bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of COVID-19 infection on maternal and reproductive health care services in governmental health institutions of Dessie town, North-East Ethiopia, 2020 G.C.
Authors: Temesgen Kibir , Workie Amare , Dilnessa Tenagnework 
Published: September 2020

AbstractBackgroundThe COVID 19 pandemic is causing huge stress on the health care system of all countries in the world. The impact of the pandemic is both social and economic. Pregnancy is an exciting and sometimes stressful experience. Being pregnant during a disease outbreak may add extra anxiety and concern for pregnant women and for those who provide care for them [1, 2].During the initial stages of the pandemic, it appeared Africa would be spared the burden of COVID-19. However, by April 7th, a total of 45 countries within the WHO African region had reported over 7000 cases (although some place it at over 10 000), with at least 292 deaths and 612 people recovered. Ethiopia, being one of the developing countries trying to address the diverse needs of its people, is currently at the verge of the epidemic [5, 7].ObjectivesThe general objective of this study was to assess the impact of COVID-19 infection on maternal and reproductive health care services among mothers getting service in governmental health institutions of Dessie town, 2020 G.C.MethodsInstitution based cross sectional study design using mixed (quantitative supplemented with qualitative) method was employed to identify the impact of COVID-19 infection on maternal and reproductive health care services among women who get service in governmental health institutions of Dessie town. The study was conducted from July 1-15 / 2020.ResultAccording to this study, Six percent (6%) of antenatal care attendees, 18% of delivery care attendees and nearly half (46.7%) of postnatal care attendees reported inappropriate service delivery due to fear of health care providers, shortage medical supplies and staff work load. The study also showed that utilization of these services was decreased due to fear of clients to go to health institutions.Conclusion and recommendationThis study concluded that COVID-19 significantly affects the quality and utilization of maternal and reproductive health care services. The study also showed that utilization of these services was decreased due to fear of clients to go to health institutions. Ministry of health should continue maternity and reproductive health care services such as family planning to be prioritized as an essential core health service.
The ground level ozone concentration is inversely correlated with the number of COVID-19 cases in Warsaw, Poland
Authors: Wiśniewski Oskar , Kozak Wiesław , Wiśniewski Maciej 
Published: September 2020

ABSTRACTCOVID-19, which is a consequence of infection with the novel viral agent SARS-CoV-2, first identified in China (Hubei Province), has been declared a pandemic by the WHO. As of September 10, 2020, over 70,000 cases and over 2,000 deaths have been recorded in Poland. Of the many factors contributing to the level of transmission of the virus, the weather appears to be significant. In this work we analyse the impact of weather factors such as temperature, relative humidity, wind speed and ground level ozone concentration on the number of COVID-19 cases in Warsaw, Poland. The obtained results show an inverse correlation between ground level ozone concentration and the daily number of COVID-19 cases.
IS THE INVERSE ASSOCIATION BETWEEN PARKINSON’S DISEASE AND SMOKING DUE TO CONFOUNDING?
Authors: Davis Susan M. 
Published: September 2020

ABSTRACTParkinson’s disease (PD) is inversely associated with smoking. Whether this association is due to a causal relationship or to confounding by a covariate of smoking is still debated.This study included populations of the United States and ten U.S. states from 2004 to 2016. The ten U.S. states included the five states with the highest PD incidence rates in 2017 (Vermont, Maine, Kansas, Missouri, Colorado) and the five states with the lowest PD incidence rates in 2017 (Arkansas, Mississippi, South Dakota, Nebraska, Alabama). The study used scatter plots to explore the association between PD incidence and smoking and the association between PD incidence and a covariate of smoking, lower endoscopy utilization.The results indicate that there is a weaker association between PD and smoking when compared to the association between PD and lower endoscopy utilization. For PD incidence verses current smoking, the coefficient of determination (R2) for the United States was 0.813 and ranged from a low of 0.000 for Arkansas to 0.798 for Colorado (average R2 for the ten states was 0.391). For PD incidence verses lower endoscopy utilization, the R2 for the United States was 0.995 and ranged from a low of 0.871 for South Dakota to 0.997 for Colorado (average R2 for the ten states was 0.959).The results suggest that the inverse association between PD incidence and smoking is confounded by the direct association between PD and lower endoscopy utilization. Further investigation of a possible relationship between PD incidence and lower endoscopy utilization is warranted.
Elevated serum uric acid is a facilitating mechanism for insulin resistance mediated accumulation of visceral adipose tissue
Authors: Fernández-Chirino Luisa , Antonio-Villa Neftali Eduardo , Fermín-Martínez Carlos Alberto , Márquez-Salinas Alejandro , Guerra Enrique C. , Vargas-Vázquez Arsenio , Almeda-Valdés Paloma , Gómez-Velasco Donají , Viveros-Ruiz Tania Leticia , Rojas Rosalba , Aguilar Salinas Carlos A. , Bello-Chavolla Omar Yaxmehen 
Published: September 2020

ABSTRACTOBJECTIVESerum uric acid (SUA) has been associated to cardiometabolic conditions such as insulin resistance (IR) and visceral adipose tissue (VAT) accumulation. Here, we aimed to clarify a unifying mechanism linking elevated SUA to IR and VAT.METHODSWe conducted analyses in 226 subjects from the UIEM cohort with both euglycemic hyperinsulinemic clamp (EHC) and dual X-ray absorptiometry (DXA) measurements for IR and VAT accumulation, and explored the role of SUA and adiponectin by developing a network of causal mediation analyses to assess their impact on IR and VAT. These models were then translated to two population-based cohorts comprising 6,337 subjects from NHANES 2003-2004 and 2011-2012 cycles in the US and ENSANUT Medio Camino 2016 in Mexico, using HOMA2IR and adipoIR as indicators of peripheral and adipose tissue IR, and METS-VF as a surrogate for VAT accumulation.ResultsSUA has a mediating role inside a bidirectional relationship between IR and visceral obesity, which was similar using either gold standard measurements or surrogate measures for IR and VAT. Furthermore, adiponectin acts as a linking mediator between elevated SUA and both peripheral IR and VAT accumulation. The proportion of the mechanism for IR-mediated (in either peripheral or adipose tissue) VAT accumulation was greater, compared to VAT-mediated IR accumulation (10.53%[9.23%-12.00%] to 5.44%[3.78%-7.00%]). Normal-range SUA levels can be used to rule-out underlying cardio-metabolic abnormalities in both men and women.CONCLUSIONSElevated SUA acts as mediator inside the bidirectional relationship between IR and VAT accumulation and these observations could be applicable at a phenotype scale.
Monitoring drinking water quality in nationally representative household surveys: cross-sectional analysis of 20 Multiple Indicator Cluster Surveys 2014-2019
Authors: Bain Rob , Johnston Rick , Khan Shane , Hancioglu Attila , Slaymaker Tom 
Published: September 2020

AbstractBackgroundThe Sustainable Development Goals set an ambitious new benchmark for safely managed drinking water services (SMDW), but many countries lack data on the availability and quality of drinking water.ObjectivesTo quantify the availability and microbiological quality of drinking water, monitor SMDW and examine risk factors for E. coli contamination in 20 low-and middle-income countries.MethodsA new water quality module for household surveys was implemented in Multiple Indicator Cluster Surveys. Teams used portable equipment to measure E. coli at the point of collection (PoC, n=48,323) and at the point of use (PoU, n=51,345) and asked respondents about the availability and location of drinking water services. E. coli levels were classified into risk categories and SMDW was calculated at the household- and domain-levels. Modified Poisson regression was used to explore risk factors for contamination.ResultsE. coli was commonly detected at PoC (range 16-90%) and was more likely at PoU (range 20-97%). Coverage of SMDW was 56% points lower than improved drinking water with water quality the limiting factor for SMDW in 14 countries. Detection of E. coli at PoC was associated with use of improved water sources (RR=0.64 [0.52-0.78]) located on premises (RR=0.78 [0.67-0.91]) but not with availability (RR=0.94 [0.82-1.06]). Households in the richest quintile (RR=0.67 [0.50-0.90]) and in communities with high (>75%) improved sanitation coverage (RR=0.95 [0.91-0.98]) were less likely to use contaminated water at PoU whereas animal ownership (RR=1.08 [1.03-1.14]) and rural residence (RR=1.11 [1.03-1.19]) increased risk of contamination.DiscussionWater quality data can be reliably collected in household surveys and can be used to assess inequalities in service levels, to track the SDG indicator of SMDW, and to examine risk factors for contamination. There is an urgent need to implement scalable and sustainable interventions to reduce exposure to faecal contamination through drinking water.
D-dimer dynamics in hospitalized COVID-19 patients: potential utility for diagnosis of pulmonary embolism
Authors: Cerdà Pau , Ribas Jesus , Iriarte Adriana , Mora-Luján José María , Torres Raquel , Río Belén del , Jofre Héctor Ignacio , Ruiz Yolanda , Huguet Marta , Fuset Maria Paz , Martínez-Yélamos Sergio , Santos Salud , Llecha Núria , Corbella Xavier , Riera-Mestre Antoni 
Published: September 2020

ABSTRACTBackgroundA higher incidence of thrombotic events, mainly pulmonary embolism (PE), has been reported in hospitalized patients with COVID-19. The main objective was to assess clinical and weekly laboratory differences in hospitalized COVID-19 patients according to occurrence of PE.MethodsThis retrospective study included all consecutive patients hospitalized with COVID-19 who underwent a computed tomography (CT) angiography for PE clinical suspicion. Clinical data and median blood test results distributed into weekly periods from COVID-19 symptoms onset were compared between PE and non-PE patients.ResultsNinety-two patients were included, 29 (32%) had PE. PE patients were younger (63.9 (SD13.7) vs 69.9 (SD12.5) years). Clinical symptoms and COVID-19 CT features were similar in both groups. PE was diagnosed after a mean of 20.0 (SD8.6) days from the onset of COVID-19 symptoms. Corticosteroid boluses were more frequently used in PE patients (62% vs. 43%). Median values [IQR] of D-dimer in PE vs non-PE patients were: week 2 (2010.7 [770.1-11208.9] vs 626.0 [374.0-2382.2]; p=0.04); 3 (3893.1 [1388.2-6694.0] vs 1184.4 [461.8-2447.8]; p=0.03); and 4 (2736.3 [1202.1-8514.1] vs 1129.1 [542.5-2834.6]; p=0.01). Median fold-increase of D-dimer between week 1 and 2 differed between groups (6.64 [3.02-23.05] vs 1.57 [0.64-2.71], p=0.003); ROC curve AUC was 0.879 (p=0.003) with a sensitivity and specificity for PE of 86% and 80%, respectively.ConclusionsAmong hospitalized COVID-19 patients, D-dimer levels are higher at weeks 2, 3 and 4 after COVID-19 symptom onset in patients who develop PE. This difference is more pronounced when the fold increase between weeks 1 and 2 is compared.
Privacy-Protecting, Reliable Response Data Discovery Using COVID-19 Patient Observations
Authors: Kim Jihoon , Neumann Larissa , Paul Paulina , Aratow Michael , Bell Douglas S. , Doctor Jason N. , Hinske Ludwig C. , Jiang Xiaoqian , Kim Katherine K. , Matheny Michael E. , Meeker Daniella , Pletcher Mark J. , Schilling Lisa M. , SooHoo Spencer , Xu Hua , Zheng Kai , Ohno-Machado Lucila ,   for the R2D2 Consortium
Published: September 2020

AbstractThere is an urgent need to answer questions related to COVID-19’s clinical course and associations with underlying conditions and health outcomes. Multi-center data are necessary to generate reliable answers, but centralizing data in a single repository is not always possible. Using a privacy-protecting strategy, we launched a public Questions & Answers web portal (https://covid19questions.org) with analyses of comorbidities, medications and laboratory tests using data from 202 hospitals (59,074 COVID-19 patients) in the USA and Germany. We find, for example, that 8.6% of hospitalizations in which the patient was not admitted to the ICU resulted in the patient returning to the hospital within seven days from discharge and that, when adjusted for age, mortality for hospitalized patients was not significantly different by gender or ethnicity.One Sentence SummaryPublicly Sharing Knowledge on COVID19 Without Sharing Patient-Level Data: A Privacy-Protecting Multivariate Analysis Approach
Single-cell Profiling of the Response to Poly I:C in Peripheral Blood Mononuclear Cells in Severe Asthma
Authors: Chen Ailu , Diaz-Soto Maria P. , Sanmamed Miguel F. , Adams Taylor , Schupp Jonas C. , Gupta Amolika , Britto Clemente , Sauler Maor , Yan Xiting , Liu Qing , Nino Gustavo , Cruz Charles S. Dela , Chupp Geoffrey L. , Gomez Jose L. 
Published: September 2020

AbstractBackgroundAsthma has been associated with impaired interferon responses. Multiple cell types have been implicated in these impaired responses and may be responsible for increased exacerbations and immunopathology of asthma.ObjectiveCharacterize the single-cell response to Poly I:C of peripheral blood mononuclear cells (PBMCs) of patients with severe asthma (SA).MethodsTwo complementary single-cell methods, DropSeq for single-cell RNA sequencing (scRNA-Seq) and mass cytometry (CyTOF), were used to profile PBMCs of SA and healthy controls (HC). Poly I:C and unstimulated cells were analyzed in this study.ResultsPBMCs (n=9,414) from five SA (n=6,099) and three HC (n=3,315) were profiled using scRNA-Seq. Six main cell subsets, including CD4+ T cells, CD8+ T cells, natural killer (NK) cells, B cells, dendritic cells (DCs), and monocytes, were identified. CD4+ T cells were the main cell type and demonstrated a pro-inflammatory profile characterized by increasedJAK1expression in unstimulated cells. Following Poly I:C stimulation, PBMCs from SA had a robust induction of interferon pathways compared with HC. Additional analyses to identify core regulators of the enhanced interferon response in SA identifiedIRF1, STAT1, IRF7, STAT2, andIRF9. CyTOF profiling of Poly I:C and unstimulated PBMCs (n=120,000) from the same individuals (SA=4; HC=2) demonstrated higher numbers of CD8+ effector cells and Th1 CD4+ T cells in unstimulated conditions, followed by a decrease of these two cell subsets after poly I:C stimulation.ConclusionSingle-cell profiling of PBMCs with scRNA-seq and CyTOF in patients with SA identified activation of pro-inflammatory pathways at baseline and strong response to Poly I:C, as well as quantitative changes in CD8+ effector cells and Th1 cells. Thus, transcriptomic and cell quantitative changes are associated with immune cell heterogeneity in severe asthma.Key Messages-Single-cell RNA sequencing identified a pro-inflammatory status in unstimulated PBMCs of severe asthmatics.-Mass cytometry identified quantitative differences in CD8+ effector cells and Th1 cells of severe asthmatics.-The response to Poly I:C stimulation, an interferon agonist, was not impaired in a subgroup of patients with severe asthma.Capsule summarySingle-cell profiling of PBMCs in severe asthmatics characterized gene expression responses to an interferon agonist and quantitative differences in distinct cell populations. Comprehensive single-cell immune may help identify key cell features responsible for asthma heterogeneity.
Identification and Epidemiological Characterization of Non-obese Type 2 Diabetic Sub-populations in the NFHS-4 Study using an Unsupervised Machine Learning Approach
Authors: Bej Saptarshi , Sarkar Jit , Biswas Saikat , Mitra Pabitra , Chakrabarti Partha , Wolkenhauer Olaf 
Published: September 2020

AbstractStudies on Type 2 Diabetes Mellitus (T2DM) have revealed heterogeneous sub-populations in terms of underlying pathologies. However, identification of subpopulations in epidemiological datasets remain unexplored. We here focus on the detection of T2DM clusters in epidemiological data, specifically analysing the National Family Health Survey-4 (NFHS-4) dataset containing a wide spectrum of features, including medical history, dietary and addiction habits, socio-economic and lifestyle patterns of 10,125 T2DM patients.Epidemiological data provide challenges for analysis due to the diverse types of features in it. In this case, applying the state-of-the-art dimension reduction tool UMAP conventionally was found to be ineffective for the NFHS-4 dataset, which contains continuous, ordinal and nominal feature types. Continuous features, although smaller in numbers, had a overpowering effect on the distribution of clusters.To address this problem, we implemented a distributed clustering workflow combining different similarity measure settings of UMAP, for clustering continuous, ordinal and nominal features separately. We integrated the reduced dimensions from each feature-type-distributed clustering to obtain interpretable and unbiased clustering of the data.Our analysis reveals four significant clusters, with two of them comprising mainly of non-obese T2DM patients. These non-obese clusters has lower mean age and majorly comprises of rural residents. Surprisingly, one of the obese clusters had 90% of the T2DM patients practising non-vegetarian diet though they did not show an increased intake of plant-based protein-rich foods.Our findings demonstrate the presence of a heterogeneity among T2DM patients with regard to socio-demography and dietary pattern. These results support the development of demography-specific screening criteria for T2DM as well as a demography-specific lifestyle modification guide-lines.
T cell anergy in COVID-19 reflects virus persistence and poor outcomes
Authors: Renner Kerstin , Müller Christine , Tiefenböck Charlotte , Salewski Jan-Niklas , Winter Frederike , Buchtler Simone , Malfertheiner Maximilian V. , Lubnow Matthias , Lunz Dirk , Graf Bernhard , Hitzenbichler Florian , Hanses Frank , Poeck Hendrik , Kreutz Marina , Orsó Evelyn , Burkhardt Ralph , Niedermair Tanja , Brochhausen Christoph , Gessner André , Salzberger Bernd , Mack Matthias 
Published: September 2020

AbstractCoronavirus disease 2019 (COVID-19) can lead to severe pneumonia and hyperinflammation. So far, insufficient or excessive T cell responses were described in patients. We applied novel approaches to analyze T cell reactivity and showed that T anergy is already present in non-ventilated COVID-19 patients, very pronounced in ventilated patients, strongly associated with virus persistence and reversible with clinical recovery. T cell activation was measured by downstream effects on responder cells like basophils, plasmacytoid dendritic cells, monocytes and neutrophils in whole blood and proved to be much more meaningful than classical readouts with PBMCs. Monocytes responded stronger in males than females and IL-2 partially reversed T cell anergy. Downstream markers of T cell anergy were also found in fresh blood samples of critically ill patients with severe T cell anergy. Based on our data we were able to develop a score to predict fatal outcomes and to identify patients that may benefit from strategies to overcome T cell anergy.
An Introduction to Proximal Causal Learning
Authors: Tchetgen Eric J Tchetgen , Ying Andrew , Cui Yifan , Shi Xu , Miao Wang 
Published: September 2020

AbstractA standard assumption for causal inference from observational data is that one has measured a sufficiently rich set of covariates to ensure that within covariate strata, subjects are exchangeable across observed treatment values. Skepticism about the exchangeability assumption in observational studies is often warranted because it hinges on investigators’ ability to accurately measure covariates capturing all potential sources of confounding. Realistically, confounding mechanisms can rarely if ever, be learned with certainty from measured covariates. One can therefore only ever hope that covariate measurements are at best proxies of true underlying confounding mechanisms operating in an observational study, thus invalidating causal claims made on basis of standard exchangeability conditions. Causal learning from proxies is a challenging inverse problem which has to date remained unresolved. In this paper, we introduce a formal potential outcome framework for proximal causal learning, which while explicitly acknowledging covariate measurements as imperfect proxies of confounding mechanisms, offers an opportunity to learn about causal effects in settings where exchangeability on the basis of measured covariates fails. Sufficient conditions for nonparametric identification are given, leading to the proximal g-formula and corresponding proximal g-computation algorithm for estimation. These may be viewed as generalizations of Robins’ foundational g-formula and g-computation algorithm, which account explicitly for bias due to unmeasured confounding. Both point treatment and time-varying treatment settings are considered, and an application of proximal g-computation of causal effects is given for illustration.
Developing a machine learning environmental allergy prediction model from real world data through a novel decentralized mobile study platform
Authors: Sarabu Chethan , Steyaert Sandra , Shah Nirav R. 
Published: September 2020

AbstractEnvironmental allergies cause significant morbidity across a wide range of demographic groups. This morbidity could be mitigated through individualized predictive models capable of guiding personalized preventive measures. We developed a predictive model by integrating smartphone sensor data with symptom diaries maintained by patients. The machine learning model was found to be highly predictive, with an accuracy of 0.801. Such models based on real-world data can guide clinical care for patients and providers, reduce the economic burden of uncontrolled allergies, and set the stage for subsequent research pursuing allergy prediction and prevention. Moreover, this study offers proof-of-principle regarding the feasibility of building clinically useful predictive models from “messy,” participant derived real-world data.
Auxin-degron system identifies immediate mechanisms of Oct4
Authors: Bates Lawrence E , Alves Mariana R P , Silva José C R 
Published: September 2020

AbstractThe pluripotency factor Oct4 is essential for the maintenance of naïve pluripotent stem cells in vitro and in vivo. However, the specific role of Oct4 in this process remains unknown. Here, we developed a rapid protein-level Oct4 depletion system that demonstrates that the immediate downstream response to loss of Oct4 is reduced expression of key pluripotency factors. Our data show a requirement for Oct4 for the efficient transcription of several key pluripotency factors, and suggest that expression of trophectoderm markers is a subsequent event. Additionally, we find that Nanog is competent to bind to the genome in the absence of Oct4, and this binding is in fact enhanced. Globally, however, active enhancer associated histone mark H3K27ac is depleted. Our work establishes that while Oct4 is required for the maintenance of the naïve transcription factor network, at a normal ESC level it antagonises this network through inhibition of Nanog binding.