A time local subset feature selection for prediction of sudden cardiac death from ECG signal

Prediction of sudden cardiac death continues to gain universal attention as a promising approach to saving millions of lives threatened by sudden cardiac death (SCD). This study attempts to promote the literature from mere feature extraction analysis to developing strategies for manipulating the extracted features to target improvement of classification accuracy. To this end, a novel approach to local feature subset selection is applied using meticulous methodologies developed in previous studies of this team for extracting features from non-linear, time-frequency, and classical processes. We are therefore enabled to select features that differ from one another in each 1-min interval before the incident. Using the proposed algorithm, SCD can be predicted 12 min before the onset; thus, more propitious results are achieved. Additionally, through defining a utility function and employing statistical analysis, the alarm threshold has effectively been determined as 83%. Having selected the best combination of features, the two classes are classified using the multilayer perceptron (MLP) classifier. The most effective features would subsequently be discussed considering their prevalence in the rank-based selection. The results indicate the significant capacity of the proposed method for predicting SCD as well as selecting the appropriate processing method at any time before the incident.

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Spatio-temporal Reconstruction of Neural Sources Using Indirect Dominant Mode Rejection

Adaptive minimum variance based beamformers (MVB) have been successfully applied to magnetoencephalogram (MEG) and electroencephalogram (EEG) data to localize brain activities. However, the performance of these beamformers falls down in situations where correlated or interference sources exist. To overcome this problem, we propose indirect dominant mode rejection (iDMR) beamformer application in brain source localization. This method by modifying measurement covariance matrix makes MVB applicable in source localization in the presence of correlated and interference sources. Numerical results on both EEG and MEG data demonstrate that presented approach accurately reconstructs time courses of active sources and localizes those sources with high spatial resolution. In addition, the results of real AEF data show the good performance of iDMR in empirical situations. Hence, iDMR can be reliably used for brain source localization especially when there are correlated and interference sources.     

Imaging of targeted lipid microbubbles to detect cancer cells using third harmonic generation microscopy

The use of receptor-targeted lipid microbubbles imaged by ultrasound is an innovative method of detecting and localizing disease. However, since ultrasound requires a medium between the transducer and the object being imaged, it is impractical to apply to an exposed surface in a surgical setting where sterile fields need be maintained and ultrasound gel may cause the bubbles to collapse. Multiphoton microscopy (MPM) is an emerging tool for accurate, label-free imaging of tissues and cells with high resolution and contrast. We have recently determined a novel application of MPM to be used for detecting targeted microbubble adherence to the upregulated plectin-receptor on pancreatic tumor cells. Specifically, the third-harmonic generation response can be used to detect bound microbubbles to various cell types presenting MPM as an alternative and useful imaging method. This is an interesting technique that can potentially be translated as a diagnostic tool for the early detection of cancer and inflammatory disorders.OCIS codes: (020.4180) Multiphoton processes, (170.1610) Clinical applications, (190.1900) Diagnostic applications of nonlinear optics, (320.7090) Ultrafast lasers     

Permissive role of cytosolic pH acidification in neurodegeneration: A closer look at its causes and consequences

The maintenance of cytosolic pH in its physiological range is required for normal neuronal activity, and even minor alterations can have serious consequences. This Review summarizes the current understanding of the conditions that are associated with cytosolic pH disruption and that lead to abnormal cytosolic acidification. Oxidative stress results in cytosolic acidification, and this plays a crucial role in the emergence of apoptosis in protein misfolding and excitotoxicity, ultimately leading to irreversible neuronal damage. Through the identification of mechanisms by which intraneuronal pH acidification promotes neurodegeneration, we may identify new approaches for preventing and treating neurodegenerative disorders. © 2016 Wiley Periodicals, Inc.     

Er:YAG laser vs. sharp debridement in management of chronic wounds: Effects on pain and bacterial load

Chronic wounds affect roughly 6.5 million patients in the US annually. Current standard of therapy entails weekly sharp debridement. However, the sharp technique is associated with significant pain, while having minimal impact on the bioburden. Our study proposes the Er:YAG laser as an alternative method of debridement that may decrease procedural pain, reduce bioburden, and potentially improve overall healing. This pilot study was performed as a prospective, randomized, controlled, crossover clinical trial, containing two groups: (1) one group underwent single laser debridement session first, followed by single sharp debridement session one week later; and (2) the other group underwent single sharp debridement session first, followed by single laser debridement session one week later. Variables analyzed included pain during debridement, pre‐ and post‐debridement wound sizes, pre‐ and post‐debridement bacterial loads and patient preference. Twenty‐two patients were enrolled (12 patients in Group 1, plus 10 patients in Group 2). The mean pain score for patients undergoing laser debridement was 3.0 ± 1.7 vs. 4.8 ± 2.6 for those undergoing sharp debridement (p = 0.003). The mean percent change in wound size 1‐week post‐laser debridement was ?20.8% ± 80.1%, as compared with ?36.7% ± 54.3% 1‐week post‐sharp debridement (p = 0.6). The percentage of patients who had a bacterial load in the low/negative category increased from 27.3% to 59.1% immediately after laser debridement (p = 0.04), vs. 54.5% to 68.2% immediately after sharp debridement (p = 0.38). Moreover, there was a sustained decrease in bacterial load 1‐week post‐laser debridement, as compared with no sustained decrease 1‐week post‐sharp debridement (p < 0.02). Overall, 52.9% of patients preferred laser debridement vs. 35.3% for sharp debridement. We believe that Er:YAG laser serves as a promising technology in chronic wounds, functioning as a potentially superior alternative to sharp debridement, the current standard of therapy.     

Total and differential leukocytes counts, but not hsCRP, ESR, and five fractioned serum proteins have significant potency to predict stable coronary artery disease

BACKGROUND: The role and diagnostic value of markers of inflammation is well recognized in acute coronary syndromes but it is uncertain in patients with stable coronary artery disease (CAD). This study was done to investigate the association of markers of inflammation with the occurrence and severity of CAD and to evaluate their predictive values. METHODS: Markers of inflammation, electrophoresis serum protein fractions, serum (apo)lipoproteins and classical risk factors were determined in 270 angiographically documented subjects. The subjects were classified as CAD cases and controls according to angiography. The severity of CAD was scored on the basis of the number and extent of lesions. RESULTS: The counts of total leukocytes (7.14+/-1.86 cell/nl vs. 6.58+/-1.62, p相似文献   

A gradient algorithm for solution of the optimal control problem for hybrid switching systems

In this article, an algorithm is presented for solving the optimal control problem for the general form of a hybrid switching system. The cost function comprises terminal, running and switching costs. The controlled system is an autonomous hybrid switching system with jumps either at some switching times or some time varying switching manifolds. The proposed algorithm is an extension of the first-order gradient method for the conventional optimal control problem. The algorithm requires a low computational effort. The system's dynamical equations together with a set of algebraic equations are solved at each iteration in order to find the descent direction. The convergence of algorithm is proved and examples are provided to demonstrate the efficiency of the algorithm for different types of hybrid switching system optimal control problems.