PERFORMANCE OF THE EXACT AND CHI-SQUARE TESTS ON SPARSE CONTINGENCY TABLES

A cross-sectional observational study design was used to determine the prevalence of Escherichia coli 0157:H7 in wild deer feces. Samples were voluntarily submitted at a number of different locations. In order to determine if the proportions of E. coli 0157: H7 positive samples submitted were equal for each of the 26 locations, a 26 by 2 contingency table was analyzed. There were only four E. coli 0157:H7 positive samples, which resulted in a sparse table. It is possible to obtain statistically significant results in sparse tables using Fisher\u27s exact test, whereas the chi-square test is generally unreliable in such situations. Thus, Fisher\u27s exact test should be considered when small expected cell counts bring into question the validity of the chi-square test. However, the statistical conclusions based on either the exact test or an asymptotic chi-square test are shown to vary drastically by slight alterations in the distribution of non-empty cells. Therefore, a different statistical conclusion very easily could have been reached if a volunteer had submitted a sample at a different location. In addition, we show that the computational times for exact tests in SAS® can be an applicational limitation

A Comparison of Culture- and PCR-Based Methods to Detect Six Major Non-O157 Serogroups of Shiga Toxin-Producing Escherichia coli in Cattle Feces

Citation: Noll, L. W., Shridhar, P. B., Dewsbury, D. M., Shi, X. R., Cernicchiaro, N., Renter, D. G., & Nagaraja, T. G. (2015). A Comparison of Culture- and PCR-Based Methods to Detect Six Major Non-O157 Serogroups of Shiga Toxin-Producing Escherichia coli in Cattle Feces. Plos One, 10(8), 12. doi:10.1371/journal.pone.0135446Culture-based methods to detect the six major non-O157 (O26, O45, O103, O111, O121 and O145) Shiga toxin-producing E. coli (STEC) are not well established. Our objectives of this study were to develop a culture-based method to detect the six non-O157 serogroups in cattle feces and compare the detection with a PCR method. Fecal samples (n = 576) were collected in a feedlot from 24 pens during a 12-week period and enriched in E. coli broth at 40 degrees C for 6 h. Enriched samples were subjected to immunomagnetic separation, spread-plated onto a selective chromogenic medium, and initially pooled colonies, and subsequently, single colonies were tested by a multiplex PCR targeting six serogroups and four virulence genes, stx1, stx2, eae, and ehxA (culture method). Fecal suspensions, before and after enrichment, were also tested by a multiplex PCR targeting six serogroups and four virulence genes (PCR method). There was no difference in the proportions of fecal samples that tested positive (74.3 vs. 77.4%) for one or more of the six serogroups by either culture or the PCR method. However, each method detected one or more of the six serogroups in samples that were negative by the other method. Both culture method and PCR indicated that O26, O45, and O103 were the dominant serogroups. Higher proportions (P < 0.05) of fecal samples were positive for O26 (44.4 vs. 22.7%) and O121 (22.9 vs. 2.3%) serogroups by PCR than by the culture method. None of the fecal samples contained more than four serogroups. Only a small proportion of the six serogroups (23/640; 3.6%) isolated carried Shiga toxin genes. The culture method and the PCR method detected all six serogroups in samples negative by the other method, highlighting the importance of subjecting fecal samples to both methods for accurate detection of the six non-O157 STEC in cattle feces

Practical Application of Sample Size Determination Models for Assessment of Mortality Outcomes in Swine Field Trials

Mortality within livestock production has a substantial impact on economic sustain­ability of enterprises. The livestock industry has a unique opportunity to maximize animal welfare and production efficiency by minimizing morbidity and mortality. To do so, investigators must appropriately balance the utilization of limited resources with the quantity necessary for robust research. The objective of the study was to illustrate the use of readily implementable statistical models to determine sample size neces­sary to detect statistically significant differences between groups with varying levels of mortality. To this end, a series of examples were created where the unit to which a treatment is independently applied (experimental unit, EU) is either half of a 1,200 pig barn (group-level) or an individual pen (pen-level, 25 pigs per pen, 48 total pens) within a 1,200 pig barn. These examples and corresponding models can be readily adapted and implemented using SAS software to meet individual needs. Model inputs include the number of pigs, barns, and pens when appropriate, and model output is the calculated statistical power. When the EU is half-barn and mortality is measured on a group-level, 7 barns would be necessary to detect a 1 percentage unit difference in mortality (2% vs. 1% for two groups, respectively). As the observed difference in mortality between groups increases, the number of barns needed to detect the respec­tive difference decreases and vice versa. When the EU is the individual pen containing 25 pigs, and mortality is measured on the pen level, a total of 240 pens or 5 barns would be necessary to detect the same 1 percentage unit reduction in mortality from 2% to 1%. Comparing the results derived from group or pen-level mortality, a relatively close number of pigs is necessary to detect differences. For example, if comparing group mortalities of 3% vs. 4%, the number of barns necessary for group-level mortality is 11 and for pen-level mortality is 9. The models currently proposed incorporate appropriate design structure features for a series of different study designs and assume that observed mortality follows a binomial distribution. Performing proper sample size calculations prior to initiation of research trials is critical to determine the necessary sample size to reasonably expect to see statistical differences. It is very important to recognize that proper use of this information requires background knowledge regarding statistical analysis including understanding of EU, observational unit, and design features such as blocking, subsampling, and other design features. When these assumptions change based on the experiment being planned, appropriate modifications must be made to the models. It is always recommended to engage a statistician in the early stages of experimental design to ensure all facets of the proposed experiment are appropriately accounted for and to reduce the risk of making inaccurate production decisions. Lastly, it is not recommended that these models be used in a manner that assumes one size fits all. Rather, we provide the information as a foundation from which the reader can use appropriate content expertise and statistical principles to assist with designing experi­ments

VAMOS: a Pathfinder for the HAWC Gamma-Ray Observatory

VAMOS was a prototype detector built in 2011 at an altitude of 4100m a.s.l. in the state of Puebla, Mexico. The aim of VAMOS was to finalize the design, construction techniques and data acquisition system of the HAWC observatory. HAWC is an air-shower array currently under construction at the same site of VAMOS with the purpose to study the TeV sky. The VAMOS setup included six water Cherenkov detectors and two different data acquisition systems. It was in operation between October 2011 and May 2012 with an average live time of 30%. Besides the scientific verification purposes, the eight months of data were used to obtain the results presented in this paper: the detector response to the Forbush decrease of March 2012, and the analysis of possible emission, at energies above 30 GeV, for long gamma-ray bursts GRB111016B and GRB120328B.Comment: Accepted for pubblication in Astroparticle Physics Journal (20 pages, 10 figures). Corresponding authors: A.Marinelli and D.Zaboro

Prevalence of Shiga toxin–producing Escherichia coli and associated virulence genes in feces of commercial feedlot cattle

The objective of this study was to determine the prevalence of Shiga toxin–producing Escherichia coli (STEC) serogroups and associated virulence genes in feces of commercial feedlot cattle. During March to May 2011, fecal samples were collected from individual cattle (n=960) in 10 cohorts (cattle subpopulations within a feedlot) comprising 17,148 total steers that originated from 48 backgrounding operations in six U.S. states. Fecal samples were enriched in E. coli broth and subjected to two detection protocols: (1) an 11-gene multiplex polymerase chain reaction (PCR) that identifies seven O serogroups (O26, O45, O103, O111, O121, O145, and O157) and four virulence genes (stx1, stx2, eae, and ehxA) applied to extracted total DNA (“direct PCR”); and (2) cultural procedures that involve immunomagnetic separation (IMS) with O26, O103, and O111 beads, plating on a nondifferential MacConkey agar, followed by the multiplex PCR of pooled colonies (“culture-based method”). Generalized linear mixed models were used to adjust prevalence estimates for clustering. Based on direct PCR detection, O157 (49.9%) was the most prevalent O serogroup followed by O26 (20.3%), O103 (11.8%), O121 (10.7%), O45 (10.4%), O145 (2.8%), and O111 (0.8%). Cumulative adjusted prevalence estimates were 22.3, 24.6, and 0.01% for O26, O103, and O111 serogroups, respectively, based on culture-based methods. However, prevalence varied significantly by cohort (p-values<0.05) for O26, O121, and O157 based on direct PCR, and for O26, O103, and O111 serogroups based on culture-based methods. Results of this study indicate that all seven STEC serogroups were identified in feedlot cattle feces, with O157, O26, and O103 being the most prevalent serogroups. A substantial proportion of serogroup-positive samples did not harbor Shiga toxin genes; thus, additional elucidation of the potential human health risk is required. Further evaluation of diagnostic methods for non-O157 STEC is needed given their impact on prevalence estimation

\u3ci\u3eEscherichia coli\u3c/i\u3e O157:H7 in Free-Ranging Deer in Nebraska

In order to determine the prevalence and distribution of the human pathogen, Escherichia coli O157:H7, in free-ranging deer, hunters were asked to collect and submit fecal samples from deer harvested during a regular firearm season (14–22 November 1998). Prior to the season, 47% of the hunters with permits in the southeastern Nebraska (USA) study area indicated a willingness to participate in the study. Approximately 25% of successful hunters in the area submitted deer fecal samples. Escherichia coli O157:H7 was cultured from four (0.25%) of 1,608 total samples submitted. All of the fecal samples that were properly identified (1,426) and all that were positive for E. coli O157:H7 were from white-tailed deer (Odocoileus virginianus). We were unable to detect a statistically significant geographic distribution pattern of E. coli O157:H7. The presence of E. coli O157:H7 in the feces of free-ranging deer has implications not only for hunters, consumers of venison, and others in contact with deer or deer feces, but also for the development of strategies aimed at reducing and/or controlling this pathogen in water sources and domestic livestock

Diversity, Frequency, and Persistence of Escherichia coli O157 Strains from Range Cattle Environments

Genetic diversity, isolation frequency, and persistence were determined for Escherichia coli O157 strains from range cattle production environments. Over the 11-month study, analysis of 9,122 cattle fecal samples, 4,083 water source samples, and 521 wildlife fecal samples resulted in 263 isolates from 107 samples presumptively considered E. coli O157 as determined by culture and latex agglutination. Most isolates (90.1%) were confirmed to be E. coli O157 by PCR detection of intimin and Shiga toxin genes. Pulsed-field gel electrophoresis (PFGE) of XbaI-digested preparations revealed 79 unique patterns (XbaI-PFGE subtypes) from 235 typeable isolates confirmed to be E. coli O157. By analyzing up to three isolates per positive sample, we detected an average of 1.80 XbaI-PFGE subtypes per sample. Most XbaI-PFGE subtypes (54 subtypes) were identified only once, yet the seven most frequently isolated subtypes represented over one-half of the E. coli O157 isolates (124 of 235 isolates). Recurring XbaI-PFGE subtypes were recovered from samples on up to 10 sampling occasions and up to 10 months apart. Seven XbaI-PFGE subtypes were isolated from both cattle feces and water sources, and one of these also was isolated from the feces of a wild opossum (Didelphis sp.). The number of XbaI-PFGE subtypes, the variable frequency and persistence of subtypes, and the presence of identical subtypes in cattle feces, free-flowing water sources, and wildlife feces indicate that the complex molecular epidemiology of E. coli O157 previously described for confined cattle operations is also evident in extensively managed range cattle environments

Inclusion of Dried or Wet Distillers' Grains at Different Levels in Diets of Feedlot Cattle Affects Fecal Shedding of Escherichia coli O157:H7 ▿

Our objectives were to evaluate the prevalence of Escherichia coli O157:H7 in cattle fed diets supplemented with 20 or 40% dried distillers' grains (DG) (DDG) or wet DG (WDG) and assess whether removing DG from diets before slaughter affected fecal shedding of E. coli O157:H7. Eight hundred forty steers were allocated to 70 pens (12 steers/pen). Treatments were no DG (control), 20% DDG or WDG, and 40% DDG or WDG, and each was replicated in 14 pens. In phase 1, eight floor fecal samples were collected from each pen every 2 weeks for 12 weeks for isolation of E. coli O157:H7 and detection of high shedders. In phase 2, half of the pens with DG were transitioned to the no-DG control diet, and pen floor fecal samples were collected weekly from all pens for 4 weeks. During phase 1, prevalence of E. coli O157:H7 was 20.8% and 3.2% for high shedders. The form of DG had no significant effect on fecal E. coli O157:H7 shedding. The prevalence levels of E. coli O157:H7 and the numbers of high shedders were not different between diets with 0 or 20% DG; however, cattle fed 40% DG had a higher prevalence and more high shedders than cattle fed 0 or 20% DG (P ≤ 0.05). During phase 2, overall and high-shedder prevalence estimates were 3.3% and <0.1%, respectively, and there were no differences between those for different DG forms and inclusion levels or when DG was removed from diets. The form of DG had no impact on E. coli O157:H7; however, fecal shedding was associated with the DG inclusion level