Sleep-wake pattern of medical students: early versus late class starting time

The sleep-wake cycle of students is characterized by delayed onset, partial sleep deprivation and poor sleep quality. Like other circadian rhythms, the sleep-wake cycle is influenced by endogenous and environmental factors. The aim of the present study was to determine the effects of different class starting times on the sleep-wake pattern of 27 medical students. The data were collected during two medical school semesters having different class starting times. All subjects answered the Portuguese version of the Horne and Östberg Morningness/Eveningness Questionnaire, the Pittsburgh Sleep Quality Index (PSQI) and kept a sleep diary for two weeks during each semester. Better sleep quality (PSQI = 5.3 vs 3.4), delayed sleep onset (23:59 vs 0:54 h) and longer sleep duration (6 h and 55 min vs 7 h and 25 min) were observed with the late schedule. We also found reduced sleep durations during weekdays and extended sleep durations during weekends. This pattern was more pronounced during the semester with the early class schedule, indicating that the students were more sleep deprived when their classes began earlier in the morning. These results require further investigation regarding the temporal organization of our institutions.

Isolation and culture of umbilical vein mesenchymal stem cells

Bone marrow contains a population of stem cells that can support hematopoiesis and can differentiate into different cell lines including adipocytes, osteocytes, chondrocytes, myocytes, astrocytes, and tenocytes. These cells have been denoted mesenchymal stem cells. In the present study we isolated a cell population derived from the endothelium and subendothelium of the umbilical cord vein which possesses morphological, immunophenotypical and cell differentiation characteristics similar to those of mesenchymal stem cells isolated from bone marrow. The cells were isolated from three umbilical cords after treatment of the umbilical vein lumen with collagenase. The cell population isolated consisted of adherent cells with fibroblastoid morphology which, when properly stimulated, gave origin to adipocytes and osteocytes in culture. Immunophenotypically, this cell population was found to be positive for the CD29, CD13, CD44, CD49e, CD54, CD90 and HLA-class 1 markers and negative for CD45, CD14, glycophorin A, HLA-DR, CD51/61, CD106, and CD49d. The characteristics described are the same as those presented by bone marrow mesenchymal stem cells. Taken together, these findings indicate that the umbilical cord obtained from term deliveries is an important source of mesenchymal stem cells that could be used in cell therapy protocols.

Towards sustainable transport: A comparison of demographic and behavioural characteristics of Finnish and international car sharing users

SStrong evidence suggests that the climate is changing and that these changes are largely caused by human activities. A consensus exists among researchers that human activity is causing global warming and that actions to mitigate global warming need to be taken swiftly. The transportation sector, which relies heavily on fossil fuel burning and primarily oil, is one of the big contributors to air pollution problems at local, regional and global levels. It is the fastest growing source of greenhouse gas emissions and is estimated to be responsible for nearly a quarter of global energyrelated carbon dioxide emissions. Car sharing is a mobility solution encouraging its users to decrease private car usage in favour of communal transit and environmental goals. The idea of car sharing originates from the aspiration to decrease personal car ownership and to reduce vehicle distance travelled. This thesis seeks to complement the understanding of Finnish car sharing users and their usage through better categorization. Through better categorization and segmentation of Finnish car sharing users the thesis seeks to provide information for improved marketing insight. Research is done on the demographic and behavioural characteristics of Finnish car sharing users and they are compared with international findings about the characteristics of International car sharing users. The main research problem is Are Finnish car sharing users similar to international ones? A theoretical research framework on the determinants of individual car sharing usage is built based on international research about demographic and behaviouristic characteristics. After this a quantitative survey is performed to the customers of a Finnish car sharing organization. The data analysed in the thesis consist out of 532 answers received from the car sharing organizations customers. The data is analysed with descriptive and other exploratory methods, which create an understanding of Finnish car sharing users. At the end of the analysis the demographic and behavioural characteristics of Finnish car sharing users are compared with international ones. The research findings of the thesis indicate that the demographic and behavioural characteristics of Finnish car sharing usage largely follow those of their international counterparts. Thanks to the thesis results the car sharing organization is able to better target their customers through improved marketing insight.

Isolation and Characterization of Ovomucin - a Bioactive Agent of Egg White

The hen’s egg is a source of new life. Therefore, it contains many biologically active compounds. In addition to being a very nutritious food and also commonly used in the food industry due to its many techno-functional properties, the egg can serve as a source of compounds used as nutra-, pharmaand cosmeceuticals. One such interesting compound is ovomucin, an egg white protein responsible for the gel-like properties of thick egg white. Previous studies have indicated that ovomucin and ovomucin-derived peptides have several different bioactive properties. The objectives of the present study were to develop isolation methods for ovomucin, to characterize the structure of ovomucin, to compare various egg fractions as sources of ovomucin, to study the effects of various dissolving methods for ovomucin, and to investigate the bioactive properties of ovomucin and ovomucin-derived peptides. A simple and rapid method for crude ovomucin separation was developed. By using this method crude ovomucin was isolated within hours, compared to the 1-2 days (including a dialysis step) needed when using several other methods. Structural characterization revealed that ovomucin is composed of two subunits, α- and β-ovomucin, as egg white protein formerly called α1-ovomucin seemed to be ovostatin. However, it might be possible that ovostatin is associated within β- and α-ovomucin. This interaction could even have some effect on the physical nature of various egg white layers. Although filtration by-product fraction was a very prominent source of both crude and β-ovomucin, process development has reduced its amount so significantly that it has no practical meaning anymore. Thus, the commercial liquid egg white is probably the best option, especially if it generally contains amounts of β-ovomucin as high as were found in these studies. Crude ovomucin was dissolved both by using physical and enzymic methods. Although sonication was the most effective physical method for ovomucin solubilisation, colloid milling seemed to be a very promising alternative. A milk-like, smooth and opaque crude ovomucin suspension was attained by using a colloid mill. The dissolved ovomucin fractions were further tested for bioactive properties, and it was found that three dissolving methods tested produced moderate antiviral activity against Newcastle disease virus, namely colloid milling, enzymatic hydrolysis and a combination of sonicaton and enzymatic hydrolysis. Moreover, trypsin-digested crude ovomucin was found to have moderate antiviral activity against avian influenza virus: both subtype H5 and H7.

Social class as a factor for the construction of a musician’s identity : The Musician’s social background and identity questionnaire (MSBIQ) – a cross-sectional comparative quantitative online survey research study of music students at two higher education institutions in Finland

There is currently little empirical knowledge regarding the construction of a musician’s identity and social class. With a theoretical framework based on Bourdieu’s (1984) distinction theory, Bronfenbrenner’s (1979) theory of ecological systems, and the identity theories of Erikson (1950; 1968) and Marcia (1966), a survey called the Musician’s Social Background and Identity Questionnaire (MSBIQ) is developed to test three research hypotheses related to the construction of a musician’s identity, social class and ecological systems of development. The MSBIQ is administered to the music students at Sibelius Academy of the University of Arts Helsinki and Helsinki Metropolia University of Applied Sciences, representing the ’highbrow’ and the ’middlebrow’ samples in the field of music education in Finland. Acquired responses (N = 253) are analyzed and compared with quantitative methods including Pearson’s chi-square test, factor analysis and an adjusted analysis of variance (ANOVA). The study revealed that (1) the music students at Sibelius Academy and Metropolia construct their subjective musician’s identity differently, but (2) social class does not affect this identity construction process significantly. In turn, (3) the ecological systems of development, especially the individual’s residential location, do significantly affect the construction of a musician’s identity, as well as the age at which one starts to play one’s first musical instrument. Furthermore, a novel finding related to the structure of a musician’s identity was the tripartite model of musical identity consisting of the three dimensions of a musician’s identity: (I) ’the subjective dimension of a musician’s identity’, (II) ’the occupational dimension of a musician’s identity’ and, (III) ’the conservative-liberal dimension of a musician’s identity’. According to this finding, a musician’s identity is not a uniform, coherent entity, but a structure consisting of different elements continuously working in parallel within different dimensions. The results and limitations related to the study are discussed, as well as the objectives related to future studies using the MSBIQ to research the identity construction and social backgrounds of a musician or other performing artists.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Isolation and intracellular localization of insulin-like proteins from leaves of Bauhinia variegata

Evidence based on immunological cross-reactivity and anti-diabetic properties has suggested the presence of insulin-like peptides in plants. The objective of the present study was to investigate the presence of insulin-like proteins in the leaves of Bauhinia variegata ("pata-de-vaca", "mororó"), a plant widely utilized in popular medicine as an anti-diabetic agent. We show that an insulin-like protein was present in the leaves of this plant. A chloroplast protein with a molecular mass similar to that of bovine insulin was extracted from 2-mm thick 15% SDS-PAGE gels and fractionated with a 2 x 24 cm Sephadex G-50 column. The activity of this insulin-like protein (0.48 mg/mL) on serum glucose levels of four-week-old Swiss albino (CF1) diabetic mice was similar to that of commercial swine insulin used as control. Further characterization of this molecule by reverse-phase hydrophobic HPLC chromatographic analysis as well as its antidiabetic activity on alloxan-induced mice showed that it has insulin-like properties. Immunolocalization of the insulin-like protein in the leaves of B. variegata was performed by transmission electron microscopy using a polyclonal anti-insulin human antibody. Localization in the leaf blades revealed that the insulin-like protein is present mainly in chloroplasts where it is also found associated with crystals which may be calcium oxalate. The presence of an insulin-like protein in chloroplasts may indicate its involvement in carbohydrate metabolism. This finding has strengthened our previous results and suggests that insulin-signaling pathways have been conserved through evolution.

Comparison of the effectiveness of initial combined antiretroviral therapy with nelfinavir or efavirenz at a university-based outpatient service in Brazil

Since there are some concerns about the effectiveness of highly active antiretroviral therapy in developing countries, we compared the initial combination antiretroviral therapy with zidovudine and lamivudine plus either nelfinavir or efavirenz at a university-based outpatient service in Brazil. This was a retrospective comparative cohort study carried out in a tertiary level hospital. A total of 194 patients receiving either nelfinavir or efavirenz were identified through our electronic database search, but only 126 patients met the inclusion criteria. Patients were included if they were older than 18 years old, naive for antiretroviral therapy, and had at least 1 follow-up visit after starting the antiretroviral regimen. Fifty-one of the included patients were receiving a nelfinavir-based regimen and 75 an efavirenz-based regimen as outpatients. Antiretroviral therapy was prescribed to all patients according to current guidelines. By intention-to-treat (missing/switch = failure), after a 12-month period, 65% of the patients in the efavirenz group reached a viral load <400 copies/mL compared to 41% of the patients in the nelfinavir group (P = 0.01). The mean CD4 cell count increase after a 12-month period was also greater in the efavirenz group (195 x 10(6) cells/L) than in the nelfinavir group (119 x 10(6) cells/L; P = 0.002). The efavirenz-based regimen was superior compared to the nelfinavir-based regimen. The low response rate in the nelfinavir group might be partially explained by the difficulty of using a regimen requiring a higher patient compliance (12 vs 3 pills a day) in a developing country.

Distribution of the human leukocyte antigen class II alleles in Brazilian patients with chronic hepatitis C virus infection

Hepatitis C virus (HCV) infection is a global medical problem. The current standard of treatment consists of the combination of peginterferon plus ribavirin. This regimen eradicates HCV in 55% of cases. The immune response to HCV is an important determinant of disease evolution and can be influenced by various host factors. HLA class II may play an important role in immune response against HCV. The objective of the present study was to determine the distribution of HLA class II (DRB1 and DQB1) alleles, their association with chronic HCV infection and their response to interferon therapy. One hundred and two unrelated white Brazilian patients with chronic HCV infection, 52 responders (45 males and 7 females) and 50 non-responders (43 males and 7 females) to antiviral treatment, were included in the study. Healthy Brazilian bone marrow donors of Caucasian origin from the same geographic area constituted the control group (HLA-DRB1, N = 99 and HLA-DQB1, N = 222 individuals). HLA class II genotyping was performed using a low-resolution DRB1, DQB1 sequence-specific primer amplification. There were higher frequencies of HLA-DRB1*13 (26.5 vs 14.1%) and HLA-DQB1*02 (52.9 vs 38.7%) in patients compared with controls; however, these were not significantly different after P correction (Pc = 0.39 and Pc = 0.082, respectively). There was no significant difference between the phenotypic frequencies of HLA-DRB1 (17.3 vs 14.0%) and HLA-DQB1 alleles in responder and non-responder HCV patients. The HLA-DRB1*07 allele was significantly more common in HCV patients (33.3 vs 12.1%) than in controls (Pc = 0.0039), suggesting that the HLA-DRB1*07 allele is associated with chronic HCV infection.

The efficacy of moxifloxacin-based triple therapy in treatment of Helicobacter pylori infection: a systematic review and meta-analysis of randomized clinical trials

Recent evidence shows that moxifloxacin could exert an antimicrobial effect against Helicobacter pylori in both in vitroand in vivo models. To systematically evaluate whether moxifloxacin-containing triple therapy could improve eradication rates and reduce side effects in first-line or second-line anti-H. pyloritreatment, eligible articles were identified by searches of electronic databases. We included all randomized trials comparing moxifloxacin-based triple therapy with standard triple or quadruple therapy during H. pylori eradication treatment. Statistical analysis was performed with Review Manager 5.0.10. Subanalysis/sensitivity analysis was also performed. We identified seven randomized trials (n=1263). Pooled H. pylori eradication rates were 79.03% (95%CI: 75.73-82.07) and 68.33% (95%CI: 64.44-72.04) for patients with moxifloxacin-based triple therapy or with standard triple or quadruple therapy, respectively (intention-to-treat analysis). The odds ratio (OR) was 1.82 (95%CI: 1.17-2.81), the occurrence of total side effects was 15.23% (95%CI: 12.58-18.20) and 27.17% (95%CI: 23.64-30.92) for groups with or without moxifloxacin, and the summary OR was 0.45 (95%CI: 0.26-0.77). In subgroup analyses, we noted that the second-line eradication rate in the moxifloxacin group was significantly higher than that in the quadruple therapy group (73.33 vs 60.17%, OR: 1.78, 95%CI: 1.16-2.73, P<0.001). However, there was no difference in first-line eradication treatment. Findings from this meta-analysis suggest that moxifloxacin-based triple therapy is more effective and better tolerated than standard triple or quadruple therapy. Therefore, a moxifloxacin-based triple regimen should be used in the second-line treatment of H. pylori infection.

Long-term efficacy of a rural community-based integrated intervention for prevention and management of chronic obstructive pulmonary disease: a cluster randomized controlled trial in China's rural areas

This study aimed to assess the efficacy of a rural community-based integrated intervention for early prevention and management of chronic obstructive pulmonary disease (COPD) in China. This 18-year cluster-randomized controlled trial encompassing 15 villages included 1008 patients (454 men and 40 women in the intervention group [mean age, 54 ± 10 years]; 482 men and 32 women in the control group [mean age, 53 ± 10 years]) with confirmed COPD or at risk for COPD. Villages were randomly assigned to the intervention or the control group, and study participants residing within the villages received treatment accordingly. Intervention group patients took part in a program that included systematic health education, smoking cessation counseling, and education on management of COPD. Control group patients received usual care. The groups were compared after 18 years regarding the incidence of COPD, decline in lung function, and mortality of COPD. COPD incidence was lower in the intervention group than in the control group (10% vs 16%, <0.05). A decline in lung function was also significantly delayed in the intervention group compared to the control group of COPD and high-risk patients. The intervention group showed significant improvement in smoking cessation compared with the control group, and smokers in the intervention group had lower smoking indices than in the control group (350 vs 450, <0.05). The intervention group also had a significantly lower cumulative COPD-related death rate than the control group (37% vs 47%, <0.05). A rural community-based integrated intervention is effective in reducing the incidence of COPD among those at risk, delaying a decline in lung function in COPD patients and those at risk, and reducing mortality of COPD.

Effects of continuous vs interval exercise training on oxygen uptake efficiency slope in patients with coronary artery disease

The oxygen uptake efficiency slope (OUES) is a submaximal index incorporating cardiovascular, peripheral, and pulmonary factors that determine the ventilatory response to exercise. The purpose of this study was to evaluate the effects of continuous exercise training and interval exercise training on the OUES in patients with coronary artery disease. Thirty-five patients (59.3±1.8 years old; 28 men, 7 women) with coronary artery disease were randomly divided into two groups: continuous exercise training (n=18) and interval exercise training (n=17). All patients performed graded exercise tests with respiratory gas analysis before and 3 months after the exercise-training program to determine ventilatory anaerobic threshold (VAT), respiratory compensation point, and peak oxygen consumption (peak VO2). The OUES was assessed based on data from the second minute of exercise until exhaustion by calculating the slope of the linear relation between oxygen uptake and the logarithm of total ventilation. After the interventions, both groups showed increased aerobic fitness (P<0.05). In addition, both the continuous exercise and interval exercise training groups demonstrated an increase in OUES (P<0.05). Significant associations were observed in both groups: 1) continuous exercise training (OUES and peak VO2 r=0.57; OUES and VO2 VAT r=0.57); 2) interval exercise training (OUES and peak VO2 r=0.80; OUES and VO2 VAT r=0.67). Continuous and interval exercise training resulted in a similar increase in OUES among patients with coronary artery disease. These findings suggest that improvements in OUES among CAD patients after aerobic exercise training may be dependent on peripheral and central mechanisms.

Market anomalies and tactical asset allocation: Utilising market anomalies in multiple asset class portfolios with the Black−Litterman model

This thesis discusses the basic problem of the modern portfolio theory about how to optimise the perfect allocation for an investment portfolio. The theory provides a solution for an efficient portfolio, which minimises the risk of the portfolio with respect to the expected return. A central feature for all the portfolios on the efficient frontier is that the investor needs to provide the expected return for each asset. Market anomalies are persistent patterns seen in the financial markets, which cannot be explained with the current asset pricing theory. The goal of this thesis is to study whether these anomalies can be observed among different asset classes. Finally, if persistent patterns are found, it is investigated whether the anomalies hold valuable information for determining the expected returns used in the portfolio optimization Market anomalies and investment strategies based on them are studied with a rolling estimation window, where the return for the following period is always based on historical information. This is also crucial when rebalancing the portfolio. The anomalies investigated within this thesis are value, momentum, reversal, and idiosyncratic volatility. The research data includes price series of country level stock indices, government bonds, currencies, and commodities. The modern portfolio theory and the views given by the anomalies are combined by utilising the Black-Litterman model. This makes it possible to optimise the portfolio so that investor’s views are taken into account. When constructing the portfolios, the goal is to maximise the Sharpe ratio. Significance of the results is studied by assessing if the strategy yields excess returns in a relation to those explained by the threefactormodel. The most outstanding finding is that anomaly based factors include valuable information to enhance efficient portfolio diversification. When the highest Sharpe ratios for each asset class are picked from the test factors and applied to the Black−Litterman model, the final portfolio results in superior riskreturn combination. The highest Sharpe ratios are provided by momentum strategy for stocks and long-term reversal for the rest of the asset classes. Additionally, a strategy based on the value effect was highly appealing, and it basically performs as well as the previously mentioned Sharpe strategy. When studying the anomalies, it is found, that 12-month momentum is the strongest effect, especially for stock indices. In addition, a high idiosyncratic volatility seems to be positively correlated with country indices on stocks.

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

Study of bacteria Gluconobacter sp.: isolation, purification, phenotypic and molecular identification

The importance of the study of acetic bacteria, on species of the Gluconobacter genus is based on its industrial application, as these possess the capacity of bioconversion of sorbitol to sorbose, enabling the process of vitamin C production. The study involved samples collected in industries of soft drinks, flowers, fruits and honey, followed by purification, phenotypic identification, molecular identification with the use of primer defined from Nucleotide Sequence Database consultation. Strains preserved were identified as members of the Acetobacteraceae family, Gluconobacter genus. 110 strains had been isolated of substrate: Pyrostegia venusta (ker-gawler), honey, Vitis vinifera (grape), Pyrus communis (pear), Malus sp. (apple) and in two samples of soft drinks. Of this total 57 strains had been recovered in manitol medium (manitol, yeast extract, peptone), 12 in YMG medium (glucose, manitol, yeast extract, ethanol, acetic acid), 41 in enrichment medium (De Ley and Swings) and later in the GYC medium (glucose, yeast extract and calcium carbonate). 68 strains were identified as Gram negative bacilli rods. Of these, 31 were characterized biochemically as belonging to the Acetobacteriaceae family as they were catalase positive, oxidase negative and producers of acid from glucose. The characterization of these strains was complemented with the biochemistry tests: gelatin liquefaction, nitrate reduction, indole and H2S production, oxidation of ethanol to acetic acid and molecular tests for genus identification. Only eight strains were characterized as pertaining to the Gluconobacter genus. The strains are maintained in collection cultures at the Microbiology Laboratory of the Biology Department at the São Paulo State University (UNESP) in Assis, stored in malt extract at -196 ºC.