| 1. |
- Günther, Juliane, et al.
(författare)
-
Assessment of the immune capacity of mammary epithelial cells : comparison with mammary tissue after challenge with Escherichia coli
- 2009
-
Ingår i: Veterinary research (Print). - Les Ulis Cedex A, France : EDP Sciences. - 0928-4249 .- 1297-9716. ; 40:4
-
Tidskriftsartikel (refereegranskat)abstract
- We examined the repertoire and extent of inflammation dependent gene regulation in a bovine mammary epithelial cell (MEC) model, to better understand the contribution of the MEC in the immune defence of the udder. We challenged primary cultures of MEC from cows with heat inactivated Escherichia coli pathogens and used Affymetrix DNA-microarrays to profile challenge related alterations in their transcriptome. Compared to acute mastitis, the most prominently activated genes comprise those encoding chemokines, interleukins, beta-defensins, serum amyloid A and haptoglobin. Hence, the MEC exert sentinel as well as effector functions of innate immune defence. E. coli stimulated a larger fraction of genes (30%) in the MEC belonging to the functional category Inflammatory Response than we recorded with the same microarrays during acute mastitis in the udder (17%). This observation underscores the exquisite immune capacity of MEC. To more closely examine the adequacy of immunological regulation in MEC, we compared the inflammation dependent regulation of factors contributing to the complement system between the udder versus the MEC. In the MEC we observed only up regulation of several complement factor-encoding genes. Mastitis, in contrast, in the udder strongly down regulates such genes encoding factors contributing to both, the classical pathway of complement activation and the Membrane Attack Complex, while the expression of factors contributing to the alternative pathway may be enhanced. This functionally polarized regulation of the complex complement pathway is not reflected in the MEC models.
|
|
| 2. |
- Graunke, Katharina L, et al.
(författare)
-
Describing temperament in an ungulate : a multidimensional approach
- 2013
-
Ingår i: PLOS ONE. - San Fransisco, USA : Public library science. - 1932-6203. ; 8:9
-
Tidskriftsartikel (refereegranskat)abstract
- Studies on animal temperament have often described temperament using a one-dimensional scale, whereas theoretical framework has recently suggested two or more dimensions using terms like "valence" or "arousal" to describe these dimensions. Yet, the valence or assessment of a situation is highly individual. The aim of this study was to provide support for the multidimensional framework with experimental data originating from an economically important species (Bos taurus). We tested 361 calves at 90 days post natum (dpn) in a novel-object test. Using a principal component analysis (PCA), we condensed numerous behaviours into fewer variables to describe temperament and correlated these variables with simultaneously measured heart rate variability (HRV) data. The PCA resulted in two behavioural dimensions (principal components, PC): novel-object-related (PC 1) and exploration-activity-related (PC 2). These PCs explained 58% of the variability in our data. The animals were distributed evenly within the two behavioural dimensions independent of their sex. Calves with different scores in these PCs differed significantly in HRV, and thus in the autonomous nervous system's activity. Based on these combined behavioural and physiological data we described four distinct temperament types resulting from two behavioural dimensions: "neophobic/fearful--alert", "interested--stressed", "subdued/uninterested--calm", and "neoophilic/outgoing--alert". Additionally, 38 calves were tested at 90 and 197 dpn. Using the same PCA-model, they correlated significantly in PC 1 and tended to correlate in PC 2 between the two test ages. Of these calves, 42% expressed a similar behaviour pattern in both dimensions and 47% in one. No differences in temperament scores were found between sexes or breeds. In conclusion, we described distinct temperament types in calves based on behavioural and physiological measures emphasising the benefits of a multidimensional approach.
|
|
| 3. |
|
|
| 4. |
- Hartmann, Anja, et al.
(författare)
-
Effects of threshold choice on the results of gene expression profiling, using microarray analysis, in a model feeding experiment with rat
- 2009
-
Ingår i: Archiv für Tierzucht. - Dummerstorf, Germany : Research Institute for the Biology of Farm Animals (FBN). - 0003-9438. ; 52:1, s. 65-78
-
Tidskriftsartikel (refereegranskat)abstract
- Global gene expression studies using microarray technology are widely employed to identify biological processes which are influenced by a treatment e.g. a specific diet. Affected processes are characterized by a significant enrichment of differentially expressed genes (functional annotation analysis). However, different choices of statistical thresholds to select candidates for differential expression will alter the resulting candidates list. This study was conducted to investigate the effect of applying a False Discovery Rate (FDR) correction and different fold change thresholds in statistical analysis of microarray data on diet-affected biological processes based on a significantly increased proportion of differentially expressed genes. In a model feeding experiment with rats fed genetically modified food additives, animals received a supplement of either lyophilized inactivated recombinant VP60 baculovirus (rBV-VP60) or lyophilized inactivated wild type baculovirus (wtBV). Comparative expression profiling was done in spleen, liver and small intestine mucosa. We demonstrated the extent to which threshold choice can affect the biological processes identified as significantly regulated and thus the conclusion drawn from the microarray data. In our study, the combined application of a moderate fold change threshold (FC≥1.5) and a stringent FDR threshold (q≤0.05) exhibited high reliability of biological processes identified as differentially regulated. The application of a stringent FDR threshold of q≤0.05 seems to be an essential prerequisite to reduce considerably the number of false positives. Microarray results of selected differentially expressed molecules were validated successfully by using real-time RT-PCR.
|
|
| 5. |
|
|
| 6. |
- Telaar, Anna, et al.
(författare)
-
An extension of PPLS-DA for classification and comparison to ordinary PLS-DA
- 2013
-
Ingår i: PLOS ONE. - San Fransisco, USA : Public Library Science. - 1932-6203. ; 8:2
-
Tidskriftsartikel (refereegranskat)abstract
- Classification studies are widely applied, e.g. in biomedical research to classify objects/patients into predefined groups. The goal is to find a classification function/rule which assigns each object/patient to a unique group with the greatest possible accuracy (classification error). Especially in gene expression experiments often a lot of variables (genes) are measured for only few objects/patients. A suitable approach is the well-known method PLS-DA, which searches for a transformation to a lower dimensional space. Resulting new components are linear combinations of the original variables. An advancement of PLS-DA leads to PPLS-DA, introducing a so called 'power parameter', which is maximized towards the correlation between the components and the group-membership. We introduce an extension of PPLS-DA for optimizing this power parameter towards the final aim, namely towards a minimal classification error. We compare this new extension with the original PPLS-DA and also with the ordinary PLS-DA using simulated and experimental datasets. For the investigated data sets with weak linear dependency between features/variables, no improvement is shown for PPLS-DA and for the extensions compared to PLS-DA. A very weak linear dependency, a low proportion of differentially expressed genes for simulated data, does not lead to an improvement of PPLS-DA over PLS-DA, but our extension shows a lower prediction error. On the contrary, for the data set with strong between-feature collinearity and a low proportion of differentially expressed genes and a large total number of genes, the prediction error of PPLS-DA and the extensions is clearly lower than for PLS-DA. Moreover we compare these prediction results with results of support vector machines with linear kernel and linear discriminant analysis.
|
|
| 7. |
- Telaar, Anna, et al.
(författare)
-
Biomarker discovery : classification using pooled samples
- 2013
-
Ingår i: Computational statistics (Zeitschrift). - Heidelberg, Germany : Springer. - 0943-4062 .- 1613-9658. ; 28:1, s. 67-106
-
Tidskriftsartikel (refereegranskat)abstract
- RNA-sample pooling is sometimes inevitable, but should be avoided in classification tasks like biomarker studies. Our simulation framework investigates a two-class classification study based on gene expression profiles to point out howstrong the outcomes of single sample designs differ to those of pooling designs. The results show how the effects of pooling depend on pool size, discriminating pattern, number of informative features and the statistical learning method used (support vector machines with linear and radial kernel, random forest (RF), linear discriminant analysis, powered partial least squares discriminant analysis (PPLS-DA) and partial least squares discriminant analysis (PLS-DA)). As a measure for the pooling effect, we consider prediction error (PE) and the coincidence of important feature sets for classification based on PLS-DA, PPLS-DAand RF. In general, PPLS-DAand PLS-DAshow constant PE with increasing pool size and low PE for patterns for which the convex hull of one class is not a cover of the other class. The coincidence of important feature sets is larger for PLS-DA and PPLS-DA as it is for RF. RF shows the best results for patterns in which the convex hull of one class is a cover of the other class, but these depend strongly on the pool size. We complete the PE results with experimental data whichwe pool artificially. The PE of PPLS-DAand PLS-DAare again least influenced by pooling and are low. Additionally, we show under which assumption the PLS-DA loading weights, as a measure for importance of features regarding classification, are equal for the different designs.
|
|
| 8. |
- Telaar, Anna, et al.
(författare)
-
Finding biomarker signatures in pooled sample designs : a simulation framework for methodological comparisons
- 2010
-
Ingår i: Advances in Bioinformatics. - USA : Hindawi Publishing Corporation. - 1687-8027 .- 1687-8035.
-
Tidskriftsartikel (refereegranskat)abstract
- Detection of discriminating patterns in gene expression data can be accomplished by using various methods of statistical learning. It has been proposed that sample pooling in this context would have negative effects; however, pooling cannot always be avoided. We propose a simulation framework to explicitly investigate the parameters of patterns, experimental design, noise, and choice of method in order to find out which effects on classification performance are to be expected. We use a two-group classification task and simulated gene expression data with independent differentially expressed genes as well as bivariate linear patterns and the combination of both. Our results show a clear increase of prediction error with pool size. For pooled training sets powered partial least squares discriminant analysis outperforms discriminance analysis, random forests, and support vector machines with linear or radial kernel for two of three simulated scenarios. The proposed simulation approach can be implemented to systematically investigate a number of additional scenarios of practical interest.
|
|
| 9. |
- Telaar, Anna, et al.
(författare)
-
Finding biomarkers in pooled samples
- 2010
-
Ingår i: 11th Day of the Doctoral Student FBN Dummerstorf. - Dummerstorf, Germany : FBN. ; , s. 11-14
-
Konferensbidrag (refereegranskat)
|
|
| 10. |
|
|
| 11. |
- Waelbroeck, Claire, et al.
(författare)
-
Consistently dated Atlantic sediment cores over the last 40 thousand years
- 2019
-
Ingår i: Scientific Data. - : NATURE PUBLISHING GROUP. - 2052-4463. ; 6
-
Tidskriftsartikel (refereegranskat)abstract
- Rapid changes in ocean circulation and climate have been observed in marine-sediment and ice cores over the last glacial period and deglaciation, highlighting the non-linear character of the climate system and underlining the possibility of rapid climate shifts in response to anthropogenic greenhouse gas forcing. To date, these rapid changes in climate and ocean circulation are still not fully explained. One obstacle hindering progress in our understanding of the interactions between past ocean circulation and climate changes is the difficulty of accurately dating marine cores. Here, we present a set of 92 marine sediment cores from the Atlantic Ocean for which we have established age-depth models that are consistent with the Greenland GICC05 ice core chronology, and computed the associated dating uncertainties, using a new deposition modeling technique. This is the first set of consistently dated marine sediment cores enabling paleoclimate scientists to evaluate leads/lags between circulation and climate changes over vast regions of the Atlantic Ocean. Moreover, this data set is of direct use in paleoclimate modeling studies.
|
|
