Extended-spectrum β-lactamase (ESBL) and AmpC β-lactamase (AmpC) producing Escherichia coli in dairy calves from the Canterbury region : a dissertation presented in partial fulfilment of the requirements for the degree of Master of Veterinary Studies in Veterinary Public Health at Massey University, Manawatū Campus Palmerston North, New Zealand

Antimicrobial resistance (AMR) has become a global public health concern threatening current effective prevention and treatment options. Infections caused by antimicrobial resistance strains are costly, often harder to treat and sometimes fatal. One group of bacteria that contributes to AMR are the extended beta lactamase (ESBL) and AmpC beta lactamase (AmpC) producing E. coli. These are on the critical list of important antibiotic-resistant bacteria of human importance compiled by the World Health Organisation and are a public health concern due to their resistance to an extended range of beta lactams. The main driver for the spread of AMR is the use of antimicrobials in both human and animals. One potential spread is by the feeding of waste milk to calves. Waste milk is the milk that contains antibiotics or other drugs. Waste milk is not recommended as feed for calves due to its association with the development of antibiotic resistance bacteria. Using the culture depended methods and whole genome sequencing, this study aimed to determine the prevalence of ESBL and AmpC producing E. coli isolated from recto-anal mucosal swabs (RAMS) from waste milk fed dairy calves, and to phenotypically and genotypically characterise ESBL and AmpC producing isolates. Recto-anal mucosal swabs samples (n = 40) from waste milk fed dairy calves collected from Canterbury region, New Zealand were screened for antimicrobial resistant E. coli. Fifty-eight percent (23/40) of the calves harboured antibiotic resistant E. coli. 25% (10/40) calves were positive for AmpC producing E. coli and none of the calves were positive for ESBL producing E. coli. The highest prevalence of resistance was observed for tetracycline. PCR and Sanger sequencing revealed that all the AmpC positive E. coli were chromosomal mediated with four mutations in the promoter region of the ampC gene. Whole genome sequencing of eight isolates resistant to both tetracycline and streptomycin revealed additional resistance genes that were not tested phenotypically. Using the Clermont phylogrouping method of E. coli, the AmpC positive, the tetracycline and streptomycin resistant E. coli isolates were distributed among phylogroups B1, C and D. In conclusion, this study revealed the presence of AmpC producing E. coli and other resistance genes in E. coli isolated from waste milk fed calves. Further epidemiological studies are required to determine whether these antibiotic resistant E. coli are associated with waste milk

Capacitive Conductivity Logging and Electrical Stratigraphy in a High-resistivity Aquifer, Boise Hydrogeophysical Research Site

We tested a prototype capacitive-conductivity borehole tool in a shallow, unconfined aquifer with coarse, unconsolidated sediments and very-low-conductivity water at the Boise Hydrogeophysical Research Site (BHRS). Examining such a high-resistivity system provides a good test for the capacitive- conductivity tool because the conventional induction- conductivity tool (known to have limited effectiveness in high-resistivity systems) did not generate expressive well logs at the BHRS. The capacitive-conductivity tool demonstrated highly repeatable, low-noise behavior but poor correlation with the induction tool in the lower-conductivity portions of the stratigraphy where the induction tool was relatively unresponsive. Singular spectrum analysis of capacitive- conductivity logs reveals similar vertical-length scales of structures to porosity logs at the BHRS. Also, major stratigraphic units identified with porosity logs are evident in the capacitive-conductivity logs. However, a previously unrecognized subdivision in the upper portion of one of the major stratigraphic units can be identified consistently as a relatively low-conductivity body (i.e., an electrostratigraphic unit) between the overlying stratigraphic unit and the relatively high-conductivity lower portion — despite similar porosity and lithology in adjacent units. The high repeatability and resolution and the wide dynamic range of the capacitive-conductivity tool are demonstrated here to extend to high-resistivity, unconsolidated sedimentary aquifer environments

Hydraulic Conductivity Imaging from 3-D Transient Hydraulic Tomography at Several Pumping/Observation Densities

[1] 3-D Hydraulic tomography (3-D HT) is a method for aquifer characterization whereby the 3-D spatial distribution of aquifer flow parameters (primarily hydraulic conductivity, K) is estimated by joint inversion of head change data from multiple partially penetrating pumping tests. While performance of 3-D HT has been studied extensively in numerical experiments, few field studies have demonstrated the real-world performance of 3-D HT. Here we report on a 3-D transient hydraulic tomography (3-D THT) field experiment at the Boise Hydrogeophysical Research Site which is different from prior approaches in that it represents a “baseline” analysis of 3-D THT performance using only a single arrangement of a central pumping well and five observation wells with nearly complete pumping and observation coverage at 1 m intervals. We jointly analyze all pumping tests using a geostatistical approach based on the quasi-linear estimator of Kitanidis (1995). We reanalyze the system after progressively removing pumping and/or observation intervals; significant progressive loss of information about heterogeneity is quantified as reduced variance of the K field overall, reduced correlation with slug test K estimates at wells, and reduced ability to accurately predict independent pumping tests. We verify that imaging accuracy is strongly improved by pumping and observational densities comparable to the aquifer heterogeneity geostatistical correlation lengths. Discrepancies between K profiles at wells, as obtained from HT and slug tests, are greatest at the tops and bottoms of wells where HT observation coverage was lacking

Three-Dimensional Stochastic Estimation of Porosity Distribution: Benefits of Using Ground-Penetrating Radar Velocity Tomograms in Simulated-Annealing-Based or Bayesian Sequential Simulation Approaches

Estimation of the three-dimensional (3-D) distribution of hydrologic properties and related uncertainty is a key for improved predictions of hydrologic processes in the subsurface. However it is difficult to gain high-quality and high-density hydrologic information from the subsurface. In this regard a promising strategy is to use high-resolution geophysical data (that are relatively sensitive to variations of a hydrologic parameter of interest) to supplement direct hydrologic information from measurements in wells (e.g., logs, vertical profiles) and then generate stochastic simulations of the distribution of the hydrologic property conditioned on the hydrologic and geophysical data. In this study we develop and apply this strategy for a 3-D field experiment in the heterogeneous aquifer at the Boise Hydrogeophysical Research Site and we evaluate how much benefit the geophysical data provide. We run high-resolution 3-D conditional simulations of porosity with both simulated-annealing-based and Bayesian sequential approaches using information from multiple intersecting crosshole gound-penetrating radar (GPR) velocity tomograms and neutron porosity logs. The benefit of using GPR data is assessed by investigating their ability, when included in conditional simulation, to predict porosity log data withheld from the simulation. Results show that the use of crosshole GPR data can significantly improve the estimation of porosity spatial distribution and reduce associated uncertainty compared to using only well log measurements for the estimation. The amount of benefit depends primarily on the strength of the petrophysical relation between the GPR and porosity data, the variability of this relation throughout the investigated site, and lateral structural continuity at the site

Electrical-hydraulic relationships observed for unconsolidated sediments in the presence of a cobble framework

Mechanistic models now exist to predict hydraulic conductivity (K) from the spectral induced polarization (SIP) response of granular media. We examined the predictions of such a model on unconsolidated coarse fluvial sediments and compared them to those obtained with a modified Kozeny Carman (KC) model. Samples were retrieved from the Boise Hydrogeophysical Research Site (BHRS), located on a gravel bar adjacent to the Boise River, Idaho. A sample holder (0.102 m diameter and 0.12 m in length) was designed to include the cobble framework in reconstituted samples representing the primary stratigraphic units defined based on porosity variation at this site. SIP (0.001-1000 Hz) and K (from Darcy tests) measurements were recorded for twelve samples, with SIP measurements made as a function of pore fluid conductivity (3-300 mS/m); grain, grain size distribution (GSD) and total porosity. K prediction with the KC model was improved after discounting of the cobble framework and multiplying by the tortuosity resulting from matrix “capillaries” around the cobbles, resulting in estimates within 0.5 orders of magnitude of the measurements. K prediction with a mechanistic SIP model based on Stern layer polarization (SLP model) that requires an estimate of the GSD alsoalso required discounting for the cobble framework to obtain estimates within 0.5 orders of magnitude of the measurements. Similarly, the SLP model over predicts the measured imaginary conductivity (σ") unless the cobble framework is discounted, which then results in estimates of σ” within 0.1 orders of magnitude of the measurements. This can be explained by the fact that the cobbles polarize at frequencies well below the minimum measurement frequency (0.001 Hz). The SLP model for K prediction parameterized in terms of the formation factor and imaginary conductivity performed well for the ten samples with a cobble framework without modification as the imaginary conductivity directly senses the matrix grain size characteristics, whereas the formation factor captures the porosity reduction and tortuosity resulting from the presence of the cobble framework (capillary tortuosity). Our findings suggest that the estimation of contrasts in hydraulic conductivityK in coarse sediments may be achievable through measurements of electrical properties after appropriate consideration of the cobble fractio

Menthol cigarette smoking and obesity in young adult daily smokers in Hawaii

This study investigates 1) the relationship between menthol cigarette smoking and obesity and 2) the association of body mass index with the nicotine metabolite ratio among menthol and non-menthol daily smokers aged 18-35 (n = 175). A brief survey on smoking and measures of height and weight, carbon monoxide, and saliva samples were collected from participants from May to December 2013 in Honolulu, Hawaii. Multiple regression was used to estimate differences in body mass index among menthol and non-menthol smokers and the association of menthol smoking with obesity. We calculated the log of the nicotine metabolite ratio to examine differences in the nicotine metabolite ratio among normal, overweight, and obese smokers. Sixty-eight percent of smokers used menthol cigarettes. Results showed that 62% of normal, 54% of overweight, and 91% of obese smokers used menthol cigarettes (p =.000). The mean body mass index was significantly higher among menthol compared with non-menthol smokers (29.4 versus 24.5, p =.000). After controlling for gender, marital status, educational attainment, employment status, and race/ethnicity, menthol smokers were more than 3 times as likely as non-menthol smokers to be obese (p =.04). The nicotine metabolite ratio was significantly lower for overweight menthol smokers compared with non-menthol smokers (16 versus.26, p =.02) in the unadjusted model, but was not significant after adjusting for the covariates. Consistent with prior studies, our data show that menthol smokers are more likely to be obese compared with non-menthol smokers. Future studies are needed to determine how flavored tobacco products influence obesity among smokers