Inhibition of β-lactamase function by de novo designed peptide.

Antimicrobial resistance is a great public health concern that is now described as a "silent pandemic". The global burden of antimicrobial resistance requires new antibacterial treatments, especially for the most challenging multidrug-resistant bacteria. There are various mechanisms by which bacteria develop antimicrobial resistance including expression of β-lactamase enzymes, overexpression of efflux pumps, reduced cell permeability through downregulation of porins required for β-lactam entry, or modifications in penicillin-binding proteins.

Influence of Tuning Element Relief Patches on Pain as Analyzed by the Resonant Recognition Model.

Tuning element relief patches (TERPs) are silicon-based titanium salt infused adhesive patches that have been developed by Tuning Element. A number of anecdotal reports have shown that TERPs diffuse pain, including chronic, inflammatory, and neuropathic. Pain is a very complex biochemical and electrical process involving sensory part, nerve transmission, and brain perception of pain.

Environmental Light and Its Relationship with Electromagnetic Resonances of Biomolecular Interactions, as Predicted by the Resonant Recognition Model.

The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health.

Analysis of Tumor Necrosis Factor Function Using the Resonant Recognition Model.

The tumor necrosis factor (TNF) is a complex protein that plays a very important role in a number of biological functions including apoptotic cell death, tumor regression, cachexia, inflammation inhibition of tumorigenesis and viral replication. Its most interesting function is that it is an inhibitor of tumorigenesis and inductor of apoptosis. Thus, the TNF could be a good candidate for cancer therapy.

Prediction of Tubulin Resonant Frequencies Using the Resonant Recognition Model (RRM).

Tubulin proteins were analyzed using the Resonant Recognition Model to predict possible electromagnetic resonances in tubulin and microtubules. We propose that these electromagnetic resonances are caused by charge transfer through the protein molecule. The frequencies of these electromagnetic resonances depend on charge velocity.

Investigation of cytotoxicity of negative control peptides versus bioactive peptides on skin cancer and normal cells: a comparative study.

Background: Resonant recognition model-myxoma virus (RRM-MV), a bioactive peptide analogue for myxoma virus MV-T5 protein, was computationally designed by the RRM. In this study, the anticancer effects of RRM-MV were assessed in vitro against four negative control peptides on human skin cancer and normal cells.

Results & Discussion: The effects of RRM-MV versus negative control peptides on cells were evaluated by quantitative and qualitative assays.

A bioactive peptide analogue for myxoma virus protein with a targeted cytotoxicity for human skin cancer in vitro.

Background: Cancer is an international health problem, and the search for effective treatments is still in progress. Peptide therapy is focused on the development of short peptides with strong tumoricidal activity and low toxicity. In this study, we investigated the efficacy of a myxoma virus peptide analogue (RRM-MV) as a candidate for skin cancer therapy.

Biological effects of a de novo designed myxoma virus peptide analogue: evaluation of cytotoxicity on tumor cells.

Background: The Resonant Recognition Model (RRM) is a physico-mathematical model that interprets protein sequence linear information using digital signal processing methods. In this study the RRM concept was employed for structure-function analysis of myxoma virus (MV) proteins and the design of a short bioactive therapeutic peptide with MV-like antitumor/cytotoxic activity.

Methodology/principal Findings: The analogue RRM-MV was designed by RRM as a linear 18 aa 2.

Developing a wireless implantable body sensor network in MICS band.

Through an integration of wireless communication and sensing technologies, the concept of a body sensor network (BSN) was initially proposed in the early decade with the aim to provide an essential technology for wearable, ambulatory, and pervasive health monitoring for elderly people and chronic patients. It has become a hot research area due to big opportunities as well as great challenges it presents. Though the idea of an implantable BSN was proposed in parallel with the on-body sensor network, the development in this area is relatively slow due to the complexity of human body, safety concerns, and some technological bottlenecks such as the design of ultralow-power implantable RF transceiver.

Low intensity microwave radiation as modulator of the L-lactate dehydrogenase activity.

In this study, we investigated experimentally the possibility of modulating protein activity by low intensity microwaves by measuring alternations of L: -Lactate Dehydrogenase enzyme (LDH) activity. The LDH enzyme solutions were irradiated by microwaves of the selected frequencies and powers using the Transverse Electro-Magnetic (TEM) cell. The kinetics of the irradiated LDH was measured by continuous monitoring of nicotine adenine dinucleotide, reduced (NADH) absorbance at 340 nm.

A fast critical arrhythmic ECG waveform identification method using cross-correlation and multiple template matching.

Critical Arrhythmic ECG such as Ventricular Tachycardia (VT) and Ventricular Fibrillation (VF) are both distinguishable by its waveform characteristics. A VF waveform is often described as disorganized and has an irregular rhythm while a VT waveform exhibits abnormal signatures and presents a regular rhythm pattern. This paper presents a fast cross-correlation algorithm using multiple waveform templates for automatic detection of life threatening arrhythmias such as VT and VF from the Normal Sinus Rhythm (NSR) waveforms.

Review of studies on modulating enzyme activity by low intensity electromagnetic radiation.

This paper is a compilation of our findings on non-thermal effects of electromagnetic radiation (EMR) at the molecular level. The outcomes of our studies revealed that that enzymes' activity can be modulated by external electromagnetic fields (EMFs) of selected frequencies. Here, we discuss the possibility of modulating protein activity using visible and infrared light based on the concepts of protein activation outlined in the resonant recognition model (RRM), and by low intensity microwaves.

Cross-correlation of EEG frequency bands and heart rate variability for sleep apnoea classification.

Sleep apnoea is a sleep breathing disorder which causes changes in cardiac and neuronal activity and discontinuities in sleep pattern when observed via electrocardiogram (ECG) and electroencephalogram (EEG). Using both statistical analysis and Gaussian discriminative modelling approaches, this paper presents a pilot study of assessing the cross-correlation between EEG frequency bands and heart rate variability (HRV) in normal and sleep apnoea clinical patients. For the study we used EEG (delta, theta, alpha, sigma and beta) and HRV (LF(nu), HF(nu) and LF/HF) features from the spectral analysis.

Alterations in sleep EEG activity during the hypopnoea episodes.

The Obstructive Sleep Apnoea Hypopnoea Syndrome (OSAH) means "cessation of breath" during the sleep hours and the sufferers often experience related changes in the electrical activity of the brain and heart. The aim of this paper is to investigate any possible changes in the human electroencephalographic (EEG) activity due to hypopnoea (mild case of cessation of breath) occurrences by applying the non-linear and linear time series methods. The results from this study indicated significant changes in the human EEG activity due to hypopnoea episodes by applying the non-linear, Lyapunov exponent method at C3 EEG electrode site.

Correlation of sleep EEG frequency bands and Heart Rate Variability.

Sleep apnoea is a sleep breathing disorder which causes changes in cardiac and neuronal activity and discontinuities in sleep pattern when observed via electrocardiogram (ECG) and electroencephalogram (EEG). This paper presents a pilot study result of assessing the correlation between EEG frequency bands and ECG Heart Rate Variability (HRV) in normal and sleep apnoea human clinical patients at different sleep stages. In sleep apnoea patients, the results have shown that EEG delta, sigma and beta bands exhibited a strong correlation with cardiac HRV parameters at different sleep stages.

A new approach to revealing functional residues from analysis of protein primary structure.

A protein's biological function is encrypted within its primary structure. Nevertheless, revealing protein function from analysis of its primary structure is still unsolved problem. In this article we present a new methodology for determining functionally significant amino acid residues in proteins sequences, which is based on time-frequency signal analysis and Smoothed Pseudo Wigner Ville distribution (SPWV).

Alterations of human electroencephalographic activity caused by multiple extremely low frequency magnetic field exposures.

In the past, many studies have claimed that extremely low frequency (ELF) magnetic field (MF) exposures could alter the human electroencephalographic (EEG) activity. This study aims at extending our ELF pilot study to investigate whether MF exposures at ELF in series from 50, 16.66, 13, 10, 8.

EEG inter/intra-hemispheric coherence and asymmetric responses to visual stimulations.

This study has attempted to increase the meaning and significance of findings in the experimental areas of electroencephalographic (EEG) visual or photic driving. The aim of this study was to investigate whether the visual stimulation at particular extremely low frequency order could possibly induce changes in the corresponding EEG frequency bands by examining the functional connectedness between brain regions. This was evaluated by applying the improved experimental protocol and objective using non-parametric spectral estimation coherence algorithm.

The effect of GSM-like ELF radiation on the alpha band of the human resting EEG.

Mobile phone handsets such as those operating in the GSM network emit extremely low frequency electromagnetic fields ranging from DC to at least 40 kHz. As a subpart of an extended protocol, the influence of these fields on the human resting EEG has been investigated in a fully counter balanced, double blind, cross-over design study that recruited 72 healthy volunteers. A decrease in the alpha frequency band was observed during the 20 minutes of ELF exposure in the exposed hemisphere only.

Sleep onset estimator: evaluation of parameters.

The electroencephalographic (EEG) alterations during the human sleep onset (falling asleep period) has been evaluated by several studies in the past. However, the analysis part has been limited due to standard signal processing methods. This paper has attempted to evaluate a number of advanced parameters for improved sleep onset estimation, such as EEG non-parametric coherence, power frequency and spectral band power.

Alterations in sleep EEG activity during the hypopnoea episodes.

The Obstructive Sleep Apnoea Hypopnoea Syndrome (OSAH) means 'cessation of breath' during the sleep hours and the sufferers often experience related changes in the electrical activity of the brain and heart. The aim of this paper is to investigate any possible changes in the human electroencephalographic (EEG) activity due to hypopnoea (mild case of cessation of breath) occurrences by applying the non-linear and linear time series methods. The results from this one-subject study indicated significant changes in the human EEG activity due to hypopnoea episodes by applying the non-linear, Lyapunov exponent method at C3 EEG electrode site.

AR spectral analysis technique for human PPG, ECG and EEG signals.

In this study, Fast Fourier transform (FFT) and autoregressive (AR) methods were selected for processing the photoplethysmogram (PPG), electrocardiogram (ECG), electroencephalogram (EEG) signals recorded in order to examine the effects of pulsed electromagnetic field (PEMF) at extremely low frequency (ELF) upon the human electrophysiological signal behavior. The parameters in the autoregressive (AR) method were found by using the least squares method. The power spectra of the PPG, ECG, and EEG signals were obtained by using these spectral analysis techniques.

Adaptive transmit diversity with orthogonal space-time block coding for telemedicine application.

Recently an adaptive transmit eigenbeamforming with orthogonal space-time block coding (Eigen-OSTBC) has been proposed. This model was simulated over macrocell environment with a uniform linear array (ULA) at the base station (BS) for next-generation (NG) wireless/mobile network. In this paper, we introduce a telemedicine simulation framework employing the Eigen-OSTBC scheme for the investigation of communication system characteristics in the application of biological data such as electrocardiogram (ECG).

A time-frequency approach for the analysis of normal and arrhythmia cardiac signals.

Previously, electrocardiogram (ECG) signals have been analyzed in either a time-indexed or spectral form. The reality, is that the ECG and all other biological signals belong to the family of multicomponent nonstationary signals. Due to this reason, the use of time-frequency analysis can be unavoidable for these signals.

Eigenvector methods for analysis of human PPG, ECG and EEG signals.

This paper presents eigenvector methods for analysis of the photoplethysmogram (PPG), electrocardiogram (ECG), electroencephalogram (EEG) signals recorded in order to examine the effects of pulsed electromagnetic field (PEMF) at extremely low frequency (ELF) upon the human electrophysiological signal behavior. The features representing the PPG, ECG, EEG signals were obtained by using the eigenvector methods. In addition to this, the problem of selecting relevant features among the features available for the purpose of discrimination of the signals was dealt with.