Development of infrared spectroscopy for assessing bacterial quality in foods

Rapid and specific detection of foodborne bacteria that can cause food spoilage or illness associated to its consumption is an increasingly important task in food industry. Bacterial detection, identification, and classification are generally performed using traditional methods based on biochemical or serological tests and the molecular methods based on DNA or RNA fingerprints. However, these methodologies are expensive, time consuming and laborious. Infrared spectroscopy is a reliable, rapid, and economic technique which could be explored as a tool for bacterial analysis in the food industry. In this thesis it was evaluated the potential of IR spectroscopy to study the bacterial quality of foods. In Chapter 2, it was developed a calibration model that successfully allowed to predict the bacterial concentration of naturally contaminated cooked ham samples kept at refrigeration temperature during 8 days. In this part, it was developed the methodology that allowed the best reproducibility of spectra from bacteria colonies with minimal sample preparation, which was used in the subsequent work. Several attempts trying different resolutions and number of scans in the IR were made. A spectral resolution of 4 cm-1, with 32 scans were the settings that allowed the best results. Subsequently, in Chapter 3, it was made an attempt to identify 22 different foodborne bacterial genera/species using IR spectroscopy coupled with multivariate analysis. The principal component analysis, used as an exploratory technique, allowed to form distinct groups, each one corresponding to a different genus, in most of the cases. Then, a hierarchical cluster analysis was performed to further analyse the group formation and the possibility of distinction between species of the same bacterial genus. It was observed that IR spectroscopy not only is suitable to the distinction of the different genera, but also to differentiate species of the same genus, with the simultaneous use of principal component analysis and cluster analysis techniques. The utilization of IR spectroscopy and multivariate statistical analysis were also investigated in Chapter 4, in order to confirm the presence of Listeria monocytogenes and Salmonella spp. isolated from contaminated foods, after growth in selective medium. This would allow to substitute the traditional biochemical and serological methods that are used to confirm these pathogens and that delay the obtainment of the results up to 2 days. The obtained results allowed the distinction of 3 different Listeria species and the distinction of Salmonella spp. from other bacteria that can be mistaken with them. Finally, in chapter 5, high pressure processing, an emerging methodology that permits to produce microbiologically safe foods and extend their shelf-life, was applied to 12 foodborne bacteria to determine their resistance and the effects of pressure in cells. A treatment of 300 MPa, during 15 minutes at room temperature was applied. Gram-negative bacteria were inactivated to undetectable levels and Gram-positive showed different resistances. Bacillus cereus and Staphylococcus aureus decreased only 2 logs and Listeria innocua decreased about 5 logs. IR spectroscopy was performed in bacterial colonies before and after HPP in order to investigate the alterations of the cellular compounds. It was found that high pressure alters bands assigned to some cellular components as proteins, lipids, oligopolysaccharides, phosphate groups from the cell wall and nucleic acids, suggesting disruption of the cell envelopes. In this work, bacterial quantification and classification, as well as assessment of cellular compounds modification with high pressure processing were successfully performed. Taking this into account, it was showed that IR spectroscopy is a very promising technique to analyse bacteria in a simple and inexpensive manner.

Genetic programming and bacterial algorithm for neural networks and fuzzy systems design

In the field of control systems it is common to use techniques based on model adaptation to carry out control for plants for which mathematical analysis may be intricate. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this line, this paper gives a perspective on the quality of results given by two different biologically connected learning algorithms for the design of B-spline neural networks (BNN) and fuzzy systems (FS). One approach used is the Genetic Programming (GP) for BNN design and the other is the Bacterial Evolutionary Algorithm (BEA) applied for fuzzy rule extraction. Also, the facility to incorporate a multi-objective approach to the GP algorithm is outlined, enabling the designer to obtain models more adequate for their intended use.

Genetic and bacterial programming for B-Spline neural networks design

The design phase of B-spline neural networks is a highly computationally complex task. Existent heuristics have been found to be highly dependent on the initial conditions employed. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this paper, the Bacterial Programming approach is presented, which is based on the replication of the microbial evolution phenomenon. This technique produces an efficient topology search, obtaining additionally more consistent solutions.

Design of B-spline neural networks using a bacterial programming approach

The design phase of B-spline neural networks represents a very high computational task. For this purpose, heuristics have been developed, but have been shown to be dependent on the initial conditions employed. In this paper a new technique, Bacterial Programming, is proposed, whose principles are based on the replication of the microbial evolution phenomenon. The performance of this approach is illustrated and compared with existing alternatives.

Bacterial algorithm applied for fuzzy rule extraction

This paper presents a method of using the so-colled "bacterial algorithm" (4,5) for extracting a fuzzy rule base from a training set. The bewly proposed bacterial evolutionary algorithm (BEA) is shown. In our application one bacterium corresponds to a fuzzy rule system.

Bacterial peroxide forming enzymes

Dissertação de mestrado, Engenharia Biológica, Faculdade de Ciências e Tecnologia, Universidade do Algarve; Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, 2015

Pharmacist intervention on adherence to therapy in the elderly

Background: Non-adherence to therapy contributes to the increase in hospitalizations, admissions to nursing homes, decreased quality of life and consequent increased morbimortality in the elderly. Aim: To assess whether pharmacist intervention contributes to the adherence to medical prescription by elderly patients.

Bacterial Biomass along the Kuroshio Extension

Senior thesis written for Oceanography 445

A Retrospective Claims Analysis of Medication Adherence and Persistence Among Patients Taking Antidepressants for the Treatment of Major Depressive Disorder (MDD)

Thesis (Master's)--University of Washington, 2015

Cardiorespiratory fitness is negatively associated with metabolic risk factors independently of the adherence to a healthy dietary pattern

Background and aim: Cardiorespiratory fitness (CRF) and diet have been involved as significant factors towards the prevention of cardio-metabolic diseases. This study aimed to assess the impact of the combined associations of CRF and adherence to the Southern European Atlantic Diet (SEADiet) on the clustering of metabolic risk factors in adolescents. Methods and Results: A cross-sectional school-based study was conducted on 468 adolescents aged 15-18, from the Azorean Islands, Portugal. We measured fasting glucose, insulin, total cholesterol (TC), HDL-cholesterol, triglycerides, systolic blood pressure, waits circumference and height. HOMA, TC/HDL-C ratio and waist-to-height ratio were calculated. For each of these variables, a Z-score was computed by age and sex. A metabolic risk score (MRS) was constructed by summing the Z scores of all individual risk factors. High risk was considered when the individual had 1SD of this score. CRF was measured with the 20 m-Shuttle-Run- Test. Adherence to SEADiet was assessed with a semi-quantitative food frequency questionnaire. Logistic regression showed that, after adjusting for potential confounders, unfit adolescents with low adherence to SEADiet had the highest odds of having MRS (OR Z 9.4; 95%CI:2.6e33.3) followed by the unfit ones with high adherence to the SEADiet (OR Z 6.6; 95% CI: 1.9e22.5) when compared to those who were fit and had higher adherence to SEADiet.

Characterizing the fungal and bacterial microflora and concentrations in fitness centres

Fitness centres are special places where conditions for microbiological proliferation should be considered. Moisture due to human perspiration and water condensation as a result of human physical activities are prevalent in this type of buildings. Exposure to microbial contaminants is clinically associated with respiratory disorders and people who work out in polluted environments would be susceptible to contaminants. This work studied the indoor air contamination in three gymnasiums in Lisbon. The sampling was performed at two periods: at the opening (morning) and closing (night) of the three gymnasiums. The airborne bacterial and fungal populations were sampled by impaction directly onto Tryptic Soy Agar (for bacteria) and Malt Extract Agar (for fungi) plates, using a Merck MAS-100 air sampler. Higher bacterial concentrations were found at night as compared to the morning but the same behaviour was not found for fungal concentrations. Gram-negative catalase positive cocci were the dominant bacteria in indoor air samples of the studied gymnasiums. In this study, 21 genera/species of fungal colonies were identified. Chrysosporium sp., Chrysonilia sp., Neoscytalidium hialinum, Sepedonium sp. and Penicillium sp. were the most prevalent species identified in the morning, while Cladosporium sp., Penicillium sp., Chrysosporium sp., Acremonium sp. and Chrysonilia sp. were more prevalent at night. A well-designed sanitation and maintenance program for gymnasiums is needed to ensure healthier space for indoor physical activity.

Bacterial inter-species communication mediated by the autoinducer-2 signal

Dissertation presented to obtain the Ph.D degree in Biology by Universidade Nova de Lisboa, Instituto de Tecnologia Química e Biológica, Instituto Gulbenkian de Ciência.

Recycling old screen-printed electrodes with newly designed plastic antibodies on the wall of carbon nanotubes as sensory element for in situ detection of bacterial toxins in water

Using low cost portable devices that enable a single analytical step for screening environmental contaminants is today a demanding issue. This concept is here tried out by recycling screen-printed electrodes that were to be disposed of and by choosing as sensory element a low cost material offering specific response for an environmental contaminant. Microcystins (MCs) were used as target analyte, for being dangerous toxins produced by cyanobacteria released into water bodies. The sensory element was a plastic antibody designed by surface imprinting with carefully selected monomers to ensure a specific response. These were designed on the wall of carbon nanotubes, taking advantage of their exceptional electrical properties. The stereochemical ability of the sensory material to detect MCs was checked by preparing blank materials where the imprinting stage was made without the template molecule. The novel sensory material for MCs was introduced in a polymeric matrix and evaluated against potentiometric measurements. Nernstian response was observed from 7.24 × 10−10 to 1.28 × 10−9 M in buffer solution (10 mM HEPES, 150 mM NaCl, pH 6.6), with average slopes of −62 mVdecade−1 and detection capabilities below 1 nM. The blank materials were unable to provide a linear response against log(concentration), showing only a slight potential change towards more positive potentials with increasing concentrations (while that ofthe plastic antibodies moved to more negative values), with a maximum rate of +33 mVdecade−1. The sensors presented good selectivity towards sulphate, iron and ammonium ions, and also chloroform and tetrachloroethylene (TCE) and fast response (<20 s). This concept was successfully tested on the analysis of spiked environmental water samples. The sensors were further applied onto recycled chips, comprehending one site for the reference electrode and two sites for different selective membranes, in a biparametric approach for “in situ” analysis.

A copper protein and a cytochrome bind at the same site on bacterial cytochrome c peroxidase

Biochemistry, 2004, 43 (46), pp 14566–14576 DOI: 10.1021/bi0485833