Inhibition of ß-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 ß-lactamase enzymes, overexpression of efflux pumps, reduced cell permeability through downregulation of porins required for ß-lactam entry, or modifications in penicillin-binding proteins. Inactivation of the ß-lactam antibiotics by ß-lactamase enzymes is the most common mechanism of bacterial resistance to these agents. Although several effective small-molecule inhibitors of ß-lactamases such as clavulanic acid and avibactam are clinically available, they act only on selected class A, C, and some class D enzymes. Currently, none of the clinically approved inhibitors can effectively inhibit Class B metallo-ß-lactamases. Additionally, there is increased resistance to these inhibitors reported in several bacteria. The objective of this study is to use the Resonant Recognition Model (RRM), as a novel strategy to inhibit/modulate specific antimicrobial resistance targets. The RRM is a bio-physical approach that analyzes the distribution of energies of free electrons and posits that there is a significant correlation between the spectra of this energy distribution and related protein biological activity. In this study, we have used the RRM concept to evaluate the structure-function properties of a group of 22 ß-lactamase proteins and designed 30-mer peptides with the desired RRM spectral periodicities (frequencies) to function as ß-lactamase inhibitors. In contrast to the controls, our results indicate 100% inhibition of the class A ß-lactamases from Escherichia coli and Enterobacter cloacae. Taken together, the RRM model can likely be utilized as a promising approach to design ß-lactamase inhibitors for any specific class. This may open a new direction to combat antimicrobial resistance.

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. We concentrated our research on nerve transmission, which is electrical signal along the nerve (axon). This electrical signal is created by a complex activity of opening and closing of pain related ion channels and redistribution of electrically charged ions on the nerve cell membrane. Ion channels are made of different proteins, which are involved with the complex processes of opening and closing ion channels. Here, we apply the resonant recognition model to analyze ion channel proteins related to the pain transmission in order to find out, how imprints and particles within TERPs can interfere with pain related activity of ion channels.

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. However, the TNF has also inflammatory and toxic effects. Therefore, it would be very important to understand complex functions of the TNF and consequently be able to predict mutations or even design the new TNF-related proteins that will have only a tumor inhibition function, but not other side effects. This can be achieved by applying the resonant recognition model (RRM), a unique computational model of analysing macromolecular sequences of proteins, DNA and RNA. The RRM is based on finding that certain periodicities in distribution of free electron energies along protein, DNA and RNA are strongly correlated to the biological function of these macromolecules. Thus, based on these findings, the RRM has capabilities of protein function identification, prediction of bioactive amino acids and protein design with desired biological function. Using the RRM, we separate different functions of TNF as different periodicities (frequencies) within the distribution of free energy electrons along TNF protein. Interestingly, these characteristic TNF frequencies are related to previously identified characteristics of proto-oncogene and oncogene proteins describing TNF involvement in oncogenesis. Consequently, we identify the key amino acids related to the crucial TNF function, i.e. receptor recognition. We have also designed the peptide which will have the ability to recognise the receptor without side effects.

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. Using different velocities of charge transfer, we predicted resonant frequencies in different frequency ranges from KHz to THz. These resonant frequencies could be relevant for taxol binding as well as a possible role of microtubules as a macromolecular computer.

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. The RRM-MV treatment was able to induce cell death in cancer cells without triggering similar effects on normal cells. However, the negative control peptides produced no toxic effects on skin cancer and normal cells. No effects on human erythrocytes were detected when treated with all peptides. CONCLUSION: It is suggested that the RRM can be applied to design therapeutic anticancer peptides.

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. RRM-MV was designed using the Resonant Recognition Model (RRM) and its effect was examined on human skin cancer and normal human skin cells in vitro. METHODS: Cell cultures were treated with various concentrations of the peptides at different incubation intervals. Cellular morphological changes (apoptosis and necrosis) were evaluated using confocal laser scanning microscopy. The cytotoxic effects of RRM-MV on human skin cancer and normal human skin cells were quantitatively determined by cytotoxicity and cell viability assays. The effect on human erythrocytes was also determined using quantitative hemolysis assay. DNA fragmentation assay was performed to detect early apoptotic events in treated cancer cells. Furthermore, to investigate the possible cell signalling pathway targeted by the peptides treatment, the levels of p-Akt expression in skin cancer and normal cells were detected by immunoblotting. RESULTS: Our results indicate that RRM-MV has a dose-dependent toxic effect on cancer cells only up to 18 h. The immunoblotting results indicated that the RRM-MV slightly increased p-Akt expression in melanoma and carcinoma cells, but did not seem to affect p-Akt expression in normal skin cells. CONCLUSIONS: RRM-MV targets and lethally harms cancer cells and leaves normal cells unharmed. It is able to reduce the cancer cell viability, disrupting the LDH activity in cancer cells and can significantly affect cancer progression. Further investigation into other cell signalling pathways is needed in the process leading to the in vivo testing of this peptide to prove its safety as a possible effective treatment for skin cancer.

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 2.3 kDa peptide. The biological activity of this computationally designed peptide analogue against cancer and normal cell lines was investigated. The cellular cytotoxicity effects were confirmed by confocal immunofluorescence microscopy, by measuring the levels of cytoplasmic lactate dehydrogenase (LDH) and by Prestoblue cell viability assay for up to 72 hours in peptide treated and non-treated cell cultures. Our results revealed that RRM-MV induced a significant dose and time-dependent cytotoxic effect on murine and human cancer cell lines. Yet, when normal murine cell lines were similarly treated with RRM-MV, no cytotoxic effects were observed. Furthermore, the non-bioactive RRM designed peptide RRM-C produced negligible cytotoxic effects on these cancer and normal cell lines when used at similar concentrations. The presence/absence of phosphorylated Akt activity in B16F0 mouse melanoma cells was assessed to indicate the possible apoptosis signalling pathway that could be affected by the peptide treatment. So far, Akt activity did not seem to be significantly affected by RRM-MV as is the case for the original viral protein. CONCLUSIONS/SIGNIFICANCE: Our findings indicate the successful application of the RRM concept to design a bioactive peptide analogue (RRM-MV) with cytotoxic effects on tumor cells only. This 2.345 kDa peptide analogue to a 49 kDa viral protein may be suitable to be developed as a potential cancer therapeutic. These results also open a new direction to the rational design of therapeutic agents for future cancer treatment.

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. This paper describes a new wireless implantable BSN that operates in medical implant communication service (MICS) frequency band. This system innovatively incorporates both sensing and actuation nodes to form a closed-control loop for physiological monitoring and drug delivery for critically ill patients. The sensing node, which is designed using system-on-chip technologies, takes advantage of the newly available ultralow-power Zarlink MICS transceiver for wireless data transmission. Finally, the specific absorption rate distribution of the proposed system was simulated to determine the in vivo electromagnetic field absorption and the power safety limits.

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 comparative analysis of changes in the activity of the irradiated LDH enzyme versus the non-radiated enzyme was performed for the selected frequencies and powers. It was found that LDH activity can be selectively increased only by irradiation at the particular frequencies of 500 MHz [electric field: 0.02 V/m (1.2 × 10⁻6 W/m²)-2.1 V/m (1.2 × 10⁻² W/m²)] and 900 MHz [electric field: 0.021-0.21 V/m (1.2 × 10⁻4 W/m²)]. Based on results obtained it was concluded that LDH enzyme activity can be modulated by specific frequencies of low power microwave radiation. This finding can serve to support the hypothesis that low intensity microwaves can induce non-thermal effects in bio-molecules.

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. The theoretical basis behind the RRM model expounds a potential interaction mechanism between electromagnetic radiation and proteins as well as protein-protein interactions. Possibility of modulating protein activity by external EMR is experimentally validated by irradiation of the L-lactate Dehydrogenase enzyme.

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. A sliding-window template cross-correlation technique is applied to an ECG signal to generate an array of correlation coefficients. Then a correlation coefficient curve is used to detect high coefficient values for a type of template that will quantify the similarity between an examined ECG signal and a template. The method presented in this paper is able to detect all three different types of ECG signals from a total 21 testing signal set with a satisfied correct rate.

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. The statistical analysis in different sleep stages highlighted that in sleep apnoea patients, the EEG delta, sigma and beta bands exhibited a strong correlation with HRV features. Then the correlation between EEG frequency bands and HRV features were examined for sleep apnoea classification using univariate and multivariate Gaussian models (UGs and MGs). The MG outperformed the UG in the classification. When EEG and HRV features were combined and modelled with MG, we achieved 64% correct classification accuracy, which is 2 or 8% improvement with respect to using only EEG or ECG features. When delta and acceleration coefficients of the EEG features were incorporated, then the overall accuracy improved to 71%.

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. This non-linear method can be applied in future evaluation of sleep EEG transients during the OSAH episodes.

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). This investigation is the extension of the Resonant Recognition Model (RRM) approach designed for structure-function analysis of proteins and DNA. The RRM is based on the finding that there is a significant correlation between spectra of the numerical presentation of amino acids and their biological activity. The RRM assumes that the selectivity of protein interactions is based on the resonant electromagnetic energy transfer at the specific frequency for each interaction. In this study Cytochrome C, Glucagon, and Hemoglobin proteins were used as the protein examples. By incorporating the SPWV distribution in the RRM, we can define the active regions along the protein molecule. In addition, it was also shown that our computational predictions are corresponding closely with the experimentally identified locations of the active/binding sites for the selected protein examples.

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.

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, 8.33 to 4 Hz could alter relative power within the corresponding EEG bands. 33 human subjects were tested under a double-blind and counter-balanced conditions. The multiple repeated three-way analysis of variance (ANOVA) mixed design (within and between-subject) analysis was employed followed by post-hoc t-tests and Bonferroni alpha-correction. The results from this study have shown that narrow alpha1 (7.5-9.5 Hz) and alpha2 (9-11 Hz) bands, associated with 8.33 and 10 Hz MF exposures, were significantly (p < 0.0005) lower than control over the temporal and parietal regions within the 10-16 min of first MF exposure session and the MF exposures were significantly higher than control of the second session MF exposure (60-65 min from the commencement of testing). Also, it was found that the beta1 (12-14 Hz) band exhibited a significant increase from before to after 13-Hz first MF exposure session at frontal region. The final outcome of our result has shown that it is possible to alter the human EEG activity of alpha and beta bands when exposed to MF at frequencies corresponding to those same bands, depending on the order and period of MF conditions. This type of EEG synchronisation of driving alpha and beta EEG by alpha and beta sinusoidal MF stimulation, demonstrated in this study, could possibly be applied as therapeutic treatment(s) of particular neurophysiological abnormalities such as sleep and psychiatric disorders.

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 findings from our study revealed a significantly higher coherence in the EEG beta2 band (16.6 Hz) corresponding to 16.66 Hz visual stimulation, suggesting a high inter-hemispheric functional connectivity during visual stimulus. A significant increase was revealed during 50 Hz visual stimulation at gamma band and a decrease during 4 Hz visual stimulation at theta band, linked with a substantial transitional shift in predominance from anterior to posterior relative power. This study may also increase the awareness of EEG visual driving response studies in clinical practice to uncover potential neurophysiologic abnormalities.

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. These power spectra were then used to compare the applied methods in terms of their frequency resolution and the effects in extraction of the features representing the PPG, ECG, and EEG signals. Some conclusions were drawn concerning the efficiency of the FFT and least squares AR methods as feature extraction methods used for representing the signals under study.

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. This result suggests that ELF fields as emitted from GSM handsets during the DTX mode may have an effect on the resting alpha band of the human EEG.