| 1. |
- Danielsson, Frida, et al.
(författare)
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Majority of differentially expressed genes are down-regulated during malignant transformation in a four-stage model
- 2013
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 110:17, s. 6853-6858
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Tidskriftsartikel (refereegranskat)abstract
- The transformation of normal cells to malignant, metastatic tumor cells is a multistep process caused by the sequential acquirement of genetic changes. To identify these changes, we compared the transcriptomes and levels and distribution of proteins in a four-stage cell model of isogenically matched normal, immortalized, transformed, and metastatic human cells, using deep transcriptome sequencing and immunofluorescence microscopy. The data show that similar to 6% (n = 1,357) of the human protein-coding genes are differentially expressed across the stages in the model. Interestingly, the majority of these genes are down-regulated, linking malignant transformation to dedifferentiation. The up-regulated genes are mainly components that control cellular proliferation, whereas the down-regulated genes consist of proteins exposed on or secreted from the cell surface. As many of the identified gene products control basic cellular functions that are defective in cancers, the data provide candidates for follow-up studies to investigate their functional roles in tumor formation. When we further compared the expression levels of four of the identified proteins in clinical cancer cohorts, similar differences were observed between benign and cancer cells, as in the cell model. This shows that this comprehensive demonstration of the molecular changes underlying malignant transformation is a relevant model to study the process of tumor formation.
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| 2. |
- Söder, Carl-Johan, et al.
(författare)
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Parametric roll mitigation using rudder control
- 2013
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Ingår i: Journal of Marine Science and Technology. - : Springer Science and Business Media LLC. - 0948-4280 .- 1437-8213. ; 18:3, s. 395-403
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Tidskriftsartikel (refereegranskat)abstract
- Severe roll angles can be developed by parametric excitation in relatively moderate weather without any apparent pre-warning for the crew onboard. In this study the prospect of using rudder control to mitigate parametric roll was investigated using multi-degree of freedom simulations. A typical modern Pure Car and Truck Carrier was considered and modelled by coupling a roll model with a planar motion manoeuvring model. The combined model was calibrated using in-service, full-scale trials and model tests. Irregular variations of the metacentric height were applied to simulate recorded, full-scale events of parametric roll that have occurred with the considered design. These simulations with rudder roll control showed promising results and demonstrate that the approach could be very efficient for mitigation of parametric roll.
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| 3. |
- Zhao, Jing, et al.
(författare)
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The Network Organization of Cancer-associated Protein Complexes in Human Tissues
- 2013
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 3
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Tidskriftsartikel (refereegranskat)abstract
- Differential gene expression profiles for detecting disease genes have been studied intensively in systems biology. However, it is known that various biological functions achieved by proteins follow from the ability of the protein to form complexes by physically binding to each other. In other words, the functional units are often protein complexes rather than individual proteins. Thus, we seek to replace the perspective of disease-related genes by disease-related complexes, exemplifying with data on 39 human solid tissue cancers and their original normal tissues. To obtain the differential abundance levels of protein complexes, we apply an optimization algorithm to genome-wide differential expression data. From the differential abundance of complexes, we extract tissue- and cancer-selective complexes, and investigate their relevance to cancer. The method is supported by a clustering tendency of bipartite cancer-complex relationships, as well as a more concrete and realistic approach to disease-related proteomics.
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