Application of pharmacokinetic/pharmacodynamic concepts to the development of treatment regimens for sporadic canine urinary tract infections: Challenges and paths forward.

Antimicrobial efficacy can be predicted based on infection site exposure to the antimicrobial agent relative to the in vitro susceptibility of the pathogen to that agent. When infections occur in soft tissues (e.g., muscle, blood, and ligaments), exposure at the infection site is generally assumed to reflect an equilibrium between the unbound concentrations in plasma and that in the interstitial fluids. In contrast, for sporadic urinary tract infections (UTIs) in dogs and uncomplicated UTIs in humans, the primary site of infection is the bladder wall. Infection develops when bacteria invade the host bladder urothelium (specifically, the umbrella cells that form the urine-contacting layer of the stratified uroepithelium) within which these bacteria can avoid exposure to host defenses and antimicrobial agents. Traditionally, pathogen susceptibility has been estimated using standardized in vitro tests that measure the minimal concentration that will inhibit pathogen growth (MIC). When using exposure-response relationships during drug development to explore dose optimization, these relationships can either be based upon an assessment of a correlation between clinical outcome, drug exposure at the infection site, and pathogen MIC, or upon benchmark exposure-response relationships (i.e., pharmacokinetic/pharmacodynamic indices) typically used for the various drug classes. When using the latter approach, it is essential that the unbound concentrations at the infection site be considered relative to the MIC within the biological matrix to which the pathogen will be exposed. For soft tissue infections, this typically is the unbound plasma concentrations versus MICs determined in standardized media such as cation-adjusted Mueller Hinton broth, which is how many indices were originally established. However, for UTIs, it is the unbound drug concentrations within the urine versus the MICs in the actual urine biophase that needs to be considered. The importance of these relationships and how they are influenced by drug resistance, resilience, and inoculum are discussed in this review using fluoroquinolones and beta-lactams as examples.

Approaches to developing judicious uses of veterinary antibacterial drugs.

Development of new veterinary antibacterials is an important and challenging endeavor. Global recognition of antimicrobial resistance as a threat across human, animal, plant, food, and environmental sectors has increased the level of scrutiny on veterinary antibacterial use. Rigorous scientific evaluation of these products has and continues to be the underpinning of effectiveness evaluations and how hazards are identified, characterized, and ultimately used to make evidence-based and risk-based safety decisions. Some scientific factors commonly considered in the development of veterinary antibacterials include the pathogenesis and sequelae of the indicated disease, clinical and bacteriological improvement, dosage regimen (dose amount, route, duration, frequency), and antimicrobial-resistance qualitative risk assessments. Key discussion areas covered are how culture and susceptibility testing help determine if antibacterial effects are primarily responsible for clinical improvement and how pharmacokinetic and pharmacodynamic data can help predict success, aid in defining an adequate dosage regimen, and help minimize resistance emergence and spread.

Improved representation of the global dust cycle using observational constraints on dust properties and abundance.

Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of two relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with geometric diameter up to 20 µm (PM20) is approximately 5,000 Tg/year, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded data sets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this data set is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.

GISS-E2.1: Configurations and Climatology.

This paper describes the GISS-E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS-E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolution the same. Model skill when compared to modern era climatologies is significantly higher than in previous versions. Additionally, updates in forcings have a material impact on the results. In particular, there have been specific improvements in representations of modes of variability (such as the Madden-Julian Oscillation and other modes in the Pacific) and significant improvements in the simulation of the climate of the Southern Oceans, including sea ice. The effective climate sensitivity to 2 × CO2 is slightly higher than previously at 2.7-3.1°C (depending on version) and is a result of lower CO2 radiative forcing and stronger positive feedbacks.

Service Utilization and Costs of Patients at a Cash-Based Physical Therapy Clinic.

Cash-based physical therapy, a model in which the clinicians do not accept insurance payments and accept only direct payment, is quickly becoming an enticing option for clinicians who own their own practice. The purpose of this study was to describe service utilization for a single cash-based physical therapy clinic. Forty-eight charts of patients who had been discharged between 2013 and 2016 were randomly selected. The data were deidentified prior to the researchers gaining access. Chronic diagnoses were predominately prevalent (n = 28). The lumbo/pelvic region of diagnoses (39.6%) and knee/leg region of diagnoses (29.2%) encompassed the majority of the diagnoses. The mean physical therapy utilization for the cohort per episode of care was 8.0 ± 8.1 visits per episode of care, total cost of $780.19 ± 530.30 per episode of care, and $97.52 per visit. This study is the first to present data regarding costs, utilization, and patient demographics for a cash-based physical therapy clinic.

Perceptions of Government and Research Expert Groups and Their Implications for Watershed Management in Oklahoma, USA.

The collaborative approach for sustainable management of watersheds is built on engagement of diverse stakeholders. Climate variability and anthropogenic activities increasingly impose challenges to successful management, as do contrasts in stakeholder perceptions about those processes. To assess differences in perceptions about watershed issues, we conducted a focus group meeting of expert stakeholder groups from research institutions, and state and federal agencies in the management of Cimarron River Watershed, Oklahoma. We employed the Strengths, Weaknesses, Opportunities, and Threats (SWOTs) approach to identify important issues, and the analytic hierarchy process to rank the perceptions of these groups. We found incongruity between these two groups over internal factors (SW) and external factors (OT) risking sustainable watershed management. External threats such as climate change dominated the research group perceptions, whereas internally prevalent weaknesses such as inability to track water use and lack of a common platform to share scientific data, dominated the government group perceptions. Despite these differences, both groups identified the negative aspect (W + T) as dominant over the positive aspect (S + O), which suggests a pessimistic watershed management future, with risks prevailing over the opportunities. We see this particular congruity of these two stakeholders as an opportunity to initiate a collaborative approach to watershed management in Oklahoma. We also note that the most important factor from each group corresponds to a relatively modest importance from the other group, and therefore suggests the possibility of cooperation rather than conflict in management goals should collaborative watershed management become established in the watershed.

Proposed Epidemiological Cutoff Values for Ceftriaxone, Cefepime, and Colistin in Salmonella.

We tested a diverse set of 500 isolates of nontyphoidal Salmonella enterica subsp. enterica from various animal, food, and human clinical sources for susceptibility to antimicrobials currently lacking epidemiological cutoff values (ECOFFs) set by the European Committee on Antimicrobial Susceptibility Testing. A consortium of five different laboratories each tested 100 isolates, using broth microdilution panels containing twofold dilutions of ceftriaxone, cefepime, and colistin to determine the minimum inhibitory concentrations of each drug when tested against the Salmonella isolates. Based on the resulting data, new ECOFFs of 0.25 µg/mL for ceftriaxone, 0.12 µg/mL for cefepime, and 2 µg/mL for colistin have been proposed. These thresholds will aid in the identification of Salmonella that have phenotypically detectable resistance mechanisms to these important antimicrobials.

Antimicrobial Drug Resistance in Fish Pathogens.

Major concerns surround the use of antimicrobial agents in farm-raised fish, including the potential impacts these uses may have on the development of antimicrobial-resistant pathogens in fish and the aquatic environment. Currently, some antimicrobial agents commonly used in aquaculture are only partially effective against select fish pathogens due to the emergence of resistant bacteria. Although reports of ineffectiveness in aquaculture due to resistant pathogens are scarce in the literature, some have reported mass mortalities in Penaeus monodon larvae caused by Vibrio harveyi resistant to trimethoprim-sulfamethoxazole, chloramphenicol, erythromycin, and streptomycin. Genetic determinants of antimicrobial resistance have been described in aquaculture environments and are commonly found on mobile genetic elements which are recognized as the primary source of antimicrobial resistance for important fish pathogens. Indeed, resistance genes have been found on transferable plasmids and integrons in pathogenic bacterial species in the genera Aeromonas, Yersinia, Photobacterium, Edwardsiella, and Vibrio. Class 1 integrons and IncA/C plasmids have been widely identified in important fish pathogens (Aeromonas spp., Yersinia spp., Photobacterium spp., Edwardsiella spp., and Vibrio spp.) and are thought to play a major role in the transmission of antimicrobial resistance determinants in the aquatic environment. The identification of plasmids in terrestrial pathogens (Salmonella enterica serotypes, Escherichia coli, and others) which have considerable homology to plasmid backbone DNA from aquatic pathogens suggests that the plasmid profiles of fish pathogens are extremely plastic and mobile and constitute a considerable reservoir for antimicrobial resistance genes for pathogens in diverse environments.

Integrative analysis of desert dust size and abundance suggests less dust climate cooling.

Desert dust aerosols affect Earth's global energy balance through interactions with radiation1,2, clouds3,4, and ecosystems5. But the magnitudes of these effects are so uncertain that it remains unclear whether atmospheric dust has a net warming or cooling effect on global climate1,4,6. Consequently, it is still uncertain whether large changes in atmospheric dust loading over the past century have slowed or accelerated anthropogenic climate change4,7-9, and the climate impact of possible future alterations in dust loading is similarly disputed9,10. Here we use an integrative analysis of dust aerosol sizes and abundance to constrain the climatic impact of dust through direct interactions with radiation. Using a combination of observational, experimental, and model data, we find that atmospheric dust is substantially coarser than represented in current climate models. Since coarse dust warms global climate, the dust direct radiative effect (DRE) is likely less cooling than the ~0.4 W/m2 estimated by models in a current ensemble2,11-13. We constrain the dust DRE to - 0.20 (-0.48 to +0.20) W/m2, which suggests that the dust DRE produces only about half the cooling that current models estimate, and raises the possibility that dust DRE is actually net warming the planet.

Revisiting the Observed Correlation Between Weekly Averaged Indian Monsoon Precipitation and Arabian Sea Aerosol Optical Depth.

Dust influences the Indian summer monsoon on seasonal timescales by perturbing atmospheric radiation. On weekly time scales, aerosol optical depth retrieved by satellite over the Arabian Sea is correlated with Indian monsoon precipitation. This has been interpreted to show the effect of dust radiative heating on Indian rainfall on synoptic (few-day) time scales. However, this correlation is reproduced by Earth System Model simulations, where dust is present but its radiative effect is omitted. Analysis of daily variability suggests that the correlation results from the effect of precipitation on dust through the associated cyclonic circulation. Boundary layer winds that deliver moisture to India are responsible for dust outbreaks in source regions far upwind, including the Arabian Peninsula. This suggests that synoptic variations in monsoon precipitation over India enhance dust emission and transport to the Arabian Sea. The effect of dust radiative heating upon synoptic monsoon variations remains to be determined.

Establishing Genotypic Cutoff Values To Measure Antimicrobial Resistance in Salmonella.

Whole-genome sequencing (WGS) has transformed our understanding of antimicrobial resistance, helping us to better identify and track the genetic mechanisms underlying phenotypic resistance. Previous studies have demonstrated high correlations between phenotypic resistance and the presence of known resistance determinants. However, there has never been a large-scale assessment of how well resistance genotypes correspond to specific MICs. We performed antimicrobial susceptibility testing and WGS of 1,738 nontyphoidal Salmonella strains to correlate over 20,000 MICs with resistance determinants. Using these data, we established what we term genotypic cutoff values (GCVs) for 13 antimicrobials against Salmonella For the drugs we tested, we define a GCV as the highest MIC of isolates in a population devoid of known acquired resistance mechanisms. This definition of GCV is distinct from epidemiological cutoff values (ECVs or ECOFFs), which currently differentiate wild-type from non-wild-type strains based on MIC distributions alone without regard to genetic information. Due to the large number of isolates involved, we observed distinct MIC distributions for isolates with different resistance gene alleles, including for ciprofloxacin and tetracycline, suggesting the potential to predict MICs based on WGS data alone.

Predicting the mineral composition of dust aerosols: Insights from elemental composition measured at the Izaña Observatory.

Regional variations of dust mineral composition are fundamental to climate impacts but generally neglected in climate models. A challenge for models is that atlases of soil composition are derived from measurements following wet sieving, which destroys the aggregates potentially emitted from the soil. Aggregates are crucial to simulating the observed size distribution of emitted soil particles. We use an extension of brittle fragmentation theory in a global dust model to account for these aggregates. Our method reproduces the size-resolved dust concentration along with the approximately size-invariant fractional abundance of elements like Fe and Al in the decade-long aerosol record from the Izaña Observatory, off the coast of West Africa. By distinguishing between Fe in structural and free forms, we can attribute improved model behavior to aggregation of Fe and Al-rich clay particles. We also demonstrate the importance of size-resolved measurements along with elemental composition analysis to constrain models.

Soil dust aerosols and wind as predictors of seasonal meningitis incidence in Niger.

BACKGROUND: Epidemics of meningococcal meningitis are concentrated in sub-Saharan Africa during the dry season, a period when the region is affected by the Harmattan, a dry and dusty northeasterly trade wind blowing from the Sahara into the Gulf of Guinea. OBJECTIVES: We examined the potential of climate-based statistical forecasting models to predict seasonal incidence of meningitis in Niger at both the national and district levels. DATA AND METHODS: We used time series of meningitis incidence from 1986 through 2006 for 38 districts in Niger. We tested models based on data that would be readily available in an operational framework, such as climate and dust, population, and the incidence of early cases before the onset of the meningitis season in January-May. Incidence was used as a proxy for immunological state, susceptibility, and carriage in the population. We compared a range of negative binomial generalized linear models fitted to the meningitis data. RESULTS: At the national level, a model using early incidence in December and averaged November-December zonal wind provided the best fit (pseudo-R2 = 0.57), with zonal wind having the greatest impact. A model with surface dust concentration as a predictive variable performed indistinguishably well. At the district level, the best spatiotemporal model included zonal wind, dust concentration, early incidence in December, and population density (pseudo-R2 = 0.41). CONCLUSIONS: We showed that wind and dust information and incidence in the early dry season predict part of the year-to-year variability of the seasonal incidence of meningitis at both national and district levels in Niger. Models of this form could provide an early-season alert that wind, dust, and other conditions are potentially conducive to an epidemic.

An evaluation of a community-academic-clinical partnership to reduce prostate cancer disparities in the South.

Engaging partners in the planning, implementation, and evaluation of cancer education programs is critical for improving the health of our communities. A 2-year pilot education intervention on prostate cancer decision making and participation in medical research was funded by the National Cancer Institute. The partnership involving community members and clinical staff at a cancer center was used to develop recruitment strategies and plan for the implementation of the intervention with African-American middle-age and older men and female family members. We assessed partners' perceptions of this community-academic-clinical research collaboration. In year 2, eight project advisory council members were selected among existing partners and year 1 participants to serve as a formal committee. Council members were required to participate in telephone and in person meetings and actively support recruitment/implementation efforts. At the conclusion of the project, 20 individuals (all clinical and community partners, including the eight advisory council members) were invited to complete a survey to assess their perceived impact of the collaboration on the community and provide suggestions for future collaborations. Most partners agreed that their organization benefitted from the collaboration and that various aspects of the advisory council process (e.g., both formal and informal communication) worked well. The most noted accomplishment of the partnership related to leveraging the collaboration to make men more knowledgeable about prostate cancer decision making. Suggested improvements for future collaborations included distributing more frequent updates regarding project successes. Evaluating partners' perceptions of this collaboration provided important recommendations for future planning, implementation, and evaluation of community-based cancer education programs.

Oxytetracycline pharmacokinetics in rainbow trout during and after an orally administered medicated feed regimen.

The pharmacokinetic-pharmacodynamic predictor of antimicrobial activity for tetracyclines is reported to be the area under the concentration-time curve at steady state (AUC(ss)) divided by the minimal inhibitory concentration of the targeted pathogen. Here, we estimate AUC(ss) values for oxytetracycline (OTC) in serum of rainbow trout Oncorhynchus mykiss by using a destructive sampling study design. Seventy-two rainbow trout were fed OTC-medicated feed at 74.7 +/- 1.5 mg/kg (mean +/- SD) body weight (BW) by oral gavage for 10 consecutive days. Serum was collected from nine fish at 1, 3, 6, 8, 10, 12, 15, and 22 d after dosing began. Serum OTC concentrations were measured by high-performance liquid chromatography with a 0.01-microg/mL limit of detection. The average OTC AUC(ss) was 29.2 microg x h/mL and was estimated using nonlinear mixed-effects modeling and bootstrap resampling techniques. The elimination half-life was estimated as 85.0 h, and the fraction of steady state achieved was estimated as 0.85. The calculated AUC(ss) (24.8 microg x h/mL) following 10 d of oral dosing with 75 mg OTC/kg BW was less than the estimated AUC(ss). Results suggest that the pharmacokinetics of OTC exposure, including the AUC(ss), is better evaluated by using multiday dosimetry than by using a standard single-dose protocol.

Amplification of the North American "Dust Bowl" drought through human-induced land degradation.

The "Dust Bowl" drought of the 1930s was highly unusual for North America, deviating from the typical pattern forced by "La Nina" with the maximum drying in the central and northern Plains, warm temperature anomalies across almost the entire continent, and widespread dust storms. General circulation models (GCMs), forced by sea surface temperatures (SSTs) from the 1930s, produce a drought, but one that is centered in southwestern North America and without the warming centered in the middle of the continent. Here, we show that the inclusion of forcing from human land degradation during the period, in addition to the anomalous SSTs, is necessary to reproduce the anomalous features of the Dust Bowl drought. The degradation over the Great Plains is represented in the GCM as a reduction in vegetation cover and the addition of a soil dust aerosol source, both consequences of crop failure. As a result of land surface feedbacks, the simulation of the drought is much improved when the new dust aerosol and vegetation boundary conditions are included. Vegetation reductions explain the high temperature anomaly over the northern U.S., and the dust aerosols intensify the drought and move it northward of the purely ocean-forced drought pattern. When both factors are included in the model simulations, the precipitation and temperature anomalies are of similar magnitude and in a similar location compared with the observations. Human-induced land degradation is likely to have not only contributed to the dust storms of the 1930s but also amplified the drought, and these together turned a modest SST-forced drought into one of the worst environmental disasters the U.S. has experienced.