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Clostridioides difficile infection (CDI) is the most frequently reported hospital-acquired infection in the United States. Bioaerosols generated during toilet flushing are a possible mechanism for the spread of this pathogen in clinical settings.
To measure the bioaerosol concentration from toilets of patients with CDI before and after flushing.
In this pilot study, bioaerosols were collected 0.15 m, 0.5 m, and 1.0 m from the rims of the toilets in the bathrooms of hospitalized patients with CDI. Inhibitory, selective media were used to detect C. difficile and other facultative anaerobes. Room air was collected continuously for 20 minutes with a bioaerosol sampler before and after toilet flushing. Wilcoxon rank-sum tests were used to assess the difference in bioaerosol production before and after flushing.
Rooms of patients with CDI at University of Iowa Hospitals and Clinics.
Bacteria were positively cultured from 8 of 24 rooms (33%). In total, 72 preflush and 72 postflush samples were collected; 9 of the preflush samples (13%) and 19 of the postflush samples (26%) were culture positive for healthcare-associated bacteria. The predominant species cultured were Enterococcus faecalis, E. faecium, and C. difficile. Compared to the preflush samples, the postflush samples showed significant increases in the concentrations of the 2 large particle-size categories: 5.0 µm (P = .0095) and 10.0 µm (P = .0082).
Bioaerosols produced by toilet flushing potentially contribute to hospital environmental contamination. Prevention measures (eg, toilet lids) should be evaluated as interventions to prevent toilet-associated environmental contamination in clinical settings.
This paper focuses on the problem of skin corrosion on the upper wing surfaces of rib-stiffened aircraft. For maritime and military transport aircraft this often results in multiple co-located repairs. The common approach to corrosion damage in operational aircraft is to blend out the corrosion and rivet a mechanical doubler over the region. In particular this paper describes the results of a combined numerical and experimental investigation into the ability of the additive metal technology, Supersonic Particle Deposition (SPD), to restore the load-carrying capacity of rib-stiffened wing planks with simulated skin corrosion. The experimental results reveal that unrepaired skin corrosion can result in failure by yielding. The experimental results also reveal that SPD repairs to skin corrosion can restore the stress field in the structure, and can ensure that the load-carrying capability of the repaired structure is above proof load.
Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (β-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-β-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites’ levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring.
In Crowe & Taylor (J. Fluid Mech., vol. 850, 2018, pp. 179–211) we described a theory for the evolution of density fronts in a rotating reference frame subject to strong vertical mixing using an asymptotic expansion in small Rossby number,
. We found that the front reaches a balanced state where vertical diffusion is balanced by horizontal advection in the buoyancy equation. The depth-averaged buoyancy obeys a nonlinear diffusion equation which admits a similarity solution corresponding to horizontal spreading of the front. Here we use numerical simulations of the full momentum and buoyancy equations to investigate this problem for a wide range of Rossby and Ekman numbers. We examine the accuracy of our asymptotic solution and find that many aspects of the solution are valid for
. However, the asymptotic solution departs from the numerical simulations for small Ekman numbers where the dominant balance in the momentum equation changes. We trace the source of this discrepancy to a depth-independent geostrophic flow that develops on both sides of the front and we develop a modification to the theory described in Crowe & Taylor (2018) to account for this geostrophic flow. The refined theory closely matches the numerical simulations, even for
. Finally, we develop a new scaling for the intense vertical velocity that can develop in thin bands at the edges of the front.
During the US military occupation of Haiti, domestic workers performed the crucial labor that allowed Marine households, the city of Port-au-Prince, and the entire country to function. In this sense, they represented a human infrastructure for the entire occupation. Their experiences show that the debates over labor, race, and sovereignty that defined the high politics of the occupation actually reached into private spaces where face-to-face interactions between occupier and occupied occurred. Domestic work, like other types of labor in the occupation, ran the gamut from highly coerced forms of unpaid child labor and convict work to various configurations of wage labor. Domestic sites influenced mutual processes of race-making, including the US exoticist obsession with Haitian Vodou. Servants’ conflicts with their Marine employers included—but ultimately went beyond—daily struggles over labor. Their proximity to marines influenced domestics’ participation in acts of anti-imperial activism, such as the Caco rebellion, and explains why servants were invoked by radical journalists and cultural nationalist writers who opposed US rule. Domestics’ activities also highlight under-explored areas of Haitian activism, such as their use of formal state institutions to seek redress and their participation in emerging forms of urban protest that included other members of the urban working class. Although novel and relatively small during the occupation, such urban protests have become a staple of Haitian politics in the present day.
The current study aimed to examine the psychometric properties of two geriatric anxiety measures: the Geriatric Anxiety Inventory (GAI) and the Geriatric Anxiety Scale (GAS). This study also aimed to determine the relationships of these measures with two measures of functional ability and impairment: the Barkley Functional Impairment Scale (BFIS) and the Everyday Cognition Scale (E-Cog).
Confirmatory factor analyses (CFA) were used to analyze the factor structures of the GAI and GAS in older adults. Tests for dependent correlations were used to examine the relationship between anxiety scales and functioning.
Amazon’s Mechanical Turk
348 participants (aged 55–85, M= 62.75 (4.8), 66.5% female) with no history of psychosis or traumatic brain injury.
CFAs supported the previously demonstrated bifactor solution for the GAI. For the GAS, the previously demonstrated three-factor model demonstrated a good-to-excellent fit. Given the high correlation between the cognitive and affective factors (r =.89), a bifactor solution was also tested. The bifactor model of the GAS was found to be primarily unidimensional. Tests for dependent correlations revealed that the GAS demonstrated stronger relationships with measures of self-reported functional impairment than the GAI.
The current study provides further psychometric validation of the factor structure of two geriatric anxiety measures in an older adult sample. The results support previous work completed on the GAI and the GAS. The GAS was more strongly correlated with self-reported functional impairment than the GAI, which may reflect differences in content in the two measures.
While much research has focused on crop damage following foliar exposure to auxin herbicides, reports documenting the risk posed by exposure via root uptake of irrigation water are lacking. Herbicide residues circulated in tailwater recovery systems may pose threats of cross-crop impacts to nonresistant cultivars with known sensitivity to auxins. An auxin-susceptible soybean [Glycine max (L.) Merr.] cultivar was grown in a controlled growth chamber environment and exposed to dicamba dissolved in irrigation water applied to the soil surface, simulating furrow irrigation. Five herbicide treatment concentrations, ranging from 0.05 to 5.0 mg L−1 and encompassing estimated field doses of 3.1 to 310g ha−1, were applied to the soil of potted soybean plants at V3/V4 or R1 growth stages. Plant injury (0% to 100%), dry mass, height, number of pods, and number of pod-bearing nodes were measured. Kruskal-Wallis and logistic regression analyses were performed to determine treatment differences and examine dose effects. Yield losses were projected using (1) 14 d after treatment plant injury assessments based on injury–yield relationships described for foliar exposures and (2) pod counts. Dicamba concentration was the main significant factor affecting all growth response metrics, and growth stage was a significant explanatory variable only for the height response metric. A nonlinear response to dicamba dose was observed, with the threshold response dose required to affect 50% of plants being three times greater for 40% crop injury compared with 20% injury. Yield projections derived from plant response to root uptake compared with foliar exposure indicate that soybean may express both magnitude of injury and specific symptomology differently when exposure occurs via root uptake. Drift exposure–based models may be incompatible to predict soybean yield loss when injury results from irrigation. Data are needed to develop correlations for predicting yield losses based on field-scale exposure to dicamba in irrigation water, as well as assessment of real-world concentrations of herbicide residues in tailwater recovery systems.
Off-target movement of dicamba and 2,4-D may injure and reduce the yield of many fruit and vegetable crops, impacting specialty crop producers and herbicide applicators alike. Two field experiments were established, using plant growth regulator–resistant soybean herbicide technologies, to evaluate drift and carryover risks to horseradish production. The drift experiment was conducted in 2015 and 2016 to evaluate impact of dicamba and 2,4-D simulated drift on horseradish production with a mid-POST application in soybean. Simulated drift rates were 1/10,000X, 1/1,000X, and 1/100X, with 1/2X, 1X, and 2X of standard application rates. Injury and yield loss was greater following application of 2,4-D than with dicamba. Yield reductions were observed beginning at the 1/1,000X rate of 2,4-D, with complete crop loss occurring when rates exceed 1/2X. In comparison, dicamba only reduced yields when applied at the 1X and 2X rates. Only horseradish roots from plants treated with dicamba at the 2X rate had greater dicamba residue than the nontreated control, and the amount detected, 0.32 parts per billion (ppb), was lower than the EPA tolerance of 100 ppb in root crops. There was little to no harvestable tissue for 2,4-D residue analysis for plants treated with 2,4-D at rates above 1/2X. The carryover experiment was a 2-yr rotational evaluation conducted in 2014, 2015, and 2016 to assess dicamba carryover to horseradish following application to dicamba-resistant soybean the previous season. Observations taken at 4, 6, and 8 wk after planting indicated no significant horseradish injury, nor was height, stand, or root weight reduced. These results suggest that horseradish growers should have few concerns about injury from dicamba drift or carryover. While 2,4-D applicators may need to be cautious when making applications near horseradish fields, 2,4-D may be an effective tool for controlling volunteer horseradish in 2,4-D–resistant soybean.
We document that the credit spread on consumer unsecured debt exhibits a persistent, hump-shaped response to an increase in the charge-off rate. This stylized fact poses a significant challenge for a standard model of consumer default in which lenders have rational expectations and, therefore, the credit spread continuously adjusts to reflect the true default incentives of each borrower. In an effort to explain this feature of the data, we construct a model of consumer default with countercyclical income risk in which lenders learn about default risk over time by observing the history of repayment decisions, as is the case in practice. In addition to matching credit spread dynamics, allowing lenders to learn about default risk substantially improves the model’s ability to generate realistic business cycle fluctuations in the consumer unsecured credit market and match the cross-sectional distribution of unsecured debt and dispersion of interest rates observed in the data.
Multiple genes/variants have been implicated in various epileptic conditions. However, there is little general guidance available on the circumstances in which genetic testing is indicated and test selection in order to guide optimal test appropriateness and benefit. This is an account of the development of guidelines for genetic testing in epilepsy, which have been developed in Ontario, Canada. The Genetic Testing Advisory Committee was established in Ontario to review the clinical utility and validity of genetic tests and the provision of genetic testing in Ontario. As part of their mandate, the committee also developed recommendations and guidelines for genetic testing in epilepsy. The recommendations include mandatory prerequisites for an epileptology/geneticist/clinical biochemical geneticist consultation, prerequisite diagnostic procedures, circumstances in which genetic testing is indicated and not indicated and guidance for selection of genetic tests, including their general limitations and considerations. These guidelines represent a step toward the development of evidence-based gene panels for epilepsy in Ontario, the repatriation of genetic testing for epilepsy into Ontario molecular genetic laboratories and public funding of genetic tests for epilepsy in Ontario.
Subglacial hydrology plays a key role in many glaciological processes, including ice dynamics via the modulation of basal sliding. Owing to the lack of an overarching theory, however, a variety of model approximations exist to represent the subglacial drainage system. The Subglacial Hydrology Model Intercomparison Project (SHMIP) provides a set of synthetic experiments to compare existing and future models. We present the results from 13 participating models with a focus on effective pressure and discharge. For many applications (e.g. steady states and annual variations, low input scenarios) a simple model, such as an inefficient-system-only model, a flowline or lumped model, or a porous-layer model provides results comparable to those of more complex models. However, when studying short term (e.g. diurnal) variations of the water pressure, the use of a two-dimensional model incorporating physical representations of both efficient and inefficient drainage systems yields results that are significantly different from those of simpler models and should be preferentially applied. The results also emphasise the role of water storage in the response of water pressure to transient recharge. Finally, we find that the localisation of moulins has a limited impact except in regions of sparse moulin density.
Repeated measurements of the same countries, people, or groups over time are vital to many fields of political science. These measurements, sometimes called time-series cross-sectional (TSCS) data, allow researchers to estimate a broad set of causal quantities, including contemporaneous effects and direct effects of lagged treatments. Unfortunately, popular methods for TSCS data can only produce valid inferences for lagged effects under some strong assumptions. In this paper, we use potential outcomes to define causal quantities of interest in these settings and clarify how standard models like the autoregressive distributed lag model can produce biased estimates of these quantities due to post-treatment conditioning. We then describe two estimation strategies that avoid these post-treatment biases—inverse probability weighting and structural nested mean models—and show via simulations that they can outperform standard approaches in small sample settings. We illustrate these methods in a study of how welfare spending affects terrorism.
Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84–88) presented a critique of our recently published paper in Cell Reports entitled ‘Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets’ (Lam et al., Cell Reports, Vol. 21, 2017, 2597–2613). Specifically, Hill offered several interrelated comments suggesting potential problems with our use of a new analytic method called Multi-Trait Analysis of GWAS (MTAG) (Turley et al., Nature Genetics, Vol. 50, 2018, 229–237). In this brief article, we respond to each of these concerns. Using empirical data, we conclude that our MTAG results do not suffer from ‘inflation in the FDR [false discovery rate]’, as suggested by Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84–88), and are not ‘more relevant to the genetic contributions to education than they are to the genetic contributions to intelligence’.
Here, we examine the influence of small-scale turbulence on the evolution of fronts in the ocean and atmosphere. Specifically, we consider the evolution of an initially balanced density front subject to an imposed viscosity and diffusivity as a simple analogue for small-scale turbulence. At late times, the dominant balance is found to be the quasisteady turbulent thermal wind balance with time evolution due to an advection–diffusion balance in the buoyancy equation. We use the leading-order balance to determine analytical similarity solutions for the spreading of a front and find that the spreading rate is maximum for an intermediate value of the Ekman number, with the spreading resulting from shear dispersion associated with the cross-front flow and vertical diffusion of density. In response to shear dispersion, the front evolves towards a density profile that is nearly linear in the cross-front coordinate. At the edges of the frontal zone, the density field develops large curvature, and these regions are associated with narrow bands of intense vertical velocity.
Background: Post-stroke depression (PSD) is the most frequent psychiatric complication following ischemic stroke. It affects up to 60% of all patients and is associated with increased morbidity and mortality following ischemic stroke. The pathophysiology of PSD remains elusive and appears to be multifactorial, rather than “purely” biological or psychosocial in origin. Thus, valid animal models of PSD would contribute to the study of the etiology (and treatment) of this disorder. Methods: The present study depicts a rat model for PSD, using middle cerebral artery occlusion (MCAO). The two-way shuttle avoidance task, Porsolt forced-swim test, and sucrose preference test were employed to assess any depression-like behavior. Localized brain expressions of brain-derived neurotrophic factor (BDNF) protein levels were evaluated to examine the possible involvement of the brain neuronal plasticity in the observed behavioral syndrome. The raw data were subjected to unsupervised fuzzy clustering (UFC) algorithms to assess the sensitivity of bio-behavioral measures indicative of depressive symptoms post MCAO. Results: About 56% of the rats developed significant depressive-like behavioral disruptions as a result of MCAO compared with 4% in the sham-operated control rats. A pattern of a depressive-like behavioral response was common to all affected MCAO animals, characterized by significantly more escape failures and reduced number of total avoidance shuttles, a significant elevation in immobility duration, and reduced sucrose preference. Significant downregulations of BDNF protein levels in the hippocampal sub-regions, frontal cortex, and hypothalamus were observed in all affected MCAO animals. Conclusion: The UFC analysis supports the behavioral analysis and thus, lends validity to our results.