The Effect of Cigarette Smoking on Diabetic Peripheral Neuropathy: A Systematic Review and Meta-Analysis.

OBJECTIVE: Studies suggest that smoking may be a risk factor for the development of microvascular complications such as diabetic peripheral neuropathy (DPN). The objective of this study was to assess the relationship between smoking and DPN in persons with type 1 or type 2 diabetes. RESEARCH DESIGN AND METHODS: A systematic review of the PubMed, Embase, and Cochrane clinical trials databases was conducted for the period from January 1966 to November 2014 for cohort, cross-sectional and case-control studies that assessed the relationship between smoking and DPN. Separate meta-analyses for prospective cohort studies and case-control or cross-sectional studies were performed using random effects models. RESULTS: Thirty-eight studies (10 prospective cohort and 28 cross-sectional) were included. The prospective cohort studies included 5558 participants without DPN at baseline. During follow-up ranging from 2 to 10 years, 1550 cases of DPN occurred. The pooled unadjusted odds ratio (OR) of developing DPN associated with smoking was 1.26 (95% CI 0.86-1.85; I(2) = 74%; evidence grade: low strength). Stratified analyses of the prospective studies revealed that studies of higher quality and with better levels of adjustment and longer follow-up showed a significant positive association between smoking and DPN, with less heterogeneity. The cross-sectional studies included 27,594 participants. The pooled OR of DPN associated with smoking was 1.42 (95% CI 1.21-1.65; I(2) = 65%; evidence grade: low strength). There was no evidence of publication bias. CONCLUSIONS: Smoking may be associated with an increased risk of DPN in persons with diabetes. Further studies are needed to test whether this association is causal and whether smoking cessation reduces the risk of DPN in adults with diabetes.

The vertical dimension of social relations and accurate interpersonal perception: A meta-analysis (Publishd online: 24 Oct. 2014)

There is little consensus regarding how verticality (social power, dominance, and status) is related to accurate interpersonal perception. The relation could be either positive or negative, and there could be many causal processes at play. The present article discusses the theoretical possibilities and presents a meta-analysis of this question. In studies using a standard test of interpersonal accuracy, higher socioeconomic status (SES) predicted higher accuracy defined as accurate inference about the meanings of cues; also, higher experimentally manipulated vertical position predicted higher accuracy defined as accurate recall of others' words. In addition, although personality dominance did not predict accurate inference overall, the type of personality dominance did, such that empathic/responsible dominance had a positive relation and egoistic/aggressive dominance had a negative relation to accuracy. In studies involving live interaction, higher experimentally manipulated vertical position produced lower accuracy defined as accurate inference about cues; however, methodological problems place this result in doubt.

Tracing the associations between sex, the atypical and the combined atypical-melancholic depression subtypes: A path analysis.

BACKGROUND: Numerous studies have examined determinants leading to preponderance of women in major depressive disorder (MDD), which is particularly accentuated for the atypical depression subtype. It is thus of interest to explore the specific indirect effects influencing the association between sex and established depression subtypes. METHODS: The data of 1624 subjects with a lifetime diagnosis of MDD derived from the population-based PsyCoLaus data were used. An atypical (n=256), a melancholic (n=422), a combined atypical and melancholic features subtype (n=198), and an unspecified MDD group (n=748) were constructed according to the DSM-IV specifiers. Path models with direct and indirect effects were applied to the data. RESULTS: Partial mediation of the female-related atypical and combined atypical-melancholic depression subtypes was found. Early anxiety disorders and high emotion-orientated coping acted as mediating variables between sex and the atypical depression subtype. In contrast, high Body Mass Index (BMI) served as a suppression variable, also concerning the association between sex and the combined atypical-melancholic subtype. The latter association was additionally mediated by an early age of MDD onset and early/late anxiety disorders. LIMITATIONS: The use of cross-sectional data does not allow causal conclusions. CONCLUSIONS: This is the first study that provides evidence for a differentiation of the general mechanisms explaining sex differences of overall MDD by depression subtypes. Determinants affecting the pathways begin early in life. Since some of them are primarily of behavioral nature, the present findings could be a valuable target in mental health care.

Effect of Smoking on Blood Pressure and Resting Heart Rate: A Mendelian Randomization Meta-Analysis in the CARTA Consortium.

BACKGROUND: Smoking is an important cardiovascular disease risk factor, but the mechanisms linking smoking to blood pressure are poorly understood. METHODS AND RESULTS: Data on 141 317 participants (62 666 never, 40 669 former, 37 982 current smokers) from 23 population-based studies were included in observational and Mendelian randomization meta-analyses of the associations of smoking status and smoking heaviness with systolic and diastolic blood pressure, hypertension, and resting heart rate. For the Mendelian randomization analyses, a genetic variant rs16969968/rs1051730 was used as a proxy for smoking heaviness in current smokers. In observational analyses, current as compared with never smoking was associated with lower systolic blood pressure and diastolic blood pressure and lower hypertension risk, but with higher resting heart rate. In observational analyses among current smokers, 1 cigarette/day higher level of smoking heaviness was associated with higher (0.21 bpm; 95% confidence interval 0.19; 0.24) resting heart rate and slightly higher diastolic blood pressure (0.05 mm Hg; 95% confidence interval 0.02; 0.08) and systolic blood pressure (0.08 mm Hg; 95% confidence interval 0.03; 0.13). However, in Mendelian randomization analyses among current smokers, although each smoking increasing allele of rs16969968/rs1051730 was associated with higher resting heart rate (0.36 bpm/allele; 95% confidence interval 0.18; 0.54), there was no strong association with diastolic blood pressure, systolic blood pressure, or hypertension. This would suggest a 7 bpm higher heart rate in those who smoke 20 cigarettes/day. CONCLUSIONS: This Mendelian randomization meta-analysis supports a causal association of smoking heaviness with higher level of resting heart rate, but not with blood pressure. These findings suggest that part of the cardiovascular risk of smoking may operate through increasing resting heart rate.

Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.

Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.

Statistical Analysis of an SEIR Epidemic Model

This thesis was focussed on statistical analysis methods and proposes the use of Bayesian inference to extract information contained in experimental data by estimating Ebola model parameters. The model is a system of differential equations expressing the behavior and dynamics of Ebola. Two sets of data (onset and death data) were both used to estimate parameters, which has not been done by previous researchers in (Chowell, 2004). To be able to use both data, a new version of the model has been built. Model parameters have been estimated and then used to calculate the basic reproduction number and to study the disease-free equilibrium. Estimates of the parameters were useful to determine how well the model fits the data and how good estimates were, in terms of the information they provided about the possible relationship between variables. The solution showed that Ebola model fits the observed onset data at 98.95% and the observed death data at 93.6%. Since Bayesian inference can not be performed analytically, the Markov chain Monte Carlo approach has been used to generate samples from the posterior distribution over parameters. Samples have been used to check the accuracy of the model and other characteristics of the target posteriors.

Statistical Analysis and Numerics of Heat Exchanger Models

The identifiability of the parameters of a heat exchanger model without phase change was studied in this Master’s thesis using synthetically made data. A fast, two-step Markov chain Monte Carlo method (MCMC) was tested with a couple of case studies and a heat exchanger model. The two-step MCMC-method worked well and decreased the computation time compared to the traditional MCMC-method. The effect of measurement accuracy of certain control variables to the identifiability of parameters was also studied. The accuracy used did not seem to have a remarkable effect to the identifiability of parameters. The use of the posterior distribution of parameters in different heat exchanger geometries was studied. It would be computationally most efficient to use the same posterior distribution among different geometries in the optimisation of heat exchanger networks. According to the results, this was possible in the case when the frontal surface areas were the same among different geometries. In the other cases the same posterior distribution can be used for optimisation too, but that will give a wider predictive distribution as a result. For condensing surface heat exchangers the numerical stability of the simulation model was studied. As a result, a stable algorithm was developed.

MCMC Analysis Of Classical Time Series Algorithms

Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.

Analysis of Patterns in Electricity Spot Market Time Series

Due to its non-storability, electricity must be produced at the same time that it is consumed, as a result prices are determined on an hourly basis and thus analysis becomes more challenging. Moreover, the seasonal fluctuations in demand and supply lead to a seasonal behavior of electricity spot prices. The purpose of this thesis is to seek and remove all causal effects from electricity spot prices and remain with pure prices for modeling purposes. To achieve this we use Qlucore Omics Explorer (QOE) for the visualization and the exploration of the data set and Time Series Decomposition method to estimate and extract the deterministic components from the series. To obtain the target series we use regression based on the background variables (water reservoir and temperature). The result obtained is three price series (for Sweden, Norway and System prices) with no apparent pattern.

Analysis of the structure and vibrational spectra of glucose and fructose

Molecular modelling using semiempirical methods AM1, PM3, PM5 and, MINDO as well as the Density Functional Theory method BLYP/DZVP respectively were used to calculate the structure and vibrational spectra of d-glucose and d-fructose in their open chain, alpha-anomer and beta-anomer monohydrate forms. The calculated data show that both molecules are not linear; ground state and the number for the point-group C is equal to 1. Generally, the results indicate that there are similarities in bond lengths and vibrational modes of both molecules. It is concluded that DFT could be used to study both the structural and vibrational spectra of glucose and fructose.

Cuticular and Suberin Polymers of Edible Plants. Analysis by Gas Chromatographic-Mass Spectrometric and Solid State Spectroscopic Methods

Cutin and suberin are structural and protective polymers of plant surfaces. The epidermal cells of the aerial parts of plants are covered with an extracellular cuticular layer, which consists of polyester cutin, highly resistant cutan, cuticular waxes and polysaccharides which link the layer to the epidermal cells. A similar protective layer is formed by a polyaromatic-polyaliphatic biopolymer suberin, which is present particularly in the cell walls of the phellem layer of periderm of the underground parts of plants (e.g. roots and tubers) and the bark of trees. In addition, suberization is also a major factor in wound healing and wound periderm formation regardless of the plants’ tissue. Knowledge of the composition and functions of cuticular and suberin polymers is important for understanding the physiological properties for the plants and for nutritional quality when these plants are consumed as foods. The aims of the practical work were to assess the chemical composition of cuticular polymers of several northern berries and seeds and suberin of two varieties of potatoes. Cutin and suberin were studied as isolated polymers and further after depolymerization as soluble monomers and solid residues. Chemical and enzymatic depolymerization techniques were compared and a new chemical depolymerization method was developed. Gas chromatographic analysis with mass spectrometric detection (GC-MS) was used to assess the monomer compositions. Polymer investigations were conducted with solid state carbon-13 cross polarization magic angle spinning nuclear magnetic resonance spectroscopy (13C CP-MAS NMR), Fourier transform infrared spectroscopy (FTIR) and microscopic analysis. Furthermore, the development of suberin over one year of post-harvest storage was investigated and the cuticular layers from berries grown in the North and South of Finland were compared. The results show that the amounts of isolated cuticular layers and cutin monomers, as well as monomeric compositions vary greatly between the berries. The monomer composition of seeds was found to differ from the corresponding berry peel monomers. The berry cutin monomers were composed mostly of long-chain aliphatic ω-hydroxy acids, with various mid-chain functionalities (double-bonds, epoxy, hydroxy and keto groups). Substituted α,ω-diacids predominated over ω-hydroxy acids in potato suberin monomers and slight differences were found between the varieties. The newly-developed closed tube chemical method was found to be suitable for cutin and suberin analysis and preferred over the solvent-consuming and laborious reflux method. Enzymatic hydrolysis with cutinase was less effective than chemical methanolysis and showed specificity towards α,ω-diacid bonds. According to ₁₃C CP-MAS NMR and FTIR, the depolymerization residues contained significant amounts of aromatic structures, polysaccharides and possible cutan-type aliphatic moieties. Cultivation location seems to have effect on cuticular composition. The materials studied contained significant amounts of different types of biopolymers that could be utilized for several purposes with or without further processing. The importance of the so-called waste material from industrial processes of berries and potatoes as a source of either dietary fiber or specialty chemicals should be further investigated in detail. The evident impact of cuticular and suberin polymers, among other fiber components, on human health should be investigated in clinical trials. These by-product materials may be used as value-added fiber fractions in the food industry and as raw materials for specialty chemicals such as lubricants and emulsifiers, or as building blocks for novel polymers.

Strategic supply chain alignment to customer buying behavior

In search for competitive advantage, designing and managing supply chain networks have become a necessary competence for organizations. The target of this thesis is to answer a question, how to design a multiple supply chain network. The purpose is to study, what kind of different supply chain designs exist and, how to choose appropriate supply chain designs for a company. In the thesis, the focus is on the supply chain alignment to customers, more specifically to customer buying behavior. The research method was a case study. A framework for measuring customer buying behavior was developed based on the literature and it was used in the study of customer buying behavior in the case environment. In the case company structured interviews and data records were used as sources of evidence. Persons working in the customer-interface were interviewed face-to-face and through an e-mail questionnaire. When analyzing the data, a Quality function deployment matrix was used as one analysis method. As a result of the thesis, supply chain network of the case company is proposed to be divided into three separate supply chains, which focus on different areas and they could be called lean, agile and continuous replenishment supply chains. In conclusion, in the supply chain alignment to customer buying behavior several aspects have to be studied from different perspectives. According to the results, a multiple supply chain strategy is recommended to be implemented in the case company, since the diversity of the customer needs cannot be managed efficiently through a single supply chain.

Spare part business analysis and development

The purpose of this Thesis was to comprehensively analyze and develop the spare part business in Company Oy’s five biggest product groups by searching development issues related to single spare parts’ supply chains as well as the spare part business process, make implementation plans for them and implement the plans when possible. The items were classified based on special characteristics of spare parts and on their actual sales volumes. The created item classes were examined for finding improvement possibilities. Management strategies for classified items were suggested. Vendors and customers were analyzed for supporting the comprehensive supply network development work. The effectiveness of the current spare part business process was analyzed in co-operation with the spare part teams in three business unit locations. Several items were taken away from inventories as uselessly stocked items. Price list related to core items with one of the main product group’s core item manufacturer was suggested to be expanded in Town A. Refinement equipment seal item supply chain management was seen important to develop in Town B. A new internal business process model was created for minimizing and enhancing the internal business between Company’s business units. SAP inventory reports and several other features were suggested to be changed or developed. Also the SAP data material management was seen very important to be developed continuously. Many other development issues related to spare parts’ supply chains and the work done in the business process were found. The need for investigating the development possibilities deeper became very clear during the project.

Working capital management in the value chain of automotive industry

The objective of this Master’s thesis is to examine working capital management in the automotive industry in years 2006-2008. The study is conducted by the analysis of financial statements. The sample consists of 65 companies that represent different stages in the value chain of automotive industry beginning from raw material suppliers and ending to car dealers. Working capital management is studied by the cash conversion cycle (CCC). The results show that the average CCC of the value chain is 67 days. Car manufacturers had the longest CCC, 106 days, whereas the CCC of oil companies was the shortest, 22 days. The findings suggest that the cycle time of working capital usually follows the cycle time of inventories, since the changes in cycle times of accounts receivable and payable compensate each other. Improvements in working capital management could be achieved by sharing more accurate information in the chain for example about inventory levels and order points of customer. It could also be discussed within the automotive industry, if the long credit periods, which tie up working capital, are really needed. New technologies enable faster payments, which would reduce the cash conversion cycles, improve the profitability of companies, and increase the competitiveness of the value chain. Working capital should not be reduced at the expense of value chain partners, because nowadays the competition is rather between the value chains than between the companies. Similar research design is applied earlier to study working capital management in the value chain of pulp and paper industry. Even if the industries and the structures of the chains differ from each other, results were surprisingly similar. In future research, working capital management in other industries’ value chains could still be studied and compared to previous studies. ICT industry, for example, could be an interesting object.

Customer relationship management through life cycle analysis, case professional service firm in B2B market

The objective of this master’s thesis was to study how customer relationships should be assessed and categorized in order to support customer relationship management (CRM) in the context of business-to-business (B2B) and professional services. This sophisticated and complex market is utilizing possibilities of CRM only rarely and even then the focus is often on technology. The theoretical part considered first CRM from the value chain point of view and then discussed the cyclical nature of relationships. The case study focused on B2B professional service firm. The data was collected from company databases and included the sample of 90 customers. The research was conducted in three phases first studying the age, then the service type of relationships and finally executing the cluster analysis. The data was analysed by statistical analysis program SAS Enterprise Guide. The results indicate that there are great differences between developments of customer relationships. While some relationships are dynamically growing and changing, most of customers are remaining constant. This implies expectations and requirements of customers are similarly divergent and relationships should be managed accordingly.