Proline-containing β-turns in peptides and proteins: Analysis of structural data on globular proteins

Tetrapeptide sequences of the type Z-Pro-Y-X were obtained from the crystal structure data on 34 globular proteins, and used in an analysis of the positional preferences of the individual amino acid residues in the β-turn conformation. The effect of fixing proline as the second position residue in the tetrapeptide sequence was studied by comparing the data obtained on the positional preferences with the corresponding data obtained by Chou and Fasman using the Z-R-Y-X sequence, where no particular residue was fixed in any of the four positions. While, in general, several amino acid residues having relatively very high or very low preferences for specific positions were found to be common to both the Z-Pro-Y-X and Z-R-Y-X sequences, many significant differences were found between the two sets of data, which are to be attributed to specific interactions arising from the presence of the proline residue.

The ozone transfer between atmosphere and vegetation. A study on Scots pine in the field

Ozone (O3) is a reactive gas present in the troposphere in the range of parts per billion (ppb), i.e. molecules of O3 in 109 molecules of air. Its strong oxidative capacity makes it a key element in tropospheric chemistry and a threat to the integrity of materials, including living organisms. Knowledge and control of O3 levels are an issue in relation to indoor air quality, building material endurance, respiratory human disorders, and plant performance. Ozone is also a greenhouse gas and its abundance is relevant to global warming. The interaction of the lower troposphere with vegetated landscapes results in O3 being removed from the atmosphere by reactions that lead to the oxidation of plant-related components. Details on the rate and pattern of removal on different landscapes as well as the ultimate mechanisms by which this occurs are not fully resolved. This thesis analysed the controlling processes of the transfer of ozone at the air-plant interface. Improvement in the knowledge of these processes benefits the prediction of both atmospheric removal of O3 and its impact on vegetation. This study was based on the measurement and analysis of multi-year field measurements of O3 flux to Scots pine (Pinus sylvestris L.) foliage with a shoot-scale gas-exchange enclosure system. In addition, the analyses made use of simultaneous CO2 and H2O exchange, canopy-scale O3, CO2 and H2O exchange, foliage surface wetness, and environmental variables. All data was gathered at the SMEAR measuring station (southern Finland). Enclosure gas-exchange techniques such as those commonly used for the measure of CO2 and water vapour can be applied to the measure of ozone gas-exchange in the field. Through analysis of the system dynamics the occurring disturbances and noise can be identified. In the system used in this study, the possible artefacts arising from the ozone reactivity towards the system materials in combination with low background concentrations need to be taken into account. The main artefact was the loss of ozone towards the chamber walls, which was found to be very variable. The level of wall-loss was obtained from simultaneous and continuous measurements, and was included in the formulation of the mass balance of O3 concentration inside the chamber. The analysis of the field measurements in this study show that the flux of ozone to the Scots pine foliage is generated in about equal proportions by stomatal and non-stomatal controlled processes. Deposition towards foliage and forest is sustained also during night and winter when stomatal gas-exchange is low or absent. The non-stomatal portion of the flux was analysed further. The pattern of flux in time was found to be an overlap of the patterns of biological activity and presence of wetness in the environment. This was seen to occur both at the shoot and canopy scale. The presence of wetness enhanced the flux not only in the presence of liquid droplets but also during existence of a moisture film on the plant surfaces. The existence of these films and their relation to the ozone sinks was determined by simultaneous measurements of leaf surface wetness and ozone flux. The results seem to suggest ozone would be reacting at the foliage surface and the reaction rate would be mediated by the presence of surface wetness. Alternative mechanisms were discussed, including nocturnal stomatal aperture and emission of reactive volatile compounds. The prediction of the total flux could thus be based on a combination of a model of stomatal behaviour and a model of water absorption on the foliage surfaces. The concepts behind the division of stomatal and non-stomatal sinks were reconsidered. This study showed that it is theoretically possible that a sink located before or near the stomatal aperture prevents or diminishes the diffusion of ozone towards the intercellular air space of the mesophyll. This obstacle to stomatal diffusion happens only under certain conditions, which include a very low presence of reaction sites in the mesophyll, an extremely strong sink located on the outer surfaces or stomatal pore. The relevance, or existence, of this process in natural conditions would need to be assessed further. Potentially strong reactions were considered, including dissolved sulphate, volatile organic compounds, and apoplastic ascorbic acid. Information on the location and the relative abundance of these compounds would be valuable. The highest total flux towards the foliage and forest happens when both the plant activity and ambient moisture are high. The highest uptake into the interior of the foliage happens at large stomatal apertures, provided that scavenging reactions located near the stomatal pore are weak or non-existent. The discussion covers the methodological developments of this study, the relevance of the different controlling factors of ozone flux, the partition amongst its component, and the possible mechanisms of non-stomatal uptake.

Estimation of local forest attributes, utilizing two-phase sampling and auxiliary data

This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Zygosity diagnosis in the absence of genotypic data: An approach using latent class analysis

For zygosity diagnosis in the absence of genotypic data, or in the recruitment phase of a twin study where only single twins from same-sex pairs are being screened, or to provide a test for sample duplication leading to the false identification of a dizygotic pair as monozygotic, the appropriate analysis of respondents' answers to questions about zygosity is critical. Using data from a young adult Australian twin cohort (N = 2094 complete pairs and 519 singleton twins from same-sex pairs with complete responses to all zygosity items), we show that application of latent class analysis (LCA), fitting a 2-class model, yields results that show good concordance with traditional methods of zygosity diagnosis, but with certain important advantages. These include the ability, in many cases, to assign zygosity with specified probability on the basis of responses of a single informant (advantageous when one zygosity type is being oversampled); and the ability to quantify the probability of misassignment of zygosity, allowing prioritization of cases for genotyping as well as identification of cases of probable laboratory error. Out of 242 twins (from 121 like-sex pairs) where genotypic data were available for zygosity confirmation, only a single case was identified of incorrect zygosity assignment by the latent class algorithm. Zygosity assignment for that single case was identified by the LCA as uncertain (probability of being a monozygotic twin only 76%), and the co-twin's responses clearly identified the pair as dizygotic (probability of being dizygotic 100%). In the absence of genotypic data, or as a safeguard against sample duplication, application of LCA for zygosity assignment or confirmation is strongly recommended.

Correlation between NIRS generated and chemically measured feed quality data in barley (Hordeum vulgare), and potential use in QTL analysis identification

A study was performed to investigate the value of near infrared reflectance spectroscopy (NIRS) as an alternate method to analytical techniques for identifying QTL associated with feed quality traits. Milled samples from an F6-derived recombinant inbred Tallon/Scarlett population were incubated in the rumen of fistulated cattle, recovered, washed and dried to determine the in-situ dry matter digestibility (DMD). Both pre- and post-digestion samples were analysed using NIRS to quantify key quality components relating to acid detergent fibre, starch and protein. This phenotypic data was used to identify trait associated QTL and compare them to previously identified QTL. Though a number of genetic correlations were identified between the phenotypic data sets, the only correlation of most interest was between DMD and starch digested (r = -0.382). The significance of this genetic correlation was that the NIRS data set identified a putative QTL on chromosomes 7H (LOD = 3.3) associated with starch digested. A QTL for DMD occurred in the same region of chromosome 7H, with flanking markers fAG/CAT63 and bPb-0758. The significant correlation and identification of this putative QTL, highlights the potential of technologies like NIRS in QTL analysis.

Impact of the Human Bacterial Environment on Mycobacteriosis and Allergy

My work describes two sectors of the human bacterial environment: 1. The sources of exposure to infectious non-tuberculous mycobacteria. 2. Bacteria in dust, reflecting the airborne bacterial exposure in environments protecting from or predisposing to allergic disorders. Non-tuberculous mycobacteria (NTM) transmit to humans and animals from the environment. Infection by NTM in Finland has increased during the past decade beyond that by Mycobacterium tuberculosis. Among the farm animals, porcine mycobacteriosis is the predominant NTM disease in Finland. Symptoms of mycobacteriosis are found in 0.34 % of slaughtered pigs. Soil and drinking water are suspected as sources for humans and bedding materials for pigs. To achieve quantitative data on the sources of human and porcine NTM exposure, methods for quantitation of environmental NTM are needed. We developed a quantitative real-time PCR method, utilizing primers targeted at the 16S rRNA gene of the genus of Mycobacterium. With this method, I found in Finnish sphagnum peat, sandy soils and mud high contents of mycobacterial DNA, 106 to 107 genome equivalents per gram. A similar result was obtained by a method based on the Mycobacterium-specific hybridization of 16S rRNA. Since rRNA is found mainly in live cells, this result shows that the DNA detected by qPCR mainly represented live mycobacteria. Next, I investigated the occurrence of environmental mycobacteria in the bedding materials obtained from 5 pig farms with high prevalence (>4 %) of mycobacteriosis. When I used for quantification the same qPCR methods as for the soils, I found that piggery samples contained non-mycobacterial DNA that was amplified in spite of several mismatches with the primers. I therefore improved the qPCR assay by designing Mycobacterium-specific detection probes. Using the probe qPCR assay, I found 105 to 107 genome equivalents of mycobacterial DNA in unused bedding materials and up to 1000 fold more in the bedding collected after use in the piggery. This result shows that there was a source of mycobacteria in the bedding materials purchased by the piggery and that mycobacteria increased in the bedding materials during use in the piggery. Allergic diseases have reached epidemic proportions in urbanized countries. At the same time, childhood in rural environment or simple living conditions appears to protect against allergic disorders. Exposure to immunoreactive microbial components in rural environments seems to prevent allergies. I searched for differences in the bacterial communities of two indoor dusts, an urban house dust shown to possess immunoreactivity of the TH2-type and a farm barn dust with TH1-activity. The immunoreactivities of the dusts were revealed by my collaborators, in vitro in human dendritic cells and in vivo in mouse. The dusts accumulated >10 years in the respiratory zone (>1.5 m above floor), thus reflecting the long-term content of airborne bacteria at the two sites. I investigated these dusts by cloning and sequencing of bacterial 16S rRNA genes from dust contained DNA. From the TH2-active urban house dust, I isolated 139 16S rRNA gene clones. The most prevalent genera among the clones were Corynebacterium (5 species, 34 clones), Streptococcus (8 species, 33 clones), Staphylococcus (5 species, 9 clones) and Finegoldia (1 species, 9 clones). Almost all of these species are known as colonizers of the human skin and oral cavity. Species of Corynebacterium and Streptococcus have been reported to contain anti-inflammatory lipoarabinomannans and immunmoreactive beta-glucans respectively. Streptococcus mitis, found in the urban house dust is known as an inducer of TH2 polarized immunity, characteristic of allergic disorders. I isolated 152 DNA clones from the TH1-active farm barn dust and found species quite different from those found from the urban house dust. Among others, I found DNA clones representing Bacillus licheniformis, Acinetobacter lwoffii and Lactobacillus each of which was recently reported to possess anti-allergy immunoreactivity. Moreover, the farm barn dust contained dramatically higher bacterial diversity than the urban house dust. Exposure to this dust thus stimulated the human dendritic cells by multiple microbial components. Such stimulation was reported to promote TH1 immunity. The biodiversity in dust may thus be connected to its immunoreactivity. Furthermore, the bacterial biomass in the farm barn dust consisted of live intact bacteria mainly. In the urban house dust only ~1 % of the biomass appeared as intact bacteria, as judged by microscoping. Fragmented microbes may possess bioactivity different from that of intact cells. This was recently shown for moulds. If this is also valid for bacteria, the different immunoreactivities of the two dusts may be explained by the intactness of dustborne bacteria. Based on these results, we offer three factors potentially contributing to the polarized immunoreactivities of the two dusts: (i) the species-composition, (ii) the biodiversity and (iii) the intactness of the dustborne bacterial biomass. The risk of childhood atopic diseases is 4-fold lower in the Russian compared with the Finnish Karelia. This difference across the country border is not explainable by different geo-climatic factors or genetic susceptibilities of the two populations. Instead, the explanation must be lifestyle-related. It has already been reported that the microbiological quality of drinking water differs on the two sides of the borders. In collaboration with allergists, I investigated dusts collected from homes in the Russian Karelia and in the Finnish Karelia. I found that bacterial 16S rRNA genes cloned from the Russian Karelian dusts (10 homes, 234 clones) predominantly represented Gram-positive taxa (the phyla Actinobacteria and Firmicutes, 67%). The Russian Karelian dusts contained nine-fold more of muramic acid (60 to 70 ng mg-1) than the Finnish Karelian dusts (3 to 11 ng mg-1). Among the DNA clones isolated from the Finnish side (n=231), Gram-negative taxa (40%) outnumbered the Gram-positives (34%). Out of the 465 DNA clones isolated from the Karelian dusts, 242 were assigned to cultured validly described bacterial species. In Russian Karelia, animal-associated species e.g. Staphylococcus and Macrococcus were numerous (27 clones, 14 unique species). This finding may connect to the difference in the prevalence of allergy, as childhood contacts with pets and farm animals have been connected with low allergy risk. Plant-associated bacteria and plant-borne 16S rRNA genes (chloroplast) were frequent among the DNA clones isolated from the Finnish Karelia, indicating components originating from plants. In conclusion, my work revealed three major differences between the bacterial communtites in the Russian and in the Finnish Karelian homes: (i) the high prevalence of Gram-positive bacteria on the Russian side and of Gram-negative bacteria on the Finnish side and (ii) the rich presence of animal-associated bacteria on the Russian side whereas (iii) plant-associated bacteria prevailed on the Finnish side. One or several of these factors may connect to the differences in the prevalence of allergy.

DNA-based detection and characterisation of strictly anaerobic beer-spoilage bacteria

Megasphaera cerevisiae, Pectinatus cerevisiiphilus, Pectinatus frisingensis, Selenomonas lacticifex, Zymophilus paucivorans and Zymophilus raffinosivorans are strictly anaerobic Gram-stain-negative bacteria that are able to spoil beer by producing off-flavours and turbidity. They have only been isolated from the beer production chain. The species are phylogenetically affiliated to the Sporomusa sub-branch in the class "Clostridia". Routine cultivation methods for detection of strictly anaerobic bacteria in breweries are time-consuming and do not allow species identification. The main aim of this study was to utilise DNA-based techniques in order to improve detection and identification of the Sporomusa sub-branch beer-spoilage bacteria and to increase understanding of their biodiversity, evolution and natural sources. Practical PCR-based assays were developed for monitoring of M. cerevisiae, Pectinatus species and the group of Sporomusa sub-branch beer spoilers throughout the beer production process. The developed assays reliably differentiated the target bacteria from other brewery-related microbes. The contaminant detection in process samples (10 1,000 cfu/ml) could be accomplished in 2 8 h. Low levels of viable cells in finished beer (≤10 cfu/100 ml) were usually detected after 1 3 d culture enrichment. Time saving compared to cultivation methods was up to 6 d. Based on a polyphasic approach, this study revealed the existence of three new anaerobic spoilage species in the beer production chain, i.e. Megasphaera paucivorans, Megasphaera sueciensis and Pectinatus haikarae. The description of these species enabled establishment of phenotypic and DNA-based methods for their detection and identification. The 16S rRNA gene based phylogenetic analysis of the Sporomusa sub-branch showed that the genus Selenomonas originates from several ancestors and will require reclassification. Moreover, Z. paucivorans and Z. raffinosivorans were found to be in fact members of the genus Propionispira. This relationship implies that they were carried to breweries along with plant material. The brewery-related Megasphaera species formed a distinct sub-group that did not include any sequences from other sources, suggesting that M. cerevisiae, M. paucivorans and M. sueciensis may be uniquely adapted to the brewery ecosystem. M. cerevisiae was also shown to exhibit remarkable resistance against many brewery-related stress conditions. This may partly explain why it is a brewery contaminant. This study showed that DNA-based techniques provide useful tools for obtaining more rapid and specific information about the presence and identity of the strictly anaerobic spoilage bacteria in the beer production chain than is possible using cultivation methods. This should ensure financial benefits to the industry and better product quality to customers. In addition, DNA-based analyses provided new insight into the biodiversity as well as natural sources and relations of the Sporomusa sub-branch bacteria. The data can be exploited for taxonomic classification of these bacteria and for surveillance and control of contaminations.

Essays on the Bioeconomics of the Northern Baltic Fisheries

World marine fisheries suffer from economic and biological overfishing: too many vessels are harvesting too few fish stocks. Fisheries economics has explained the causes of overfishing and provided a theoretical background for management systems capable of solving the problem. Yet only a few examples of fisheries managed by the principles of the bioeconomic theory exist. With the aim of bridging the gap between the actual fish stock assessment models used to provide management advice and economic optimisation models, the thesis explores economically sound harvesting from national and international perspectives. Using data calibrated for the Baltic salmon and herring stocks, optimal harvesting policies are outlined using numerical methods. First, the thesis focuses on the socially optimal harvest of a single salmon stock by commercial and recreational fisheries. The results obtained using dynamic programming show that the optimal fishery configuration would be to close down three out of the five studied fisheries. The result is robust to stock size fluctuations. Compared to a base case situation, the optimal fleet structure would yield a slight decrease in the commercial catch, but a recreational catch that is nearly seven times higher. As a result, the expected economic net benefits from the fishery would increase nearly 60%, and the expected number of juvenile salmon (smolt) would increase by 30%. Second, the thesis explores the management of multiple salmon stocks in an international framework. Non-cooperative and cooperative game theory are used to demonstrate different "what if" scenarios. The results of the four player game suggest that, despite the commonly agreed fishing quota, the behaviour of the countries has been closer to non-cooperation than cooperation. Cooperation would more than double the net benefits from the fishery compared to a past fisheries policy. Side payments, however, are a prerequisite for a cooperative solution. Third, the thesis applies coalitional games in the partition function form to study whether the cooperative solution would be stable despite the potential presence of positive externalities. The results show that the cooperation of two out of four studied countries can be stable. Compared to a past fisheries policy, a stable coalition structure would provide substantial economic benefits. Nevertheless, the status of the salmon stocks would not improve significantly. Fourth, the thesis studies the prerequisites for and potential consequences of the implementation of an individual transferable quota (ITQ) system in the Finnish herring fishery. Simulation results suggest that ITQs would result in a decrease in the number of fishing vessels, but enables positive profits to overlap with a higher stock size. The empirical findings of the thesis affirm that the profitability of the studied fisheries could be improved. The evidence, however, indicates that incentives for free riding exist, and thus the most preferable outcome both in economic and biological terms is elusive.

Enzyme molecular choreography : studies on soluble inorganic pyrophosphatases

Inorganic pyrophosphatases (PPases, EC 3.6.1.1) hydrolyse pyrophosphate in a reaction that provides the thermodynamic 'push' for many reactions in the cell, including DNA and protein synthesis. Soluble PPases can be classified into two families that differ completely in both sequence and structure. While Family I PPases are found in all kingdoms, family II PPases occur only in certain prokaryotes. The enzyme from baker's yeast (Saccharomyces cerevisiae) is very well characterised both kinetically and structurally, but the exact mechanism has remained elusive. The enzyme uses divalent cations as cofactors; in vivo the metal is magnesium. Two metals are permanently bound to the enzyme, while two come with the substrate. The reaction cycle involves the activation of the nucleophilic oxygen and allows different pathways for product release. In this thesis I have solved the crystal structures of wild type yeast PPase and seven active site variants in the presence of the native cofactor magnesium. These structures explain the effects of the mutations and have allowed me to describe each intermediate along the catalytic pathway with a structure. Although establishing the ʻchoreographyʼ of the heavy atoms is an important step in understanding the mechanism, hydrogen atoms are crucial for the mechanism. The most unambiguous method to determine the positions of these hydrogen atoms is neutron crystallography. In order to determine the neutron structure of yeast PPase I perdeuterated the enzyme and grew large crystals of it. Since the crystals were not stable at ambient temperature, a cooling device was developed to allow neutron data collection. In order to investigate the structural changes during the reaction in real time by time-resolved crystallography a photolysable substrate precursor is needed. I synthesised a candidate molecule and characterised its photolysis kinetics, but unfortunately it is hydrolysed by both yeast and Thermotoga maritima PPases. The mechanism of Family II PPases is subtly different from Family I. The native metal cofactor is manganese instead of magnesium, but the metal activation is more complex because the metal ions that arrive with the substrate are magnesium different from those permanently bound to the enzyme. I determined the crystal structures of wild type Bacillus subtilis PPase with the inhibitor imidodiphosphate and an inactive H98Q variant with the substrate pyrophosphate. These structures revealed a new trimetal site that activates the nucleophile. I also determined that the metal ion sites were partially occupied by manganese and iron using anomalous X- ray scattering.

Autoxidation of conjugated linoleic acid methyl ester in the presence of α-tocopherol: the hydroperoxide pathway

The autoxidation of conjugated linoleic acid (CLA) is poorly understood in spite of increasing interest in the beneficial biological properties of CLA and growing consumption of CLA-rich foods. In this thesis, the autoxidation reactions of the two major CLA isomers, 9-cis,11-trans-octadecadienoic acid and 10-trans,12-cis-octadecadienoic acid, are investigated. The results contribute to an understanding of the early stages of the autoxidation of CLA methyl ester, and provide for the first time a means of producing and separating intact CLA methyl ester hydroperoxides as well as basic knowledge on lipid hydroperoxides and their hydroxy derivatives. Conjugated diene allylic monohydroperoxides were discovered as primary autoxidation products formed during autoxidation of CLA methyl esters in the presence and absence of α-tocopherol. This established that one of the autoxidation pathways of CLA methyl ester is the hydroperoxide pathway. Hydroperoxides were produced from the two major CLA methyl esters by taking advantage of the effect of α-tocopherol to promote hydroperoxide formation. The hydroperoxides were analysed and separated first as methyl hydroxyoctadecadienoates and then as intact hydroperoxides by HPLC. The isolated products were characterized by UV, GC-MS, and NMR techniques. In the presence of a high amount of α-tocopherol, the autoxidation of CLA methyl ester yields six kinetically-controlled conjugated diene monohydroperoxides and is diastereoselective in favour of one particular geometric isomer as a pair of enantiomers. The primary autoxidation products produced from the two major CLA isomers include new positional isomers of conjugated diene monohydroperoxides, the 8-, 10-, 12-, and 14-hydroperoxyoctadecadienoates. Furthermore, two of these new positional isomers have an unusual structure for a cis,trans lipid hydroperoxide where the allylic methine carbon is adjacent to the cis instead of the usual trans double bond. The 1H and 13C NMR spectra of nine isomeric methyl hydroxyoctadecadienoates and of ten isomeric methyl hydroperoxyoctadecadienoates including the unusual cis,trans hydroperoxides, i.e. Me 8-OOH-9c,11t and Me 14-OOH-10t,12c, were fully assigned with the aid of 2D NMR spectroscopy. The assigned NMR data enabled determination of the effects of the hydroxyl and hydroperoxyl groups on the carbon chemical shifts of CLA isomers, identification of diagnostic signals, and determination of chemical shift differences of the olefinic resonances that may help with the assignment of structure to as yet unknown lipid hydroperoxides either as hydroxy derivatives or as intact hydroperoxides. A mechanism for the hydroperoxide pathway of CLA autoxidation in the presence of a high amount of α-tocopherol was proposed based on the characterized primary products, their relative distribution, and theoretical calculations. This is an important step forward in CLA research, where exact mechanisms for the autoxidation of CLA have not been presented before. Knowledge of these hydroperoxide formation steps is of crucial importance for understanding the subsequent steps and the different pathways of the autoxidation of CLA. Moreover, a deeper understanding of the autoxidation mechanisms is required for ensuring the safety of CLA-rich foods. Knowledge of CLA oxidation and how it differs from the oxidation of nonconjugated polyunsaturated fatty acids may also be the key to understanding the biological mechanisms of CLA activity.

Deriving optimal fishing effort for managing Australia's Moreton Bay multispecies trawl fishery with aggregated effort data

Deriving an estimate of optimal fishing effort or even an approximate estimate is very valuable for managing fisheries with multiple target species. The most challenging task associated with this is allocating effort to individual species when only the total effort is recorded. Spatial information on the distribution of each species within a fishery can be used to justify the allocations, but often such information is not available. To determine the long-term overall effort required to achieve maximum sustainable yield (MSY) and maximum economic yield (MEY), we consider three methods for allocating effort: (i) optimal allocation, which optimally allocates effort among target species; (ii) fixed proportions, which chooses proportions based on past catch data; and (iii) economic allocation, which splits effort based on the expected catch value of each species. Determining the overall fishing effort required to achieve these management objectives is a maximizing problem subject to constraints due to economic and social considerations. We illustrated the approaches using a case study of the Moreton Bay Prawn Trawl Fishery in Queensland (Australia). The results were consistent across the three methods. Importantly, our analysis demonstrated the optimal total effort was very sensitive to daily fishing costs—the effort ranged from 9500–11 500 to 6000–7000, 4000 and 2500 boat-days, using daily cost estimates of $0, $500, $750, and $950, respectively. The zero daily cost corresponds to the MSY, while a daily cost of $750 most closely represents the actual present fishing cost. Given the recent debate on which costs should be factored into the analyses for deriving MEY, our findings highlight the importance of including an appropriate cost function for practical management advice. The approaches developed here could be applied to other multispecies fisheries where only aggregated fishing effort data are recorded, as the literature on this type of modelling is sparse.

Comprehensive Two-Dimensional Gas Chromatography: Instrumental and Methodological Development

Comprehensive two-dimensional gas chromatography (GC×GC) offers enhanced separation efficiency, reliability in qualitative and quantitative analysis, capability to detect low quantities, and information on the whole sample and its components. These features are essential in the analysis of complex samples, in which the number of compounds may be large or the analytes of interest are present at trace level. This study involved the development of instrumentation, data analysis programs and methodologies for GC×GC and their application in studies on qualitative and quantitative aspects of GC×GC analysis. Environmental samples were used as model samples. Instrumental development comprised the construction of three versions of a semi-rotating cryogenic modulator in which modulation was based on two-step cryogenic trapping with continuously flowing carbon dioxide as coolant. Two-step trapping was achieved by rotating the nozzle spraying the carbon dioxide with a motor. The fastest rotation and highest modulation frequency were achieved with a permanent magnetic motor, and modulation was most accurate when the motor was controlled with a microcontroller containing a quartz crystal. Heated wire resistors were unnecessary for the desorption step when liquid carbon dioxide was used as coolant. With use of the modulators developed in this study, the narrowest peaks were 75 ms at base. Three data analysis programs were developed allowing basic, comparison and identification operations. Basic operations enabled the visualisation of two-dimensional plots and the determination of retention times, peak heights and volumes. The overlaying feature in the comparison program allowed easy comparison of 2D plots. An automated identification procedure based on mass spectra and retention parameters allowed the qualitative analysis of data obtained by GC×GC and time-of-flight mass spectrometry. In the methodological development, sample preparation (extraction and clean-up) and GC×GC methods were developed for the analysis of atmospheric aerosol and sediment samples. Dynamic sonication assisted extraction was well suited for atmospheric aerosols collected on a filter. A clean-up procedure utilising normal phase liquid chromatography with ultra violet detection worked well in the removal of aliphatic hydrocarbons from a sediment extract. GC×GC with flame ionisation detection or quadrupole mass spectrometry provided good reliability in the qualitative analysis of target analytes. However, GC×GC with time-of-flight mass spectrometry was needed in the analysis of unknowns. The automated identification procedure that was developed was efficient in the analysis of large data files, but manual search and analyst knowledge are invaluable as well. Quantitative analysis was examined in terms of calibration procedures and the effect of matrix compounds on GC×GC separation. In addition to calibration in GC×GC with summed peak areas or peak volumes, simplified area calibration based on normal GC signal can be used to quantify compounds in samples analysed by GC×GC so long as certain qualitative and quantitative prerequisites are met. In a study of the effect of matrix compounds on GC×GC separation, it was shown that quality of the separation of PAHs is not significantly disturbed by the amount of matrix and quantitativeness suffers only slightly in the presence of matrix and when the amount of target compounds is low. The benefits of GC×GC in the analysis of complex samples easily overcome some minor drawbacks of the technique. The developed instrumentation and methodologies performed well for environmental samples, but they could also be applied for other complex samples.

Eurasian large mammal dynamics in response to changing environments during the Late Neogene

Nisäkkäiden levinneisyyteen, niiden morfologisiin ja ekologisiin piirteisiin vaikuttavat ympäristön sekä lyhyet että pitkäkestoiset muutokset, etenkin ilmaston ja kasvillisuuden vaihtelut. Työssä tutkittiin nisäkkäiden sopeutumista ilmastonmuutoksiin Euraasiassa viimeisen 24 miljoonan vuoden aikana. Tutkimuksessa keskityttiin varsinkin viimeiseen kahteen miljoonaan vuoteen, jonka aikana ilmasto muuttui voimakkaasti ja ihmisen toiminta alkoi tulla merkittäväksi. Tämän takia on usein vaikea erottaa, kummasta em. seikasta jonkin nisäkäslajin sukupuutto tai häviäminen alueelta johtui. Aineistona käytettiin laajaa venäjänkielistä kirjallisuutta, josta löytyvät tiedot ovat kääntämättöminä jääneet aiemmin länsimaisen tutkimuksen ulkopuolelle. Työssä käytettiin myös NOW-tietokantaa, jossa on fossiilisten nisäkkäiden löytöpaikat sekä niiden iät.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.