Antisense Oligonucleotide STK-002 Increases OPA1 in Retina and Improves Mitochondrial Function in Autosomal Dominant Optic Atrophy Cells.

Autosomal dominant optic atrophy (ADOA) is an inherited optic neuropathy most frequently associated with mutations. Most variants result in haploinsufficiency, and patient cells express roughly half of the normal levels of OPA1 protein. OPA1 is a mitochondrial GTPase that is essential for normal mitochondrial function.

A review of machine learning in scanpath analysis for passive gaze-based interaction.

The scanpath is an important concept in eye tracking. It refers to a person's eye movements over a period of time, commonly represented as a series of alternating fixations and saccades. Machine learning has been increasingly used for the automatic interpretation of scanpaths over the past few years, particularly in research on passive gaze-based interaction, i.

Sensitivity of air quality to vehicle ammonia emissions in the United States.

The US Environmental Protection Agency (EPA) estimates on-road vehicles emissions using the Motor Vehicle Emission Simulator (MOVES). We developed updated ammonia emission rates for MOVES based on road-side exhaust emission measurements of light-duty gasoline and heavy-duty diesel vehicles. The resulting nationwide on-road vehicle ammonia emissions are 1.

Reactive organic carbon air emissions from mobile sources in the United States.

Mobile sources are responsible for a substantial controllable portion of the reactive organic carbon (ROC) emitted to the atmosphere, especially in urban environments of the United States. We update existing methods for calculating mobile source organic particle and vapor emissions in the United States with over a decade of laboratory data that parameterize the volatility and organic aerosol (OA) potential of emissions from on-road vehicles, nonroad engines, aircraft, marine vessels, and locomotives. We find that existing emission factor information from Teflon filters combined with quartz filters collapses into simple relationships and can be used to reconstruct the complete volatility distribution of ROC emissions.

Cross-Viewpoint Semantic Mapping: Integrating Human and Robot Perspectives for Improved 3D Semantic Reconstruction.

Allocentric semantic 3D maps are highly useful for a variety of human-machine interaction related tasks since egocentric viewpoints can be derived by the machine for the human partner. Class labels and map interpretations, however, may differ or could be missing for the participants due to the different perspectives. Particularly, when considering the viewpoint of a small robot, which significantly differs from the viewpoint of a human.

Digital ink and differentiated subjective ratings for cognitive load measurement in middle childhood.

Background: New methods are constantly being developed to adapt cognitive load measurement to different contexts. However, research on middle childhood students' cognitive load measurement is rare. Research indicates that the three cognitive load dimensions (intrinsic, extraneous, and germane) can be measured well in adults and teenagers using differentiated subjective rating instruments.

2002-2017 anthropogenic emissions data for air quality modeling over the United States.

The United States Environmental Protection Agency (US EPA) has developed a set of annual North American emissions data for multiple air pollutants across 18 broad source categories for 2002 through 2017. The sixteen new annual emissions inventories were developed using consistent input data and methods across all years. When a consistent method or tool was not available for a source category, emissions were estimated by scaling data from the EPA's 2017 National Emissions Inventory with scaling factors based on activity data and/or emissions control information.

Evaluation of a Complex Intervention to Strengthen Participation-Centred Care for Children with Special Healthcare Needs: Protocol of the Stepped Wedge Cluster Randomised PART-CHILD Trial.

Introduction: Participation is an important dimension of healthy child development and is associated with higher self-rated health, educational attainment and civic engagement. Many children with special healthcare needs (SHCN) experience limited participation and are thus at risk for adverse health and developmental outcomes. Despite this, interventions that promote participation in healthcare are scarce.

Plasma Metabolic Signatures of Healthy Overweight Subjects Challenged With an Oral Glucose Tolerance Test.

Insulin secretion following ingestion of a carbohydrate load affects a multitude of metabolic pathways that simultaneously change direction and quantity of interorgan fluxes of sugars, lipids and amino acids. In the present study, we aimed at identifying markers associated with differential responses to an OGTT a population of healthy adults. By use of three metabolite profiling platforms, we assessed these postprandial responses of a total of 202 metabolites in plasma of 72 healthy volunteers undergoing comprehensive phenotyping and of which half enrolled into a weight-loss program over a three-month period.

Modeling Users' Cognitive Performance Using Digital Pen Features.

Digital pen features model characteristics of sketches and user behavior, and can be used for various supervised machine learning (ML) applications, such as multi-stroke sketch recognition and user modeling. In this work, we use a state-of-the-art set of more than 170 digital pen features, which we implement and make publicly available. The feature set is evaluated in the use case of analyzing paper-pencil-based neurocognitive assessments in the medical domain.

TATL: Task agnostic transfer learning for skin attributes detection.

Existing skin attributes detection methods usually initialize with a pre-trained Imagenet network and then fine-tune on a medical target task. However, we argue that such approaches are suboptimal because medical datasets are largely different from ImageNet and often contain limited training samples. In this work, we propose Task Agnostic Transfer Learning (TATL), a novel framework motivated by dermatologists' behaviors in the skincare context.

Patients with persistent idiopathic dentoalveolar pain in dental practice.

Aim: To assess whether persistent idiopathic dentoalveolar pain (PIDAP), a diagnosis of exclusion, exhibits common features that can facilitate its diagnosis. PIDAP is defined by the International Classification of Orofacial Pain (ICOP 6.3.

Investigating the Usability of a Head-Mounted Display Augmented Reality Device in Elementary School Children.

Augmenting reality via head-mounted displays (HMD-AR) is an emerging technology in education. The interactivity provided by HMD-AR devices is particularly promising for learning, but presents a challenge to human activity recognition, especially with children. Recent technological advances regarding speech and gesture recognition concerning Microsoft's HoloLens 2 may address this prevailing issue.

Automatic Visual Attention Detection for Mobile Eye Tracking Using Pre-Trained Computer Vision Models and Human Gaze.

Processing visual stimuli in a scene is essential for the human brain to make situation-aware decisions. These stimuli, which are prevalent subjects of diagnostic eye tracking studies, are commonly encoded as rectangular areas of interest (AOIs) per frame. Because it is a tedious manual annotation task, the automatic detection and annotation of visual attention to AOIs can accelerate and objectify eye tracking research, in particular for mobile eye tracking with egocentric video feeds.

A multicentric survey to evaluate preclinical education in Endodontology in German-speaking countries.

Aim: To evaluate preclinical education in Endodontology at Austrian, German and Swiss dental schools using an online survey.

Methodology: An online survey divided into nine categories was sent using SurveyMonkey software to 37 dental schools, before the spread of the COVID-19 pandemic. The questionnaire included 50 questions to evaluate preclinical endodontic education, such as faculty-to-student ratios, topics taught and materials used, in preclinical phantom head courses.

Evaluation of 15 years of modeled atmospheric oxidized nitrogen compounds across the contiguous United States.

Atmospheric nitrogen oxide and nitrogen dioxide (NO + NO, together termed as NO ) estimates from annual photochemical simulations for years 2002-2016 are compared to surface network measurements of NO and total gas-phase-oxidized reactive nitrogen (NO ) to evaluate the Community Multiscale Air Quality (CMAQ) modeling system performance by U.S. region, season, and time of day.

[Artificial intelligence in medicine and gynecology-the wrong track or promise of cure?].

Artificial intelligence (AI) has attained a new level of maturity in recent years and is becoming the driver of digitalization in all areas of life. AI is a cross-sectional technology with great importance for all areas of medicine employing image data, text data and bio-data. There is no medical field that will remain unaffected by AI, with AI-assisted clinical decision-making assuming a particularly important role.

ARETT: Augmented Reality Eye Tracking Toolkit for Head Mounted Displays.

Currently an increasing number of head mounted displays (HMD) for virtual and augmented reality (VR/AR) are equipped with integrated eye trackers. Use cases of these integrated eye trackers include rendering optimization and gaze-based user interaction. In addition, visual attention in VR and AR is interesting for applied research based on eye tracking in cognitive or educational sciences for example.

Digital pen technology for conducting cognitive assessments: a cross-over study with older adults.

Many digitalized cognitive assessments exist to increase reliability, standardization, and objectivity. Particularly in older adults, the performance of digitized cognitive assessments can lead to poorer test results if they are unfamiliar with the computer, mouse, keyboard, or touch screen. In a cross-over design study, 40 older adults (age M = 74.

Modeling Obesity in Norway (The MOON Study): A Decision-Analytic Approach-Prevalence, Costs, and Years of Life Lost.

Background: Limited knowledge exists on the expected long-term effects and cost-effectiveness of initiatives aiming to reduce the burden of obesity.

Aim: To develop a Norwegian obesity-focused disease-simulation model: the MOON model.

Material And Methods: We developed a Markov model and simulated a Norwegian birth cohort's movement between the health states "normal weight,""overweight,""obese 1,""obese 2," and "dead" using a lifetime perspective.

Image quality of a portable X-ray device (Nomad Pro 2) compared to a wall-mounted device in intraoral radiography.

Objectives: The aim of this study was to determine whether a handheld (HH) X-ray device (Nomad Pro 2) is capable of producing equivalent or even superior X-ray image quality in comparison to a wall-mounted (WM) dental X-ray unit (Heliodent Plus) on the basis of objectifiable image quality parameters.

Methods: Anatomical, radiological and biological dental X-ray image quality parameters of a handheld dental X-ray device (Nomad Pro 2, Kavo Kerr, Biberach, Germany) were compared to a standard wall-mounted dental X-ray unit (Heliodent Plus, Sirona Dental Systems, Bensheim, Germany) using a maxillofacial phantom. In addition, the effect of different operators (dentists, dental students, dental assistants) on the dental X-ray image quality was measured.

Assessing the Lifetime Cost-Effectiveness of Low-Protein Infant Formula as Early Obesity Prevention Strategy: The CHOP Randomized Trial.

Background: Although there is a growing number of early childhood obesity prevention programs, only a few of them are effective in the long run. Even fewer reports exist on lifetime cost-effectiveness of early prevention strategies. This paper aimed to assess the lifetime cost-effectiveness of infant feeding modification aiming at reducing risk of later obesity.

[Artificial intelligence in medicine-the wrong track or promise of cure?].

Artificial intelligence (AI) has attained a new level of maturity in recent years and is developing into the driver of digitalization in all areas of life. AI is a cross-sectional technology with great importance for all branches of medicine employing imaging as well as text and biodata. There is no field of medicine that remains unaffected by AI, with AI-assisted clinical decision-making assuming a particularly important role.

The potential for long-term cost-effectiveness of obesity prevention interventions in the early years of life.

Background: Early childhood obesity prevention is gaining increasing importance, as the prevalence of children with overweight and obesity aged 5 years and under increases worldwide. Along with understanding the effectiveness of obesity interventions, it is important to understand the cost-effectiveness of interventions over time.

Objectives: To estimate the long-term health benefits and health care cost-savings of reductions in BMI for the Australian population of children aged between 2 and 5 years.