Studying diastology with speckle tracking echocardiography: The essentials

Diastolic dysfunction is common in cardiac disease and an important finding independent of systolic function as it contributes to the signs and symptoms of heart failure. Tissue Doppler mitral early diastolic velocity (Ea) combined with peak transmitral early diastolic velocity (E) to obtain E/Ea ratio provides an estimate of the left ventricular (LV) filling pressure. However, E/Ea has a significant gray zone and less reliable in patients with preserved ejection fraction (>50%). Two-dimensional echocardiographic speckle tracking measure myocardial strain and strain rate (Sr) avoiding the Doppler-associated angulation errors and tethering artifacts. Global myocardial peak diastolic strain (Ds) and diastolic Sr (DSr) at the time of E and isovolumic relaxation combined with E (E/Ds and E/10 DSr) have been recently proposed as novel indices to determine LV filling pressure. The present article elucidates the methodology of studying diastology with strain echocardiography along with the advantages and limitations of the novel technique in light of the available literature.

Study of the sign change of exchange bias across the spin reorientation transition in Co(Cr1-x Fe x )2O4 (x = 0.00-0.125)

We present the evolution of novel phenomena of magnetic compensation effect, exchange bias (EB) effect and the field induced anomalies in '[Formula: see text]' substituted multiferroic compound [Formula: see text]. A few percent of '[Formula: see text]' substitution for '[Formula: see text]' in [Formula: see text] results in the reversal of field cooled magnetization under low applied fields below compensation temperature T _comp. Further, increase in the field leads to the spin reorientation transition (T _SR). Signature of EB in a narrow temperature window in the vicinity of T _SR and its sign change across T _SR is observed. Magnitude of EB depends on the amount of compensation and rigidity of the spin reorientation. We also notice the appearance of positive EB below the lock-in transition (T _L). Presence of unidirectional anisotropy developed in the commensurate spin-spiral below T _L could be responsible for the appearance of EB below T _L.

Management standards for stable coronary artery disease in India

Coronary artery disease (CAD) is one of the important causes of cardiovascular morbidity and mortality globally, giving rise to more than 7 million deaths annually. An increasing burden of CAD in India is a major cause of concern with angina being the leading manifestation. Stable coronary artery disease (SCAD) is characterised by episodes of transient central chest pain (angina pectoris), often triggered by exercise, emotion or other forms of stress, generally triggered by a reversible mismatch between myocardial oxygen demand and supply resulting in myocardial ischemia or hypoxia. A stabilised, frequently asymptomatic phase following an acute coronary syndrome (ACS) is also classified as SCAD. This definition of SCAD also encompasses vasospastic and microvascular angina under the common umbrella.

2B-Alert Web: An Open-Access Tool for Predicting the Effects of Sleep/Wake Schedules and Caffeine Consumption on Neurobehavioral Performance

STUDY OBJECTIVES

Computational tools that predict the effects of daily sleep/wake amounts on neurobehavioral performance are critical components of fatigue management systems, allowing for the identification of periods during which individuals are at increased risk for performance errors. However, none of the existing computational tools is publicly available, and the commercially available tools do not account for the beneficial effects of caffeine on performance, limiting their practical utility. Here, we introduce 2B-Alert Web, an open-access tool for predicting neurobehavioral performance, which accounts for the effects of sleep/wake schedules, time of day, and caffeine consumption, while incorporating the latest scientific findings in sleep restriction, sleep extension, and recovery sleep.

METHODS

We combined our validated Unified Model of Performance and our validated caffeine model to form a single, integrated modeling framework instantiated as a Web-enabled tool. 2B-Alert Web allows users to input daily sleep/wake schedules and caffeine consumption (dosage and time) to obtain group-average predictions of neurobehavioral performance based on psychomotor vigilance tasks. 2B-Alert Web is accessible at: https://2b-alert-web.bhsai.org.

RESULTS

The 2B-Alert Web tool allows users to obtain predictions for mean response time, mean reciprocal response time, and number of lapses. The graphing tool allows for simultaneous display of up to seven different sleep/wake and caffeine schedules. The schedules and corresponding predicted outputs can be saved as a Microsoft Excel file; the corresponding plots can be saved as an image file. The schedules and predictions are erased when the user logs off, thereby maintaining privacy and confidentiality.

CONCLUSIONS

The publicly accessible 2B-Alert Web tool is available for operators, schedulers, and neurobehavioral scientists as well as the general public to determine the impact of any given sleep/wake schedule, caffeine consumption, and time of day on performance of a group of individuals. This evidence-based tool can be used as a decision aid to design effective work schedules, guide the design of future sleep restriction and caffeine studies, and increase public awareness of the effects of sleep amounts, time of day, and caffeine on alertness.

Evidence for bulk superconductivity in pure bismuth single crystals at ambient pressure

At ambient pressure, bulk rhombohedral bismuth is a semimetal that remains in the normal state down to at least 10 millikelvin. Superconductivity in bulk bismuth is thought to be unlikely because of the extremely low carrier density. We observed bulk superconductivity in pure bismuth single crystals below 0.53 millikelvin at ambient pressure, with an estimated critical magnetic field of 5.2 microteslas at 0 kelvin. Superconductivity in bismuth cannot be explained by the conventional Bardeen-Cooper-Schrieffer theory because its adiabatic approximation does not hold true for bismuth. Future theoretical work will be needed to understand superconductivity in the nonadiabatic limit in systems with low carrier densities and unusual band structures, such as bismuth.

Two-stage dilute-acid and organic-solvent lignocellulosic pretreatment for enhanced bioprocessing

A two stage pretreatment approach for biomass is developed in the current work in which dilute acid (DA) pretreatment is followed by a solvent based pretreatment (N-methyl morpholine N oxide - NMMO). When the combined pretreatment (DAWNT) is applied to sugarcane bagasse and corn stover, the rates of hydrolysis and overall yields (>90%) are seen to dramatically improve and under certain conditions 48h can be taken off the time of hydrolysis with the additional NMMO step to reach similar conversions. DAWNT shows a 2-fold increase in characteristic rates and also fractionates different components of biomass - DA treatment removes the hemicellulose while the remaining cellulose is broken down by enzymatic hydrolysis after NMMO treatment to simple sugars. The remaining residual solid is high purity lignin. Future work will focus on developing a full scale economic analysis of DAWNT for use in biomass fractionation.

Detection of Alzheimer disease in MR images using structure tensor

Alzheimer's disease (AD) is the most common progressive neurodegenerative disorder. Therefore, early detection and evaluation of prognosis of AD is an important issue in contemporary brain research. Magnetic Resonance Imaging (MRI) provides valuable diagnostic information about AD. In this work, brain tissue is extracted using phase-based level set method. Structure tensor analysis is used to visualize and quantify structural features of the brain from MRI. Further, quantitative measures are derived to classify different stages of AD. Normal and AD subjects were classified up to an accuracy of 88% using these features. It is observed that structural changes in brain can be characterized using this technique and therefore can be helpful in tracking the progression of AD and aid in classification between normal and AD subjects.

Cross-generational effects of parental low dose BPA exposure on the Gonadotropin-Releasing Hormone3 system and larval behavior in medaka (Oryzias latipes)

Growing evidence indicates that chronic exposure to Bisphenol A (BPA) may disrupt normal brain function and behavior mediated by gonadotropin-releasing hormone (GnRH) pathways. Previous studies have shown that low dose BPA (200ng/ml) exposure during embryogenesis altered development of extra-hypothalamic GnRH3 systems and non-reproductive locomotor behavior in medaka. Effects of parental low-dose BPA exposure on the development of GnRH3 systems and locomotor behavior of offspring are not well known. This study examines whether the neurophysiological and behavioral effects of BPA in parents (F0 generation) are carried over to their offspring (F1 generation) using stable transgenic medaka embryos/larvae with GnRH3 neurons tagged with green fluorescent protein (GFP). Parental fish were exposed to BPA (200ng/ml) for either life-long or different developmental time windows. Fertilized F1 eggs were collected and raised in egg/fish water with no environmental exposure to BPA. All experiments were performed on F1 embryos/larvae, which were grouped based on the following parental (F0) BPA exposure conditions - (i) Group 1 (G1): through life; (ii) G2: during embryogenesis and early larval development [1-14days post fertilization (dpf)]; (iii) G3: during neurogenesis (1-5dpf); and (iv) G4: during sex differentiation (5-14dpf). Embryos from unexposed vehicle treated parents served as controls (G0). G1 embryos showed significantly reduced survival rates and delayed hatching time compared to other groups, while G4 embryos hatched significantly earlier than all other groups. At 3 dpf, the GnRH3-GFP intensity was increased by 47% in G3 embryos and decreased in G4 embryos by 59% compared to controls. At 4dpf, G1 fish showed 42% increased intensity, while GFP intensity was reduced by 44% in G3 subjects. In addition, the mean brain size of G1, G3 and G4 embryos were smaller than that of control at 4dpf. At 20dpf, all larvae from BPA-treated parents showed significantly decreased total movement (distance covered) compared with controls, with G2 and G3 fish showing reduced velocity of movement. While at 20 dpf no group differences were seen in the soma diameter of GnRH3-GFP neurons, a 34% decrease in SV2 expression, a marker for synaptic transmission, in G1 larvae was observed. These data suggest that parental BPA exposure during critical windows of embryonic development or chronic treatment affects next-generation offspring both in embryonic and larval brain development as well as larval behavior.

A Unified Model of Performance for Predicting the Effects of Sleep and Caffeine

STUDY OBJECTIVES

Existing mathematical models of neurobehavioral performance cannot predict the beneficial effects of caffeine across the spectrum of sleep loss conditions, limiting their practical utility. Here, we closed this research gap by integrating a model of caffeine effects with the recently validated unified model of performance (UMP) into a single, unified modeling framework. We then assessed the accuracy of this new UMP in predicting performance across multiple studies.

METHODS

We hypothesized that the pharmacodynamics of caffeine vary similarly during both wakefulness and sleep, and that caffeine has a multiplicative effect on performance. Accordingly, to represent the effects of caffeine in the UMP, we multiplied a dose-dependent caffeine factor (which accounts for the pharmacokinetics and pharmacodynamics of caffeine) to the performance estimated in the absence of caffeine. We assessed the UMP predictions in 14 distinct laboratory- and field-study conditions, including 7 different sleep-loss schedules (from 5 h of sleep per night to continuous sleep loss for 85 h) and 6 different caffeine doses (from placebo to repeated 200 mg doses to a single dose of 600 mg).

RESULTS

The UMP accurately predicted group-average psychomotor vigilance task performance data across the different sleep loss and caffeine conditions (6% < error < 27%), yielding greater accuracy for mild and moderate sleep loss conditions than for more severe cases. Overall, accounting for the effects of caffeine resulted in improved predictions (after caffeine consumption) by up to 70%.

CONCLUSIONS

The UMP provides the first comprehensive tool for accurate selection of combinations of sleep schedules and caffeine countermeasure strategies to optimize neurobehavioral performance.

Analysis of muscle fatigue conditions using time-frequency images and GLCM features

In this work, an attempt has been made to differentiate muscle non-fatigue and fatigue conditions using sEMG signals and texture representation of the time-frequency images. The sEMG signals are recorded from the biceps brachii muscle of 25 healthy adult volunteers during dynamic fatiguing contraction. The first and last curls of these signals are considered as the non-fatigue and fatigue zones, respectively. These signals are preprocessed and the time-frequency spectrum is computed using short time fourier transform (STFT). Gray-Level Co-occurrence Matrix (GLCM) is extracted from low (15–45 Hz), medium (46–95 Hz) and high (96–150 Hz) frequency bands of the time-frequency images. Further, the features such as contrast, correlation, energy and homogeneity are calculated from the resultant matrices. The results show that the high frequency band based features are able to differentiate non-fatigue and fatigue conditions. The features such as correlation, contrast and homogeneity extracted at angles 0°, 45°, 90°, and 135° are found to be distinct with high statistical significance (p < 0.0001). Hence, this framework can be used for analysis of neuromuscular disorders.

Atrophy analysis of corpus callosum in Alzheimer brain MR images using anisotropic diffusion filtering and level sets

In this work, an attempt has been made to analyze the atrophy of Corpus Callosum (CC) in Alzheimer brain magnetic resonance images using anisotropic diffusion filtering and modified distance regularized level set method. Anisotropic diffusion filtering is used as preprocessing to obtain the edge map. The modified distance regularized level set method is employed to segment CC using this edge map. Geometric features are extracted from the segmented CC and are analyzed. Results show that anisotropic diffusion filtering is able to extract the edge map with high contrast and continuous boundaries. Modified distance regularized level set method could perform the segmentation of CC in both normal and Alzheimer images. The extracted geometric features such as minor axis, Euler number and solidity are able to demarcate the Alzheimer subjects from the control normals. As atrophy of CC is closely associated with the pathology, this study seems to be clinically useful.

Coexistence of superconductivity and a charge density wave in LaPt2(Si1-x Ge x )2 (0 ⩽ x ⩽ 0.5)

Interplay between a charge density wave (CDW) and superconductivity in LaPt2(Si1-x Ge x )2 has been studied by electrical transport and magnetic measurements. LaPt2Si2 crystallizes in CaBe2Ge2 type structure which shows a first order structural phase transition from tetragonal to orthorhombic accompanied by a CDW transition at 112 K and superconducting transition at around 1.22 K as confirmed by temperature dependence of resistivity and magnetic measurements. For 2[Formula: see text] doping of germanium, while the CDW temperature T CDW decreases, the superconducting transition temperature T C shows an increase. T CDW increases for 5[Formula: see text] doping of germanium and the superconducting transition decreases. These findings demonstrate the competing nature of a CDW and superconductivity.

Steganography in arrhythmic electrocardiogram signal

Security and privacy of patient data is a vital requirement during exchange/storage of medical information over communication network. Steganography method hides patient data into a cover signal to prevent unauthenticated accesses during data transfer. This study evaluates the performance of ECG steganography to ensure secured transmission of patient data where an abnormal ECG signal is used as cover signal. The novelty of this work is to hide patient data into two dimensional matrix of an abnormal ECG signal using Discrete Wavelet Transform and Singular Value Decomposition based steganography method. A 2D ECG is constructed according to Tompkins QRS detection algorithm. The missed R peaks are computed using RR interval during 2D conversion. The abnormal ECG signals are obtained from the MIT-BIH arrhythmia database. Metrics such as Peak Signal to Noise Ratio, Percentage Residual Difference, Kullback-Leibler distance and Bit Error Rate are used to evaluate the performance of the proposed approach.