Managing Forests for Biodiversity Conservation and Climate Change Mitigation.

We include biodiversity impacts in forest management decision making by incorporating the countryside species area relationship model into the partial equilibrium model GLOBIOM-Forest. We tested three forest management intensities (low, medium, and high) and limited biodiversity loss via an additional constraint on regional species loss. We analyzed two scenarios for climate change mitigation. RCP1.9, the higher mitigation scenario, has more biodiversity loss than the reference RCP7.0, suggesting a trade-off between climate change mitigation, with increased bioenergy use, and biodiversity conservation in forests. This trade-off can be alleviated with biodiversity-conscious forest management by (1) shifting biomass production destined to bioenergy from forests to energy crops, (2) increasing areas under unmanaged secondary forest, (3) reducing forest management intensity, and (4) reallocating biomass production between and within regions. With these mechanisms, it is possible to reduce potential global biodiversity loss by 10% with minor changes in economic outcomes. The global aggregated reduction in biodiversity impacts does not imply that biodiversity impacts are reduced in each ecoregion. We exemplify how to connect an ecologic and an economic model to identify trade-offs, challenges, and possibilities for improved decisions. We acknowledge the limitations of this approach, especially of measuring and projecting biodiversity loss.

Relation of blood lead levels and lead in gasoline: an updated systematic review.

BACKGROUND: Millions of tons of lead were added to gasoline worldwide beginning in 1922, and leaded gasoline has been a major source of population lead exposure. In 1960s, lead began to be removed from automotive gasoline. Removal was completed in 2021. OBJECTIVES: To determine whether removal of lead from automotive gasoline is associated with declines in population mean blood lead levels (BPb). METHODS: We examined published studies that reported population blood leaded levels for two or more years, and we calculated average concentrations of lead in gasoline corresponding to the years and locations of the blood lead level measurements. RESULTS: Removal of lead from gasoline is associated with declines in BPb in all countries examined. In some countries, BPb continues to fall after lead has been eliminated from gasoline. Following elimination of lead from gasoline, BPb less than 1 µg/dL have been observed in several European and North American countries, and BPb less than 3 µg/dL have been documented in several studies from South America. DISCUSSION: There remain many countries for which no multi-year studies of populations BPb have been identified, including all of Central America, high population countries including Pakistan and Indonesia, and major lead producers including Australia and Russia. CONCLUSION: Removal of lead from gasoline has been a public health success. Elimination of lead from gasoline has enabled many countries to achieve population mean BPb levels of 1 µg/dL or lower. These actions have saved lives, increased children's intelligence and created great economic benefit in countries worldwide.

Incorporating New Technologies in EEIO Models.

We propose a methodology to add new technologies into Environmentally Extended Input-Output (EEIO) models based on a Supply and Use framework. The methodology provides for adding new industries (new technologies) and a new commodity under the assumption that the new commodity will partially substitute for a functionally-similar existing commodity of the baseline economy. The level of substitution is controlled by a percentage (%) as a variable of the model. In the Use table, a percentage of the current use of the existing commodity is transferred to the new commodity. The Supply or Make table is modified assuming that the new industries are the only ones producing the new commodity. We illustrate the method for the USEEIO model, for the addition of second generation biofuels, including naphtha, jet fuel and diesel fuel. The new industries' inputs, outputs and value-added components needed to produce the new commodity are drawn from process-based life cycle inventories (LCIs). Process-based LCI inputs and outputs per physical functional unit are transformed to prices and assigned to commodities and environmental flow categories for the EEIO model. This methodology is designed to evaluate the environmental impacts of substituting products in the current US economy with bio-versions, produced by new technologies, that are intended to reduce negative environmental impacts. However, it can be applied for any new commodity for which the substitution assumption is reasonable.

Scientific and Regulatory Policy Committee Points to Consider for Medical Device Implant Site Evaluation in Nonclinical Studies.

Nonclinical implantation studies are a common and often critical step for medical device safety assessment in the bench-to-market pathway. Nonclinical implanted medical devices or drug-device combination products require complex macroscopic and microscopic pathology evaluations due to the physical presence of the device itself and unique tissue responses to device materials. The Medical Device Implant Site Evaluation working group of the Society of Toxicologic Pathology's (STP) Scientific and Regulatory Policy Committee (SRPC) was tasked with reviewing scientific, technical, and regulatory considerations for these studies. Implant site evaluations require highly specialized methods and analytical schemes that should be designed on a case-by-case basis to address specific study objectives. Existing STP best practice recommendations can serve as a framework when performing nonclinical studies under Good Laboratory Practices and help mitigate limitations in standards and guidances for implant evaluations (e.g., those from the International Organization for Standardization [ISO], ASTM International). This article integrates standards referenced by sponsors and regulatory bodies with practical pathology evaluation methods for implantable medical devices and combination products. The goal is to ensure the maximum accuracy and scientific relevance of pathology data acquired during a medical device or combination drug-device implantation study.

Recovery of Critical Metals from Aqueous Sources.

Critical metals, identified from supply, demand, imports, and market factors, include rare earth elements (REE), platinum group metals, precious metals, and other valuable metals such as lithium, cobalt, nickel, and uranium. Extraction of metals from U.S. saline aqueous, emphasizing saline, sources is explored as an alternative to hardrock ore mining. Potential aqueous sources include seawater, desalination brines, oil-and-gas produced waters, geothermal aquifers, and acid mine drainage, among others. A feasibility assessment reveals opportunities for recovery of lithium, strontium, magnesium, and several REE from select sources, in quantities significant for U.S. manufacturing and for reduction of U.S. reliance on international supply chains. This is a conservative assessment given that water quality data are lacking for a significant number of critical metals in certain sources. The technology landscape for extraction and recovery of critical metals from aqueous sources is explored, identifying relevant processes along with knowledge gaps. Our analysis indicates that aqueous mining would result in much lower environmental impacts on water, air, and land than ore mining. Preliminary assessments of the economics and energy consumption of recovery show potential for recovery of critical metals.

Combined Heat and Power May Conflict with Decarbonization Goals-Air Emissions of Natural Gas Combined Cycle Power versus Combined Heat and Power Systems for Commercial Buildings.

This study compares the environmental impacts of a centralized natural gas combined cycle (NGCC) and a distributed natural gas-fired combined heat and power (CHP) energy system in the United States. We develop an energy-balance model in which each energy system supplies the electric, heating, and cooling demands of 16 commercial building types in 16 climate zones of the United States. We assume a best-case scenario where all the CHP's heat and power are allocated toward building demands to ensure robust results. We quantify the greenhouse gas (GHG) emissions, conventional air pollutants (CAPs), and natural gas (NG) consumption. In most cases, the decentralized CHP system increases GHG emissions, decreases CAP emissions, and decreases NG consumption relative to the centralized NGCC system. Only fuel-cell CHPs were able to simultaneously reduce GHG, CAP, and NG consumption relative to the NGCC-based system. The results suggest that despite their energy efficiency benefits, standard distributed CHP-based systems typically do not have enough benefits compared to an NGCC-based system to justify a reorganization of existing infrastructure systems. Because fuel-cell CHPs can also use hydrogen as a fuel source, they are compatible with decarbonized energy systems and may aid in the transition toward a cleaner energy economy.

Similarities in Recalcitrant Structures of Industrial Non-Kraft and Kraft Lignin.

This work compares the structure of industrially isolated lignin samples from kraft pulping and three alternative processes: butanol organosolv, supercritical water hydrolysis, and sulfur dioxide/ethanol/water fractionation. Kraft processes are known to produce highly condensed lignin, with reduced potential for catalytic depolymerization, whereas the alternative processes have been hypothesized to impact the lignin less. The structural properties most relevant to catalytic depolymerization are characterized by elemental analysis, quantitative 13 C and 2 D HQSC NMR spectroscopy, gel permeation chromatography, and thermogravimetric analysis. Quantification of the ß-O-4 ether bond content shows partial depolymerization, with all samples having less than 12 bonds per 100 aromatic units. This results in theoretical monomer yields of less than 5 %, strongly suggesting the alternative fractionation processes generate highly condensed lignin structures that are no more suitable for catalytic depolymerization than kraft lignin. However, the different thermal degradation profiles suggest there are physicochemical differences that could be leveraged in other valorization strategies.

Future Lyme disease risk in the south-eastern United States based on projected land cover.

Lyme disease is the most significant vector-borne disease in the United States, and its southward advance over several decades has been quantified. Previous research has examined the potential role of climate change on the disease's expansion, but no studies have considered the role of future land cover upon its distribution. This research examines Lyme disease risk in the south-eastern U.S. based on projected land cover developed under four Intergovernmental Panel on Climate Change Scenarios: A1B, A2, B1, and B2. Land cover types and edge indices significantly associated with Lyme disease in Virginia were incorporated into a spatial Poisson regression model to quantify potential land cover suitability for Lyme disease in the south-eastern U.S. under each scenario. Our results indicate an intensification of potential land cover suitability for Lyme disease under the A scenarios and a decrease of potential land cover suitability under the B scenarios. The decrease under the B scenarios is a critical result, indicating that Lyme disease risk can be decreased by making different land cover choices. Additionally, health officials can focus efforts in projected high incidence areas.

A mid-century ecological forecast with partitioned uncertainty predicts increases in loblolly pine forest productivity.

Ecological forecasting of forest productivity involves integrating observations into a process-based model and propagating the dominant components of uncertainty to generate probability distributions for future states and fluxes. Here, we develop a forecast for the biomass change in loblolly pine (Pinus taeda) forests of the southeastern United States and evaluate the relative contribution of different forms of uncertainty to the total forecast uncertainty. Specifically, we assimilated observations of carbon and flux stocks and fluxes from sites across the region, including global change experiments, into a forest ecosystem model to calibrate the parameter distributions and estimate the process uncertainty (i.e., model structure uncertainty revealed in the residuals of the calibration). Using this calibration, we forecasted the change in biomass within each 12-digit Hydrologic (H12) unit across the native range of loblolly pine between 2010 and 2055 under the Representative Concentration Pathway 8.5 scenario. Averaged across the region, productivity is predicted to increase by a mean of 31% between 2010 and 2055 with an average forecast 95% quantile interval of ±15 percentage units. The largest increases were predicted in cooler locations, corresponding to the largest projected changes in temperature. The forecasted mean change varied considerably among the H12 units (3-80% productivity increase), but only units in the warmest and driest extents of the loblolly pine range had forecast distributions with probabilities of a decline in productivity that exceeded 5%. By isolating the individual components of the forecast uncertainty, we found that ecosystem model process uncertainty made the largest individual contribution. Ecosystem model parameter and climate model uncertainty had similar contributions to the overall forecast uncertainty, but with differing spatial patterns across the study region. The probabilistic framework developed here could be modified to include additional sources of uncertainty, including changes due to fire, insects, and pests: processes that would result in lower productivity changes than forecasted here. Overall, this study presents an ecological forecast at the ecosystem management scale so that land managers can explicitly account for uncertainty in decision analysis. Furthermore, it highlights that future work should focus on quantifying, propagating, and reducing ecosystem model process uncertainty.

Use of self-monitoring tools in a clinic sample of adults with type 2 diabetes.

Self-monitoring is an effective strategy for chronic disease management; many readily available mobile applications allow tracking of diabetes-related health behaviors but their use has not yet been integrated into routine clinical care. How patients engage with these applications in the real world is not well understood. The specific aim of this study is to survey adults with type 2 diabetes (T2D) regarding self-monitoring behaviors, including mobile application use. In 2015, we surveyed an adult diabetes clinic population (n = 96) regarding self-monitoring behaviors: diet, physical activity, weight, and blood glucose. Self-monitoring with any method ranged from 20-90 %. About half of the participants owned smartphones; few had mobile applications. The most common app-tracked behavior was physical activity, then weight and diet. Despite numerous available mobile health-tracking applications, few T2D adults from our sample used them, though many reported self-monitoring with other methods.

Monitoring of antimicrobial susceptibility of respiratory tract pathogens isolated from diseased cattle and pigs across Europe, 2009-2012: VetPath results.

VetPath is an ongoing pan-European antibiotic susceptibility monitoring programme that collects pathogens from diseased cattle, pigs and poultry. In the current study, 996 isolates from cattle and pig respiratory tract infections were tested for their antimicrobial susceptibilities. Non-replicate lung samples or nasopharyngeal/nasal swabs were collected from animals with acute clinical signs in 10 countries during 2009-2012. Pasteurella multocida, Mannheimia haemolytica and Histophilus somni from cattle and P. multocida, Actinobacillus pleuropneumoniae, Haemophilus parasuis, Bordetella bronchiseptica and Streptococcus suis from pigs were isolated by standard methods. S. suis was also isolated from meningitis cases. MIC values of 16 or 17 antibiotics were assessed centrally by broth microdilution following CLSI standards. Results were interpreted using CLSI breakpoints where available. Cattle isolates were generally highly susceptible to most antibiotics, except to tetracycline (3.0-12.0% resistance). Low levels of resistance (0-4.0%) were observed for the macrolide antibiotics. Resistance to spectinomycin varied from 0 to 6.0%. In pig isolates similar observations were made. Resistance to amoxicillin/clavulanic acid, ceftiofur, enrofloxacin, florfenicol, tulathromycin, tiamulin and tilmicosin was absent or <2%. Trimethoprim/sulfamethoxazole resistance varied from 1.9 to 5.3%, but tetracycline resistance varied from 20.4% in P. multocida to 88.1% in S. suis. For most antibiotics and pathogens the percentage resistance remained unchanged or only increased numerically as compared to that of the period 2002-2006. In conclusion, absence or low resistance to antibiotics with defined clinical breakpoints, except for tetracycline, was observed among the major respiratory tract pathogens recovered from livestock. Comparison of all antibiotics and organisms was hampered since for almost half of the antibiotics no CLSI-defined breakpoints were available.

Longitudinal effects of prenatal exposure to air pollutants on self-regulatory capacities and social competence.

BACKGROUND: We evaluated the influence of prenatal exposure to widespread urban air pollutants on the development of self-regulation and social competence in a longitudinal prospective cohort of children born to nonsmoking minority women in New York City. METHODS: Air pollutant exposure was estimated categorically by level of polycyclic aromatic hydrocarbon (PAH)-DNA adducts in maternal blood collected at delivery, providing a biomarker of maternal exposure to PAH over a 2- to 3-month period. Deficient emotional self-regulation (DESR) was defined as moderate elevations on three specific scales of the child behavior checklist (anxious/depressed, aggressive behavior, and attention problems). We used generalized estimating equations to assess the influence of prenatal exposure to PAH on DESR in children at 3-5, 7, 9, and 11 years of age, adjusted for gender and race/ethnicity. Next, we assessed the association of prenatal exposure to PAH with social competence, as measured by the social responsiveness scale (SRS), the association of impaired self-regulation with social competence, and whether impairment in self-regulation mediated the association of prenatal exposure to PAH with social competence. RESULTS: We detected a significant interaction (at p = .05) of exposure with time, in which the developmental trajectory of self-regulatory capacity was delayed in the exposed children. Multiple linear regression revealed a positive association between presence of PAH-DNA adducts and problems with social competence (p < .04), level of dysregulation and problems with social competence (p < .0001), and evidence that self-regulation mediates the association of prenatal exposure to PAH with social competence (p < .0007). CONCLUSIONS: These data suggest that prenatal exposure to PAH produces long-lasting effects on self-regulatory capacities across early and middle childhood, and that these deficits point to emerging social problems with real-world consequences for high-risk adolescent behaviors in this minority urban cohort.

New approach for optimal electricity planning and dispatching with hourly time-scale air quality and health considerations.

Integrating accurate air quality modeling with decision making is hampered by complex atmospheric physics and chemistry and its coupling with atmospheric transport. Existing approaches to model the physics and chemistry accurately lead to significant computational burdens in computing the response of atmospheric concentrations to changes in emissions profiles. By integrating a reduced form of a fully coupled atmospheric model within a unit commitment optimization model, we allow, for the first time to our knowledge, a fully dynamical approach toward electricity planning that accurately and rapidly minimizes both cost and health impacts. The reduced-form model captures the response of spatially resolved air pollutant concentrations to changes in electricity-generating plant emissions on an hourly basis with accuracy comparable to a comprehensive air quality model. The integrated model allows for the inclusion of human health impacts into cost-based decisions for power plant operation. We use the new capability in a case study of the state of Georgia over the years of 2004-2011, and show that a shift in utilization among existing power plants during selected hourly periods could have provided a health cost savings of $175.9 million dollars for an additional electricity generation cost of $83.6 million in 2007 US dollars (USD2007). The case study illustrates how air pollutant health impacts can be cost-effectively minimized by intelligently modulating power plant operations over multihour periods, without implementing additional emissions control technologies.

Antimicrobial susceptibility monitoring of mastitis pathogens isolated from acute cases of clinical mastitis in dairy cows across Europe: VetPath results.

VetPath is an ongoing pan-European antimicrobial susceptibility monitoring programme collecting pathogens from diseased cattle, pigs and poultry not recently treated with antibiotics. Non-replicate milk samples were collected from cows with acute clinical mastitis in eight countries. Escherichia coli, Staphylococcus aureus and Streptococcus uberis were isolated by standardised methods. Antimicrobial susceptibility was determined in a central laboratory by CLSI broth microdilution methodology; results were interpreted using clinical breakpoints where available. Among E. coli (n=280), resistance to tetracycline (14.3%) and cefapirin (11.1%) were most common. Resistance to other ß-lactam antibiotics was absent (ceftiofur) or very low (cefalexin, amoxicillin/clavulanic acid). The MIC90 of enrofloxacin and marbofloxacin was 0.03 and 0.06µg/mL, respectively, with 0.7% of strains displaying a deviating high MIC. Staphylococcus aureus (n=250) were susceptible to most antibiotics tested, although 36.0% were resistant to penicillin G. For other ß-lactam antibiotics where a CLSI breakpoint was available, no resistance was detected. Tetracycline resistance was low (5.2%). Streptococcus uberis (n=282) were susceptible to all ß-lactam antibiotics, although 29.8% were intermediately susceptible to penicillin G; 18.8% of strains were resistant to erythromycin and 28.7% to tetracycline. This European study shows that bacteria associated with acute clinical mastitis are susceptible to most antibiotics with the exception of penicillin G against S. aureus, and erythromycin and tetracycline against S. uberis. The results of this study should serve as a reference baseline. This work also highlights the urgent need to set additional clinical breakpoints for antibiotics frequently used to treat mastitis.

Antimicrobial susceptibility monitoring of respiratory tract pathogens isolated from diseased cattle and pigs across Europe: the VetPath study.

VetPath is an ongoing pan-European antibiotic susceptibility monitoring programme collecting pathogens from diseased antimicrobial non-treated cattle, pigs and poultry. In the current study, 1001 isolates from cattle and pig respiratory tract infections were tested for their antimicrobial susceptibilities. Non-replicate lung samples or nasopharyngeal/nasal swabs were collected from animals with acute clinical signs in 11 countries during 2002-2006. Pasteurella multocida and Mannheimia haemolytica from cattle and P. multocida, Actinobacillus pleuropneumoniae and Streptococcus suis from pigs were isolated by standard methods. S. suis was also isolated from meningitis cases. MICs of 16 antibiotics were assessed centrally by broth microdilution following CLSI recommendations. Results were interpreted using CLSI breakpoints where available. P. multocida (231) and M. haemolytica (138) isolates were all susceptible to amoxicillin/clavulanic acid, ceftiofur, enrofloxacin and trimethoprim/sulfamethoxazole. Resistance to florfenicol and spectinomycin was 0.4% and 3.5% in P. multocida, respectively, and absent in M. haemolytica isolates. Tetracycline resistance was 5.7% and 14.6% for P. multocida and M. haemolytica. In pigs, 230 P. multocida, 220 A. pleuropneumoniae and 182 S. suis isolates were recovered. Resistance to amoxicillin/clavulanic acid, ceftiofur, enrofloxacin, florfenicol, tiamulin and tilmicosin was absent or <1%. Trimethoprim/sulfamethoxazole resistance was 3-6% and tetracycline resistance varied from 14.7% in A. pleuropneumoniae to 81.8% in S. suis. In conclusion, low resistance to antibiotics with defined clinical breakpoints, except for tetracycline, was observed among the major respiratory tract pathogens recovered from cattle and pigs. Since for approximately half of the antibiotics in this panel no CLSI-defined breakpoints were available, setting of the missing veterinary breakpoints is important.

Antimicrobial resistance monitoring projects for zoonotic and indicator bacteria of animal origin: common aspects and differences between EASSA and EFSA.

Resistance monitoring programmes are essential to generate data for inclusion in the scientific risk assessment of the potential for transmission of antimicrobial-resistant bacteria or their resistance determinants from food-producing animals to humans. This review compares the technical specifications on monitoring of antimicrobial resistance in zoonotic Salmonella, Campylobacter and indicator Escherichia coli and Enterococcus as performed by the European Food Safety Authority (EFSA) with veterinary pharmaceutical industry's European Antimicrobial Susceptibility Surveillance in Animals (EASSA) programme. The authors conclude that most of EFSA's recent monitoring recommendations have been covered by EASSA since the start of the latter programme in 1998. The major difference between the two programmes is the classification into 'susceptible' versus 'resistant'. While EFSA categorises all isolates with an MIC value above the epidemiological cut-off value as 'resistant', EASSA differentiates between 'percentage decreased susceptible' and 'percentage clinical resistant' strains by applying both epidemiological cut-off values and clinical breakpoints. Because there is still a need to further improve harmonisation among individual EU Member State activities, Animal Health Industry welcomes EFSA's initiative to further improve the quality of resistance monitoring as it is of utmost importance to apply standardised collection procedures and harmonised susceptibility testing, when monitoring antimicrobial resistance across Europe.

Coordinated EV adoption: double-digit reductions in emissions and fuel use for $40/vehicle-year.

Adoption of electric vehicles (EVs) would affect the costs and sources of electricity and the United States efficiency requirements for conventional vehicles (CVs). We model EV adoption scenarios in each of six regions of the Eastern Interconnection, containing 70% of the United States population. We develop electricity system optimization models at the multidecade, day-ahead, and hour-ahead time scales, incorporating spatial wind energy modeling, endogenous modeling of CV efficiencies, projections for EV efficiencies, and projected CV and EV costs. We find two means to reduce total consumer expenditure (TCE): (i) controlling charge timing and (ii) unlinking the fuel economy regulations for CVs from EVs. Although EVs provide minimal direct GHG reductions, controlled charging provides load flexibility, lowering the cost of renewable electricity. Without EVs, a 33% renewable electricity standard (RES) would cost $193/vehicle-year more than the reference case (10% RES). Combining a 33% RES, EVs with controlled charging and unlinking would reduce combined electric- and vehicle-sector CO2 emissions by 27% and reduce gasoline consumption by 59% for $40/vehicle-year more than the reference case. Coordinating EV adoption with adoption of controlled charging, unlinked fuel economy regulations, and renewable electricity standards would provide low-cost reductions in emissions and fuel usage.

Electric urban delivery trucks: energy use, greenhouse gas emissions, and cost-effectiveness.

We compare electric and diesel urban delivery trucks in terms of life-cycle energy consumption, greenhouse gas (GHG) emissions, and total cost of ownership (TCO). The relative benefits of electric trucks depend heavily on vehicle efficiency associated with drive cycle, diesel fuel price, travel demand, electric drive battery replacement and price, electricity generation and transmission efficiency, electric truck recharging infrastructure, and purchase price. For a drive cycle with frequent stops and low average speed such as the New York City Cycle (NYCC), electric trucks emit 42-61% less GHGs and consume 32-54% less energy than diesel trucks, depending upon vehicle efficiency cases. Over an array of possible conditions, the median TCO of electric trucks is 22% less than that of diesel trucks on the NYCC. For a drive cycle with less frequent stops and high average speed such as the City-Suburban Heavy Vehicle Cycle (CSHVC), electric trucks emit 19-43% less GHGs and consume 5-34% less energy, but cost 1% more than diesel counterparts. Considering current and projected U.S. regional electricity generation mixes, for the baseline case, the energy use and GHG emissions ratios of electric to diesel trucks range from 48 to 82% and 25 to 89%, respectively.

Pan-European monitoring of susceptibility to human-use antimicrobial agents in enteric bacteria isolated from healthy food-producing animals.

OBJECTIVES: To determine the antimicrobial susceptibility of Escherichia coli, Salmonella, Campylobacter and Enterococcus from cattle, pigs and chickens across the European Union (EU) using uniform methodology. METHODS: Intestinal samples (1624) were taken at slaughter across five EU countries. Bacteria were isolated in national laboratories, whilst MICs were determined in a central laboratory for key antimicrobials used in human medicine. Clinical resistance was based on CLSI breakpoints and decreased susceptibility based on European Food Safety Authority (EFSA)/EUCAST epidemiological cut-off values. RESULTS: Isolation rates were high for E. coli (n=1540), low for Salmonella (n=201) and intermediate for Campylobacter (n=940) and Enterococcus (n=786). For E. coli and Salmonella, clinical resistance to newer compounds (cefepime, cefotaxime and ciprofloxacin) was absent or low, but decreased susceptibility was apparent, particularly in chicken strains. Resistance to older compounds (except gentamicin) was variable and higher. Colistin resistance was absent for E. coli, but apparent for Salmonella. For Campylobacter jejuni, ciprofloxacin resistance was markedly prevalent for chickens, whereas clinical resistance and decreased susceptibility to erythromycin was absent or very low. For Campylobacter coli, resistance was notably higher. None of the Enterococcus faecium strains was resistant to linezolid, but some were resistant to ampicillin or vancomycin. Resistance to quinupristin/dalfopristin was frequent. CONCLUSIONS: Resistance patterns varied widely depending on bacterial species, antibiotics, hosts and region. Resistance varied among countries, particularly for older antimicrobials, but clinical resistance to newer antibiotics used to treat foodborne disease in humans was generally very low. In the absence of resistance to newer compounds in E. coli and Salmonella, the apparent decreased susceptibility should be monitored.

Individual trabecula segmentation (ITS)-based morphological analyses and microfinite element analysis of HR-pQCT images discriminate postmenopausal fragility fractures independent of DXA measurements.

Osteoporosis is typically diagnosed by dual-energy X-ray absorptiometry (DXA) measurements of areal bone mineral density (aBMD). Emerging technologies, such as high-resolution peripheral quantitative computed tomography (HR-pQCT), may increase the diagnostic accuracy of DXA and enhance our mechanistic understanding of decreased bone strength in osteoporosis. Women with (n = 68) and without (n = 101) a history of postmenopausal fragility fracture had aBMD measured by DXA, trabecular plate and rod microarchitecture measured by HR-pQCT image-based individual trabecula segmentation (ITS) analysis, and whole bone and trabecular bone stiffness by microfinite element analysis (µFEA) of HR-pQCT images at the radius and tibia. DXA T-scores were similar in women with and without fractures at the spine, hip, and 1/3 radius, but lower in fracture subjects at the ultradistal radius. Trabecular microarchitecture of fracture subjects was characterized by preferential reductions in trabecular plate bone volume, number, and connectivity over rod trabecular parameters, loss of axially aligned trabeculae, and a more rod-like trabecular network. In addition, decreased thickness and size of trabecular plates were observed at the tibia. The differences between groups were greater at the radius than the tibia for plate number, rod bone volume fraction and number, and plate-rod and rod-rod junction densities. Most differences between groups remained after adjustment for T-score by DXA. At a fixed bone volume fraction, trabecular plate volume, number, and connectivity were directly associated with bone stiffness. In contrast, rod volume, number, and connectivity were inversely associated with bone stiffness. In summary, HR-pQCT-based ITS and µFEA measurements discriminate fracture status in postmenopausal women independent of DXA measurements. Moreover, these results suggest that preferential loss of plate-like trabeculae contribute to lower trabecular bone and whole bone stiffness in women with fractures. We conclude that HR-pQCT-based ITS and µFEA measurements increase our understanding of the microstructural pathogenesis of fragility fracture in postmenopausal women.