bluuebunny/crossref_metadata_2025_split huggingface dataset:
Throat wash as a source of SARS-CoV-2 RNA to monitor community spread of COVID-19
Authors: Lopez-Lopes Giselle Ibette , Ahagon Cintia , Benega Margarete Aparecida , Silva Daniela Bernardes Borges da , Silva Valéria Oliveira , Corrêa de Oliveira Santos Katia , Prado Lincoln Spinazola do , Santos Fabiana Pereira dos , Cilli Audrey , Saraceni Claudia , da Cruz Núria Borges , Afonso Ana Maria Sardinha , Timenetsky Maria do Carmo , de Macedo Brígido Luís Fernando ,   the IAL-COVID working group
Published: August 2020

AbstractBackgroundSARS-CoV-2 RNA detection with real time PCR is currently the central diagnostic tool to determine ongoing active infection. Nasopharyngeal and oral swabs are the main collection tool of biological material used as the source of viral RNA outside a hospital setting. However, limitation in swabs availability, trained health professional with proper PPE and potential risk of aerosols may hinder COVID diagnosis. Self-collection with swabs, saliva and throat wash to obtain oropharyngeal wash has been suggested as having comparable performance of regular swab. We performed throat wash (TW) based surveillance with laboratory heath workers and other employees (LHW) at a laboratory research institute.MethodsConsecutive volunteer testing of LWH and external household and close contacts were included. TW self-collection was performed in 5 mL of sterile saline that was returned to original vial after approximate 5 secs of gargle. RNA extraction and rtPCR were performed as part of routine COVID protocols using Allplex (Seegene, Korea).ResultsFour hundred and twenty two volunteers, 387 (93%) LHW and 43 (7%) contacts participated in the survey. One or more positive COVID rtPCR was documented in 63 (14.9% CI95 12%-19%) individuals. No correlation was observed between with direct activities with COVID samples to positivity, with infection observed in comparable rates among different laboratory areas, administrative or supportive activities. Among 63 with detected SARS-CoV-2 RNA, 59 with clinical information, 58% reported symptoms at a median of 4 days prior to collection, most with mild disease. Over a third (38%) of asymptomatic cases developed symptoms 1-3 days after collection. Although overall CT values of TW were higher than that of contemporary swab tests from hospitalized cases, TW from symptomatic cases had comparable CTs.ConclusionsThe study suggests that TW may be a valid alternative to the detection of SARS-CoV-2 RNA. The proportion of asymptomatic and pre-symptomatic cases is elevated and reinforces the need of universal precautions and frequent surveys to limit the spread of the disease.
Long-term patient-reported symptoms of COVID-19: an analysis of social media data
Authors: Banda Juan M. , Singh Gurdas Viguruji , Alser Osaid H. , Prieto-Alhambra Daniel 
Published: August 2020

AbstractAs the COVID-19 virus continues to infect people across the globe, there is little understanding of the long term implications for recovered patients. There have been reports of persistent symptoms after confirmed infections on patients even after three months of initial recovery. While some of these patients have documented follow-ups on clinical records, or participate in longitudinal surveys, these datasets are usually not publicly available or standardized to perform longitudinal analyses on them. Therefore, there is a need to use additional data sources for continued follow-up and identification of latent symptoms that might be underreported in other places. In this work we present a preliminary characterization of post-COVID-19 symptoms using social media data from Twitter. We use a combination of natural language processing and clinician reviews to identify long term self-reported symptoms on a set of Twitter users.
Prevalence of Iron, Vitamin B12 deficiency and inflammatory anaemia in treatment naive individual consecutive cancer patients: A cross sectional study
Authors: Pandey A , Singh S , Aryan R , Murari K 
Published: August 2020

BackgroundIn treatment naive Indian cancer patients, prevalence of iron, B12 deficiency and inflammatory anaemia in poorly known.Aims and ObjectivesTo evaluate prevalence of anaemia and iron, B12 deficiency along with inflammation in treatment naive individual consecutive cancer patients.Material and MethodsAll patients registered from 1st July 2019 till 31st December 2019 in Medical Oncology Outpatient Department were offered to undergo Iron profile, Serum B12 levels and Serum ferritin along with routine haematological investigations. Anaemia was defined as Haemoglobin < 11gm/dL. Transferrin saturation <20%, Serum Ferritin >300 microgram/litre and Vitamin B12 level <200 picogram/millilitre were ‘cut-offs’ used to define iron deficiency, inflammation and Vitamin B12 deficiency respectively. Data was analysed using descriptive statistics, frequency distribution, crosstabs and Bar Diagram in SPSS version 17.0. Pearsons Chi square test and Odds ratio was used to measure the strength of association with variables.Results311/441 (70.5%) were found eligible. Median age was 52 ± 15.9 (Range 18-84) years with 144/331(46%) females. The prevalence of anaemia was 61% ± 2.7 (95% CI 55-66%). Mean Haemoglobin was 9.86 ± 2.08 (range 3-16) gram/decilitre. 21/311(7%) had severe anaemia (Haemoglobin < 6.9 gm/dl). 135/311 (71%), 61/189 (32%) and 89/189 (47%) anaemic patients had iron deficiency, inflammation and B12 deficiency respectively. More than 70% of Gastrointestinal (50/69), Gynaecological(17/24) and Lung Cancer(18/22) patients had underling Iron deficiency.ConclusionTwo-third of cancer patients are iron deficient. B12 deficiency and inflammation are present in half and one-third patients respectively.
KL-VS heterozygosity is associated with reduced tau accumulation and lower memory impairment in Alzheimer’s disease
Authors: Neitzel Julia , Franzmeier Nicolai , Rubinski Anna , Dichgans Martin , Brendel Matthias , Malik Rainer , Ewers Michael ,   for the Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Published: August 2020

ABSTRACTKlotho-VS heterozygosity (KL-VShet) is associated with reduced risk of Alzheimer’s disease (AD). However, whether KL-VShet is associated with lower levels of pathologic tau, i.e. the key AD pathology driving neurodegeneration and cognitive decline, is unknown. Here, we assessed the interaction between KL-VShet and levels of beta-amyloid, a key driver of tau pathology, on the levels of PET-assessed neurofibrillary tau in 354 controls and patients within the AD continuum. KL-VShet showed lower cross-sectional increase in tau-PET per unit increase in amyloid-PET when compared to that of non-carriers. This effect of KL-VShet on tau-PET showed a tendency to be stronger in Klotho mRNA-expressing brain regions mapped onto a gene expression atlas. KL-VShet was related to better memory functions and this association was mediated by lower tau-PET. Amyloid-PET levels did not differ between KL-VShet carriers versus non-carriers. Together, our findings provide evidence for a protective role of KL-VShet against tau pathology and tau-related memory impairments in elderly humans at risk of AD dementia.
Household transmission of SARS-CoV-2: a systematic review and meta-analysis of secondary attack rate
Authors: Madewell Zachary J. , Yang Yang , Longini Ira M. , Halloran M. Elizabeth , Dean Natalie E. 
Published: August 2020

SummaryBackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spread by direct, indirect, or close contact with infected people via infected respiratory droplets or saliva. Crowded indoor environments with sustained close contact and conversations are a particularly high-risk setting.MethodsWe performed a meta-analysis through July 29, 2020 of SARS-CoV-2 household secondary attack rate (SAR), disaggregating by several covariates (contact type, symptom status, adult/child contacts, contact sex, relationship to index case, index case sex, number of contacts in household, coronavirus).FindingsWe identified 40 relevant published studies that report household secondary transmission. The estimated overall household SAR was 18·8% (95% confidence interval [CI]: 15·4%–22·2%), which is higher than previously observed SARs for SARS-CoV and MERS-CoV. We observed that household SARs were significantly higher from symptomatic index cases than asymptomatic index cases, to adult contacts than children contacts, to spouses than other family contacts, and in households with one contact than households with three or more contacts.InterpretationTo prevent the spread of SARS-CoV-2, people are being asked to stay at home worldwide. With suspected or confirmed infections referred to isolate at home, household transmission will continue to be a significant source of transmission.
Manuscript title: Loss in the expansion of SARS-CoV-2 specific immunity is a key risk factor in fatal patients with COVID-19
Authors: Zeng Qiang , Huang Gang , Li Yong-zhe , Xu Guoqiang , Dong Sheng-yong , Zhong Tian-yu , Chen Zong-tao , Xu Yang 
Published: August 2020

ABSTRACTKnowledge of the dynamic immunological characteristics of patients with coronavirus disease 2019 (COVID-19) is essential for clinicians to understand the progression of the disease. Our data showed that the immune system and function gradually remodeled and declined with age, starting from age 16 until age 91 in 25,239 healthy controls. An analysis of the relationship between the number of lymphocytes and age revealed that the lymphocyte and subset counts tended to decline with age significantly. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific immunity declined with age and was associated with survival time in fatal cases. Loss in the expansion of SARS-CoV-2-specific immunity could be expanded in vitro. The concurrent decline in SARS-CoV-2-specific cellular and humoral immunities and prolonged SARS-CoV-2 exposure predicted fatal outcomes. Our findings provide a basis for further analysis of SARS-CoV-2-specific immunity and understanding of the pathogenesis of fatal COVID-19 cases.HighlightsThe immune system and function gradually remodeled and declined with age.SARS-CoV-2-specific immunity declined with age in fatal cases.SARS-CoV-2-specific immunity was associated with survival time in fatal cases.Loss in the expansion of SARS-CoV-2-specific immunity could be expanded in vitro.A concurrent decline in SARS-CoV-2-specific cellular and humoral immunities and prolonged SARS-CoV-2 exposure predicted fatal outcomes.
COVID-19 Recurrent Varies with Different Combinatorial Medical Treatments Determined by Machine Learning Approaches
Authors: Huang Jia , Zhai Song , Ye Fangfan , Wang Song , Zeng Manfei , Way George , Madahar Vipul , Zhu Tengfei , Qiu Liping , Xu Zehui , Ye Manhua , Liu Lei , Cui Xinping , Liao Jiayu 
Published: August 2020

AbstractVarious medical treatments for COVID-19 are attempted. After patients are discharged, SARS-CoV-2 recurring cases are reported and the recurrence could profoundly impact patient healthcare and social economics. To date, no data on the effects of medical treatments on recurrence has been published. We analyzed the treatment data of combinations of ten different drugs for the recurring cases in a single medical center, Shenzhen, China. A total of 417 patients were considered and 414 of them were included in this study (3 deaths) with mild-to-critical COVID-19. Patients were treated by 10 different drug combinations and followed up for recurrence for 28 days quarantine after being discharged from the medical center between February and May, 2020. We applied the Synthetic Minority Oversampling Technique (SMOTE) to overcome the rare recurring events in certain age groups and performed Virtual Twins (VT) analysis facilitated by random forest regression for medical treatment-recurrence classification. Among those drug combinations, Methylprednisolone/Interferon/Lopinavir/Ritonavir/Arbidol led to the lowest recurring rate (0.133) as compared to the average recurring rate (0.203). For the younger group (age 20-27) or the older group (age 60-70), the optimal drug combinations are different, but the above combination is still the second best. For obese patients, the combination of Ribavirin/Interferon/Lopinavir/Ritonavir/Arbidol led to the lowest recurring rate for age group of 20-50, whereas the combination of Interferon/Lopinavir/Ritonavir/Arbidol led to lowest recurring rate for age group of 50-70. The insights into combinatorial therapy we provided here shed lights on the use of a combination of (biological and chemical) anti-virus therapy and/or anti-cytokine storm as a potentially effective therapeutic treatment for COVID-19.
Analysis of the correlation between anti-MDA5 antibody and the severity of COVID-19: a retrospective study
Authors: Liu Changzheng , Wang Qian , Wang Yeming , Wang Geng , Wang Linghang , Chen Hong , Jiao Tao , Hu Chaojun , Lei Xiaobo , Guo Li , Ren Lili , Li Mengtao , Zeng Xiaofeng , Zhang Dingyu , Cao Bin , Wang Jianwei 
Published: August 2020

AbstractOBJECTIVETo identify the anti-melanoma differentiation-associated gene 5 (MDA5) antibody (Ab) in coronavirus disease 2019 (COVID-19) and its relationship with the severity and clinical outcomes of COVID-19.DESIGNRetrospective cohort study.SETTINGThree hospitals in China.PARTICIPANTS274 adult inpatients diagnosed with COVID-19 according to the Protocol for Prevention and Control of COVID-19 (Edition 7) of China and confirmed by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) RNA testing, were included from three hospitals from Wuhan, Harbin and Beijing, China from 1 December 2019 to 19 April 2020. The Biobank of Myositis Registry Department of Rheumatology, Peking Union Medical College Hospital, provided the plasma of five patients with anti-MDA5 Ab-related dermatomyositis as positive control group. Demographic, clinical and laboratory data were collected from medical records. The anti-MDA5 Ab was determined by an ELISA assay and was verified by immunoblotting analysis.MAIN OUTCOME MEASURESIn hospital death of all cause.RESULTSThe positive rate of anti-MDA5 Ab in patients with COVID-19 was 48.2% (132/274) and the anti-MDA5 Ab positive patients tended to represent with severe disease (88.6% vs 66.9%, P<0.0001). The titer of anti-MDA5 Ab was significantly elevated in the non-survivals (5.95±5.16 vs 8.22±6.64, P=0.030) and the positive rate was also higher than that in the survivals (23.5% vs 12.0%, P=0.012). Regarding to severe COVID-19 patients, we found that high titer of anti-MDA5 Ab (≥10.0 U/mL) was more prevalent in the non-survivals (31.2% vs 14.0%, P=0.006). Moreover, early profiling of anti-MDA5 Ab could distinguish severe patients from those with non-severe ones.CONCLUSIONAnti-MDA5 Ab was prevalent in the COVID-19 patients and high titer of this antibody is correlated with severe disease and unfavorable outcomes. Early screening and serially monitoring of anti-MDA5 Ab titer have the potential to predict the disease progression of COVID-19.
Comparative experimental evidence on compliance with social distancing during the COVID-19 pandemic
Authors: Becher Michael , Stegmueller Daniel , Brouard Sylvain , Kerrouche Eric 
Published: August 2020

AbstractSocial distancing is a central public health measure in the fight against the COVID-19 pandemic, but individuals’ compliance cannot be taken for granted. We use a survey experiment to examine the prevalence of non-compliance with social distancing in nine countries and test pre-registered hypotheses about individual-level characteristics associated with less social distancing. Leveraging a list experiment to control for social desirability bias, we find large cross-national variation in adherence to social distancing guidelines. Compliance varies systematically with COVID-19 fatalities and the strictness of lockdown measures. We also find substantial heterogeneity in the role of individual-level predictors. While there is an ideological gap in social distancing in the US and New Zealand, this is not the case in European countries. Taken together, our results suggest caution when trying to model pandemic health policies on other countries’ experiences. Behavioral interventions targeted towards specific demographics that work in one context might fail in another.
Whether the Weather Will Help Us Weather the COVID-19 Pandemic: Using Machine Learning to Measure Twitter Users’ Perceptions
Authors: Gupta Marichi , Bansal Aditya , Jain Bhav , Rochelle Jillian , Oak Atharv , Jalali Mohammad S. 
Published: August 2020

ABSTRACTObjectiveThe potential ability for weather to affect SARS-CoV-2 transmission has been an area of controversial discussion during the COVID-19 pandemic. Individuals’ perceptions of the impact of weather can inform their adherence to public health guidelines; however, there is no measure of their perceptions. We quantified Twitter users’ perceptions of the effect of weather and analyzed how they evolved with respect to real-world events and time.Materials and MethodsWe collected 166,005 tweets posted between January 23 and June 22, 2020 and employed machine learning/natural language processing techniques to filter for relevant tweets, classify them by the type of effect they claimed, and identify topics of discussion.ResultsWe identified 28,555 relevant tweets and estimate that 40.4% indicate uncertainty about weather’s impact, 33.5% indicate no effect, and 26.1% indicate some effect. We tracked changes in these proportions over time. Topic modeling revealed major latent areas of discussion.DiscussionThere is no consensus among the public for weather’s potential impact. Earlier months were characterized by tweets that were uncertain of weather’s effect or claimed no effect; later, the portion of tweets claiming some effect of weather increased. Tweets claiming no effect of weather comprised the largest class by June. Major topics of discussion included comparisons to influenza’s seasonality, President Trump’s comments on weather’s effect, and social distancing.ConclusionThere is a major gap between scientific evidence and public opinion of weather’s impacts on COVID-19. We provide evidence of public’s misconceptions and topics of discussion, which can inform public health communications.
Developing methods for measuring national distributions and densities of wild mammals using camera traps: A Kosovo study
Authors: Beatham Sarah E. , Ward Alastair I. , Fouracre David , Muhaxhiri Jeton , Sallmann Michael , Zogu Besim , Gjinovci Valdet , Wilsmore Anthony J. , Smith Graham C. 
Published: August 2020

AbstractUnderstanding the distributions and density of wild mammals is integral to the implementation of wildlife management strategies, particularly for controlling diseases and conservation management. Recent advances in camera trap technology together with the development of the Random Encounter Model have provided a non-invasive method for estimating mammal densities. In addition, the development of citizen science initiatives have advanced ecological data collection. This study describes a national camera trap survey delivered by local stakeholders in eleven forest sites in Kosovo from 2014 to 2015 to measure the distributions and abundance of medium to large wild mammals as part of the Control and/or eradication of animal diseases project. The Random Encounter Model was used to calculate density data for each species, which appear realistic when compared to densities found in other European countries. The study particularly focussed on the red fox (Vulpes vulpes) and the grey wolf (Canis lupus) as potential vectors of rabies and wild boar (Sus scrofa) as a vector of classical swine fever. These species were found to be three of the most widely distributed species in Kosovo and were present at the majority of sites at high densities. The camera survey also provided information on species of conservation concern such as the Eurasian brown bear (Ursus arctos) and provided the first physical evidence of a live Eurasian golden jackal (Canis aureus) in Kosovo. Although sources of bias were identified, these estimates are likely to be more accurate than those devised from methods such as hunting bags and the findings of this study suggest that, with a moderate amount of development, camera trapping implemented by local stakeholders can be used as an effective and practicable method to estimate national distributions and population sizes of medium to large sized wild mammals.
A composite method to infer drug resistance with mixed genomic data
Authors: Datta Gargi , Hasan Nabeeh A , Strong Michael , Leach Sonia M 
Published: August 2020

AbstractBackgroundThe increasing incidence of drug resistance in tuberculosis and other infectious diseases poses an escalating cause for concern, emphasizing the urgent need to devise robust computational and molecular methods identify drug resistant strains. Although machine learning-based approaches using whole-genome sequence data can facilitate the inference of drug resistance, current implementations do not optimally take advantage of information in public databases and are not robust for small sample sizes and mixed attribute types.ResultsIn this paper we introduce the Composite MetaDistance method, an approach for feature selection and classification of high-dimensional, unbalanced datasets with mixed attribute features from various data sources. We introduce a mixed-attribute, multi-view distance function to calculate distances between samples, with optimal handling of nominal features and different feature views. We also introduce a novel feature set for drug resistance prediction inMycobacterium tuberculosis, using data from diverse sources. We compare the performance of Composite MetaDistance to multiple machine learning algorithms forMycobacterium tuberculosisdrug resistance prediction for three drugs. Composite MetaDistance consistently outperforms existing algorithms for small sample training sets, and performs as well as other algorithms for training sets with larger sample sizes.ConclusionThe feature set formulation introduced in this paper is utilizes mutational and publicly available information for each gene, and is much richer than ever devised previously. The prediction algorithm, Composite MetaDistance, is sample size agnostic and robust especially given small sample sizes. Proper handling of nominal features improves performance even with a very small number of nominal features. We expect Composite MetaDistance to be even more robust for datasets with a higher percentage of nominal features. The algorithm is application independent and can be used for any mixed attribute dataset.
Social Learning in a Network Model of Covid-19
Authors: Davids Allan , Rand Gideon Du , Georg Co-Pierre , Koziol Tina , Schasfoort Joeri Anton 
Published: August 2020

AbstractThis paper studies the effects of social learning on the transmission of Covid-19 in a network model. We calibrate our model to detailed data for Cape Town, South Africa and show that the inclusion of social learning improves the prediction of excess fatalities, reducing the best-fit squared difference from 19.34 to 11.40. The inclusion of social learning both flattens and shortens the curves for infections, hospitalizations, and excess fatalities, which is qualitatively different from flattening the curve by reducing the contact rate or transmission probability through non-pharmaceutical interventions. While social learning reduces infections, this alone is not sufficient to curb the spread of the virus because learning is slower than the disease spreads. We use our model to study the efficacy of different vaccination strategies and find that vaccinating vulnerable groups first leads to a 72% reduction in fatalities and 5% increase in total infections compared to a random-order benchmark. By contrast, using a contact-based vaccination strategy reduces infections by only 0.9% but results in 42% more fatalities relative to the benchmark.