Varje år skjuts det ungefär 80 000 älgar i Sverige. Av en älgberäknas 55% av vikten som ätbart kött och 45% slängs.Jag tror att det skulle kunna gå att ta till vara på dessa såkallade rester på ett mer meningsfullt sätt.Det är en fråga om respekt.Om en tar livet av ett djur så menar jag att ett mål bordevara att göra det yttersta för att ta till vara på så mycket avdet som möjligt.Under hösten har jag samlat in dessa rester.Vad har gjorts historiskt med dessa delar? Material och metoder som idag är bortglömda eller saknar marknad. Vadkan jag som formgivare göra idag som en inte kunde då?Jag har arbetat undersökande med hår, ben och hud frånälg och designat ett antal objekt för hemmet för en ökadmedvetenhet om potentialen i detta material.

Det här arbetet har gått ut på att jag har analyserat och fördjupat mig i tre professionella mixteknikers arbetsprocesser. Jag har studerat deras arbetsflöden, tillvägagångssätt och specifika metoder i syfte att skaffa mig ny kunskap och nya perspektiv på mixning. Jag har sedan gjort praktiska undersökningar där jag testat på att mixa utifrån teknikernas arbetsprocesser för att skaffa mig en djupare förståelse kring deras olika sätt att arbeta på. Det jag kommer fram till i mitt arbete är att det viktigaste för att mixa på en professionell nivå är att ha rätt tankesätt. Det finns stora tekniska skillnader mellan de tre professionella mixteknikerna men den gemensamma nämnaren är att de alla har samma syfte och helhetstänk bakom sina tekniska beslut. Detta har således givit mig insikt i att jag själv behöver bli bättre på att fokusera utifrån ett helhetstänk istället för på specifika tekniska metoder för att nå en högre nivå i min roll som mixningstekniker.

No description available.

The aim of this study was to identify the algal genera found in the different freshwater bodies on Marion Island, to relate the presence or absence of the genera to the chemistry of the water bodies and to group the genera according to their limno-chemical preferences. The Island's freshwater algal genera were also compared with genera found on other Southern Ocean islands. The major factors influencing the chemical composition of the freshwaters of the island are the surrounding ocean and the manuring of seals and seabirds. The Western and Southern lakelets and wallows had higher mean conductivity values than most of the other water bodies. Eastern Inland lakelets, crater lakes and glacial lakes had low ion and nutrient concentrations, since they are mainly situated inland, away from bird or seal colonies. The chemical composition of wallows was influenced by manuring of seals and seabirds. The freshwaters are acidic and lakelets tend to be more acidic than glacial lakes. The lentic waters were more acidic than the stream. In total, 106 genera, mainly belonging to Chlorophyta (60 genera; 56% of total) and Cyanophyta (29 genera; 27% of total), were found in the freshwaters on the island. Other algal divisions found were Chrysophyta (7 genera), Euglenophyta (4 genera), Pyrrophyta (2 genera) and Xanthophyta (4 genera). Mean number of genera per sample ranged from 8 (in wallows) to 16 (in Eastern Inland lakelets). Filamentous algae were present in all the samples. Abundant green algae were Cosmarium, Klebsormidium, Mougeotia and Oedogonium. The most common cyanobacteria were Lyngbya and Chroococcus. The filamentous yellow-green alga, Tribonema, was also common. There were distinct differences in the algal composition between the southern, western and northern lakelets and the lakelets on the eastern side of the island. Sixty percent of the algal genera were present in waters with low conductivity values. Trichodesmium, Sphaerocystis and Tolypothrix occurred in freshwater bodies with higher conductivity values. Variance analysis showed that 87 of the 106 genera were less likely to occur in nitrogen and phosphate containing waters. Chlamydomonas, Prasiola, Spirogyra Trachelomonas, Tribonema, Ulothrix and Xanthidium were among the genera commonly found in nitrogen and phosphate containing waters. Diversity (number of genera per sample) was negatively correlated with conductivity, PO4-P, NH4-N and NO3-N. Diversity declined significantly with increasing salinity and eutrophication. Genera likely to occur in acidic waters include Binuclearia, Chlamydomonas, Chroococcus, Cosmarium, Klebsormidium, Microspora, Oedogonium, Oocystis, Prasiola, Scenedesmus, Staurastrum, Stigeoclonium, Tetrastrum, Ulothrix, Lyngbya, Synura and Tribonema. Marion Island’s algal flora shows a high affinity with that of Îles Kerguelen and Crozet, both located in the same biogeographical province (South Indian Ocean Province) of the sub-Antarctic than Marion Island, and a lesser affinity with islands in other sub-Antarctic provinces. Algal genera were grouped according to their limno-chemistry preferences. / Thesis (MSc (Environmental Sciences))--North-West University, Potchefstroom Campus, 2012.

The aim of this study was to identify the algal genera found in the different freshwater bodies on Marion Island, to relate the presence or absence of the genera to the chemistry of the water bodies and to group the genera according to their limno-chemical preferences. The Island's freshwater algal genera were also compared with genera found on other Southern Ocean islands. The major factors influencing the chemical composition of the freshwaters of the island are the surrounding ocean and the manuring of seals and seabirds. The Western and Southern lakelets and wallows had higher mean conductivity values than most of the other water bodies. Eastern Inland lakelets, crater lakes and glacial lakes had low ion and nutrient concentrations, since they are mainly situated inland, away from bird or seal colonies. The chemical composition of wallows was influenced by manuring of seals and seabirds. The freshwaters are acidic and lakelets tend to be more acidic than glacial lakes. The lentic waters were more acidic than the stream. In total, 106 genera, mainly belonging to Chlorophyta (60 genera; 56% of total) and Cyanophyta (29 genera; 27% of total), were found in the freshwaters on the island. Other algal divisions found were Chrysophyta (7 genera), Euglenophyta (4 genera), Pyrrophyta (2 genera) and Xanthophyta (4 genera). Mean number of genera per sample ranged from 8 (in wallows) to 16 (in Eastern Inland lakelets). Filamentous algae were present in all the samples. Abundant green algae were Cosmarium, Klebsormidium, Mougeotia and Oedogonium. The most common cyanobacteria were Lyngbya and Chroococcus. The filamentous yellow-green alga, Tribonema, was also common. There were distinct differences in the algal composition between the southern, western and northern lakelets and the lakelets on the eastern side of the island. Sixty percent of the algal genera were present in waters with low conductivity values. Trichodesmium, Sphaerocystis and Tolypothrix occurred in freshwater bodies with higher conductivity values. Variance analysis showed that 87 of the 106 genera were less likely to occur in nitrogen and phosphate containing waters. Chlamydomonas, Prasiola, Spirogyra Trachelomonas, Tribonema, Ulothrix and Xanthidium were among the genera commonly found in nitrogen and phosphate containing waters. Diversity (number of genera per sample) was negatively correlated with conductivity, PO4-P, NH4-N and NO3-N. Diversity declined significantly with increasing salinity and eutrophication. Genera likely to occur in acidic waters include Binuclearia, Chlamydomonas, Chroococcus, Cosmarium, Klebsormidium, Microspora, Oedogonium, Oocystis, Prasiola, Scenedesmus, Staurastrum, Stigeoclonium, Tetrastrum, Ulothrix, Lyngbya, Synura and Tribonema. Marion Island’s algal flora shows a high affinity with that of Îles Kerguelen and Crozet, both located in the same biogeographical province (South Indian Ocean Province) of the sub-Antarctic than Marion Island, and a lesser affinity with islands in other sub-Antarctic provinces. Algal genera were grouped according to their limno-chemistry preferences. / Thesis (MSc (Environmental Sciences))--North-West University, Potchefstroom Campus, 2012.

No description available.

Kieselalgen – auch Diatomeen genannt – verfügen über die einzigartige Fähigkeit, nanostrukturierte, hierarchisch aufgebaute Zellwände aus Siliziumdioxid – auch als Biosilica bekannt – mit beispielloser Genauigkeit und Reproduzierbarkeit zu bilden. Ein tieferes Verständnis für diesen Prozess, der als “Biomineralisation“ bekannt ist, ist nicht nur auf dem Gebiet der Grundlagenforschung zu Kieselalgen sehr bedeutsam, sondern auch für die Nutzung dieser Nanostrukturierung in den Materialwissenschaften oder der Nanobiotechnologie. Nach dem derzeitigem Stand der Wissenschaft wird diese Strukturierung durch die Selbstorganisation von Proteinmustern, an denen sich das Siliziumdioxid bildet, erreicht. Um die Funktion und das Zusammenspiel einzelner Proteine, die an diesem Biomineralisationsprozess beteiligt sind, entschlüsseln zu können, ist es essentiell ihre strukturelle Organisation aufzuklären und diese mit den morphologischen Zellwandmerkmalen zu korrelieren. Die Größenordnung dieser Merkmale ist im Bereich von Nanometern angesiedelt. Mit Hilfe der Elektronenmikroskopie können diese Biosilicastrukturen aufgelöst werden, jedoch ist keine proteinspezifische Information verfügbar. Ziel dieser Arbeit war es daher, eine Technik zu etablieren, die in der Lage ist, einzelne Biosilica-assozierte Proteine mit Nanometer-Präzision zu lokalisieren. Um dieses Ziel zu erreichen, wurde Einzelmoleküllokalisationsmikroskopie (single-molecule localization microscopy, kurz: SMLM) beispielhaft in der Kieselalge Thalassiosira pseudonana etabliert. Die Position verschiedener Biosilica-assoziierte Proteine innerhalb des Biosilicas und nach dessen chemischer Auflösung wurde mit einer hohen räumlichen Auflösung bestimmt. Um quantitative Ergebnisse zu erhalten, wurde ein Analyse-Workflow entwickelt, der grafische Benutzeroberflächen und Skripte für die Visualisierung, das Clustering und die Kolokalisation von SMLM Daten beinhaltet. Um optimale Markierungen für SMLM an Biosilica-eingebetteten Proteinen zu finden, wurde ein umfassendes Screening von photo-schaltbaren fluoreszierenden Proteinen durchgeführt. Diese wurden als Fusionsproteine mit Silaffin3, einem Protein, welches eng mit der Biosilica-Zellwand assoziiert ist, exprimiert. Es konnte gezeigt werden, dass nur drei von sechs Kandidaten funktional sind, wenn sie in Biosilica eingebettet sind. Silaffin3 konnte indirekt mittels SMLM mit einer Lokalisationsgenauigkeit von 25 nm detektiert werden. Dies erlaubte es, seine strukturelle Organisation aufzulösen und Silaffin3 als eine Hauptkomponente in der Basalkammer der Fultoportulae zu identifizieren. / Diatoms feature the unique ability to form nanopatterned hierarchical silica cell walls with unprecedented accuracy and reproducibility. Gathering a deeper understanding of this process that is known as “biomineralization” is vitally important not only in the field of diatom research. In fact, the nanopatterning can also be exploited in the fields of material sciences or nanobiotechnology. According to the current understanding, the self-assembly of protein patterns along which biosilica is formed is key to this nanopatterning. Thus, in order to unravel the function of individual proteins that are involved in this biomineralization process, their structural organization has to be deciphered and correlated to morphological cell wall features that are in the order of tens of nanometer. Electron microscopy is able to resolve these features but does not provide protein-specific information. Therefore, a technique has to be established that is able to localize individual biosilica-associated proteins with nanometer precision. To achieve this objective, single-molecule localization microscopy (SMLM) for the diatom Thalassiosira pseudonana has been pioneered and exploited to localize different biosilica associated proteins inside silica and after silica removal. To obtain quantitative data, an analysis workflow was developed including graphical user interfaces and scripts for SMLM visualization, clustering, and co-localization. In order to find optimal labels for SMLM to target biosilica-embedded proteins, a comprehensive screening of photo-controllable fluorescent proteins has been carried out. Only three of six candidates were functional when embedded inside biosilica and fused to Silaffin3 – a protein that is tightly associated with the biosilica cell wall. Silaffin3 could be localized using SMLM with a localization precision of 25 nm. This allowed to resolve its structural organization and therefore identified Silaffin3 as a major component in the basal chamber of the fultoportulae. Additionally, co-localization studies on cingulins – a protein family hypothesized to be involved in silica formation – have been performed to decipher their pattern-function relationship. Towards this end, novel imaging strategies, co-localization calculations and pattern quantifications have been established. With the help of these results, the spatial arrangement of cingulins W2 and Y2 could be compared with unprecedented resolution. In summary, this work has laid ground for quantitative SMLM studies of proteins in diatoms in general and contributed insights into the spatial organization of proteins involved in biomineralization in the diatom T. pseudonana.

Kieselalgen – auch Diatomeen genannt – verfügen über die einzigartige Fähigkeit, nanostrukturierte, hierarchisch aufgebaute Zellwände aus Siliziumdioxid – auch als Biosilica bekannt – mit beispielloser Genauigkeit und Reproduzierbarkeit zu bilden. Ein tieferes Verständnis für diesen Prozess, der als “Biomineralisation“ bekannt ist, ist nicht nur auf dem Gebiet der Grundlagenforschung zu Kieselalgen sehr bedeutsam, sondern auch für die Nutzung dieser Nanostrukturierung in den Materialwissenschaften oder der Nanobiotechnologie. Nach dem derzeitigem Stand der Wissenschaft wird diese Strukturierung durch die Selbstorganisation von Proteinmustern, an denen sich das Siliziumdioxid bildet, erreicht. Um die Funktion und das Zusammenspiel einzelner Proteine, die an diesem Biomineralisationsprozess beteiligt sind, entschlüsseln zu können, ist es essentiell ihre strukturelle Organisation aufzuklären und diese mit den morphologischen Zellwandmerkmalen zu korrelieren. Die Größenordnung dieser Merkmale ist im Bereich von Nanometern angesiedelt. Mit Hilfe der Elektronenmikroskopie können diese Biosilicastrukturen aufgelöst werden, jedoch ist keine proteinspezifische Information verfügbar. Ziel dieser Arbeit war es daher, eine Technik zu etablieren, die in der Lage ist, einzelne Biosilica-assozierte Proteine mit Nanometer-Präzision zu lokalisieren. Um dieses Ziel zu erreichen, wurde Einzelmoleküllokalisationsmikroskopie (single-molecule localization microscopy, kurz: SMLM) beispielhaft in der Kieselalge Thalassiosira pseudonana etabliert. Die Position verschiedener Biosilica-assoziierte Proteine innerhalb des Biosilicas und nach dessen chemischer Auflösung wurde mit einer hohen räumlichen Auflösung bestimmt. Um quantitative Ergebnisse zu erhalten, wurde ein Analyse-Workflow entwickelt, der grafische Benutzeroberflächen und Skripte für die Visualisierung, das Clustering und die Kolokalisation von SMLM Daten beinhaltet. Um optimale Markierungen für SMLM an Biosilica-eingebetteten Proteinen zu finden, wurde ein umfassendes Screening von photo-schaltbaren fluoreszierenden Proteinen durchgeführt. Diese wurden als Fusionsproteine mit Silaffin3, einem Protein, welches eng mit der Biosilica-Zellwand assoziiert ist, exprimiert. Es konnte gezeigt werden, dass nur drei von sechs Kandidaten funktional sind, wenn sie in Biosilica eingebettet sind. Silaffin3 konnte indirekt mittels SMLM mit einer Lokalisationsgenauigkeit von 25 nm detektiert werden. Dies erlaubte es, seine strukturelle Organisation aufzulösen und Silaffin3 als eine Hauptkomponente in der Basalkammer der Fultoportulae zu identifizieren.:1 INTRODUCTION 1 1.1 Diatoms – a model system for biomineralization 3 1.2 Imaging of biosilica and associated organic components 8 1.3 Single-molecule localization microscopy (SMLM) 10 2 METHODS & METHOD DEVELOPMENT FOR SMLM DATASETS 17 2.1 Super-resolution reconstruction 19 2.2 Tools for SMLM resolution estimates 21 2.3 Voronoi tessellation for noise-removal and cluster estimation 25 2.4 Tools for SMLM cluster analysis 27 2.5 Coordinate-based co-localization 32 2.6 PairRice – A novel algorithm to extract distances between cluster pairs 33 2.7 SiMoNa – A new GUI for exploring SMLM datasets 35 3 RESOLUTION OF THE SMLM SETUP TESTED WITH DNA ORIGAMI NANOSTRUCTURES 41 3.1 DNA origami as a length standard 42 3.2 Global resolution estimates 44 3.3 Local resolution estimates 47 3.4 Conclusion 53 4 EVALUATION OF PHOTO-CONTROLLABLE FLUORESCENT PROTEINS FOR PALM IN DIATOMS 55 4.1 Selecting PCFPs to minimize interference with the diatom autofluorescence 56 4.2 Screening results for cytosolic and biosilica-embedded PCFPs 58 4.3 The underlying conversion mechanism 61 4.4 Conclusion 63 5 IMAGING THE SIL3 MESHWORK 65 5.1 Analyzing protein layer thickness using tpSil3-Dendra2 65 5.2 Imaging the valve region using tpSil3 68 5.3 Resolution and localization parameters of tpSil3 70 5.4 Conclusion 72 6 DECIPHERING CINGULIN PATTERNS WITH CO LOCALIZATION STUDIES 73 6.1 A two-color cingulin construct for PALM-STORM 73 6.2 Steps towards PALM-STORM: screening, alignment, and imaging routine 76 6.3 Co-localization studies: quantification, clustering, and correlations 83 6.4 Conclusion 91 7 OUTLOOK 93 8 MATERIALS & METHODS 97 8.1 Microscope specifications 97 8.2 DNA origami annealing and AFM measurements 99 8.3 Diatom sample preparations 100 8.4 Fluorescence imaging conditions 102 8.5 Buffer systems 103 9 APPENDICES 105 9.1 Tables and Protocols 105 9.2 Satellite projects 112 9.2.1 Quantitative fluorescence intensity analysis of 3D time-lapse confocal microscopy data in diatoms 112 9.2.2 Applying neural networks to filter SMLM localizations 118 9.2.3 In vivo imaging at super-resolution conditions using SOFI 121 9.2.4 Quantifying chromatic aberrations in the microscope using fiducials 123 10 REFERENCES 127 / Diatoms feature the unique ability to form nanopatterned hierarchical silica cell walls with unprecedented accuracy and reproducibility. Gathering a deeper understanding of this process that is known as “biomineralization” is vitally important not only in the field of diatom research. In fact, the nanopatterning can also be exploited in the fields of material sciences or nanobiotechnology. According to the current understanding, the self-assembly of protein patterns along which biosilica is formed is key to this nanopatterning. Thus, in order to unravel the function of individual proteins that are involved in this biomineralization process, their structural organization has to be deciphered and correlated to morphological cell wall features that are in the order of tens of nanometer. Electron microscopy is able to resolve these features but does not provide protein-specific information. Therefore, a technique has to be established that is able to localize individual biosilica-associated proteins with nanometer precision. To achieve this objective, single-molecule localization microscopy (SMLM) for the diatom Thalassiosira pseudonana has been pioneered and exploited to localize different biosilica associated proteins inside silica and after silica removal. To obtain quantitative data, an analysis workflow was developed including graphical user interfaces and scripts for SMLM visualization, clustering, and co-localization. In order to find optimal labels for SMLM to target biosilica-embedded proteins, a comprehensive screening of photo-controllable fluorescent proteins has been carried out. Only three of six candidates were functional when embedded inside biosilica and fused to Silaffin3 – a protein that is tightly associated with the biosilica cell wall. Silaffin3 could be localized using SMLM with a localization precision of 25 nm. This allowed to resolve its structural organization and therefore identified Silaffin3 as a major component in the basal chamber of the fultoportulae. Additionally, co-localization studies on cingulins – a protein family hypothesized to be involved in silica formation – have been performed to decipher their pattern-function relationship. Towards this end, novel imaging strategies, co-localization calculations and pattern quantifications have been established. With the help of these results, the spatial arrangement of cingulins W2 and Y2 could be compared with unprecedented resolution. In summary, this work has laid ground for quantitative SMLM studies of proteins in diatoms in general and contributed insights into the spatial organization of proteins involved in biomineralization in the diatom T. pseudonana.:1 INTRODUCTION 1 1.1 Diatoms – a model system for biomineralization 3 1.2 Imaging of biosilica and associated organic components 8 1.3 Single-molecule localization microscopy (SMLM) 10 2 METHODS & METHOD DEVELOPMENT FOR SMLM DATASETS 17 2.1 Super-resolution reconstruction 19 2.2 Tools for SMLM resolution estimates 21 2.3 Voronoi tessellation for noise-removal and cluster estimation 25 2.4 Tools for SMLM cluster analysis 27 2.5 Coordinate-based co-localization 32 2.6 PairRice – A novel algorithm to extract distances between cluster pairs 33 2.7 SiMoNa – A new GUI for exploring SMLM datasets 35 3 RESOLUTION OF THE SMLM SETUP TESTED WITH DNA ORIGAMI NANOSTRUCTURES 41 3.1 DNA origami as a length standard 42 3.2 Global resolution estimates 44 3.3 Local resolution estimates 47 3.4 Conclusion 53 4 EVALUATION OF PHOTO-CONTROLLABLE FLUORESCENT PROTEINS FOR PALM IN DIATOMS 55 4.1 Selecting PCFPs to minimize interference with the diatom autofluorescence 56 4.2 Screening results for cytosolic and biosilica-embedded PCFPs 58 4.3 The underlying conversion mechanism 61 4.4 Conclusion 63 5 IMAGING THE SIL3 MESHWORK 65 5.1 Analyzing protein layer thickness using tpSil3-Dendra2 65 5.2 Imaging the valve region using tpSil3 68 5.3 Resolution and localization parameters of tpSil3 70 5.4 Conclusion 72 6 DECIPHERING CINGULIN PATTERNS WITH CO LOCALIZATION STUDIES 73 6.1 A two-color cingulin construct for PALM-STORM 73 6.2 Steps towards PALM-STORM: screening, alignment, and imaging routine 76 6.3 Co-localization studies: quantification, clustering, and correlations 83 6.4 Conclusion 91 7 OUTLOOK 93 8 MATERIALS & METHODS 97 8.1 Microscope specifications 97 8.2 DNA origami annealing and AFM measurements 99 8.3 Diatom sample preparations 100 8.4 Fluorescence imaging conditions 102 8.5 Buffer systems 103 9 APPENDICES 105 9.1 Tables and Protocols 105 9.2 Satellite projects 112 9.2.1 Quantitative fluorescence intensity analysis of 3D time-lapse confocal microscopy data in diatoms 112 9.2.2 Applying neural networks to filter SMLM localizations 118 9.2.3 In vivo imaging at super-resolution conditions using SOFI 121 9.2.4 Quantifying chromatic aberrations in the microscope using fiducials 123 10 REFERENCES 127