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1.
Appl Environ Microbiol ; 78(22): 8045-55, 2012 Nov.
Article in English | MEDLINE | ID: mdl-22961893

ABSTRACT

Experimental oral challenge studies with three different genotypes of Escherichia coli O157:H7 were conducted in cattle to determine the genotype-specific variability in shedding frequencies and concentrations and the frequency and extent of contamination of the environment. The results indicated that the E. coli O157:H7 genotype and ecological origin maybe important factors for the occurrence and concentration in the cattle host. Four groups of six young Holstein steers each were orally challenged with 10(6) CFU of one of three E. coli O157:H7 strains: FRIK 47 (groups 1 and 2), FRIK 1641 (group 3), and FRIK 2533 (group 4). Recto-anal mucosal swabs (RAMS) and environmental samples were taken on alternate days over 30 days. The numbers of E. coli O157:H7 cells and generic E. coli cells per sample were determined. Also, the presence and absence of 28 gene targets were determined for 2,411 isolates using high-throughput real-time PCR. Over the study period, strains FRIK 47, FRIK 1641, and FRIK 2533 were detected in 52%, 42%, and 2% of RAMS, respectively. Environmental detection of the challenge strains was found mainly in samples of the hides and pen floors, with strains FRIK 47, FRIK 1641, and FRIK 2533 detected in 22%, 27%, and 0% of environmental samples, respectively. Based on the panel of 28 gene targets, genotypes of enterohemorrhagic E. coli (EHEC) and generic E. coli from the experimental samples were clustered into three subgroups. In conclusion, the results suggested that the type and intensity of measures to control this pathogen at the preharvest level may need to be strain specific.


Subject(s)
Bacterial Shedding , Cattle Diseases/microbiology , Escherichia coli Infections/veterinary , Escherichia coli O157/isolation & purification , Escherichia coli O157/pathogenicity , Anal Canal/microbiology , Animals , Cattle , DNA, Bacterial/genetics , Environmental Microbiology , Escherichia coli Infections/microbiology , Escherichia coli O157/genetics , Genes, Bacterial , Genotype , Polymerase Chain Reaction , Rectum/microbiology , Virulence Factors/genetics
2.
Mol Cell Probes ; 25(5-6): 222-30, 2011.
Article in English | MEDLINE | ID: mdl-21925264

ABSTRACT

Enterohemorrhagic Escherichia coli (EHEC), including O157 and non-O157 serotypes are significant foodborne pathogens that require sensitive and discriminatory methods for detection and characterization. There are numerous PCR-based methods for the detection of EHEC virulence factors, but the time and cost involved with large-scale screening efforts and population level analyses have limited the size and scope of studies. Recent technological advancements have combined the high-throughput performance of the microarray with the specificity and sensitivity of real-time qPCR to make large-scale screening efforts both time- and cost-effective. This study identified and evaluated a panel of 28 genetic markers including known virulence and regulatory genes, O-antigen genes, and select prophage regions of O157 and non-O157 EHEC that can be used with high-throughput PCR to virulotype, serotype, and preliminarily subtype large numbers of isolates. The PCR assays for the target genes were shown to be robust using multiple extraction methods and PCR platforms. Preliminary quantitative PCR showed that an EHEC concentration of 10(4) CFU/ml or lower could be detected, with a linear range of detection over five to six orders of magnitude. The panel of 28 target genes has the potential to become an integral tool in outbreak, environmental, and genetic investigations of EHEC.


Subject(s)
Antigens, Bacterial/analysis , Bacterial Typing Techniques , Escherichia coli Infections/diagnosis , Escherichia coli O157/genetics , Escherichia coli Proteins/genetics , Multiplex Polymerase Chain Reaction/methods , O Antigens/analysis , Antigens, Bacterial/genetics , Coliphages/genetics , Escherichia coli Infections/genetics , Escherichia coli O157/classification , Escherichia coli O157/isolation & purification , Escherichia coli O157/virology , Genetic Markers , High-Throughput Screening Assays , Humans , Limit of Detection , O Antigens/genetics , Prophages/genetics , Real-Time Polymerase Chain Reaction
3.
J Alzheimers Dis ; 76(3): 1029-1046, 2020.
Article in English | MEDLINE | ID: mdl-32623397

ABSTRACT

BACKGROUND: While sex hormones are essential for normal cognitive health, those individuals with greater endocrine dyscrasia around menopause and with andropause are more likely to develop cognitive loss and Alzheimer's disease (AD). OBJECTIVE: To assess whether circulating sex hormones may provide an etiologically significant, surrogate biomarker, for cognitive decline. METHODS: Plasma (n = 152) and serum (n = 107) samples from age- and gender-matched AD and control subjects from the Wisconsin Alzheimer's Disease Research Center (ADRC) were analyzed for 11 steroids and follicle-stimulating hormone. Logistic regression (LR), correlation analyses, and recursive partitioning (RP) were used to examine the interactions of hormones and hormone ratios and their association with AD. Models generated were then tested on an additional 43 ADRC samples. RESULTS: The wide variation and substantial overlap in the concentrations of all circulating sex steroids across control and AD groups precluded their use for predicting AD. Classification tree analyses (RP) revealed interactions among single hormones and hormone ratios that associated with AD status, the most predictive including only the hormone ratios identified by LR. The strongest associations were observed between cortisol, cortisone, and androstenedione with AD, with contributions from progesterone and 17ß-estradiol. Utilizing this model, we correctly predicted 81% of AD test cases and 64% of control test cases. CONCLUSION: We have developed a diagnostic model for AD, the Wisconsin Hormone Algorithm Test for Cognition (WHAT-Cog), that utilizes classification tree analyses of hormone ratios. Further refinement of this technology could provide a quick and cheap diagnostic method for screening those with AD.


Subject(s)
Alzheimer Disease/diagnosis , Alzheimer Disease/psychology , Cognitive Dysfunction/psychology , Estradiol/metabolism , Predictive Value of Tests , Aged , Aged, 80 and over , Biomarkers/blood , Cognition/physiology , Cognitive Dysfunction/diagnosis , Female , Gonadal Steroid Hormones/metabolism , Humans , Male , Testosterone/blood
4.
BMJ Open ; 7(1): e011529, 2017 01 23.
Article in English | MEDLINE | ID: mdl-28115328

ABSTRACT

OBJECTIVES: This study examined how environmental, health, social, behavioural and genetic factors interact to contribute to myocardial infarction (MI) risk. DESIGN: Survey data collected by Wisconsin Longitudinal Study (WLS), USA, from 1957 to 2011, including 235 environmental, health, social and behavioural factors, and 77 single- nucleotide polymorphisms were analysed for association with MI. To identify associations with MI we utilized recursive partitioning and random forest prior to logistic regression and chi-squared analyses. PARTICIPANTS: 6198 WLS participants (2938 men; 3260 women) who (1) had a MI before 72 years and (2) had a MI between 65 and 72 years. RESULTS: In men, stroke (LR OR: 5.01, 95% CI 3.36 to 7.48), high cholesterol (3.29, 2.59 to 4.18), diabetes (3.24, 2.53 to 4.15) and high blood pressure (2.39, 1.92 to 2.96) were significantly associated with MI up to 72 years of age. For those with high cholesterol, the interaction of smoking and lower alcohol consumption increased prevalence from 23% to 41%, with exposure to dangerous working conditions, a factor not previously linked with MI, further increasing prevalence to 50%. Conversely, MI was reported in <2.5% of men with normal cholesterol and no history of diabetes or depression. Only stroke (4.08, 2.17 to 7.65) and diabetes (2.71, 1.81 to 4.04) by 65 remained significantly associated with MI for men after age 65. For women, diabetes (5.62, 4.08 to 7.75), high blood pressure (3.21, 2.34 to 4.39), high cholesterol (2.03, 1.38 to 3.00) and dissatisfaction with their financial situation (4.00, 1.94 to 8.27) were significantly associated with MI up to 72 years of age. Conversely, often engaging in physical activity alone (0.53, 0.32 to 0.89) or with others (0.34, 0.21 to 0.57) was associated with the largest reduction in odds of MI. Being non-diabetic with normal blood pressure and engaging in physical activity often lowered prevalence of MI to 0.2%. Only diabetes by 65 (4.25, 2.50 to 7.24) and being exposed to dangerous work conditions at 54 (2.24, 1.36 to 3.69) remained significantly associated with MI for women after age 65, while still menstruating at 54 (0.46, 0.23 to 0.91) was associated with reduced odds of MI. CONCLUSIONS: Together these results indicate important differences in factors associated with MI between the sexes, that combinations of factors greatly influence the likelihood of MI, that MI-associated factors change and associations weaken after 65 years of age in both sexes, and that the limited genotypes assessed were secondary to environmental, health, social and behavioral factors.


Subject(s)
Myocardial Infarction/epidemiology , Aged , Alcohol Drinking/epidemiology , Apolipoproteins/genetics , Body Mass Index , Cigarette Smoking/epidemiology , Diabetes Mellitus/epidemiology , Environmental Health , Exercise/physiology , Female , Gene-Environment Interaction , Genotype , Humans , Hypertension/epidemiology , Income , Life Style , Longitudinal Studies , Male , Myocardial Infarction/genetics , Parity , Polymorphism, Single Nucleotide , Prevalence , Risk Factors , Sex Distribution , Smoking/epidemiology , Socioeconomic Factors , Wisconsin/epidemiology
5.
J Food Prot ; 75(4): 643-50, 2012 Apr.
Article in English | MEDLINE | ID: mdl-22488051

ABSTRACT

Escherichia coli O26, O45, O103, O111, O121, O145, and O157 are the predominant Shiga toxin-producing E. coli (STEC) serogroups implicated in outbreaks of human foodborne illness worldwide. The increasing prevalence of these pathogens has important public health implications. Beef products have been considered a main source of foodborne human STEC infections. Robust and sensitive methods for the detection and characterization of these pathogens are needed to determine prevalence and incidence of STEC in beef processing facilities and to improve food safety interventions aimed at eliminating STEC from the food supply. This study was conducted to develop Taqman real-time multiplex PCR assays for the screening and rapid detection of the predominant STEC serogroups associated with human illness. Three serogroup-specific assays targeted the O-antigen gene clusters of E. coli O26 (wzy), O103 (wzx), and O145 (wzx) in assay 1, O45 (wzy), O111 (manC), and O121 (wzx) in assay 2, and O157 (rfbE) in assay 3. The uidA gene also was included in the serogroup-specific assays as an E. coli internal amplification control. A fourth assay was developed to target selected virulence genes for Shiga toxin (stx(1) and stx(2)), intimin (eae), and enterohemolysin (ehxA). The specificity of the serogroup and virulence gene assays was assessed by testing 100 and 62 E. coli strains and non-E. coli control strains, respectively. The assays correctly detected the genes in all strains examined, and no cross-reactions were observed, representing 100 % specificity. The detection limits of the assays were 10(3) or 10(4) CFU/ml for pure cultures and artificially contaminated fecal samples, and after a 6-h enrichment period, the detection limit of the assays was 10(0) CFU/ml. These results indicate that the four real-time multiplex PCR assays are robust and effective for the rapid and reliable detection of the seven predominant STEC serogroups of major public health concern and the detection of their virulence genes.


Subject(s)
Food Contamination/analysis , Meat Products/microbiology , Real-Time Polymerase Chain Reaction/methods , Shiga Toxin/genetics , Shiga-Toxigenic Escherichia coli/isolation & purification , Colony Count, Microbial , Consumer Product Safety , Food Microbiology , Humans , Prevalence , Sensitivity and Specificity , Time Factors
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