bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep neural net tracking of human pluripotent stem cells reveals intrinsic behaviors directing morphogenesis
Authors: Joy David A. , Libby Ashley R. G. , McDevitt Todd C. 
Published: September 2020

AbstractLineage tracing is a powerful tool traditionally used in developmental biology to interrogate the evolutionary time course of tissue formation, but the dense, three-dimensional nature of tissue limits the ability to assemble individual traces into complete reconstructions of development. Human induced pluripotent stem cells (hiPSCs) enable recapitulation of various aspects of developmental processes, thereby providing anin vitroplatform to assess the dynamic collective behaviors directing tissue morphogenesis. Here, we trained an ensemble of independent convolutional neural networks to identify individual hiPSCs imaged via time lapse microscopy in order to generate longitudinal measures of individual cell and dense cellular neighborhood properties simultaneously on timescales ranging from minutes to days. Our analysis reveals that while individual cell parameters are not strongly affected by extracellular microenvironmental conditions such as pluripotency maintenance regime or soluble morphogenic cues, regionally specific cell behaviors change in a manner predictive of organization dynamics. By generating complete multicellular reconstructions of hiPSC behavior, our cell tracking pipeline enables fine-grained understanding of developmental organization by elucidating the role of regional behavior stratification in early tissue formation.
Subclinical ocular inflammation in persons recovered from ambulatory COVID-19
Authors: Bakhoum Mathieu F. , Ritter Michele , Garg Anupam K. , Chan Alison X , Bakhoum Christine Y. , Smith Davey M. 
Published: September 2020

ABSTRACTCoronavirus disease 2019 (COVID-19) is characterized by striking variability in clinical severity, and a hyperinflammatory response in the lung is associated with high mortality. Little is known about the extent and duration of inflammation in persons recovering from COVID-19. Here, we used spectral domain optical coherence tomography (SD-OCT) to detect the presence of inflammatory cells in the vitreous cavity, an immune-privileged microenvironment, in persons recovered from COVID-19. Our results provide quasi-histologic evidence that neuroinflammation is present in persons who recovered from COVID-19, only one of whom required hospitalization. Our results also suggest that persons who feel that their recovery is incomplete have evidence of subclinical eye inflammation, which may be a marker of residual inflammation elsewhere as well.
Performance of a universally offered prenatal screening program incorporating cfDNA in Ontario, Canada: a descriptive population-based cohort study of 280,000 pregnancies
Authors: Dougan Shelley D , Okun Nan , Bellai-Dussault Kara , Meng Lynn , Howley Heather E , Huang Tianhua , Reszel Jessica , Lanes Andrea , Walker Mark C , Armour Christine M 
Published: September 2020

AbstractObjectivesTo measure the population-based performance and impact of Ontario, Canada’s modified-contingent prenatal screening system for the detection of trisomies 21 (T21) and 18 (T18).DesignA retrospective, descriptive cohort study examining routinely collected data from BORN Ontario, which captures linkable population data for prenatal and neonatal health encounters across a variety of settings (e.g., laboratories, birthing hospitals and midwifery practice groups).SettingA province-wide and publicly funded prenatal screening program in Ontario, Canada offering cfDNA screening for those at increased risk of having a pregnancy with T21 or T18.Participants373,682 singleton pregnancies with an estimated due date between September 1 2016 and March 31, 2019 who were offered publicly funded prenatal screening.Main outcome measuresPrenatal detection of T21 or T18, ascertained by cytogenetic results. Performance was assessed by calculating sensitivity, specificity, positive predictive value and negative predictive value against confirmatory diagnostic cytogenetic results and birth outcomes. The secondary objective was to determine the impact of contingent cfDNA screening by measuring uptake and the proportion of T21 screen-positive pregnancies undergoing subsequent cfDNA screening and invasive prenatal diagnostic testing (PND).Results69% of pregnancies in Ontario underwent prenatal screening for T21/T18. The modified-contingent screen sensitivity was 89.9% for T21 and 80.5% for T18. The modified-contingent screen-positive rate was 1.6% for T21 and 0.2% for T18. The cfDNA screening test failure rate was 2.2% (final result including multiple attempts). The PND rate among pregnancies screened was 2.4%.ConclusionsThis study is the largest evaluation of population-based performance of a publicly funded cfDNA prenatal screening system. We demonstrated a robust screening system with high sensitivity and low PND consistent with smaller validation studies
Epidemiology and precision of SARS-CoV-2 detection following lockdown and relaxation measures
Authors: Leuzinger Karoline , Gosert Rainer , Søgaard Kirstine K. , Naegele Klaudia , Bielicki Julia , Roloff Tim , Bingisser Roland , Nickel Christian H. , Khanna Nina , Sutter Sarah Tschudin , Widmer Andreas F. , Rentsch Katharina , Pargger Hans , Siegemund Martin , Stolz Daiana , Tamm Michael , Bassetti Stefano , Osthoff Michael , Battegay Manuel , Egli Adrian , Hirsch Hans H. 
Published: September 2020

AbstractIntroductionSARS-CoV-2-detection is critical for clinical and epidemiological assessment of the ongoing CoVID-19 pandemic.AimTo cross-validate manual and automated high-throughput (Roche-cobas®6800-Target1/Target2) testing for SARS-CoV-2-RNA, to describe detection rates following lockdown and relaxation, and to evaluate SARS-CoV-2-loads in different specimens.MethodThe validation cohort prospectively compared Basel-S-gene, Roche-E-gene, and Roche-cobas®6800-Target1/Target2 in 1344 naso-oropharyngeal swabs (NOPS) taken in calendar week 13 using Basel-ORF8-gene-assay for confirmation. Follow-up-cohort-1 and -2 comprised 12363 and 10207 NOPS taken over 10 weeks until calendar week 24 and 34, respectively. SARS-CoV-2-loads were compared in follow-up NOPS, lower respiratory fluids, and plasma.ResultsConcordant results were obtained in 1308 cases (97%) including 97 (9%) SARS-CoV-2-positives showing high quantitative correlations (Spearman r>0.95; p<0.001) for all assays. Discordant samples (N=36) had significantly lower SARS-CoV-2-loads (p<0.001). Following lockdown, weekly detection rates declined to <1% reducing single-test positive predictive values from 99.3% to 85.1%. Following relaxation, rates flared up to 4% with similarly high SARS-CoV-2-loads, but patients were significantly younger than during lockdown (34 vs 52 years, p<0.001). SARS-CoV-2-loads in follow-up NOPS declined by 3log10 copies/mL within 10 days post-diagnosis (p<0.001). SARS-CoV-2-loads in NOPS correlated weakly with those in time-matched lower respiratory fluids and plasma, but remained detectable in 14 and 7 cases of NOPS with undetectable SARS-CoV-2, respectively.ConclusionEvaluated manual and automated assays are highly concordant and correlate quantitatively. Following successful lockdown, declining positive predictive values require dual-target-assays for clinical and epidemiologic assessment. Confirmatory and quantitative follow-up testing should be considered within <5 days, using lower respiratory fluids in symptomatic patients with SARS-CoV-2-negative NOPS.
Optimal Dynamic Prioritization of Scarce COVID-19 Vaccines
Authors: Buckner Jack H. , Chowell Gerardo , Springborn Michael R. 
Published: September 2020

AbstractMultiple promising COVID-19 vaccines are under rapid development, with deployment of the initial supply expected by 2021. Careful design of a vaccine prioritization strategy across socio-demographic groups is an imminent and crucial public policy challenge given that (1) the eventual vaccine supply will be highly constrained for at least the first several months of the vaccination campaign, and (2) there are stark differences in transmission and severity of impacts from SARS-CoV-2 across groups. Previous experience with vaccine development mid-pandemic offers limited insights for SARS-CoV-2 prioritization: SARS and Zika vaccine development was incomplete when those outbreaks ended and the epidemiology of endemic human influenza viruses differ substantially from that of SARS-CoV-2. We assess the optimal allocation of a limited and dynamic COVID-19 vaccine supply in the U.S. across socio-demographic groups differentiated by age and essential worker status. The transmission dynamics are modeled using a compartmental (SEIR) model parameterized to capture our current understanding of the transmission and epidemiological characteristics of COVID-19, including key sources of group heterogeneity (susceptibility, severity, and contact rates). We investigate tradeoffs between three alternative policy objectives: minimizing infections, years of life lost, or deaths. Moreover, we model dynamic vaccine prioritization policies that respond to changes in the epidemiological status of the population as SARS-CoV-2 continues its march. Because contacts tend to be concentrated within age groups, there is diminishing marginal returns as vaccination coverage increases in a given group, increasing the group’s protective immunity against infection and mortality. We find that optimal prioritization consistently targets older essential workers. However, depending on the policy objective, younger essential workers are prioritized to minimize infections or seniors in order to minimize mortality. Optimal prioritization outperforms non-targeted vaccination strategies by up to 18% depending on the outcome optimized. For example, in our baseline model, cumulative mortality decreased on average by 17% (25,000 deaths in the U.S. population) over the course of the outbreak.
A Cost Analysis of Childbirth for Pregnant Women with COVID-19 in Nigeria’s Epicentre
Authors: Banke-Thomas Aduragbemi , Makwe Christian Chigozie , Balogun Mobolanle , Afolabi Bosede Bukola , Alex-Nwangwu Theresa Amaogechukwu , Ameh Charles Anawo 
Published: September 2020

AbstractThe Coronavirus disease 2019 (COVID-19) has been a major disruptor of health systems globally. Its emergence has warranted the need to reorganize maternity services for childbirth. However, it is not known if this comes at an additional cost to women. We conducted a hospital-based cost analysis to estimate the out-of-pocket cost of spontaneous vaginal delivery (SVD) and caesarean delivery (CD). Specifically, we collected facility-based and household costs of all nine pregnant women with COVID-19 who were managed between 1st April and 30th August 2020 at the largest teaching hospital in Lagos, the epicentre of COVID-19 in Nigeria. We compared the mean facility-based costs for the cohort with costs paid by pregnant women pre-COVID-19, identifying major cost drivers. We also estimated what would have been paid without subsidies, testing assumptions with a sensitivity analysis. Findings showed that total utilization cost ranged from US$494 (N190,150) for SVD with mild COVID-19 to US$4,553 (N1,751,165) for emergency CD with severe COVID-19. Though 32-66% of facility-based cost has been subsidized, cost of SVD and CD have doubled and tripled respectively during the pandemic compared to those paid pre-COVID. Out of the facility-based costs paid, cost of personal protective equipment (PPE) was the major cost driver (50%) for SVD and CD. Supplemental oxygen was a major cost driver when women had severe COVID-19 symptoms and required long admission (48%). Excluding treatment costs specifically for COVID-19, mean facility-based costs for SVD and CD are US$228 (N87,750) and US$948 (N364,551) respectively. Our study demonstrates that despite cost exemptions and donations, utilization costs remain prohibitive. Regulation of the PPE and medical oxygen supply chain can help drive down utilization cost and reduce mark-ups being passed to users. The pandemic offers an opportunity to expand advocacy for subscription to health insurance schemes in order to avoid any catastrophic health expenditure.KEY MESSAGESTotal utilization cost ranged from US$494 (N190,150) for spontaneous vaginal delivery with mild COVID-19 to US$4,553 (N1,751,165) for emergency caesarean delivery with severe COVID-19.Cost of personal protective equipment was the major cost driver (50%) for vaginal and elective caesarean deliveries. Medical oxygen was a major cost driver when women had severe COVID-19 symptoms (48%) and required long admission.Though 32-66% of total cost have been subsidized, facility-based cost of vaginal and caesarean deliveries has doubled and tripled respectively during the pandemic compared to those paid pre-COVID.The study findings highlight the urgent need to implement strategies that can help to minimize the rising costs that pregnant women with COVID-19 face in accessing and utilizing critical intra-partum care.
Delayed viral clearance and exacerbated airway hyperinflammation in hypertensive COVID-19 patients
Authors: Trump Saskia , Lukassen Soeren , Anker Markus S. , Chua Robert Lorenz , Liebig Johannes , Thürmann Loreen , Corman Victor , Binder Marco , Loske Jennifer , Klasa Christina , Krieger Teresa , Hennig Bianca P. , Messingschlager Marey , Pott Fabian , Kazmierski Julia , Twardziok Sven , Albrecht Jan Philipp , Eils Jürgen , Hadzibegovic Sara , Lena Alessia , Heidecker Bettina , Goffinet Christine , Kurth Florian , Witzenrath Martin , Völker Maria Theresa , Müller Sarah Dorothea , Liebert Uwe Gerd , Ishaque Naveed , Kaderali Lars , Sander Leif-Erik , Laudi Sven , Drosten Christian , Eils Roland , Conrad Christian , Landmesser Ulf , Lehmann Irina 
Published: September 2020

AbstractIn COVID-19, hypertension and cardiovascular diseases have emerged as major risk factors for critical disease progression. Concurrently, the impact of the main anti-hypertensive therapies, angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARB), on COVID-19 severity is controversially discussed. By combining clinical data, single-cell sequencing data of airway samples andin vitroexperiments, we assessed the cellular and pathophysiological changes in COVID-19 driven by cardiovascular disease and its treatment options. Anti-hypertensive ACEi or ARB therapy, was not associated with an altered expression of SARS-CoV-2 entry receptorACE2in nasopharyngeal epithelial cells and thus presumably does not change susceptibility for SARS-CoV-2 infection. However, we observed a more critical progress in COVID-19 patients with hypertension associated with a distinct inflammatory predisposition of immune cells. While ACEi treatment was associated with dampened COVID-19-related hyperinflammation and intrinsic anti-viral responses, under ARB treatment enhanced epithelial-immune cell interactions were observed. Macrophages and neutrophils of COVID-19 patients with hypertension and cardiovascular comorbidities, in particular under ARB treatment, exhibited higher expression ofCCL3, CCL4, and its receptorCCR1, which associated with critical COVID-19 progression. Overall, these results provide a potential explanation for the adverse COVID-19 course in patients with cardiovascular disease, i.e. an augmented immune response in critical cells for the disease course, and might suggest a beneficial effect of clinical ACEi treatment in hypertensive COVID-19 patients.
An analysis of clinical and geographical metadata of over 75,000 records in the GISAID COVID-19 database
Authors: Velazquez Anjelina , Bustria Mhealyssah , Ouyang Youwen , Moshiri Niema 
Published: September 2020

AbstractDuring the SARS-CoV-2 outbreak that caused the coronavirus pandemic it is important now more than ever that scientists and public health officials work side-by-side and use their available resources to track patient information from those that have been affected by the novel coronavirus. The ability to track the disease helps identify possible trends and patterns that can be used by public health officials to make more informed decisions. Tracking data like this may be the key to helping states and countries safely re-open. However, when analyzing large collections of data there is the occurrence of confounding factors such as biases in patient sampling. In this project, a massive collection of COVID-19 data was analyzed, and explored potential biases in patient sampling were explored.
APPLAUSE: Automatic Prediction of PLAcental health via U-net Segmentation and statistical Evaluation
Authors: Pietsch Maximilian , Ho Alison , Bardanzellu Alessia , Zeidan Aya Mutaz Ahmad , Chappell Lucy C. , Hajnal Joseph V. , Rutherford Mary , Hutter Jana 
Published: September 2020

PurposeArtificial-intelligence population-based automated quantification of placental maturation and health from a rapid functional Magnetic Resonance scan. The placenta plays a crucial role for any successful human pregnancy. Deviations from the normal dynamic maturation throughout gestation are closely linked to major pregnancy complications. Antenatal assessment in-vivo using T2* relaxometry has shown great promise to inform management and possible interventions but clinical translation is hampered by time consuming manual segmentation and analysis techniques based on comparison against normative curves over gestation.MethodsThis study proposes a fully automatic pipeline to predict the biological age and health of the placenta based on a rapid (sub-30 second) T2* scan in two steps: Automatic segmentation using a U-Net and a Gaussian Process regression model to characterize placental maturation and health. These are trained and evaluated on 110 3T MRI placental data sets including 20 high-risk pregnancies diagnosed with pre-eclampsia and/or fetal growth restriction.ResultsAutomatic segmentation achieves comparable performance to human experts (mean DICE coefficients automatic-manual 0.76, Pearson Correlation Coefficient 0.986 for mean T2* within the masks). The placental health prediction achieves an excellent ability to differentiate early cases of placental in-sufficiency before 32 weeks. High abnormality scores correlate with low birth weight, premature birth and histopathological findings. Retrospective application on a different cohort imaged at 1.5T illustrates the ability for direct clinical translation.ConclusionThe presented automatic pipeline facilitates a fast, robust and reliable prediction of placental maturation. It yields human-interpretable and verifiable intermediate results and quantifies uncertainties on the cohort-level and for individual predictions. The proposed machine-learning pipeline runs in close to real-time and, deployed in clinical settings, has the potential to become a cornerstone of diagnosis and intervention of placental insufficiency.
Empirical transmission advantage of the D614G mutant strain of SARS-CoV-2
Authors: Leung Kathy , Pei Yao , Leung Gabriel M , Lam Tommy TY , Wu Joseph T 
Published: September 2020

AbstractThe SARS-CoV-2 lineage carrying the amino acid change D614G has become the dominant variant in the global COVID-19 pandemic. The rapid spread of the G614 mutant suggests that it may have a transmission advantage over the D614 wildtype. Using our previous epidemiological framework to analyze COVID-19 surveillance and sequence data, we estimated that the G614 mutant is 31% (28-34%) more transmissible than the D614 wildtype. As such, interventions that were previously effective in containing or mitigating the D614 wildtype (e.g. in China, Vietnam, Thailand, etc.) might be less effective against the G614 mutant. Our framework can be readily integrated into current COVID-19 surveillance to monitor the emergence and fitness of mutant strains, such that pandemic surveillance, disease control and development of treatment and vaccines can be adjusted dynamically.
Quantification of abdominal fat from computed tomography using deep learning and its association with electronic health records in an academic biobank
Authors: MacLean Matthew T. , Jehangir Qasim , Vujkovic Marijana , Ko Yi-An , Litt Harold , Borthakur Arijitt , Sagraiya Hersh , Rosen Mark , Mankoff David A. , Schnall Mitchell D. , Shou Haochang , Chirinos Julio , Damrauer Scott M. , Torigian Drew A. , Carr Rotonya , Rader Daniel J. , Witschey Walter R. 
Published: September 2020

AbstractObjectiveThe objective was to develop a fully automated algorithm for abdominal fat segmentation and deploy this method at scale and associated with diagnoses in an academic biobank.Materials and MethodsWe built a fully automated image curation and labeling technique using deep learning and distributive computing to identify subcutaneous and visceral abdominal fat compartments from 47,587 CT scans in 13,422 patients in the Penn Medicine Biobank (PMBB). A classification network identified the inferior and superior borders of the abdomen, and a segmentation network differentiated visceral and subcutaneous fat. Following technical evaluation of our method, we conducted studies to validate known relationships with adiposity.ResultsWhen compared with 100 manually annotated cases, the classification network was on average within one 5 mm slice for both the superior (0.3±0.6 slices) and inferior (0.7±0.6 slices) borders. The segmentation network also demonstrated excellent performance with interclass correlation coefficients of 0.99 (p<2e-16) for subcutaneous and 0.99 (p<2e-16) for visceral fat on 100 testing cases. We performed integrative analyses of abdominal fat with the phenome extracted from the electronic health record and found highly significant associations with diabetes mellitus, hypertension, renal failure, among other phenotypes.ConclusionThis work presents a fully automated and highly accurate method for the quantification of abdominal fat that can be applied to routine clinical imaging studies to fuel translation scientific discovery.
Exploratory and confirmatory factor analysis of the Cognitive Social Capital Scale in a Colombian sample
Authors: Campo-Arias Adalberto , Caballero-Domínguez Carmen Cecilia , Pedrozo-Pupo John Carlos 
Published: September 2020

SUMMARYDuring the last two decades, the concept of social capital has been used with increasing frequency in health sciences due to the direct and indirect relationships between social capital and populations’ physical and mental health. Therefore, it is necessary to build an instrument to quantify this concept confidently and reliably. The study aimed to perform exploratory and confirmatory factor analyses on a seven-item scale to measure social capital in adults of Colombia’s general population. An online validation study was done, including a sample of 700 adults aged between 18 and 76 years; 68% were females. Participants completed a seven-item scale called the Cognitive Social Capital Scale (CSCS). Cronbach’s alpha and McDonald’s omega were computed to test internal consistency. Exploratory and confirmatory factor analyses were conducted to explore the dimensionality of the CSCS. The CSCS presented a low internal consistency (Cronbach’s alpha of 0.56 and McDonald’s omega of 0.59) and poor dimensionality. Then, a five-item version (CSCS-5) was tested. The CSCS-5 showed high internal consistency (Cronbach’s alpha of 0.79 and McDonald’s omega of 0.80) and a one-dimension structure with acceptable goodness-of-fit indicators. In conclusion, the CSCS-5 presents high internal consistency and a one-dimension structure to measure cognitive capital social in Colombian sample. It can be recommended for the measuring of social capital in the general Colombian population. Further research should corroborate these findings on pencil and paper applications and explore other reliability and validity indicators.