Lineshape Asymmetry for joint CPT and three photon N resonances

We show that a characteristic two photon lineshape asymmetry arises in coherent population trapping (CPT) and three photon (N) resonances because both resonances are simultaneously induced by modulation sidebands in the interrogating laser light. The N resonance is a three-photon resonance in which a two-photon Raman excitation is combined with a resonant optical pumping field. This joint CPT and N resonance can be the dominant source of lineshape distortion, with direct relevance for the operation of miniaturized atomic frequency standards. We present the results of both an experimental study and theoretical treatment of the asymmetry of the joint CPT and N resonance under conditions typical to the operation of an N resonance clock.Comment: Accepted for publication in Optics Letters, 5 page

Imaging of giant cell arteritis – recent advances

Imaging is increasingly being used to guide clinical decision-making in patients with giant cell arteritis (GCA). While ultrasound has been rapidly adopted in fast-track clinics worldwide as an alternative to temporal artery biopsy for the diagnosis of cranial disease, whole-body PET/CT is emerging as a potential gold standard test for establishing large vessel involvement. However, many unanswered questions remain about the optimal approach to imaging in GCA. For example, it is uncertain how best to monitor disease activity, given there is frequent discordance between imaging findings and conventional disease activity measures, and imaging changes typically fail to resolve completely with treatment. This chapter addresses the current body of evidence for the use of imaging modalities in GCA across the spectrum of diagnosis, monitoring disease activity, and long-term surveillance for structural changes of aortic dilatation and aneurysm formation and provides suggestions for future research directions

Cloning a Profibrotic Stem Cell Variant in Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive, irreversible, and rapidly fatal interstitial lung disease marked by the replacement of lung alveoli with dense fibrotic matrices. Although the mechanisms initiating IPF remain unclear, rare and common alleles of genes expressed in lung epithelia, combined with aging, contribute to the risk for this condition. Consistently, single-cell RNA sequencing (scRNA-seq) studies have identified lung basal cell heterogeneity in IPF that might be pathogenic. We used single-cell cloning technologies to generate libraries of basal stem cells from the distal lungs of 16 patients with IPF and 10 controls. We identified a major stem cell variant that was distinguished from normal stem cells by its ability to transform normal lung fibroblasts into pathogenic myofibroblasts in vitro and to activate and recruit myofibroblasts in clonal xenografts. This profibrotic stem cell variant, which was shown to preexist in low quantities in normal and even fetal lungs, expressed a broad network of genes implicated in organ fibrosis and showed overlap in gene expression with abnormal epithelial signatures identified in previously published scRNA-seq studies of IPF. Drug screens highlighted specific vulnerabilities of this profibrotic variant to inhibitors of epidermal growth factor and mammalian target of rapamycin signaling as prospective therapeutic targets. This profibrotic stem cell variant in IPF was distinct from recently identified profibrotic stem cell variants in chronic obstructive pulmonary disease and may extend the notion that inappropriate accrual of minor and preexisting stem cell variants contributes to chronic lung conditions

Interpretable machine learning models for classifying low back pain status using functional physiological variables.

PURPOSE:To evaluate the predictive performance of statistical models which distinguishes different low back pain (LBP) sub-types and healthy controls, using as input predictors the time-varying signals of electromyographic and kinematic variables, collected during low-load lifting. METHODS:Motion capture with electromyography (EMG) assessment was performed on 49 participants [healthy control (con) = 16, remission LBP (rmLBP) = 16, current LBP (LBP) = 17], whilst performing a low-load lifting task, to extract a total of 40 predictors (kinematic and electromyographic variables). Three statistical models were developed using functional data boosting (FDboost), for binary classification of LBP statuses (model 1: con vs. LBP; model 2: con vs. rmLBP; model 3: rmLBP vs. LBP). After removing collinear predictors (i.e. a correlation of > 0.7 with other predictors) and inclusion of the covariate sex, 31 predictors were included for fitting model 1, 31 predictors for model 2, and 32 predictors for model 3. RESULTS:Seven EMG predictors were selected in model 1 (area under the receiver operator curve [AUC] of 90.4%), nine predictors in model 2 (AUC of 91.2%), and seven predictors in model 3 (AUC of 96.7%). The most influential predictor was the biceps femoris muscle (peak [Formula: see text]  = 0.047) in model 1, the deltoid muscle (peak [Formula: see text] =  0.052) in model 2, and the iliocostalis muscle (peak [Formula: see text] =  0.16) in model 3. CONCLUSION:The ability to transform time-varying physiological differences into clinical differences could be used in future prospective prognostic research to identify the dominant movement impairments that drive the increased risk. These slides can be retrieved under Electronic Supplementary Material

Early experience of COVID-19 vaccination in adults with systemic rheumatic diseases : Results from the COVID-19 Global Rheumatology Alliance Vaccine Survey

Funding Information: Competing interests SES has received funding from the Vasculitis Foundation and the Vasculitis Clinical Research Consortium unrelated to this work. JL has received research grant funding from Pfizer unrelated to this work. ES is a Board Member of the Canadian Arthritis Patient Alliance, a patient run, volunteer-based organisation whose activities are primarily supported by independent grants from pharmaceutical companies. MP was supported by a Rheumatology Research Foundation Scientist Development grant. DA-R is a Scientific Advisor for GlaxoSmithKilne unrelated to this work. FB reports personal fees from Boehringer, Bone Therapeutics, Expanscience, Galapagos, Gilead, GSK, Merck Sereno, MSD, Nordic, Novartis, Pfizer, Regulaxis, Roche, Sandoz, Sanofi, Servier, UCB, Peptinov, TRB Chemedica and 4P Pharma outside of the submitted work. No funding relevant to this manuscript. RC: speakers bureau for Janssen, Roche, Sanofi, AbbVie. KD reports no COI-unpaid volunteer president of the Autoinflammatory Alliance. Any grants or funding from pharma is received by the non-profit organisation only. CLH received funding under a sponsored research agreement unrelated to the data in the paper from Vifor Pharmaceuticals. LeK has received a research grant from Lilly unrelated to this work. AHJK participated in consulting, advisory board or speaker's bureau for Alexion Pharmaceuticals, Aurinia Pharmaceuticals, Annexon Biosciences, Exagen Diagnostics and GlaxoSmithKilne and received funding under a sponsored research agreement unrelated to the data in the paper from GlaxoSmithKline. JSingh has received consultant fees from Crealta/ Horizon, Medisys, Fidia, PK Med, Two Labs, Adept Field Solutions, Clinical Care Options, Clearview Healthcare Partners, Putnam Associates, Focus Forward, Navigant Consulting, Spherix, MedIQ, Jupiter Life Science, UBM, Trio Health, Medscape, WebMD and Practice Point Communications; and the National Institutes of Health and the American College of Rheumatology. JSingh owns stock options in TPT Global Tech, Vaxart Pharmaceuticals and Charlotte’s Web Holdings. JSingh previously owned stock options in Amarin, Viking and Moderna Pharmaceuticals. JSingh is on the speaker’s bureau of Simply Speaking. JSingh is a member of the executive of Outcomes Measures in Rheumatology (OMERACT), an organisation that develops outcome measures in rheumatology and receives arms-length funding from eight companies. JSingh serves on the FDA Arthritis Advisory Committee. JSingh is the chair of the Veterans Affairs Rheumatology Field Advisory Committee. JSingh is the editor and the Director of the University of Alabama at Birmingham (UAB) Cochrane Musculoskeletal Group Satellite Center on Network Meta-analysis. NSingh is supported by funding from the Rheumatology Research Foundation Investigator Award and the American Heart Association. MFU-G has received research support from Pfizer and Janssen, unrelated to this work. SB reports personal fees from Novartis, AbbVie, Pfizer and Horizon Pharma, outside the submitted work. RG reports personal fees from AbbVie New Zealand, Cornerstones, Janssen New Zealand and personal fees and non-financial support Pfizer New Zealand (all <US$10 000) outside the submitted work. PMM reports personal fees from AbbVie, Eli Lilly, Janssen, Novartis, Pfizer and UCB, grants and personal fees from Orphazyme, outside the submitted work. PCR reports personal fees from AbbVie, Gilead, Lilly and Roche, grants and personal fees from Novartis, UCB Pharma, Janssen and Pfizer and non-financial support from BMS, outside the submitted work. PS reports honoraria from Social media editor for @ACR_Journals, outside the submitted work. ZSW reports grants from NIH, BMS and Principia/ Sanofi and personal fees from Viela Bio and MedPace, outside the submitted work. JY reports personal fees from Pfizer and Eli Lilly, and grants and personal fees from AstraZeneca, outside the submitted work. MJL reports grants from American College of Rheumatology, during the conduct of the study and consulting fees from AbbVie, Amgen, Actelion, Boehringer Ingelheim, BMS, Celgene, Gilead, J&J, Mallinckrodt, Novartis, Pfizer, Roche, Sandoz, Sanofi, Sobi and UCB, outside the submitted work. LGR was supported by the Intramural Research Program of the National Institute of Environmental Health Sciences (NIEHS; ZIAES101074) of the National Institutes of Health. JH reports grants from Childhood Arthritis and Rheumatology Research Alliance (CARRA) and Rheumatology Research Alliance, and personal fees from Novartis, Pfizer and Biogen, outside the submitted work. JSimard received research grant funding from the National Institutes of Health unrelated to this work (NIAMS: R01 AR077103 and NIAID R01 AI154533). JSparks has performed consultancy for AbbVie, Boehringer Ingelheim, Bristol-Myers Squibb, Gilead, Inova Diagnostics, Optum and Pfizer unrelated to this work. Funding Information: Funding This study was supported by the European Alliance of Associations for Rheumatology and American College of Rheumatology Research and Education Foundation. Dr. Lisa Rider's involvement was supported in part by the Intramural Research Program of the National Institutes of Health, National Institute of Environmental Health Sciences. Publisher Copyright: © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.Background. We describe the early experiences of adults with systemic rheumatic disease who received the COVID-19 vaccine. Methods From 2 April to 30 April 2021, we conducted an online, international survey of adults with systemic rheumatic disease who received COVID-19 vaccination. We collected patient-reported data on clinician communication, beliefs and intent about discontinuing disease-modifying antirheumatic drugs (DMARDs) around the time of vaccination, and patient-reported adverse events after vaccination. Results We analysed 2860 adults with systemic rheumatic diseases who received COVID-19 vaccination (mean age 55.3 years, 86.7% female, 86.3% white). Types of COVID-19 vaccines were Pfizer-BioNTech (53.2%), Oxford/AstraZeneca (22.6%), Moderna (21.3%), Janssen/Johnson & Johnson (1.7%) and others (1.2%). The most common rheumatic disease was rheumatoid arthritis (42.3%), and 81.2% of respondents were on a DMARD. The majority (81.9%) reported communicating with clinicians about vaccination. Most (66.9%) were willing to temporarily discontinue DMARDs to improve vaccine efficacy, although many (44.3%) were concerned about rheumatic disease flares. After vaccination, the most reported patient-reported adverse events were fatigue/somnolence (33.4%), headache (27.7%), muscle/joint pains (22.8%) and fever/chills (19.9%). Rheumatic disease flares that required medication changes occurred in 4.6%. Conclusion. Among adults with systemic rheumatic disease who received COVID-19 vaccination, patient-reported adverse events were typical of those reported in the general population. Most patients were willing to temporarily discontinue DMARDs to improve vaccine efficacy. The relatively low frequency of rheumatic disease flare requiring medications was reassuring.publishersversionPeer reviewe

Executive summary of the KDIGO 2021 Guideline for the Management of Glomerular Diseases.

The Kidney Disease: Improving Global Outcomes (KDIGO) Clinical Practice Guideline for the Management of Glomerular Diseases is an update to the KDIGO 2012 guideline. The aim is to assist clinicians caring for individuals with glomerulonephritis (GN), both adults and children. The scope includes various glomerular diseases, including IgA nephropathy and IgA vasculitis, membranous nephropathy, nephrotic syndrome, minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), infection-related GN, antineutrophil cytoplasmic antibody (ANCA) vasculitis, lupus nephritis, and anti-glomerular basement membrane antibody GN. In addition, this guideline will be the first to address the subtype of complement-mediated diseases. Each chapter follows the same format providing guidance related to diagnosis, prognosis, treatment, and special situations. The goal of the guideline is to generate a useful resource for clinicians and patients by providing actionable recommendations based on evidence syntheses, with useful infographics incorporating views from experts in the field. Another aim is to propose research recommendations for areas where there are gaps in knowledge. The guideline targets a broad global audience of clinicians treating GN while being mindful of implications for policy and cost. Development of this guideline update followed an explicit process whereby treatment approaches and guideline recommendations are based on systematic reviews of relevant studies, and appraisal of the quality of the evidence and the strength of recommendations followed the "Grading of Recommendations Assessment, Development and Evaluation" (GRADE) approach. Limitations of the evidence are discussed, with areas of future research also presented

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Results From the Global Rheumatology Alliance Registry

Funding Information: We acknowledge financial support from the ACR and EULAR. The ACR and EULAR were not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Publisher Copyright: © 2022 The Authors. ACR Open Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.Objective: Some patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID-19 ARDS in this population and to create a simple risk score calculator for use in clinical settings. Methods: Data were derived from the COVID-19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID-19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier. Results: The study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67-0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%-83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator. Conclusion: We were able to predict ARDS with good sensitivity using information readily available at COVID-19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID-19 disease progression.publishersversionepub_ahead_of_prin

Chronic Stroke Sensorimotor Impairment Is Related to Smaller Hippocampal Volumes: An ENIGMA Analysis

Background. Persistent sensorimotor impairments after stroke can negatively impact quality of life. The hippocampus is vulnerable to poststroke secondary degeneration and is involved in sensorimotor behavior but has not been widely studied within the context of poststroke upper‐limb sensorimotor impairment. We investigated associations between non‐lesioned hippocampal volume and upper limb sensorimotor impairment in people with chronic stroke, hypothesizing that smaller ipsilesional hippocampal volumes would be associated with greater sensorimotor impairment. Methods and Results. Cross‐sectional T1‐weighted magnetic resonance images of the brain were pooled from 357 participants with chronic stroke from 18 research cohorts of the ENIGMA (Enhancing NeuoImaging Genetics through Meta‐Analysis) Stroke Recovery Working Group. Sensorimotor impairment was estimated from the FMA‐UE (Fugl‐Meyer Assessment of Upper Extremity). Robust mixed‐effects linear models were used to test associations between poststroke sensorimotor impairment and hippocampal volumes (ipsilesional and contralesional separately; Bonferroni‐corrected, P<0.025), controlling for age, sex, lesion volume, and lesioned hemisphere. In exploratory analyses, we tested for a sensorimotor impairment and sex interaction and relationships between lesion volume, sensorimotor damage, and hippocampal volume. Greater sensorimotor impairment was significantly associated with ipsilesional (P=0.005; β=0.16) but not contralesional (P=0.96; β=0.003) hippocampal volume, independent of lesion volume and other covariates (P=0.001; β=0.26). Women showed progressively worsening sensorimotor impairment with smaller ipsilesional (P=0.008; β=−0.26) and contralesional (P=0.006; β=−0.27) hippocampal volumes compared with men. Hippocampal volume was associated with lesion size (P<0.001; β=−0.21) and extent of sensorimotor damage (P=0.003; β=−0.15). Conclusions. The present study identifies novel associations between chronic poststroke sensorimotor impairment and ipsilesional hippocampal volume that are not caused by lesion size and may be stronger in women.S.-L.L. is supported by NIH K01 HD091283; NIH R01 NS115845. A.B. and M.S.K. are supported by National Health and Medical Research Council (NHMRC) GNT1020526, GNT1045617 (A.B.), GNT1094974, and Heart Foundation Future Leader Fellowship 100784 (A.B.). P.M.T. is supported by NIH U54 EB020403. L.A.B. is supported by the Canadian Institutes of Health Research (CIHR). C.M.B. is supported by NIH R21 HD067906. W.D.B. is supported by the Heath Research Council of New Zealand. J.M.C. is supported by NIH R00HD091375. A.B.C. is supported by NIH R01NS076348-01, Hospital Israelita Albert Einstein 2250-14, CNPq/305568/2016-7. A.N.D. is supported by funding provided by the Texas Legislature to the Lone Star Stroke Clinical Trial Network. Its contents are solely the responsibility of the authors and do not necessarily represent the of ficial views of the Government of the United States or the State of Texas. N.E.-B. is supported by Australian Research Council NIH DE180100893. W.F. is sup ported by NIH P20 GM109040. F.G. is supported by Wellcome Trust (093957). B.H. is funded by and NHMRC fellowship (1125054). S.A.K is supported by NIH P20 HD109040. F.B. is supported by Italian Ministry of Health, RC 20, 21. N.S. is supported by NIH R21NS120274. N.J.S. is supported by NIH/National Institute of General Medical Sciences (NIGMS) 2P20GM109040-06, U54-GM104941. S.R.S. is supported by European Research Council (ERC) (NGBMI, 759370). G.S. is supported by Italian Ministry of Health RC 18-19-20-21A. M.T. is sup ported by National Institute of Neurological Disorders and Stroke (NINDS) R01 NS110696. G.T.T. is supported by Temple University sub-award of NIH R24 –NHLBI (Dr Mickey Selzer) Center for Experimental Neurorehabilitation Training. N.J.S. is funded by NIH/National Institute of Child Health and Human Development (NICHD) 1R01HD094731-01A1