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1.
NPJ Digital Medicine ; 5(1), 2022.
Article in English | ProQuest Central | ID: covidwho-1837420

ABSTRACT

Continued COVID-19 surges have highlighted the need for widespread testing in addition to vaccination for disease containment. SARS-COV-2 RNA can be found in faecal matter, making human stool another potential source for COVID-19 diagnostics. In this commentary, we highlight potential strategies to use a smart toilet platform to passively monitor COVID-19 surges, enabling earlier detection of infected individuals and promoting public health.

2.
Alcohol Clin Exp Res ; 2022 May 09.
Article in English | MEDLINE | ID: covidwho-1831907

ABSTRACT

BACKGROUND: This study characterized the prevalence, drinking patterns, and sociodemographic characteristics of U.S. adult subpopulations with distinct drinking trajectories during the COVID-19 pandemic's first 42 weeks. METHODS: Adult respondents (n = 8130) in a nationally representative prospective longitudinal study completed 21 biweekly web surveys (March 2020 to January 2021). Past-week alcohol drinking frequency (drinking days [range: 0 to 7]) and intensity (binge drinking on usual past-week drinking day [yes/no]) were assessed at each timepoint. Growth mixture models identified multiple subpopulations with homogenous drinking trajectories based on mean drinking days or binge drinking proportional probabilities across time. RESULTS: Four drinking frequency trajectories were identified: Minimal/stable (72.8% [95% CI = 71.8 to 73.8]) with <1 mean past-week drinking days throughout; Moderate/late decreasing (6.7% [95% CI = 6.2 to 7.3) with 3.13 mean March drinking days and reductions during summer, reaching 2.12 days by January 2021; Moderate/early increasing (12.9% [95% CI = 12.2 to 13.6) with 2.13 mean March drinking days that increased in April and then plateaued, ending with 3.20 mean days in January 2021; and Near daily/early increasing (7.6% [95% CI = 7.0 to 8.2]) with 5.58 mean March drinking days that continued increasing without returning to baseline. Four drinking intensity trajectories were identified: Minimal/stable (85.8% [95% CI = 85.0% to 86.5%]) with <0.01 binge drinking probabilities throughout; Low-to-moderate/fluctuating (7.4% [95% CI = 6.8% to 8%]) with varying binge probabilities across timepoints (range:0.12 to 0.26); Moderate/mid increasing (4.2% [95% CI = 3.7% to 4.6%]) with 0.39 April binge drinking probability rising to 0.65 during August-September without returning to baseline; High/early increasing trajectory (2.7% [95% CI = 2.3% to 3%]) with 0.84 binge drinking probability rising to 0.96 by June without returning to baseline. Males, Whites, middle-aged/older adults, college degree recipients, those consistently working, and those above the poverty limit were overrepresented in various increasing (vs. minimal/stable) frequency trajectories. Males, Whites, nonmarried, those without college degree, 18 to 39-year-olds, and middle aged were overrepresented in increasing (vs. minimal/stable) intensity trajectories. CONCLUSIONS: Several distinct U.S. adult sociodemographic subpopulations appear to have acquired new drinking patterns during the pandemic's first 42 weeks. Frequent alcohol use assessment in the COVID-19 era could improve personalized medicine and population health efforts to reduce drinking.

3.
Vaccine ; 40(24): 3288-3293, 2022 May 26.
Article in English | MEDLINE | ID: covidwho-1799675

ABSTRACT

Identifying factors associated with COVID-19 vaccination acceptance among vulnerable groups, including autistic individuals, can increase vaccination rates and support public health. The purpose of this study was to determine differences among autistic adults who reported COVID-19 vaccination acceptance from those who did not. In this study we describe COVID-19 vaccination status and self-reported preferences among autistic adults and identify related factors. Vaccine accepters were more likely to report increased loneliness during COVID-19, lived in more populous counties (p = 0.02), and lived in counties won by President Biden in the 2020 US presidential election (p < 0.001). Positive correlations were found between desire to protect others, concern about contracting COVID-19, and trusting vaccine safety (p < 0.001). Concern about vaccine safety was common among the vaccine hesitant, while lack of concern about COVID-19 overall was not. Identifying health promotion strategies based on self-reported, lived experiences about COVID-19 among vulnerable groups is key for public health impact.


Subject(s)
Autistic Disorder , COVID-19 , Vaccines , Adult , COVID-19/prevention & control , COVID-19 Vaccines , Humans , SARS-CoV-2 , Self Report , Vaccination
4.
Int J Environ Res Public Health ; 19(8)2022 04 18.
Article in English | MEDLINE | ID: covidwho-1792693

ABSTRACT

Concerns regarding the physical and mental health impacts of frontline healthcare roles during the COVID-19 pandemic have been well documented, but the impacts on family functioning remain unclear. This study provides a unique contribution to the literature by considering the impacts of the COVID-19 pandemic on frontline healthcare workers and their families. Thirty-nine frontline healthcare workers from Victoria, Australia, who were parents to at least one child under 18 were interviewed. Data were analysed using reflexive thematic analysis. Five superordinate and 14 subordinate themes were identified. Themes included more family time during lockdowns, but at a cost; changes in family responsibilities and routines; managing increased demands; healthcare workers hypervigilance and fear of bringing COVID-19 home to their family members; ways in which families worked to "get through it". While efforts have been made by many healthcare organisations to support their workers during this challenging time, the changes in family functioning observed by participants suggest that more could be done for this vulnerable cohort, particularly with respect to family support.


Subject(s)
COVID-19 , COVID-19/epidemiology , Child , Communicable Disease Control , Health Personnel/psychology , Humans , Pandemics , SARS-CoV-2 , Victoria/epidemiology
5.
6.
J Natl Med Assoc ; 114(3): 265-273, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1702004

ABSTRACT

INTRODUCTION: Black, Hispanic, and Indigenous groups have carried the burden of COVID-19 disease in comparison to non-marginalized groups within the United States. It is important to examine the factors that have led to the observed disparities in COVID-19 risk, morbidity, and mortality. We described primary health care access within large US metropolitan cities in relation to COVID-19 rate, race/ethnicity, and income level and hypothesized that observed racial/ethnic disparities in COVID-19 rates are associated with health care provider number. METHODS: We accessed public city health department records for reported COVID-19 cases within 10 major metropolitan cities in the United States and also obtained publicly available racial/ethnic demographic median income and primary health care provider counts within individual zip codes. We made comparisons of COVID-19 case numbers within zip codes based on racial/ethnic and income makeup in relation to primary health care counts. RESULTS: Median COVID-19 rates differed by race/ethnicity and income. There was an inverse relationship between median income and COVID-19 rate within zip codes (rho: -0.515; p<0.001). However, this relationship was strongest within racially/ethnically non-marginalized zip codes relative to those composed mainly of racially/ethnically marginalized populations (rho: -0.427 vs. rho: -0.175 respectively). Health care provider number within zip codes was inversely associated with the COVID-19 rate. (rho: -0.157; p<0.001) However, when evaluated by stratified groups by race the association was only significant within racially/ethnically marginalized zip codes(rho: -0.229; p<0.001). DISCUSSION: COVID-19 case rates were associated with racial/ethnic makeup and income status within zip codes across the United States and likewise, primary care provider access also differed by these factors. However, our study reveals that structural and systemic barriers and inequities have led to disproportionate access to health care along with other factors that require identification. CONCLUSION: These results pose a concern in terms of pandemic progression into the next year and how these structural inequities have impacted and will impact vaccine distribution.


Subject(s)
COVID-19 , Racism , COVID-19/epidemiology , Cities , Health Services Accessibility , Health Status Disparities , Humans , United States/epidemiology
7.
Cell Rep ; 38(11): 110508, 2022 03 15.
Article in English | MEDLINE | ID: covidwho-1700144

ABSTRACT

Concerns that infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of coronavirus disease 2019 (COVID-19), may cause new-onset diabetes persist in an evolving research landscape, and precise risk assessment is hampered by, at times, conflicting evidence. Here, leveraging comprehensive single-cell analyses of in vitro SARS-CoV-2-infected human pancreatic islets, we demonstrate that productive infection is strictly dependent on the SARS-CoV-2 entry receptor ACE2 and targets practically all pancreatic cell types. Importantly, the infection remains highly circumscribed and largely non-cytopathic and, despite a high viral burden in infected subsets, promotes only modest cellular perturbations and inflammatory responses. Similar experimental outcomes are also observed after islet infection with endemic coronaviruses. Thus, the limits of pancreatic SARS-CoV-2 infection, even under in vitro conditions of enhanced virus exposure, challenge the proposition that in vivo targeting of ß cells by SARS-CoV-2 precipitates new-onset diabetes. Whether restricted pancreatic damage and immunological alterations accrued by COVID-19 increase cumulative diabetes risk, however, remains to be evaluated.


Subject(s)
COVID-19 , Diabetes Mellitus , Insulin-Secreting Cells , Humans , Pancreas , SARS-CoV-2
8.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-314979

ABSTRACT

Objectives: Federal open data initiatives that promote increased sharing of federally collected data are important for transparency, data quality, trust, and relationships with the public and state, tribal, local, and territorial (STLT) partners. These initiatives advance understanding of health conditions and diseases by providing data to more researchers, scientists, and policymakers for analysis, collaboration, and valuable use outside CDC responders. This is particularly true for emerging conditions such as COVID-19 where we have much to learn and have evolving data needs. Since the beginning of the outbreak, CDC has collected person-level, de-identified data from jurisdictions and currently has over 8 million records, increasing each day. This paper describes how CDC designed and produces two de-identified public datasets from these collected data. Materials and Methods: Data elements were included based on the usefulness, public request, and privacy implications;specific field values were suppressed to reduce risk of reidentification and exposure of confidential information. Datasets were created and verified for privacy and confidentiality using data management platform analytic tools as well as R scripts. Results: Unrestricted data are available to the public through Data.CDC.gov and restricted data, with additional fields, are available with a data use agreement through a private repository on GitHub.com. Practice Implications: Enriched understanding of the available public data, the methods used to create these data, and the algorithms used to protect privacy of de-identified individuals allow for improved data use. Automating data generation procedures allows greater and more timely sharing of data.

9.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-305407

ABSTRACT

This conceptual paper overviews how blockchain technology is involving the operation of multi-robot collaboration for combating COVID-19 and future pandemics. Robots are a promising technology for providing many tasks such as spraying, disinfection, cleaning, treating, detecting high body temperature/mask absence, and delivering goods and medical supplies experiencing an epidemic COVID-19. For combating COVID-19, many heterogeneous and homogenous robots are required to perform different tasks for supporting different purposes in the quarantine area. Controlling and decentralizing multi-robot play a vital role in combating COVID-19 by reducing human interaction, monitoring, delivering goods. Blockchain technology can manage multi-robot collaboration in a decentralized fashion, improve the interaction among them to exchange information, share representation, share goals, and trust. We highlight the challenges and provide the tactical solutions enabled by integrating blockchain and multi-robot collaboration to combat COVID-19 pandemic. The framework of our conceptual proposed can increase the intelligence, decentralization, and autonomous operations of connected multi-robot collaboration in the blockchain network. We overview blockchain potential benefits to defining a framework of multi-robot collaboration applications to combat COVID-19 epidemics such as monitoring and outdoor and hospital End to End (E2E) delivery systems. Furthermore, we discuss the challenges and opportunities of integrated blockchain, multi-robot collaboration, and the Internet of Things (IoT) for combating COVID-19 and future pandemics.

10.
Critical Care Medicine ; 50:414-414, 2022.
Article in English | Academic Search Complete | ID: covidwho-1599070

ABSTRACT

B Description: b We present a case of a 36-year-old patient, G2P1001 at a gestational age of 26 weeks and 4 days with severe acute hypoxemic respiratory failure secondary to COVID-19 infection, requiring extracorporeal membrane oxygenation who underwent successful cesarean section while on ECMO. B Introduction: b Severe Sars-CoV-2 (COVID-19) infection has been reported in both pregnant and postpartum women despite young age and lack of comorbidities. While there are no randomized clinical trials demonstrating improved outcomes in peripartum women, current literature supports the use of ECMO in both pregnant and postpartum patients with severe COVID-19 infection. [Extracted from the article] Copyright of Critical Care Medicine is the property of Lippincott Williams & Wilkins and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

12.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-292099

ABSTRACT

Concerns that infection with SARS-CoV-2, the etiological agent of COVID-19, may cause new-onset diabetes persist amidst an evolving research landscape, and precise risk assessment is hampered by at times conflicting evidence. Here, leveraging comprehensive single-cell analyses of in vitro SARS-CoV-2-infected human pancreatic islets, we demonstrate that productive infection is strictly dependent on the SARS-CoV-2 entry receptor ACE2 and targets all pancreatic cell types. Importantly, the infection remains highly circumscribed, largely non-cytopathic, and despite high viral burden in infected subsets, promotes only modest cellular perturbations and inflammatory responses. Similar experimental outcomes are also observed after islet infection with endemic coronaviruses. Thus, the limits of pancreatic SARS-CoV-2 infection, even under in vitro conditions of enhanced virus exposure, do not support the proposition that in vivo targeting of beta cells by SARS-CoV-2 precipitates new-onset diabetes. If restricted pancreatic damage accrued by COVID-19 increases cumulative diabetes risk, however, remains to be evaluated.Funding: These efforts were supported by JDRF 3-PDF-2018-575-A-N (V.v.d.H.);NIH/NIDDK R01DK12392, NIH/NIAID P01AI042288 and NIH/NIAID U54AI142766-S1 (M.A.A.);NIH/NIAID Center of Excellence for Influenza Research and Response/Center for Research for Influenza Pathogenesis and Transmission contract # 75N93019R00028, NIH/NIAID U19AI135972 (supplement), Defense Advanced Research Projects Agency HR0011-19-2-0020, JPB Foundation, and Open Philanthropy Project # 2020-215611 (5384), Anonymous (A.G.-S.);NIH/NIAID R01AI151029 and NIA/NIAID U01AI150748 (B.R.R.);NIH/NIDDK R01DK130425 (M.S.);and NIH/NIAID R01AI134971, NIH/NIDDK U01DK123716, NIH/NIDDK U01DK104162, NIH/NIDDK P30DK020541 and NIH/NIDDK R01DK130425 (D.H.).Funding: The AG-S laboratory has received research support from Pfizer, Senhwa Biosciences, Kenall Manufacturing, Avimex, Johnson & Johnson, Dynavax, 7Hills Pharma, Pharmamar, ImmunityBio, Accurius, Nanocomposix, Hexamer, N-fold LLC, Model Medicines and Merck, outside of the reported work. Declaration of Interests: AG-S has consulting agreements for the following companies involving cash and/or stock: Vivaldi Biosciences, Contrafect, 7Hills Pharma, Avimex, Vaxalto, Pagoda, Accurius, Esperovax, Farmak, Applied Biological Laboratories and Pfizer, outside of the reported work. AG-S is inventor on patents and patent applications on the use of antivirals and vaccines for the treatment and prevention of virus infections and cancer, owned by the Icahn School of Medicine at Mount Sinai, New York, outside of the reported work. All other authors declare no conflict of interest. Ethics Approval Statement: Our study is considered “not human subjects research” since all donor islet preparations were provided as de-identified tissue specimens by a commercial purveyor

13.
Nucleic Acids Res ; 50(D1): D1115-D1122, 2022 01 07.
Article in English | MEDLINE | ID: covidwho-1493885

ABSTRACT

The UCSC Genome Browser, https://genome.ucsc.edu, is a graphical viewer for exploring genome annotations. The website provides integrated tools for visualizing, comparing, analyzing, and sharing both publicly available and user-generated genomic datasets. Data highlights this year include a collection of easily accessible public hub assemblies on new organisms, now featuring BLAT alignment and PCR capabilities, and new and updated clinical tracks (gnomAD, DECIPHER, CADD, REVEL). We introduced a new Track Sets feature and enhanced variant displays to aid in the interpretation of clinical data. We also added a tool to rapidly place new SARS-CoV-2 genomes in a global phylogenetic tree enabling researchers to view the context of emerging mutations in our SARS-CoV-2 Genome Browser. Other new software focuses on usability features, including more informative mouseover displays and new fonts.


Subject(s)
Databases, Genetic , Web Browser , Animals , Genome, Human , Humans , Phylogeny , Polymerase Chain Reaction , SARS-CoV-2/genetics , User-Computer Interface , Whole Exome Sequencing
15.
MMWR Morb Mortal Wkly Rep ; 70(23): 846-850, 2021 Jun 11.
Article in English | MEDLINE | ID: covidwho-1389869

ABSTRACT

SARS-CoV-2, the virus that causes COVID-19, is constantly mutating, leading to new variants (1). Variants have the potential to affect transmission, disease severity, diagnostics, therapeutics, and natural and vaccine-induced immunity. In November 2020, CDC established national surveillance for SARS-CoV-2 variants using genomic sequencing. As of May 6, 2021, sequences from 177,044 SARS-CoV-2-positive specimens collected during December 20, 2020-May 6, 2021, from 55 U.S. jurisdictions had been generated by or reported to CDC. These included 3,275 sequences for the 2-week period ending January 2, 2021, compared with 25,000 sequences for the 2-week period ending April 24, 2021 (0.1% and 3.1% of reported positive SARS-CoV-2 tests, respectively). Because sequences might be generated by multiple laboratories and sequence availability varies both geographically and over time, CDC developed statistical weighting and variance estimation methods to generate population-based estimates of the proportions of identified variants among SARS-CoV-2 infections circulating nationwide and in each of the 10 U.S. Department of Health and Human Services (HHS) geographic regions.* During the 2-week period ending April 24, 2021, the B.1.1.7 and P.1 variants represented an estimated 66.0% and 5.0% of U.S. SARS-CoV-2 infections, respectively, demonstrating the rise to predominance of the B.1.1.7 variant of concern† (VOC) and emergence of the P.1 VOC in the United States. Using SARS-CoV-2 genomic surveillance methods to analyze surveillance data produces timely population-based estimates of the proportions of variants circulating nationally and regionally. Surveillance findings demonstrate the potential for new variants to emerge and become predominant, and the importance of robust genomic surveillance. Along with efforts to characterize the clinical and public health impact of SARS-CoV-2 variants, surveillance can help guide interventions to control the COVID-19 pandemic in the United States.


Subject(s)
COVID-19/virology , SARS-CoV-2/genetics , COVID-19/epidemiology , Epidemiological Monitoring , Humans , SARS-CoV-2/isolation & purification , United States/epidemiology
17.
Diagn Microbiol Infect Dis ; 101(4): 115518, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1347572

ABSTRACT

We compared the performance of the Abbott Real Time SARS-CoV-2 assay (Abbott assay), Aptima™ SARS-CoV-2 assay (Aptima assay), BGI Real-Time SARS-CoV-2 assay (BGI assay), Lyra® SARS-CoV-2 assay (Lyra assay), and DiaSorin Simplexa™ COVID assay for SARS-CoV-2 detection. Residual nasopharyngeal samples (n = 201) submitted for routine SARS-CoV-2 testing by Simplexa assay during June-July 2020 and January 2021 were salvaged. Aliquots were tested on other assays and compared against the CDC 2019-nCoV Real-Time RT-PCR assay. Viral load in positive samples was determined by droplet digital PCR. Among 201 samples, 99 were positive and 102 were negative by the CDC assay. The Aptima and Abbott assays exhibited the highest positive percent agreement (PPA) at 98.9% while the BGI assay demonstrated the lowest PPA of 89.9% with 10 missed detections. Negative percent agreement for all 5 platforms was comparable, ranging from 96.1% to 100%. The performance of all five assays was comparable.


Subject(s)
COVID-19 Testing/methods , COVID-19/diagnosis , Molecular Diagnostic Techniques/methods , SARS-CoV-2/isolation & purification , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/virology , Female , Humans , Male , Middle Aged , Nasopharynx/virology , Prospective Studies , Sensitivity and Specificity , Viral Load , Young Adult
18.
SSRN; 2021.
Preprint in English | SSRN | ID: ppcovidwho-290031
19.
BMJ Open ; 11(6): e047561, 2021 06 25.
Article in English | MEDLINE | ID: covidwho-1282099

ABSTRACT

OBJECTIVE: To assess the impact of diabetes, hypertension and cardiovascular diseases on inpatient mortality from COVID-19, and its relationship to ethnicity and social deprivation. DESIGN: Retrospective, single-centre observational study SETTING: Birmingham, UK. PARTICIPANTS: 907 hospitalised patients with laboratory-confirmed COVID-19 from a multi-ethnic community, admitted between 1 March 2020 and 31 May 2020. MAIN OUTCOME MEASURES: The primary analysis was an evaluation of cardiovascular conditions and diabetes in relation to ethnicity and social deprivation, with the end-point of inpatient death or death within 30 days of discharge. A multivariable logistic regression model was used to calculate HRs while adjusting for confounders. RESULTS: 361/907 (39.8%) died in hospital or within 30 days of discharge. The presence of diabetes and hypertension together appears to confer the greatest mortality risk (OR 2.75; 95% CI 1.80 to 4.21; p<0.001) compared with either condition alone. Age >65 years (OR 3.32; 95% CI 2.15 to 5.11), male sex (OR 2.04; 95% CI 1.47 to 2.82), hypertension (OR 1.69; 95% CI 1.10 to 2.61) and cerebrovascular disease (OR 1.87; 95% CI 1.31 to 2.68) were independently associated with increased risk of death. The mortality risk did not differ between the quintiles of deprivation. High-sensitivity troponin I was the best predictor of mortality among biomarkers (OR 4.43; 95% CI 3.10 to 7.10). Angiotensin-receptor blockers (OR 0.57; 95% CI 0.33 to 0.96) and ACE inhibitors (OR 0.65; 95% CI 0.43 to 0.97) were not associated with adverse outcome. The Charlson Index of Comorbidity scores were significantly higher in non-survivors. CONCLUSIONS: The combined prevalence of hypertension and diabetes appears to confer the greatest risk, where diabetes may have a modulating effect. Hypertension and cerebrovascular disease had a significant impact on inpatient mortality. Social deprivation and ethnicity did not have any effect once the patient was in hospital.


Subject(s)
COVID-19 , Hypertension , Aged , Comorbidity , Hospital Mortality , Hospitalization , Humans , Hypertension/epidemiology , Inpatients , Male , Retrospective Studies , Risk Factors , SARS-CoV-2 , United Kingdom/epidemiology
20.
Public Health Rep ; 136(5): 554-561, 2021.
Article in English | MEDLINE | ID: covidwho-1277841

ABSTRACT

OBJECTIVES: Federal open-data initiatives that promote increased sharing of federally collected data are important for transparency, data quality, trust, and relationships with the public and state, tribal, local, and territorial partners. These initiatives advance understanding of health conditions and diseases by providing data to researchers, scientists, and policymakers for analysis, collaboration, and use outside the Centers for Disease Control and Prevention (CDC), particularly for emerging conditions such as COVID-19, for which data needs are constantly evolving. Since the beginning of the pandemic, CDC has collected person-level, de-identified data from jurisdictions and currently has more than 8 million records. We describe how CDC designed and produces 2 de-identified public datasets from these collected data. METHODS: We included data elements based on usefulness, public request, and privacy implications; we suppressed some field values to reduce the risk of re-identification and exposure of confidential information. We created datasets and verified them for privacy and confidentiality by using data management platform analytic tools and R scripts. RESULTS: Unrestricted data are available to the public through Data.CDC.gov, and restricted data, with additional fields, are available with a data-use agreement through a private repository on GitHub.com. PRACTICE IMPLICATIONS: Enriched understanding of the available public data, the methods used to create these data, and the algorithms used to protect the privacy of de-identified people allow for improved data use. Automating data-generation procedures improves the volume and timeliness of sharing data.


Subject(s)
COVID-19/epidemiology , Centers for Disease Control and Prevention, U.S./organization & administration , Confidentiality/standards , Data Anonymization/standards , Centers for Disease Control and Prevention, U.S./standards , Humans , Pandemics , SARS-CoV-2 , United States/epidemiology
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