Viininmaistelun alkeet -tapahtuma Maria P:ssä

Tiivistelmä Tekijät: Paananen Riina ja Korkiakoski Merika Työn nimi: Viininmaistelun alkeet -tapahtuma Maria P:ssä Tutkintonimike: Restonomi (AMK), matkailun koulutus Asiasanat: tapahtuma, viini, viininmaistelu, Chile Opinnäytetyön tarkoituksena oli suunnitella ja järjestää Viininmaistelun alkeet -tapahtuma. Tapahtuman toimeksiantajana toimi kajaanilainen yritys Viinibaari Maria P. Tapahtuma haluttiin toteuttaa baarin imagoon sopivaksi. Opinnäytetyön tavoitteena oli saada Viini-baarille lisää asiakkaita tutustuttamalla kokemattomia viininmaistajia viineihin. Työ oli toiminnallinen opinnäytetyö, jonka tuotoksena oli Viininmaistelun alkeet -tapahtuma. Opinnäytetyöhön kerättiin teoriapohjaa viininmaistelusta sekä viinin ja ruoan yhdistämisestä, Chilestä viinimaana ja tapahtuman järjestämisestä. Näitä kaikkia käytettiin lopullisen tuotoksen valmistumiseen. Toteutuksen arviointina toimi tapahtumaan osallistuneilta saatu kirjallinen palaute. Palautteen mukaan kehittämistehtävän toteutuksessa onnistuttiin hyvin, sillä opinnäytetyön ennalta määritellyt tavoitteet saavutettiin. Opinnäytetyötä voidaan käyttää apuna jatkossa vastaavien tapahtumien suunnittelussa.Abstract Authors: Paananen Riina & Korkiakoski Merika Title of the Publication: Basics of wine tasting- event Degree title: Bachelor of Hospitality Management Keywords: event, wine, tasting, Chile The purpose for this thesis was to plan and arrange Basics of wine tasting –event. The commissioner for this thsesis was a local bar in Kajaani called Viinibaari Maria P. The event was planned to suit the imago of the bar. The objective of the thesis was to gain more customers to Viinibaari Maria P by introducing various wines to novice wine tasters. This research was a functional thesis which produced the Basics wine tasting event. The theory of this thesis focused on wine tasting, combining wine and food, Chile as a wine producer, and on planning and arranging an event. The feedback for the execution consists of the feedback forms that the customers of the event were asked to fill in. In addition observation method was used for evaluation. According to the feedback the event was successful because the objective of the thesis was reached. Our conclusion is that this thesis can be used as a guide in planning similar events

Antimicrobial susceptibility of <i>Streptococcus pneumoniae</i> strains carried by children infected with HIV.

<p>Antimicrobial susceptibility of <i>Streptococcus pneumoniae</i> strains carried by children infected with HIV.</p

Represents results from multivariate regression analysis following bivariate regression analysis.

<p>The x-axis depicts the by bivariate regression selected 68 OTUs and the y–axis the selected variables. The heatmap shows significant correlations (p-value less than 0.05) from multivariate analysis. Blue squares show positive changes in relative abundance, whereas red squares show negative correlations. The intensity of colour correlates with the magnitude of the (log) fold change value (see colour key).</p

Represent the results from multivariate logistic regression analysis following CCA.

<p>Significant correlations are depicted between the by CCA selected 12 variables and 31 OTU’s. The x-axis depicts the respective OTUs and the y–axis the 12 variables tested. The heatmap shows significant correlations (p-value less than 0.05) from multivariate analysis. The colour represents the effect size and direction of the correlation. Blue squares show positive changes in relative abundance, whereas red squares show negative correlations. The intensity of color correlates with the magnitude of the (log) fold change value (see colour key).</p

Represents the results from bivariate regression analysis.

<p>Significant correlations between 14 variables and the top 100 OTUs are depicted after correcting for the correlation between season and OUT composition. The x-axis depicts the respective OTUs and the y–axis the 15 variables tested. The heatmap shows significant correlations (p-value less than 0.05) from univariate analysis. Blue squares show positive changes in relative abundance, whereas red squares show negative correlations. The intensity of colour correlates with the magnitude of the (log) fold change value (see colour key).</p

Represents the results from univariate regression analysis. Significant correlations between 15 variables and the top 100 OTUs are depicted.

<p>The x-axis depicts the respective OTUs and the y–axis the 15 variables tested. The heatmap shows significant correlations (p-value less than 0.05) from univariate analysis. Blue squares show positive changes in relative abundance, whereas red squares show negative correlations. The intensity of colour correlates with the magnitude of the (log) fold change value (see colour key).</p

Correlations between variables and microbiome composition at OTU level identified by the different types of analysis.

<p>In <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050267#pone-0050267-g001" target="_blank">figure 1</a>, results from Canonical Correlation Analysis (CCA) are depicted, where each variable is plotted with the weight of this variable from the first order and second order variates as coordinates. Pairs of variables with relatively large weights in the same direction represent positive correlations and variables whose weights have opposite directions exhibit inverse correlations.After applying the canonical correlation analysis with a cut off p-value <0.15, 12 external variables (in blue color) and 31 OTUs (in old rose color) remained as potential determinants of microbiota composition.</p

Phyla composition of individual 1 per sample site and DNA extraction method.

<p>Samples extracted with Agowa and Qiagen showed a significant higher proportion of Actinobacteria and Firmicutes and a lower proportion of Bacteriodetes, compared to Epicentre and Mobio, especially in the oropharyngeal and saliva samples for all 4 individuals. Note that nasopharyngeal samples from all four individuals isolated with Epicentre failed to give results.</p

Principal component analyses (PCA) of the microbiota profiles and Principal Coordinate of Analyses (PcoA) plot of the weighted and unweighted UniFrac average distance per site and DNA extraction method.

<p><i>a</i>. Principal component analyses (PCA) of the microbiota profiles of the nares and nasopharynx depicted per dilution and DNA extraction method. Depicted in colors are 16S DNA levels (blue = ≥1 pg/µl, green = <1 pg/µl). Depicted in characters are the DNA extraction methods (A = Agowa, E = Epicentre, Q = qiagen, M = Mobio). Clustering of the samples is according to DNA level and DNA extraction method. Differences in template concentration were due to differences in DNA extraction efficiency between used methods and effects of template concentration on microbiota analyses were therefore fully tied to DNA extraction effects. <i>b</i>.PcoA plot of the weighted UniFrac. Shown in colored circles are the DNA extraction methods (yellow = Epicentre, red = Mobio, blue = Qiagen and green = Agowa). The abbreviations represent the site of sampling (NP = nasopharynx, N = nares, OP = oropharynx, SA = saliva). Clear clustering per site of sampling was observed with saliva and oropharynx distant from nares and nasopharynx samples. For the oropharynx and saliva clusters significant sub-clustering per DNA extraction method was seen with clusters of Epicentre and Mobio, distant from Agowa and Qiagen clusters. DNA extraction method in these high density sites even introduced a larger distance in microbiota profile than origin of the sample (saliva or oropharynx). <i>c</i>. PCoA plot of the unweighted UniFrac as described above. Clear clustering per site of sampling was observed with saliva and oropharynx distant from nares and nasopharynx samples, and also between saliva and oropharynx. For the nares and nasopharynx clusters significant sub-clustering per DNA extraction method was seen with clusters of Agowa, Qiagen and Epicentre distant from Mobio. Both weighted and unweighted UniFrac analysis of sequence data revealed distinct clustering of saliva and oropharyngeal separate from nares and nasopharynx samples, reflecting unique differences in microbiota composition between these sites (Amova, p<0.001, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032942#pone.0032942.s004" target="_blank">Figure S4</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032942#pone.0032942.s005" target="_blank">S5</a>).</p

Average relative abundance of the 6 main taxa in undiluted saliva and dilutions 1 to 3 (10⁷ to 10⁵ bacteria per ml, respectively).

<p>Shown in error bars is the standard deviation per dilution indicative of the variation between DNA extraction methods. We used ANOVA statistics to test for significant differences. Dilution 3 shows a significant increase in Proteobacteria (p<0.001, mean 26,11% and 3.6%, SD 17.5 and 2.5% respectively) and a significant decrease in Bacteroidetes (p<0.001, mean 18.99% and 43.1% respectively) compared to the undiluted saliva samples. By diluting the sample up to 10⁵ bacteria per ml an increase in Firmicutes, mostly <i>Veilonella</i>, was observed, and a decrease in Bacteroidetes, mostly <i>Prevotella</i>.</p