Frågeställningar i examensarbeten

För att klara examinationsmålen i civilingenjörsexamen (SFS 1993:100 bilaga 2) ska varje student visa förmåga att med helhetssyn kritiskt, självständigt och kreativt identifiera, formulera och hantera komplexa frågeställningar. För att öka förståelsen för hur forskningsfrågan identifieras, formuleras och hanteras vid LTH har ett tjugotal examensarbetsrapporter från olika institutioner granskats. Granskningen har utgått från rapporternas inledande och avslutande kapitel för att se om forskningsfrågan tydligt formuleras i inledningen och om den besvaras i slutsatserna. Utifrån det material vi har studerat och publicerad litteratur kan vi konstatera att det är ett allmänt problem att studenter på masters-nivå överlag har liten vana vid att hantera komplexa frågeställningar. Det tycks finnas bristande kunskaper om vad vetenskaplighet/vetenskaplig metodik/vetenskaplig tradition innebär för vad som ska presenteras och vi kan konstatera att det både på LTH och i stort finns ett behov för åtgärder för att på ett mer effektiv sätt träna studenter i detta. Att litteraturen inom detta område är begränsad visar på både behovet men kanske också svårigheter att identifiera precis hur detta kan göras. Vi identifierade detta som ett viktigt utvecklingsområde för handledare av examensarbeten inom civilingenjörsutbildningarna på LTH, som dock också kan komma att behöva stöd av nya strukturer och systematiska åtgärder för att nå gemensamma mål för hela fakulteten

Proteomic analysis of breast tumors confirms the mRNA intrinsic molecular subtypes using different classifiers: a large-scale analysis of fresh frozen tissue samples

Background: Breast cancer is a complex and heterogeneous disease that is usually characterized by histological parameters such as tumor size, cellular arrangements/rearrangments, necrosis, nuclear grade and the mitotic index, leading to a set of around twenty subtypes. Together with clinical markers such as hormone receptor status, this classification has considerable prognostic value but there is a large variation in patient response to therapy. Gene expression profiling has provided molecular profiles characteristic of distinct subtypes of breast cancer that reflect the divergent cellular origins and degree of progression.Methods: Here we present a large-scale proteomic and transcriptomic profiling study of 477 sporadic and hereditary breast cancer tumors with matching mRNA expression analysis. Unsupervised hierarchal clustering was performed and selected proteins from large-scale tandem mass spectrometry (MS/MS) analysis were transferred into a highly multiplexed targeted selected reaction monitoring assay to classify tumors using a hierarchal cluster and support vector machine with leave one out cross-validation.Results: The subgroups formed upon unsupervised clustering agree very well with groups found at transcriptional level; however, the classifiers (genes or their respective protein products) differ almost entirely between the two datasets. In-depth analysis shows clear differences in pathways unique to each type, which may lie behind their different clinical outcomes. Targeted mass spectrometry analysis and supervised clustering correlate very well with subgroups determined by RNA classification and show convincing agreement with clinical parameters.Conclusions: This work demonstrates the merits of protein expression profiling for breast cancer stratification. These findings have important implications for the use of genomics and expression analysis for the prediction of protein expression, such as receptor status and drug target expression. The highly multiplexed MS assay is easily implemented in standard clinical chemistry practice, allowing rapid and cheap characterization of tumor tissue suitable for directing the choice of treatment

Profiling the cancer proteome

Cancer is a complex and heterogeneous disease where cells have started to grow uncontrolled and this disease remains a major health problem. Because of diffuse symptoms it often presents at a late stage. Insufficient understanding of the different phenotypes hinders the development of targeted therapeutics and consequently patients show a diverse range of responses to a given treatment. This thesis is based on four original papers where mass spectrometry based proteomics has been used to study three different cancers; breast, ovarian and prostate cancer. Two-dimensional gel electrophoresis and shotgun proteomics LC-MS/MS based analysis has been applied. Ovarian cancers often have a bad prognosis because of late presentation. Diagnostic markers for early detection are urgently needed. Two studies in this thesis analysed ovarian cancer tumours for this purpose. Protein expression profiles from 2D-DIGE could separate the tumour subgroups and proteins differentially expressed with increased malignancy were identified. A more in-depth characterisation of benign and malignant samples was done using a shotgun proteomics approach and iTRAQ for quantitation. Breast cancer consists of several pathological subtypes with different clinical presentations and outcomes. Using 2D-DIGE protein expression profiles were constructed for tumours previously analysed for gene expression to stratify these tumours. The subgroups found agree very well with groups found on transcriptional level and these correlate well with clinical information. Proteins characterising these subgroups could be useful as prognostic markers in the clinic. Somatostatin can potentially inhibit tumour growth in advance stage hormone refractory prostate cancer. A derivative of somatostatin that increases its half-life is interesting as a potential treatment. The effect of somatostatin and its derivative was studied in a prostate cancer cell line using 2DE. Differentially expressed proteins were identified. Somatostatin and its derivative were shown to exert the same effect on the cell line pointing at the derivate as a potential treatment

Pedagogers val av metod vid tidig läsinlärning

Syftet med detta arbete är att få en ökad insikt om vilka arbetsmetoder pedagoger väljer att använda sig av när de arbetar med den tidiga läsinlärningen. Jag har velat ta reda på om pedagoger väljer att kombinera två skilda metoder såsom analytisk och syntetisk arbetsmetod. Analytisk arbetsmetod innebär att läsinlärningen utgår från en helhet för att sedan analysera delarna. En syntetisk arbetsmetod innebär att läsinlärningen utgår från olika delar för att sedan fogas samman till en helhet. Jag vill få en djupare kunskap om hur de pedagoger som medverkar i min undersökning ser på sina egna läsinlärningsmetoder. Använder de sig konsekvent av en särskild arbetsmetod eller är pedagogerna flexibla och kombinerar två skilda arbetsmetoder för att tillgodose läroplanens mål om en individanpassad undervisning? För att kunna ta del av lärarnas uppfattningar har jag gjort intervjuer på två olika skolor. Slutsatserna från intervjuerna diskuteras och analyseras med hjälp av styrdokumenten samt relevant litteratur. Resultaten kan sammanfattas med att de flesta pedagoger har en pragmatisk syn på vilka arbetsmetoder som bör användas

Automated PreScan function for scanning fluorescently stained 2D-PAGE gels

To automate the acquisition of images from fluorescently stained gels, the power of the excitation laser(s) must be optimized for each sample to prevent spot saturation (or to allow unimportant spots to saturate) yet still retaining sensitivity. In this work, we describe the implementation and effectiveness of a pre-scan function in a robotic solution for the automation of 2D gel scanning

Automated quality control system for LC-SRM setups.

Selected reaction monitoring (SRM) is emerging as a standard tool for high-throughput protein quantification. For reliable and reproducible SRM protein quantification it is essential that system performance is stable. We present here a quality control workflow that is based on repeated analysis of a standard sample to allow insight into the stability of the key properties of a SRM setup. This is supported by automated software to monitor system performance and display information like signal intensities and retention time stability over time, and alert upon deviations from expected metrics. Utilising the software to evaluate 407 repeated injections of a standard sample during half a year, outliers in relative peptide signal intensities and relative peptide fragment ratios are identified, indicating the need for instrument maintenance. We therefore believe that the software could be a vital and powerful tool for any lab regularly performing SRM, increasing the reliability and quality of the SRM platform. BIOLOGICAL SIGNIFICANCE: Selected reaction monitoring (SRM) mass spectrometry is becoming established as a standard technique for accurate protein quantification. However, to achieve the required quantification reproducibility of the liquid chromatography (LC)-SRM setup, system performance needs to be monitored over time. Here we introduce a workflow with associated software to enable automated monitoring of LC-SRM setups. We believe that usage of the presented concepts will further strengthen the role of SRM as a reliable tool for protein quantification. This article is part of a Special Issue entitled: Standardization and Quality Control

Molecular Portrait of Breast-Cancer-Derived Cell Lines Reveals Poor Similarity with Tumors.

Breast-cancer-derived cell lines are an important sample source for cancer proteomics and can be classified on the basis of transcriptomic analysis into subgroups corresponding to the molecular subtypes observed in mammary tumors. This study describes a tridimensional fractionation method that allows high sequence coverage and proteome-wide estimation of protein expression levels. This workflow has been used to conduct an in-depth quantitative proteomic survey of five breast cancer cell lines matching all major cancer subgroups and shows that despite their different classification, these cell lines display a very high level of similarity. A proteome-wide comparison with the RNA levels observed in the same samples showed very little to no correlation. Finally, we demonstrate that the proteomes of in vitro models of breast cancer display surprisingly little overlap with those of clinical samples

Analysis of DIGE data using a linear mixed model allowing for protein-specific dye effects

Abstract in UndeterminedDifferential in-gel electrophoresis (DIGE) experiments allow three protein samples to be run per gel. The three samples are labeled with the spectrally resolvable fluorescent dyes, Cy2, Cy3, and Cy5, respectively. Here, we show that protein-specific dye effects exist, and we present a linear mixed model for analysis of DIGE data which takes dye effects into account. A Java implementation of the model, called DIGEanalyzer, is freely available at http://bioinfo.thep.lu.se/digeanalyzer.html. Three DIGE experiments from our laboratory, with 173, 64, and 24 gels, respectively, were used to quantify and verify the dye effects. DeCyder 5.0 and 6.5 were used for spot detection and matching. The fractions of proteins with a statistically significant (0.001 level) dye effect were 19, 34, and 23%, respectively. The fractions of proteins with a dye effect above 1.4-fold change were 1, 4, and 6%, respectively. The median magnitude of the dye effect was 1.07-fold change for Cy5 versus Cy3 and 1.16-fold change for Cy3 versus Cy2. The maximal dye effect was a seven-fold change. The dye effects of spots corresponding to the same protein tend to be similar within each of the three experiments, and to a smaller degree across experiments