bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neuroinflammation, Depressive Affect, and Amyloid Burden in Alzheimer’s Disease: Insights from the Kynurenine Pathway
Authors: Willette Auriel A. , Pappas Colleen , Hoth Nathan , Wang Qian , Klinedinst Brandon , Willette Sara A. , Larsen Brittany , Pollpeter Amy , Li Tianqi , Le Scott , Mochel Jonathan P. , Allenspach Karin , Dantzer Robert ,   and for the Alzheimer’s disease Neuroimaging Initiative
Published: August 2020

AbstractBackgroundDepressive symptoms in Alzheimer’s disease (AD) predict worse cognitive and functional outcomes. Both AD and major depression are characterized by shunted tryptophan metabolism away from serotonin (5-HT) and toward the neuroinflammatory kynurenine (Kyn) pathway. The present study assessed the role of Kyn across the AD continuum in behavioral, neuroanatomical, neuropathological, and physiological outcomes.MethodsIn 746 participants from the Alzheimer’s Disease Neuroimaging Initiative-1 (ADNI1) cohort, serum markers of 5-HT, tryptophan, and Kyn were measured and their relationships investigated with immunologic markers, affect and functional outcomes, CSF markers of beta-amyloid (Aβ) and tau, and regional gray matter.ResultsA higher Kyn/Tryptophan ratio was linked to many inflammatory markers, as well as lower functional independence and memory scores. A higher Kyn/5-HT ratio showed similar associations, but also strong relationships with depressive affect and neuropsychiatric disturbance, executive dysfunction, and global cognitive decline. Further, gray matter atrophy was seen in hippocampus, anterior cingulate, and prefrontal cortices, as wel as greater amyloid and total tau deposition. Finally, using moderated-mediation, several pro-inflammatory factors partially mediated Kyn/5-HT and depressive affect scores in participants with subclinical Aβ (i.e., Aβ-), whereas such associations were fully mediated by Complement 3 in Aβ+ participants.ConclusionsThese findings suggest that neuroinflammatory signaling cascades may occur during AD, resulting in increased Kyn metabolism that influences the pathogenesis of depressive symptoms. Aβ and the complement system may be critical contributing factors in this process.
Quantitative analysis of SARS-CoV-2 RNA from wastewater solids in communities with low COVID-19 incidence and prevalence
Authors: D’Aoust Patrick M. , Mercier Élisabeth , Montpetit Danika , Jia Jian-Jun , Alexandrov Ilya , Neault Nafisa , Baig Aiman Tariq , Mayne Janice , Zhang Xu , Alain Tommy , Servos Mark R. , MacKenzie Malcolm , Figeys Daniel , MacKenzie Alex E. , Graber Tyson E. , Delatolla Robert 
Published: August 2020

AbstractIn the absence of an effective vaccine to prevent COVID-19 it is important to be able to track community infections to inform public health interventions aimed at reducing the spread and therefore reduce pressures on health-care units, improve health outcomes and reduce economic uncertainty. Wastewater surveillance has rapidly emerged as a potential tool to effectively monitor community infections for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), through measuring trends of viral RNA signal in wastewater systems. In this study SARS-CoV-2 viral RNA N1 and N2 genes are quantified in solids collected from influent post grit solids (PGS) and primary clarified sludge (PCS) in two water resource recovery facilities (WRRF) serving Canada’s national capital region, i.e., the City of Ottawa, ON (pop. ≈ 1.1M) and the City of Gatineau, QC (pop. ≈ 280K). PCS samples show signal inhibition using RT-ddPCR compared to RT-qPCR, with PGS samples showing similar quantifiable concentrations of RNA using both assays. RT-qPCR shows higher frequency of detection of N1 and N2 genes in PCS (92.7, 90.6%) as compared to PGS samples (79.2, 82.3%). Sampling of PCS may therefore be an effective approach for SARS-CoV-2 viral quantification, especially during periods of declining and low COVID-19 incidence in the community. The pepper mild mottle virus (PMMV) is determined to have a less variable RNA signal in PCS over a three month period for two WRRFs, regardless of environmental conditions, compared to Bacteroides 16S rRNA or human eukaryotic 18S rRNA, making PMMV a potentially useful biomarker for normalization of SARS-CoV-2 signal. PMMV-normalized PCS RNA signal from WRRFs of two cities correlated with the regional public health epidemiological metrics, identifying PCS normalized to a fecal indicator (PMMV) as a potentially effective tool for monitoring trends during decreasing and low-incidence of infection of SARS-Cov-2 in communities.
Development and Validation of a Simple Risk Score for Diagnosing COVID-19 in the Emergency Room
Authors: Sung Joowhan , Choudry Naveed , Bachour Rima 
Published: August 2020

AbstractAs the COVID-19 pandemic continues to escalate and place pressure on hospital system resources, a proper screening and risk stratification score is essential. We aimed to develop a risk score to identify patients with increased risk of COVID-19, allowing proper identification and allocation of limited resources. A retrospective study was conducted of 338 patients who were admitted to the hospital from the emergency room and tested for COVID-19 at an acute care hospital in the Metropolitan Washington D.C. area. The dataset was split into development and validation sets with a ratio of 6:4. Demographics, presenting symptoms, sick contact, triage vital signs, initial laboratory and chest X-ray results were analyzed to develop a prediction model for COVID-19 diagnosis. Multivariable logistic regression was performed in a stepwise fashion to develop a prediction model, and a scoring system was created based on the coefficients of the final model. Among 338 patients admitted to the hospital from the emergency room, 136 (40.2%) patients tested positive for COVID-19 and 202 (59.8%) patients tested negative. Nursing facility residence (2 points), sick contact (2 points), constitutional symptom (1 point), respiratory symptom (1 point), gastrointestinal symptom (1 point), obesity (1 point), hypoxia at triage (1 point), and leukocytosis (−1 point) were included in the prediction score. A risk score for COVID-19 diagnosis achieved AUROC of 0.87 (95% CI 0.83-0.92) in the development dataset and 0.83 (95% CI 0.76-0.90) in the validation dataset. A risk prediction score for COVID-19 can be used as a supplemental tool to assist clinical decision to triage, test, and quarantine patients admitted to the hospital from the emergency room.
Displaying emergency patient estimated wait times: a multi-centre, qualitative study of patient, community, paramedic and health administrator perspectives
Authors: Walker Katie , Stephenson Melanie , Hutton Jennie , Loupis Anne , Joe Keith , Ben-Meir Michael , Martini Ella , Stephenson Michael , Lowthian Judy , Yip Beatrice , Wu Elena , Ho James , Blecher Gabriel , Hansen Kim , Buntine Paul 
Published: August 2020

AbstractBackgroundEmergency Departments have the potential ability to predict patient wait times and to display this to patients and other stakeholders. Little is known about whether consumers and stakeholders would want this information and how wait time predictions might be used. The aim of this study was to gain perspectives from consumer, referrer and health services personnel regarding the concept of emergency wait time visibility.MethodsIn 2019, 103 semi-structured interviews and one focus group were conducted with emergency medicine patients/families, paramedics, well community members and hospital/paramedic administrators. Nine emergency departments and multiple organisations in Victoria, Australia, contributed data. Transcripts were coded and themes are presented.ResultsConsumers and paramedics face physical and psychological difficulties when wait times aren’t visible. Consumers believe about a 2-hour wait is tolerable, beyond this most begin to consider alternative strategies for seeking care. Consumers want to see triage to doctor times; paramedics want door to off-stretcher times (for all possible transport destinations); with 47/50 consumers and 30/31 paramedics potentially using this information. Twenty-eight of 50 consumers would use times to inform facility or provider choice, 19/50 want information once in the waiting room. During prolonged waits, 1/52 consumers would consider not seeking care. Visibility of approximate waits would better inform decision-making, improve load-spreading, allow planning and access to basic needs and might reduce anxiety.ConclusionsConsumers and paramedics want wait time information visibility. They would use the information in a variety of ways, both pre-hospital and whilst waiting for care.
Extensive Genetic Diversity and Host Range of Rodent-borne Coronaviruses
Authors: Wang Wen , Lin Xian-Dan , Zhang Hai-Lin , Wang Miao-Ruo , Guan Xiao-Qing , Holmes Edward C. , Zhang Yong-Zhen 
Published: August 2020

AbstractTo better understand the genetic diversity, host association and evolution of coronaviruses (CoVs) in China we analyzed a total of 696 rodents encompassing 16 different species sampled from Zhejiang and Yunnan provinces. Based on the reverse transcriptase PCR-based CoV screening CoVs of fecal samples and subsequent sequence analysis of the RdRp gene, we identified CoVs in diverse rodent species, comprisingApodemus agrarius, Apodemus latronum, Bandicota indica, Eothenomys miletus, E. eleusis, Rattus andamanesis, Rattus norvegicus, andR. tanezumi. Apodemus chevrieriwas a particularly rich host, harboring 25 rodent CoVs. Genetic and phylogenetic analysis revealed the presence of three groups of CoVs carried by a range of rodents that were closely related to the Lucheng Rn rat coronavirus (LRNV), China Rattus coronavirus HKU24 (ChRCoV_HKU24) and Longquan Rl rat coronavirus (LRLV) identified previously. One newly identifiedA. chevrieri-associated virus closely related to LRNV lacked an NS2 gene. This virus had a similar genetic organization to AcCoV-JC34, recently discovered in the same rodent species in Yunnan, suggesting that it represents a new viral subtype. Notably, additional variants of LRNV were identified that contained putative nonstructural NS2b genes located downstream of the NS2 gene that were likely derived from the host genome. Recombination events were also identified in the ORF1a gene of Lijiang-71. In sum, these data reveal the substantial genetic diversity and genomic complexity of rodent-borne CoVs, and greatly extend our knowledge of these major wildlife virus reservoirs.
Obesity, old age and frailty are the true risk factors for COVID-19 mortality and not chronic disease or ethnicity in Croydon
Authors: Philipose Zinu , Smati Nadia , Wong Chun Shing Jefferson , Aspey Karen , Mendall Michael 
Published: August 2020

AbstractBackgroundCoronavirus-19 (COVID-19) mortality in hospitalised patients is strongly associated with old age, nursing home residence, male sex and obesity, with a more controversial association with ethnicity and chronic diseases, in particular diabetes mellitus. Further complicating the evaluation of the independent impacts of these risk factors is the failure to control for frailty in the published studies thus far.AimTo determine the true risk factors for mortality in patients confirmed to have COVID-19 in Croydon needing hospital admission and to evaluate the independence of these risk factors in this group after adjusting for body mass index (BMI) and frailty.MethodsThis observational study retrospectively reviewed hospital electronic medical records of 466 consecutive patients who were admitted to Croydon University Hospital confirmed positive by rapid PCR test from 11th March 2020 to 9th April 2020. Statistical analysis was performed by multiple unconditional and univariate logistic regression.ResultsAfter multivariate analysis, male sex [OR 1.44 (CI 0.92-2.40)], age (per year) [OR 1.07 (CI 1.05-1.09)], morbid obesity (BMI > 40 kg/m2 vs reference BMI 18.5-24.9 kg/m2) [OR 14.8 (CI 5.25-41.8)], and nursing home residence (OR 3.01 (CI 1.56-5.79) were independently associated with COVID-19 mortality with no statistically significant association found with chronic diseases or ethnicity. In the non-nursing home population, after adjusting for age and sex, the odds ratio for type 2 diabetes mellitus (T2DM) as a risk factor was 1.64 (CI 1.03-2.61, p = 0.03) and was and was attenuated to 1.30 (CI 0.78-2.18)) after controlling for BMI; the association of mortality with male sex was strengthened [OR 1.66 (CI 0.96-2.87)] and that for ethnic minority patients was weakened [South Asians [from OR 1.30 (CI 0.67-2.53)) to OR 1.21 (CI 0.60-2.46)]; African Caribbeans [from OR 1.24 (CI 0.65-2.34) to OR 1.16 (CI 0.58-2.30)]. There was a borderline but potentially large protective effect (p= 0.09) in patients who were on anticoagulation drugs prior to admission [OR 0.56 (CI 0.28-1.11)].ConclusionOur study found no significant effect of ethnicity and chronic diseases as independent risk factors on COVID-19 mortality in Croydon population whereas male sex, high BMI, old age and frailty were found to be independent risk factors. Routine prophylactic treatment with anticoagulant drugs in the high-risk COVID-19 population warrants further prompt investigation.
Place and underlying cause of death during the COVID19 pandemic: retrospective cohort study of 3.5 million deaths in England and Wales, 2014 to 2020
Authors: Wu Jianhua , Malfam Marion , Mamas Mamas , Rashid Muhammad , Kontopantelis Evangelos , Deanfield John E , de Belder Mark A , Gale Chris P 
Published: August 2020

AbstractBackgroundThe COVID-19 pandemic has resulted in a high death toll. We aimed to describe the place and cause of death during the COVID-19 pandemic.MethodsThis national death registry included all adult (aged ≥18 years) deaths in England and Wales between 1st January 2014 and 30th June 2020. Analyses were based upon ICD-10 codes corresponding to the underlying cause of death as stated on the Medical Certificate of Cause of Death. Daily deaths during COVID-19 pandemic were compared against the expected daily deaths estimated using Farrington surveillance algorithm for daily historical data between 2014 and 2020, by place and cause of death.FindingsBetween 2nd March and 30th June 2020, there was an excess mortality of 57,860 (a proportional increase of 35%) compared with the expected deaths, of which 50,603 (86.2%) were COVID-19 related. Almost half the excess deaths occurred in care homes (25,611 deaths) where deaths were 55% higher than expected. One fifth of the excess deaths occurred in hospital (15,938 deaths; a proportional increase of 21%) with the remainder occurring at home (16,190 deaths; a proportional increase of 39%). At home, only 14% of 16,190 excess deaths were related to COVID-19, with 5,963 deaths due to cancer and 2,485 deaths due to cardiac disease, very few of which involved COVID-19. In care homes or hospices, 61% of the 25,611 excess deaths were related to COVID-19, 5,539 of which were due to respiratory disease and most of these (4,315 deaths) involved COVID-19. In hospital, there were 16,174 fewer deaths than expected which did not involve COVID-19, and there were 4,088 fewer deaths due to cancer and 1,398 fewer deaths due to cardiac disease than expected.InterpretationThe COVID-19 pandemic has resulted in a substantial increase in the absolute numbers of deaths occurring at home and care homes. There was a huge burden of excess deaths occurring in care homes, which were poorly characterised, and were likely to be, at least in part, the result of undiagnosed COVID-19. There was a smaller but important and ongoing excess in deaths at home, particularly from cancer and cardiac disease, which suggests avoidance of hospital care for non-COVID-19 conditions.FundingThe study is unfunded.
Immediate Effects of COVID-19 Outbreak on Psychiatric Outpatients: Posttraumatic Stress and Influencing Factors
Authors: Poyraz Burç Çağrı , Poyraz Cana Aksoy , Turan Şenol , Demirel Ömer Faruk , Kavla Yasin , Bulu Ersel , Hacısalihoğlu İrem , Ersungur Elif Burcu 
Published: August 2020

AbstractWe aimed to investigate the effects of COVID-19 outbreak and public health measures on the psychological well-being of patients with psychiatric disorders. This cross-sectional study assessed 436 outpatients recruited from a tertiary psychiatry clinic in Istanbul, Turkey, nearly one month after the government introduced strict measures of lockdown against the ongoing outbreak. Respondents completed a web-based survey on sociodemographic data, subjective sleep quality, and a range of psychiatric symptoms using the Impact of Events Scale-Revised (IES-R), and Hospital Anxiety and Depression Scale (HADS). Respondents reported high frequencies of clinically significant posttraumatic stress disorder (PTSD) (32.6%, IES-R score ≥ 33), anxiety (36.4%, HADS anxiety score > 10), and depression (51%, HADS depression score > 10). 20.5% of respondents described that their psychological status worsened during the COVID-19 outbreak, and 12.1% of respondents described poor or very poor sleep in the prior month. Positive predictors of increased PTSD symptoms included the chronic medical diseases, knowing someone in the social vicinity diagnosed with the COVID-19 infection, job loss or being on temporary leave after the outbreak, and increased exposure time to TV or social media. In contrast, male gender, older age, higher educational attainment, and the psychiatric diagnoses of schizophrenia and (to a lesser degree) bipolar disorder were the negative predictors. Our results suggest that patients with psychiatric disorders are prone to substantial psychological distress during the COVID-19 outbreak, and various individual, behavioral, and social factors mediate this effect.
Strengthening Policy Coding Methodologies to Improve COVID-19 Disease Modeling and Policy Responses: A Proposed Coding Framework and Recommendations
Authors: Lane Jeff , Garrison Michelle M. , Kelley James , Sarma Priya , Katz Aaron 
Published: August 2020

AbstractIn recent months, multiple efforts have sought to characterize COVID-19 social distancing policy responses. These efforts have used various coding frameworks, but most have relied on binary coding that may not adequately describe the gradient in social distancing policies as states “re-open.” We developed a COVID-19 social distancing intensity framework that is sufficiently specific and sensitive to capture this gradient. Based on a review of policies from a 12-state sample, we developed a social distancing intensity framework consisting of 16 domains and intensity scales of 0-5 for each domain. We found that the states with the highest average daily intensity from our sample were Pennsylvania, Washington, Colorado, California, and New Jersey, with Georgia, Florida, Massachusetts, and Texas having the lowest. While some domains (such as restaurants and movie theaters) showed bimodal policy intensity distributions compatible with binary (yes/no) coding, others (such as childcare and religious gatherings) showed broader variability that would be missed without more granular coding. We also present a range of methodological recommendations to strengthen COVID-19 comparative policy coding efforts.
Comparative Evaluation of SARS-CoV-2 IgG Assays in India
Authors:   DBT India Consortium for Covid-19 Research, Shinjini Bhatnagar 
Published: August 2020

AbstractIgG immunoassays have been developed and used widely for clinical samples and serosurveys for SARS-CoV-2. We compared the performance of three immunoassays, an in-house RBD assay, and two commercial assays, the Diasorin LIAISON SARS-CoV-2 IgG CLIA which detects antibodies against S1/S2 domains of the Spike protein and the Zydus Kavach assay based on inactivated virus using a well-characterized sera-panel. 379 sera/plasma samples from RT-PCR positive individuals >20 days of illness in symptomatic or RT-PCR positivity in asymptomatic individuals and 184 pre-pandemic samples were used. The sensitivity of the assays were 84.7, 82.6 and 75.7 respectively for RBD, LIAISON and Kavach. Kavach and the in-house RBD ELISA showed a specificity of 99.5% and 100%, respectively. The RBD and LIAISON (S1/S2) assays showed high agreement (94.7%;95%CI:92.0,96.6) and were able to correctly identify more positives than Kavach. All three assays are suitable for serosurveillance studies, but in low prevalence sites, estimation of exposure may require adjustment based on our findings.
The genetic variation landscape of African swine fever virus reveals frequent positive selection and adaptive flexibility
Authors: Bao Yun-Juan , Qiu Junhui , Luo Yuzi , Rodríguez Fernando , Qiu Hua-Ji 
Published: August 2020

AbstractAfrican swine fever virus (ASFV) is a lethal disease agent that causes high mortality in swine population and devastating loss in swine industries. The development of efficacious vaccines has been hindered by the gap in knowledge concerning genetic variation of ASFV and the genetic factors involved in host adaptation and virus-host interactions. In this study, we performed a meta-genetic study of ASFV aiming to profile the variation landscape and identify genetic factors with signatures of positive selection and relevance to host adaptation. Our data reveals a high level of genetic variability of ASFV shaped by both diversifying selection and selective sweep. The selection signatures are widely distributed across the genome with the diversifying selection falling within 29 genes and selection sweep within 25 genes, highlighting strong signals of adaptive evolution of ASFV. Further examination of the sequence properties reveals the link of the selection signatures with virus-host interactions and adaptive flexibility. Specifically, we discovered a site at 157th of the key antigen protein EP402R under diversifying selection, which is located in the cytotoxic T-cell epitope related with the low level of cross-reaction in T-cell response. Importantly, two multigene families MGF360 and MGF505, the host range factors of ASFV, exhibit divergent selection among the paralogous members, conferring sequence pools for genetic diversification and adaptive capability. By integrating the genes with selection signatures into a unified framework of interactions between ASFV and hosts, we showed that the genes are involved in multiple processes of host immune interaction and virus life cycles, and may play crucial roles in circumventing host defense systems and enhancing adaptive fitness. Our findings will allow enhanced understanding of genetic basis of rapid spreading and adaptation of ASFV among the hosts.
Precise Prediction of COVID-19 in Chest X-Ray Images Using KE Sieve Algorithm
Authors: Thejeshwar S Sai , Chokkareddy Chaitanya , Eswaran K 
Published: August 2020

AbstractThe novel coronavirus (COVID-19) pandemic is pressurizing the healthcare systems across the globe and few of them are on the verge of failing. The detection of this virus as early as possible will help in contaminating the spread of it as the virus is mutating itself as fast as possible and currently there are about 4,300 strains of the virus according to the reports. Clinical studies have shown that most of the COVID-19 patients suffer from a lung infection similar to influenza. So, it is possible to diagnose lung infection using imaging techniques. Although a chest computed tomography (CT) scan has been shown to be an effective imaging technique for lung-related disease diagnosis, chest X-ray is more widely available across the hospitals due to its considerably lower cost and faster imaging time than CT scan. The advancements in the area of machine learning and pattern recognition has resulted in intelligent systems that analyze CT Scans or X-ray images and classify between pneumonia and normal patients. This paper proposes KE Sieve Neural Network architecture, which helps in the rapid diagnosis of COVID-19 using chest X-ray images. This architecture is achieving an accuracy of 98.49%. This noninvasive prediction method can assist the doctors in this pandemic and reduce the stress on health care systems.