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Leveraging of Machine Learning to Evaluate Genotypic-Phenotypic Concordance of Pasteurella Multocida Isolated from Bovine Respiratory Disease CasesTessa R Sheets (15354472) 27 April 2023 (has links)
<p> Pasteurella multocida is a respiratory pathogen that is frequently isolated from cattle suffering from bovine respiratory disease (BRD), the leading cause of mortality and morbidity on modern day cattle farms. Treatment involves the use of antimicrobials which have been shown to fail for about 30% of BRD cases, leading to the suspicion that etiologic agents, such as P. multocida, may be resistant. Phenotypic resistance can be confirmed via laboratory antibiotic susceptibility testing (AST) but this requires several days to complete. Genotypic resistance could be quickly assessed via nucleic acid assays based on the presence of known antibiotic resistance genes (ARGs). In human medicine, resistant genes associated with common antibiotics (i.e., ampicillin and penicillin) in common pathogens (i.e., Salmonella) are very accurate in predicting phenotypic resistance; however, ARGs associated with antibiotics used to treat BRD, such as enrofloxacin and tulathromycin, have shown low genotype-phenotype concordance. Hence, this study aims to improve P. multocida genotype-phenotype concordance by applying a machine learning (ML) algorithm to identify novel genomic sequences (biomarkers) that have greater accuracy in predicting resistance to antibiotics commonly used to treat BRD compared to known ARGs. Cultures of P. multocida were isolated from cattle with clinical signs of BRD. Antibiotic susceptibility testing was performed and recorded for each isolate. Genomes were sequenced and assembled, followed by annotating and identifying ARGs using the comprehensive antibiotic resistance database (CARD). Assembled genomes were then split into 31-base long segments (31- mers), and these segments along with phenotypic antibiotic susceptibility were used as input data for the ML algorithm. Important genomic biomarkers for four out of the six tested antibiotics were found to have greater accuracy when predicting resistance phenotype compared to known ARGs. The biomarker for enrofloxacin had the highest accuracy of 100% whereas the accuracy for the 12 tulathromycin biomarker was 81% but was still greater than the accuracy given by ARGs of 63%. On the other hand, resistance genes for florfenicol and tetracycline showed greater genotype?phenotype concordance, with accuracies of 95% and 91%, respectively. Annotations to important rulesets determined by ML were associated with clustered regularly interspaced short palindromic repeats (CRISPR) sequences, ligases that function to recycle murein into the peptidoglycan (PDG) layer, and transferases that control the synthesis and modulation of the lipopolysaccharide (LPS). External validation revealed that phenotypic resistance could be accurately predicted for danofloxacin and enrofloxacin using genomic biomarkers determined by ML, and for florfenicol using the floR gene. This study demonstrated that genomic biomarkers determined by ML can provide an accurate prediction of antibiotic resistance within Pasteurella multocida isolates. Assays could be developed to target ML-generated biomarkers and known ARGs to predict resistance in sick animals and to limit treatment failures associated with antibiotic resistance in cattle suffering from BRD. </p>
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Utilization of bioinformatic and next generation sequencing approaches for the discovery of predictive biomarkers and molecular pathways involved in bovine respiratory diseaseScott, Matthew Adam 06 August 2021 (has links)
Bovine respiratory disease (BRD) is a highly dynamic disease complex that results from host, microbial agent, and environmental interactions. Despite nearly a century of targeted research, BRD remains the most economically damaging disease in beef cattle production and appears to be increasing in global incidence. While modern modalities for BRD detection exist, clinical diagnosis and management decisions largely depend upon clinical observations and their associated risk of disease. Though these approaches lack precision, they remain in use for many reasons, including fiscal and time constraints within beef production systems. Advancements in high-throughput sequencing have demonstrated the ability to provide insight into complex biological disorders, leading to the development of predictive biomarkers and individualized therapy. Through the use of observational research methods and previously published data, transcriptome analyses were used to capture biological information related to the host-disease or host-pathogen relationship. These studies independently elaborated findings related to host management of inflammation, ultimately being associated with both acquisition and severity of BRD. Through advances in sequencing technology and data analysis methodology, novel components related to host inflammatory mitigation and antimicrobial defense are described for clinical BRD. Factors related to increased alternative complement activation, decreased specialized proresolving lipid mediator biosynthesis, decreased antimicrobial peptide production, and increased type I interferon stimulation were associated with severe clinical BRD. These findings define molecular networks, mechanisms, and pathways that are associated with BRD outcome, and may serve as a foundation for precision medicine in beef cattle.
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Use of Software Modeling Tools to Understand Population Health Dynamics: Application to Bovine Respiratory Disease in US Beef Calves Prior to WeaningWang, Min 08 December 2017 (has links)
Bovine respiratory disease (BRD) is a significant health problem for cattle producers in terms of economic cost and animal welfare. In the United States (US), it is one of the leading causes of sickness and death in beef calves prior to weaning. Although much research has been conducted to develop vaccines for prevention and antibiotics for treatment, the morbidity and mortality of BRD in beef calves prior to weaning has not improved over the years. The identification of risk factors associated with BRD is an area of focus which might ultimately allow producers to minimize morbidity and mortality from BRD. Little research has been performed to understand factors contributing to the risk of BRD in beef calves prior to weaning. BRD affects the beef cattle industry through losses due to mortality, prevention cost, treatment cost, or morbidity effect on productivity. Currently, the economic losses due to BRD for beef calves prior to weaning is not available. Price paid for feeder cattle is a major factor influencing the income of producers. The effect of BRD is a complicated problem since the parameters associated with the cost of BRD in beef cow-calf production are variable and interrelated. To better understand the economic effect of BRD in beef calves prior to weaning, concepts of uncertainty, variability, stochasticity, nonlinearity, and feedback might be involved during the process of assessing risk. The objectives of this dissertation are the following: 1) to test if calf sex, birth weight, and age of dam are associated with BRD of beef calves prior to weaning in different age periods; 2) to identify factors affecting the national market price of beef feeder cattle in the US and how the prices change over time; 3) to investigate the prevention and treatment cost of BRD in beef calves prior to weaning; 4) to estimate the economic cost of BRD in US beef calves prior to weaning; and 5) to understand the effect of BRD occurrence or absence on the national net income of the US beef cow-calf industry.
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Bovine Parainfluenza-3 Specific Antibodies in Veal Calves Supplemented with Cinnamaldehyde or LactoferrinHogshead, Bradley Thomas January 2017 (has links)
No description available.
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VIRAL-ALLERGEN INTERACTIONS: INSIGHTS INTO THE ORIGINS OF ALLERGIC ASTHMA.Al-Garawi, Amal 10 1900 (has links)
<p>Asthma is a chronic immune-inflammatory disease of the airways, characterized by reversible airflow obstruction and airway hyperresponsiveness (AHR), and is associated with the development of airway remodeling. While our understanding of the pathophysiology of allergic asthma has increased remarkably in the last few decades, the origins of the disease remain elusive. Indeed, studies indicate that the prevalence of allergic asthma, has increased dramatically over the last 30 years. Within this context, a number of environmental factors including respiratory viral infections have been associated with the onset of this disease but causal evidence is lacking. The work presented in this thesis examines the interactions between a respiratory viral infection, specifically influenza A, and the common aeroallergen house dust mite (HDM) in an experimental murine model. To this end, we investigated the impact of an acute influenza A infection on the exposure to a subclinical dose of HDM (Chapter 2) and addressed potential underlying immune mechanisms using a global, genomic approach (Chapter 3). Our data demonstrate an enhancement of immune inflammatory responses to HDM and reveals multiple immune pathways by which influenza A may enhance the response to subsequent allergen exposure. Collectively these immune pathways are capable of lowering the threshold of HDM responsiveness. Lastly, as allergic asthma develops in most instances during infancy, we investigated the impact of an influenza A infection on allergen responses in infant mice (Chapter 4). In this setting, acute influenza A infection subverts constitutive allergen hyporesponsiveness thus resulting in sensitization, airway inflammation and, ultimately, structural and functional alterations persisting into adulthood.</p> / Doctor of Philosophy (PhD)
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Evaluation of Dust Control Technologies for Drywall Finishing Operations: Industry Implementation Trends, Worker Perceptions, Effectiveness and UsabilityYoung, Deborah Elspeth 15 August 2007 (has links)
Drywall finishing operations have been associated with worker exposure to dust that contains known particulate respiratory health hazards, such as silica, talc, and mica. Despite the existence of engineering, work-practice, and personal-protective-equipment (PPE) control technologies for the mitigation of this hazard, worker exposures persist in the drywall finishing industry. This research employed a macroergonomic framework to evaluate this problem and identify barriers to dust control technology adoption in the key subsystems: personnel, technological, and organizational.
In the first study, the organizational subsystem was evaluated through a telephone interview of 264 drywall finishing firm owners. This study found the most commonly used dust control technology was respiratory protection. Cost, usability, environmental factors, and productivity were barriers identified in preventing adoption of other technologies.
In the second study, of the technological subsystem, 16 participants performed simulated drywall finishing tasks with each of four methods, in a laboratory setting. Dust particles were monitored and compared among the technologies used. Participants performed usability evaluations of the four tools. The ventilated sander produced less respirable-size class dust than did the other three tools. The block sander produced more dust than the other three tools. Usability evaluations revealed that the block sander was easiest to learn, easiest to use, and perceived to be the best overall, while the wet method and pole sander were considered to have poor usability in terms of ease of use and productivity. Usability problems associated with perceived comfort and ease of use were identified for the ventilated sander, but it was tied for "overall best" with the block sander.
The third study, of drywall finishing worker perceptions, employed the Health Belief Model to assess barriers to technology adoption, risk, susceptibility, and benefits. Results showed that workers have a high perception of the risk associated with drywall dust, but a lower perception of individual susceptibility to disease as a result of occupational exposure. Barriers to the use of dust control technologies were identified as being associated with organizational and usability factors. Most participants indicated having access only to respiratory protection, among the available dust control methods. / Ph. D.
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Comparing the performance of a targeted pull-down assay to shotgun sequencing for improving respiratory infectious disease surveillanceChristian, Monica R. 07 June 2023 (has links)
No description available.
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DEVELOPMENT OF MOLECULAR DIAGNOSTIC ASSAYS FOR EQUINE RESPIRATORY VIRUSES AND ANALYSIS OF THE ROLE OF EQUINE ARTERITIS VIRUS ENVELOPE PROTEINS IN THE EARLY EVENTS OF VIRUS ENTRYLu, Zhengchun 01 January 2012 (has links)
There is an urgent need for detection of viral respiratory pathogens to identify the causal agent(s) involved and to prevent the spread of related diseases. The first part of this dissertation focuses on development, optimization and validation of Real-time reverse transcription polymerase chain reaction (rRT-PCR) assays for the detection of several common equine viral pathogens: equine arteritis virus (EAV), equine influenza virus and equine rhinitis viruses A and B. Emphasis of the second part of this dissertation is on studying the role of EAV envelope proteins in virus attachment and entry. Using an infectious cDNA clone of EAV and reverse genetics, a panel of chimeric viruses was generated by swapping the N-terminal ectodomains and full-lengths of the two major envelope proteins (GP5 and M) from porcine reproductive and respiratory syndrome virus (PRRSV). The recombinant viruses expressing the N-terminal ectodomain of PRRSV GP5 or M or both (GP5ecto, Mecto, and GP5&Mecto, respectively) in an EAV backbone were viable and genetically stable. Compared to the parental virus, these three chimeric viruses produced lower titers and smaller plaque sizes indicating that they have a crippled phenotype. Interestingly, the three chimeric viruses could only infect EAV susceptible cell lines but not the PRRSV susceptible cell line. Therefore, the exchange of GP5 and/or M protein N-terminal ectodomains from PRRSV did not alter the cellular tropism of the chimeric viruses. We also investigated the role of one of the minor envelope proteins (E) of EAV in virus attachment and entry. The results showed that EAV infection of equine endothelial cells is heparin-dependent and the Cterminus of the E protein contains a putative heparin-binding domain. We generated a panel of arginine to glycine mutations in the conserved region of both the full-length EAV infectious cDNA clone and individual E protein expression vectors. The triple mutation R52,60,65G construct grew significantly slower and produced much smaller plaques. The double mutant R52,60G completely blocked the interaction between E protein and heparin. Taken together, these data indicated that E protein interacts with heparin to facilitate virus attachment and plays a major role in EAV infection.
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[en] A STUDY ON THE PERIODICITY OF ATMOSPHERIC POLLUTION DATA IN THE ESTIMATION OF HEALTH EFFECTS IN RIO DE JANEIRO CITY / [pt] ESTUDO DE PERIODICIDADE DOS DADOS DE POLUIÇÃO ATMOSFÉRICA NA ESTIMAÇÃO DE EFEITOS NA SAÚDE NO MUNICÍPIO DO RIO DE JANEIROCARLA FERNANDES DE MELLO 26 March 2008 (has links)
[pt] Esta dissertação apresenta um estudo de validação das
estimações dos efeitos da poluição atmosférica na saúde da
população quando se utilizam dados com periodicidade de
seis dias. O estudo foi realizado utilizando duas
abordagens complementares. A primeira consiste em comparar
os efeitos estimados a partir da análise de duas séries de
morbidade diárias na cidade do Rio de Janeiro com aqueles
obtidos particionando-se estas mesmas séries em seis séries
distintas, cada qual com periodicidade de seis dias. As
estimativas dos efeitos nas series particionadas de seis
dias variaram substancialmente em relação à série diária
para contagem de internações por doenças respiratórias em
crianças. Para a mesma análise feita para a série de
idosos, não foram detectadas diferenças tão significativas.
Para complementar esta análise, realizou-se um estudo de
Monte Carlo considerando diferentes cenários quanto aos
padrões de poluição do ar. Os resultados mostraram que
quanto maior a quantidade de dia atípicos por mês, maior
pode ser a variação entre as estimações das séries diárias
e as séries com periodicidade de 6 dias. Ao fim deste
trabalho são apresentados resultados utilizando dados reais
com periodicidade de 6 dias. Os efeitos estimados de PM10
para doenças respiratórias em crianças foram de 8.1% (IC:
5.4% ; 10.8%) para o dia corrente e 7.3% (IC: 4.5% ; 10.2%)
para 1 dia após a exposição à poluição do ar. Para idosos,
houve um aumento estatisticamente significativo apenas para
o dia corrente de 3.36% (IC: 1.19% ;5.58%). / [en] This dissertation presents a validation study on the
analysis of the effect of atmospheric pollution on
morbidity using data sampled every sixth day. This has been
investigated using two complementary frameworks. We first
compared such pollution effects using two morbidity daily
time series in Rio de Janeiro city, which have been sampled
every sixth day, thus generating, for each series, a set of
six sampled series. For the daily counts of hospital events
for children due to respiratory diseases the estimated
pollution effect for the six sampled series was markedly
different from the same effect estimated on the original
daily time series, while for elderly people such difference
has not been observed. The second part of our analysis was
carried over using a Monte Carlo study. Finally we conclude
our work presenting risk estimates using real data sampled
every six days. The estimated relative risks of particulate
material (PM10) on respiratory diseases for inhabitants of
Rio de Janeiro city were as follows. For children the risk
was estimated in 8.1% (5.4%; 10.8%) for current day
exposure and 7.3% (4.5%; 10.2%) for exposition lagging one
day. For elderly people it was observed a significant
increase on hospital attendances due to pollution on the
same day of exposition. and the estimated risk was 3.36%
(1.19%; 5.58%).
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Análise espacial das doenças respiratórias e a poluição relacionada ao tráfego no município de São Paulo / Spatial analysis of respiratory diseases and traffic- related air pollution in São PauloAlmeida, Samuel Luna de 25 April 2013 (has links)
Introdução: A avaliação dos riscos a saúde da população associados a exposição aos poluentes de origem veicular é, ainda, um importante desafio para pesquisadores e formuladores de políticas públicas de saúde e ambiente. Objetivos: Estudar a associação espacial das internações por doenças respiratórias e a poluição relacionada ao tráfego no município de São Paulo. Método: Dados de internações hospitalares por doenças respiratórias do sistema público e privado, no periodo de 2004-2006, foram georreferenciados por endereço do paciente. Foram selecionados os CIDs J20-J22 e J40-J47 para crianças menores de 5 anos e os diagnósticos J40-J47 para idosos com idade superior a 64 anos. A área urbana do município foi dividida em uma grade com células de 500mx500m e calculada a densidade de tráfego. Variáveis populacionais, socioeconômicas e o IDH foram convertidos da base de setor censitários para a grade, usando o ArcGIS ArcInfo 9.3. Análise de clusters foi realizada usando o modelo discreto de Poisson para o cálculo do risco esperado para cada grupo etário, com o uso do Software SaTScan v8.0. Para estudo da dependência espacial entre a taxa de internação por respiratórias em cada subgrupo e a densidade de tráfego total foram empregados o índice de Moran (I) e o Local Indicator for Spatial Autocorrelation (LISA), utilizando o software OpenGeoDa 1.2.0. A análise de regressão espacial entre a taxa de internação em cada grupo e a densidade de tráfego foi realizada utilizando o Pacote R R Core Team (2012). Resultados: Foi encontrada associação espacial significativa entre o risco de internação por doenças respiratórias em crianças menores de 5 anos e a densidade de tráfego no município de São Paulo. Para idosos, com idade superior a 64 anos, os resultados não foram significativos. As análises de cluster e de autocorrelação espacial mostraram padrões espaciais diferenciados para crianças e idosos. A análise de autocorrelação (I de Moran) evidenciou maior associação entre internações por doenças respiratórias e densidade veicular para crianças do que para idosos. Os resultados da análise de regressão espacial mostrou associação positiva entre a taxa de internações em crianças e a densidade de tráfego, quando controlado pelo IDH-M. No caso de idosos, o coeficiente de regressão foi negativo. Conclusão: A poluição relacionada ao tráfego configura-se como importante fator de risco à saúde de crianças na cidade de São Paulo e medidas de redução das exposições bem como de redução dos fatores de vulnerabilidade devem ser priorizadas / Introduction: The assessment of population health risks associated with exposure to vehicular pollutants source is, still, a major challenge for researchers and policymakers to health and environment. Objectives: Studying the spatial association of hospitalization for respiratory diseases and air pollution related to traffic in São Paulo. Methods: Data on hospital admissions for respiratory diseases from the public and private sectors, for the period 2004-2006, were geocoded by patient address. We selected CIDs J20-J22 and J40-J47 for children under 5 years and the diagnoses J40-J47 for elderly over the age of 64 years. The urban area was divided into a grid of cells with 500mx500m and calculated the density of traffic. Population variables, socioeconomic and HDI were converted base census sector to the grid, using ArcGIS ArcInfo 9.3. Cluster analysis was performed using the discrete Poisson model to calculate the expected risk for each age group, using the software SaTScan v8.0. To study the spatial dependence between the rate of hospitalization for respiratory in each subgroup and traffic density were employed full index Moran (I) and Local Indicator for Spatial autocorrelation (LISA) using the software OpenGeoDa 1.2.0. Spatial regression analysis between the rate of hospitalization for each group and the traffic density was performed using the package R \"R Core Team (2012). Results: We found significant spatial association between the risk of hospitalization for respiratory diseases in children under 5 years and the traffic density in the city of São Paulo. For elderly people, aged over 64 years, the results were not significant. The cluster analysis and spatial autocorrelation showed distinct spatial patterns for children and elderly. The analysis of autocorrelation (Moran\'s I) showed greater association between hospital admissions for respiratory and vehicular density for children than for older people. The results of the spatial regression analysis showed a positive association between the rate of hospital admissions in children and traffic density when controlled by HDI. In the case of the elderly, the regression coefficient was negative. Conclusion: The traffic- related air pollution configured as an important risk factor to the health of children in the city of São Paulo and measures to reduce exposures and reduction of vulnerability factors should be prioritized
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