Assessment of toxicity using dehydrogenases activity and mathematical modeling

Dehydrogenase activity is frequently used to assess the general condition of microorganisms in soil and activated sludge. Many studies have investigated the inhibition of dehydrogenase activity by various compounds, including heavy metal ions. However, the time after which the measurements are carried out is often chosen arbitrarily. Thus, it can be difficult to estimate how the toxic effects of compounds vary during the reaction and when the maximum of the effect would be reached. Hence, the aim of this study was to create simple and useful mathematical model describing changes in dehydrogenase activity during exposure to substances that inactivate enzymes. Our model is based on the Lagergrens pseudo-first-order equation, the rate of chemical reactions, enzyme activity, and inactivation and was created to describe short-term changes in dehydrogenase activity. The main assumption of our model is that toxic substances cause irreversible inactivation of enzyme units. The model is able to predict the maximum direct toxic effect (MDTE) and the time to reach this maximum (T_MDTE). In order to validate our model, we present two examples: inactivation of dehydrogenase in microorganisms in soil and activated sludge. The model was applied successfully for cadmium and copper ions. Our results indicate that the predicted MDTE and T_MDTE are more appropriate than EC₅₀ and IC₅₀ for toxicity assessments, except for long exposure times.     

Representation,Exemplification, and Risk: Resonance of Tobacco Graphic Health Warnings Across Diverse Populations

As countries implement Article 11 of the World Health Organization (WHO) Framework Convention on Tobacco Control, graphic warning labels that use images of people and their body parts to illustrate the consequences of smoking are being added to cigarette packs. According to exemplification theory, these case examples—exemplars—can shape perceptions about risk and may resonate differently among demographic subpopulations. Drawing on data from eight focus groups (N = 63) with smokers and nonsmokers from vulnerable populations, this qualitative study explores whether people considered exemplars in their reactions to and evaluations of U.S. graphic health warning labels initially proposed by the Food and Drug Administration. Participants made reference to prior and concurrent mass media messages and exemplars during the focus groups and used demographic cues in making sense of the images on the warning labels. Participants were particularly sensitive to age of the exemplars and how it might affect label effectiveness and beliefs about smoking. Race and socioeconomic status also were salient for some participants. We recommend that exemplars and exemplification be considered when selecting and evaluating graphic health warnings for tobacco labels and associated media campaigns.     

Extended Kalman smoother with differential evolution technique for denoising of ECG signal

Electrocardiogram (ECG) signal gives a lot of information on the physiology of heart. In reality, noise from various sources interfere with the ECG signal. To get the correct information on physiology of the heart, noise cancellation of the ECG signal is required. In this paper, the effectiveness of extended Kalman smoother (EKS) with the differential evolution (DE) technique for noise cancellation of the ECG signal is investigated. DE is used as an automatic parameter selection method for the selection of ten optimized components of the ECG signal, and those are used to create the ECG signal according to the real ECG signal. These parameters are used by the EKS for the development of the state equation and also for initialization of the parameters of EKS. EKS framework is used for denoising the ECG signal from the single channel. The effectiveness of proposed noise cancellation technique has been evaluated by adding white, colored Gaussian noise and real muscle artifact noise at different SNR to some visually clean ECG signals from the MIT-BIH arrhythmia database. The proposed noise cancellation technique of ECG signal shows better signal to noise ratio (SNR) improvement, lesser mean square error (MSE) and percent of distortion (PRD) compared to other well-known methods.