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Exposome throughout human well being: Paradise or imagination?
Identifying and controlling the emergence of antimicrobial resistance (AMR) is a high priority for researchers and public health officials. One critical component of this control effort is timely detection of emerging or increasing resistance using surveillance programs. Currently, detection of temporal changes in AMR relies mainly on analysis of the proportion of resistant isolates based on the dichotomization of minimum inhibitory concentration (MIC) values. In our work, we developed a hierarchical Bayesian latent class mixture model that incorporates a linear trend for the mean log2MIC of the non-resistant population. By introducing latent variables, our model addressed the challenges associated with the AMR MIC values, compensating for the censored nature of the MIC observations as well as the mixed components indicated by the censored MIC distributions. Inclusion of linear regression with time as a covariate in the hierarchical structure allowed modelling of the linear creep of the mean log2MIC in the non-resistant population. The hierarchical Bayesian model was accurate and robust as assessed in simulation studies. The proposed approach was illustrated using Salmonella enterica I,4,[5],12i- treated with chloramphenicol and ceftiofur in human and veterinary samples, revealing some significant linearly increasing patterns from the applications. Implementation of our approach to the analysis of an AMR MIC dataset would provide surveillance programs with a more complete picture of the changes in AMR over years by exploring the patterns of the mean resistance level in the non-resistant population. OUL232 cell line Our model could therefore serve as a timely indicator of a need for antibiotic intervention before an outbreak of resistance, highlighting the relevance of this work for public health. Currently, however, due to extreme right censoring on the MIC data, this approach has limited utility for tracking changes in the resistant population.Antibiotic resistance is a global human health problem. We partnered with Dignity Health Mercy Medical Center to study antibiotic resistance in clinical isolates. We tested whether growth rates, a sensitive assay used to measure the fitness of bacterial samples, correlate with a clinical test to measure antibiotic resistance. We found a strong correlation between these two methods suggesting that growth rates could be reliably applied to evolutionary studies of clinically relevant problems. Moreover, the sensitivity of the growth rates assay enabled us to identify fitness effects of specific antibiotic resistance genes.Lady's-slipper orchid (Cypripedium calceolus) is considered an endangered species in most countries within its geographical range. The main reason for the decline in the number of populations of this species in Europe is habitat destruction. In this paper the ecological niche modelling approach was used to estimate the effect of future climate change on the area of niches suitable for C. calceolus. Predictions of the extent of the potential range of this species in 2070 were made using climate projections obtained from the Community Climate System Model for four representative concentration pathways rcp2.6, rcp4.5, rcp6.0 and rcp8.5. According to these analyses all the scenarios of future climate change will result in the total area of niches suitable for C. calceolus decreasing. Considering areas characterized by a suitability of at least 0.4 the loss of habitat will vary between ca. 30% and 63%. The highest habitat loss of ca. 63% is predicted to occur in scenario rcp 8.5. Surprisingly, in the most damaging rcp 8.5 prediction the highest overlap between potential range of C. calceolus and its pollinators will be observed and in all other scenarios some pollinators will be available for this species in various geographical regions. Based on these results at least two approaches should be implemented to improve the chances of survival of C. calceolus. In view of the unavoidable loss of suitable habitats in numerous European regions, conservation activities should be intensified in areas where this species will still have suitable niches in the next 50 years. In addition, for C. calceolus ex-situ activities should be greatly increased so that it can be re-introduced in the remaining suitable areas.OBJECTIVES The R102G variant in complement 3 (C3) results in two allotypic variants C3 fast (C3F) and C3 slow (C3S). C3F presents at increased frequency in patients with chronic kidney disease (CKD), our aim is to explore its role in CKD progression and mortality. METHODS Delta (Δ) eGFR for 2038 patients in the Salford Kidney Study (SKS) was calculated by linear regression; those with ≤-3ml/min/1.73m2/yr were defined as rapid progressors (RP) and those with ΔeGFR between -0.5 and +1ml/min/1.73m2/yr, labelled stable CKD patients (SP).A group of 454 volunteers was used as a control group. In addition, all biopsy-proven glomerulonephritis (GN) patients were studied regardless of their ΔeGFR. R102G was analysed by real-time PCR, and genotypic and allelic frequencies were compared between RP and SP along with the healthy control group. RESULTS There were 255 SP and 259 RP in the final cohort. Median ΔeGFR was 0.07 vs. -4.7 ml/min/1.73m2/yr in SP vs. RP. C3F allele frequency was found to be significantly higher in our CKD cohort (25.7%) compared with the healthy control group (20.6%); p = 0.008.However, there was no significant difference in C3F allele frequency between the RP and SP groups. In a subgroup analysis of 37 patients with IgA nephropathy in the CKD cohort (21 RP and 16 SP), there was a significantly higher frequency of C3F in RP 40.5% vs. 9.4% in SP; p = 0.003. In the GN group, Cox regression showed an association between C3F and progression only in those with IgA nephropathy (n = 114);HR = 1.9 (95% CI 1.1-3.1; p = 0.018) for individuals heterozygous for the C3F variant, increased further for individuals homozygous for the variant, HR = 2.8 (95% CI 1.2-6.2; p = 0.014). CONCLUSION The C3 variant R102G is associated with progression of CKD in patients with IgA nephropathy.Antimicrobial drugs administered systemically may cause the emergence and dissemination of antimicrobial resistance among enteric bacteria. To develop logical, research-based recommendations for food animal veterinarians, we must understand how to maximize antimicrobial drug efficacy while minimizing risk of antimicrobial resistance. Our objective is to evaluate the effect of two approved dosing regimens of enrofloxacin (a single high dose or three low doses) on Escherichia coli in cattle. We look specifically at bacteria above and below the epidemiological cutoff (ECOFF), above which the bacteria are likely to have an acquired or mutational resistance to enrofloxacin. We developed a differential equation model for the antimicrobial drug concentrations in plasma and colon, and bacteria populations in the feces. The model was fit to animal data of drug concentrations in the plasma and colon obtained using ultrafiltration probes. Fecal E. coli counts and minimum inhibitory concentrations were measured for the week after receiving the antimicrobial drug.
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