Objective 1 was to investigate effects of heat stress and breed on milk and component yield for Holstein and Jersey cows on the same farm. Objective 2 was to determine the effects of breed on udder health as measured by somatic cell count (SCC) during times of heat stress. Data were collected from DHIA records of 142 Jersey cows and 586 Holstein cows from the University herd at Mississippi State University. During heat stress Jersey milk yield and 4% fat corrected milk (FCM) increased (P<0.01). Holstein milk yield and FCM decreased during heat stress (P<0.01). Heat stress affected somatic cell count (SCC) although effects varied by intensity of heat stress. Breed did not have an affect on SCC. Milk fat and protein percentages declined for both breeds in heat stress conditions. Milk fat but not milk protein of Jersey cows increased as stress increased from mild to severe.

In this episode, we visit some ancient Sumerians so we can expand our view of finger counting and see how this applies to counting with transistors. From this, we will have the basis for unsigned binary integers and the humble binary digit or bit. We also show how to calculate the upper limit to which a fixed number of transistors can count.

The evaluation of policy-relevant economic research requires an ethical foundation. Classical liberal theory provides the requisite foundation for this dissertation, which uses various econometric tools to estimate the effects of shifting some of the property tax from buildings to land in 15 cities in Pennsylvania. Economic theory predicts that such a shift will lead to higher building activity. However, this prediction has been supported little by empirical evidence so far. The first part of the dissertation examines the effect of the land-building tax differential on the number of building permits that were issued in 219 municipalities in Pennsylvania between 1972 and 1994. For such count data a conventional analysis based on a continuous distribution leads to incorrect results; a discrete maximum likelihood analysis with a negative binomial distribution is more appropriate. Two models, a non-linear and a fixed effects model, are developed to examine the influence of the tax differential. Both models suggest that this influence is positive, albeit not statistically significant. Application of maximum likelihood techniques is computationally cumbersome if the assumed distribution of the data cannot be written in closed form. The negative binomial distribution is the only discrete distribution with a variance that is larger than its mean that can easily be applied, although it might not be the best approximation of the true distribution of the data. The second part of the dissertation uses a Markov Chain Monte Carlo method to examine the influence of the tax differential on the number of building permits, under the assumption that building permits are generated by a Poisson process whose parameter varies lognormally. Contrary to the analysis in the first part, the tax is shown to have a strong and significantly positive impact on the number of permits. The third part of the dissertation uses a fixed-effects weighted least squares method to estimate the effect of the tax differential on the value per building permit. The tax coefficient is not significantly different from zero. Still, the overall impact of the tax differential on the total value of construction is shown to be positive and statistically significant. / Ph. D.

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Analyses based upon rank correlation methods, such as Spearman's Rho and Kendall's Tau, can provide quick insights into large biological data sets. Comparing expression levels between different technologies and models is problematic due to the different units of measure. Here again, rank correlation provides an effective means of comparison between the two techniques. Massively Parallel Signature Sequencing (MPSS) transcript abundance levels to microarray signal intensities for Arabidopsis thaliana are compared. Rank correlations can be applied to subsets as well as the entire set. Results of subset comparisons can be used to improve the capabilities of predictive models, such as Predicted Highly Expressed (PHX). This is done for Escherichia coli. Methods are given to combine predictive models based upon feedback from experimental data. The problem of feature selection in supervised learning situations is also considered, where all features are drawn from a common domain and are best interpreted via ordinal comparisons with other features, rather than as numerical values. This is done for synthetic data as well as for microarray experiments examining the life cycle of Drosophila melanogaster and human leukemia cells. Two novel methods are presented based upon Rho and Tau, and their efficacy is tested with synthetic and real world data. The method based upon Spearman's Rho is shown to be more effective. / Ph. D.

There is increasing evidence indicating that exposure to air pollutants may be associated with the onset of several respiratory diseases such as allergic airway disease and chronic obstructive pulmonary disorder (COPD). Many lung diseases demonstrate an outgrowth of pathogenic bacteria belonging to the Proteobacteria phylum, and the incidence of occurrence of these diseases is higher in heavily polluted regions. Within the human body, the lungs are among the first to be exposed to the harmful effects of inhaled pollutants and microbes. Research in the past few decades have expounded on the air-pollution-induced local and systemic inflammatory responses, but the involvement of the lung microbial communities has not yet been well-characterized. Lungs were historically considered to be sterile, but recent advances have demonstrated that the lower respiratory tract is replete with a wide variety of microorganisms - both in health and disease. Recent studies show that these lung microbes may play a significant role in modulating the immune environment by inducing IgA and mucus production. Air pollutants have previously been shown to alter intestinal bacterial populations that increase susceptibility to inflammatory diseases; however, to date, the effects of traffic-generated air pollutants on the resident microbial communities on the lungs have not been explored. The microbiome is influenced by several factors, including diet and environmental exposures. A large percentage of the Western world population consumes a high-fat (HF) diet which has resulted in the epidemic of obesity. Consumption of an HF diet has been shown to alter the intestinal microflora and increase baseline inflammation. We aimed to understand whether diet might also contribute to the alteration of the commensal lung microbiome, either alone or related to exposure. Thus, we investigated the hypothesis that exposure to air pollutants can alter the commensal lung microbiota, thereby promoting alterations in the lung's immune and inflammatory responses; in addition to determining whether these outcomes are exacerbated by a high fat-diet. We performed two studies with exposures to different components of air pollutant mixtures on C57Bl/6 mice placed on either a control (LF) diet or a high-fat (HF) diet. Our first exposure study was performed on C57Bl/6 mice with a mixture of gasoline and diesel engine emissions (ME: 30 µg PM/m3 gasoline engine emissions + 70 µg PM/m3 diesel engine emissions) or filtered air (FA) for 6h/d, 7 d/wk for 30 days. The ME study investigated the alterations in immunoglobulin A (IgA), IgG and IgM, and lung microbiota abundance and diversity. Our results revealed ME exposures alongside the HF diet causes a decrease in IgA and IgG when compared to FA controls, thereby decreasing airway barrier protection. This was accompanied by the expansion of bacteria within the Proteobacteria phylum and a decrease in the overall bacterial diversity and richness in the exposed vs. control groups. In our second study, we exposed C57Bl/6 mice to only the diesel exhaust particle component (35µg DEP, suspended in 35µl 0.9% sterile saline) or sterile saline only (control) twice a week for 30 days. We investigated immunoglobulin profiles by ELISA that revealed a significant increase in IgA and IgG in response to DEP. We also observed an increase in inflammatory tumor necrosis factor (TNF) - α, Interleukin (IL) -10, Toll-like receptors (TLR) - 2,4, nuclear factor kappa B (NF-κB) histologically and by RT-qPCR. Mucus production and collagen deposition within the lungs were also significantly elevated with DEP exposures. Microbial abundance determined quantitatively from the bronchoalveolar lavage fluid (BALF) by qPCR revealed an expansion of bacteria belonging to the Proteobacteria phylum in the DEP exposed groups on the HF diet. We also observed an increase in reactive oxygen and nitrogen species (ROS-RNS) products (nitrates), within the groups that revealed an expansion of Proteobacteria. These observations are most likely due to the unique metabolic capabilities of Proteobacteria to proliferate in inflammatory environments with excess nitrates. We assessed if treatments with probiotics could attenuate the DEP-induced inflammation by supplementing a separate group of study animals on the HF diet with 0.3 g/day of Winclove Ecologic® Barrier probiotics in their drinking water throughout the study. With probiotic treatments, we observed a significant decrease in ROS-RNS that was accompanied by complete elimination of Proteobacteria suggesting that in the absence of nitrates, the expansion of Proteobacteria is curbed effectively. We also observed a decrease in proinflammatory TNF-α and collagen deposition with probiotic treatments, and an increase in IgA levels within the BALF, suggesting that probiotics aid in balancing proinflammatory responses and enhance beneficial immune responses to efficiently mediate the DEP-induced inflammation. Both studies showed that air pollutants alter the immune defenses and contribute to lung microbial alterations with an expansion of Proteobacteria. The immunoglobulin profiles discordant between the two studies can be explained by the route and/or duration and composition of air pollutant exposure. Collectively these studies suggest that exposure to air pollutants alter immune responses and/or increase the availability of inflammatory by-products within the lungs that can enable the selective outgrowth of pathogenic bacteria. The observed detrimental outcomes are further exacerbated when coupled with the consumption of an HF diet. Importantly, these results may shed light on the missing link between air pollution-induced inflammation and bacterial expansion and also point to therapeutic alternatives to curb bacterial outgrowth in lung disease exacerbations observed in patient populations living and/or working in heavily polluted regions.

Vårdrelaterade infektioner (VRI) är ett ökande problem inom hälso- och sjukvården. På neonatalavdelningen på Länssjukhuset Ryhov i Jönköping har det förekommit inkonsekventa odlingsresultat vid misstänkt VRI orsakad av Staphylococcus aureus. Att förebygga VRI samt värna om patientsäkerheten kräver känsliga och pålitliga laboratorieanalyser. Syftet med studien var att bestämma och jämföra lägsta detektionsintervall för metoderna odling och qPCR med och utan anrikning i MAMSA-buljong, av S. aureus. Seriespädningar av S. aureus tillreddes och koncentrationer för ursprungsrören uträknades via viable count (VC). Odling på blodagar samt qPCR med och utan anrikning i MAMSA-buljong utfördes. Resultaten användes för att bestämma ett lägsta detektionsintervall. Odling gav ett lägsta detektionsintervall mellan 0,5–62 CFU/ml, och qPCR mellan 6400–140 000 CFU/ml. Anrikning med MAMSA-buljong innan qPCR-analys gav ett lägsta detektionsintervall mellan 0,6–140 CFU/ml. För detektion via odling räcker enstaka till tiotals CFU/ml i analysprovet. Vid qPCR behövs tusentals till hundratusentals CFU/ml i analysprovet, men vid qPCR med MAMSA-anrikning kan detektionsintervallet sänkas till nivåer jämförbara med odling. För att kunna applicera studiens resultat på den laborativa verksamheten krävs vidare studier med fler bakteriearter och replikat. / Hospital-acquired infections (HAI) are an increasing problem in health care facilities. In the neonatal intensive care unit at Länssjukhuset Ryhov in Jönköping, inconsistent cultivation results have been observed for suspected HAI caused by Staphylococcus aureus. To prevent HAI and to maintain patient safety, sensitive and reliable laboratory tests are essential. The aim of the study was to determine and compare the lowest range of detection for cultivation and qPCR with and without enrichment in MAMSA broth, for S. aureus. Serial dilutions of S. aureus were made, and the original concentration was determined through viable count. Cultivation on blood agar and qPCR with and without enrichment in MAMSA broth was performed. The results were used to determine a minimum detection range. For cultivation, a minimum detection range of 0,5–62 CFU/ml was determined and for qPCR a range of 6400–140 000 CFU/ml. For qPCR after enrichment in MAMSA broth, a lowest detection range of 0,6–140 CFU/ml was determined. For detection with cultivation single to tenths of CFU/ml were needed in the sample. For qPCR thousands to tenths of thousands of CFU/ml were needed. For qPCR with enrichment in MAMSA broth the detection range could be lowered to levels comparable with cultivation. For clinical application, further studies are needed with more bacterial species and replicates.