Exhaled breath condensate as a matrix for combustion-based nanoparticle exposure and health effect evaluation

Health assessment and medical surveillance of workers exposed to combustion nanoparticles are challenging. The aim was to evaluate the feasibility of using exhaled breath condensate (EBC) from healthy volunteers for (1) assessing the lung deposited dose of combustion nanoparticles and (2) determining the resulting oxidative stress by measuring hydrogen peroxide (H2O2) and malondialdehyde (MDA). Methods: Fifteen healthy nonsmoker volunteers were exposed to three different levels of sidestream cigarette smoke under controlled conditions. EBC was repeatedly collected before, during, and 1 and 2 hr after exposure. Exposure variables were measured by direct reading instruments and by active sampling. The different EBC samples were analyzed for particle number concentration (light-scattering-based method) and for selected compounds considered oxidative stress markers. Results: Subjects were exposed to an average airborne concentration up to 4.3×10(5) particles/cm(3) (average geometric size ∼60-80 nm). Up to 10×10(8) particles/mL could be measured in the collected EBC with a broad size distribution (50(th) percentile ∼160 nm), but these biological concentrations were not related to the exposure level of cigarette smoke particles. Although H2O2 and MDA concentrations in EBC increased during exposure, only H2O2 showed a transient normalization 1 hr after exposure and increased afterward. In contrast, MDA levels stayed elevated during the 2 hr post exposure. Conclusions: The use of diffusion light scattering for particle counting proved to be sufficiently sensitive to detect objects in EBC, but lacked the specificity for carbonaceous tobacco smoke particles. Our results suggest two phases of oxidation markers in EBC: first, the initial deposition of particles and gases in the lung lining liquid, and later the start of oxidative stress with associated cell membrane damage. Future studies should extend the follow-up time and should remove gases or particles from the air to allow differentiation between the different sources of H2O2 and MDA.

Genome-wide prediction of matrix attachment regions that increase gene expression in mammalian cells.

Gene transfer in eukaryotic cells and organisms suffers from epigenetic effects that result in low or unstable transgene expression and high clonal variability. Use of epigenetic regulators such as matrix attachment regions (MARs) is a promising approach to alleviate such unwanted effects. Dissection of a known MAR allowed the identification of sequence motifs that mediate elevated transgene expression. Bioinformatics analysis implied that these motifs adopt a curved DNA structure that positions nucleosomes and binds specific transcription factors. From these observations, we computed putative MARs from the human genome. Cloning of several predicted MARs indicated that they are much more potent than the previously known element, boosting the expression of recombinant proteins from cultured cells as well as mediating high and sustained expression in mice. Thus we computationally identified potent epigenetic regulators, opening new strategies toward high and stable transgene expression for research, therapeutic production or gene-based therapies.

Customer-Related Internal Communication in a Global Matrix Organization

The objective of the thesis was to explore the nature and characteristics of customer-related internal communication in a global industrial matrix organization during a specific customer relationship, and how it could be improved. The theoretical part of the study views the field of the concepts of intra-organizational information and knowledge sharing. The theoretical part also views the internal communications influences to customer relationships, its problematic, and the suggestions to improve internal communication in literature. The empirical part of the study was conducted with the Content Analysis and the Social Network Analysis as research methods. The data was collected by interviews and a questionnaire. Internal communication was observed first generally within the organization from the point of view of a certain business, and secondly, during a specific customer relationship at personal level and at departmental level. The results of the study describe the nature and characteristics of internal communication in the organization. The results give 13 suggestions for improving internal communication in the organization. Although the study has been done in one specific organization, it also offers insights for other organizations as well as managers to improve their internal communication.

The ESRg matrix for strong field d5 systems

This review has tried to collect and correlate all the various equations for the g matrix of strong field d5 systems obtained from different basis sets using full electron and hole formalism calculations. It has corrected mistakes found in the literature and shown how the failure to properly take in symmetry boundary conditions has produced a variety of apparently inconsistent equations in the literature. The review has reexamined the problem of spin-orbit interaction with excited t4e states and finds that the earlier reports that it is zero in octahedral symmetry is not correct. It has shown how redefining what x, y, and z are in the principal coordinate system simplifies, compared to previous methods, the analysis of experimental g values with the equations.

Methods for assessing the sustainability of integrated municipal waste management and

The general striving to bring down the number of municipal landfills and to increase the reuse and recycling of waste-derived materials across the EU supports the debates concerning the feasibility and rationality of waste management systems. Substantial decrease in the volume and mass of landfill-disposed waste flows can be achieved by directing suitable waste fractions to energy recovery. Global fossil energy supplies are becoming more and more valuable and expensive energy sources for the mankind, and efforts to save fossil fuels have been made. Waste-derived fuels offer one potential partial solution to two different problems. First, waste that cannot be feasibly re-used or recycled is utilized in the energy conversion process according to EU’s Waste Hierarchy. Second, fossil fuels can be saved for other purposes than energy, mainly as transport fuels. This thesis presents the principles of assessing the most sustainable system solution for an integrated municipal waste management and energy system. The assessment process includes: · formation of a SISMan (Simple Integrated System Management) model of an integrated system including mass, energy and financial flows, and · formation of a MEFLO (Mass, Energy, Financial, Legislational, Other decisionsupport data) decision matrix according to the selected decision criteria, including essential and optional decision criteria. The methods are described and theoretical examples of the utilization of the methods are presented in the thesis. The assessment process involves the selection of different system alternatives (process alternatives for treatment of different waste fractions) and comparison between the alternatives. The first of the two novelty values of the utilization of the presented methods is the perspective selected for the formation of the SISMan model. Normally waste management and energy systems are operated separately according to the targets and principles set for each system. In the thesis the waste management and energy supply systems are considered as one larger integrated system with one primary target of serving the customers, i.e. citizens, as efficiently as possible in the spirit of sustainable development, including the following requirements: · reasonable overall costs, including waste management costs and energy costs; · minimum environmental burdens caused by the integrated waste management and energy system, taking into account the requirement above; and · social acceptance of the selected waste treatment and energy production methods. The integrated waste management and energy system is described by forming a SISMan model including three different flows of the system: energy, mass and financial flows. By defining the three types of flows for an integrated system, the selected factor results needed in the decision-making process of the selection of waste management treatment processes for different waste fractions can be calculated. The model and its results form a transparent description of the integrated system under discussion. The MEFLO decision matrix has been formed from the results of the SISMan model, combined with additional data, including e.g. environmental restrictions and regional aspects. System alternatives which do not meet the requirements set by legislation can be deleted from the comparisons before any closer numerical considerations. The second novelty value of this thesis is the three-level ranking method for combining the factor results of the MEFLO decision matrix. As a result of the MEFLO decision matrix, a transparent ranking of different system alternatives, including selection of treatment processes for different waste fractions, is achieved. SISMan and MEFLO are methods meant to be utilized in municipal decision-making processes concerning waste management and energy supply as simple, transparent and easyto- understand tools. The methods can be utilized in the assessment of existing systems, and particularly in the planning processes of future regional integrated systems. The principles of SISMan and MEFLO can be utilized also in other environments, where synergies of integrating two (or more) systems can be obtained. The SISMan flow model and the MEFLO decision matrix can be formed with or without any applicable commercial or free-of-charge tool/software. SISMan and MEFLO are not bound to any libraries or data-bases including process information, such as different emission data libraries utilized in life cycle assessments.

Advanced chemometric methods: Applicability on industrial data

Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

Evaluation of sample processing methods for the polar contaminant analysis of sewage sludge using liquid chromatography - mass spectrometry (LC/MS)

Monitoring of sewage sludge has proved the presence of many polar anthropogenic pollutants since LC/MS techniques came into routine use. While advanced techniques may improve characterizations, flawed sample processing procedures, however, may disturb or disguise the presence and fate of many target compounds present in this type of complex matrix before analytical process starts. Freeze-drying or oven-drying, in combination with centrifugation or filtration as sample processing techniques were performed followed by visual pattern recognition of target compounds for assessment of pretreatment processes. The results shown that oven-drying affected the sludge characterization, while freeze-drying led to less analytical misinterpretations.

Comparison of USEPA 3050B and ISO 14869-1: 2001 digestion methods for sediment analysis by using FAAS and ICP-OES quantification techniques

A study of the partial USEPA 3050B and total ISO 14869-1:2001 digestion methods of sediments was performed. USEPA 3050B was recommended as the simpler method with less operational risk. However, the extraction ability of the method should be taken in account for the best environmental interpretation of the results. FAAS was used to quantify metal concentrations in sediment solutions. The alternative use of ICP-OES quantification should be conditioned by a previous detailed investigation and eventual correction of the matrix effect. For the first time, the EID method was employed for the detection and correction of the matrix effect in sediment ICP-OES analysis. Finally, some considerations were made about the level of metal contamination in the area under study.

Development and validation of a dissolution test for primaquine/polyethylene oxide matrix tablets

A simple, precise, specific, repeatable and discriminating dissolution test for primaquine (PQ) matrix tablets was developed and validated according to ICH and FDA guidelines. Two UV assaying methods were validated for determination of PQ released in 0.1 M hydrochloric acid and water media. Both methods were linear (R²>0.999), precise (R.S.D.<1.87%) and accurate (97.65-99.97%). Dissolution efficiency (69-88%) and equivalence of formulations (f2) was assessed in different media and apparatuses (basket/100 rpm and paddle/50 rpm) tested. Discriminating condition was 900 mL aqueous medium, basket at 100 rpm and sampling times at 1, 4 and 8 h. Repeatability (R.S.D.<2.71%) and intermediate precision (R.S.D.<2.06%) of dissolution method were satisfactory.

Cat's claw oxindole alkaloid isomerization induced by common extraction methods

Cat's claw oxindole alkaloids are prone to isomerization in aqueous solution. However, studies on their behavior in extraction processes are scarce. This paper addressed the issue by considering five commonly used extraction processes. Unlike dynamic maceration (DM) and ultrasound-assisted extraction, substantial isomerization was induced by static maceration, turbo-extraction and reflux extraction. After heating under reflux in DM, the kinetic order of isomerization was established and equations were fitted successfully using a four-parameter Weibull model (R² > 0.999). Different isomerization rates and equilibrium constants were verified, revealing a possible matrix effect on alkaloid isomerization.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

First dice your dill – new methods and techniques in sample handling

This book is dedicated to celebrate the 60th birthday of Professor Rainer Huopalahti. Professor Rainer “Repe” Huopalahti has had, and in fact is still enjoying a distinguished career in the analysis of food and food related flavor compounds. One will find it hard to make any progress in this particular field without a valid and innovative sample handling technique and this is a field in which Professor Huopalahti has made great contributions. The title and the front cover of this book honors Professor Huopahti’s early steps in science. His PhD thesis which was published on 1985 is entitled “Composition and content of aroma compounds in the dill herb, Anethum graveolens L., affected by different factors”. At that time, the thesis introduced new technology being applied to sample handling and analysis of flavoring compounds of dill. Sample handling is an essential task that in just about every analysis. If one is working with minor compounds in a sample or trying to detect trace levels of the analytes, one of the aims of sample handling may be to increase the sensitivity of the analytical method. On the other hand, if one is working with a challenging matrix such as the kind found in biological samples, one of the aims is to increase the selectivity. However, quite often the aim is to increase both the selectivity and the sensitivity. This book provides good and representative examples about the necessity of valid sample handling and the role of the sample handling in the analytical method. The contributors of the book are leading Finnish scientists on the field of organic instrumental analytical chemistry. Some of them are also Repe’ s personal friends and former students from the University of Turku, Department of Biochemistry and Food Chemistry. Importantly, the authors all know Repe in one way or another and are well aware of his achievements on the field of analytical chemistry. The editorial team had a great time during the planning phase and during the “hard work editorial phase” of the book. For example, we came up with many ideas on how to publish the book. After many long discussions, we decided to have a limited edition as an “old school hard cover book” – and to acknowledge more modern ways of disseminating knowledge by publishing an internet version of the book on the webpages of the University of Turku. Downloading the book from the webpage for personal use is free of charge. We believe and hope that the book will be read with great interest by scientists working in the fascinating field of organic instrumental analytical chemistry. We decided to publish our book in English for two main reasons. First, we believe that in the near future, more and more teaching in Finnish Universities will be delivered in English. To facilitate this process and encourage students to develop good language skills, it was decided to be published the book in English. Secondly, we believe that the book will also interest scientists outside Finland – particularly in the other member states of the European Union. The editorial team thanks all the authors for their willingness to contribute to this book – and to adhere to the very strict schedule. We also want to thank the various individuals and enterprises who financially supported the book project. Without that support, it would not have been possible to publish the hardcover book.

Comparison measures of maps generated by geostatistical methods

This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.

A platform for anti-biofilm assays combining viability, biomass and matrix quantifications in susceptibility assessments of antimicrobials against Staphylococcus aureus biofilms

Bacteria can exist as planktonic, the lifestyle in which single cells exist in suspension, and as biofilms, which are surface-attached bacterial communities embedded in a selfproduced matrix. Most of the antibiotics and the methods for antimicrobial work have been developed for planktonic bacteria. However, the majority of the bacteria in natural habitats live as biofilms. Biofilms develop dauntingly fast high resistance towards conventional antibacterial treatments and thus, there is a great need to meet the demands of effective anti-biofilm therapy. In this thesis project it was attempted to fill the void of anti-biofilm screening methods by developing a platform of assays that evaluate the effect that screened compounds have on the total biomass, viability and the extracellular polysaccharide (EPS) layer of the biofilms. Additionally, a new method for studying biofilms and their interactions with compounds in a continuous flow system was developed using capillary electrochromatography (CEC). The screening platform was utilized with a screening campaign using a small library of cinchona alkaloids. The assays were optimized to be statistically robust enough for screening. The first assay, based on crystal violet staining, measures total biofilm biomass, and it was automated using a liquid handling workstation to decrease the manual workload and signal variation. The second assay, based on resazurin staining, measures viability of the biofilm, and it was thoroughly optimized for the strain used, but was then a very simple and fast method to be used for primary screening. The fluorescent resazurin probe is not toxic to the biofilms. In fact, it was also shown in this project that staining the biofilms with resazurin prior to staining with crystal violet had no effect on the latter and they can be used in sequence on the same screening plate. This sequential addition step was indeed a major improvement on the use of reagents and consumables and also shortened the work time. As a third assay in the platform a wheat germ agglutinin based assay was added to evaluate the effect a compound has on the EPS layer. Using this assay it was found that even if compounds might have clear effect on both biomass and viability, the EPS layer can be left untouched or even be increased. This is a clear implication of the importance of using several assays to be able to find “true hits” in a screening setting. In the pilot study of screening for antimicrobial and anti-biofilm effects using a cinchona alkaloid library, one compound was found to have antimicrobial effect against planktonic bacteria and prevent biofilm formation at low micromolar concentration. To eradicate biofilms, a higher concentration was needed. It was also shown that the chemical space occupied by the active compound was slightly different than the rest of the cinchona alkaloids as well as the rest of the compounds used for validatory screening during the optimization processes of the separate assays.

Immunohistochemical evaluation of fibrillar components of the extracellular matrix of transversalis fascia and anterior abdominal rectus sheath in men with inguinal hernia

OBJECTIVE: to evaluate the role of fibrillar extracellular matrix components in the pathogenesis of inguinal hernias. METHODS: samples of the transverse fascia and of the anterior sheath of the rectus abdominis muscle were collected from 40 men aged between 20 and 60 years with type II and IIIA Nyhus inguinal hernia and from 10 fresh male cadavers (controls) without hernia in the same age range. The staining technique was immunohistochemistry for collagen I, collagen III and elastic fibers; quantification of fibrillar components was performed with an image analysis processing software. RESULTS: no statistically significant differences were found in the amount of elastic fibers, collagen I and collagen III, and the ratio of collagen I / III among patients with inguinal hernia when compared with subjects without hernia. CONCLUSION: the amount of fibrillar extracellular matrix components did not change in patients with and without inguinal hernia.