Chronic Health Conditions as a Risk Factor for Falls among the Community-Dwelling US Older Adults: A Zero-Inflated Regression Modeling Approach

Falls are an important health concern among older adults due to age-related changes in the body. Having a medical history of chronic health condition may pose even higher risk of falling. Only few studies have assessed a number of chronic health conditions as risk factor for falls over a large nationally representative sample of US older adults. In this study, Behavioral Risk Factor Surveillance System (BRFSS) 2014 participants aged 65 years and older (n = 159,336) were evaluated. It was found that 29.7% (n = 44,550) of the sample experienced at least one fall and 16.3% (n = 20,444) experienced more than one fall in the past 12 months. According to the study findings, having a medical history of stroke, CKD, arthritis, depression, and diabetes independently predict the risk of first-time falling as well as the risk of recurrent falling in older adult population while controlling for other factors. On the other hand, having a medical history of the heart attack, angina, asthma, and COPD did not predict the risk of first-time falling, but did predict the risk of recurrent falling after experiencing the first fall in this population

Non-Equilibrium Surface Tension of the Vapour-Liquid Interface of Active Lennard-Jones Particles

We study a three-dimensional system of self-propelled Brownian particles interacting via the Lennard-Jones potential. Using Brownian Dynamics simulations in an elongated simulation box, we investigate the steady states of vapour-liquid phase coexistence of active Lennard-Jones particles with planar interfaces. We measure the normal and tangential components of the pressure tensor along the direction perpendicular to the interface and verify mechanical equilibrium of the two coexisting phases. In addition, we determine the non-equilibrium interfacial tension by integrating the difference of the normal and tangential component of the pressure tensor, and show that the surface tension as a function of strength of particle attractions is well-fitted by simple power laws. Finally, we measure the interfacial stiffness using capillary wave theory and the equipartition theorem, and find a simple linear relation between surface tension and interfacial stiffness with a proportionality constant characterized by an effective temperature.Comment: 12 pages, 5 figures (Corrected typos and References

Pressure dependent electronic properties of MgO polymorphs: A first-principles study of Compton profiles and autocorrelation functions

The first-principles periodic linear combination of atomic orbitals method within the framework of density functional theory implemented in the CRYSTAL06 code has been applied to explore effect of pressure on the Compton profiles and autocorrelation functions of MgO. Calculations are performed for the B1, B2, B3, B4, B8_1 and h-MgO polymorphs of MgO to compute lattice constants and bulk moduli. The isothermal enthalpy calculations predict that B4 to B8_1, h-MgO to B8_1, B3 to B2, B4 to B2 and h-MgO to B2 transitions take place at 2, 9, 37, 42 and 64 GPa respectively. The high pressure transitions B8_1 to B2 and B1 to B2 are found to occur at 340 and 410 GPa respectively. The pressure dependent changes are observed largely in the valence electrons Compton profiles whereas core profiles are almost independent of the pressure in all MgO polymorphs. Increase in pressure results in broadening of the valence Compton profiles. The principal maxima in the second derivative of Compton profiles shifts towards high momentum side in all structures. Reorganization of momentum density in the B1 to B2 structural phase transition is seen in the first and second derivatives before and after the transition pressure. Features of the autocorrelation functions shift towards lower r side with increment in pressure.Comment: 19 pages, 8 figures, accepted for publication in Journal of Materials Scienc

Controlled release from zein matrices: Interplay of drug hydrophobicity and pH

Purpose: In earlier studies, the corn protein zein is found to be suitable as a sustained release agent, yet the range of drugs for which zein has been studied remains small. Here, zein is used as a sole excipient for drugs differing in hydrophobicity and isoelectric point: indomethacin, paracetamol and ranitidine. Methods: Caplets were prepared by hot-melt extrusion (HME) and injection moulding (IM). Each of the three model drugs were tested on two drug loadings in various dissolution media. The physical state of the drug, microstructure and hydration behaviour were investigated to build up understanding for the release behaviour from zein based matrix for drug delivery. Results: Drug crystallinity of the caplets increases with drug hydrophobicity. For ranitidine and indomethacin, swelling rates, swelling capacity and release rates were pH dependent as a consequence of the presence of charged groups on the drug molecules. Both hydration rates and release rates could be approached by existing models. Conclusion: Both the drug state as pH dependant electrostatic interactions are hypothesised to influence release kinetics. Both factors can potentially be used factors influencing release kinetics release, thereby broadening the horizon for zein as a tuneable release agent

A Characterization of Scale Invariant Responses in Enzymatic Networks

An ubiquitous property of biological sensory systems is adaptation: a step increase in stimulus triggers an initial change in a biochemical or physiological response, followed by a more gradual relaxation toward a basal, pre-stimulus level. Adaptation helps maintain essential variables within acceptable bounds and allows organisms to readjust themselves to an optimum and non-saturating sensitivity range when faced with a prolonged change in their environment. Recently, it was shown theoretically and experimentally that many adapting systems, both at the organism and single-cell level, enjoy a remarkable additional feature: scale invariance, meaning that the initial, transient behavior remains (approximately) the same even when the background signal level is scaled. In this work, we set out to investigate under what conditions a broadly used model of biochemical enzymatic networks will exhibit scale-invariant behavior. An exhaustive computational study led us to discover a new property of surprising simplicity and generality, uniform linearizations with fast output (ULFO), whose validity we show is both necessary and sufficient for scale invariance of enzymatic networks. Based on this study, we go on to develop a mathematical explanation of how ULFO results in scale invariance. Our work provides a surprisingly consistent, simple, and general framework for understanding this phenomenon, and results in concrete experimental predictions

Modulation of enhancer looping and differential gene targeting by Epstein-Barr virus transcription factors directs cellular reprogramming

Epstein-Barr virus (EBV) epigenetically reprogrammes B-lymphocytes to drive immortalization and facilitate viral persistence. Host-cell transcription is perturbed principally through the actions of EBV EBNA 2, 3A, 3B and 3C, with cellular genes deregulated by specific combinations of these EBNAs through unknown mechanisms. Comparing human genome binding by these viral transcription factors, we discovered that 25% of binding sites were shared by EBNA 2 and the EBNA 3s and were located predominantly in enhancers. Moreover, 80% of potential EBNA 3A, 3B or 3C target genes were also targeted by EBNA 2, implicating extensive interplay between EBNA 2 and 3 proteins in cellular reprogramming. Investigating shared enhancer sites neighbouring two new targets (WEE1 and CTBP2) we discovered that EBNA 3 proteins repress transcription by modulating enhancer-promoter loop formation to establish repressive chromatin hubs or prevent assembly of active hubs. Re-ChIP analysis revealed that EBNA 2 and 3 proteins do not bind simultaneously at shared sites but compete for binding thereby modulating enhancer-promoter interactions. At an EBNA 3-only intergenic enhancer site between ADAM28 and ADAMDEC1 EBNA 3C was also able to independently direct epigenetic repression of both genes through enhancer-promoter looping. Significantly, studying shared or unique EBNA 3 binding sites at WEE1, CTBP2, ITGAL (LFA-1 alpha chain), BCL2L11 (Bim) and the ADAMs, we also discovered that different sets of EBNA 3 proteins bind regulatory elements in a gene and cell-type specific manner. Binding profiles correlated with the effects of individual EBNA 3 proteins on the expression of these genes, providing a molecular basis for the targeting of different sets of cellular genes by the EBNA 3s. Our results therefore highlight the influence of the genomic and cellular context in determining the specificity of gene deregulation by EBV and provide a paradigm for host-cell reprogramming through modulation of enhancer-promoter interactions by viral transcription factors

Allostatic self-efficacy: a metacognitive theory of dyshomeostasis-induced fatigue and depression

This paper outlines a hierarchical Bayesian framework for interoception, homeostatic/allostatic control, and meta-cognition that connects fatigue and depression to the experience of chronic dyshomeostasis. Specifically, viewing interoception as the inversion of a generative model of viscerosensory inputs allows for a formal definition of dyshomeostasis (as chronically enhanced surprise about bodily signals, or, equivalently, low evidence for the brain's model of bodily states) and allostasis (as a change in prior beliefs or predictions which define setpoints for homeostatic reflex arcs). Critically, we propose that the performance of interoceptive-allostatic circuitry is monitored by a metacognitive layer that updates beliefs about the brain's capacity to successfully regulate bodily states (allostatic self-efficacy). In this framework, fatigue and depression can be understood as sequential responses to the interoceptive experience of dyshomeostasis and the ensuing metacognitive diagnosis of low allostatic self-efficacy. While fatigue might represent an early response with adaptive value (cf. sickness behavior), the experience of chronic dyshomeostasis may trigger a generalized belief of low self-efficacy and lack of control (cf. learned helplessness), resulting in depression. This perspective implies alternative pathophysiological mechanisms that are reflected by differential abnormalities in the effective connectivity of circuits for interoception and allostasis. We discuss suitably extended models of effective connectivity that could distinguish these connectivity patterns in individual patients and may help inform differential diagnosis of fatigue and depression in the future

Concept of Shatkriyakala as mentioned in Sushruta Samhita

Ayurveda, our cultural heritage, is the ancient system of medicine, serving living beings since time immemorial. It is a unique system, in the sense of its fundamental doctrines and concepts. Kriyakala is one of the various important concepts described in Ayurveda treatises. Kriyakala means opportunity or time to administer treatment. These are six in number and are hence known as Shatkriyakala viz. sanchaya, prakopa, prasara, sthansamshraya, vyakti and bheda. It is a concept which describes different phases of a disease in its own unique way. It shows the step wise progress of dosha and disease. Kriyakala is helpful in the diagnosis, prognosis and the treatment of a disease. This very concept is useful even in prevention of diseases

Chromatographic Separation of Heavy Metal Cations on a Silica Gel-G with Amino Acid

Thin layer chromatographic method has been developed for the separation of metal ions such as Cr(VI), Cr(III), As(III), Cd(II), Tl(III) and Hg(II) from their two, three and four component mixtures. The separations were performed on thin layer of silica gel ‘G’ using aqueous l-Alanine as mobile phase. The effect of concentration and pH of mobile phase on the Rf values of individual metal ions were studied and the optimum conditions for separation of metal ions from their mixture were determined

IDENTIFICATION OF FLOODED AREAS DUE TO SEVERE STORM USING ENVISAT ASAR DATA AND NEURAL NETWORKS

The specific objective of the present study is to identify flooded areas due to cyclonic storm using Envisat ASAR VV polarized data and Artificial Neural Network (ANN). On October 30, 2006, the Ogni storm crossed the Indian coast. It impacted three coastal districts in Andhra Pradesh, including Guntur, Prakasam, and Krishna. The present study considers only nine mandals of Guntur district of Andhra Pradesh for identification of flooded areas. For this purpose, pre and post event images of study area were procured of Envisat satellite (April 23, 2006 and November 4, 2006). Field visit to the affected district after the disaster was carried out to gather landcover information. In all, 564 pixels landcover information was collected during the visit (These were corresponding to pre event Envisat image of April 23, 2006). Out of the 564 pixels, randomly 406 pixels (91 were water and the remaining 315 were non-water pixels) were used for training the Neural Network and the remaining for testing. Using the trained ANN model, the total water area in the nine mandals of Guntur using Envisat ASAR satellite imagery of April 23, 2006 was found to be 2.344 thousand hectares. The trained model was applied to the post event Envisat ASAR image of November 4, 2006 to obtain completely submerged and partial/non submerged areas under water. The completely submerged landcover under water in nine mandals of Guntur district on November 4, 2006 was found to be 13.2705 thousand hectares. Results suggest a high accuracy of classification and indicate that this may be a rapid tool for damage estimation and post disaster relief and recovery efforts