multi-contrast EPI-based sequence (EPIMix) with comparable diagnostic performance.

High capacity city transport with intelligent access - A Swedish case study of transporting excavated material

This project studies how the HCT-concept (High Capacity Transport) can be applied in cities, by performing pilots in Varberg and Stockholm. The project will test the hypothesis that the HCT-concept will improve both productivity construction and transport efficiency and thereby reduce CO2 by up to 40%. The pilots include tests of new optimized trucks and new concepts with sensors in trucks, machin

You can have your ensemble and run it too - Deep Ensembles Spread Over Time

Ensembles of independently trained deep neural networks yield uncertainty estimates that rival Bayesian networks in performance. They also offer sizable improvements in terms of predictive performance over single models. However, deep ensembles are not commonly used in environments with limited computational budget - such as autonomous driving - since the complexity grows linearly with the number