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Perennial ornamental grasses are often recommended for rain gardens, but few data support their use. We conducted two experiments to evaluate the ability of ornamental grass cultivars to grow while subjected to cyclical flooding, submergence, and drought typical of rain gardens. Our objectives were to determine the effects of cyclical flood and drought (Expt. 1) and submergence depth and duration (Expt. 2) on grass growth and survival. Seven cultivars were evaluated during greenhouse trials, including Pixie Fountain tufted hairgrass [Deschampsia cespitosa (L.) P. Beauv.], Northwind switchgrass (Panicum virgatum L.), Red October big bluestem (Andropogon gerardii Vitman), Purpurascens Chinese silvergrass (Miscanthus sinensis Andersson), Blue Heaven® little bluestem [Schizachyrium scoparium (Michx.) Nash], Blonde Ambition blue grama grass [Bouteloua gracilis (Kunth) Lag. ex Griffiths], and Karl Foerster feather reed grass [Calamagrostis ×acutiflora (Schrad.) DC]. During Expt. 1, grasses underwent four cycles of flooding duration (2 days or 7 days) followed by drought (drying to volumetric soil water contents of 0.14 or 0.07 cm3·cm−3). During Expt. 2, grasses were cyclically submerged at 15 or 30 cm above the soil surface for 2, 4, or 7 days, followed by floodwater removal and drainage for 2 days before being resubmerged. Cyclical submergence continued until the 7-day submergence treatments completed four cycles. Both experiments were replicated in a full factorial randomized complete block design. Controls were included in both experiments. Plants were measured to determine plant height, shoot count, visual damage rating, shoot dry weight, and root dry weight. Floodwater chemistry and soil reducing conditions were measured during Expt. 2. Chinese silvergrass and switchgrass survived cyclical soil flooding/drought and submergence for 7 days at a depth of 30 cm while maintaining acceptable foliar damage. All grasses survived cyclical flood and drought when the soil volumetric water content was maintained at 14%, suggesting they can withstand periodic soil flooding as long as the water is not too deep. As water depth and duration increased from 4 days to 7 days, little bluestem, blue grama grass, and feather reed grass experienced significant foliar damage. Tufted hair grass and big bluestem experienced significant foliar damage when submerged for 2 days. Our results showed that perennial ornamental grasses can tolerate cyclical flood and drought and periodic submergence, but that plant conditions and survival vary, which can inform strategic plant placement within rain gardens, bioretention basins, and other stormwater management systems.

Introduction The English National Health Service (NHS) Diabetic Eye Screening Programme (DESP) performs around 2.3 million eye screening appointments annually, generating approximately 13 million retinal images that are graded by humans for the presence or severity of diabetic retinopathy. Previous research has shown that automated retinal image analysis systems, including artificial intelligence (AI), can identify images with no disease from those with diabetic retinopathy as safely and effectively as human graders, and could significantly reduce the workload for human graders. Some algorithms can also determine the level of severity of the retinopathy with similar performance to humans. There is a need to examine perceptions and concerns surrounding AI-assisted eye-screening among people living with diabetes and NHS staff, if AI was to be introduced into the DESP, to identify factors that may influence acceptance of this technology.Methods and analysis People living with diabetes and staff from the North East London (NEL) NHS DESP were invited to participate in two respective focus groups to codesign two online surveys exploring their perceptions and concerns around the potential introduction of AI-assisted screening.Focus group participants were representative of the local population in terms of ages and ethnicity. Participants’ feedback was taken into consideration to update surveys which were circulated for further feedback. Surveys will be piloted at the NEL DESP and followed by semistructured interviews to assess accessibility, usability and to validate the surveys.Validated surveys will be distributed by other NHS DESP sites, and also via patient groups on social media, relevant charities and the British Association of Retinal Screeners. Post-survey evaluative interviews will be undertaken among those who consent to participate in further research.Ethics and dissemination Ethical approval has been obtained by the NHS Research Ethics Committee (IRAS ID: 316631). Survey results will be shared and discussed with focus groups to facilitate preparation of findings for publication and to inform codesign of outreach activities to address concerns and perceptions identified.

Abstract COVID-19 mortality risk stratification tools could improve care, inform accurate and rapid triage decisions, and guide family discussions regarding goals of care. A minority of COVID-19 prognostic tools have been tested in external cohorts. Our objective was to compare machine learning algorithms and develop a tool for predicting subsequent clinical outcomes in COVID-19. We conducted a retrospective cohort study that included hospitalized patients with COVID-19 from March 2020 to March 2021. Seven Hundred Twelve consecutive patients from University of Washington and 345 patients from Tongji Hospital in China were included. We applied three different machine learning algorithms to clinical and laboratory data collected within the initial 24 h of hospital admission to determine the risk of in-hospital mortality, transfer to the intensive care unit, shock requiring vasopressors, and receipt of renal replacement therapy. Mortality risk models were derived, internally validated in UW and externally validated in Tongji Hospital. The risk models for ICU transfer, shock and RRT were derived and internally validated in the UW dataset but were unable to be externally validated due to a lack of data on these outcomes. Among the UW dataset, 122 patients died (17%) during hospitalization and the mean days to hospital mortality was 15.7 +/− 21.5 (mean +/− SD). Elastic net logistic regression resulted in a C-statistic for in-hospital mortality of 0.72 (95% CI, 0.64 to 0.81) in the internal validation and 0.85 (95% CI, 0.81 to 0.89) in the external validation set. Age, platelet count, and white blood cell count were the most important predictors of mortality. In the sub-group of patients > 50 years of age, the mortality prediction model continued to perform with a C-statistic of 0.82 (95% CI:0.76,0.87). Prediction models also performed well for shock and RRT in the UW dataset but functioned with lower accuracy for ICU transfer. We trained, internally and externally validated a prediction model using data collected within 24 h of hospital admission to predict in-hospital mortality on average two weeks prior to death. We also developed models to predict RRT and shock with high accuracy. These models could be used to improve triage decisions, resource allocation, and support clinical trial enrichment.

The delivery of nanomedicines into cells holds enormous therapeutic potential; however little is known regarding how the extracellular matrix (ECM) can influence cell–nanoparticle (NP) interactions. Changes in ECM organization and composition occur in several pathophysiological states, including fibrosis and tumorigenesis, and may contribute to disease progression. We show that the physical characteristics of cellular substrates, that more closely resemble the ECM in vivo, can influence cell behavior and the subsequent uptake of NPs. Electrospinning was used to create two different substrates made of soft polyurethane (PU) with aligned and non-aligned nanofibers to recapitulate the ECM in two different states. To investigate the impact of cell–substrate interaction, A549 lung epithelial cells and MRC-5 lung fibroblasts were cultured on soft PU membranes with different alignments and compared against stiff tissue culture plastic (TCP)/glass. Both cell types could attach and grow on both PU membranes with no signs of cytotoxicity but with increased cytokine release compared with cells on the TCP. The uptake of silica NPs increased more than three-fold in fibroblasts but not in epithelial cells cultured on both membranes. This study demonstrates that cell–matrix interaction is substrate and cell-type dependent and highlights the importance of considering the ECM and tissue mechanical properties when designing NPs for effective cell targeting and treatment.

Abstract Age-related macular degeneration (AMD) and Stargardt disease are the leading causes of blindness for the elderly and young adults respectively. Geographic atrophy (GA) of AMD and Stargardt atrophy are their end-stage outcomes. Efficient methods for segmentation and quantification of these atrophic lesions are critical for clinical research. In this study, we developed a deep convolutional neural network (CNN) with a trainable self-attended mechanism for accurate GA and Stargardt atrophy segmentation. Compared with traditional post-hoc attention mechanisms which can only visualize CNN features, our self-attended mechanism is embedded in a fully convolutional network and directly involved in training the CNN to actively attend key features for enhanced algorithm performance. We applied the self-attended CNN on the segmentation of AMD and Stargardt atrophic lesions on fundus autofluorescence (FAF) images. Compared with a preexisting regular fully convolutional network (the U-Net), our self-attended CNN achieved 10.6% higher Dice coefficient and 17% higher IoU (intersection over union) for AMD GA segmentation, and a 22% higher Dice coefficient and a 32% higher IoU for Stargardt atrophy segmentation. With longitudinal image data having over a longer time, the developed self-attended mechanism can also be applied on the visual discovery of early AMD and Stargardt features.

Abstract Background Long-term treatment adherence is a worldwide concern, with nonadherence resulting from a complex interplay of behaviors and health beliefs. Determining an individual’s risk of nonadherence and identifying the drivers of that risk are crucial for the development of successful interventions for improving adherence. Here, we describe the development of a new tool assessing a comprehensive set of characteristics predictive of patients’ treatment adherence based on the Social, Psychological, Usage and Rational (SPUR) adherence framework. Concepts from existing self-reporting tools of adherence-related behaviors were identified following a targeted MEDLINE literature review and a subset of these concepts were then selected for inclusion in the new tool. SPUR tool items, simultaneously generated in US English and in French, were tested iteratively through two rounds of cognitive interviews with US and French patients taking long-term treatments for chronic diseases. The pilot SPUR tool, resulting from the qualitative analysis of patients’ responses, was then adapted to other cultural settings (China and the UK) and subjected to further rounds of cognitive testing. Results The literature review identified 27 relevant instruments, from which 49 concepts were included in the SPUR tool (Social: 6, Psychological: 13, Usage: 11, Rational: 19). Feedback from US and French patients suffering from diabetes, multiple sclerosis, or breast cancer (n = 14 for the first round; n = 16 for the second round) indicated that the SPUR tool was well accepted and consistently understood. Minor modifications were implemented, resulting in the retention of 45 items (Social: 5, Psychological: 14, Usage: 10, Rational: 16). Results from the cognitive interviews conducted in China (15 patients per round suffering from diabetes, breast cancer or chronic obstructive pulmonary disease) and the UK (15 patients suffering from diabetes) confirmed the validity of the tool content, with no notable differences being identified across countries or chronic conditions. Conclusion Our qualitative analyses indicated that the pilot SPUR tool is a promising model that may help clinicians and health systems to predict patient treatment behavior. Further steps using quantitative methods are needed to confirm its predictive validity and other psychometric properties.

BackgroundSelf-reported questions on blindness and vision problems are collected in many national surveys. Recently released surveillance estimates on the prevalence of vision loss used self-reported data to predict variation in the prevalence of objectively measured acuity loss among population groups for whom examination data are not available. However, the validity of self-reported measures to predict prevalence and disparities in visual acuity has not been established. ObjectiveThis study aimed to estimate the diagnostic accuracy of self-reported vision loss measures compared to best-corrected visual acuity (BCVA), inform the design and selection of questions for future data collection, and identify the concordance between self-reported vision and measured acuity at the population level to support ongoing surveillance efforts. MethodsWe calculated accuracy and correlation between self-reported visual function versus BCVA at the individual and population level among patients from the University of Washington ophthalmology or optometry clinics with a prior eye examination, randomly oversampled for visual acuity loss or diagnosed eye diseases. Self-reported visual function was collected via telephone survey. BCVA was determined based on retrospective chart review. Diagnostic accuracy of questions at the person level was measured based on the area under the receiver operator curve (AUC), whereas population-level accuracy was determined based on correlation. ResultsThe survey question, “Are you blind or do you have serious difficulty seeing, even when wearing glasses?” had the highest accuracy for identifying patients with blindness (BCVA ≤20/200; AUC=0.797). The highest accuracy for detecting any vision loss (BCVA

Abstract The rapid evolution of the novel coronavirus disease (COVID-19) pandemic has resulted in an urgent need for effective clinical tools to reduce transmission and manage severe illness. Numerous teams are quickly developing artificial intelligence approaches to these problems, including using deep learning to predict COVID-19 diagnosis and prognosis from chest computed tomography (CT) imaging data. In this work, we assess the value of aggregated chest CT data for COVID-19 prognosis compared to clinical metadata alone. We develop a novel patient-level algorithm to aggregate the chest CT volume into a 2D representation that can be easily integrated with clinical metadata to distinguish COVID-19 pneumonia from chest CT volumes from healthy participants and participants with other viral pneumonia. Furthermore, we present a multitask model for joint segmentation of different classes of pulmonary lesions present in COVID-19 infected lungs that can outperform individual segmentation models for each task. We directly compare this multitask segmentation approach to combining feature-agnostic volumetric CT classification feature maps with clinical metadata for predicting mortality. We show that the combination of features derived from the chest CT volumes improve the AUC performance to 0.80 from the 0.52 obtained by using patients’ clinical data alone. These approaches enable the automated extraction of clinically relevant features from chest CT volumes for risk stratification of COVID-19 patients.

This study aimed to evaluate the impact of Nystatin oral rinse on salivary and supragingival microbiota in adults with oral candidiasis and identify predictive factors related to individuals’ responses to Nystatin. The trial involved twenty participants who used 600,000 International Units/application of Nystatin oral rinse for seven days, four times a day, and were followed up at one week and three months after the rinse. The salivary and plaque microbiome of the participants were assessed via 16S rDNA amplicon sequencing. Overall, salivary and plaque microbiomes remained stable. However, among the participants (53 percent) who responded to Nystatin rinse (defined as free of oral Candida albicans post treatment), Veillonella emerged as a core genus alongside Streptococcus and Actinomyces in supragingival plaque at the 3-month follow-up. Furthermore, statistical models were fit to identify predictive factors of Nystatin rinse success (elimination of C. albicans) or failure (remaining C. albicans). The results revealed that an increased level of salivary Interferon (IFN)-γ-inducible protein (IP-10), also known as C-X-C motif chemokine ligand 10 (CXCL10), was an indicator of a failure of responding to Nystatin rinse. Future clinical trials are warranted to comprehensively assess the impact of antifungal treatment on the oral flora.

Abstract The COVID-19 epidemic of 2019–20 is due to the novel coronavirus SARS-CoV-2. Following first case description in December, 2019 this virus has infected over 10 million individuals and resulted in at least 500,000 deaths world-wide. The virus is undergoing rapid mutation, with two major clades of sequence variants emerging. This study sought to determine whether SARS-CoV-2 sequence variants are associated with differing outcomes among COVID-19 patients in a single medical system. Whole genome SARS-CoV-2 RNA sequence was obtained from isolates collected from patients registered in the University of Washington Medicine health system between March 1 and April 15, 2020. Demographic and baseline clinical characteristics of patients and their outcome data including their hospitalization and death were collected. Statistical and machine learning models were applied to determine if viral genetic variants were associated with specific outcomes of hospitalization or death. Full length SARS-CoV-2 sequence was obtained 190 subjects with clinical outcome data. 35 (18.4%) were hospitalized and 14 (7.4%) died from complications of infection. A total of 289 single nucleotide variants were identified. Clustering methods demonstrated two major viral clades, which could be readily distinguished by 12 polymorphisms in 5 genes. A trend toward higher rates of hospitalization of patients with Clade 2 infections was observed (p = 0.06, Fisher’s exact). Machine learning models utilizing patient demographics and co-morbidities achieved area-under-the-curve (AUC) values of 0.93 for predicting hospitalization. Addition of viral clade or sequence information did not significantly improve models for outcome prediction. In summary, SARS-CoV-2 shows substantial sequence diversity in a community-based sample. Two dominant clades of virus are in circulation. Among patients sufficiently ill to warrant testing for virus, no significant difference in outcomes of hospitalization or death could be discerned between clades in this sample. Major risk factors for hospitalization and death for either major clade of virus include patient age and comorbid conditions.

Background: We aimed to evaluate the long-term complication profile associated with port-a-catheter placement. Methods: Patients undergoing port-a-catheter placement from 2007 to 2012 with 5-year follow up were identified. Descriptive statistics, χ2 tests, and multivariate regression models were analyzed. Results: Any complication occurring within 5 years postoperatively was common (59.04%, n = 53,353). Arrhythmogenic (32.66%, n = 30,625) and thrombovascular (36.80%, n = 34,499) complications were more common than infection (17.86%, n = 16,745) and mechanical (10.31%, n = 9,670) complications. Multivariate analysis demonstrated that history of atrial fibrillation is a risk factor for developing any complication (odds ratio 7.99, 95% confidence interval 7.29–8.77). Conclusion: Patients with history of atrial fibrillation have increased odds of developing infectious, thrombovascular, mechanical, and arrhythmogenic complications with port-a-catheter placement. This study is the first to show that postprocedure arrhythmias occur at significant rates within the 5-year follow-up period. We caution that development of new arrhythmia should be monitored throughout a prolonged follow-up period. We hope our analysis encourages multidisciplinary coordination of patients with ports so that implants are promptly removed when they are no longer needed to avoid these complications.

Obstruction of the inferior vena cava (IVC) following surgical repair of an atrial septal defect (ASD) is a rare complication. We present the case of a patient who developed IVC obstruction following surgical repair of a large secundum ASD. The diagnostic and management approaches used to care for this patient are discussed. (Level of Difficulty: Intermediate.)

Abstract North Dakota producers have adopted conservation tillage practices to conserve soil moisture and reduce wind and water erosion. As a result, an accumulation of crop residue has been observed but current recommendations encourage a fertilizer N credit in fields under no‐till for more than 6 yr. Producers are concerned that post‐harvest crop residues are not contributing to N needs of subsequent crops during the growing season. This study was established to assess N mineralization from common crop residue in conventional tillage systems using long‐term incubation studies in order to establish a baseline for future studies on no‐till systems. Three commonly cultivated North Dakota soil series were selected for study with seven residue treatments (varying C/N ratios) including corn (Zea mays L.), soybean [Glycine max (L.) Merr.], flax (Linum usitatissimum L.), forage radish (Raphanus sativus L.), winter pea (Pisum sativum L.), spring and winter wheat (Triticum aestivum L.), and a soil‐only control. Biweekly leachings were collected for nine incubation periods and analyzed for nitrate‐nitrogen (NO3–N). Soils with higher organic matter (OM) resulted in increased soil N mineralization (Fargo [1.63 mg kg–1 N] > Forman [0.65 mg kg–1 N] > Heimdal–Emrick [0.38 mg kg–1 N]). Radish and pea residues (narrow C/N ratios) were the only treatments showing N mineralization potential compared with the soil only controls. However, post‐harvest residues with wide C/N ratios (>25:1) promote N immobilization when compared with mineralization by the soil alone. These findings raise the question of whether the N credits for >6 yr of no‐till management are appropriate in the northern Great Plains.

Commercial static cell culture substrates can usually not change their physical properties over time, resulting in a limited representation of the variation in biomechanical cues in vivo. To overcome this limitation, approaches incorporating gold nanoparticles to act as transducers to external stimuli have been employed. In this work, gold nanorods were embedded in an elastomeric matrix and used as photothermal transducers to fabricate biocompatible light-responsive substrates. The nanocomposite films analysed by lock-in thermography and nanoindentation show a homogeneous heat distribution and a greater stiffness when irradiated with NIR light. After irradiation, the initial stiffness values were recovered. In vitro experiments performed during NIR irradiation with NIH-3T3 fibroblasts demonstrated that these films were biocompatible and cells remained viable. Cells cultured on the light stiffened nanocomposite exhibited a greater proliferation rate and stronger focal adhesion clustering, indicating increased cell-surface binding strength.

Oral mucositis (OM) is a treatment-limiting adverse side effect of radiation and chemotherapy. Approximately 80% of patients undergoing radiotherapy (RT) for head and neck cancers (HNC) develop OM, representing a major unmet medical condition. Our understanding of the immunopathogenesis of OM is limited, due in part to the surprising paucity of information regarding healing mechanisms in the oral mucosa. RNAseq of oral tissue in a murine model that closely mimics human OM, showed elevated expression of IL-17 and related immune pathways in response to head and neck irradiation (HNI). Strikingly, mice lacking the IL-17 receptor (IL-17RA) exhibited markedly more severe OM. Restoration of the oral mucosa was compromised in Il17ra−/− mice and components associated with healing, including matrix metalloproteinase 3, 10 and IL-24 were diminished. IL-17 is typically associated with recruitment of neutrophils to mucosal sites following oral infections. Unexpectedly, in OM the absence of IL-17RA resulted in excessive neutrophil recruitment and immunopathology. Instead, neutrophil activation was IL-1R-driven in Il17ra−/− mice. Blockade of IL-1R and depletion of neutrophils lessened the severity of damage in these mice. Overall, we show IL-17 is protective in OM through multiple mechanisms including restoration of the damaged epithelia and control of the neutrophil response. We also present a clinically relevant murine model of human OM to improve mechanistic understanding and develop rational translational therapeutics.

Background:. We aimed to longitudinally study the relative research contributions of US and international plastic surgeons by evaluating publications within the premier plastic surgery journal over the last 2 decades. We hypothesized that even with an increased pressure to publish in this journal, the relative research contributions from American plastic surgeons will continue to be the largest overall and in all subspecialties. Methods:. Data for the surgical subspecialty, corresponding author’s country of origin, and region were extracted from all original articles in 2 randomly selected monthly issues of Plastic & Reconstructive Surgery (PRS) from the last 2 decades to evaluate longitudinal trends. Data were also extracted from all of the original articles published in PRS for the last 3 years to analyze the recent distribution of research output. Results:. During the last 2 decades, the relative proportion of total original articles written by US authors has increased. They have published proportionally more articles in the Reconstructive and Breast field while publishing relatively less in the hand/peripheral nerve field. From the first decade of analysis, US authors wrote relatively fewer articles in the hand/peripheral nerve field, whereas in the second decade, the US authors wrote relatively fewer articles in the Experimental field. In the last 3 years, US authors published relatively fewer articles in the Experimental and Cosmetic fields. Conclusions:. Each country’s scientific productivity in PRS is related to funding, interest, patients’ demand, and healthcare market pressure. In this study, we see that these factors influence trends within research publications over the last 2 decades.

Background: Although arterial stiffness has demonstrated moderate heritability, our knowledge of the genes modulating arterial stiffness is still limited. We conducted genome-wide association studies (GWASs) of aortic distensibility (AoD) in both ascending (AA) and proximal descending aorta (PDA) to discover novel genetic loci. Methods: Our study included ~14,500 European-ancestry participants in the UK Biobank study. AoD in AA and PDA were assessed at the level of pulmonary artery bifurcation using transverse cine images obtained from 1.5 Tesla cardiovascular magnetic resonance scanners1. Relative cross-sectional aortic area change was calculated using an automated tool2. GWASs were performed in a discovery cohort (n = 3,841), with replication in 9,630 individuals. We also performed GWASs for each trait in the combined cohort (n = 14,596). All GWASs were performed under a linear mixed model and adjusted for age, sex, height, weight, systolic blood pressure, diabetes, smoking, genotype array type and the first ten principal components. Results: We found three significant loci (p < 5 × 10–8) for AA AoD and six for PDA AoD (Figure 1A). The ELN locus was discovered and replicated for AA AoD, and was significantly associated with PDA AoD in the combined cohort (Figure 1B). ELN encodes elastin a central component of elastic fibres in the heart and blood vessels. The most significant locus for PDA AoD was FBLN5; FBLN5 encodes fibulin 5 which is vital for elastic fibre formation. Conclusions: In the first GWAS of AoD, we discovered seven unique loci. These results enhance our understanding of the biological processes underlying arterial stiffness. Figure 1AVenn diagram of the 7 genome-wide significant loci from our study Figure 1BMiami plot of distensibility in the ascending (AA) and proximal descending aorta (PDA) in the combined cohort. Quartered cross symbol denotes locus was also genome-wide significant in discovery and replication cohorts.

Abstract Economic projections after widespread deep compaction during wet harvests are essentially nonexistent. Therefore, we project state‐level economic costs to producers in North Dakota and Minnesota for the upcoming 2020 and 2021 crops. We provide economic cost graphs as functions of grain sell prices and fractions of land impacted by deep wheel‐traffic compaction. At corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] sell prices of US$3.06 bu−1 and $8.78 bu−1 for North Dakota and $3.26 bu−1 and $8.98 bu−1 for Minnesota, we estimate a minimum economic cost of US$587 million through 2021, excluding environmental externalities and other feedbacks, for every 10% of lands compacted during the 2019 harvest. Actual impacted land area may range up to 30%, resulting in a range of US$0 to $1.76 billion of actual costs. Precise large‐scale, deep‐compaction reports/sensing is needed to determine actual fractions of impacted land. Policies incentivizing conservation practices to reduce the occurrence of field traffic on wet soils are strongly encouraged.

In the US upper Midwest, the narrow growing season causes many farmers to presume yield losses when reducing tillage. The purpose of this study was to determine how four production-scale tillage systems affected residue cover, stand populations, crop yields, and soil chemical, biological, and physical properties. Tillage systems (chisel plow, fall strip-till with shanks, spring strip-till with coulters, and shallow vertical till) were continued for 4 yr. Tillage effects within a site were few and mixed (0.17–0.36 Mg ha difference), whereas site effects were common (0.50–3.00 Mg ha difference). Among 19 soil properties, only fungal/bacteria ratios differed among strip-till with shanks (0.078) and strip-till with coulters (0.066) at one site. Our results suggest that many farmers’ concerns about using conservation tillage practices do not necessarily translate into yield losses when compared to standard chisel plow practices. Economics and the level of erosion control among the tillage practices compared here, rather than yield alone, should guide farmer preferences.

Background: Diabetic retinopathy screening in England involves labour-intensive manual grading of retinal images. Automated retinal image analysis systems (ARIASs) may offer an alternative to manual grading. Objectives: To determine the screening performance and cost-effectiveness of ARIASs to replace level 1 human graders or pre-screen with ARIASs in the NHS diabetic eye screening programme (DESP). To examine technical issues associated with implementation. Design: Observational retrospective measurement comparison study with a real-time evaluation of technical issues and a decision-analytic model to evaluate cost-effectiveness. Setting: A NHS DESP. Participants: Consecutive diabetic patients who attended a routine annual NHS DESP visit. Interventions: Retinal images were manually graded and processed by three ARIASs: iGradingM (version 1.1; originally Medalytix Group Ltd, Manchester, UK, but purchased by Digital Healthcare, Cambridge, UK, at the initiation of the study, purchased in turn by EMIS Health, Leeds, UK, after conclusion of the study), Retmarker (version 0.8.2, Retmarker Ltd, Coimbra, Portugal) and EyeArt (Eyenuk Inc., Woodland Hills, CA, USA). The final manual grade was used as the reference standard. Arbitration on a subset of discrepancies between manual grading and the use of an ARIAS by a reading centre masked to all grading was used to create a reference standard manual grade modified by arbitration. Main outcome measures: Screening performance (sensitivity, specificity, false-positive rate and likelihood ratios) and diagnostic accuracy [95% confidence intervals (CIs)] of ARIASs. A secondary analysis explored the influence of camera type and patients’ ethnicity, age and sex on screening performance. Economic analysis estimated the cost per appropriate screening outcome identified. Results: A total of 20,258 patients with 102,856 images were entered into the study. The sensitivity point estimates of the ARIASs were as follows: EyeArt 94.7% (95% CI 94.2% to 95.2%) for any retinopathy, 93.8% (95% CI 92.9% to 94.6%) for referable retinopathy and 99.6% (95% CI 97.0% to 99.9%) for proliferative retinopathy; and Retmarker 73.0% (95% CI 72.0% to 74.0%) for any retinopathy, 85.0% (95% CI 83.6% to 86.2%) for referable retinopathy and 97.9% (95% CI 94.9 to 99.1%) for proliferative retinopathy. iGradingM classified all images as either ‘disease’ or ‘ungradable’, limiting further iGradingM analysis. The sensitivity and false-positive rates for EyeArt were not affected by ethnicity, sex or camera type but sensitivity declined marginally with increasing patient age. The screening performance of Retmarker appeared to vary with patient’s age, ethnicity and camera type. Both EyeArt and Retmarker were cost saving relative to manual grading either as a replacement for level 1 human grading or used prior to level 1 human grading, although the latter was less cost-effective. A threshold analysis testing the highest ARIAS cost per patient before which ARIASs became more expensive per appropriate outcome than human grading, when used to replace level 1 grader, was Retmarker £3.82 and EyeArt £2.71 per patient. Limitations: The non-randomised study design limited the health economic analysis but the same retinal images were processed by all ARIASs in this measurement comparison study. Conclusions: Retmarker and EyeArt achieved acceptable sensitivity for referable retinopathy and false-positive rates (compared with human graders as reference standard) and appear to be cost-effective alternatives to a purely manual grading approach. Future work is required to develop technical specifications to optimise deployment and address potential governance issues. Funding: The National Institute for Health Research (NIHR) Health Technology Assessment programme, a Fight for Sight Grant (Hirsch grant award) and the Department of Health’s NIHR Biomedical Research Centre for Ophthalmology at Moorfields Eye Hospital and the University College London Institute of Ophthalmology.

Purpose. Health status and social networks are associated with resilience among older adults. Each of these factors may be important to the ability of adults to remain in rural and remote communities as they age. We examined the association of health status and social networks and resilience among older adults dwelling in a rural and remote county in the Western United States. Methods. We selected a random sample of 198 registered voters aged 65 years or older from a frontier Wyoming county. Hierarchical linear regression was used to examine the association of health status as well as social networks and resilience. We also examined health status as a moderator of the relationship between social networks and resilience. Results. Family networks (p=0.024) and mental health status (p

Abstract Introduction Having a solid foundation in human anatomy is essential for all medical students. It is a widely-accepted dogma that achieving competency in any field requires hours of practice. When studying human anatomy, this practice is acquired by studying the structures of interest in an anatomy atlas and in a human cadaver. Methods The Human Anatomy Module (HAM) was designed to provide students with a supplemental resource for learning the anatomy of the extremities. The HAM has three sections that are designated Atlas, Learn, and Identify. The Atlas section contains photos from prosected cadavers, and it allows for the learner to toggle labels for the structures on and off. The Learn section contains tables, outlines, interactive learning activities, and multiple choice quizzes, all of which were created to help students establish a strong conceptual understanding of anatomy of the extremities. The Identify section allows students to practice identifying structures displayed in photos from prosected cadavers. The learner receives instant feedback upon submitting an answer so that knowledge gaps can immediately be corrected. Results The Human Anatomy Module (HAM) has been used by first-year medical and dental students at our institution for the past two school years (classes of 2016 and 2017). We have received positive feedback from students who have chosen to use it as a resource to study anatomy of the extremities. The module was hosted on our university web server, and usage statistics show that 95% of students accessed the module. A voluntary survey administered to both classes showed that 95% of students found the module to be useful and 87% felt that it helped them to prepare for the anatomy practical exam. Students felt that the most important sections of the module were the Identify section (96%), Atlas section (90%), and quizzes (77%). Discussion E-learning is becoming increasingly prevalent in medical education, and the HAM delivers content in an online format that is very comfortable for students to navigate. This module is not meant to replace the traditional resources that are used for learning anatomy such as atlases, cadavers, and direct instruction from faculty, but rather as a supplemental resource.