bluuebunny/crossref_metadata_2025_split huggingface dataset:
Global surveillance of potential antiviral drug resistance in SARS-CoV-2: proof of concept focussing on the RNA-dependent RNA polymerase
Authors: Mari Alfredo , Roloff Tim , Stange Madlen , Søgaard Kirstine K. , Asllanaj Erblin , Tauriello Gerardo , Alexander Leila Tamara , Schweitzer Michael , Leuzinger Karoline , Gensch Alexander , Martinez Aurélien , Bielicki Julia , Pargger Hans , Siegemund Martin , Nickel Christian H. , Bingisser Roland , Osthoff Michael , Bassetti Stefano , Sendi Parham , Battegay Manuel , Marzolini Catia , Seth-Smith Helena M.B. , Schwede Torsten , Hirsch Hans H. , Egli Adrian 
Published: January 2021

AbstractAntiviral treatments for COVID-19 have involved many repurposed drugs. Currently, SARS-CoV-2 RNA-dependent RNA polymerase (RdRp, encoded bynsp12-nsp7-nsp8) has been targeted by numerous inhibitors with debated clinical impact. Among these, remdesivir has been conditionally approved for the treatment of COVID-19 patients. Although the emergence of antiviral resistance, an indirect proxy for antiviral efficacy, poses a considerable healthcare threat, an evolutionary perspective on emerging resistant mutants is still lacking.Here we show that SARS-CoV-2 RdRp is under purifying selection, that potential escape mutations are rare, and unlikely to lead to viral fitness loss.In more than 56,000 viral genomes from 105 countries dating from December 2019 to July 2020 we found negative selective pressure affectingnsp12(Tajima’s D = −2.62), with potential antiviral escape mutations in only 0.3% of sequenced genomes. Those affected known key residues, such as Nsp12:Val473 and Nsp12:Arg555. Of the potential escape mutations found globally,in silicostructural models show that this rarely implies loss of stability in RdRp. No potential escape mutation were found in our local cohort of remdesivir treated patients from the first wave (n=8). Our results indicate that RdRp is a suitable drug target, and that remdesivir does not seem to exert high selective pressure. Our study could be the starting point of a larger monitoring effort of drug resistance throughout the COVID-19 pandemic. We recommend the application of repetitive genome sequencing of SARS-CoV-2 from patients treated with antivirals to provide early insights into the evolution or antiviral resistance.
Speech pause distribution as an early marker for Alzheimer’s disease
Authors: Pastoriza-Domínguez Patricia , Torre Iván G. , Diéguez-Vide Faustino , Gómez-Ruiz Isabel , Geladó Sandra , Bello-López Joan , Ávila-Rivera Asunción , Matías-Guiu Jordi , Pytel Vanesa , Hernández-Fernández Antoni 
Published: January 2021

AbstractBackgroundPause duration analysis is a common feature in the study of discourse in Alzheimer’s disease (AD) and may also be helpful for its early detection. However, studies involving patients with amnestic mild cognitive impairment (aMCI) have yielded varying results.ObjectivesTo characterize the probability density distribution of speech pause durations in AD, two multi-domain amnestic MCI patients (with memory encoding deficits, a-mdMCI-E, and with retrieval impairment only, a-mdMCI-R) and healthy controls (HC) in order check whether there are significant differences between them.Method112 picture-based oral narratives were manually transcribed and annotated for the automatic extraction and analysis of pause durations. Different probability distributions were tested for the fitting of pause durations while truncating shorter ranges. Recent findings in the field of Statistics were considered in order to avoid the inherent methodological uncertainty that this type of analysis entails.ResultsA lognormal distribution (LND) explained the distribution of pause duration for all groups. Its fitted parameters (µ,σ) followed a gradation from the group with shorter durations and a higher tendency to produce short pauses (HC) to the group with longer pause durations and a considerably higher tendency to produce long pauses with greater variance (AD). Importantly, a-mdMCI-E produced significantly longer pauses and with greater variability than their a-mdMCI-R counterparts (α= 0.05).ConclusionWe report significant differences at the group level in pause distribution across all groups of study that could be used in future diagnostic tools and discuss the clinical implications of these findings, particularly regarding the characterization of aMCI.
COVID-19 vaccine hesitancy worldwide: a systematic review of vaccine acceptance rates
Authors: Sallam Malik 
Published: January 2021

AbstractIntroductionUtility of vaccine campaigns to control coronavirus disease 2019 (COVID-19) is not merely dependent on vaccine efficacy and safety. Vaccine acceptance among the general public and the healthcare workers, appears to have a decisive role for successful control of the pandemic.AimTo provide an up-to-date assessment of COVID-19 vaccination acceptance rates worldwide.MethodsA systematic search of the peer-reviewed English survey literature indexed in PubMed was done on December 25, 2020. Results from 30 studies, met the inclusion criteria and formed the basis for final COVID-19 vaccine acceptance estimates. Results of an additional recent survey from Jordan and Kuwait was considered in this review as well.ResultsSurvey studies on COVID-19 vaccine acceptance rates were found from 33 different countries. Among adults representing the general public, the highest COVID-19 vaccine acceptance rates were found in Ecuador (97.0%), Malaysia (94.3%), Indonesia (93.3%) and China (91.3%). On the other hand, the lowest COVID-19 vaccine acceptance rates were found in Kuwait (23.6%), Jordan (28.4%), Italy (53.7), Russia (54.9%), Poland (56.3%), US (56.9%), and France (58.9%). Only eight surveys among healthcare workers (doctors, nurses) were found, with vaccine acceptance rates ranging from 27.7% in the Democratic Republic of the Congo to 78.1% in Israel. In a majority of survey studies among the general public (62%), the acceptance of COVID-19 vaccination showed a level of ≥ 70%.ConclusionsLow rates of COVID-19 vaccine acceptance were reported in the Middle East, Russia, Africa and several European countries. This could represent a major problem in the global efforts that aim to control the current COVID-19 pandemic. More studies are recommended to address the scope of COVID-19 vaccine hesitancy. Such studies are particularly needed in the Middle East Africa, Eastern Europe, Central Asia, Middle and Latin America.Graphical AbstractCOVID-19 vaccine acceptance rates worldwideFor countries with more than one survey study, the vaccine acceptance rate of the latest survey was used in this graph. The estimates were also based on studies from the general population, except in the following cases were no studies from the general public were found (Australia: parents/guardians; DRC: healthcare workers; Hong Kong: healthcare workers; Malta: healthcare workers).
PREDICTORS OF UPTAKE OF A POTENTIAL COVID-19 VACCINE AMONG NIGERIAN ADULTS
Authors: Olomofe Charles Oluwatemitope , Soyemi Victor Kehinde , Udomah Bolaji Felicia , Owolabi Adeyinka Olabisi , Ajumuka Emmanuel Eziashi , Igbokwe Chukwudum Martin , Ashaolu Uriel Oludare , Adeyemi Ayodele Olusola , Aremu-Kasumu Yetunde Bolatito , Dada Olufunke Folasade , Ochieze John Chikezie , Fayemi Olaniyi Bamidele , Ologunde Kehinde Williams , Popoola Gbenga Omotade , Ariyo Olumuyiwa Elijah 
Published: January 2021

ABSTRACTBackgroundThe Coronavirus diseases (COVID-19) pandemic is not abating and there is no approved treatment yet. The development of vaccines is hoped to help in addressing this disease outbreak. However, in the face of anti-vaccines uprise, it is important to understand the factors that may influence the uptake of COVID-19 vaccines as this will influence how successful the fight against COVID-19 will be in the long term.MethodsA cross-sectional study among 776 adult Nigerians (age ≥18 years) was conducted in the 36 States of Nigeria and the Capital City with online questionnaire. The questionnaire consisted of 5 sections: socio-demographic characteristics of respondents, respondent’s knowledge of COVID-19, respondents risk perception of COVID-19, vaccination history of respondents, and willingness to receive COVID-19 vaccine. Descriptive analysis of variables was done and multivariate analysis using logistic regression was carried out to determine the predictors of uptake of a potential COVID-19 vaccine. The level of significance was predetermined at a p-value < 0.05. Data analysis was done with SPSS version 21.ResultsMost of the respondents were male (58.1%). Most participants were willing to take a potential COVID-19 vaccine (58.2%), while 19.2% would not take it with 22.6% indecisive. 53.5% would prefer a single dose COVID-19 vaccine. For vaccine uptake, being male (p= 0.002) and the perception that “vaccines are good” (p< 0.001) were the positive predictor of uptake of a potential COVID-19 vaccine.ConclusionMost Nigerians were willing to take a potential COVID-19 vaccine with the male gender and perception that “vaccines are good” being positive predictors. There is a need for public enlightenment aim at encouraging those that are indecisive or averse to receiving COVID-19 vaccines.
Characterizing Two Outbreak Waves of COVID-19 in Spain Using Phenomenological Epidemic Modelling
Authors: López Miguel , Peinado Alberto , Ortiz Andrés 
Published: January 2021

AbstractSince the first case reported of SARS-CoV-2 the end of December 2019 in China, the number of cases quickly climbed following an exponential growth trend, demonstrating that aglobal pandemicis possible. As of December 3, 2020, the total number of cases reported are around 65,527,000 contagions worldwide, and 1,524,000 deaths affecting 218 countries and territories. In this scenario, Spain is one of the countries that has suffered in a hard way, the ongoing epidemic caused by the novel coronavirus SARS-CoV-2, namely COVID-19 disease. In this paper, we present the utilization of phenomenological epidemic models to characterize the two first outbreak waves of COVID-19 in Spain. The study is driven using a two-step phenomenological epidemic approach. First, we use a simple generalized growth model to fit the main parameters at the early epidemic phase; later, we apply our previous finding over a logistic growth model to that characterize both waves completely. The results show that even in the absence of accurate data series, it is possible to characterize the curves of case incidence, and even construct short-term forecast in the near time horizon.
Cyproterone Acetate and risk of Meningioma
Authors: Mikkelsen Anders P. , Greiber Iben K. , Scheller Nikolai M. , Hilden Malene , Lidegaard Øjvind 
Published: January 2021

AbstractCyproterone acetate (CPA) is a synthetic steroid hormone. We assessed the association between the use of CPA and the risk of developing meningioma.In a historical prospective cohort study, using Danish national healthcare registers we included a cohort of 5,730,654 individuals, among whom 1,982 were exposed to CPA. During follow-up, we identified 8,957 cases of meningioma, of which 16 were exposed to CPA. From 2013 to 2019 the number of new users increased from 18.1 to 62.3 new users per million, while the proportion of new users who were transgender increased from 18.4 to 68.3%. Analyses showed a significantly increased risk of meningioma according to cumulative dose of CPA; 0.1-10 grams of CPA, incidence rate 78.8 (95% CI 15.7-141.9) per 100.000 person years and adjusted hazard ratio 7.0 (3.1-15.6); >10 grams of CPA, incidence 187.5 (71.3-303.7) and adjusted hazard ratio 19.2 (10.3-35.8), as compared to the background population.In conclusion, the cumulative dose of CPA was associated with an increased incidence and hazard ratio of meningioma, showing a dose-response relationship. The number of new CPA users increased more than 3-fold from 2013 to 2019, primarily driven by new transgender users.
Efficiency of Artificial Intelligence in Detecting COVID-19 Pneumonia and Other Pneumonia Causes by Quantum Fourier Transform Method
Authors: Acar Erdi , Öztoprak Bilge , Reşorlu Mustafa , Daş Murat , Yılmaz İhsan , Öztoprak İbrahim 
Published: January 2021

AbstractThe new coronavirus (COVID-19) appeared in Wuhan in December 2019 and has been announced as a pandemic by the World Health Organization (WHO). Currently, this deadly pandemic has caused more than 1 million deaths worldwide. Therefore, it is essential to detect positive cases as early as possible to prevent the further spread of this outbreak. Currently, the most widely used COVID-19 detection technique is a real-time reverse transcription-polymerase chain reaction (RT-PCR). However, RT-PCR is time-consuming to confirm infection in the patient. Because RT-PCR is less sensitive, it provides high false-negative results. Computed tomography (CT) is recommended as a solution to this problem by healthcare professionals because of its higher sensitivity for early and rapid diagnosis. In addition, radiation used in CT poses a serious threat to patients. In this study, we propose a CNN-based method to distinguish COVID-19 pneumonia from other types of viral and bacterial pneumonia using low-dose CT images to reduce the radiation dose used in CT. In our study, we used a data set consisting of 7717 CT images of 350 patients that we collected from Çanakkale Onsekiz Mart University Research Hospital. We used a CNN-based network that suppresses noise to remove interference from low-dose CT images. In the image preprocessing phase, we provided lung segmentation from CT images and applied quantum Fourier transform. By evaluating all possible variations of local knowledge at the same time with quantum Fourier transformation, the most informative spatial information was extracted. In CNN-based architecture, we used pre-trained ResNet50v2 as a feature extractor and fine-tune by training with our dataset. We visualized the efficiency of the ResNet50v2 network using the t-SNE method. We performed the classification process with a fully connected layer. We created a heat map using the GradCam technique to see where the model focuses on the images while classifying. In this experimental study, the results of 99.5%, 99.2%, 99.0%, 99.7%, and 99.1%, were obtained in the context of performance criteria such as accuracy, precision, sensitivity, specificity, and f1 score, respectively. This study revealed the artificial intelligence-based computer-aided diagnosis (CAD)system as an effective and fast method to accurately diagnose COVID-19 pneumonia.
COVID-19: Can early home treatment with Azithromycin alone or with Zinc help prevent hospitalisation, death, and long-COVID-19? A review
Authors: Lepere Philippe , Escarguel Bruno , Yolartiran Selda , Escarguel Claude 
Published: January 2021

AbstractIntroductionThe effects of the SARS-CoV-2 pandemic continues to disrupt health systems worldwide, leading to population lockdowns in many countries. Preventing hospitalisation, death and long-COVID-19 with repurposed drugs remains a priority. Hydroxychloroquine (HCQ) and azithromycin (AZM) are the most commonly used in ambulatory care, with divergent results. With the aim of decentralizing early treatment to family practitioners, we addressed the question: Can early home treatment with AZM alone or with zinc help prevent hospitalisation, death, and long-COVID-19?MethodologyWe conducted a scoping review of articles published from 31st December 2019 to 5th November 2020 in Pubmed, Google Scholar, MedRxiv, and BioRxiv databases, and a review of undergoing clinical trials published in the Clinicaltrial.gov database.ResultsMany studies report on outpatient treatment with a combination of AZM + HCQ versus AZM alone, and few studies propose the addition of Zinc (Zn) to AZM. In addition, we identified 5 clinical trials currently recruiting individuals for early outpatient treatment with AZM. However, we failed in identifying any study or clinical trial conducted with family practitioners responding to our question.DiscussionThe antiviral, anti-inflammatory, immunomodulatory benefits of AZM + Zn make this drugs combination a good candidate therapy to treat flu-like-COVID-19 and atypical pneumoniae. The antibacterial action of AZM can also help disrupting the bacteria/virus cooperation that is poorly documented. Considering pros and cons of macrolide use (including antimicrobial resistance), we call for early use of this therapy by family practitioners for home treatment of individuals presenting mild or moderate symptoms under rigorous scientific guidance to prevent hospitalisation, death and long-COVID.
Estimating event ban effects on COVID-19 outbreak in Japan
Authors: Kurita Junko , Sugawara Tamie , Ohkusa Yasushi 
Published: January 2021

AbstractBackgroundBefore Olympic and Paralympic Games in Tokyo, whether an audience shall be allowed or not has been a subject of concern in Japan as of early June, 2021. Object: We evaluated effects of professional baseball games with audiences as an example of the large sports events, on COVID-19 infectiousness.MethodWe regressed the effective reproduction number R(t) on a dummy variable for professional baseball games with audiences as along with temperature, humidity, mobility, and countermeasures. We examined two study periods: those including and excluding before initiation of the games in 2020.ResultsEstimation results indicate that the period with audiences exhibited significantly lower infectiousness than when audiences were excluded before initiation of the games with audience attendance. However, audiences were found to have a negative but insignificant effect when compared to the period before initiation of the attended games.Discussion and ConclusionThis study found no clear evidence indicating that big sports events with audiences raise the COVID-19 infectiousness.
Early measurement of blood sST2 is a good predictor of death and poor outcomes in patients admitted for COVID-19 infection
Authors: Sánchez-Marteles M , Rubio-Gracia J , Peña-Fresneda N. , Garcés-Horna V , Gracia-Tello B , Martínez-Lostao L , Crespo-Aznárez S , Pérez-Calvo JI , Giménez-López I 
Published: January 2021

AbstractImportanceAlthough several biomarkers have shown correlation to prognosis in COVID-19 patients, their clinical value is limited because of lack of specificity, suboptimal sensibility, or poor dynamic behavior.ObjectiveIn search of better prognostic markers in COVID-19, we hypothesized that circulating soluble ST2 (sST2) could be associated to a worse outcome, prompted by our previous knowledge of sST2 involvement in heart failure-associated lung deterioration, and by mounting evidence favoring a role of IL-33/ST2 axis in the disease.Design, Setting and participantsOne hundred and fifty-two patients admitted for confirmed COVID-19 infection were included in a prospective non-interventional, observational study carried out in a tertiary teaching center. Blood samples were drawn at admission, 48-72 hours later and at discharge. sST2 concentrations, and routine blood laboratory were analyzed.Main outcomesPrimary end-points were admission at intensive care unit (ICU) and, mortality. Other outcomes were a need for high oxygen flow therapy (HOF) or increasing treatment at 48/72 hours.ResultsMedian age was 57.5 years (SD: 12.8), 60.4% males. Ten per cent of patients (n=15) were derived to ICU and/or died during admission. The rest stayed hospitalized 8(IQR:6) days on average. About 34% (n=47), 38% (n=53) and 48.5% (n=66) needed HOF, up-titrate therapy or both, respectively.Median (IQR) sST2 serum concentration (ng/mL) rose to 53.1(30.9) at admission, peaked at 48-72h (79.5[64]) and returned to admission levels at discharge (44.9[36.7]), remaining significantly elevated above healthy donor values (18.6[15.1]).A concentration of sST2 above 58.9 ng/mL identified patients progressing to ICU admission or death. These results remained significant after multivariable analysis. The area under the receiver operating characteristics curve (AUC) of sST2 for the occurrence of end-points was 0.776 (p=0.001). Admission sST2 was higher in patients who needed up-tritate therapy.Conclusions and relevanceIn patients admitted for COVID-19 infection, measurement of sST2 measurement early within 24h after at admission was able to identify patients at risk of severe complications or death.
Sociodemographic Characteristics of Missing Data in Digital Phenotyping
Authors: Kiang Mathew V , Chen Jarvis T , Krieger Nancy , Buckee Caroline O , Alexander Monica J , Baker Justin T , Buckner Randy L , Coombs Garth , Rich-Edwards Janet W , Carlson Kenzie W , Onnela Jukka-Pekka 
Published: January 2021

AbstractThe ubiquity of smartphones, with their increasingly sophisticated array of sensors, presents an unprecedented opportunity for researchers to collect diverse, temporally-dense data about human behavior while minimizing participant burden. Researchers increasingly make use of smartphone applications for “digital phenotyping,” the collection of phone sensor and log data to study the lived experiences of subjects in their natural environments. While digital phenotyping has shown promise in fields such as psychiatry and neuroscience, there are fundamental gaps in our knowledge about data collection and non-collection (i.e., missing data) in smartphone-based digital phenotyping. Here, we show that digital phenotyping presents a viable method of data collection, over long time periods, across diverse study participants with a range of sociodemographic characteristics. We examined accelerometer and GPS sensor data of 211 participants, amounting to 29,500 person-days of observation, using Bayesian hierarchical negative binomial regression. We found that iOS users had higher rates of accelerometer non-collection but lower GPS non-collection than Android users. For GPS data, rates of non-collection did not differ by race/ethnicity, education, age, or gender. For accelerometer data, Black participants had higher rates of non-collection while Asian participants had slightly lower non-collection. For both sensors, non-collection increased by 0.5% to 0.9% per week. These results demonstrate the feasibility of using smartphone-based digital phenotyping across diverse populations, for extended periods of time, and within diverse cohorts. As smartphones become increasingly embedded in everyday life, the insights of this study will help guide the design, planning, and analysis of digital phenotyping studies.
PD-L1+and Hyal2+myeloid cells in renal cell carcinoma: a case report
Authors: Kwenda Elizabeth , Dominguez-Gutierrez Paul R. , O’Malley Padraic , Crispen Paul L. , Kusmartsev Sergei 
Published: January 2021

AbstractRCC patients frequently have increased numbers of immunosuppressive myeloid cells in circulation. High numbers of myeloid derived suppressor cells (MDSCs) in the blood are associated with immune suppression as well as with cancer-related inflammation which drives the mobilization of myeloid cells to tumor tissue. Here we show that peripheral blood from a previously untreated renal cell carcinoma patient has increased numbers of monocytic CD33+CD11b+MDSCs, which also co-expressed PD-L1 and membrane-bound enzyme hyaluronidase 2 (Hyal2). PD-L1 expression is associated with immune suppression, whereas expression of Hyal2 is associated with inflammation, because Hyal2+myeloid cells can degrade the extracellular hyaluronan (HA), leading to the accumulation of pro-inflammatory HA fragments with low molecular weight. These findings implicate the potential involvement of monocytic MDSCs in both tumor-associated immune suppression and cancer-related inflammation. Analysis of organoid-like tumor-tissue slice cultures prepared from cancer tissue of the same patient revealed the significant presence of PD-L1+HLA-DR+macrophage-like or dendritic cell-like antigen-presenting cells in tumor stroma. Interestingly that stroma-associated PD-L1+cells frequently have intracellular hyaluronan. Collectively, data presented in this study suggest that the interplay between tumor-recruited myeloid cells and stromal hyaluronan may contribute to the inflammation and immune tolerance in cancer.