bluuebunny/crossref_metadata_2025_split huggingface dataset:
The liver in COVID-19: prevalence, patterns, predictors, and impact on outcomes of liver test abnormalities
Authors: Goel Harsh , Harmouch Farah , Garg Kawish , Saraiya Pooja , Daly Timothy , Kumar Ashish , Hippen John T. 
Published: December 2020

Background
Coronavirus disease 2019 (COVID-19) has caused a global pandemic unprecedented in over a century, with ≈35 million cases, and more than 1 million deaths globally. Though predominantly a lower respiratory illness, other organ injuries are well-recognized. Among these, liver injury is of major interest.

Objective
To define prevalence, pattern, predictors, and impact of liver injury among patients hospitalized with COVID-19.

Methods
Demographic, clinical, and biochemical data were collected retrospectively among patients admitted to St. Luke’s University Hospital with COVID-19 between 1 March and 18 April 2020. Association of liver tests (LTs) with mortality and need for mechanical ventilation, adjusted for demographic, clinical and biochemical predictors, was examined.

Results
Data were available on 551 patients. Prevalence of any or ≥3 × upper limit of normal transaminase elevation on was 61.2 and 9.4% on admission, and 72.1 and 22.4% at peak. Bilirubin and alkaline phosphatase elevations were less common on admission (11.4 and 12.6%, respectively), and at peak (17.7 and 22%, respectively). All liver test (LT) elevations were consistently predicted by inflammatory markers. Hyperbilirubinemia predicted mortality on admission and at peak. Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) had opposite impact on mortality with AST positively, and ALT negatively associated with mortality. Hence, besides hyperbilirubinemia, AST:ALT ratio emerged as the best marker for mortality among the LTs.

Conclusion
LT elevations among patients presenting with COVID-19 are very common, though majority are mild. Admission and peak bilirubin ≥1 mg/dl, as well as admission and peak AST:ALT ratio were significant predictors of mortality, along with age, myocardial injury, and chronic medical illness.
Combined RT-qPCR and Pyrosequencing of a SARS-CoV-2 Spike Glycoprotein Polybasic Cleavage Motif Uncovers Rare Pediatric COVID-19 Spectrum Diseases of Unusual Presentation
Authors: Weil Patrick Philipp , Hentschel Jacqueline , Schult Frank , Pembaur Anton , Ghebremedhin Beniam , Mboma Olivier , Heusch Andreas , Reuter Anna-Christin , Müller Daniel , Wirth Stefan , Aydin Malik , Jenke Andreas C. W. , Postberg Jan 
Published: December 2020

AbstractBackgroundSurveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is essential for the global containment measures with regard to the ongoing pandemic. Diagnostic gold standard is currently reverse transcription of the (+)RNA genome and subgenomic RNAs and subsequent quantitative polymerase chain reaction (RT-qPCR) from nasopharyngeal swabs or bronchoalveolar lavages. In order to further improve the diagnostic accuracy, particularly for the reliable discrimination between negative and false-negative specimens, we propose the combination of the RT-qPCR workflow with subsequent pyrosequencing of a S-gene amplicon. This extension might add important value mainly in cases with low SARS-CoV-2 load, where RT-qPCR alone can deliver conflicting results.sResultsWe successfully established a combined RT-qPCR and S-gene pyrosequencing method which can be optionally exploited after routine diagnostics or for epidemiologic studies. This allows a more reliable interpretation of conflicting RT-qPCR results in specimens with relatively low viral loads and close to the detection limits of qPCR (CT values >30). After laboratory implementation and characterization of a best practice protocol we tested the combined method in a large pediatric cohort from two German medical centers (n=769). Pyrosequencing after RT-qPCR enabled us to uncover 6 previously unrecognized cases of pediatric SARS-CoV-2 associated diseases, partially exhibiting unusual and heterogeneous presentation. Moreover, it is notable that in the course of RT-qPCR/pyrosequencing method establishment we did not observe any case of false-positive diagnosis when confirmed SARS-CoV-2-positive specimens were used from foregoing routine testing.ConclusionsThe proposed protocol allows a specific and sensitive detection of SARS-CoV-2 close to the detection limits of RT-qPCR. Combined RT-qPCR/pyrosequencing does not negatively affect preceding RT-qPCR pipeline in SARS-CoV-2 diagnostics and can be optionally applied in routine to inspect conflicting RT-qPCR results.
Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Integrated Bioinformatics Analysis and Molecular Docking Experiments
Authors: Vastrad Basavaraj , Vastrad Chanabasayya , Tengli Anandkumar 
Published: December 2020

AbstractThe current investigation aimed to mine therapeutic molecular targets that play an key part in the advancement of pancreatic ductal adenocarcinoma (PDAC). The expression profiling by high throughput sequencing dataset profile GSE133684 dataset was downloaded from the Gene Expression Omnibus (GEO) database. Limma package of R was used to identify differentially expressed genes (DEGs). Functional enrichment analysis of DEGs were performed. Protein-protein interaction (PPI) networks of the DEGs were constructed. An integrated gene regulatory network was built including DEGs, microRNAs (miRNAs), and transcription factors. Furthermore, consistent hub genes were further validated. Molecular docking experiment was conducted. A total of 463 DEGs (232 up regulated and 231 down regulated genes) were identified between very early PDAC and normal control samples. The results of Functional enrichment analysis revealed that the DEGs were significantly enriched in vesicle organization, secretory vesicle, protein dimerization activity, lymphocyte activation, cell surface, transferase activity, transferring phosphorus-containing groups, hemostasis and adaptive immune system. The PPI network and gene regulatory network of up regulated genes and down regulated genes were established, and hub genes were identified. The expression of hub genes (CCNB1, FHL2, HLA-DPA1 and TUBB1) were also validated to be differentially expressed among PDAC and normal control samples. Molecular docking experiment predicted the novel inhibitory molecules for CCNB1 and FHL2. The identification of hub genes in PDAC enhances our understanding of the molecular mechanisms underlying the progression of this disease. These genes may be potential diagnostic biomarkers and/or therapeutic molecular targets in patients with PDAC.
Low vitamin K status predicts mortality in a cohort of 138 hospitalized patients with COVID-19
Authors: Linneberg A , Kampmann FB , Israelsen SB , Andersen LR , Jørgensen HL , Sandholt H , Jørgensen NR , Thysen SM , Benfield T 
Published: December 2020

AbstractIt has recently been hypothesised that Vitamin K could play a role in COVID-19. We aimed to test the hypothesis that low vitamin K status is a common characteristic of patients hospitalized with COVID-19 compared to population controls; and that low vitamin K status predicts mortality in COVID-19 patients. In a cohort of 138 COVID-19 patients and 140 population controls, we measured plasma dephosphorylated-uncarboxylated Matrix Gla Protein (dp-ucMGP), which reflects the functional Vitamin K status in peripheral tissue. Fourty-three patients died within 90-days from admission. In patients, levels of dp-ucMGP differed significantly between survivors (mean 877; 95% CI: 778; 995) and non-survivors (mean 1445; 95% CI: 1148; 1820). Furthermore, levels of dp-ucMGP (pmol/L) were considerably higher in patients (mean 1022; 95% CI: 912; 1151) compared to controls (mean 509; 95% CI: 485; 540). Cox regression survival analysis showed that increasing levels of dp-ucMGP (reflecting low Vitamin K status) were associated with higher mortality risk (sex- and age-adjusted hazard ratio per doubling of dp-ucMGP was 1.50, 95% CI: 1.03; 2.18). In conclusion, we found that low Vitamin K status predicted mortality in patients with COVID-19 supporting a potential role of Vitamin K in COVID-19.
Renin-angiotensin system blockers and mortality in COVID-19: a territory-wide study from Hong Kong
Authors: Zhou Jiandong , Tse Gary , Lee Sharen , Wong Wing Tak , Wang Xingsong , Wu William KK , Liu Tong , Cao Zhidong , Zeng Daniel Dajun , Wong Ian Chi Kei , Cheung Bernard Man Yung , Zhang Qingpeng 
Published: December 2020

AbstractAimsRenin–angiotensin system blockers such as angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) may increase the risk of adverse outcomes in COVID-19. In this study, the relationships between ACEI/ARB use and COVID-19 related mortality were examined.MethodsConsecutive patients diagnosed with COVID-19 by RT-PCR at the Hong Kong Hospital Authority between 1st January and 28th July 2020 were included.ResultsThis study included 2774 patients. The mortality rate of the COVID-19 positive group was 1.5% (n=42). Those who died had a higher median age (82.3[76.5-89.5] vs. 42.9[28.2-59.5] years old; P<0.0001), more likely to have baseline comorbidities of cardiovascular disease, diabetes mellitus, hypertension, and chronic kidney disease (P<0.0001). They were more frequently prescribed ACEI/ARBs at baseline, and steroids, lopinavir/ritonavir, ribavirin and hydroxychloroquine during admission (P<0.0001). They also had a higher white cell count, higher neutrophil count, lower platelet count, prolonged prothrombin time and activated partial thromboplastin time, higher D-dimer, troponin, lactate dehydrogenase, creatinine, alanine transaminase, aspartate transaminase and alkaline phosphatase (P<0.0001). Multivariate Cox regression showed that age, cardiovascular disease, renal disease, diabetes mellitus, the use of ACEIs/ARBs and diuretics, and various laboratory tests remained significant predictors of mortality.ConclusionsWe report that an association between ACEIs/ARBs with COVID-19 related mortality even after adjusting for cardiovascular and other comorbidities, as well as medication use. Patients with greater comorbidity burden and laboratory markers reflecting deranged clotting, renal and liver function, and increased tissue inflammation, and ACEI/ARB use have a higher mortality risk.Key PointsWe report that an association between ACEIs/ARBs with COVID-19 related mortality even after adjusting for cardiovascular and other comorbidities, as well as medication use.Patients with greater comorbidity burden and laboratory markers reflecting deranged clotting, renal and liver function, and increased tissue inflammation, and ACEI/ARB use have a higher mortality risk.
Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses
Authors: Vastrad Basavaraj , Vastrad Chanabasayya , Kotturshetti Iranna 
Published: December 2020

AbstractSporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened. Pathway and GO enrichment analyses of DEGs were performed. Furthermore, the protein-protein interaction (PPI) network was predicted using the IntAct Molecular Interaction Database and visualized with Cytoscape software. In addition, hub genes and important modules were selected based on the network. Finally, we constructed target genes - miRNA regulatory network and target genes - TF regulatory network. Hub genes were validated. A total of 891 DEGs 448 of these DEGs presented significant up regulated, and the remaining 443 down regulated were obtained. Pathway enrichment analysis indicated that up regulated genes were mainly linked with glutamine degradation/glutamate biosynthesis, while the down regulated genes were involved in melatonin degradation. GO enrichment analyses indicated that up regulated genes were mainly linked with chemical synaptic transmission, while the down regulated genes were involved in regulation of immune system process. hub and target genes were selected from the PPI network, modules, and target genes - miRNA regulatory network and target genes - TF regulatory network namely YWHAZ, GABARAPL1, EZR, CEBPA, HSPB8, TUBB2A and CDK14. The current study sheds light on the molecular mechanisms of sCJD and may provide molecular targets and diagnostic biomarkers for sCJD.
Predicting the Evolution of COVID-19 Mortality Risk: a Recurrent Neural Network Approach
Authors: Villegas Marta , Gonzalez-Agirre Aitor , Gutiérrez-Fandiño Asier , Armengol-Estapé Jordi , Carrino Casimiro Pio , Pérez Fernández David , Soares Felipe , Serrano Pablo , Pedrera Miguel , García Noelia , Valencia Alfonso 
Published: December 2020

AbstractBackgroundThe propagation of COVID-19 in Spain prompted the declaration of the state of alarm on March 14, 2020. On 2 December 2020, the infection had been confirmed in 1,665,775 patients and caused 45,784 deaths. This unprecedented health crisis challenged the ingenuity of all professionals involved. Decision support systems in clinical care and health services management were identified as crucial in the fight against the pandemic.MethodsThis study applies Deep Learning techniques for mortality prediction of COVID-19 patients. Two datasets with clinical information (medication, laboratory tests, vital signs etc.) were used. They are comprised of 2,307 and 3,870 COVID-19 infected patients admitted to two Spanish hospital chains. Firstly, we built a sequence of temporal events gathering all the clinical information for each patient. Next, we used the temporal sequences to train a Recurrent Neural Network (RNN) model with an attention mechanism exploring interpretability. We conducted extensive experiments and trained the RNNs in different settings, performing hyperparameter search and cross-validation. We ensembled resulting RNNs to reduce variability and enhance sensitivity.ResultsWe assessed the performance of our models using global metrics, by averaging the performance across all the days in the sequences. We also measured day-by-day metrics starting from the day of hospital admission and the outcome day and evaluated the daily predictions. Regarding sensitivity, when compared to more traditional models, our best two RNN ensemble models outperform a Support Vector Classifier in 6 and 16 percentage points, and Random Forest in 23 and 18 points. For the day-by-day predictions from the outcome date, the models also achieved better results than baselines showing its ability towards early predictions.ConclusionsWe have shown the feasibility of our approach to predict the clinical outcome of patients infected with SARS-CoV-2. The result is a time series model that can support decision-making in healthcare systems and aims at interpretability. The system is robust enough to deal with real world data and it is able to overcome the problems derived from the sparsity and heterogeneity of the data. In addition, the approach was validated using two datasets showing substantial differences. This not only validates the robustness of the proposal but also meets the requirements of a real scenario where the interoperability between hospitals’ datasets is difficult to achieve.
Privacy-first health research with federated learning
Authors: Sadilek Adam , Liu Luyang , Nguyen Dung , Kamruzzaman Methun , Rader Benjamin , Ingerman Alex , Mellem Stefan , Kairouz Peter , Nsoesie Elaine O. , MacFarlane Jamie , Vullikanti Anil , Marathe Madhav , Eastham Paul , Brownstein John S. , Howell Michael , Hernandez John 
Published: December 2020

AbstractPrivacy protection is paramount in conducting health research. However, studies often rely on data stored in a centralized repository, where analysis is done with full access to the sensitive underlying content. Recent advances in federated learning enable building complex machine-learned models that are trained in a distributed fashion. These techniques facilitate the calculation of research study endpoints such that private data never leaves a given device or healthcare system. We show on a diverse set of health studies that federated models can achieve the same level of accuracy, precision, and generalizability, and result in the same interpretation as standard centralized statistical models whilst achieving significantly stronger privacy protections. This work is the first to apply modern and general federated learning methods to clinical and epidemiological research -- across a spectrum of units of federation and model architectures. As a result, it enables health research participants to remain in control of their data and still contribute to advancing science -- aspects that used to be at odds with each other.
Comparing Non-Communicable Disease Risk Factors in Asian Migrants and Native Koreans
Authors: Piao Heng , Yun Jae Moon , Shin Aesun , Kang Daehee , Cho Belong 
Published: December 2020

AbstractImportanceRegarding international migrants, the theories of healthy migration effect and sick migration effect both exist; thus, assessing the health of international migrants is crucial in the Republic of Korea, Asia, and even worldwide.ObjectiveTo compare non-communicable disease risk factors among Asian migrants in Korea and the Korean population.DesignA cross-sectional (2015) and longitudinal (2009□2015) observational study.SettingPopulation-wide analysis using the National Health Information Database of the Korean National Health Insurance Service for 2009□2015.ParticipantsAsian migrants (n=987,214) in Korea and Korean nationals (n=1,693,281) aged ≥20 years were included. In addition, Asian migrants were divided into Chinese, Japanese, Filipino, Vietnamese, and other Asian migrants.ExposureThe nationality of Asian migrants compared with Koreans.Main Outcomes and MeasuresThe prevalence of non-communicable disease risk factors, such as current smoking, obesity, diabetes, and hypertension, in 2015 was analyzed. Regarding the age-adjusted prevalence, direct age standardization was conducted separately by sex using 10-year age bands; the World Standard Population was used as the standard population.ResultsAmong participants aged ≥20 years, the age-adjusted prevalence of current smoking was higher among Chinese migrant men than among Korean men (P<0.001) and among other Asian migrant women than among Korean women (P<0.001). The age-adjusted prevalence of obesity was higher in Chinese, Filipino, and other Asian migrant women than in Korean women (P<0.001, P=0.002, and P<0.001, respectively). Among participants aged 20–49 years, the age-adjusted prevalence of diabetes and hypertension was higher in Filipino migrant women than in Korean women (P=0.009 and P<0.001, respectively).Conclusion and RelevanceThe current status of smoking and obesity among Asian migrants of specific nationalities is worse than that among native Koreans. Moreover, the health inequalities among Filipino migrant women in Korea, especially those aged 20–49 years, should be addressed.Key PointsQuestionDo international migrants in Korea have a health advantage regarding non-communicable disease risk factors?FindingsAmong participants aged ≥20 years, the problem of current smoking among Chinese migrant men and other Asian migrant women and that of obesity among Chinese, Filipino, and other Asian migrant women in Korea needs to be addressed. The prevalence of diabetes and hypertension was higher among Filipino migrant women than among Korean women in the 20–49-year age group.MeaningThe relationships between Asian migrant nationality and non-communicable disease risk factors provide evidence for targeting high-risk groups and improving policy development in Korea.
Functional imaging to guide network-based TMS treatments: toward a tailored medicine approach in Alzheimer’s disease
Authors: Bagattini Chiara , Brignani Debora , Bonnì Sonia , Gasparotti Roberto , Pievani Michela 
Published: December 2020

AbstractINTRODUCTIONTranscranial magnetic stimulation (TMS) has gained increasing attention as a potential therapeutic strategy in Alzheimer’s disease (AD). Among factors determining a clinical response, the choice of the stimulation site represents a key point. In this proof of concept study, we prove the feasibility of a tailored TMS targeting approach for AD, which stems from a network-based perspective. Based on functional imaging, the procedure allows to extract individual optimal targets meanwhile accounting for functional variability.METHODSSingle-subject resting-state fMRI was used to extract individual target coordinates of two networks primarily affected in AD, the default mode and the fronto-parietal network. The localization of these targets was compared to that of traditional group-level approaches and tested against varying degrees of TMS focality.RESULTSThe distance between individual fMRI-derived coordinates and traditionally-defined targets was significant for a focality <12mm, but not for >20mm. Comparison with anatomical labels confirmed a lack of 1:1 correspondence between anatomical and functional targets.DISCUSSIONThe proposed network-based fMRI-guided TMS approach allows targeting disorder-specific networks meanwhile accounting for inter-individual functional variability in Alzheimer’s disease. This approach might represent a step toward tailored TMS interventions for AD.
SARS-CoV-2 Envelope (E) Protein Interacts with PDZ-Domain-2 of Host Tight Junction Protein ZO1
Authors: Shepley-McTaggart Ariel , Sagum Cari A. , Oliva Isabela , Rybakovsky Elizabeth , DiGuilio Katie , Liang Jingjing , Bedford Mark T. , Cassel Joel , Sudol Marius , Mullin James M. , Harty Ronald N. 
Published: December 2020

AbstractNewly emerged SARS-CoV-2 is the cause of an ongoing global pandemic leading to severe respiratory disease in humans. SARS-CoV-2 targets epithelial cells in the respiratory tract and lungs, which can lead to amplified chloride secretion and increased leak across epithelial barriers, contributing to severe pneumonia and consolidation of the lungs as seen in many COVID-19 patients. There is an urgent need for a better understanding of the molecular aspects that contribute to SARS-CoV-2-induced pathogenesis and for the development of approaches to mitigate these damaging pathologies. The multifunctional SARS-CoV-2 Envelope (E) protein contributes to virus assembly/egress, and as a membrane protein, also possesses viroporin channel properties that may contribute to epithelial barrier damage, pathogenesis, and disease severity. The extreme C-terminal (ECT) sequence of E also contains a putative PDZ-domain binding motif (PBM), similar to that identified in the E protein of SARS-CoV-1. Here, we screened an array of GST-PDZ domain fusion proteins using either a biotin-labeled WT or mutant ECT peptide from the SARS-CoV-2 E protein. Notably, we identified a singular specific interaction between the WT E peptide and the second PDZ domain of human Zona Occludens-1 (ZO1), one of the key regulators of TJ formation/integrity in all epithelial tissues. We used homogenous time resolve fluorescence (HTRF) as a second complementary approach to further validate this novel modular E-ZO1 interaction. We postulate that SARS-CoV-2 E interacts with ZO1 in infected epithelial cells, and this interaction may contribute, in part, to tight junction damage and epithelial barrier compromise in these cell layers leading to enhanced virus spread and severe respiratory dysfunction that leads to morbidity. Prophylactic/therapeutic intervention targeting this virus-host interaction may effectively reduce airway barrier damage and mitigate virus spread.