Immune parametres of mussels treated with Prestige fuel oil M. Camino Ordás, Joan Albaiges, Josep M. Bayona, Amando Ordás and Antonio Figueras Instituto.

Slides:



Advertisements
Similar presentations
Statistics and Research methods Wiskunde voor HMI Bijeenkomst 5.
Advertisements

Randomized Complete Block and Repeated Measures (Each Subject Receives Each Treatment) Designs KNNL – Chapters 21,
Analysis of Variance (ANOVA)
Copyright © Allyn & Bacon (2007) Single-Variable, Independent-Groups Designs Graziano and Raulin Research Methods: Chapter 10 This multimedia product and.
2 factor ANOVA. Drug ADrug BDrug C High doseSample 1Sample 2Sample 3 Low doseSample 4Sample 5Sample 6 2 X 3 Dose by drug (row by column)
2  How to compare the difference on >2 groups on one or more variables  If it is only one variable, we could compare three groups with multiple ttests:
Chapter Fourteen The Two-Way Analysis of Variance.
Spatial and temporal distribution of petroleum hydrocarbons in wild mussels in Galicia after the Prestige oil spill L. VIÑAS, M.A. FRANCO, J.A. SORIANO.
Variations in the V and Ni content in mussels after the Prestige spill VERTIMAR-2005 SYMPOSIUM ON MARINE ACCIDENTAL OIL SPILLS Vigo, Spain, July.
LEVELS OF NICKEL AND VANADIUM IN SEAWATER FROM AREAS AFFECTED BY THE PRESTIGE SHIPWRECK ONE YEAR AFTER THE DISASTER Juan Santos Echeandía, Ricardo Prego.
Sample Selection Issues in Experiment Random sampling (difficult) Convenience & purposive sampling Volunteers External validity Representativeness & generalizability.
Effects of Prestige fuel oil ingestion on growth of juvenile turbot (Scophtalmus maximus) Rosario Domínguez Petit Instituto de Investigaciones Marinas,
Analysis of Variance. Experimental Design u Investigator controls one or more independent variables –Called treatment variables or factors –Contain two.
Chapter 10 - Part 1 Factorial Experiments.
Biol 500: basic statistics
Comparing Several Means: One-way ANOVA Lesson 14.
Experimental Research
Pathogens  Microorganisms causing diseases  eg. bacteria viruses fungi protozoa.
Analysis of Variance Introduction The Analysis of Variance is abbreviated as ANOVA The Analysis of Variance is abbreviated as ANOVA Used for hypothesis.
Understanding the Two-Way Analysis of Variance
Chapter 12 Inferential Statistics Gay, Mills, and Airasian
Inferential statistics Hypothesis testing. Questions statistics can help us answer Is the mean score (or variance) for a given population different from.
To state another function of the circulatory system To identify the three lines of defence mechanism To describe phagocytosis To state the meaning of.
Chapter 12: Analysis of Variance
Analysis of Variance. ANOVA Probably the most popular analysis in psychology Why? Ease of implementation Allows for analysis of several groups at once.
Integration of chemical and biological measurements in mussels, passive samplers and sediments to investigate the effects of chemical pollution in ports.
Chapter 14: Repeated-Measures Analysis of Variance.
Which Test Do I Use? Statistics for Two Group Experiments The Chi Square Test The t Test Analyzing Multiple Groups and Factorial Experiments Analysis of.
Chapter 11 HYPOTHESIS TESTING USING THE ONE-WAY ANALYSIS OF VARIANCE.
Comparing Several Means: One-way ANOVA Lesson 15.
Statistical Analysis. Statistics u Description –Describes the data –Mean –Median –Mode u Inferential –Allows prediction from the sample to the population.
Educational Research: Competencies for Analysis and Application, 9 th edition. Gay, Mills, & Airasian © 2009 Pearson Education, Inc. All rights reserved.
1 Chapter 13 Analysis of Variance. 2 Chapter Outline  An introduction to experimental design and analysis of variance  Analysis of Variance and the.
Parametric tests (independent t- test and paired t-test & ANOVA) Dr. Omar Al Jadaan.
ITEC6310 Research Methods in Information Technology Instructor: Prof. Z. Yang Course Website: c6310.htm Office:
Chapter 17 Comparing Multiple Population Means: One-factor ANOVA.
Experimental Research Methods in Language Learning
Chapter Seventeen. Figure 17.1 Relationship of Hypothesis Testing Related to Differences to the Previous Chapter and the Marketing Research Process Focus.
Inferential Statistics. The Logic of Inferential Statistics Makes inferences about a population from a sample Makes inferences about a population from.
ETM U 1 Analysis of Variance (ANOVA) Suppose we want to compare more than two means? For example, suppose a manufacturer of paper used for grocery.
Repeated Measures Analysis of Variance Analysis of Variance (ANOVA) is used to compare more than 2 treatment means. Repeated measures is analogous to.
Chapter 11.  The general plan for carrying out a study where the independent variable is changed  Determines the internal validity  Should provide.
IE241: Introduction to Design of Experiments. Last term we talked about testing the difference between two independent means. For means from a normal.
One-Way Analysis of Variance Recapitulation Recapitulation 1. Comparing differences among three or more subsamples requires a different statistical test.
Pathogens  Microorganisms causing diseases  eg. bacteria viruses fungi protozoa.
1 Chapter 14: Repeated-Measures Analysis of Variance.
Research Methods and Data Analysis in Psychology Spring 2015 Kyle Stephenson.
ANOVA Overview of Major Designs. Between or Within Subjects Between-subjects (completely randomized) designs –Subjects are nested within treatment conditions.
© 2006 by The McGraw-Hill Companies, Inc. All rights reserved. 1 Chapter 11 Testing for Differences Differences betweens groups or categories of the independent.
Chapter Pgs This is challenging material!!! *Don’t think black & white: There are always exceptions… Objective: I can describe the basic.
Educational Research Inferential Statistics Chapter th Chapter 12- 8th Gay and Airasian.
Engineering Statistics Design of Engineering Experiments.
Experimental Designs The objective of Experimental design is to reduce the magnitude of random error resulting in more powerful tests to detect experimental.
Immune System Section 1: Infectious Diseases
Pathogens Cause Infectious Disease
Factorial ANOVA.
Between-Subjects, within-subjects, and factorial Experimental Designs
Statistical Reporting Format
Single-Variable, Independent-Groups Designs
Chapter 10: Analysis of Variance: Comparing More Than Two Means
Two Way ANOVAs Factorial Designs.
2 independent Groups Graziano & Raulin (1997).
PARAMETRIC TESTS t-tests (parametric, interval and ratio data)
Randomized Complete Block and Repeated Measures (Each Subject Receives Each Treatment) Designs KNNL – Chapters 21,
Chapter 9: Differences among Groups
Chapter 13: Repeated-Measures Analysis of Variance
Experiments with More Than Two Groups
Chapter 10 – Part II Analysis of Variance
CLASS 6 CLASS 7 Tutorial 2 (EXCEL version)
One way Analysis of Variance (ANOVA)
Presentation transcript:

Immune parametres of mussels treated with Prestige fuel oil M. Camino Ordás, Joan Albaiges, Josep M. Bayona, Amando Ordás and Antonio Figueras Instituto de Investigaciones Marinas (Vigo) Centro de Investigación y Desarrollo (Barcelona) Misión Biológica de Galicia (Pontevedra)

Inespecific system  no antibody production Cellular defenseHumoral defense Phagocytosis Respiratory burst NO production Lysozyme Lectins Prophenoloxidase SERUM SOLUBLE FACTORSHEMOCYTES External barriers Hemocytic infiltration Immune system of bivalve molluscs

contaminants depression in immune system infection by pathogens MORTALITY important economical losses in Galicia, one of the main Mediterranean mussel producers worldwide To assess the influence of the Prestige fuel oil on the immune response of Mediterranean mussel. Objective of this work

contaminants depression in immune system infection by pathogens MORTALITY important economical losses in Galicia, one of the main Mediterranean mussel producers worldwide To assess the influence of the Prestige fuel oil on the immune response of Mediterranean mussel. Objective of this work

contaminants depression in immune system infection by pathogens MORTALITY important economical losses in Galicia, one of the main Mediterranean mussel producers worldwide To assess the influence of the Prestige fuel oil on the immune response of Mediterranean mussel. Objective of this work

contaminants depression in immune system infection by pathogens MORTALITY important economical losses in Galicia, one of the main Mediterranean mussel producers worldwide To assess the influence of the Prestige fuel oil on the immune response of Mediterranean mussel. Objective of this work

contaminants depression in immune system infection by pathogens MORTALITY important economical losses in Galicia, one of the main Mediterranean mussel producers worldwide To assess the influence of the Prestige fuel oil on the immune response of Mediterranean mussel. Objective of this work

Methodology +1 kg fuel+2 kg fuel control Monthly sampling during four months Histology. Immune parametres: Cellular: hemocyte viability, phagocytosis, NO production, chemiluminescence (CL). Humoral: protein concentration and lysozime activity. PAH concentration in water and mussel tissue (gills and digestive gland). tank 1tank 2tank 3

Results - No granulocytomes or neoplasia - Mytilicola in 68% of sampled animals 1. HISTOLOGY

2. IMMUNE PARAMETRES df Viab.Phagoc. CL NOProteinLisoz. Month (M) ** ** ** ** Treatment (T) * *54.98 ** M  T ** ** * * Error Mean squares (34 factorial ANOVA): No significant differences in phagocytic activity and significant differences in protein concentration. Remaining parametres: interaction between month and treatment.

2.2. One way ANOVA (without taking into account the sampling month): significant differences in protein concentration and lysozyme activity Least square means: TreatmentViab.Phagoc.CLNOProteinLysoz. 2 kg0.220a11.080a0.015a52.770a0.242a7.507ab 1 kg0.219a13.890a0.013a50.120a0.283ab9.636a 0 kg0.236a19.108a0.010a61.200a0.381b5.943b Means followed by the same letter in a column are not statistically different according to the Waller-Duncan k- ratio t Test.

3. PAH CONCENTRATION Prestige fuel oil Similar methylphenantrene profiles in mussel organs and Prestige fuel oil  real exposure to the fuel.

TPAH gill TPAH dig. gland Higher TPAH concentration (ng/ g) in digestive gland than in gill. Low TPAH conc. in control mussels. Excepting gill from the first month, organs treated with 2 kg of fuel show higher TPAH conc. than 1 kg- treated ones.

REGRESSION PROCEDURE: Model: [contam]= 0 +  1  MONTH +  2  TREATMENT Number of PAHs depending on each independent variable: ^ For comparisons between [PAH] and immune parametres, it would be more appropriate to use data from digestive gland, since [PAH] in gill is independent of our experimental design. Comparison between gland [PAH] and immune data (difficult due to the experimental design). Future analysis

Muchas gracias