[COMPLICATED URINARY TRACT INFECTIONS IN THE ELDERLY].

Urinary tract infections (UTI) are the most common bacterial infections involving lower (cystitis, prostatitis) or upper (pyelonephritis, renal abscess, perinephric abscess) urinary tract. Differentiation of complicated and uncomplicated UTI is usually based on the presence of structural or functional urinary tract abnormalities, which can increase the risk of treatment failure and development of serious complications. Factors that increase the risk are foreign bodies, stones, obstruction, neurogenic bladder, kidney transplantation, immunosuppression, and pregnancy. Complicated UTI includes a spectrum of conditions that increase the risk of treatment failure, as well as of serious complications such as bacteremia and sepsis, perinephric abscess, renal impairment and emphysematous pyelonephritis. To avoid the potentially devastating outcomes, appropriate diagnostic procedures, antibiotic and surgical treatment, and appropriate follow-up are required. The incidence of complicated UTI will grow in the future due to general aging of the population, increasing incidence of diabetes, and ever growing number of immunocompromised and immunosuppressed patients. It is of key importance to recognize complicated UTI on time, and treat it wisely and aggressively to reduce duration of the disease and the risk of antibiotic resistance.

Corruption: Engineers are Victims, Perpetrators or Both?

This study was conducted in Serbian companies on licensed engineers and in its first part included a total of 336 licensed engineers who voluntarily completed the questionnaires about their ethical orientation and attitudes toward corruption and in the second part 214 engineers who participated in the first survey, who voluntarily evaluated their company's business operations characteristics. This study has clearly shown that there is a direct significant influence of the engineer's ethical orientations and attitudes toward corruption on their evaluation of the characteristics of their respective companies regarding business operations. This research also clearly shows that only engineers with a strong deontological orientation, low ethical subjectivity, and strong readiness to fight corruption, low corruption acceptance and high awareness of corruption can successfully fight corruption, improve the business operations of their companies and make beneficial changes to society. Otherwise, they should be considered as corruption perpetrators, not just as its victims.

Comparison of the effects of continuous and pulsed mobile phone like RF exposure on the human EEG.

It is not clear yet whether Global System for Mobiles (GSM) mobile phone radiation has the ability to interfere with normal resting brain function. There have been reports that GSM exposure increases alpha band power, and does so only when the signal is modulated at low frequencies (Huber, R., Treyer, V., Borbely, A. A., Schuderer, J., Gottselig, J. M., Landolt, H.P., Werth, E., Berthold,T., Kuster, N., Buck, A and Achermann, P. Electromagnetic fields, such as those from mobile phones, alter regional cerebral blood flow and sleep and waking EEG. J Sleep Res 11, 289-295, 2002.) However, as that research employed exposure distributions that are not typical of normal GSM handset usage (deep brain areas were overexposed), it remains to be determined whether a similar result patterning would arise from a more representative exposure. In this fully counterbalanced cross-over design, we recruited 12 participants and tried to replicate the modulation linked post exposure alpha band power increase described above, but with an exposure source (dipole antenna) more closely resembling that of a real GSM handset. Exposures lasted for 15 minutes. No changes to alpha power were found for either modulated or unmodulated radiofrequency fields, and thus we failed to replicate the above results. Possible reasons for this failure to replicate are discussed, with the main reason argued to be the lower and more representative exposure distribution employed in the present study. In addition we investigated the possible GSM exposure related effects on the non-linear features of the resting electroencephalogram using the Approximate Entropy (ApEn) method of analysis. Again, no effect was demonstrated for either modulated or unmodulated radiofrequency exposures.

Prediction of "hot spots" in interleukin-2 based on informational spectrum characteristics of growth-regulating factors. Comparison with experimental data.

The Resonant Recognition Model (RRM) is a theoretical method for analysis of protein and nucleotide sequences, based on the Fourier transform of the numerical representation of sequences. The amplitude spectrum of this transform is designated Informational Spectrum (IS). There are certain common frequencies in IS of growth-regulating factors. These characteristic frequencies may correlate with their roles in cell proliferation and metabolism, and in antitumor activity. IS of IL-2 has prominent characteristics in the main frequency domain of growth factors, frequency domain of antitumor factors, and frequency domain characteristic for IL-2-alpha receptor. By means of the inverse method for these 3 domains, the amino acids in the sequence of human IL-2 that may be relevant to its biological function, the so-called "hot spots", were predicted. The most probable hot spots, obtained in this way, are in the potential binding site of IL-2 to its receptor, which agrees with experimental data.

The resonant recognition model (RRM) predicts amino acid residues in highly conserved regions of the hormone prolactin (PRL).

The resonant recognition model (RRM) is a model which treats the protein sequence as a discrete signal. It has been shown previously that certain periodicities (frequencies) in this signal characterise protein biological function. The RRM was employed to determine the characteristic frequencies of the hormone prolactin (PRL), and to identify amino acids ('hot spots') mostly contributing to these frequencies and thus proposed to mostly contribute to the biological function. The predicted 'hot spot' amino acids, Phe-19, Ser-26, Ser-33, Phe-37, Phe-40, Gly-47, Gly-49, Phe-50, Ser-61, Gly-129, Arg-176, Arg-177, Cys-191 and Arg-192 are found in the highly conserved amino-terminal and C-terminus regions of PRL. Our predictions agree with previous experimentally tested residues by site-direct mutagenesis and photoaffinity labelling.

The relationship of the resonant recognition model to effects of low-intensity light on cell growth.

The resonant recognition model (RRM) is a model of protein-protein and protein-DNA interaction based on a significant correlation between spectra of numerical presentation of the amino acid or nucleotide sequences and their biological activity. Having compared absorption characteristics of photosensitive proteins with their RRM spectral characteristics we obtained a linear correlation between the RRM frequency space and real frequency space, which determines a scaling factor between these two frequency spaces. On applying the RRM model to several groups of peptide growth factors, characteristic RRM frequencies were revealed and the corresponding real characteristic frequencies for these groups of growth factors were calculated using the scaling factor previously obtained. The real frequency characteristics of growth factors obtained in this way correspond with maxima in the action spectra of low-intensity light irradiation effects on cell proliferation.

Macromolecular bioactivity: is it resonant interaction between macromolecules?--Theory and applications.

Biological processes in any living organism are based on selective interactions between particular biomolecules. In most cases, these interactions involve and are driven by proteins which are the main conductors of any living process within the organism. The physical nature of these interactions is still not well known. This paper represents a whole new view to biomolecular interactions, in particular protein-protein and protein-DNA interactions, based on the assumption that these interactions are electromagnetic in their nature. This new approach is incorporated in the Resonant Recognition Model (RRM), which was developed over the last 10 years. It has been shown initially that certain periodicities within the distribution of energies of delocalized electrons along a protein molecule are critical for protein biological function, i.e., interaction with its target. If protein conductivity was introduced, then a charge moving through protein backbone can produce electromagnetic irradiation or absorption with spectral characteristics corresponding to energy distribution along the protein. The RRM enables these spectral characteristics, which were found to be in the range of infrared and visible light, to be calculated. These theoretically calculated spectra were proved using experimentally obtained frequency characteristics of some light-induced biological processes. Furthermore, completely new peptides with desired spectral characteristics, and consequently corresponding biological activities, were designed.

Acupuncture needles and the Seebeck effect: do temperature gradients produce electrostimulation?

Acupuncture may act through modifying bioelectric events and this may occur through different mechanisms including the application of external currents. According to the Seebeck effect which produces a potential difference when a temperature gradient is placed across a conductor, the physical properties of acupuncture needles may produce internal currents due to the temperature gradient across the needle when placed insitu. Such currents were detected when needles were differentially heated and these currents were found to be in the range capable of producing biological effects. The traditional design of acupuncture needles and traditional needle manipulations seem to maintain a temperature gradient across the needle and thus enhance the Seebeck effect.

Protein structure analysis using the resonant recognition model and wavelet transforms.

An approach based on the resonant recognition model and the discrete wavelet transform is introduced here for characterising proteins' biological function. The protein sequence is converted into a numerical series by assigning the electron-ion interaction potential to each amino acid from N-terminal to C-terminal. A set of peaks is found after performing a wavelet transform onto a numerical series representing a group of homologous proteins. These peaks are related to protein structural and functional properties and named characteristic vector of that protein group. Further more, the amino acids contributing mostly to a protein's biological functions, the so-called 'hot spots' amino acids, are predicted by the continuous wavelet transform. It is found that the hot spots are clustered around the protein's cleft structure. The wavelets approach provides a novel methods for amino acid sequence analysis as well as an expansion for the newly established macromolecular interaction model: the resonant recognition model.

Preliminary expansion of the resonant recognition model to incorporate multi variable analysis.

The Resonant Recognition Model (rrm) uses digital signal processing methods to investigate protein structure-function; and links the biological function of protein families to unique characteristic frequencies. The rrm originally used a single set of variables: the electron ion interaction potential (EIIP). Here the rrm has been expanded to include 242 sets of variables to analyse a sample of protein families. Despite the evident increase in complexity of the data, distinguishing patterns can be observed between the different protein families. The thus-obtained Signature Profiles (SP) indicate that proteins having similar overall functions may be identifiable and differentiated from others by their characteristic frequency signatures far more readily than with the single variable rrm spectra.

RRM analysis of protoporphyrinogen oxidase.

Enzymes are crucial in accelerating metabolic reactions in living organisms. Protoporphyrinogen oxidase (PpOI) is an enzyme that catalyses the production of protoporphyrin IX (PpIX), a protein used in a cancer treatment known as photodynamic therapy (PDT). In this study, a structure-function analysis of PpOI was carried out using the Resonant Recognition Model (RRM), a physico-mathematical approach for analysis of proteins interactions. This method is based on the finding that the distribution of delocalised electron energies along the protein plays a crucial role in determining the protein's biological activity. Two digital signal processing (DSP) methods were used: Fourier Transform (FT) and Continuous Wavelet Transform (CWT). Here we have determined the characteristic frequencies and the "hot spot" amino acids, and predicted the location of proteins' active site(s). Several proteins that potentially belong to the PpOI functional group were also analysed to distinguish their viability in this role.

Mapping acupuncture points using multi channel device.

The practice of acupuncture involves the stimulation of specific points on the skin called 'acupuncture points' which are small regions of local or referred pain that are more sensitive than surrounding tissue. The fact that acupuncture points can be identified subjectively as tender points and are found to have characteristic electrical properties suggest that they are functional entities rather than structural ones. These functional properties are used diagnostically in a clinical setting as pathology in a particular body location has been shown to correlate with increased tenderness and electrical conductivity of the 'corresponding' acupuncture point using electronic 'point locators', which measure the DC resistance of points compared to surrounding skin. Commercially available point locators generally utilize a metal locator probe and an indifferent electrode and are designed to produce an auditory output (usually a high pitched tone) when a point is located. These devices however, are open to criticism. They are unable to control for local variations in skin thickness, surface secretions, or pressure placed on the electrode, and are only able to measure a single point at a time. These make them time consuming to use and subjective to user bias in point selection. Furthermore these devices do not store data and are therefore unsuitable for producing a map of skin resistance, which can be accessed over time. To overcome some of the limitations of currently available single probe devices, we have designed a multi-channel probe capable of measuring and then mapping the skin resistance of multiple points.

EEG coherence changes between right and left motor cortical areas during voluntary muscular contraction.

It is known that movements of the right side of the body are controlled by the left motor cortex of the brain. The aim of this study is to evaluate the contribution of right motor cortex of the brain in the central motor control of right-sided muscle contraction. EEG/EEG coherence analysis has been used to determine the functional coupling between the right and left motor cortical areas in twenty normal volunteers, during maximum voluntary contraction (MVC) and 50% MVC of right Adductor Pollicis muscle (APM). It shows that the maximum mean coherence values were: 0.751 during MVC at 10 and 12 Hz, and 0.274 during 50% of MVC at 22 Hz. The minimum mean coherence values were: 0.716 during MVC at 48 and 50 Hz, and 0.242 during 50% MVC at 34 Hz. The high coherence values obtained during MVC, and to a lesser extent during 50% of MVC, could be attributed to the need of recruitment of both motor cortical areas during the decision phase of central motor control of voluntary muscular contraction. The "will" to perform maximum voluntary contraction could be a major factor, which contribute to the higher coherence values obtained during MVC than these associated with 50% of MVC.

Human brain wave activity during exposure to radiofrequency field emissions from mobile phones.

The aim of this study was to determine whether there is an effect of mobile phone electromagnetic field emissions on the human electroencephalograph (EEG). EEG recordings from ten awake subjects were taken during exposure to radiofrequency (RF) emissions from a mobile phone positioned behind the head. Two experimental trials were conducted. In the first trial, RF exposures were generated by a GSM mobile phone with the speaker disabled and configured to transmit at full-radiated power. During the second trial, exposures were generated by a non-modified GSM mobile phone in active standby mode. For each trial, subjects were exposed in five minute intervals to a randomized, interrupted sequence of five active and five sham exposures. The experiment was conducted under single-blind conditions. The average EEG band power in active exposure recordings was compared to corresponding sham recordings. Statistical tests indicated significant difference in the full-power mode trial within the EEG alpha (8-13 Hz) and beta (13-32 Hz) bands. A subsequent statistical analysis of median spectral power in discrete EEG rhythms revealed significant differences in 7 of the 32 distinct frequencies overall. In conclusion, the results of this study lend support to EEG effects from mobile phones activated in talk-mode.

Airway hyperreactivity in the electroceramic industry.

Seventy-four female shift workers employed in the oxide ceramics industry were examined: a group of 38 workers from the press workshop and a group of 36 controls from the mounting workshop from the same factory. The two groups did not differ by age, years of employment, smoking habit or height. Persons with atopic constitution and serious respiratory disease were excluded from the study. Interstitial lung disease was eliminated by X-ray examinations. All subjects underwent a clinical examination and completed a questionnaire. Measurements of ventilatory lung functions demonstrated no difference between the groups; lung function values were normal. Non-specific airway reactivity was expressed as PC50 Rt i.e. 50% increase in resistance in relation to the value measured after inhalation of the physiological solution. A significant difference was found for PC50 Rt between the exposed and control workers during (P < 0.001) and outside working hours (P < 0.01). Significantly different PC50 Rt values were also established within the group of exposed workers as well as within that of control workers during and outside working hours (P < 0.014 and P < 0.0018 respectively). The majority of hyperreactive persons were workers from the press workshop (n = 17) when measurements were performed during working hours. For early detection of respiratory diseases in workers employed in the oxide ceramics industry preemployment examinations and regular check-ups aiming to determine non-specific airway reactivity are suggested as necessary.

The alpha band of the resting electroencephalogram under pulsed and continuous radio frequency exposures.

The effect of GSM-like electromagnetic fields with the resting electroencephalogram (EEG) alpha band activity was investigated in a double-blind cross-over experimental paradigm, testing the hypothesis that pulsed but not continuous radio frequency (RF) exposure would affect alpha activity, and the hypothesis that GSM-like pulsed low frequency fields would affect alpha. Seventy-two healthy volunteers attended a single recording session where the eyes open resting EEG activity was recorded. Four exposure intervals were presented (sham, pulsed modulated RF, continuous RF, and pulsed low frequency) in a counterbalanced order where each exposure lasted for 20 min. Compared to sham, a suppression of the global alpha band activity was observed under the pulsed modulated RF exposure, and this did not differ from the continuous RF exposure. No effect was seen in the extremely low frequency condition. That there was an effect of pulsed RF that did not differ significantly from continuous RF exposure does not support the hypothesis that "pulsed" RF is required to produce EEG effects. The results support the view that alpha is altered by RF electromagnetic fields, but suggest that the pulsing nature of the fields is not essential for this effect to occur.

Monte Carlo simulations of the electric field close to the body in realistic environments for application in personal radiofrequency dosimetry.

Personal dosemeters can play an important role in epidemiological studies and in radiofrequency safety programmes. In this study, a Monte Carlo approach is used in conjunction with the finite difference time domain method to obtain distributions of the electric field strength close to a human body model in simulated realistic environments. The field is a proxy for the response of an ideal body-worn electric field dosemeter. A set of eight environments were modelled based on the statistics of Rayleigh, Rice and log-normal fading to simulate outdoor and indoor multipath exposures at 450, 900 and 2100 MHz. Results indicate that a dosemeter mounted randomly within 10-50 mm of the adult or child body model (torso region) will on average underestimate the spatially averaged value of the incident electric field strength by a factor of 0.52 to 0.74 over the frequencies of 450, 900 and 2100 MHz. The uncertainty in results, assessed at the 95 % confidence level (between the 2.5th and 97.5th percentiles) was largest at 2100 MHz and smallest at 450 MHz.

Advances in methods for therapeutic peptide discovery, design and development.

Drug discovery and development are intense, lengthy and interdisciplinary processes. Traditionally, drugs were discovered by synthesizing compounds in time-consuming multi-step experimental investigations followed by in vitro and in vivo biological screening. Promising candidates were then further studied for their pharmacokinetic properties, metabolism and potential toxicity. Today, the process of drug discovery has been revolutionized due to the advances in genomics, proteomics, and bioinformatics. Efficient technologies such as combinatorial chemistry, high throughput screening (HTS), virtual screening, de novo design and structure-based drug design contribute greatly to drug discovery. Peptides are emerging as a novel class of drugs for cancer therapy, and many efforts have been made to develop peptide-based pharmacologically active compounds. This paper presents a review of current advances and novel approaches in experimental and computational drug discovery and design. We also present a novel bioactive peptide analogue, designed using the Resonant Recognition Model (RRM), and discuss its potential use for cancer therapeutics.

Factors influencing uncertainty in measurement of electric fields close to the body in personal RF dosimetry.

This paper provides an insight into factors that can influence uncertainty in measurements at 900 MHz of electric fields close to the body for use in personal dosimetry. Computational simulations using the finite difference time domain method were used to determine the total electric field near the surface of the torso of heterogeneous (adult and child) human body models for a set of exposure scenarios that simulated both spatially constant and randomly varying incident fields. Modelling has shown that a properly responding isotropic electric field dosemeter mounted between 10 and 50 mm of the torso will on average underestimate the incident field strength by up to 6.45 dB. In the worst case (i.e. spatially constant field), the standard deviation or uncertainty reached 6.42 dB. Uncertainty was reduced to <2.17 dB by combining the simultaneous outputs of a pair of body-worn dosemeters (mounted front and rear of torso).

Ataxin active site determination using spectral distribution of electron ion interaction potentials of amino acids.

Ataxia is a genetic neurological disorder characterised by a neurodegenerative process affecting a motor cortex responsible for balance and coordination. Recently several genes that cause autosomal dominant ataxia development were identified. These abnormal genes share a common ability to produce abnormal ataxin proteins that can affect nerve cells in the cerebellum and spinal cord. Here, using the Resonant Recognition Model (RRM) based on signal processing, we analysed ataxin proteins and identified the characteristic features corresponding to their biological activities. The RRM is a physico-mathematical model developed for analysis of protein interactions. By incorporating Smoothed Pseudo Wigner-Ville distribution (SPWV) in the RRM, we can define the active regions along the protein molecule. The results showed that our computational predictions correspond closely with the experimentally identified locations of the active/binding sites for ataxin-1 and ataxin-3 protein groups. The results obtained provide a valuable insight into the functional performance of ataxin proteins.