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Clusters seem to not only contribute directly to productivity of the nation as a whole but seem to have a positive effect on other clusters. Yet there has been no research made by researchers that look into the development of business models or joint value propositions made by a cluster as a whole. The authors have failed to identify any common view on the research field today of just how a business model for an industrial logistic cluster should look like as well as what components are essential and must be included. Therefore, the purpose of our research was to explore the contextual conditions for developing BM for industrial cluster in the logistic area.  In order to reach the goal of our research, inductive based approach was used when trying to investigate a cluster in Halmstad called “Innovative Logistic in Halmstad”. The cluster is in a early stage at this moment. Data was collected through interviews and secondary data was collected to complement our findings as well.  The main findings of our study are as follows. The authors create a conceptual business model for industrial cluster in the logistic area. We also offer a value package proposal where the cluster offer a client a joint value proposition as the main majority of companies buy their logistic transports. This could result in e.g. more eco-driven means of transportation.

Finding the approximate location of short read genome sequences by comparing them to an already available closely related organism's complete genome sequence is a challenging research issue. Predicting intron locations in the short form of mRNA called Expressed Sequence Tags (ESTs) and the variability of intron lengths are the major challenges. More specifically, finding the intron positions in an EST sequence by comparing it with a reference genome sequence is a time consuming task, as currently it is done manually. In my thesis, I designed a pipeline that can predict the intron positions in ESTs of non-model organisms. Initially, I compared the ESTs to the closest completely sequenced genome. The pipeline then finds the alignment of the ESTs, the reference genome sequence, and the coding region of the gene (known as Coding DNA Sequence or CDS) from the reference genome.

Previously, we have demonstrated that a DNA helicase-like protein, termed RTEL (regulator of telomere length) is essential for the maintenance of genomic stability. RTEL deficiency induced telomere loss and genomic instability, leading to embryonic lethality. However, the role of RTEL in these biological pathways is largely unknown. To uncover RTEL’s function(s), we applied several approaches to identify the proteins that could interact with RTEL. Proliferating Cell Nuclear Antigen (PCNA), the key regulator of the replication fork, was found to be a strong candidate. In this study, we have demonstrated the interaction between RTEL and PCNA. Further characterization of the interaction between RTEL and PCNA revealed that the interaction is important for maintaining genomic stability. Due to the essential role of PCNA in nucleic acid metabolism as a component of the replication and repair machinery, its interaction with RTEL could be the key to the role of RTEL in the maintenance of genomic stability and mouse development. Along with a bioinformatics approach, we have employed several biochemical approaches to identify the interaction of PCNA with RTEL. Using co-immunoprecipitation, we have demonstrated that RTEL can specifically interact with PCNA. A PCR-based mutagenesis method was used to mutate the PCNA-interacting motif (PIP) in RTEL. Further we have demonstrated that several key amino acids in the PIP motif are responsible for mediating RTEL/PCNA interaction by using co-immunoprecipitation and immunofluorescence studies. Using a gene-targeting approach, we have specifically knocked-in a mutant RTEL with a mutation in PIP motif into mouse genome. Thus we have developed a transgenic mouse model to study the significance of the interaction between RTEL/PCNA in vivo. This study not only validated the interaction of RTEL with PCNA, via the PIP box, but also generated the RTEL PIP mutant alleles for further functional analysis by transgenic approaches. We have employed biochemical and cytogenetic studies to characterize the phenotypes in RtelI1169A/I1169A mouse. This is the first direct genetic approach to address whether PCNA is an important downstream mediator of RTEL’s function in the regulation of genomic integrity

Helicase-like Transcription Factor (HLTF) is a DNA helicase protein which is homologous to SNF/SWI family. It has been demonstrated to be a functional homolog of yeast Rad5, required for the maintenance of genomic stability. Although the physiologic role of HLTF is largely unknown,inactivation of HLTF by promoter hypermethylation has been found in more than 40% human colon cancers. In this study, we have applied mouse transgenic approaches to determine whether loss of HLTF function could be important for colorectal carcinogenesis. HLTF knockout mice were generated by the deletion of first 5 exons of the HLTF gene. The complete loss of HLTF expression in HLTF -/- mice was confirmed by northern blot and real time RT-PCR assays. HLTF -/- mice did not show any developmental defects within a 2-year observation indicating that HLTF is dispensable for mouse development. Furthermore, HLTF -/- mice were free of intestinal or colorectal tumors or other types of tumors, suggesting that loss of HLTF function alone is not sufficient to drive oncogenic transformation in intestinal track and other tissues. To determine whether loss of HLTF function could cooperate with other tumor suppressors in the formation of colorectal cancers, we have bred HLTF knockout mice with the mutant mice for APC (adenomtous polyposis coli) and P53. In HLTF -/-APC Min/+ mice, a significantly increased formation of intestinal adenocarcinoma and colorectal cancers were observed. Although very few HLTF -/-P53 -/- mice developed colorectal cancers, these mice had increased incidence of the formation of metastatic lymphomas. Cytogenetic analysis of colorectal cancer cells derived from HLTF -/-APC Min/+ mice demonstrated a high incidence of gross chromosomal instabilities, including Robertsonian fusions, fragments and aneuploidy. All these genetic alterations were not observed in the intestinal tumor cells from APC Min/+, implicating that loss of HLTF function could induce genomic instability which contributes to intestinal carcinogenesis. To further investigate the role of HLTF in colorectal carcinogenesis, we have also applied a shRNA knockdown approach to down-regulate HLTF expression in human HCT-116 colon cancer cells. HCT-116 cells highly express HLTF and show less chromosomal instability, making these cells as a very useful model to investigate the loss of function of HLTF in human colorectal carcinogenesis. Using Western blot approach, we confirmed that HLTF knockdown HCT-116 cells had less than 5% of HLTF expression as compared to the scramble controls. By inoculating HLTF knockdown HCT-116 cells to Rag1 -/-IL2 -/- immunocompromised mice, we further demonstrated that HLTF knockdown promote tumor growth and invasion. Moreover, spectral karyotyping analysis revealed that HLTF knockdown human colon cancer cells had significantly increased chromosomal instability, including both aneuploidy and chromosomal translocation. Taken together, our work strongly indicates that loss of HLTF function can promote the malignant transformation of intestinal or colonic adenomas to carcinomas by inducing genomic instability. Given the high frequency of epigenetic inactivation by hypermethylation of HLTF in human colon cancers, our studies strongly suggest that this epigenetic alteration could be directly involved in the development of colorectal cancer rather than a consequence of this carcinogenesis.

Background: Longitudinal studies enable the study of within person change over time in addition to between person differences. In longitudinal studies of older adult populations even when not the question of interest, identifying participants with dementia is desirable, and often necessary. Yet in practice, the time to collect information from each participant may be limited. Therefore, some studies include only a brief general cognitive measure of which the Mini Mental State Examination (MMSE) is the most commonly used (Raina et al., 2009). The current study explores whether group-based trajectory modeling of MMSE scores with a selection of covariates can identify individuals who have or will develop dementia in an 8 year longitudinal study. Methods: The sample included 651 individuals from the Origins of Variance in the Oldest Old study of Swedish twins 80 years old or older (OCTO-Twin). Participants had completed the MMSE every two years, and cases of dementia were diagnosed according to DSM-III criteria. The accuracy of using the classes formed in growth mixture modeling and latent class growth modeling as indicative of dementia status was compared to that of more standard methods, the typical 24/30 cut score and a logistic regression. Results: A three-class quadratic model with covariate effects on class membership was found to best characterize the data. The classes were characterized as High Performing Late Decline, Rapidly Declining, and Decreasing Low Performance, and were labeled as such. Comparing the diagnostic accuracy of the latent trajectory groups against simple methods; the sensitivity of the final model was lower but it was the same or superior in specificity, positive predictive value, negative predictive value, and allowed a more fine-grained analysis of participant risk. Conclusions: Group-based trajectory models may be helpful for grouping longitudinal study participants, particularly if sensitivity is not the primary concern. / Graduate

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