bluuebunny/crossref_metadata_2025_split huggingface dataset:
An epithelial microRNA upregulates airway IL-25 and TSLP expression in type 2-high asthma via targeting CD39-extracellular ATP axis
Authors: Zhang Kan , Feng Yuchen , Liang Yuxia , Wu Wenliang , Chang Chenli , Chen Dian , Chen Shengchong , Yi Lingling , Zhen Guohua 
Published: September 2020

AbstractThe presence of type 2 inflammation is a prominent endotype of asthma. Airway epithelial cell-derived cytokines IL-25, IL-33 and TSLP initiate type 2 inflammation. However, the upstream signaling pathway regulating these cytokines’ expression remains elusive. We identified a small set of epithelial microRNAs differentially expressed between type 2-low and –high asthma patients. MiR-206 was the most highly expressed microRNA in type 2-high asthma relative to type 2-low asthma, but was downregulated in both asthma subsets compared to control subjects. CD39, an ecto-nucleotidase degrading extracellular ATP, was a target of miR-206 and upregulated in asthma. In cultured human bronchial epithelial cells, allergen-induced rapid accumulation of extracellular ATP was responsible for miR-206 downregulation and CD39 upregulation, suggesting a protective mechanism to eliminate excessive ATP. Importantly, BALF ATP levels were increased in asthma patients, and strongly correlated with elevated IL-25 and TSLP expression in type 2-high asthma. Intriguingly, inhibition of airway miR-206 increased Cd39 expression, suppressed airway ATP accumulation and Il-25, Il-33, Tslp expression, and alleviated type 2 inflammation in a mouse model of asthma. In contrast, airway miR-206 overexpression had opposite effects. Taken together, airway epithelial miR-206 upregulates IL-25, TSLP expression via targeting CD39-extracellular ATP axis in type 2-high asthma.
Combination of Tocilizumab and Steroids to Improve Mortality in Patients with Severe COVID-19 Infection: A Spanish, Multicenter, Cohort Study
Authors: Ruiz-Antorán Belén , Sancho-López Aránzazu , Torres MD Ferrán , Concha Víctor Moreno-Torres , de Abechuco Itziar de Pablo López , López Paulina García , Abad-Santos Francisco , Fernández Clara María Rosso , Aldea-Perona Ana , Montané Eva , Aparicio-Hdez Ruth M. , LLop Rius Roser , Pedrós Consuelo , Gijón Paloma , Carballo Carolina Hernández , Martínez María José Pedrosa , Jiménez Consuelo Rodríguez , Prada-Ramallal Guillermo , García Lourdes Cabrera , García Josefa Andrea Aguilar , Sanjuan-Jimenez Rocío , Barraza Evelyn Iveth Ortiz , Sánchez-Chica Enrique , Fernández-Cruz Ana 
Published: September 2020

ABSTRACTBackgroundWe aimed to determine the impact of tocilizumab use in severe COVID-19 pneumonia mortality.MethodsWe performed a multicentre retrospective cohort study in 18 tertiary hospitals in Spain, from March to April 2020. Consecutive patients admitted with severe COVID-19 treated with tocilizumab were compared to patients not treated with tocilizumab, adjusting by Inverse Probability of the Treatment Weights (IPTW). Tocilizumab effect in patients receiving steroids during the 48h following inclusion was analyzed.ResultsDuring the study period, 506 patients with severe COVID-19 fulfilled inclusion criteria. Among them, 268 were treated with tocilizumab and 238 patients were not. Median time to tocilizumab treatment from onset of symptoms was 11 days (IQR 8-14). Global mortality was 23.7%. Mortality was lower in patients treated with tocilizumab than in controls (16.8% versus 31.5%, HR 0.514 [95CI 0.355-0.744], p< 0.001; weighted HR 0.741 [95CI 0.619-0.887], p = 0.001). Tocilizumab treatment reduced mortality by 14.7% relative to no tocilizumab treatment (RRR 46.7%). We calculated a number necessary to treat of 7. Among patients treated with steroids, mortality was lower in patients treated with tocilizumab than in those treated with steroids alone (10.9% versus 40.2%, HR 0.511 [95CI 0.352-0.741], p = 0.036; weighted HR 0.6 [95CI 0.449-0.804], p< 0.001) (Interaction p = 0.094).ConclusionsThese results show that survival of patients with severe COVID-19 is higher in patients treated with tocilizumab than in those not treated, and that tocilizumab effect adds to that of steroids administered to non-intubated cases with COVID-19 during the first 48 hours of presenting with respiratory failure despite of oxygen therapy. Randomised controlled studies are needed to confirm these results.SummaryWe investigated in-hospital mortality of patients with severe SARS-CoV-2 pneumonia in a multicenter series of patients treated with tocilizumab compared to controls, and adjusted using IPTW. Our results show a beneficial impact of tocilizumab treatment in SARS-CoV-2 pneumonia, that adds to that of steroids.
COVID-19 in patients with hepatobiliary and pancreatic diseases: A single-centre cross-sectional study in East London
Authors: Ullah Abu Z M Dayem , Sivapalan Lavanya , Kocher Hemant M , Chelala Claude 
Published: September 2020

ABSTRACTObjectiveTo explore risk factors associated with COVID-19 susceptibility and survival in patients with pre-existing hepato-pancreato-biliary (HPB) conditions.DesignCross-sectional study.SettingEast London Pancreatic Cancer Epidemiology (EL-PaC-Epidem) study at Barts Health NHS Trust, UK. Linked electronic health records were interrogated on a cohort of participants (age ≥ 18 years), reported with HPB conditions between 1 April 2008 and 6 March 2020.ParticipantsEL-PaC-Epidem study participants, alive on 12 February 2020, and living in East London within the previous six months (n=15 440). The cohort represents a multi-ethnic population with 51.7% belonging to the non-White background.Main outcome measureCOVID-19 incidence and mortality.ResultsSome 226 (1.5%) participants had confirmed COVID-19 diagnosis between 12 February and 12 June 2020, with an increased odds for men (OR 1.56; 95% CI 1.2 to 2.04) and Black ethnicity (2.04; 1.39 to 2.95) as well as patients with moderate to severe liver disease (2.2; 1.35 to 3.59). Each additional comorbidity increased the odds of infection by 62%. Substance mis-users were at more risk of infection, so were patients on Vitamin D treatment. The higher odds ratios in patients with chronic pancreatic or mild liver conditions, age>70, and history of smoking or obesity were due to co-existing comorbidities. Increased odds of death were observed for men (3.54; 1.68 to 7.85) and Black ethnicity (3.77; 1.38 to 10.7). Patients having respiratory complications from COVID-19 without a history of chronic respiratory disease also had higher odds of death (5.77; 1.75 to 19).ConclusionsIn this large population-based study of HPB patients, men, Black ethnicity, pre-existing moderate to severe liver conditions, six common medical multi-morbidities, substance mis-use, and a history of Vitamin D treatment independently posed higher odds of acquiring COVID-19 compared to their respective counterparts. The odds of death were significantly high for men and Black people.STRENGTHS AND LIMITATIONS OF THIS STUDYFirst multi-ethnic population-based study on COVID-19 in patients with hepato-pancreato-biliary group of diseases.Systematic identification of the effect, or the lack of it, of individual demographic and clinical factors on the infection and mortality of COVID-19 in a large cohort of over 15 000 patients, robustly controlling for potential confounders in their evaluation.Access to longitudinal data from linked primary and secondary care electronic health records, and use of rule-based phenotyping algorithms allowed for improved completeness and accuracy of the explored variables.Some observed increased odds of SARS-CoV-2 infection and related death could be plausibly explained by unmeasured confounding.The effects reported in the study could be influenced by the relatively smaller size of COVID-19 cases within this cohort.
Molecular characterisation of longitudinally collected circulating cell-free DNA in HPV+ve and HPV-ve oropharyngeal cancer
Authors: Thomson John P , Warlow Sophie J , Adamowicz Martyna , Thain Helen , Cuschieri Kate , Li Lucy Q , Conn Brendan , Hay Ashley , Nixon Iain J , Aitman Timothy J 
Published: September 2020

AbstractOropharyngeal squamous cell carcinoma (OPSCC) is an increasing global health problem and is divided into two types dependent on association with human papillomavirus (HPV), with a more favourable prognosis in virus-associated tumours. Current methods of establishing viral aetiology, assessing response to therapy and clinical monitoring rest on tissue biopsy, clinical examination and post-treatment imaging. However, tissue biopsy is invasive and carries significant risk of morbidity, and post-treatment scans are frequently indeterminate. Analysis of cell-free DNA (cfDNA) from the circulation provides a minimally invasive method for detecting and monitoring cancer-derived DNA fragments, with the potential for enhancing clinical care. Through the longitudinal collection of 166 blood samples in 67 OPSCC patients we evaluate the utility of three cfDNA analysis methods: droplet digital PCR (ddPCR) and fragment size analysis in both HPV+ve and HPV-ve disease, and ultra-deep sequencing in patients with HPV-ve disease. We show that ddPCR analysis of cfDNA for five HPV types (16, 18, 31, 33 & 35) is strongly concordant with existing clinical assays (p16 immunohistochemistry (IHC) and quantitative PCR analysis of solid tumour tissue) and that cfDNA fragment size was reduced in OPSCC patients compared to healthy controls. Sequential ddPCR measurements of cfDNA HPV copy number showed a decrease to undetectable levels in all 30 HPV+ve patients in at least one of their post-treatment samples and a corresponding increase in cfDNA fragment size in patients who had a complete response to chemoradiotherapy. In two HPV+ve patients, clinical decision-making based on HPV ddPCR of cfDNA may have led to earlier detection of relapse in one patient or avoided surgical exploration in a second patient, which led to resection of tissue that did not harbour malignancy. In HPV-ve disease, ultra-deep sequencing identified tumour-derived somatic mutations of circulating cfDNA in genes such as TP53 and members of the ERBB family that are potential markers of therapeutic responsiveness and patient prognosis. Together our data suggest that analysis of circulating cfDNA can enhance current clinical strategies for assessing therapeutic response and disease monitoring in both HPV+ve and HPV-ve OPSCC.
The impact of timely cancer diagnosis on age disparities in colon cancer survival in New Zealand
Authors: Pilleron Sophie , Maringe Camille , Charvat Hadrien , Atkinson June , Morris Eva , Sarfati Diana 
Published: September 2020

AbstractObjectiveWe described the role of patient-related and clinical factors on age disparities in colon cancer survival among patients aged 50-99 using New Zealand population-based cancer registry data linked to hospitalization data.DesignWe included new colon cancer cases diagnosed between 1 January 2006 and 31 July 2017, followed up to 31 December 2019. We linked these cases to hospitalisation data for the five years before the cancer diagnosis. We modelled the effect of age at diagnosis, sex, deprivation, comorbidity, and route to diagnosis on colon cancer survival by stage at diagnosis (localized, regional, distant, missing).ResultsNet survival decreased as the age at diagnosis increased, notably in advanced stages and missing stage. The excess mortality in older patients was minimal for localised cancers, maximal during the first six months for regional cancers, the first 18 months for distant cancers, and over the three years for missing stages. The age pattern of the excess mortality hazard varied according to sex for distant cancers, the route to diagnosis for regional and distant cancers, and comorbidity for cancer with missing stages.ConclusionThe present population-based study shows that factors reflecting timeliness of cancer diagnosis most affected the difference in survival between middle-aged and older patients, probably by impacting treatment strategy. Because of the high risk of poor outcomes related to treatment in older patients, efforts made to improve earlier diagnosis in older patients are likely to help reduce age disparities in colon cancer survival in New Zealand.
Network for subclinical prognostication of COVID 19 Patients from data of thoracic roentgenogram: A feasible alternative screening technology
Authors: Bararia Akash , Ghosh Abhirup , Bose Chiranjit , Bhar Debarati 
Published: September 2020

AbstractBackground and Study AimCOVID 19 is the terminology driving people’s life in the year 2020 without a supportive globally high mortality rate. Coronavirus lead pandemic is a new found disease with no gold standard diagnostic and therapeutic guideline across the globe. Amidst this scenario our aim is to develop a prediction model that makes mass screening easy on par with reducing strain on hospitals diagnostic facility and doctors alike. For this prediction model, a neural network based on Chest X-ray images has been developed. Alongside the aim is also to generate a case record form that would include prediction model result along with few other subclinical factors for generating disease identification. Once found positive then only it will proceed to RT-PCR for final validation. The objective was to provide a cheap alternative to RT-PCR for mass screening and to reduced burden on diagnostic facility by keeping RT-PCR only for final confirmation.MethodsDatasets of chest X-ray images gathered from across the globe has been used to test and train the network after proper dataset curing and augmentation.ResultsThe final neural network-based prediction model showed an accuracy of 81% with sensitivity of 82% and specificity of 90%. The AUC score obtained is 93.7%.Discussion and ConclusionThe above results based on the existing datasets showcase our model capability to successfully distinguish patients based on Chest X-ray (a non-invasive tool) and along with the designed case record form it can significantly contribute in increasing hospitals monitoring and health care capability.
Geographical variation and factors associated with unsafe child stool disposal in Ethiopia: A spatial and multilevel analysis
Authors: Sahiledengle Biniyam , Teferu Zinash , Tekalegn Yohannes , Awoke Tadesse , Zenbaba Demisu , Bekele Kebebe , Tesemma Abdi , Seyoum Fikadu , Woldeyohannes Demelash 
Published: September 2020

AbstractBackgroundUnsafe disposal of children’s stool makes children susceptible to fecal-oral diseases and children remain vulnerable till the stools of all children are disposed of safely. There is a paucity of data on spatial distribution and factors associated with unsafe child stool disposal in Ethiopia. Previous estimates, however, do not include information regarding individual and community-level factors associated with unsafe child stool disposal. Hence, the current study aimed (i) to explore the spatial distribution and (ii) to identify factors associated with unsafe child stool disposal in Ethiopia.MethodsA secondary data analysis was conducted using the recent 2016 Ethiopian demographic and health survey data. A total of 4145 children aged 0–23 months with their mother were included in this analysis. The Getis-Ord spatial statistical tool was used to identify high and low hotspots areas of unsafe child stool disposal. The Bernoulli model was applied using Kilduff SaTScan version 9.6 software to identify significant spatial clusters. A multilevel binary logistic regression model was fitted to identify factors associated with unsafe child stool disposal.ResultsUnsafe child stool disposal was spatially clustered in Ethiopia (Moran’s Index = 0.211, p-value < 0.0001), and significant spatial SaTScan clusters of areas with a high rate of unsafe child stool disposal were detected. The most likely primary SaTScan cluster was detected in Tigray, Amhara, Afar (north), and Benishangul-Gumuz (north) regions (LLR: 41.62, p< 0.0001). Unsafe child stool disposal is more prevalent among households that had unimproved toilet facility (AOR = 1.54, 95%CI: 1.17-2.02), and those with high community poorer level (AOR: 1.74, 95%CI: 1.23-2.46). Higher prevalence of unsafe child stool disposal was also found in households with poor wealth quintiles. Children belong to agrarian regions (AOR: 0.62, 95%CI 0.42-0.91), children 6-11 months of age (AOR: 0.66, 95%CI: 0.52-0.83), 12-17 months of age (AOR: 0.68, 95%CI: 0.54-0.86), and 18-23 months of age (AOR: 0.58, 95%CI: 0.45-0.74) had lower odds of unsafe child stool disposal.ConclusionsUnsafe child stool disposal was spatially clustered. Higher odds of unsafe child stool disposal were found in households with high community poverty level, poor, unimproved toilet facility, and with the youngest children. Hence, the health authorities could tailor effective child stool management programs to mitigate the inequalities identified in this study. It is also better to consider child stool management intervention in existing sanitation activities considering the identified factors.
Performance and Robustness of Machine Learning-based Radiomic COVID-19 Severity Prediction
Authors: Yip Stephen S.F. , Klanecek Zan , Naganawa Shotaro , Kim John , Studen Andrej , Rivetti Luciano , Jeraj Robert 
Published: September 2020

ABSTRACTObjectivesThis study investigated the performance and robustness of radiomics in predicting COVID-19 severity in a large public cohort.MethodsA public dataset of 1110 COVID-19 patients (1 CT/patient) was used. Using CTs and clinical data, each patient was classified into mild, moderate, and severe by two observers: (1) dataset provider and (2) a board-certified radiologist. For each CT, 107 radiomic features were extracted. The dataset was randomly divided into a training (60%) and holdout validation (40%) set. During training, features were selected and combined into a logistic regression model for predicting severe cases from mild and moderate cases. The models were trained and validated on the classifications by both observers. AUC quantified the predictive power of models. To determine model robustness, the trained models was cross-validated on the inter-observer’s classifications.ResultsA single feature alone was sufficient to predict mild from severe COVID-19 with and (p<< 0.01). The most predictive features were the distribution of small size-zones (GLSZM-SmallAreaEmphasis) for provider’s classification and linear dependency of neighboring voxels (GLCM-Correlation) for radiologist’s classification. Cross-validation showed that both . In predicting moderate from severe COVID-19, first-order-Median alone had sufficient predictive power of . For radiologist’s classification, the predictive power of the model increased to as the number of features grew from 1 to 5. Cross-validation yielded and .ConclusionsRadiomics significantly predicted different levels of COVID-19 severity. The prediction was moderately sensitive to inter-observer classifications, and thus need to be used with caution.Key pointsInterpretable radiomic features can predict different levels of COVID-19 severityMachine Learning-based radiomic models were moderately sensitive to inter-observer classifications, and thus need to be used with caution
Electromyography recordings detect muscle activity before observable contractions in acute stroke care
Authors: Papazian Christina , Baicoianu Nick A. , Peters Keshia M. , Feldner Heather , Steele Katherine M. 
Published: September 2020

ABSTRACTObjectiveTo determine whether electromyography (EMG) can be used in acute stroke care to identify muscle activity in patients with no observable activity during clinical examination.DesignStroke survivors admitted to a level one trauma hospital with initial NIH Stroke Scale scores of two or higher for arm function were recruited within five days of stroke (average 3±1 days), including eleven stroke survivors (7 male/4 female, age 56±11) with no observable or palpable arm muscle activity (Manual Muscle Test, MMT=0) and ten stroke survivors (6 male/4 female, age 64±1) with observable muscle activity (MMT>0). We placed wireless EMG sensors on five major muscle groups (anterior deltoid, biceps, triceps, wrist extensors, and wrist flexors) of the impaired arm for 3-4 hours during standard care.ResultsWe were able to identify muscle contractions in all five muscles for all participants from EMG recordings. Contractions were easily identified from 30-minutes of monitoring for participants with MMT>0, but up to three hours of monitoring was required for participants with MMT=0 to detect contractions in all five muscles during standard care. Only the wrist extensors demonstrated significantly larger amplitude contractions for participants with MMT>0 than MMT=0. Co-contraction was rare, involving less than 10% of contractions. Co-contraction of two muscles most commonly aligned with the flexor synergy pattern commonly observed after stroke. For participants with MMT=0, number of contractions and maximum amplitude in acute care were moderately correlated with MMT scores at follow-up.ConclusionMuscle activity can be detected with surface EMG recordings during standard care, even for stroke survivors with no observable activity by clinical exam.
Understanding SARSCOV-2 propagation, impacting factors to derive possible scenarios and simulations
Authors: Mehl-Madrona Lewis , Bricaire François , Cuyugan Adrian , Barac Jovan , Parvaiz Asadullah , Jamil Ali Bin , Iqbal Sajid , Vally Ryan , Koliali Meryem , Sellier Mohamed Karim 
Published: September 2020

AbstractObjectivesWe aimed to analyze factors impacting the Covid-19 epidemic on a macro level, comparing multiple countries across the world, and verifying the occurrence at a micro level through cluster analysis.DesignStatistical analysis of large datasets.MethodsWe used publicly available large world datasets (1-11). Data was transformed to fit parametric distributions prior to statistical analyses, which were performed with Student’s t-test, linear regression and post-hoc tests. Especially for ordinary least squares regression, natural logarithmic transformations were done to remediate normality violations in the standardized residuals.ResultsThe severity of the epidemic was most strongly related to exposure to ultraviolet light and extrapolated levels of vitamin D and to the health of the population, especially with regards to obesity. We found no county with an obesity level < 8% with a severe epidemic. We also found that countries where the population benefited from sun exposure or vitamin D supplementation and spent time outside fared well. Factors related to increased propagation of the virus included the use of heating ventilation and air conditioning (HVAC), population density, poorly aerated gatherings, relative humidity, timely policies of closing clustering places until aeration was improved, and daily amount of ridership on public transportation, especially subways. Population lockdowns, masks, and blood type did not provide much explanatory power. The excess mortality observed is within the ranges of severe past influenza epidemics of 2016/2017 or 1999/2000.ConclusionsOur study suggested that prevention measures should be directed to improving aeration systems, enhancing diets and exercise, and ensuring adequate levels of vitamin D. Further research on masking is indicated as our study could not separate policies from how well they were actually followed.FundingThis research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors’Strengths and Limitations of the StudyThe Study examines large datasets across countries to look for macrotrends in management of the Covid-19 outbreak.The Study cannot necessarily establish causation but rather correlation.The Study raises some novel possibilities for further studies in relation to country-wide and individual-level susceptibility to Covid-19 and to other epidemics in general.The Study raises questions about some political policies based upon country-level comparisons and suggests some areas for exploration of prevention policies.