Search

Background: Diabetes is a risk factor for heart failure and promotes cardiac dysfunction. Diabetic tissues are associated with nicotinamide adenine dinucleotide (NAD + ) redox imbalance; however, the hypothesis that NAD + redox imbalance causes diabetic cardiomyopathy has not been tested. This investigation used mouse models with altered NAD + redox balance to test this hypothesis. Methods: Diabetic stress was induced in mice by streptozotocin. Cardiac function was measured by echocardiography. Heart and plasma samples were collected for biochemical, histological, and molecular analyses. Two mouse models with altered NAD + redox states (1, Ndufs4 [NADH:ubiquinone oxidoreductase subunit S4] knockout, cKO, and 2, NAMPT [nicotinamide phosphoribosyltranferase] transgenic mice, NMAPT) were used. Results: Diabetic stress caused cardiac dysfunction and lowered NAD + /NADH ratio (oxidized/reduced ratio of nicotinamide adenine dinucleotide) in wild-type mice. Mice with lowered cardiac NAD + /NADH ratio without baseline dysfunction, cKO mice, were challenged with chronic diabetic stress. NAD + redox imbalance in cKO hearts exacerbated systolic (fractional shortening: 27.6% versus 36.9% at 4 weeks, male cohort P P + redox imbalance promoted superoxide dismutase 2 acetylation, protein oxidation, troponin I S150 phosphorylation, and impaired energetics in diabetic cKO hearts. Importantly, elevation of cardiac NAD + levels by NAMPT normalized NAD + redox balance, alleviated cardiac dysfunction (fractional shortening: 40.2% versus 24.8% in cKO:NAMPT versus cKO, P P Conclusions: Our results show that NAD + redox imbalance to regulate acetylation and phosphorylation is a critical mediator of the progression of diabetic cardiomyopathy and suggest the therapeutic potential for diabetic cardiomyopathy by harnessing NAD + metabolism.

Diabetes is a risk factor of heart failure and leads to cardiac dysfunction, a condition named diabetic cardiomyopathy (DCM). NAD redox imbalance is observed in diabetic tissues. However, whether NAD redox imbalance promotes cardiac dysfunction in DCM remains unknown. The objective of this study is to determine the causal role of NAD redox imbalance in DCM.Type 1 diabetes was induced in C57BL6 mice by streptozotocin (STZ) injections, and DCM was allowed to develop for 16 weeks. Diabetes-induced chronic stress led to systolic and diastolic cardiac dysfunction along with a lowered NAD/NADH ratio. The diabetogenic protocol was applied to control and cardiac-specific Ndufs4-KO mice (cKO), a mouse model with lowered cardiac NAD/NADH without baseline cardiac dysfunction. Analyses of blood glucose and >200 metabolites in plasma showed no significant change in diabetic control and diabetic cKO mice, suggesting that their hearts experienced similar diabetic stress. Diabetic cKO hearts showed lowered NAD/NADH, aggravated contractile and relaxation dysfunction compared to the diabetic control hearts in both sexes. The data suggest that NAD redox imbalance exacerbated DCM. Collagen staining and transcript analyses of fibrosis-related genes showed no change in diabetic cKO hearts, signifying that the exacerbated dysfunction was due to cardiomyocyte dysfunction. A global protein acetylation was promoted in the diabetic cKO hearts with an increase in SOD2 acetylation levels at lysine-68 (SOD2-K68Ac) and enhanced protein oxidation. Diabetic cKO mice displayed enhanced levels of TnI S150 phosphorylation (TnI-S150Pi), but not phosphorylation of TnI-S23/24 or MyBPc-S282. These data suggest that enhanced oxidative stress and altered myofilament Ca 2+ sensitivity via TnI-S150Pi are responsible for the NAD redox imbalance-exacerbated DCM.To confirm the role of NAD redox imbalance in DCM, we elevated cardiac NAD levels in diabetic cKO mice by cardiac-specific expression of NAMPT. Expression of NAMPT in the heart improved cardiac systolic and diastolic function in diabetic cKO hearts. This was due to increased NAD/NADH ratio and reversed pathogenic mechanisms (lowered SOD2-K68Ac and TnI-S150Pi). This study supports the causal role of NAD redox imbalance in DCM.

Thermal images are mainly used to detect the presence of people at night or in bad lighting conditions, but perform poorly at daytime. To solve this problem, most state-of-the-art techniques employ a fusion network that uses features from paired thermal and color images. Instead, we propose to augment thermal images with their saliency maps, to serve as an attention mechanism for the pedestrian detector especially during daytime. We investigate how such an approach results in improved performance for pedestrian detection using only thermal images, eliminating the need for paired color images. For our experiments, we train the Faster R-CNN for pedestrian detection and report the added effect of saliency maps generated using static and deep methods (PiCA-Net and R3-Net). Our best performing model results in an absolute reduction of miss rate by 13.4% and 19.4% over the baseline in day and night images respectively. We also annotate and release pixel level masks of pedestrians on a subset of the KAIST Multispectral Pedestrian Detection dataset, which is a first publicly available dataset for salient pedestrian detection., Comment: Accepted at CVPR 2019 Workshop (PBVS), 10 pages, 7 figures

In this paper, we apply speech and audio processing techniques to bird vocalizations and for the classification of birds found in the lower Himalayan regions. Mel frequency cepstral coefficients (MFCC) are extracted from each recording. As a result, the recordings are now represented as varying length sets of feature vectors. Dynamic kernel based support vector machines (SVMs) and deep neural networks (DNNs) are popularly used for the classification of such varying length patterns obtained from speech signals. In this work, we propose to use dynamic kernel based SVMs and DNNs for classification of bird calls represented as sets of feature vectors. Results of our studies show that both approaches give comparable performance.

An Intelligent Fixturing System (IFS) is currently being developed to hold a family of cylinder heads for machining operations. This system incorporates a Part Location System (PLS) to locate the workpiece reference frame of a cylinder head relative to a pallet. This two-part paper describes the development and evaluation of various part location algorithms that have been created for this application. Part 1 of this paper provides a detailed description of the IFS and the PLS and of the cylinder head location problem. It also provides a detailed description of three different algorithms that were developed for the PLS. The first algorithm, SeQuential Least Squares (SQLS), is based on the sequential, parametric regression model. The second class of algorithms, SiMultaneous Least Squares (SMLS), is based on the simultaneous, parametric regression model. The third algorithm, SQLS-SMLS (fixed cd) is a hybrid of the first two methods.

An Intelligent Fixturing System (IFS) is currently being developed to hold a family of cylinder heads for machining operations. This system incorporates a Part Location System (PLS) to locate the workpiece reference frame of a cylinder head relative to a pallet. This two-part paper describes the development and evaluation of various part location algorithms that have been created for this application. Part 2 of this paper describes a series of simulation experiments that was carried out to assess the accuracy and computation speed of the SeQuential Least Squares (SQLS) algorithm, the SiMultaneous Least Squares (SMLS) algorithm, and the SQLS-SMLS (fixed cd) algorithm. The results of this study reveal that the SQLS algorithm is fast to execute, but its accuracy is very sensitive to random variations in the coordinate data. Alternatively, the SMLS algorithm is insensitive to random variations in the coordinate data but is computationally more expensive to execute. Furthermore, its accuracy is sensitive to bias errors in the chordal distance between the dowel holes. Only the SQLS-SMLS (fixed cd) is insensitive to both types of variations.