Outcomes of Shoulder Arthroplasty Performed for Postinfectious Arthritis.

Background: The purpose of this study was to evaluate the functional outcomes, infection rate, and complications associated with shoulder arthroplasty for sequelae of prior septic arthritis. Methods: This is a retrospective cohort study of 17 patients who underwent shoulder arthroplasty for sequelae of septic arthritis. Patients were analyzed for patient-reported outcomes, complications, and reoperations. Results: The 17 patients in this cohort were an average age of 65.4 ± 12.2 years old, were 58.8% male, and had an average body mass index of 27.9 ± 4.1 kg/m Conclusions: Shoulder arthroplasty after septic arthritis had inconsistent functional outcomes and high complication rates but no reinfection

Long-term success for people living with HIV: A framework to guide practice

Objectives: In recent decades, the needs of people living with HIV have evolved as life expectancy has greatly improved. Now, a new definition of long-term success (LTS) is necessary to help address the multifaceted needs of all people living with HIV. Methods: We conducted a two-phase research programme to delineate the range of experiences of people living with HIV. The insights garnered from these research phases were explored in a series of expert-led workshops, which led to the development and refinement of the LTS framework. Results: The insights generated from the research phases identified a series of themes that form a part of LTS. These themes were subsequently incorporated into the LTS framework, which includes five outcome pillars: sustained undetectable viral load, minimal impact of treatment and clinical monitoring, optimized health-related quality of life, lifelong integration of healthcare, and freedom from stigma and discrimination. A series of supporting statements were also developed by the expert panel to help in the achievement of each of the LTS pillars. Conclusions: The LTS framework offers a comprehensive and person-centric approach that, if achieved, could help improve the long-term well-being of people living with HIV and support the LTS vision of 'every person living with HIV being able to live their best life'

Why we need to re-define long-term success for people living with HIV

: Over the past few decades, the life expectancy of people living with HIV has markedly improved due to the advances in HIV diagnosis, linkage to care, and treatment. However, with these advances, a new set of challenges has emerged that must be addressed to ensure the long-term well-being of people living with HIV. In this article, as part of a wider journal supplement, we explore the unmet needs and challenges across the HIV continuum of care and re-define what long-term success looks like to support the healthy ageing of all people affected by HIV

Labeling poststorm coastal imagery for machine learning: measurement of interrater agreement

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Goldstein, E. B., Buscombe, D., Lazarus, E. D., Mohanty, S. D., Rafique, S. N., Anarde, K. A., Ashton, A. D., Beuzen, T., Castagno, K. A., Cohn, N., Conlin, M. P., Ellenson, A., Gillen, M., Hovenga, P. A., Over, J.-S. R., Palermo, R., Ratliff, K. M., Reeves, I. R. B., Sanborn, L. H., Straub, J. A., Taylor, L. A., Wallace E. J., Warrick, J., Wernette, P., Williams, H. E. Labeling poststorm coastal imagery for machine learning: measurement of interrater agreement. Earth and Space Science, 8(9), (2021): e2021EA001896, https://doi.org/10.1029/2021EA001896.Classifying images using supervised machine learning (ML) relies on labeled training data—classes or text descriptions, for example, associated with each image. Data-driven models are only as good as the data used for training, and this points to the importance of high-quality labeled data for developing a ML model that has predictive skill. Labeling data is typically a time-consuming, manual process. Here, we investigate the process of labeling data, with a specific focus on coastal aerial imagery captured in the wake of hurricanes that affected the Atlantic and Gulf Coasts of the United States. The imagery data set is a rich observational record of storm impacts and coastal change, but the imagery requires labeling to render that information accessible. We created an online interface that served labelers a stream of images and a fixed set of questions. A total of 1,600 images were labeled by at least two or as many as seven coastal scientists. We used the resulting data set to investigate interrater agreement: the extent to which labelers labeled each image similarly. Interrater agreement scores, assessed with percent agreement and Krippendorff's alpha, are higher when the questions posed to labelers are relatively simple, when the labelers are provided with a user manual, and when images are smaller. Experiments in interrater agreement point toward the benefit of multiple labelers for understanding the uncertainty in labeling data for machine learning research.The authors gratefully acknowledge support from the U.S. Geological Survey (G20AC00403 to EBG and SDM), NSF (1953412 to EBG and SDM; 1939954 to EBG), Microsoft AI for Earth (to EBG and SDM), The Leverhulme Trust (RPG-2018-282 to EDL and EBG), and an Early Career Research Fellowship from the Gulf Research Program of the National Academies of Sciences, Engineering, and Medicine (to EBG). U.S. Geological Survey researchers (DB, J-SRO, JW, and PW) were supported by the U.S. Geological Survey Coastal and Marine Hazards and Resources Program as part of the response and recovery efforts under congressional appropriations through the Additional Supplemental Appropriations for Disaster Relief Act, 2019 (Public Law 116-20; 133 Stat. 871)

Anticipatory stress restores decision-making deficits in heavy drinkers by increasing sensitivity to losses

Background: Substance abusers are characterized by hypersensitivity to reward. This leads to maladaptive decisions generally, as well as those on laboratory-based decision-making tasks, such as the Iowa Gambling Task (IGT). Negative affect has also been shown to disrupt the decision-making of healthy individuals, particularly decisions made under uncertainty. Neuropsychological theories of learning, including the Somatic Marker Hypothesis (SMH), argue this occurs by amplifying affective responses to punishment. In substance abusers, this might serve to rebalance their sensitivity to reward with punishment, and improve decision-making

Gene–gene interaction of AhRwith and within the Wntcascade affects susceptibility to lung cancer

Background: Aberrant Wnt signalling, regulating cell development and stemness, influences the development of many cancer types. The Aryl hydrocarbon receptor (AhR) mediates tumorigenesis of environmental pollutants. Complex interaction patterns of genes assigned to AhR/Wnt-signalling were recently associated with lung cancer susceptibility. Aim: To assess the association and predictive ability of AhR/Wnt-genes with lung cancer in cases and controls of European descent. Methods: Odds ratios (OR) were estimated for genomic variants assigned to the Wnt agonist and the antagonistic genes DKK2, DKK3, DKK4, FRZB, SFRP4 and Axin2. Logistic regression models with variable selection were trained, validated and tested to predict lung cancer, at which other previously identified SNPs that have been robustly associated with lung cancer risk could also enter the model. Furthermore, decision trees were created to investigate variant × variant interaction. All analyses were performed for overall lung cancer and for subgroups. Results: No genome-wide significant association of AhR/Wnt-genes with overall lung cancer was observed, but within the subgroups of ever smokers (e.g., maker rs2722278 SFRP4; OR = 1.20; 95% CI 1.13–1.27; p = 5.6 × 10–10) and never smokers (e.g., maker rs1133683 Axin2; OR = 1.27; 95% CI 1.19–1.35; p = 1.0 × 10–12). Although predictability is poor, AhR/Wnt-variants are unexpectedly overrepresented in optimized prediction scores for overall lung cancer and for small cell lung cancer. Remarkably, the score for never-smokers contained solely two AhR/Wnt-variants. The optimal decision tree for never smokers consists of 7 AhR/Wnt-variants and only two lung cancer variants. Conclusions: The role of variants belonging to Wnt/AhR-pathways in lung cancer susceptibility may be underrated in main-effects association analysis. Complex interaction patterns in individuals of European descent have moderate predictive capacity for lung cancer or subgroups thereof, especially in never smokers

Extended-spectrum β-lactamase-producing Escherichia coli in human-derived and foodchain-derived samples from England, Wales, and Scotland: an epidemiological surveillance and typing study

Background: Escherichia coli isolates producing extended-spectrum βlactamases (‘ESBL-E. coli’) cause >5000 bacteraemias annually in the UK. The contribution of the food chain to this challenge is debated. Methods: Selective media were used to seek ESBL-E. coli in routinely-submitted human faeces, sewage, farm slurry, and retail foodstuffs in London, East Anglia, Northwest England, Scotland and Wales. Recovered isolates were sequenced and compared with 293 bloodstream and 83 veterinary surveillance ESBL-E. coli isolates from the same regions. Findings: 10.7% (2157/20243) of human faeces contained ESBL-E. coli, rising to 17.0% (678/3995) in London. ESBL-E. coli also were frequent in sewage and present in 65.4% (104/159) of retail chicken, but rare in other meats and absent from plant-based foods. Sequence Type (ST) 131 dominated among ESBL-E. coli from human blood (188/293, 64.2%), faeces (128/360, 35.6%) and sewage (14/65, 21.5%) with STs 38 and 648 also widespread; CTX-M-15 was the predominant ESBL in these lineages. By contrast, STs 602, 23, 117 - mostly with CTX-M-1 ESBL - dominated among food and veterinary isolates, with only two ST131 organisms recovered. ST10 occurred in both animals and humans: being frequent in surveillance bovines and representing 4.2% (15/360) of human faecal isolates (but only 1% [3/293] from bacteraemias); however both human and animal ST10 isolates were diverse in serotype. Interpretation: Most human bacteraemias with ESBL-E. coli in the UK involve successful human-associated STs, particularly ST131; non-human reservoirs made little contribution to invasive human disease. Funding: NIHR Policy Research

I am hiQ—a novel pair of accuracy indices for imputed genotypes

Background: Imputation of untyped markers is a standard tool in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy with which genotypes are imputed is fundamental. Several accuracy measures have been proposed and some are implemented in imputation software, unfortunately diversely across platforms. In the present paper, we introduce Iam hiQ, an independent pair of accuracy measures that can be applied to dosage files, the output of all imputation software. Iam (imputation accuracy measure) quantifies the average amount of individual-specific versus population-specific genotype information in a linear manner. hiQ (heterogeneity in quantities of dosages) addresses the inter-individual heterogeneity between dosages of a marker across the sample at hand. Results: Applying both measures to a large case–control sample of the International Lung Cancer Consortium (ILCCO), comprising 27,065 individuals, we found meaningful thresholds for Iam and hiQ suitable to classify markers of poor accuracy. We demonstrate how Manhattan-like plots and moving averages of Iam and hiQ can be useful to identify regions enriched with less accurate imputed markers, whereas these regions would by missed when applying the accuracy measure info (implemented in IMPUTE2). Conclusion: We recommend using Iam hiQ additional to other accuracy scores for variant filtering before stepping into the analysis of imputed GWAS data

Impact of month of birth on the development of autoimmune thyroid disease in the United Kingdom and Europe

CONTEXT: Viral/bacterial infection is proposed as a trigger for the autoimmune thyroid diseases (AITD): Graves' disease (GD) and Hashimoto's thyroiditis (HT). Previous studies in European Caucasian AITD subjects found higher birth rates in the autumn/winter, suggesting those born in the autumn/winter experience increased viral/bacterial exposure after birth, impacting upon immune system development and predisposing to AITD later in life. OBJECTIVE: Month of birth effects were investigated in three independent European Caucasian AITD datasets. DESIGN: Variation in GD and HT onset was compared across months and seasons, with fluctuations across all 12 months analyzed using a Walter-Elwood test. SETTING: The study was conducted at a research laboratory. PATIENTS: National UK Caucasian AITD Case Control Collection (2746 GD and 502 HT compared with 1 423 716 UK births), National UK Caucasian GD Family Collection (239 GD and 227 unaffected siblings), and OXAGEN AITD Caucasian Family Collection (885 GD, 717 HT, and 794 unaffected siblings of European Caucasian decent). MAIN OUTCOME MEASURES: Case-control and family-based association studies were measured. RESULTS: No consistent month of birth effects were detected in GD females or males across all three collections. In HT females from the OXAGEN AITD Caucasian Family Collection, slightly higher birth rates were detected in autumn (Walter's test statistic = 7.47, P = .024) however, this was not seen in the HT females from the case-control cohort. CONCLUSION: Our results suggest in UK/Northern European Caucasian GD subjects, month of birth does not impact on AITD development. Although some month of birth effects for HT females in one collection cannot be excluded, only further work in larger European Caucasian AITD collections can confirm these effects