bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genomic surveillance at scale is required to detect newly emerging strains at an early timepoint
Authors: Vavrek Darcy , Speroni Lucia , Curnow Kirsten J. , Oberholzer Michael , Moeder Vanessa , Febbo Phillip G. 
Published: January 2021

AbstractGenomic surveillance in the setting of the coronavirus disease 2019 (COVID-19) pandemic has the potential to identify emerging SARS-CoV-2 strains that may be more transmissible, virulent, evade detection by standard diagnostic tests, or vaccine escapes. The rapid spread of the SARS-CoV-2 B.1.1.7 strain from southern England to other parts of the country and globe is a clear example of the impact of such strains. Early discovery of the B.1.1.7 strain was enabled through the proactive COVID-19 Genomics UK (COG-UK) program and the UK’s commitment to genomic surveillance, sequencing about 10% of positive samples.1 In order to enact more aggressive public health measures to minimize the spread of such strains, genomic surveillance needs to be of sufficient scale to detect early emergence and expansion in the broader virus population. By modeling common performance characteristics of available diagnostic and sequencing tests, we developed a model that assesses the sampling required to detect emerging strains when they are less than 1% of all strains in a population. This model demonstrates that 5% sampling of all positive tests allows the detection of emerging strains when they are a prevalence of 0.1% to 1.0%. While each country will determine their risk tolerance for the emergence of novel strains, as vaccines are distributed and we work to end the pandemic and prevent future SARS-CoV-2 outbreaks, genomic surveillance will be an integral part of success.
Using Mendelian randomisation to explore the gateway hypothesis: Possible causal effects of smoking initiation and alcohol consumption on substance use outcomes
Authors: Reed Zoe E. , Wootton Robyn E. , Munafò Marcus R. 
Published: January 2021

AbstractBackground and AimsInitial use of drugs such as tobacco and alcohol may lead to subsequent more problematic drug use – the ‘gateway’ hypothesis. However, observed associations may be due to a shared underlying risk factor, such as trait impulsivity. We used bidirectional Mendelian Randomisation (MR) to test the gateway hypothesis.DesignOur main method was inverse-variance weighted (IVW) MR, with other methods included as sensitivity analyses (where consistent results across methods would raise confidence in our primary results). MR is a genetic instrumental variable approach used to support stronger causal inference in observational studies.SettingEuropean ancestry individuals.ParticipantsGenome-wide association summary data for smoking initiation, alcoholic drinks per week, cannabis use and dependence, cocaine and opioid dependence (N=1,749 to 1,232,091).MeasurementsGenetic variants for exposure.FindingsWe found evidence of causal effects from smoking initiation to increased drinks per week (IVW: β=0.06; 95% CI=0.03 to 0.09; p=9.44×10−06), cannabis use (IVW: OR=1.34; 95% CI=1.24 to 1.44; p=1.95×10−14), and cannabis dependence (IVW: OR=1.68; 95% CI=1.12 to 2.51; p=0.01). We also found evidence of an effect of cannabis use on increased likelihood of smoking initiation (IVW: OR=1.39; 95% CI=1.08 to 1.80; p=0.01). We did not find evidence of an effect of drinks per week on other substance use outcomes, except weak evidence of an effect on cannabis use. We found weak evidence of an effect of opioid dependence on increased drinks per week (IVW: β=0.002; 95% CI=0.0005 to 0.003; p=8.61×10−03).ConclusionsSmoking initiation may lead to increased alcohol consumption, cannabis use and dependence. Cannabis use may also lead to smoking initiation, and opioid dependence to alcohol consumption. However, given tobacco and alcohol use typically begin before other drug use, these results may reflect a shared risk factor, or a bidirectional effect for cannabis use. Further research should explore potentially shared risk factors.
Characteristics and outcomes of 118,155 COVID-19 individuals with a history of cancer in the United States and Spain
Authors: Roel Elena , Pistillo Andrea , Recalde Martina , Sena Anthony G. , Fernández-Bertolín Sergio , Aragón María , Puente Diana , Ahmed Waheed-Ul-Rahman , Alghoul Heba , Alser Osaid , Alshammari Thamir M. , Areia Carlos , Blacketer Clair , Carter William , Casajust Paula , Culhane Aedin C. , Dawoud Dalia , DeFalco Frank , Duvall Scott L. , Falconer Thomas , Golozar Asieh , Gong Mengchun , Hester Laura , Hripcsak George , Tan Eng Hooi , Jeon Hokyun , Jonnagaddala Jitendra , Lai Lana Y.H. , Lynch Kristine E. , Matheny Michael E. , Morales Daniel R. , Natarajan Karthik , Nyberg Fredrik , Ostropolets Anna , Posada José D. , Prats-Uribe Albert , Reich Christian G. , Rivera Donna , Schilling Lisa M. , Soerjomataram Isabelle , Shah Karishma , Shah Nigam , Shen Yang , Spotniz Matthew , Subbian Vignesh , Suchard Marc A. , Trama Annalisa , Zhang Lin , Zhang Ying , Ryan Patrick , Prieto-Alhambra Daniel , Kostka Kristin , Duarte-Salles Talita 
Published: January 2021

AbstractPurposeWe aimed to describe the demographics, cancer subtypes, comorbidities and outcomes of patients with a history of cancer with COVID-19 from March to June 2020. Secondly, we compared patients hospitalized with COVID-19 to patients diagnosed with COVID-19 and patients hospitalized with influenza.MethodsWe conducted a cohort study using eight routinely-collected healthcare databases from Spain and the US, standardized to the Observational Medical Outcome Partnership common data model. Three cohorts of patients with a history of cancer were included: i) diagnosed with COVID-19, ii) hospitalized with COVID-19, and iii) hospitalized with influenza in 2017-2018. Patients were followed from index date to 30 days or death. We reported demographics, cancer subtypes, comorbidities, and 30-day outcomes.ResultsWe included 118,155 patients with a cancer history in the COVID-19 diagnosed and 41,939 in the COVID-19 hospitalized cohorts. The most frequent cancer subtypes were prostate and breast cancer (range: 5-19% and 1-14% in the diagnosed cohort, respectively). Hematological malignancies were also frequent, with non-Hodgkin’s lymphoma being among the 5 most common cancer subtypes in the diagnosed cohort. Overall, patients were more frequently aged above 65 years and had multiple comorbidities. Occurrence of death ranged from 8% to 14% and from 18% to 26% in the diagnosed and hospitalized COVID-19 cohorts, respectively. Patients hospitalized with influenza (n=242,960) had a similar distribution of cancer subtypes, sex, age and comorbidities but lower occurrence of adverse events.ConclusionPatients with a history of cancer and COVID-19 have advanced age, multiple comorbidities, and a high occurence of COVID-19-related events. Additionaly, hematological malignancies were frequent in these patients.This observational study provides epidemiologic characteristics that can inform clinical care and future etiological studies.
Differential T cell reactivity to seasonal coronaviruses and SARS-CoV-2 in community and health care workers
Authors: da Silva Antunes Ricardo , Pallikkuth Suresh , Williams Erin , Yu Esther Dawen , Mateus Jose , Quiambao Lorenzo , Wang Eric , Rawlings Stephen A. , Stadlbauer Daniel , Jiang Kaijun , Amanat Fatima , Arnold David , Andrews David , Fuego Irma , Dan Jennifer M. , Grifoni Alba , Weiskopf Daniela , Krammer Florian , Crotty Shane , Hoffer Michael E. , Pahwa Savita G. , Sette Alessandro 
Published: January 2021

AbstractHerein we measured CD4+ T cell responses against common cold corona (CCC) viruses and SARS-CoV-2 in high-risk health care workers (HCW) and community controls. We observed higher levels of CCC reactive T cells in SARS-CoV-2 seronegative HCW compared to community donors, consistent with potential higher occupational exposure of HCW to CCC. We further show that SARS-CoV-2 reactivity of seronegative HCW was higher than community controls and correlation between CCC and SARS-CoV-2 responses is consistent with cross-reactivity and not associated with recent in vivo activation. Surprisingly, CCC reactivity was decreased in SARS-CoV-2 infected HCW, suggesting that exposure to SARS-CoV-2 might interfere with CCC responses, either directly or indirectly. This result was unexpected, but consistently detected in independent cohorts derived from Miami and San Diego.
Towards a platform for robot-assisted minimally-supervised therapy of hand function: design and pilot usability evaluation
Authors: Ranzani Raffaele , Eicher Lucas , Viggiano Federica , Engelbrecht Bernadette , Held Jeremia P.O. , Lambercy Olivier , Gassert Roger 
Published: January 2021

AbstractBackgroundRobot-assisted therapy can increase therapy dose after stroke, which is often considered insufficient in clinical practice and after discharge, especially with respect to hand function. Thus far, there has been a focus on rather complex systems that require therapist supervision. To better exploit the potential of robot-assisted therapy, we propose a platform designed for minimal therapist supervision, and present the preliminary evaluation of its immediate usability, one of the main and frequently neglected challenges for real-world application. Such an approach could help increase therapy dose by allowing the training of multiple patients in parallel by a single therapist, as well as independent training in the clinic or at home.MethodsWe implemented design changes on a hand rehabilitation robot, considering aspects relevant to enabling minimally-supervised therapy, such as new physical/graphical user interfaces and two functional therapy exercises to train hand motor coordination, somatosensation and memory. Ten participants with chronic stroke assessed the usability of the platform and reported the perceived workload during a single therapy session with minimal supervision. The ability to independently use the platform was evaluated with a checklist.ResultsParticipants were able to independently perform the therapy session after a short familiarization period, requiring assistance in only 13.46(7.69-19.23)% of the tasks. They assigned good-to-excellent scores on the SUS to the user-interface and the exercises (85.00(75.63-86.88) and 73.75(63.13-83.75) out of 100, respectively). Nine participants stated that they would use the platform frequently. Perceived workloads lay within desired workload bands. Object grasping with simultaneous control of forearm pronosupination and stiffness discrimination were identified as the most difficult tasks.DiscussionOur findings demonstrate that a robot-assisted therapy device can be rendered safely and intuitively usable upon first exposure with minimal supervision through compliance with usability and perceived workload requirements. The preliminary usability evaluation identified usability challenges that should be solved to allow real-world minimally-supervised use. Such a platformcould complement conventional therapy, allowing to provide increased dose with the available resources, and establish a continuum of care that progressively increases therapy lead of the patient from the clinic to the home.
Optimal SARS-CoV-2 vaccine allocation using real-time seroprevalence estimates in Rhode Island and Massachusetts
Authors: Tran Thu Nguyen-Anh , Wikle Nathan , Albert Joseph , Inam Haider , Strong Emily , Brinda Karel , Leighow Scott M , Yang Fuhan , Hossain Sajid , Pritchard Justin R , Chan Philip , Hanage William P , Hanks Ephraim M , Boni Maciej F 
Published: January 2021

AbstractAs three SARS-CoV-2 vaccines come to market in Europe and North America in the winter of 2020-2021, distribution networks will be in a race against a major epidemiological wave of SARS-CoV-2 that began in autumn 2020. Rapid and optimized vaccine allocation is critical during this time. With 95% efficacy reported for two of the vaccines, near-term public health needs require that distribution is prioritized to the elderly, health-care workers, teachers, essential workers, and individuals with co-morbidities putting them at risk of severe clinical progression. Here, we evaluate various age-based vaccine distributions using a validated mathematical model based on current epidemic trends in Rhode Island and Massachusetts. We allow for varying waning efficacy of vaccine-induced immunity, as this has not yet been measured. We account for the fact that known COVID-positive cases may not be included in the first round of vaccination. And, we account for current age-specific immune patterns in both states. We find that allocating a substantial proportion (> 75%) of vaccine supply to individuals over the age of 70 is optimal in terms of reducing total cumulative deaths through mid-2021. As we do not explicitly model other high mortality groups, this result on vaccine allocation applies to all groups at high risk of mortality if infected. Our analysis confirms that for an easily transmissible respiratory virus, allocating a large majority of vaccinations to groups with the highest mortality risk is optimal. Our analysis assumes that health systems during winter 2020-2021 have equal staffing and capacity to previous phases of the SARS-CoV-2 epidemic; we do not consider the effects of understaffed hospitals or unvaccinated medical staff. Vaccinating only seronegative individuals avoids redundancy in vaccine use on individuals that may already be immune, and will result in 1% to 2% reductions in cumulative hospitalizations and deaths by mid-2021. Assuming high vaccination coverage (> 28%) and no major relaxations in distancing, masking, gathering size, or hygiene guidelines between now and spring 2021, our model predicts that a combination of vaccination and population immunity will lead to low or near-zero transmission levels by the second quarter of 2021.
Impact of COVID-19 on the indigenous population of Brazil: A geo-epidemiological study
Authors: Alves Josilene D , Abade André S , Peres Wigis P , Borges Jonatas E , Santos Sandra M , Scholze Alessandro R 
Published: January 2021

SUMMARYThis study aimed to analyze the geographical distribution of COVID-19 and to identify highrisk areas for the occurrence of cases and deaths from the disease in the indigenous population of Brazil. This is an ecological study whose units of analysis were the Special Indigenous Sanitary Districts. Cases and deaths by COVID-19 notified by the Special Secretariat for Indigenous Health between March and October 2020 were included. To verify the spatial association, the Getis-Ord General G and Getis-Ord Gi * techniques were used. High spatial risk clusters have been identified by the scan statistics technique. 32,041 cases of COVID-19 and 471 deaths were reported. The incidence and mortality rates were between 758.14 and 18530.56 cases and 5.96 and 265.37 deaths per 100 thousand inhabitants, respectively. The non-randomness of cases (z-score = 5.40; p <0.001) and deaths (z-score = 3.83; p <0.001) was confirmed. Hotspots were evidenced for both events with confidence levels of 90, 95 and 99% concentrated in the North and Midwest regions of the country. Eight high-risk spatial clusters for cases with a relative risk (RR) between 1.08 and 4.11 (p <0.05) and two risk clusters for deaths with RR between 3.08 and 3.97 (p <0.05) were identified. The results indicate critical areas in the indigenous territories of Brazil and contribute to better targeting the control actions of COVID-19 in this population.
The influence of positive emotion and negative emotion on false memory based on EEG signal analysis
Authors: Li Ying , Ni Zhaobing , He Renjie , Zhang Junyu , Zhang Zhimou , Yang Shuo , Yin Ning 
Published: January 2021

AbstractAnalyzing the influence of emotion on false memory through electroencephalogram is helpful to further explore the cognition function of brain. In this study, we improved the Deese-Roediger-McDermott paradigm experiment to study the false memory. The memory materials are combined with mixed emotions, which are closer to real life. Twenty-eight participants were randomly divided into positive group and negative group. We used music to induce the participants in the positive group and the negative group to generate corresponding emotions. Finally, we analyzed the difference between the positive group and the negative group from the behavior data, source location and cortex functional network of event related potential. The results of behavioral data analysis show that the false memory rate of positive group (85%) is significantly higher than that of negative group (72%). The results of source localization show that the brain of the positive group is more active than that of the negative group, and the difference of brain activation location between the two groups is mainly manifested in the BA24 and BA45 brain regions. The results of cortex functional network show that the node degree, clustering coefficient, global efficiency and small-world property of the positive group are significantly higher than those of the negative group. It can be found from the three aspects that participants’ emotional state and brain’s understanding of semantic are the main reasons for the difference in the incidence of false memory between the two groups.
The joint role of coevolutionary selection and network structure in shaping trait complementarity in mutualisms
Authors: Pedraza Fernando , Bascompte Jordi 
Published: January 2021

AbstractCoevolution can sculpt remarkable trait similarity between mutualistic partners. Yet, it remains unclear which network topologies and selection regimes enhance such trait complementarity. To address this, we simulate coevolution in topologically-distinct net-works under a gradient of mutualistic selection strength. We describe three main insights. First, trait matching is jointly influenced by the strength of mutualistic selection and the structural properties of the network where coevolution is unfolding. Second, the strength of mutualistic selection determines the network descriptors better correlated with higher trait matching. When coevolution is weak, network modularity enhances trait matching, but when it is strong, network connectance amplifies trait matching. Third, the structural properties of networks outrank those of modules or species in determining the evolved degree of trait matching. Our findings suggest networks can both enhance or constrain trait complementary, depending on the strength of mutualistic selection.
Establishment of a closed artificial ecosystem to ensure human long-term survival on the moon
Authors: Fu Yuming , Yi Zhihao , Du Yao , Liu Hui , Xie Beizhen , Liu Hong 
Published: January 2021

AbstractBioregenerative life support system (BLSS) is a critical technology maintaining long-term human survival on the Moon or other extraterrestrial bodies. In the current study, we carried out a 370-day integrated high-closure experiment (“Lunar Palace 365” experiment) on the Earth in an upgraded ground-based BLSS experimental facility called “Lunar Palace 1”. This experiment was designed to develop techniques to run and adjust system stability under long-term operation and crew shift change conditions. Eight volunteering crew members were divided into two groups with three time phases: Group I stayed in the cabin for the initial 60-day phase; Group II inhabited the cabin instead for a record-breaking duration of 200 days as the second phase; Group I re-entered the cabin, replaced Group II and stayed for the last 105 days. Our results demonstrated the BLSS had excellent stability with a material closure degree of 98.2%. Levels of O2, CO2and trace harmful gases were well controlled within ranges optimal for crew health and plant production. The system exhibited a strong robustness and could quickly minimize effects of disturbances through self-feedback adjustments. The efficiency of plant production completely met the crew’s need of plant-based food. The purification efficiency of domestic and sanitary wastewater was up to irrigation standards, and the recovery rate of urine and solid waste achieved 99.7% and 67%, respectively. These results are valuable for further optimization of the BLSS in a lunar base and computer simulations of similar systems.
Biomaterials direct functional B cell response in a material specific manner
Authors: Moore Erika M. , Maestas David R. , Cherry Chris C. , Garcia Jordan A. , Comeau Hannah Y. , Huyer Locke Davenport , Blosser Richard L. , Rosson Gedge D. , Elisseeff Jennifer H. 
Published: January 2021

AbstractB cells are an adaptive immune target of biomaterials development in vaccine research but despite their role in wound healing have not been studied in tissue engineering and regenerative medicine. We evaluated the B cell response to biomaterial scaffold materials implanted in a muscle wound; a biological extracellular matrix (ECM) and synthetic polyester polycaprolactone. In the local muscle tissue, small numbers of B cells are recruited in response to tissue injury and biomaterial implantation. ECM materials induced plasmablasts in lymph nodes and antigen presentation in the spleen while the synthetic PCL implants delayed B cell migration and induced an antigen presenting phenotype. In muMt−mice lacking B cells, the fibrotic response to the synthetic biomaterials decreased. Immunofluorescence confirmed antigen presenting B cells in fibrotic tissue surrounding silicone breast implants. In sum, the adaptive B cell immune response to biomaterial depends on composition and induces local, regional and systemic immunological changes.
Chicken peripheral blood lymphocyte response to ALV-J infection assessed by single-cell RNA sequencing
Authors: Dai Manman , Feng Min , Li Ziwei , Chen Weisan , Liao Ming 
Published: January 2021

ABSTRACTChicken peripheral blood lymphocytes (PBLs) exhibit wide-ranging cell types, but current understanding of their subclasses, immune cell classification, and function is limited and incomplete. Previously, we found that viremia caused by avian leukosis virus subgroup J (ALV‐J) was eliminated by 21 days post infection (DPI), accompanied by increased CD8+T cell ratio in PBLs and low antibody levels. Here we performed single-cell RNA sequencing (scRNA-seq) of PBLs in ALV-J infected and control chickens at 21 DPI to determine chicken PBL subsets and their specific molecular and cellular characteristics, before and after viral infection. Eight cell clusters and their potential marker genes were identified in chicken PBLs. T cell populations (clusters 6 and 7) had the strongest response to ALV-J infection at 21 DPI, based on detection of the largest number of differentially expressed genes (DEGs). T cell populations of clusters 6 and 7 could be further divided into four subsets: activated CD4+T cells (cluster A0), Th1-like cells (cluster A2), Th2-like cells (cluster A1), and cytotoxic CD8+T cells. Hallmark genes for each T cell subset response to viral infection were initially identified. Furthermore, pseudotime analysis results suggested that chicken CD4+T cells could potentially differentiate into Th1-like and Th2-like cells. Moreover, ALV-J infection probably induced CD4+T cell differentiation into Th1-like cells in which the most immune related DEGs were detected. With respect to the control group, ALV-J infection also had an obvious impact on PBL cell composition. B cells showed inconspicuous response and their numbers decreased in PBLs of the ALV-J infected chickens at 21 DPI. Percentages of cytotoxic Th1-like cells and CD8+T cells were increased in the T cell population of PBLs from ALV-J infected chicken, which were potentially key mitigating factors against ALV-J infection. More importantly, our results provided a rich resource of gene expression profiles of chicken PBL subsets for a systems-level understanding of their function in homeostatic condition as well as in response to viral infection.