bluuebunny/crossref_metadata_2025 huggingface dataset:
Electronic trauma resuscitation documentation and decision support using T6 Health Systems Mobile Application: A combat trauma center pilot program
Authors: Angotti Lisa M. , How Remealle A. , Barnack Katie R. , Aden James K. , Vitale Dominick A. , Folwell Jared S. , Neel Jason M. , Srivilasa Charlie N. , Sams Valerie G.
Published: August 2020

BACKGROUND

The care of trauma patients in combat operations is handwritten on a five-page flow sheet. The process requires the manual scanning and uploading of paper documents to bridge the gap between electronic and paper record management. There is an urgent operational need for an information technology solution that will enable medics to better capture patient treatment information, which will improve long-term health care without impacting short-term care responsibilities.

METHODS

We conducted a process improvement project to evaluate the ability of T6 Health Systems Mobile Application to improve combat casualty care data collection at a deployed trauma hospital. We performed a head-to-head comparison of the completeness and accuracy of data capture of electronic versus handwritten records to determine noninferiority.

RESULTS

During the 90-day pilot, there were 131 trauma evaluations of which 53 casualty resuscitations (40.5%) were also documented in the electronic application. We compared completeness and accuracy of admit, prehospital, primary survey, secondary survey, interventions, and trends data. We found an overall 13% increase in data capture at 96% accuracy compared with the written record, suggesting that the electronic record was superior. Completion of electronic documentation compared with paper by section was statistically significantly higher for admitting data, 119.7% (p < 0.0001); prehospital, 116.2% (p = 0.0039); primary, 109.6% (p < 0.001); and secondary, 125.5% (p < 0.001). We also had the medical evacuation teams document prehospital and en route care and then synchronize the record in the trauma bay, allowing the trauma teams there to continue documenting on the same casualty record, likely contributing to superiority because teams did not have to redocument based on an oral report.

CONCLUSION

Our pilot program in the deployed environment demonstrated a mobile technology that actually enhanced the completeness and accuracy of paper trauma documentation that has the capability of providing patient-specific decision support and real-time data analysis.

LEVEL OF EVIDENCE

Care Management, level IV.
Ancient crested penguin constrains timing of recruitment into seabird hotspot
Authors: Thomas Daniel B. , Tennyson Alan J. D. , Scofield R. Paul , Heath Tracy A. , Pett Walker , Ksepka Daniel T.
Published: August 2020

New Zealand is a globally significant hotspot for seabird diversity, but the sparse fossil record for most seabird lineages has impeded our understanding of how and when this hotspot developed. Here, we describe multiple exceptionally well-preserved specimens of a new species of penguin from tightly dated (3.36–3.06 Ma) Pliocene deposits in New Zealand. Bayesian and parsimony analyses place
Eudyptes atatu
sp. nov. as the sister species to all extant and recently extinct members of the crested penguin genus
Eudyptes
. The new species has a markedly more slender upper beak and mandible compared with other
Eudyptes
penguins. Our combined evidence approach reveals that deep bills evolved in both crested and stiff-tailed penguins (
Pygoscelis
) during the Pliocene. That deep bills arose so late in the greater than 60 million year evolutionary history of penguins suggests that dietary shifts may have occurred as wind-driven Pliocene upwelling radically restructured southern ocean ecosystems. Ancestral area reconstructions using BioGeoBEARS identify New Zealand as the most likely ancestral area for total-group penguins, crown penguins and crested penguins. Our analyses provide a timeframe for recruitment of crown penguins into the New Zealand avifauna, indicating this process began in the late Neogene and was completed via multiple waves of colonizing lineages.
Machine Learning Applied to Clinical Laboratory Data Predicts Patient-Specific, Near-Term Relapse in Patients in Medication for Opioid Use Disorder Treatment
Authors: Pyzowski Paul , Herbert Barbara , Malik Wasim Q
Published: August 2020

We have developed a data-driven, algorithmic method for identifying patients in an out-patient buprenorphine program at high risk for relapse in the following seven days. This method uses data already available in clinical laboratory data, can be made available in a timely matter, and is easily understandable and actionable by clinicians. Use of this method could significantly reduce the rate of relapse in addiction treatment programs by targeting interventions at those patients most at risk for near term relapse.
Etiological Profile and Resistance of Bacterial Isolates from Samples of Cerebrospinal Fluid in Kosovo, during the years 2014-2019
Authors: Qarkaxhija Rita
Published: August 2020

Cerebrospinal fluid is a dynamic, metabolically active substance that has numerous important functions. It is considered a valuable diagnostic aid in assessing infectious inflammatory conditions, involving the brain, spinal cord, and meninges.

The discovery and use of antimicrobial agents has fundamentally changed medicine from a therapeutic point of view, enabling the treatment of many diseases once considered threatening and deadly. However, after prolonged exposure of various microorganisms to these agents, the development of antimicrobial resistance has been enabled through the adaptive selection mechanism. The emergence of this resistance in the main pathogenic microorganisms is a very problematic and threatening issue in public health, making it a global problem. Resistance of various microorganisms in Kosovo, according to annual reports of CAESAR, compared to other European countries, is quite worrying. It reaches the tops of the lists for high resistance, along with other Balkan countries, such as Serbia, Montenegro, and North Macedonia.

The purpose of this research was to define the etiology and level of resistance of microorganisms to antimicrobial agents, which are encountered in invasive samples of cerebrospinal fluid. This research is a retrospective, descriptive type analysis, which includes the data gathered from January 1, 2014 to May 7, 2019. We have a total of 185 bacteria isolated from 1499 isolates, conducted at the National Institute of Public Health in Kosovo. The determination of antimicrobial resistance was performed according to automated systems and the method of disk diffusion.
Face Coverings and Respiratory Tract Droplet Dispersion
Authors: Bandiera Lucia , Pavar Geethanjali , Pisetta Gabriele , Otomo Shuji , Mangano Enzo , Seckl Jonathan R. , Digard Paul , Molinari Emanuela , Menolascina Filippo , Viola Ignazio Maria
Published: August 2020

Respiratory droplets are the primary transmission route for SARS-CoV-2. Evidence suggests that virus transmission can be reduced by face coverings, but robust evidence for how mask usage might affect safe distancing parameters is lacking. Accordingly, we investigate the effectiveness of surgical masks and single-layer cotton masks on mitigating dispersion of large respiratory droplets (i.e. non aerosol). We tested a manikin ejecting fluorescent droplets and human volunteers in speaking and coughing conditions. We quantified the number of droplets in flight using laser sheet illumination and UV-light for those that had landed at table height at up to 2m. For human volunteers, expiratory droplets were caught on a microscope slide 5cm from the mouth. Whether manikin or human, wearing a face covering decreased the number of projected droplets by >1000-fold. We estimated that a person standing 2m from someone coughing without a mask is exposed to over 1000 times more respiratory droplets than from someone standing 5 cm away wearing a basic single layer mask. Our results indicate that face coverings show consistent efficacy at blocking respiratory droplets. If aerosol transmission is later determined to be a significant driver of infection, then our findings may overestimate the effectiveness of face coverings.
ACE2 expression in adipose tissue is associated with COVID-19 cardio-metabolic risk factors and cell type composition
Authors: El-Sayed Moustafa Julia S. , Jackson Anne U. , Brotman Sarah M. , Guan Li , Villicaña Sergio , Roberts Amy L. , Zito Antonino , Bonnycastle Lori , Erdos Michael R. , Narisu Narisu , Stringham Heather M. , Welch Ryan , Yan Tingfen , Lakka Timo , Parker Stephen , Tuomilehto Jaakko , Collins Francis S. , Pajukanta Päivi , Boehnke Michael , Koistinen Heikki A. , Laakso Markku , Falchi Mario , Bell Jordana T. , Scott Laura J. , Mohlke Karen L. , Small Kerrin S.
Published: August 2020

COVID-19 severity has varied widely, with demographic and cardio-metabolic factors increasing risk of severe reactions to SARS-CoV-2 infection, but the underlying mechanisms for this remain uncertain. We investigated phenotypic and genetic factors associated with subcutaneous adipose tissue expression of Angiotensin I Converting Enzyme 2 (ACE2), which has been shown to act as a receptor for SARS-CoV-2 cellular entry. In a meta-analysis of three independent studies including up to 1,471 participants, lower adipose tissue ACE2 expression was associated with adverse cardio-metabolic health indices including type 2 diabetes (T2D) and obesity status, higher serum fasting insulin and BMI, and lower serum HDL levels (P<5.32×10-4). ACE2 expression levels were also associated with estimated proportions of cell types in adipose tissue; lower ACE2 expression was associated with a lower proportion of microvascular endothelial cells (P=4.25×10-4) and higher macrophage proportion (P=2.74×10-5), suggesting a link to inflammation. Despite an estimated heritability of 32%, we did not identify any proximal or distal genetic variants (eQTLs) associated with adipose tissue ACE2 expression. Our results demonstrate that at-risk individuals have lower background ACE2 levels in this highly relevant tissue. Further studies will be required to establish how this may contribute to increased COVID-19 severity.
Lower respiratory tract myeloid cells harbor SARS-CoV-2 and display an inflammatory phenotype
Authors: Bain William , Peñaloza Hernán F. , Ladinsky Mark S. , van der Geest Rick , Sullivan Mara , Ross Mark , Kitsios Georgios D. , Methe Barbara , McVerry Bryan J. , Morris Alison , Watson Alan M. , Watkins Simon C. , St Croix Claudette M. , Stolz Donna B. , Bjorkman Pamela J. , Lee Janet S.
Published: August 2020

SARS-CoV-2 pneumonia may induce an aberrant immune response with brisk recruitment of myeloid cells into the lower respiratory tract, which may contribute to morbidity and mortality. We describe endotracheal aspirate samples from seven patients with SARS-CoV-2 pneumonia requiring mechanical ventilation. We note SARS-CoV-2 virions within lower respiratory tract myeloid cells shown by electron tomography, immunofluorescence confocal imaging, and immuno-electron microscopy. Endotracheal aspirates are primarily composed of mononuclear and polymorphonuclear leukocytes. These myeloid cells that harbor virus are frequently positive for CD14 and/or CD16 and most display an inflammatory phenotype marked by expression of IL-6 and tissue factor mRNA transcript and protein expression.
Classification of 12-lead ECGs: the PhysioNet/Computing in Cardiology Challenge 2020
Authors: Alday Erick Andres Perez , Gu Annie , Shah Amit , Robichaux Chad , Wong An-Kwok Ian , Liu Chengyu , Liu Feifei , Rad Ali Bahrami , Elola Andoni , Seyedi Salman , Li Qiao , Sharma Ashish , Clifford Gari D. , Reyna Matthew A.
Published: August 2020

The subject of the PhysioNet/Computing in Cardiology Challenge 2020 was the identification of cardiac abnormalities in 12-lead electrocardiogram (ECG) recordings. A total of 66,405 recordings were sourced from hospital systems from four distinct countries and annotated with clinical diagnoses, including 43,101 annotated recordings that were posted publicly.

For this Challenge, we asked participants to design working, open-source algorithms for identifying cardiac abnormalities in 12-lead ECG recordings. This Challenge provided several innovations. First, we sourced data from multiple institutions from around the world with different demographics, allowing us to assess the generalizability of the algorithms. Second, we required participants to submit both their trained models and the code for reproducing their trained models from the training data, which aids the generalizability and reproducibility of the algorithms. Third, we proposed a novel evaluation metric that considers different misclassification errors for different cardiac abnormalities, reflecting the clinical reality that some diagnoses have similar outcomes and varying risks.

Over 200 teams submitted 850 algorithms (432 of which successfully ran) during the unofficial and official phases of the Challenge, representing a diversity of approaches from both academia and industry for identifying cardiac abnormalities. The official phase of the Challenge is ongoing.
Is Blood Type Associated with COVID-19 Severity?
Authors: Mendy Angelico , Keller Jason L. , Apewokin Senu , Morrow Ardythe L.
Published: August 2020

Blood type purportedly influences susceptibility to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, but whether it affects severity of coronavirus disease 2019 (COVID-19) is unclear. Therefore, we examined the association of blood type and rhesus with hospitalization and disease severity among 428 COVID-19 patients diagnosed at the University of Cincinnati health system. In the sample, 50.2% of participants had the blood type O, 38.7% had the blood type A, 17.5% had the blood type B, and 3.5% had the blood type AB. In analysis adjusted for sociodemographic characteristics and comorbidities, the blood types A (OR: 0.90, 95% CI: 0.54, 1.50), B (OR: 0.93, 95% CI: 0.51, 1.69), AB (OR: 0.69, 95% CI: 0.20, 2.41), and O (OR: 1.18, 95%: 0.74, 1.98) were not associated with hospitalization for COVID-19. Similarly, the blood types A (OR: 0.93, 95% CI: 0.52, 1.65), B (OR: 0.92, 95% CI: 0.46, 1.84), AB (OR: 0.30, 95% CI: 0.04, 2.44), and O (OR: 1.25, 95%: 0.73, 2.14) were not associated with admission to intensive care unit or death in COVID-19. In conclusion, blood type is not associated with hospitalization or disease severity in COVID-19; therefore, it may not be useful marker for identifying patients at risk for severe COVID-19.
Clinical, Laboratory, and Imaging Features of 148 Patients with COVID-19 in Bushehr: A Report from the South of Iran
Authors: Keshavarz Mohsen , Tavakoli Ahmad , Zanganeh Sareh , Mousavi Mohammad Javad , Vahdat Katayoun , Mahmudpour Mehdi , Nabipour Iraj , Darabi Amir Hossein , Keshmiri Saeid
Published: August 2020

Aim

To investigate clinical characteristics, laboratory findings, and imaging features of patients confirmed with COVID-19 in Bushehr, a southern province of Iran.

Method

During April 29th to May 30th 2020, a total of 148 patients confirmed with COVID-19 infection were admitted to three hospitals in Bushehr province, assigned by the Iranian Ministry of Health.

Results

The most common coexisting disease was type 2 diabetes. Levels of ESR, CRP, LDH, and AST among inpatients were higher than the outpatients (P<0.05). There were significant differences in the levels of creatinine and BUN between elderly and non-elderly patients (P<0.05).

Conclusion

Patients with comorbidities and elderly patients are at increased risk of severe progression of COVID-19.
Federated Learning of Electronic Health Records Improves Mortality Prediction in Patients Hospitalized with COVID-19
Authors: Vaid Akhil , Jaladanki Suraj K , Xu Jie , Teng Shelly , Kumar Arvind , Lee Samuel , Somani Sulaiman , Paranjpe Ishan , Freitas Jessica K De , Wanyan Tingyi , Johnson Kipp W , Bicak Mesude , Klang Eyal , Kwon Young Joon , Costa Anthony , Zhao Shan , Miotto Riccardo , Charney Alexander W , Böttinger Erwin , Fayad Zahi A , Nadkarni Girish N , Wang Fei , Glicksberg Benjamin S
Published: August 2020

Machine learning (ML) models require large datasets which may be siloed across different healthcare institutions. Using federated learning, a ML technique that avoids locally aggregating raw clinical data across multiple institutions, we predict mortality within seven days in hospitalized COVID-19 patients. Patient data was collected from Electronic Health Records (EHRs) from five hospitals within the Mount Sinai Health System (MSHS). Logistic Regression with L1 regularization (LASSO) and Multilayer Perceptron (MLP) models were trained using local data at each site, a pooled model with combined data from all five sites, and a federated model that only shared parameters with a central aggregator. Both the federated LASSO and federated MLP models performed better than their local model counterparts at four hospitals. The federated MLP model also outperformed the federated LASSO model at all hospitals. Federated learning shows promise in COVID-19 EHR data to develop robust predictive models without compromising patient privacy.
Lockdown Measures and their Impact on Single- and Two-age-structured Epidemic Model for the COVID-19 Outbreak in Mexico
Authors: Cuevas-Maraver J. , Kevrekidis P. G. , Chen Q. Y. , Kevrekidis G. A. , Villalobos-Daniel Víctor , Rapti Z. , Drossinos Y.
Published: August 2020

The role of lockdown measures in mitigating COVID-19 in Mexico is investigated using a comprehensive nonlinear ODE model. The model includes both asymptomatic and presymptomatic populations with the latter leading to sickness (with recovery, hospitalization and death possibilities). We consider situations involving the application of social-distancing and other intervention measures in the time series of interest. We find optimal parametric fits to the time series of deaths (only), as well as to the time series of deaths and cumulative infections. We discuss the merits and disadvantages of each approach, we interpret the parameters of the model and assess the realistic nature of the parameters resulting from the optimization procedure. Importantly, we explore a model involving two sub-populations (younger and older than a specific age), to more accurately reflect the observed impact as concerns symptoms and behavior in different age groups. For definiteness and to separate people that are (typically) in the active workforce, our partition of population is with respect to members younger vs. older than the age of 65. The basic reproduction number of the model is computed for both the single- and the two-population variant. Finally, we consider what would be the impact of partial lockdown (involving only the older population) and full lockdown (involving the entire population) on the number of deaths and cumulative infections.
Drawing transmission graphs for COVID-19 in the perspective of network science
Authors: Gürsakal N. , Batmaz B. , Aktuna G.
Published: August 2020

When we consider a probability distribution about how many COVID-19 infected people will transmit the disease, two points become important. First, there should be super-spreaders in these distributions/networks and secondly, the Pareto principle should be valid in these distributions/networks. When we accept that these two points are valid, the distribution of transmission becomes a discrete Pareto distribution, which is a kind of power law. Having such a transmission distribution, then we can simulate COVID-19 networks and find super-spreaders using the centricity measurements in these networks. In this research, in the first we transformed a transmission distribution of statistics and epidemiology into a transmission network of network science and secondly we try to determine who the super-spreaders are by using this network and eigenvalue centrality measure. We underline that determination of transmission probability distribution is a very important point in the analysis of the epidemic and determining the precautions to be taken.
Development of a duplex real-time PCR assay for the differentiation ofBlastomyces dermatitidisandB. gilchristiiand a retrospective study of blastomycosis in New York (2005-2019)
Authors: Kaplan Mitchell , Zhu YanChun , Kus Julianne V , McTaggart Lisa , Chaturvedi Vishnu , Chaturvedi Sudha
Published: August 2020

Blastomycosis due toBlastomyces dermatitidisandB. gilchristiiis a notable cause of respiratory mycoses in North America with recurrent outbreaks. We developed a highly sensitive, specific, and reproducible Taqman duplex real-time PCR assay for the differentiation ofB. dermatitidisandB. gilchristii. The new assay permitted retrospective analysis ofBlastomycescultures (2005 to 2019), and primary clinical specimens (2013-2019) from NY patients.Blastomyces dermatitidiswas the causal agent for the majority of 38 cases whileB. gilchristiiwas implicated in five cases; a rare finding reported from New York. The duplex real-time PCR assay will be useful for further understanding of ecology and epidemiology of blastomycosis caused byB. dermatitidisandB. gilchristii.
Clinical Explainability Failure (CEF) & Explainability Failure Ratio (EFR) – changing the way we validate classification algorithms?
Authors: Venugopal V. , Takhar R. , Gupta S. , Saboo A. , Mahajan V.
Published: August 2020

Adoption of Artificial Intelligence (AI) algorithms into the clinical realm will depend on their inherent trustworthiness, which is built not only by robust validation studies but is also deeply linked to the explainability and interpretability of the algorithms. Most validation studies for medical imaging AI report performance of algorithms on study-level labels and lay little emphasis on measuring the accuracy of explanations generated by these algorithms in the form of heat maps or bounding boxes, especially in true positive cases. We propose a new metric – Explainability Failure Ratio (EFR) – derived from Clinical Explainability Failure (CEF) to address this gap in AI evaluation. We define an Explainability Failure as a case where the classification generated by an AI algorithm matches with study-level ground truth but the explanation output generated by the algorithm is inadequate to explain the algorithms output. We measured EFR for two algorithms that automatically detect consolidation on chest X-rays to determine the applicability of the metric and observed a lower EFR for the model that had lower sensitivity for identifying consolidation on chest X-rays, implying that trustworthiness of a model should be determined not only by routine statistical metrics but also by novel ‘clinically-oriented’ models.
Observational Study on Clinical Features, Treatment and Outcome of COVID 19 in a tertiary care Centre in India- a retrospective case series
Authors: Bhattacharya Raja , Ghosh Rohini , Kulshrestha Manish , Chowdhury Sampurna , Mukherjee Rishav , Ray Indranil
Published: August 2020

Objective

This study will attempt to explore the demographic profile and outcome in the patients receiving multidisciplinary, personalised approach including use of Broad Spectrum Antivirals - Ivermectin, anti-inflammatory and antioxidants roles of Statins and N-acetyl-cysteine along with Standard of Care (SOC) in hospitalised COVID19 patients in a tertiary care centre.

Setting

Inpatient department

Participants

191 COVID-19 patients with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in the year 2020 between June 14-28, 2020

Main outcome measures

The outcome of Interests are:

Studying the demographic profile of COVID 19 cases

Study the treatment outcomes in terms of death or discharge in patients receiving Ivermectin+N-acetyl-cysteine+Statin along with Standard of care.

Results

148 patients were included in the study. All of them had confirmed COVID19 infection by the rtPCR method. Average age of the patients was 57.57 years (Range = 17 - 88), 49% were male, 51% female. 81% of the patients had at least one or more comorbidities. Most common comorbidities included diabetes (32%), Hypertension (27%),Ischaemic Heart Disease (8%). More comorbidities. The in hospital, Case Fatality Rate was therefore, 1.35 %. The remaining 144 were discharged from the facility after an average 12 days duration of stay.

Conclusions

Triple therapy with ivermectin + atorvastatin + N-acetylcysteine can be an useful adjunct to standard of care.
Integrating psychosocial variables and societal diversity in epidemic models for predicting COVID-19 transmission dynamics
Authors: Jirsa VK , Petkoski S , Wang H , Woodman M , Fousek J , Betsch C , Felgendreff L , Böhm R , Lilleholt L , Zettler I , Faber SM , Shen K , McIntosh AR
Published: August 2020

During the current COVID-19 pandemic, governments must make decisions based on a variety of information including estimations of infection spread, health care capacity, economic and psychosocial considerations. The disparate validity of current short-term forecasts of these factors is a major challenge to governments. By causally linking an established epidemiological spread model with dynamically evolving psychosocial variables, using Bayesian inference we estimate the strength and direction of these interactions for German and Danish data of disease spread, human mobility, and psychosocial factors based on the serial cross-sectional COVID-19 Snapshot Monitoring (COSMO;N= 16,981). We demonstrate that the strength of cumulative influence of psychosocial variables on infection rates is of a similar magnitude as the influence of physical distancing. We further show that the efficacy of political interventions to contain the disease strongly depends on societal diversity, in particular group-specific sensitivity to affective risk perception. As a consequence, the model may assist in quantifying the effect and timing of interventions, forecasting future scenarios, and differentiating the impact on diverse groups as a function of their societal organization. Importantly, the careful handling of societal factors, including support to the more vulnerable groups, adds another direct instrument to the battery of political interventions fighting epidemic spread.
Patient outcomes after hospitalisation with COVID-19 and implications for follow-up; results from a prospective UK cohort
Authors: Arnold DT , Hamilton FW , Milne A , Morley A , Viner J , Attwood M , Noel A , Gunning S , Hatrick J , Hamilton S , Elvers KT , Hyams C , Bibby A , Moran E , Adamali H , Dodd J , Maskell NA , Barratt S
Published: August 2020

Background

COVID-19 causes a wide spectrum of disease. The incidence and severity of sequelae after the acute infection is uncertain. Data measuring the longer-term impact of COVID-19 on symptoms, radiology and pulmonary function are urgently needed to plan follow-up services.

Methods

Consecutive patients hospitalised with COVID-19 were prospectively recruited to this observational study with outcomes recorded at 28-days. All were invited to a systematic follow up at 8-12 weeks, including chest radiograph, spirometry, exercise test, bloods, and health-related quality of life (HRQoL) questionnaires.

Findings

Between 30th March and 3rd June 2020, 163 patients with COVID-19 were recruited. Median hospital length of stay was 5 days (IQR 2-8) and 19 patients died. At 8-12 weeks post admission, 134 patients were available for follow up and 110 attended. Most (74%) had persistent symptoms (notably breathlessness and excessive fatigue) with reduced HRQoL.

Only patients who required oxygen therapy in hospital had abnormal radiology, clinical examination or spirometry at follow up. Thirteen (12%) patients had an abnormal chest X-ray with improvement in all but 2 from admission. Eleven (10%) had restrictive spirometry. Blood test abnormalities had returned to baseline in the majority (104/110).

Interpretation

Patients with COVID-19 remain highly symptomatic at 8-12 weeks, however, clinical abnormalities requiring action are infrequent, especially in those without a supplementary oxygen requirement during their acute illness. This has significant implications for physicians assessing patients with persistent symptoms, suggesting that a more holistic approach focussing on rehabilitation and general wellbeing is paramount.

Funding

Southmead Hospital Charity
Temporal Dynamics of Viral Load and False negative Rate Influence the Levels of Testing Necessary to Combat COVID19 Spread
Authors: Jarvis Katherine F. , Kelley Joshua B.
Published: August 2020

Colleges and other organizations are considering testing plans to return to operation as the COVID19 pandemic continues. Pre-symptomatic spread and high false negative rates for testing may make it difficult to stop viral spread. Here, we develop a stochastic agent-based model of COVID19 in a university sized population, considering the dynamics of both viral load and false negative rate of tests on the ability of testing to combat viral spread. Reported dynamics of SARS-CoV-2 can lead to an apparent false negative rate from ~17% to ~48%. Nonuniform distributions of viral load and false negative rate lead to higher requirements for frequency and fraction of population tested in order to bring the apparent Reproduction number (Rt) below 1. Thus, it is important to consider non-uniform dynamics of viral spread and false negative rate in order to model effective testing plans.
Severity Assessment of COVID-19 based on Clinical and Imaging Data
Authors: Quiroz Juan C. , Feng You-Zhen , Cheng Zhong-Yuan , Rezazadegan Dana , Chen Ping-Kang , Lin Qi-Ting , Qian Long , Liu Xiao-Fang , Berkovsky Shlomo , Coiera Enrico , Song Lei , Qiu Xiao-Ming , Liu Sidong , Cai Xiang-Ran
Published: August 2020

Objectives

This study aims to develop a machine learning approach for automated severity assessment of COVID-19 patients based on clinical and imaging data.

Materials and Methods

Clinical data—demographics, signs, symptoms, comorbidities and blood test results—and chest CT scans of 346 patients from two hospitals in the Hubei province, China, were used to develop machine learning models for automated severity assessment of diagnosed COVID-19 cases. We compared the predictive power of clinical and imaging data by testing multiple machine learning models, and further explored the use of four oversampling methods to address the imbalance distribution issue. Features with the highest predictive power were identified using the SHAP framework.

Results

Targeting differentiation between mild and severe cases, logistic regression models achieved the best performance on clinical features (AUC:0.848, sensitivity:0.455, specificity:0.906), imaging features (AUC:0.926, sensitivity:0.818, specificity:0.901) and the combined features (AUC:0.950, sensitivity:0.764, specificity:0.919). The SMOTE oversampling method further improved the performance of the combined features to AUC of 0.960 (sensitivity:0.845, specificity:0.929).

Discussion

Imaging features had the strongest impact on the model output, while a combination of clinical and imaging features yielded the best performance overall. The identified predictive features were consistent with findings from previous studies. Oversampling yielded mixed results, although it achieved the best performance in our study.

Conclusions

This study indicates that clinical and imaging features can be used for automated severity assessment of COVID-19 patients and have the potential to assist with triaging COVID-19 patients and prioritizing care for patients at higher risk of severe cases.
Maraviroc inhibits SARS-CoV-2 multiplication and s-protein mediated cell fusion in cell culture
Authors: Risner Kenneth H. , Tieu Katie V. , Wang Yafei , Getz Michael , Bakovic Allison , Bhalla Nishank , Nathan Steven D. , Conway Daniel E. , Macklin Paul , Narayanan Aarthi , Alem Farhang
Published: August 2020

In an effort to identify therapeutic intervention strategies for the treatment of COVID-19, we have investigated a selection of FDA-approved small molecules and biologics that are commonly used to treat other human diseases. A investigation into 18 small molecules and 3 biologics was conducted in cell culture and the impact of treatment on viral titer was quantified by plaque assay. The investigation identified 4 FDA-approved small molecules, Maraviroc, FTY720 (Fingolimod), Atorvastatin and Nitazoxanide that were able to inhibit SARS-CoV-2 infection. Confocal microscopy with over expressed S-protein demonstrated that Maraviroc reduced the extent of S-protein mediated cell fusion as observed by fewer multinucleate cells in the context of drugtreatment. Mathematical modeling of drug-dependent viral multiplication dynamics revealed that prolonged drug treatment will exert an exponential decrease in viral load in a multicellular/tissue environment. Taken together, the data demonstrate that Maraviroc, Fingolimod, Atorvastatin and Nitazoxanide inhibit SARS-CoV-2 in cell culture.
Mitogenomic Phylogeny ofCallithrixwith Special Focus on Human Transferred Taxa
Authors: Malukiewicz Joanna , Cartwright Reed A. , Curi Nelson H.A. , Dergam Jorge A. , Igayara Claudia S. , Moreira Silvia B. , Molina Camila V. , Nicola Patricia A. , Noll Angela , Passamani Marcello , Pereira Luiz C.M. , Pissinatti Alcides , Ruiz-Miranda Carlos R. , Silva Daniel L. , Stone Anne C. , Zinner Dietmar , Roos Christian
Published: August 2020

Callithrixmarmosets are a relatively young primate radiation, whose phylogeny is not yet fully resolved. These primates are naturally para- and allopatric, but three species with highly invasive potential have been introduced into the southeastern Brazilian Atlantic Forest by the pet trade. There, these species hybridize with each other and endangered, native congeners. We aimed here to reconstruct a robustCallithrixphylogeny and divergence time estimates, and identify the biogeographic origins of autochthonous and allochthonousCallithrixmitogenome lineages. We sequenced 49 mitogenomes from four species (C. aurita, C. geoffroyi, C. jacchus, C. penicillata) and anthropogenic hybrids (C. auritaxCallithrixsp.,C. penicillataxC. jacchus, Callithrixsp. xCallithrixsp.,C. penicillataxC. geoffroyi) via Sanger and whole genome sequencing. We combined these data with previously publishedCallithrixmitogenomes to analyze fiveCallithrixspecies in total.

Results

We report the complete sequence and organization of theC. auritamitogenome. Phylogenetic analyses showed thatC. auritawas the first to diverge withinCallithrix3.54 million years ago (Ma), whileC. jacchusandC. penicillatalineages diverged most recently 0.5 Ma as sister clades. MtDNA clades ofC. aurita, C. geoffroyi, andC. penicillatashow intraspecific geographic structure, butC. penicillataclades appear polyphyletic. Hybrids, which were identified by phenotype, possessed mainlyC. penicillataorC. jacchusmtDNA haplotypes. The biogeographic origins of mtDNA haplotypes from hybrid and allochthonousCallithrixwere broadly distributed across naturalCallithrixranges. Our phylogenetic results also evidence introgression ofC. jacchusmtDNA intoC. aurita.

Conclusion

Our robustCallithrixmitogenome phylogeny showsC. auritalineages as basal andC. jacchuslineages among the most recent withinCallithrix. We provide the first evidence that parental mtDNA lineages of anthropogenic hybrid and allochthonous marmosets are broadly distributed inside and outside of the Atlantic Forest. We also show evidence of cryptic hybridization between allochthonousCallithrixand autochthonousC. aurita. Our results encouragingly show that further development of genomic resources will allow to more clearly elucidateCallithrixevolutionary relationships and understand the dynamics ofCallithrixanthropogenic introductions into the Brazilian Atlantic Forest.
Rapid Parallel Adaptation to Anthropogenic Heavy Metal Pollution
Authors: Papadopulos Alexander S.T. , Helmstetter Andrew J. , Osborne Owen G. , Comeault Aaron A. , Wood Daniel P. , Straw Edward A. , Mason Laurence , Fay Michael F. , Parker Joe , Dunning Luke T. , Foote Andrew D. , Smith Rhian J. , Lighten Jackie
Published: August 2020

The impact of human mediated environmental change on the evolutionary trajectories of wild organisms is poorly understood. In particular, species’ capacity to adapt rapidly (in hundreds of generations or less), reproducibly and predictably to extreme environmental change is unclear.Silene uniflorais predominantly a coastal species, but it has also colonised isolated, disused mines with phytotoxic, zinc-contaminated soils. Here, we found that rapid parallel adaptation to anthropogenic pollution has taken place without geneflow spreading adaptive alleles between populations of the mine ecotype. Across replicate ecotype pairs, we identified shared targets of selection with functions linked to physiological differences between the ecotypes, although the genetic response is only partially shared between mine populations. Our results are consistent with a complex, polygenic genetic architecture underpinning rapid adaptation. This shows that even under a scenario of strong selection and rapid adaptation, evolutionary responses to human activities may be idiosyncratic at the genetic level and, therefore, difficult to predict from genomic data.
Single-molecule view of coordination in a multi-functional DNA polymerase
Authors: Pauszek Raymond F. , Lamichhane Rajan , Singh Arishma Rajkarnikar , Millar David P.
Published: August 2020

Replication and repair of genomic DNA requires the action of multiple enzymatic functions that must be coordinated in order to ensure efficient and accurate product formation. Here we have used single-molecule FRET microscopy to investigate the physical basis of functional coordination in DNA polymerase I (Pol I) fromE. coli, a key enzyme involved in lagging-strand replication and base excision repair. Pol I contains active sites for template-directed DNA polymerization and 5’ flap processing in separate domains. We show that a DNA substrate can spontaneously transfer between polymerase (pol) and 5’ nuclease (5’ nuc) domains during a single encounter with Pol I. Additionally, we show that the flexibly tethered5’ nucdomain adopts different positions within Pol I-DNA complexes, depending on the nature of the DNA substrate. Our results reveal the structural dynamics that underlie functional coordination in Pol I and are likely relevant to other multi-functional DNA polymerases.
Attenuated influenza virions expressing the SARS-CoV-2 receptor-binding domain induce neutralizing antibodies in mice
Authors: Loes Andrea N. , Gentles Lauren E. , Greaney Allison J. , Crawford Katharine H. D. , Bloom Jesse D.
Published: August 2020

An effective vaccine is essential to controlling the spread of SARS-CoV-2 virus. Here, we describe an influenza-virus-based vaccine for SARS-CoV-2. We incorporated a membrane-anchored form of the SARS-CoV-2 Spike receptor binding domain (RBD) in place of the neuraminidase (NA) coding sequence in an influenza virus also possessing a mutation that reduces the affinity of hemagglutinin for its sialic acid receptor. The resulting ΔNA(RBD)-Flu virus can be generated by reverse genetics and grown to high titers in cell culture. A single-dose intranasal inoculation of mice with ΔNA(RBD)-Flu elicits serum neutralizing antibody titers against SAR-CoV-2 comparable to those observed in humans following natural infection (∼1:200). Furthermore, ΔNA(RBD)-Flu itself causes no apparent disease in mice. It might be possible to produce a vaccine similar to ΔNA(RBD)-Flu at scale by leveraging existing platforms for production of influenza vaccines.
An antiviral self-replicating molecular heterotroph
Authors: Shapiro Anastasia , Rosenberg Alexander , Levy-Zamir Adva , Bassali Liron , Ittah Shmulik , Abu-Horowitz Almogit , Bachelet Ido
Published: August 2020

We report the synthesis of a molecular machine, fabricated from nucleic acids, which is capable of digesting viral RNA and utilizing it to assemble additional copies of itself inside living cells. The machine’s body plan combines several parts that build upon the target RNA, assembling an immobile, DNA:RNA 4-way junction, which contains a single gene encoding a hammerhead ribozyme (HHR). Full assembly of the machine’s body from its parts enables the subsequent elongation of the gene and transcription of HHR molecules, followed by HHR-mediated digestion of the target molecule. This digestion converts the target to a building block suitable for participation in the assembly of more copies of the machine, mimicking biological heterotrophy. In this work we describe the general design of a prototypical machine, characterize its activity cycle and kinetics, and show that it can be efficiently and safely delivered into live cells. As a proof of principle, we constructed a machine that targets theAutographa californicamulticapsid nucleopolyhedrovirus (AcMNPV) GP64 gene, and show that it effectively suppresses viral propagation in a cell population, exhibiting predator/prey-like dynamics with the infecting virus. In addition, the machine significantly reduced viral infection, stress signaling, and innate immune activation inside virus-infected animals. This preliminary design could control the behavior of antisense therapies for a range of applications, particularly against dynamic targets such as viruses and cancer.
Microbial community shifts reflect losses of native soil carbon with pyrogenic and fresh organic matter additions and are greatest in low-carbon soils
Authors: Whitman Thea , DeCiucies Silene , Hanley Kelly , Enders Akio , Woolet Jamie , Lehmann Johannes
Published: August 2020

Soil organic carbon (SOC) plays an important role in regulating global climate change, carbon and nutrient cycling in soils, and soil moisture. Organic matter (OM) additions to soils can affect the rate at which SOC is mineralized by microbes, with potentially important effects on SOC stocks. Understanding how pyrogenic organic matter (PyOM) affects the cycling of native SOC (nSOC) and the soil microbes responsible for these effects is important for fire-affected ecosystems as well as for biochar-amended systems. We used an incubation trial with five different soils from National Ecological Observatory Network sites across the US and13C-labelled 350°C corn stover PyOM and fresh corn stover OM to trace nSOC-derived CO2emissions with and without PyOM and OM amendments. We used high-throughput sequencing of rRNA genes to characterize bacterial, archaeal, and fungal communities and their response to PyOM and OM. We found that the effects of amendments on nSOC-derived CO2reflected the unamended soil C status, where amendments increased C mineralization the most in low-C soils. OM additions produced much greater effects on nSOC-CO2emissions than PyOM additions. Furthermore, the magnitude of microbial community composition change mirrored the magnitude of increases in nSOC-CO2, indicating a specific subset of microbes were likely responsible for the observed changes in nSOC mineralization. However, PyOM responders differed across soils and did not necessarily reflect a common “charosphere”. Overall, this study suggests that soils that already have low SOC may be particularly vulnerable to short-term increases in SOC loss with OM or PyOM additions.

Importance

Soil organic matter (SOM) has an important role in global climate change, carbon and nutrient cycling in soils, and soil moisture dynamics. Understanding the processes that affect SOM stocks is important for managing these functions. Recently, understanding how fire-affected, or “pyrogenic” organic matter (PyOM) affects existing SOM stocks has become increasingly important, both due to changing fire regimes, and to interest in “biochar” – pyrogenic organic matter that is produced intentionally for carbon management or as an agricultural soil amendment. We found that soils with less SOM were more prone to increased losses with PyOM (and fresh organic matter) additions, and that soil microbial communities changed more in soils that also had greater SOM losses with PyOM additions. This suggests that soils that already have low SOM content may be particularly vulnerable to short-term increases in SOM loss, and that a subset of the soil microbial community is likely responsible for these effects.
Association between the Mediterranean diet and prostate cancer risk in a Greek population
Authors: Vaioulis Alexandros , Yiannis Kiouvrekis , Perivoliotis Konstantinos , Stavros Gravas , Vasilios Tzortzis , Anastasios Karatzas
Published: August 2020

Purpose

Dietary modifications have been correlated with survival in several neoplasia, such as prostate cancer. The present study was designed to investigate the association between the Mediterranean diet and prostate cancer risk.

Methods

A retrospective analysis of patients with a high suspicion of suffering from prostate cancer (PCa) who underwent prostate biopsy was performed. According to histopathology, two groups were generated, the PCa group and the Healthy group. The dietary profile of our study population was implemented, based on a modified MDS (Mediterranean Diet Score) questionnaire. A logistic regression model was used for the interpretation of our data.

Results

In total, 431 patients with prostate cancer and 279 healthy men were included in our study. The demographic characteristics of the patients were comparable. Daily consumption of white meat (OR: 0.59), dairy products (OR: 0.64), nuts (OR: 0.63) and whole grains (OR: 0.55) was higher in healthy males. Infrequent consumption of vegetables was linked with an increased rate of PCa (OR: 2.55). Interestingly daily consumption of processed meat rates was higher in healthy men. However, a significant correlation between specific intake products or frequency and the incidence of PCa was not established.

Conclusions

Although, an association between the dietary patterns and PCa was not determined, components consumption patterns displayed a higher daily intake rate of white meat, dairy products, nuts and whole grains. Further prospective trials are required to validate the effect of Mediterranean diet in the incidence and mortality of PCa patients.
Validation of Saliva and Self-Administered Nasal Swabs for COVID-19 Testing
Authors: Teo Alvin Kuo Jing , Choudhury Yukti , Tan Iain Beehuat , Cher Chae Yin , Chew Shi Hao , Wan Zi Yi , Cheng Lionel Tim Ee , Oon Lynette Lin Ean , Tan Min Han , Chan Kian Sing , Hsu Li Yang
Published: August 2020

Background

Active cases of COVID-19 has primarily been diagnosed via RT-PCR of nasopharyngeal (NP) swabs. Saliva and self-administered nasal (SN) swabs can be collected safely without trained staff.

We aimed to test the sensitivity of “naso-oropharyngeal” saliva and SN swabs compared to NP swabs in a large cohort of migrant workers in Singapore.

Methods

We recruited 200 male adult subjects: 45 with acute respiratory infection, 104 asymptomatic close contacts, and 51 confirmed COVID-19 cases. Each subject underwent NP swab, SN swab and saliva collection for RT-PCR testing at 1 to 3 timepoints. We additionally used a direct-from-sample amplicon-based next-generation sequencing (NGS) workflow to establish phylogeny.

Results

Of 200 subjects, 91 and 46 completed second and third rounds of testing, respectively. Of 337 sets of tests, there were 150 (44.5%) positive NP swabs, 127 (37.7%) positive SN swabs, and 209 (62.0%) positive saliva.

Test concordance between different sample sites was good, with a kappa statistic of 0.616 for NP and SN swabs, and 0.537 for NP and saliva. In confirmed symptomatic COVID-19 subjects, the likelihood of a positive test from any sample fell beyond 14 days of symptom onset.

NGS was conducted on 18 SN and saliva samples, with phylogenetic analyses demonstrating lineages for all samples tested were Clade O (GISAID nomenclature) and lineage B.6 (PANGOLIN nomenclature).

Conclusion

This study supports saliva as a sensitive and less intrusive sample for COVID-19 diagnosis and further delineates the role of oropharyngeal secretions in increasing the sensitivity of testing. However, SN swabs were inferior as an alternate sample type. Our study also provides evidence that a straightforward next-generation sequencing workflow can provide direct-from-sample phylogenetic analysis for public health decision-making.