Solid and Effective Upper Limb Segmentation in Egocentric Vision

Upper limb segmentation in egocentric vision is a challenging and nearly unexplored task that extends the well-known hand localization problem and can be crucial for a realistic representation of users' limbs in immersive and interactive environments, such as VR/MR applications designed for web browsers that are a general-purpose solution suitable for any device. Existing hand and arm segmentation approaches require a large amount of well-annotated data. Then different annotation techniques were designed, and several datasets were created. Such datasets are often limited to synthetic and semi-synthetic data that do not include the whole limb and differ significantly from real data, leading to poor performance in many realistic cases. To overcome the limitations of previous methods and the challenges inherent in both egocentric vision and segmentation, we trained several segmentation networks based on the state-of-the-art DeepLabv3+ model, collecting a large-scale comprehensive dataset. It consists of 46 thousand real-life and well-labeled RGB images with a great variety of skin colors, clothes, occlusions, and lighting conditions. In particular, we carefully selected the best data from existing datasets and added our EgoCam dataset, which includes new images with accurate labels. Finally, we extensively evaluated the trained networks in unconstrained real-world environments to find the best model configuration for this task, achieving promising and remarkable results in diverse scenarios. The code, the collected egocentric upper limb segmentation dataset, and a video demo of our work will be available on the project page1

Human segmentation in surveillance video with deep learning

Advanced intelligent surveillance systems are able to automatically analyze video of surveillance data without human intervention. These systems allow high accuracy of human activity recognition and then a high-level activity evaluation. To provide such features, an intelligent surveillance system requires a background subtraction scheme for human segmentation that captures a sequence of images containing moving humans from the reference background image. This paper proposes an alternative approach for human segmentation in videos through the use of a deep convolutional neural network. Two specific datasets were created to train our network, using the shapes of 35 different moving actors arranged on background images related to the area where the camera is located, allowing the network to take advantage of the entire site chosen for video surveillance. To assess the proposed approach, we compare our results with an Adobe Photoshop tool called Select Subject, the conditional generative adversarial network Pix2Pix, and the fully-convolutional model for real-time instance segmentation Yolact. The results show that the main benefit of our method is the possibility to automatically recognize and segment people in videos without constraints on camera and people movements in the scene (Video, code and datasets are available at http://graphics.unibas.it/www/HumanSegmentation/index.md.html)

A Preliminary Investigation into a Deep Learning Implementation for Hand Tracking on Mobile Devices

Hand tracking is an essential component of computer graphics and human-computer interaction applications. The use of RGB camera without specific hardware and sensors (e.g., depth cameras) allows developing solutions for a plethora of devices and platforms. Although various methods were proposed, hand tracking from a single RGB camera is still a challenging research area due to occlusions, complex backgrounds, and various hand poses and gestures. We present a mobile application for 2D hand tracking from RGB images captured by the smartphone camera. The images are processed by a deep neural network, modified specifically to tackle this task and run on mobile devices, looking for a compromise between performance and computational time. Network output is used to show a 2D skeleton on the user's hand. We tested our system on several scenarios, showing an interactive hand tracking level and achieving promising results in the case of variable brightness and backgrounds and small occlusions

Freehand-Steering Locomotion Techniques for Immersive Virtual Environments: A Comparative Evaluation

Virtual reality has achieved significant popularity in recent years, and allowing users to move freely within an immersive virtual world has become an important factor critical to realize. The user’s interactions are generally designed to increase the perceived realism, but the locomotion techniques and how these affect the user’s task performance still represent an open issue, much discussed in the literature. In this article, we evaluate the efficiency and effectiveness of, and user preferences relating to, freehand locomotion techniques designed for an immersive virtual environment performed through hand gestures tracked by a sensor placed in the egocentric position and experienced through a head-mounted display. Three freehand locomotion techniques have been implemented and compared with each other, and with a baseline technique based on a controller, through qualitative and quantitative measures. An extensive user study conducted with 60 subjects shows that the proposed methods have a performance comparable to the use of the controller, further revealing the users’ preference for decoupling the locomotion in sub-tasks, even if this means renouncing precision and adapting the interaction to the possibilities of the tracker sensor

Pancreaticoduodenectomy model demonstrates a fundamental role of dysfunctional β cells in predicting diabetes

BACKGROUND. The appearance of hyperglycemia is due to insulin resistance, functional deficits in the secretion of insulin, and a reduction of β cell mass. There is a long-standing debate as to the relative contribution of these factors to clinically manifesting β cell dysfunction. The aim of this study was to verify the acute effect of one of these factors, the reduction of β cell mass, on the subsequent development of hyperglycemia. METHODS. To pursue this aim, nondiabetic patients, scheduled for identical pancreaticoduodenectomy surgery, underwent oral glucose tolerance tests (OGTT) and hyperglycemic clamp (HC) procedures, followed by arginine stimulation before and after surgery. Based on postsurgery OGTT, subjects were divided into 3 groups depending on glucose tolerance: normal glucose tolerance (post-NGT), impaired glucose tolerance (post-IGT), or having diabetes mellitus (post-DM). RESULTS. At baseline, the 3 groups showed similar fasting glucose and insulin levels; however, examining the various parameters, we found that reduced first-phase insulin secretion, reduced glucose sensitivity, and rate sensitivity were predictors of eventual postsurgery development of IGT and diabetes. CONCLUSION. Despite comparable functional mass and fasting glucose and insulin levels at baseline and the very same 50% mass reduction, only reduced first-phase insulin secretion and glucose sensitivity predicted the appearance of hyperglycemia. These functional alterations could be pivotal to the pathogenesis of type 2 diabetes (T2DM)

Effect of Dapagliflozin on Myocardial Insulin Sensitivity and Perfusion: Rationale and Design of The DAPAHEART Trial

Introduction: Sodium-glucose co-transporter-2 (SGLT-2) inhibitors have been shown to have beneficial effects on various cardiovascular (CV) outcomes in patients with type 2 diabetes (T2D) in primary prevention and in those with a high CV risk profile. However, the mechanism(s) responsible for these CV benefits remain elusive and unexplained. The aim of the DAPAHEART study will be to demonstrate that treatment with SGLT-2 inhibitors is associated with greater myocardial insulin sensitivity in patients with T2D, and to determine whether this improvement can be attributed to a decrease in whole-body (and tissue-specific) insulin resistance and to increased myocardial perfusion and/or glucose uptake. We will also determine whether there is an appreciable degree of improvement in myocardial-wall conditions subtended by affected and non-affected coronary vessels, and if this relates to changes in left ventricular function. Methods: The DAPAHEART trial will be a phase III, single-center, randomized, two-arm, parallel-group, double-blind, placebo-controlled study. A cohort of 52 T2D patients with stable coronary artery disease (without any previous history of myocardial infarction, with or without previous percutaneous coronary intervention), with suboptimal glycemic control (glycated hemoglobin [HbA1c] 7\u20138.5%) on their current standard of care anti-hyperglycemic regimen, will be randomized in a 1:1 ratio to dapagliflozin or placebo. The primary outcome is to detect changes in myocardial glucose uptake from baseline to 4 weeks after treatment initiation. The main secondary outcome will be changes in myocardial blood flow, as measured by 13N-ammonia positron emission tomography/computed tomography (PET/CT). Other outcomes include cardiac function, glucose uptake in skeletal muscle, adipose tissue, liver, brain and kidney, as assessed by fluorodeoxyglucose (FDG) PET-CT imaging during hyperinsulinemic-euglycemic clamp; pericardial, subcutaneous and visceral fat, and browning as observed on CT images during FDG PET-CT studies; systemic insulin sensitivity, as assessed by hyperinsulinemic-euglycemic clamp, glycemic control, urinary glucose output; and microbiota modification. Discussion: SGLT-2 inhibitors, in addition to their insulin-independent plasma glucose-lowering effect, are able to directly (substrate availability, fuel utilization, insulin sensitivity) as well as indirectly (cardiac after-load reduction, decreased risk factors for heart failure) affect myocardial functions. Our study will provide novel insights into how these drugs exert CV protection in a diabetic population. Trial registration: EudraCT No. 2016-003614-27; ClinicalTrials.gov Identifier: NCT03313752

Dapagliflozin treatment is associated with a reduction of epicardial adipose tissue thickness and epicardial glucose uptake in human type 2 diabetes

Objective: We recently demonstrated that treatment with sodium-glucose cotransporter-2 inhibitors (SGLT-2i) leads to an increase in myocardial flow reserve in patients with type 2 diabetes (T2D) with stable coronary artery disease (CAD). The mechanism by which this occurs is, however, unclear. One of the risk factors for cardiovascular disease is inflammation of epicardial adipose tissue (EAT). Since the latter is often increased in type 2 diabetes patients, it could play a role in coronary microvascular dysfunction. It is also well known that SGLT-2i modify adipose tissue metabolism. We aimed to investigate the effects of the SGLT-2i dapagliflozin on metabolism and visceral and subcutaneous adipose tissue thickness in T2D patients with stable coronary artery disease and to verify whether these changes could explain observed changes in myocardial flow. Methods: We performed a single-center, prospective, randomized, double-blind, controlled clinical trial with 14 T2D patients randomized 1:1 to SGLT-2i dapagliflozin (10 mg daily) or placebo. The thickness of visceral (epicardial, mediastinal, perirenal) and subcutaneous adipose tissue and glucose uptake were assessed at baseline and 4 weeks after treatment initiation by 2-deoxy-2-[18F]fluoro-D-glucose Positron Emission Tomography/Computed Tomography during hyperinsulinemic euglycemic clamp. Results: The two groups were well-matched for baseline characteristics (age, diabetes duration, HbA1c, BMI, renal and heart function). Dapagliflozin treatment significantly reduced EAT thickness by 19% (p = 0.03). There was a significant 21.6% reduction in EAT glucose uptake during euglycemic hyperinsulinemic clamp in the dapagliflozin group compared with the placebo group (p = 0.014). There were no significant effects on adipose tissue thickness/metabolism in the other depots explored. Conclusions: SGLT-2 inhibition selectively reduces EAT thickness and EAT glucose uptake in T2D patients, suggesting a reduction of EAT inflammation. This could explain the observed increase in myocardial flow reserve, providing new insights into SGLT-2i cardiovascular benefits

The Mechanism of Substrate Inhibition in Human Indoleamine 2,3-Dioxygenase

Indoleamine 2,3-dioxygenase catalyzes the O(2)-dependent oxidation of L-tryptophan (L-Trp) to N-formylkynurenine (NFK) as part of the kynurenine pathway. Inhibition of enzyme activity at high L-Trp concentrations was first noted more than 30 years ago, but the mechanism of inhibition has not been established. Using a combination of kinetic and reduction potential measurements, we present evidence showing that inhibition of enzyme activity in human indoleamine 2,3-dioxygenase (hIDO) and a number of site-directed variants during turnover with L-tryptophan (L-Trp) can be accounted for by the sequential, ordered binding of O(2) and L-Trp. Analysis of the data shows that at low concentrations of L-Trp, O(2) binds first followed by the binding of L-Trp; at higher concentrations of L-Trp, the order of binding is reversed. In addition, we show that the heme reduction potential (E(m)(0)) has a regulatory role in controlling the overall rate of catalysis (and hence the extent of inhibition) because there is a quantifiable correlation between E(m)(0) (that increases in the presence of L-Trp) and the rate constant for O(2) binding. This means that the initial formation of ferric superoxide (Fe(3+)-O(2)(•-)) from Fe(2+)-O(2) becomes thermodynamically less favorable as substrate binds, and we propose that it is the slowing down of this oxidation step at higher concentrations of substrate that is the origin of the inhibition. In contrast, we show that regeneration of the ferrous enzyme (and formation of NFK) in the final step of the mechanism, which formally requires reduction of the heme, is facilitated by the higher reduction potential in the substrate-bound enzyme and the two constants (k(cat) and E(m)(0)) are shown also to be correlated. Thus, the overall catalytic activity is balanced between the equal and opposite dependencies of the initial and final steps of the mechanism on the heme reduction potential. This tuning of the reduction potential provides a simple mechanism for regulation of the reactivity, which may be used more widely across this family of enzymes

The Mechanism of Formation of N-Formylkynurenine by Heme Dioxygenases

[Image: see text] Heme dioxygenases catalyze the oxidation of l-tryptophan to N-formylkynurenine (NFK), the first and rate-limiting step in tryptophan catabolism. Although recent progress has been made on early stages in the mechanism, there is currently no experimental data on the mechanism of product (NFK) formation. In this work, we have used mass spectrometry to examine product formation in a number of dioxygenases. In addition to NFK formation (m/z = 237), the data identify a species (m/z = 221) that is consistent with insertion of a single atom of oxygen into the substrate during O(2)-driven turnover. The fragmentation pattern for this m/z = 221 species is consistent with a cyclic amino acetal structure; independent chemical synthesis of the 3a-hydroxypyrroloindole-2-carboxylic acid compound is in agreement with this assignment. Labeling experiments with (18)O(2) confirm the origin of the oxygen atom as arising from O(2)-dependent turnover. These data suggest that the dioxygenases use a ring-opening mechanism during NFK formation, rather than Criegee or dioxetane mechanisms as previously proposed