High efficacy of a characterized lytic bacteriophage in combination with thyme essential oil against multidrug-resistant Staphylococcus aureus in chicken products.

BACKGROUND: The emergence and spread of methicillin-resistant Staphylococcus aureus (MRSA) in the food industry have led to using alternative natural bioagents for controlling S. aureus in food. AIMS: The current work aimed to isolate and characterize a lytic phage specific to S. aureus and evaluate its efficacy with thyme essential oil for controlling S. aureus growth in chicken fillets. METHODS: Twenty S. aureus strains previously isolated from ready-to-eat chicken products were tested for antimicrobial susceptibility and used for phage isolation. RESULTS: All S. aureus strains were multidrug-resistant (MDR). The isolated phage (vB_SauM_CP9) belonged to the family Myoviridae and maintained its stability at pH (4-9) and temperature (30-70°C). The phage showed lytic activity on ten S. aureus strains and had a burst size (228 PFU/infected cell), latent period (45 min), and rise period (15 min). A combination of S. aureus phage multiplicity of infection (MOI) 10 + thyme oil 1% caused a higher significant reduction in S. aureus growth (87.22%) in artificially inoculated chicken fillets than individual treatment with bacteriophage or thyme essential oil. CONCLUSION: To our knowledge, this is the first report to evaluate the efficacy of bacteriophage and thyme oil for controlling the growth of MDR S. aureus in chicken products and recommending application of S. aureus phage and thyme oil combination in the food industry to achieve food safety goals and consumer protection as well as mitigate the antimicrobial resistance crisis.

Insights on toxin genotyping, virulence, antibiogram profiling, biofilm formation and efficacy of disinfectants on biofilms of Clostridium perfringens isolated from poultry, animals and humans.

AIMS: This study aimed to determine the toxin genotypes, virulence determinants and antibiogram of Clostridium perfringens isolated from poultry, animals and humans. Biofilm formation and the efficacy of disinfectants on C. perfringens biofilms were studied. METHODS AND RESULTS: Thirty C. perfringens isolates (20 clinical and 10 from chicken carcasses) were genotyped by PCR and all isolates were genotype A (cpa+). The overall prevalence of cpe, cpb2, netB and tpeL virulence genes was 6·7, 56·7, 56·7 and 36·7% respectively. Twenty-one isolates (70%) were multidrug-resistant, 8 (26·7%) were extensive drug-resistant and one isolate (3·3%) was pan drug-resistant. The average multiple antibiotic resistance index was 0·7. Biofilms were produced by 63·3% of C. perfringens isolates and categorized as weak (36·7%), moderate (16·7%) and strong (10%). Sodium hypochlorite caused significant reduction in C. perfringens biofilms (P < 0·0001). CONCLUSIONS: All C. perfringens strains in this study were type A, resistant to multiple antibiotics and most of them were biofilm producers. Sodium hypochlorite showed higher efficacy in reducing C. perfringens biofilms. SIGNIFICANCE AND IMPACT OF THE STUDY: This study reported the efficacy of disinfectants in reducing C. perfringens biofilms of economic and public health concern and recommends application on surfaces in farms, food processing plants and slaughterhouses.

Segmentation and tracking of the electro-encephalogram signal using an adaptive recursive bandpass filter.

An adaptive filtering approach for the segmentation and tracking of electro-encephalogram (EEG) signal waves is described. In this approach, an adaptive recursive bandpass filter is employed for estimating and tracking the centre frequency associated with each EEG wave. The main advantage inherent in the approach is that the employed adaptive filter has only one unknown coefficient to be updated. This coefficient, having an absolute value less than 1, represents an efficient distinct feature for each EEG specific wave, and its time function reflects the non-stationarity behaviour of the EEG signal. Therefore the proposed approach is simple and accurate in comparison with existing multivariate adaptive approaches. The approach is examined using extensive computer simulations. It is applied to computer-generated EEG signals composed of different waves. The adaptive filter coefficient (i.e. the segmentation parameter) is -0.492 for the delta wave, -0.360 for the theta wave, -0.191 for the alpha wave, -0.027 for the sigma wave, 0.138 for the beta wave and 0.605 for the gamma wave. This implies that the segmentation parameter increases with the increase in the centre frequency of the EEG waves, which provides fast on-line information about the behaviour of the EEG signal. The approach is also applied to real-world EEG data for the detection of sleep spindles.

Noise reduction in brain evoked potentials based on third-order correlations.

In this paper, we use third-order correlations (TOC) in developing a filtering technique for the recovery of brain evoked potentials (EPs). The main idea behind the presented technique is to pass the noisy signal through a finite impulse response filter whose impulse response is matched with the shape of the noise-free signal. It is shown that it is possible to estimate the filter impulse response on basis of a selected third-order correlation slice (TOCS) of the input noisy signal. This is justified by two facts. The first one is that the noise-free EPs can be modeled as a sum of damped sinusoidal signals and the selected TOCS preserve the signal structure. The second fact is that the TOCS is insensitive to both Gaussian noise and other symmetrically distributed non-Gaussian noise, (white or colored). Furthermore, the approach can be applied to either nonaveraged or averaged EP observation data. In the nonaveraged data case, the approach therefore preserves information about amplitude and latency changes. Both fixed and adaptive versions of the proposed filtering technique are described. Extensive simulation results are provided to show the validity and effectiveness of the proposed cumulant-based filtering technique in comparison with the conventional correlation-based counterpart.