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

results from the COVID-19 Global Rheumatology Alliance Vaccine Survey

Funding Information: MP, KK, and ES contributed equally and are co-first authors. JHS, JASp, and JFS contributed equally and are co-senior authors. The authors thank Berk Degirmenci, Christele Feliix, Shangyi Jin, Candace A Palmerlee, Andrea Peirce, Lisa G Rider, Esra Sari, Robert Tseng, and Leslie Wang for their invaluable contributions to the GRA Vax Survey. MP, KK, ES, SES, and JWL contributed to data collection, data quality control, and data analysis and interpretation. AAA, DA-R, SA, RPB, FB, IB, YPEC, RC, AD-G, ED, KLD, TAG, CLH, RH, BFH, EH, LK, AK, AHJK, DFLL, CL, EFM, BM, SM, MN, ADS, JASi, NS, MFU-G, JW, KJY, and EAZ-T, critically revised the manuscript and provided intellectual content. TTM, CH, MJL, ML, GF, and LT contributed to planning and data collection, reviewed the manuscript, and provided important intellectual content. SB, WC, RG, PMM, PCR, PS, ZSW, and JY contributed to the acquisition, analysis, and interpretation of the data. JASp, JFS, and JSH directed the work, designed the data collection methods, and contributed to the analysis and interpretation of the data. MP, KK, ES, SES, JWL, SB, WC, RG, PMM, PCR, PS, ZSW, JY, JASp, JFS, and JSH drafted and revised the manuscript critically for important intellectual content and gave final approval of the version to be published. SES, JWL, KK, JFS, and JASp had full access to the data and verify the credibility of the underlying data. All authors have read, revised, and approved this manuscript and take final responsibility for the decision to submit for publication. MP reports clinical trials participation with AbbVie and grants from Rheumatology Research Foundation, outside the submitted 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. JWL has received research grant funding from Pfizer unrelated to this work. SES reports research funding related to clinical trials from AstraZeneca (MANDARA), outside of the submitted work and is supported by the Vasculitis Clinical Research Consortium and Vasculitis Foundation outside of the submitted work. DA-R is a scientific advisor for GlaxoSmithKilne unrelated to this work. RC reports speaker fees from Janssen, Roche, Sanofi, and AbbVie, outside of the submitted work. AD-G reports grants from the Center for Disease Control and Prevention, Rheumatology Research Foundation, and Mayo Clinic, outside the submitted work. KLD is an unpaid volunteer president of the Autoinflammatory Alliance and reports grants from Novartis, Sobi, National Institutes of Health (NIH), and Horizon Bio, all received by the non-profit organisation outside of the submitted work. CLH received funding under a sponsored research agreement unrelated to the data in the paper from Vifor Pharmaceuticals. RH reports grants from AbbVie, Amgen, Boehringer Ingleheim, Johnson and Johnson, Lilly, Novartis, Pfizer, and Union Chimique Belge, all paid to Spondylitis Association of America, consultant fees from GlaxoSmithKline and Novartis, outside the submitted work. RH also owns stocks (<20 shares and representing <4% of personal investments) in AbbVie, Amgen, Bristol Myers Squibb, GlaxoSmithKline, Johnson & Johnson, Eli Lilly, Merck, Novartis, Pfizer, Teva, and Union Chimique Belge. AHJK reports personal fees from Exagen Diagnostics, Alexion Pharmaceuticals, and Aurinia Pharmaceuticals, grants from National Institutes of Health, Rheumatology Research Foundation, and Helmsley Charitable Trust, grants and personal fees from GlaxoSmithKline, outside the submitted work. EFM reports personal fees from Boehringer Ingelheim, and that Liga Portuguesa Contra as Doenças Reumaticas has received grants from AbbVie, Novartis, Lilly Portugal, Amgen Biofarmacêutica, Grünenthal, Merck Sharp & Dohme, Medac and from A Menarini Portugal–Farmacêutica; grants and non-financial support from Pfizer and Grünenthal, outside the submitted work. JASi 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, United BioMed, Trio Health, Medscape, WebMD, and Practice Point communications; and the National Institutes of Health, and the American College of Rheumatology. JASi owns stock options in TPT Global Tech, Vaxart pharmaceuticals, and Charlotte's Web Holdings and previously owned stock options in Amarin, Viking and Moderna pharmaceuticals. JASi is on the speaker's bureau of Simply Speaking and is a member of the executive of Outcomes Measures in Rheumatology, an organisation that develops outcome measures in rheumatology and receives funding from eight companies . JASi also serves on the FDA Arthritis Advisory Committee and is the chair of the Veterans Affairs Rheumatology Field Advisory Committee. JASi is also the editor and the Director of the University of Alabama at Birmingham Cochrane Musculoskeletal Group Satellite Center on Network Meta-analysis. MFU-G has received research support from Pfizer and Janssen, unrelated to this work. SB reports non-branded consulting fees from Novartis, AbbVie, Pfizer, and Horizon Pharma, outside the submitted work, and is a Pfizer employee as of September, 2021. RG reports personal fees from AbbVie New Zealand, Cornerstones, Janssen New Zealand, and Novartis, and personal fees and non-financial support Pfizer Australia (all <AU$10,000) outside the submitted work. PMM reports personal fees from AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, and Union Chimique Belge; and 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, Union Chimique Belge, Janssen, and Pfizer; and non-financial support from Bristol Myers Squibb, outside the submitted work. PS reports honoraria from bring the social media editor for the American College of Rheumatology journals, outside the submitted work. ZSW reports grants from NIH, Bristol Myers Squibb, 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. CH reports personal fees from AstraZeneca and Aurinia Pharmaceuticals, 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, Bristol Myers Squibb, Celgene, Gilead, Johnson and Johnson, Mallinckrodt, Novartis, Pfizer, Roche, Sandoz, Sanofi, Sobi, and Union Chimique Belge, outside the submitted work. JSH reports grants from Childhood Arthritis and Rheumatology Research Alliance and Rheumatology Research Alliance, and personal fees from Novartis, Pfizer, and Biogen, outside the submitted work. JASp reports grants from National Institute of Arthritis and Musculoskeletal and Skin Diseases, Rheumatology Research Foundation, and R Bruce and Joan M Mickey Research Scholar Fund; and consulting fees for AbbVie, Boehringer Ingelheim, Bristol Myers Squibb, Gilead, Inova Diagnostics, Optum, and Pfizer, unrelated to this work. JFS received research grant funding from the National Institutes of Health unrelated to this work (NIAMS R01 AR077103, and NIAID R01 AI154533). All other authors report no competing interests. This study was funded by the American College of Rheumatology (ACR). The ACR was not involved in any aspect of study design, collection, analysis, or interpretation of data, writing of the report, or the decision to submit the paper for publication. The views expressed here are those of the authors and participating members of the COVID-19 Global Rheumatology Alliance and do not necessarily represent the views of the ACR, the European Alliance of Associations for Rheumatology, the UK National Health Service, the National Institute for Health Research, or the UK Department of Health, or any other organisation. Researchers interested in performing additional analyses from survey data are invited to submit proposals through the COVID-19 Global Rheumatology Alliance at rheumcovid.org . For approved projects, we will provide summary tables and data analyses as requested. We do not currently have institutional review board approval to make the raw data available to other researchers.publishersversionpublishe

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

Associations of alcohol and cannabis use with change in posttraumatic stress disorder and depression symptoms over time in recently trauma-exposed individuals.

BACKGROUND: Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians. METHODS: In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance. RESULTS: Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12. CONCLUSIONS: Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies

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