Visceral Obesity and Its Shared Role in Cancer and Cardiovascular Disease: A Scoping Review of the Pathophysiology and Pharmacological Treatments

The association between obesity, cancer and cardiovascular disease (CVD) has been demonstrated in animal and epidemiological studies. However, the specific role of visceral obesity on cancer and CVD remains unclear. Visceral adipose tissue (VAT) is a complex and metabolically active tissue, that can produce different adipokines and hormones, responsible for endocrine-metabolic comorbidities. This review explores the potential mechanisms related to VAT that may also be involved in cancer and CVD. In addition, we discuss the shared pharmacological treatments which may reduce the risk of both diseases. This review highlights that chronic inflammation, molecular aspects, metabolic syndrome, secretion of hormones and adiponectin associated to VAT may have synergistic effects and should be further studied in relation to cancer and CVD. Reductions in abdominal and visceral adiposity improve insulin sensitivity, lipid profile and cytokines, which consequently reduce the risk of CVD and some cancers. Several medications have shown to reduce visceral and/or subcutaneous fat. Further research is needed to investigate the pathophysiological mechanisms by which visceral obesity may cause both cancer and CVD. The role of visceral fat in cancer and CVD is an important area to advance. Public health policies to increase public awareness about VAT’s role and ways to manage or prevent it are needed.     

Bayesian channel equalisation and robust features for speechrecognition

The use of a speech recognition system with telephone channel environments, or different microphones, requires channel equalisation. In speech recognition, the speech model provides a bank of statistical information that can be used in the channel identification and equalisation process. The authors consider HMM-based channel equalisation, and present results demonstrating that substantial improvement can be obtained through the equalisation process. An alternative method, for speech recognition, is to use a feature set which is more robust to channel distortion. Channel distortions result in an amplitude tilt of the speech cepstrum, and therefore differential cepstral features provide a measure of immunity to channel distortions. In particular the cepstral-time feature matrix, in addition to providing a framework for representing speech dynamics, can be made robust to channel distortions. The authors present results demonstrating that a major advantage of cepstral-time matrices is their channel insensitive character     

Production of active lipase by Rhizopus oryzae from sugarcane bagasse: solid state fermentation in a tray bioreactor

This study deals with production of lipase in solid state fermentation by Rhizopus oryzae from sugarcane bagasse. A tray bioreactor was designed for the extracellular enzyme production. Daily, lipase production was evaluated at several incubation temperatures. Furthermore, the influence of temperature and humidity of the cabinet, depth of solid bed, particle size, initial moisture content and supplementary substrate (olive oil) as carbon source was investigated. The obtained results showed that bioreactor temperature of 45 °C, humidity of 80%, solid bed depth of 0.5 cm, particle size in the range of 0.335–1 mm, substrate initial moisture content of 80% for the top tray and 70% for the middle tray and supplementary substrate of 8% (v/w) olive oil led to maximum lipase production. Under optimum fermentation conditions after 72‐h incubation, maximum lipase activities for the top, middle and bottom trays were 215.16, 199.36 and 52.64 U gds^?1, respectively.     

Modelling and study of PM machines with inter-turn fault dynamic model-FEM model

In this paper, a simple dynamic model for a PMSM with inter-turn winding fault is derived. Finite element method is used for parameter determination of machine with fault. This dynamic fault model is used to study the PM machine behaviour under various inter-turn fault conditions. A 2D time stepping finite element method (FEM) model is carried out to validate the dynamic fault model. The dynamic model results exhibit the same trend as predicted by FEM analysis for different fault insulation resistances. An experimental test is also conducted to verify the fault model. This model is used to study the machine behaviour under various fault conditions and severity. The proposed model seems to be well adapted for PM motors health monitoring and inter-turn fault diagnosis.     

Parametric Formant Modelling and Transformation in Voice Conversion

This paper presents a method for the estimation and mapping of parametric models of speech resonance at formants for voice conversion. The spectral features at formants that contribute to voice characteristics are the trajectories of the frequencies, the bandwidths and intensities of the resonance at formants. The formant features are extracted from the poles of a linear prediction (LP) model of speech. The statistical distributions of formants are modelled by a two-dimensional hidden Markov model (HMM) spanning the time and frequency dimensions. Experimental results are presented which show a close match between HMM-based formant models and the histograms of formants. For voice conversion two alternative methods are explored for mapping the formants of a source speaker to those of a target speaker. The first method is based on an adaptive formant-tracking warping of the frequency response of the LP model and the second method is based on the rotation of the poles of the LP model of speech. Both methods transform all spectral parameters of the resonance at formants of the source speaker towards those of the target speaker. In addition, the issues affecting the selection of the warping ratios for the mapping functions are investigated. Experimental results of formant estimation and perceptual evaluation of voice morphing based on parametric formant models are presented.     

"The lasting effect of words on feelings: Words may facilitate exposure effects to threatening images": Correction to Tabibnia, Lieberman, and Craske (2008).

Reports an error in "The lasting effect of words on feelings: Words may facilitate exposure effects to threatening images" by Golnaz Tabibnia, Matthew D. Lieberman and Michelle G. Craske (Emotion, 2008[Jun], Vol 8[3], 307-317). The URL provided for the supplemental materials was incorrect. The correct URL is provided in the erratum. (The following abstract of the original article appeared in record 2008-06717-001.) Previous studies have shown that mere words, particularly affective words, can dampen emotional responses. However, the effect of affective labels on emotional responding in the long term is unknown. The authors examined whether repeated exposure to aversive images would lead to more reduction in autonomic reactivity a week later if the images were exposed with single-word labels than without labels. In Experiment 1, healthy individuals were exposed to pictures of disturbing scenes with or without labels on Day 1. On Day 8, the same pictures from the previous week were exposed, this time without labels. In Experiment 2, participants were spider fearful and were exposed to pictures of spiders. In both experiments, although repeated exposure to aversive images (without labels) led to long-term attenuation of autonomic reactivity, exposure plus affective labels, but not nonaffective labels, led to more attenuation than exposure alone. Thus, affective labels may help dampen emotional reactivity in both the short and long terms. Implications for exposure therapy and translational studies are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Characterization of thermochemical properties of Al nanoparticle and NiO nanowire composites

Thermochemical properties and microstructures of the composite of Al nanoparticles and NiO nanowires were characterized. The nanowires were synthesized using a hydrothermal method and were mixed with these nanoparticles by sonication. Electron microscopic images of these composites showed dispersed NiO nanowires decorated with Al nanoparticles. Thermal analysis suggests the influence of NiO mass ratio was insignificant with regard to the onset temperature of the observed thermite reaction, although energy release values changed dramatically with varying NiO ratios. Reaction products from the fuel-rich composites were found to include elemental Al and Ni, Al₂O₃, and AlNi. The production of the AlNi phase, confirmed by an ab initio molecular dynamics simulation, was associated with the formation of some metallic liquid spheres from the thermite reaction.     

Effects of hysteretic damping on the seismic performance of tuned mass dampers

A tuned mass damper (TMD) as a convenient passive device in average to tall buildings has limitations specifically against broad band seismic excitations. According to evidences from the literature, this drawback can be dominated by using nonlinear stiffness in TMDs; however, past studies did not explore this issue, and observations are not sufficient to reach a conclusion about seismic performance of nonlinear TMDs. This paper considers seismic performance of a nonlinear TMD developed by adding a martensitic shape memory alloy spring with significant stable features to conventional TMDs. To this end, single degree of freedom structures (from short to large periods) equipped with the nonlinear TMD are investigated subjected to set of ground motions, and through numerical analyses, effects of hysteretic damping and energy absorption capacity of the nonlinear TMD are examined. In addition, features of the proposed TMD configuration and effects of the excitation properties have been scrutinized through graphing frequency response curves by the arc length continuation method. Results indicate that the proposed configuration can make the nonlinear TMD robust against variations of the loading properties. Moreover, due to significant hysteretic damping of the shape memory alloy, spring seismic performance of the nonlinear TMD is better than conventional TMDs.     

A Facile Magnetic Extrusion Method for Preparing Endosome-Derived Vesicles for Cancer Drug Delivery

To date, the scaled-up manufacturing and efficient drug loading of exosomes are two existing challenges limiting the clinical translation of exosome-based drug delivery. Herein, a facile magnetic extrusion method is developed for preparing endosome-derived vesicles, also known as exosome mimetics (EMs), which share the same biological origin and similar morphology, composition, and biofunctions with native exosomes. The high yield and consistency of this magnetic extrusion method help to overcome the manufacturing bottleneck in exosome research. Moreover, the proposed standardized multi-step method readily facilitates the ammonium sulfate gradient approach to actively load chemodrugs such as doxorubicin into EMs. The engineered EMs developed and tested here exhibit comparable drug delivery properties as do native exosomes, and potently inhibit tumor growth by delivering doxorubicin in an orthotopic breast tumor model. These findings demonstrate that EMs can be prepared in a facile and scaled-up manner as a promising biological nanomedicine for cancer drug delivery.