bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of Vitamin D Deficiency and Treatment with COVID-19 Incidence
Authors: Meltzer David O. , Best Thomas J. , Zhang Hui , Vokes Tamara , Arora Vineet , Solway Julian 
Published: May 2020

AbstractImportanceVitamin D treatment has been found to decrease incidence of viral respiratory tract infection, especially in vitamin D deficiency. It is unknown whether COVID-19 incidence is associated with vitamin D deficiency and treatment.ObjectiveTo examine whether vitamin D deficiency and treatment are associated with testing positive for COVID-19.DesignRetrospective cohort studySettingUniversity of Chicago MedicineParticipantsPatients tested for COVID-19 from 3/3/2020-4/10/2020. Vitamin D deficiency was defined by the most recent 25-hydroxycholecalciferol <20ng/ml or 1,25-dihydroxycholecalciferol <18pg/ml within 1 year before COVID-19 testing. Treatment was defined by the most recent vitamin D type and dose, and treatment changes between the time of the most recent vitamin D level and time of COVID-19 testing. Vitamin D deficiency and treatment changes were combined to categorize vitamin D status at the time of COVID-19 testing as likely deficient (last-level-deficient/treatment-not-increased), likely sufficient(last-level-not-deficient/treatment-not-decreased), or uncertain deficiency(last-level-deficient/treatment-increased or last-level-not-deficient/treatment-decreased).Main Outcomes and MeasuresThe main outcome was testing positive for COVID-19. Multivariable analysis tested whether the most recent vitamin D level and treatment changes after that level were associated with testing positive for COVID-19 controlling for demographic and comorbidity indicators. Bivariate analyses of associations of treatment with vitamin D deficiency and COVID-19 were performed.ResultsAmong 4,314 patients tested for COVID-19, 499 had a vitamin D level in the year before testing. Vitamin D status at the time of COVID-19 testing was categorized as likely deficient for 127(25%) patients, likely sufficient for 291(58%) patients, and uncertain for 81(16%) patients. In multivariate analysis, testing positive for COVID-19 was associated with increasing age(RR(age<50)=1.05,p<0.021;RR(age≥50)=1.02,p<0.064)), non-white race(RR=2.54,p<0.01) and being likely vitamin D deficient (deficient/treatment-not-increased:RR=1.77,p<0.02) as compared to likely vitamin D sufficient(not-deficient/treatment-not-decreased), with predicted COVID-19 rates in the vitamin D deficient group of 21.6%(95%CI[14.0%-29.2%]) versus 12.2%(95%CI[8.9%-15.4%]) in the vitamin D sufficient group. Vitamin D deficiency declined with increasing vitamin D dose, especially of vitamin D3. Vitamin D dose was not significantly associated with testing positive for COVID-19.Conclusions and RelevanceVitamin D deficiency that is not sufficiently treated is associated with COVID-19 risk. Testing and treatment for vitamin D deficiency to address COVID-19 warrant aggressive pursuit and study.
Defining the Pandemic at the State Level: Sequence-Based Epidemiology of the SARS-CoV-2 virus by the Arizona COVID-19 Genomics Union (ACGU)
Authors: Ladner Jason T. , Larsen Brendan B. , Bowers Jolene R. , Hepp Crystal M. , Bolyen Evan , Folkerts Megan , Sheridan Krystal , Pfeiffer Ashlyn , Yaglom Hayley , Lemmer Darrin , Sahl Jason W. , Kaelin Emily A. , Maqsood Rabia , Bokulich Nicholas A. , Quirk Grace , Watts Thomas D. , Komatsu Kenneth , Waddell Victor , Lim Efrem S. , Caporaso J. Gregory , Engelthaler David M. , Worobey Michael , Keim Paul 
Published: May 2020

AbstractIn December of 2019, a novel coronavirus, SARS-CoV-2, emerged in the city of Wuhan, China causing severe morbidity and mortality. Since then, the virus has swept across the globe causing millions of confirmed infections and hundreds of thousands of deaths. To better understand the nature of the pandemic and the introduction and spread of the virus in Arizona, we sequenced viral genomes from clinical samples tested at the TGen North Clinical Laboratory, provided to us by the Arizona Department of Health Services, and at Arizona State University and the University of Arizona, collected as part of community surveillance projects. Phylogenetic analysis of 79 genomes we generated from across Arizona revealed a minimum of 9 distinct introductions throughout February and March. We show that >80% of our sequences descend from clades that were initially circulating widely in Europe but have since dominated the outbreak in the United States. In addition, we show that the first reported case of community transmission in Arizona descended from the Washington state outbreak that was discovered in late February. Notably, none of the observed transmission clusters are epidemiologically linked to the original travel-related cases in the state, suggesting successful early isolation and quarantine. Finally, we use molecular clock analyses to demonstrate a lack of identifiable, widespread cryptic transmission in Arizona prior to the middle of February 2020.
Effects of underlying morbidities on the occurrence of deaths in COVID-19 patients: A systematic review and meta-analysis
Authors: Khan Md. Mostaured Ali , Khan Md. Nuruzzaman , Mustagir Md. Golam , Rana Juwel , Islam Md. Saiful , Kabir Md. Iqbal 
Published: May 2020

AbstractBackgroundCoronavirus disease 2019 (COVID-19), the most hectic pandemic of the era, is increasing exponentially and taking thousands of lives worldwide. This study aimed to assess the prevalence of pre-existing morbidities among COVID-19 infected patients and their mortality risks against each type of pre-existing morbidity category.MethodsTo conduct this systematic review and meta-analysis, Medline, Web of Science, Scopus, and CINAHL databases were searched using specified relavent keywords. Further searches were conducted using the reference list of the selected studies, renowned pre-print servers (e.g., medRxiv, bioRixv, SSRN), and relevant journal websites. Studies written in the English language included if those were conducted among COVID-19 patients with and without comorbidities and presented survivor vs. non-survivor counts or hazard/odds of deaths or survivors against types of pre-existing morbidities. Comorbidities reported in the selected studies were grouped into eight categories. The pooled likelihoods of deaths in each category were estimated using a fixed or random-effect model, based on the heterogeneity assessment. Publication bias was assessed by visual inspection of the funnel plot asymmetry and Egger’s regression test. Trim and Fill method was used if there any publication bias was found.ResultsA total of 42 studies included in this study comprised of 39,398 samples. The most common pre-existing morbidities in COVID-19 infected patients were hypertension (36.5%), cardiovascular disease (11.9%), and diabetes (22.0%). The higher likelihood of deaths was found among COVID-19 patients who had pre-existing cardiovascular diseases (OR: 3.32, 95% CI: 2.79-3.95), immune and metabolic disorders (OR: 2.39, 95% CI: 2.00-2.85), respiratory diseases (OR: 2.02, 95% CI: 1.80-2.26), cerebrovascular diseases (OR: 4.12, 95% CI: 3.04-5.58), any types of cancers (OR: 2.22, 95% CI: 1.63-3.03), renal (OR: 3.02, 95% CI: 2.60-3.52), and liver diseases (OR: 1.44, 95% CI: 1.21-1.71).ConclusionsThis study provides evidence of a higher likelihood of deaths among COVID-19 patients against morbidity categories. These findings could potentially help healthcare providers to sort out the most endangered COVID-19 patients by comorbidities, take precautionary measures during hospitalization, assess susceptibility to death, and prioritize their treatment, which could potentially reduce the number of fatalities in COVID-19.
CoViD-19 Epidemic in India and Projections: Is Relief in Sight?
Authors: Indrayan Abhaya , Shukla Shubham 
Published: May 2020

AbstractBackgroundProjection of cases and deaths in an epidemic such as CoViD-19 is hazardous and the early projections were way-off the actual pattern. However, we now have actual data for more than 50 consecutive days in India that can be effectively used for projection.MethodsWe closely track the trend and use the same pattern for projection. We call this Empirical Model. We also fit a Theoretical Model based on a Gamma function on the pattern of some of the previous epidemics.ResultsThe Empirical Model predicts the peak around the fourth week of May and the near end of the epidemic by the end of June 2020. The maximum number of active cases is likely to be nearly 75,000 during the second week of June. This would mean a peak demand of nearly 15,000 beds and nearly 4000 ventilators. The case-fatality based on those who have reached an outcome was nearly 10% in the first week of May and is likely to remain at this level for some time. Theoretical Model projected a peak of nearly 2500 new cases per day in the second week of May that seems to have been already breached. This model predicts the near end of the epidemic by the middle of July 2020.ConclusionWith the current trend, the end of the epidemic is in sight with relatively mild consequences in India compared with most other countries.
COVID-19 and Acute Kidney Injury Requiring Kidney Replacement Therapy: A Bad Prognostic Sign
Authors: Shekhar Rahul , Upadhyay Shubhra , Shah Silvi , Kapuria Devika 
Published: May 2020

AbstractThe development of acute kidney injury in patients with COVID-19 is estimated to about 0.5% from earlier studies from China. The incidence of AKI in patients with COIVID-19 in the largest inpatient series in the United States is 22.2%3. Development of AKI requiring kidney replacement therapy in hospitalized patients is a bad prognostic sign. Out of Fifty patients admitted to our hospital with COVID-19 13/50(26%) developed AKI. All patients required hospitalization in intensive care unit care and 12/13 required initiation of kidney replacement therapy. The median age was 41 years (31-85 years) and 50% were men. Common comorbidities were obesity (83%), diabetes (42%), and hypertension (25%). 10/12 (83%) patients were hypoxemic and required oxygen therapy. 11/12 (92%) patients required invasive ventilation. Majority of patients had elevated neutrophils counts (81.8%) and low lymphocyte counts (81.8%). All patients had chest x-ray findings suggestive of pneumonia. 11/12(91.6%) developed septic shock requiring vasopressors. Review of UA showed all patient (9/9) had active urine sediments with blood but 7/9 of them have sterile pyuria. At the end of study period, 1 patient remained hospitalized. 10/11(90%) patients died and one patient was discharged home with resolution of AKI. Median length of stay was 13 days. The exact mechanism of AKI is not well understood in COVID-19 but can be due to acute tubular necrosis due to septic shock because of cytokine storm in severe COVID-19 or direct invasion by SARS-CoV-2 on podocytes and proximal renal tubular cells. Our findings suggest poor prognosis despite continuous kidney replacement therapies in patients who develop AKI with COVID-19.
Cognitive decline associated with anticholinergics, benzodiazepines, and Z-drugs: findings from The Irish Longitudinal Study on Ageing (TILDA)
Authors: Moriarty Frank , Savva George M , Grossi Carlota M , Bennett Kathleen , Fox Chris , Maidment Ian , Loke Yoon K , Steel Nicholas , Kenny Rose Anne , Richardson Kathryn 
Published: May 2020

AbstractAimTo estimate the association between patterns of anticholinergic, benzodiazepine, and Z-drug medication use and change in cognitive function in middle-aged and older adults.MethodThis prospective cohort study used data from the first three waves of The Irish Longitudinal Study on Ageing (TILDA), including community-dwelling adults aged ≥50 years followed for up to four years (n=7,027).Cognitive function was assessed using the Mini Mental State Examination, animal naming test, and word recall tests. Regular medication use was self-reported at baseline and follow-up interviews at two and four years. Pharmacy dispensing claims for a subset (n=2,905) allowed assessment of medication use between interviews and cumulative dosage. Medication use at consecutive waves of TILDA was analysed in relation to change in cognitive function between waves.ResultsStrongly anticholinergic medications (Anticholinergic Cognitive Burden scale 3), benzodiazepines, and Z-drugs were reported by 7.3%, 5.8% and 5.1% of participants respectively at any time during the study. Adjusting for potential confounders, new anticholinergic use between interviews was associated with change in recall score (−1.09, 95% confidence interval −1.64, −0.53) over 2 years compared to non-use, but not with MMSE (0.07; 95%CI -0.21, 0.34) or animal naming (−0.70; −1.43, 0.03). The pharmacy claims analysis was consistent with this finding. Other hypothesised associations were not supported.DiscussionExcept for new use of anticholinergic medications, no other findings supported a risk of cognitive decline over 2-year periods in this middle-aged and older cohort. Patients and prescribers should weigh this potential risk against potential benefits of commencing anticholinergic medications.What is already known about this subject:Benzodiazepines, Z-drugs and drugs with anticholinergic activity have been linked with cognitive impairment.Most evidence is derived from observational studies of older people, with little research on middle-aged adults.Medication effects may be confounded by indication and these medications are often prescribed for early symptoms of prodromal stages of dementia.What this study adds:In this study of adults aged 50 years and older, no consistent pattern of change in cognitive function was associated with the medication exposures tested, except for reduced recall among new users of anticholinergic medications.Further research in the younger-old adult population should be conducted to confirm these findings.
A Novel Box for Aerosol and Droplet Guarding and Evacuation in Respiratory Infection (BADGER) for COVID-19 and Future Outbreaks
Authors: Le Hau D. , Novak Gordon A. , Janek Kevin C. , Wang Jesse , Huynh Khang N. , Myer Chris , Weinstein Adam , Oberstar Erick L. , Rasmussen Jim , Bertram Timothy H. 
Published: May 2020

AbstractThe coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has infected millions and killed hundreds of thousands of people worldwide as of May 2020. Healthcare providers are at increased risks of infection when caring for patients with COVID-19. The mechanism of transmission of SARS-CoV-2 is still not fully understood. However, there is growing evidence for airborne spread, in addition to direct droplet and indirect contact. Here, we report on the design, construction, and testing of the BADGER (Box for Aerosol and Droplet Guarding and Evacuation in Respiratory Infection), an affordable, scalable device that contains droplets and aerosol particles. A semi-sealed environment is created inside the BADGER, which maintains at least twelve-air changes per hour using in-wall vacuum suction, and multiple hand-ports enable healthcare providers to perform essential tasks on a patient’s airway and head. Overall, the BADGER has the potential to contain large droplets and small airborne particles as demonstrated by simulated qualitative and quantitative assessments to provide an additional layer of protection for healthcare providers treating COVID-19 patients.
rest2vec: Vectorizing the resting-state functional connectome using graph embedding
Authors: Morrissey Zachery D. , Zhan Liang , Ajilore Olusola , Leow Alex D. 
Published: May 2020

AbstractResting-state functional magnetic resonance imaging (rs-fmri) is widely used in connectomics for studying the functional relationships between regions of the human brain. rs-fmri connectomics, however, has inherent analytical challenges, such as accounting for negative correlations. In addition, functional relationships between brain regions do not necessarily correspond to their anatomical distance, making the intrinsic geometry of the functional connectome less well understood. Recent techniques in natural language processing and machine learning, such as word2vec, have used embedding methods to map high-dimensional data into meaningful vector spaces. Inspired by this approach, we have developed a graph embedding pipeline, rest2vec, for studying the intrinsic geometry of functional connectomes. We demonstrate how rest2vec uses the phase angle spatial embedding (phase) method with dimensionality reduction techniques to embed the functional connectome into lower dimensions. Rest2vec can also be linked to the maximum mean discrepancy (mmd) metric to assign functional modules of the connectome in a continuous manner, improving upon traditional binary classification methods. Together, this allows for studying the functional connectome such that the full range of correlative information is preserved and gives a more informed understanding of the functional organization of the brain.
Identifying a supramodal language network in human brain with individual fingerprint
Authors: Liu Lanfang , Yan Xin , Li Hehui , Gao Dingguo , Ding Guosheng 
Published: May 2020

AbstractWhere is human language processed in the brain independent of its form? We addressed this issue by analyzing the cortical responses to spoken, written and signed sentences at the level of individual subjects. By applying a novel fingerprinting method based on the distributed pattern of brain activity, we identified a left-lateralized network composed by the superior temporal gyrus/sulcus (STG/STS), inferior frontal gyrus (IFG), precentral gyrus/sulcus (PCG/PCS), and supplementary motor area (SMA). In these regions, the local distributed activity pattern induced by any of the three language modalities can predict the activity pattern induced by the other two modalities, and such cross-modal prediction is individual-specific. The prediction is successful for speech-sign bilinguals across all possible modality pairs, but fails for monolinguals across sign-involved pairs. In comparison, conventional group-mean focused analysis detects shared cortical activations across modalities only in the STG, PCG/PCS and SMA, and the shared activations were found in two groups. This study reveals the core language system in the brain that is shared by spoken, written and signed language, and demonstrates that it is possible and desirable to utilize the information of individual differences for functional brain mapping.
IN SILICOSCREENING AND MOLECULAR DYNAMIC SIMULATION STUDIES OF POTENTIAL SMALL MOLECULE IMMUNOMODULATORS OF THE KIR2DS2 RECEPTOR
Authors: Rowaiye Adekunle Babajide , Olubiyi Jide , Bur Doofan , Uzochukwu Ikemefuna Chijioke , Akpa Alex , Esimone Charles Okechukwu 
Published: May 2020

AbstractThe World Health Organization reports that cancer is one of the most common causes of death worldwide and it accounted for an estimated 9.6 million deaths in 2018. As compared with chemotherapy or radiotherapy, immunotherapy offers a safer, less stressful and selective strategy in the destruction of cancer cells. The killer cell immunoglobulin-like receptor 2DS2 (KIR2DS2) expressed on Natural Killer (NK) cells are involved in signal transduction processes that produce pro-inflammatory cytokines and directly destroy cancer and virally infected cells. The aim of this study is to identify small molecules from natural products that have strong binding affinity with KIR2DS2 and possible bioactivity. A library of small molecule natural compounds obtained from edible African plants was used forin Silicomolecular docking simulations of KIR2DS2 (PDBID: 1m4k) usingPyrx. An arbitrary docking score ≥ −7.0 kcal/mol was chosen as cut off value. Screening for drug-likeness and ligand efficiency was based on the molecular descriptors of the compounds as provided byPubchem. Further screening for saturation, molar refractivity, promiscuity, pharmacokinetic properties, and bioactivity was done usingSWISSADME, PKCSM, andMolinspirationrespectively. The molecular dynamic simulation and analyses was done using theGalaxywebserver which uses the GROMACS software. Analyses of molecular dynamic simulation were done usingGalaxyandMDWEBwebservers. Gibberellin A20 and A29 were obtained as the lead compounds and they show better promise as drug candidates for KIR2DS2 than the standard. It is recommended that the immuno-stimulatory effect of the lead compounds on KIR2DS2 be further investigated.
Performance trade-offs for single- and dual-objective light-sheet microscope designs
Authors: Bishop Kevin W. , Glaser Adam K. , Liu Jonathan T.C. 
Published: May 2020

AbstractLight-sheet microscopy (LSM) has emerged as a powerful tool for high-speed volumetric imaging of live model organisms and large optically cleared specimens. When designing cleared-tissue LSM systems with certain desired imaging specifications (e.g. resolution, contrast, and working distance), various design parameters must be taken into consideration. In order to elucidate some of the key design trade-offs for LSM systems, we present a diffraction-based analysis of single- and dual-objective LSM configurations where Gaussian illumination is utilized. Specifically, we analyze the effects of the illumination and collection numerical aperture (NA), as well as their crossing angle, on spatial resolution and contrast. Assuming an open-top light-sheet (OTLS) architecture, we constrain these parameters based on fundamental geometric considerations as well as those imposed by currently available microscope objectives. In addition to revealing the performance tradeoffs of various single- and dual-objective LSM configurations, our analysis showcases the potential advantages of a novel, non-orthogonal dual-objective (NODO) architecture, especially for moderate-resolution imaging applications (collection NA of 0.5 to 0.8).