A framework was developed to characterize the antimicrobial use/antimicrobial resistance complex in livestock systems in Indonesia, Vietnam, and Thailand. Farm profitability, disease prevention, and mortality rate reduction were identified as drivers toward antimicrobial use in livestock systems. It revealed that antimicrobial use was high in all sectors studied, and that routine preventative use was of particular importance to broiler production systems. Misleading feed labeling was identified as a hurdle to the collection of accurate antimicrobial use data, with farmers being unaware of the antimicrobials contained in some commercial feed. Economic analysis found that the cost of antimicrobials was low relative to other farm inputs, and that farm profitability was precariously balanced. High disease and poor prices were identified as potential drivers toward economic loss. The research indicates that antimicrobial use in small-scale poultry production systems improves feed conversion ratios and overall productivity. However, data were limited to quantify adequately these potential gains and their impacts on the food supply. During the study, all countries embraced and implemented policies on better management of antimicrobial use in livestock and surveillance of antimicrobial resistance. Future policies need to consider farm-level economics and livestock food supply issues when developing further antimicrobial use interventions in the region.

The study aimed to examine the prevalence and genetic characteristics of ESBL-production and colistin resistance in Salmonella and Escherichia coli from pigs and pork in the border area among Thailand, Cambodia, Lao PDR, and Myanmar. Salmonella (n = 463) and E. coli (n = 767) isolates were collected from pig rectal swab from slaughterhouses (n = 441) and pork from retail markets (n = 368) during October 2017 and March 2018. All were determined for susceptibility to colistin and cephalosporins, ESBL production and mcr and ESBL genes. Salmonella was predominantly found in Cambodia (65.8%). Serovars Rissen (35.6%) and Anatum (15.3%) were the most common. The E. coli prevalence in pork was above 91% in all countries. Colistin-resistance rate in E. coli (10.4%) was significantly higher than Salmonella (2.6%). ESBL-producing Salmonella (1.9%) and E. coli (6.3%) were detected. The blaCTX-M-55 and blaCTX-M-14 were identified. The mcr-1 gene was detected in Salmonella (n = 12) and E. coli (n = 68). The mcr-1/blaCTX-M-55 and mcr-3/blaCTX-M-55 co-concurrence was observed in one Salmonella and three E. coli isolates, respectively. In conclusion, pigs and pork serve as carriers of colistin and new generation cephalosporins resistance. Testing for resistance to last line antibiotics should be included in national AMR surveillance program using One Health approach.

Metabolite profiles from biological samples suffer from both technical variations and subject-specific variants. To improve the quality of metabolomics data, conventional data processing methods can be employed to remove technical variations. These methods do not consider sources of subject variation as separate factors from biological factors of interest. This can be a significant issue when performing quantitative metabolomics in clinical trials or screening for a potential biomarker in early-stage disease, because changes in metabolism or a desired-metabolite signal are small compared to the total metabolite signals. As a result, inter-individual variability can interfere subsequent statistical analyses. Here, we propose an additional data processing step using linear mixed-effects modelling to readjust an individual metabolite signal prior to multivariate analyses. Published clinical metabolomics data was used to demonstrate and evaluate the proposed method. We observed a substantial reduction in variation of each metabolite signal after model fitting. A comparison with other strategies showed that our proposed method contributed to improved classification accuracy, precision, sensitivity and specificity. Moreover, we highlight the importance of patient metadata as it contains rich information of subject characteristics, which can be used to model and normalize metabolite abundances. The proposed method is available as an R package lmm2met.

No abstract

This randomized controlled trial characterized the transfer of E. coli from animal feces and/or furrow water onto adjacent heads of lettuce during foliar irrigation, and the subsequent survival of bacteria on the adaxial surface of lettuce leaves. Two experiments were conducted in Salinas Valley, California: (1) to quantify the transfer of indicator E. coli from chicken and rabbit fecal deposits placed in furrows to surrounding lettuce heads on raised beds, and (2) to quantify the survival of inoculated E. coli on Romaine lettuce over 10 days. E. coli was recovered from 97% (174/180) of lettuce heads to a maximal distance of 162.56 cm (5.33 ft) from feces. Distance from sprinklers to feces, cumulative foliar irrigation, and lettuce being located downwind of the fecal deposit were positively associated, while distance from fecal deposit to lettuce was negatively associated with E. coli transference. E. coli exhibited decimal reduction times of 2.2 and 2.5 days when applied on the adaxial surface of leaves within a chicken or rabbit fecal slurry, respectively. Foliar irrigation can transfer E. coli from feces located in a furrow onto adjacent heads of lettuce, likely due to the kinetic energy of irrigation droplets impacting the fecal surface and/or impacting furrow water contaminated with feces, with the magnitude of E. coli enumerated per head of lettuce influenced by the distance between lettuce and the fecal deposit, cumulative application of foliar irrigation, wind aspect of lettuce relative to feces, and time since final irrigation. Extending the time period between foliar irrigation and harvest, along with a 152.4 cm (5 ft) no-harvest buffer zone when animal fecal material is present, may substantially reduce the level of bacterial contamination on harvested lettuce.