Hypertriglyceridemic Waist Phenotype Predicts Increased Visceral Fat in Subjects With Type 2 Diabetes

OBJECTIVE: Greater accumulation of visceral fat is strongly linked to risk of cardiovascular disease. However, elevated waist circumference by itself does not always identify individuals with increased visceral fat. RESEARCH DESIGN AND METHODS: We examined 375 subjects with type 2 diabetes from the CHICAGO cohort for presence of hypertriglyceridemic waist phenotype (waist circumference >90 cm in men or >85 cm in women, in conjunction with a plasma triglyceride concentration of ≥177 mg/dl) to determine its usefulness for identifying subjects with increased amounts of visceral fat. We divided subjects into three groups: group 1 (low waist circumference and low triglycerides; waist circumference ≤90 cm in men or ≤85 cm in women and triglyceride <177 mg/dl, n = 18), group 2 (high waist circumference and low triglycerides; waist circumference >90 cm in men or >85 cm in women and triglycerides <177 mg/dl, n = 230), and group 3 (high waist circumference and high triglycerides; waist circumference >90 cm in men or >85 cm in women and triglycerides ≥177 mg/dl, n = 127). RESULTS: Subjects in group 3 had significantly higher visceral fat (P < 0.0001), A1C (P < 0.01), and coronary artery calcium (P < 0.05) compared with group 2, despite similar age, BMI, and waist circumference. The relationship of the phenotype to atherosclerosis, however, was attenuated by adjustment for HDL cholesterol, triglyceride-rich lipoprotein cholesterol, apolipoprotein B, or LDL particle number. CONCLUSIONS: The presence of hypertriglyceridemic waist phenotype in subjects with type 2 diabetes identifies a subset with greater degree of visceral adiposity. This subset also has greater degree of subclinical atherosclerosis that may be related to the proatherogenic lipoprotein changes.Takeda Global Research and Development; National Institutes of Health (DK 71711); University of Illinois at Chicag

Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping

We present an autoencoder-based semi-supervised approach to classify perceived human emotions from walking styles obtained from videos or motion-captured data and represented as sequences of 3D poses. Given the motion on each joint in the pose at each time step extracted from 3D pose sequences, we hierarchically pool these joint motions in a bottom-up manner in the encoder, following the kinematic chains in the human body. We also constrain the latent embeddings of the encoder to contain the space of psychologically-motivated affective features underlying the gaits. We train the decoder to reconstruct the motions per joint per time step in a top-down manner from the latent embeddings. For the annotated data, we also train a classifier to map the latent embeddings to emotion labels. Our semi-supervised approach achieves a mean average precision of 0.84 on the Emotion-Gait benchmark dataset, which contains both labeled and unlabeled gaits collected from multiple sources. We outperform current state-of-art algorithms for both emotion recognition and action recognition from 3D gaits by 7%--23% on the absolute. More importantly, we improve the average precision by 10%--50% on the absolute on classes that each makes up less than 25% of the labeled part of the Emotion-Gait benchmark dataset.Comment: In proceedings of the 16th European Conference on Computer Vision, 2020. Total pages 18. Total figures 5. Total tables

Current directions in visual working memory research: An introduction and emerging insights

Visual working memory (VWM) is a core construct in the cognitive (neuro-)sciences, assumed to serve as a hub for information exchange and thus supporting a multitude of cognitive functions related to processing visual information. Here, we give an introduction into key terms and paradigms and an overview of ongoing debates in the field, to which the articles collected in this Special Issue on 'Current Directions in Visual Working Memory Research' contribute. Our aim is to extract, from this overview, some 'emerging' theoretical insights concerning questions such as the optimal way to examine VWM, which types of mental representations contribute to performance on VWM tasks, and how VWM keeps features from the same object together and apart from features of concurrently maintained objects (the binding problem)

Assessment of coronary artery disease and calcified coronary plaque burden by computed tomography in patients with and without diabetes mellitus

Purpose: To compare the coronary atherosclerotic burden in patients with and without type-2 diabetes using CT Coronary Angiography (CTCA). Methods and Materials: 147 diabetic (mean age: 65 ± 10 years; male: 89) and 979 nondiabetic patients (mean age: 61 ± 13 years; male: 567) without a history of coronary artery disease (CAD) underwent CTCA. The per-patient number of diseased coronary segments was determined and each diseased segment was classified as showing obstructive lesion (luminal narrowing >50%) or not. Coronary calcium scoring (CCS) was assessed too. Results: Diabetics showed a higher number of diseased segments (4.1 ± 4.2 vs. 2.1 ± 3.0; p 400 (p < 0.001), obstructive CAD (37% vs. 18% of patients; p < 0.0001), and fewer normal coronary arteries (20% vs. 42%; p < 0.0001), as compared to nondiabetics. The percentage of patients with obstructive CAD paralleled increasing CCS in both groups. Diabetics with CCS ≤ 10 had a higher prevalence of coronary plaque (39.6% vs. 24.5%, p = 0.003) and obstructive CAD (12.5% vs. 3.8%, p = 0.01). Among patients with CCS ≤ 10 all diabetics with obstructive CAD had a zero CCS and one patient was asymptomatic. Conclusions: Diabetes was associated with higher coronary plaque burden. The present study demonstrates that the absence of coronary calcification does not exclude obstructive CAD especially in diabetics

Non-invasive cardiac imaging techniques and vascular tools for the assessment of cardiovascular disease in type 2 diabetes mellitus

Cardiovascular disease is the major cause of mortality in type 2 diabetes mellitus. The criteria for the selection of those asymptomatic patients with type 2 diabetes who should undergo cardiac screening and the therapeutic consequences of screening remain controversial. Non-invasive techniques as markers of atherosclerosis and myocardial ischaemia may aid risk stratification and the implementation of tailored therapy for the patient with type 2 diabetes. In the present article we review the literature on the implementation of non-invasive vascular tools and cardiac imaging techniques in this patient group. The value of these techniques as endpoints in clinical trials and as risk estimators in asymptomatic diabetic patients is discussed. Carotid intima–media thickness, arterial stiffness and flow-mediated dilation are abnormal long before the onset of type 2 diabetes. These vascular tools are therefore most likely to be useful for the identification of ‘at risk’ patients during the early stages of atherosclerotic disease. The additional value of these tools in risk stratification and tailored therapy in type 2 diabetes remains to be proven. Cardiac imaging techniques are more justified in individuals with a strong clinical suspicion of advanced coronary heart disease (CHD). Asymptomatic myocardial ischaemia can be detected by stress echocardiography and myocardial perfusion imaging. The more recently developed non-invasive multi-slice computed tomography angiography is recommended for exclusion of CHD, and can therefore be used to screen asymptomatic patients with type 2 diabetes, but has the associated disadvantages of high radiation exposure and costs. Therefore, we propose an algorithm for the screening of asymptomatic diabetic patients, the first step of which consists of coronary artery calcium score assessment and exercise ECG

Coronary artery calcium screening: current status and recommendations from the European Society of Cardiac Radiology and North American Society for Cardiovascular Imaging

Current guidelines and literature on screening for coronary artery calcium for cardiac risk assessment are reviewed for both general and special populations. It is shown that for both general and special populations a zero score excludes most clinically relevant coronary artery disease. The importance of standardization of coronary artery calcium measurements by multi-detector CT is discussed

Visual long-term memory has weaker fidelity than working memory

ABSTRACT Recent research suggests that visual long-term memory (VLTM) and visual working memory (VWM) possess similar resolution for feature memory. We investigated resolution in more holistic terms, exploiting a two alternative forced choice (2AFC) procedure and injecting noise into stimuli. Participants were exposed to two real-world objects per trial in a VWM experiment. One object was tested after a short delay. The other object (from each trial) was tested in a later session. We observed better performance for VWM, and the two systems were affected by noise in distinct ways. These results have broad implications for theories of visual memory

You Cannot “Count” How Many Items People Remember in Visual Working Memory: The Importance of Signal Detection–Based Measures for Understanding Change Detection Performance

Change detection tasks are commonly used to measure and understand the nature of visual working memory capacity. Across three experiments, we examine whether the nature of the memory signals used to perform change detection are continuous or all-or-none and consider the implications for proper measurement of performance. In Experiment 1, we find evidence from confidence reports that visual working memory is continuous in strength, with strong support for an equal variance signal detection model with no guesses or lapses. Experiments 2 and 3 test an implication of this, which is that K should confound response criteria and memory. We found K values increased by roughly 30% when criteria are shifted despite no change in the underlying memory signals. Overall, our data call into question a large body of work using threshold measures, like K, to analyze change detection data. This metric confounds response bias with memory performance and is inconsistent with the vast majority of visual working memory models, which propose variations in precision or strength are present in working memory. Instead, our data indicate an equal variance signal detection model (and thus, d')-without need for lapses or guesses-is sufficient to explain change detection performance. (PsycInfo Database Record (c) 2022 APA, all rights reserved)