bluuebunny/crossref_metadata_2025 huggingface dataset:
Remnant Cystic Duct Disease After Cholecystectomy: A Case Series
Authors: Xu Suqin , Zou Shubing
Published: June 2020

Background:

Remnant cystic duct (RCD) may be responsible for postcholecystectomy syndrome. We present our experience with the management of remnant cystic duct disease (RCDD) after cholecystectomy.

Methods:

Over a period of 5 years, 10 patients underwent reoperation for RCDD in our hospital. Cystic duct was identified by intraoperative exploration.

Results:

There were 4 men and 6 women ranging in age from 37 to 76 years (median, 60.40 y). All 10 had biliary pain, 5 had jaundice, and 2 had pancreatitis. The time from initial cholecystectomy to reoperation ranged from 4 to 28 years (median, 12.22 y). Eight patients had an abnormal liver function. Six of these 8 patients (75%) were diagnosed by magnetic resonance cholangiopancreatography. In 7 patients treated by completed cholecystectomy (6 by laparoscopy and 1 by laparotomy), pathology proved the presence of an RCD and chronic cholecystitis. The other 3 patients were treated by removing stones. All patients had 6- to 14-day hospital stays after reoperation, except for 1 patient with a 3-day stay.

Conclusions:

RCDD may be a more reasonable explanation for a source of postcholecystectomy syndrome. Magnetic resonance cholangiopancreatography has a role in the diagnosis of RCDD. We believe that excision of diseased RCD is necessary and that laparoscopic surgery is feasible.
Effectiveness of mepolizumab in a real-life cohort of patients with severe refractory eosinophilic asthma and multiple comorbidities
Authors: Crimi Claudia , Campisi Raffaele , Cacopardo Giulia , Intravaia Rossella , Nolasco Santi , Porto Morena , Pelaia Corrado , Crimi Nunzio
Published: June 2020

BACKGROUND

Patients with severe asthma often suffer from comorbidities whose impact on the course of biological therapy has not been elucidated yet.

OBJECTIVE

To evaluate real-life effectiveness and the presence/absence of predictors of treatment response in patients with one or more comorbidities who received mepolizumab (MEPO) for the treatment of severe eosinophilic asthma (EA).

METHODS

Health records of 31 patients were retrospectively analyzed. Asthma control test (ACT) score, blood eosinophil count, forced expiratory volume in 1 second (FEV1), FEV1% of predicted and FEV1/FVC (Forced Vital Capacity) ratio, oral corticosteroid (OCS) dosage and exacerbations were recorded at baseline (T0), after 3 (T1), 6 (T3), nine (T6) and 12 months (T12). A clinical response was defined as: i) 30% exacerbation decrease; ii) 80% blood eosinophilia reduction; iii) 3 point ACT increase; iv) FEV1 increase ≥ 200 mL.

RESULTS

At T12 blood eosinophil level decreased by 89.89% (p>0.0001), an improvement in ACT of 3 points from baseline was recorded in 80.65% of patients (p>0.0001) and 96.77% of patients reduced by minimum 30% the number of exacerbations (p>0.0001). 84% of patients discontinued OCS (p>0.0001). FEV1 increased by 0.22 (p=0.0224) while FEV1/FVC was statistically significant only at T1. No significant differences were generally found among patients with a specific comorbidity. The number of comorbidities did not influence treatment response. Neither the comorbidities nor other characteristics (sex, BMI, age, smoking, baseline eosinophil level) influenced treatment response.

CONCLUSIONS

MEPO in patients with severe EA is effective regardless of the presence of one or more comorbidities.
Diagnostic accuracy of a host response point-of-care test in patients with suspected COVID-19
Authors: Clark Tristan W , Brendish Nathan J , Poole Stephen , Naidu Vasanth V , Mansbridge Christopher , Norton Nicholas , Wheeler Helen , Presland Laura , Ewings Sean
Published: June 2020

Rationale

Management of the COVID-19 pandemic is hampered by long delays associated with centralised laboratory PCR testing. In hospitals this leads to poor patient flow and nosocomial transmission and rapid, accurate diagnostic tests are urgently required. The FebriDx is a point-of-care test that detects an antiviral host response protein in finger prick blood within 10 minutes, but its accuracy for the detection of COVID-19 is unknown.

Objectives

To evaluate the diagnostic accuracy of FebriDx in hospitalised patients during the first wave of the pandemic

Methods

Measures of diagnostic accuracy were calculated based on FebriDx results compared to the reference standard of PCR, and stratified by duration of symptoms. A multivariable predictive model was developed and underwent internal validation.

Results

FebriDx was performed on 251 patients and gave a valid result in 248. 118 of 248 (48%) were PCR positive for COVID-19. Sensitivity of FebriDx for the identification of COVID-19 was 93% (110/118; 95% CI 87 to 97%) and specificity was 86% (112/130; 95%CI 79 to 92%). Positive and negative likelihood ratios were 6.73 (95%CI 4.37 to 10.37) and 0.08 (95%CI 0.04 to 0.15) respectively. In the multivariate model diagnosis of COVID-19 was not significantly influenced by clinical symptoms and signs, and FebriDx accuracy was not improved by restricting testing to those with duration of symptoms of less than seven days.

Conclusions

During the first wave of the pandemic, FebriDx had high sensitivity for the identification of COVID-19 in hospitalised adults and could be deployed as a front door triage tool.

Trial registration

ISRCTN14966673
SARS-CoV-2 genetic variations associated with COVID-19 severity
Authors: Aiewsakun Pakorn , Wongtrakoongate Patompon , Thawornwattana Yuttapong , Hongeng Suradej , Thitithanyanont Arunee
Published: June 2020

Herein, we performed a genome-wide association study on SARS-CoV-2 genomes to identify genetic variations that might be associated with the COVID-19 severity. 152 full-length genomes of SARS-CoV-2 that were generated from original clinical samples and whose patient status could be determined conclusively as either “asymptomatic” or “symptomatic” were retrieved from the GISAID database. We found that nucleotide variations at the genomic position 11,083, locating in the coding region of non-structural protein 6, were associated with the COVID-19 severity. While the 11083G variant (i.e. having G at the position 11,083) was more commonly found in symptomatic patients, the 11083T variant appeared to associate more often with asymptomatic infections. We also identified three microRNAs that differentially target the two variants, namely miR-485-3p, miR-539-3p, and miR-3149. This may in part contribute to the differential association of the two SARS-CoV-2 variants with the disease severity.
Effectiveness of Growth Hormone–Releasing Hormone Agonists (GHRH-A) in Chronic Kidney Disease-Induced Heart Failure with Preserved Ejection Fraction
Authors: Rieger Angela C. , Bagno Luiza L , Salerno Alessandro , Florea Victoria , Rodriguez Jose , Rosado Marcos , Turner Darren , Takeuchi Lauro M. , Dulce Raul , Balkan Wayne , Schulman Ivonne H. , Schally Andrew , Hare Joshua M.
Published: June 2020

Background

Therapies that improve morbidity and mortality in heart failure with preserved ejection fraction (HFpEF) are lacking. Growth hormone releasing hormone analogues (GHRH-A) reverse fibrosis and improve cardiac function in ischemic and non-ischemic animal models. We tested the hypothesis that GHRH-A treatment ameliorates chronic kidney disease (CKD)-induced HFpEF in a large animal model.

Methods

Female Yorkshire pigs (n=16) underwent 5/6 nephrectomy via renal artery embolization, which induced HFpEF, and 12-weeks later received daily subcutaneous injections of GHRH-A (n=8) or placebo (n=8). Kidney function, renal and cardiac MRI, pressure-volume loops, and electrical stimulation were assessed at baseline, 12-weeks, and 16-18 weeks post-embolization.

Results

The CKD model was confirmed by increased creatinine and BUN. HFpEF was demonstrated at 12 weeks by maintenance of ejection fraction associated with increased left ventricular mass, relative wall thickening, end-diastolic pressure (EDP), end-diastolic pressure-volume relationship (EDPVR), and tau. After 6 weeks of treatment, diastolic function improved in the GHRH-A group, evidenced by normalization of EDP (p=0.03) associated with improved diastolic compliance as measured by EDP/EDV ratio (p=0.018).

Conclusion

A beneficial effect of GHRH-A in diastolic function was observed in a CKD large animal model that manifests the characteristics of HFpEF. These findings have important therapeutic implications for the HFpEF syndrome.
Pharmacogenetics at scale: An analysis of the UK Biobank
Authors: McInnes Greg , Lavertu Adam , Sangkuhl Katrin , Klein Teri E. , Whirl-Carrillo Michelle , Altman Russ B.
Published: June 2020

Pharmacogenetics (PGx) studies the influence of genetic variation on drug response. Clinically actionable associations inform guidelines created by the Clinical Pharmacogenetics Implementation Consortium (CPIC), but the broad impact of genetic variation on entire populations is not well-understood. We analyzed PGx allele and phenotype frequencies for 487,409 participants in the U.K. Biobank, the largest PGx study to date. For fourteen CPIC pharmacogenes known to influence human drug response, we find that 99.5% of individuals may have an atypical response to at least one drug; on average they may have an atypical response to 12 drugs. Non-European populations carry a greater frequency of variants that are predicted to be functionally deleterious; many of these are not captured by current PGx allele definitions. Strategies for detecting and interpreting rare variation will be critical for enabling broad application of pharmacogenetics.
Machine learning in predicting respiratory failure in patients with COVID-19 pneumonia - challenges, strengths, and opportunities in a global health emergency
Authors: Davide Ferrari , Jovana Milic , Roberto Tonelli , Francesco Ghinelli , Marianna Meschiari , Sara Volpi , Matteo Faltoni , Giacomo Franceschi , Vittorio Iadisernia , Dina Yaacoub , Giacomo Ciusa , Erica Bacca , Carlotta Rogati , Marco Tutone , Giulia Burastero , Alessandro Raimondi , Marianna Menozzi , Erica Franceschini , Gianluca Cuomo , Luca Corradi , Gabriella Orlando , Antonella Santoro , Margherita Di Gaetano , Cinzia Puzzolante , Federica Carli , Andrea Bedini , Riccardo Fantini , Luca Tabbì , Ivana Castaniere , Stefano Busani , Enrico Clini , Massimo Girardis , Mario Sarti , Andrea Cossarizza , Cristina Mussini , Federica Mandreoli , Paolo Missier , Giovanni Guaraldi
Published: June 2020

Aims

The aim of this study was to estimate a 48 hour prediction of moderate to severe respiratory failure, requiring mechanical ventilation, in hospitalized patients with COVID-19 pneumonia.

Methods

This was an observational study that comprised consecutive patients with COVID-19 pneumonia admitted to hospital from 21 February to 6 April 2020. The patients’ medical history, demographic, epidemiologic and clinical data were collected in an electronic patient chart. The dataset was used to train predictive models using an established machine learning framework leveraging a hybrid approach where clinical expertise is applied alongside a data-driven analysis. The study outcome was the onset of moderate to severe respiratory failure defined as PaO2/FiO2 ratio <150 mmHg in at least one of two consecutive arterial blood gas analyses in the following 48 hours. Shapley Additive exPlanations values were used to quantify the positive or negative impact of each variable included in each model on the predicted outcome.

Results

A total of 198 patients contributed to generate 1068 usable observations which allowed to build 3 predictive models based respectively on 31-variables signs and symptoms, 39-variables laboratory biomarkers and 91-variables as a composition of the two. A fourth “boosted mixed model” included 20 variables was selected from the model 3, achieved the best predictive performance (AUC=0.84) without worsening the FN rate. Its clinical performance was applied in a narrative case report as an example.

Conclusion

This study developed a machine model with 84% prediction accuracy, which is able to assist clinicians in decision making process and contribute to develop new analytics to improve care at high technology readiness levels.
Risk factors for mortality in pregnant women with SARS-CoV-2 infection
Authors: Martinez-Portilla Raigam J. , Sotiriadis Alexandros , Torres-Torres Johnatan , Christos Chatzakis , Hawkins-Villarreal Ameth , Villafan-Bernal Jose R. , Gurrola-Ochoa Rodolfo A. , Figueras Francesc
Published: June 2020

Since the first case of pneumonia was described, SARS-CoV-2 infection (coronavirus disease [COVID]-19) rapidly spread worldwide With 94,288 infections and more than 10,000 deaths, Mexico is the third Latin-American country in number of confirmed cases and second in mortality1. A major risk factor for adverse outcome in COVID-19 infection is the presence of advance age, co-morbidities including diabetes, hypertension and obesity among other non-communicable diseases2. Epidemiological data from high-prevalence countries reveal that compared to men, women are less likely to die or to require hospital admission to intensive care. This may suggest that pregnant women are not more susceptible to infection or to experience serious complications. However, whether the presence of co-morbidities or advanced maternal age confers a higher risk of adverse outcome in pregnant women with COVID-19 is unknown3.

In this research letter, we aimed at evaluating the risk factor associated with maternal mortality secondary to COVID-19 infection in a middle-income country.

Advanced maternal age is linked to an increased risk of mortality, while diabetes is the most important risk factor for maternal death. This is partly explained by an increasing incidence of non-communicable diseases in women of advanced age which is a common feature in most countries4. In the last decades, low- and middle-income countries have experienced accelerated socio-cultural changes associated with its incorporation into the international economic community, which have increased the number of obese and diabetic population, including pregnant women5. This has caused an increased risk for complications and fatality among COVID-19 positive population2,3. Thus, policies for reducing obesity and diabetes in low- and middle-income countries are most needed to reduce the mortality of COVID-19 in pregnant women.
Detection of SARS-CoV-2 in Exhaled Breath from COVID-19 Patients Ready for Hospital Discharge
Authors: Zhou Lian , Yao Maosheng , Zhang Xiang , Hu Bicheng , Li Xinyue , Chen Haoxuan , Zhang Lu , Liu Yun , Du Meng , Sun Bochao , Jiang Yunyu , Zhou Kai , Hong Jie , Yu Na , Ding Zhen , Xu Yan , Hu Min , Morawska Lidia , Grinshpun Sergey A. , Biswas Pratim , Flagan Richard C. , Zhu Baoli , Liu Wenqing , Zhang Yuanhang
Published: June 2020

The COVID-19 pandemic has brought an unprecedented crisis to the global health sector1. When recovering COVID-19 patients are discharged in accordance with throat or nasal swab protocols using reverse transcription polymerase chain reaction (RT-PCR), the potential risk of re-introducing the infection source to humans and the environment must be resolved 2,3,4. Here we show that 20% of COVID-19 patients, who were ready for a hospital discharge based on current guidelines, had SARS-CoV-2 in their exhaled breath (~105 RNA copies/m3). They were estimated to emit about 1400 RNA copies into the air per minute. Although fewer surface swabs (1.3%, N=318) tested positive, medical equipment frequently contacted by healthcare workers and the work shift floor were contaminated by SARS-CoV-2 in four hospitals in Wuhan. All air samples (N=44) appeared negative likely due to the dilution or inactivation through natural ventilation (1.6-3.3 m/s) and applied disinfection. Despite the low risk of cross environmental contamination in the studied hospitals, there is a critical need for strengthening the hospital discharge standards in preventing re-emergence of COVID-19 spread.
Lung Bronchial Epithelial Cells are HIV Targets for Proviral Genomic Integration
Authors: Devadoss Dinesh , Singh Shashi P. , Acharya Arpan , Do Kieu Chinh , Periyasamy Palsamy , Manevski Marko , Mishra Neerad , Tellez Carmen , Ramakrishnan Sundaram , Belinsky Steve , Byrareddy Siddappa , Buch Shilpa , Chand Hitendra S. , Sopori Mohan
Published: June 2020

In the era of highly active anti-retroviral therapy (HAART), obstructive lung diseases (OLDs) are common among the people living with HIV (PLWH); however, the mechanism by which HIV induces OLDs is unclear. Although human bronchial epithelial cells (HBECs) express HIV coreceptors and are critical in regulating lung immune responses, their role in transmitting HIV remains unclear. Herein, we present evidence that HIV-1 infects normal HBECs and the viral DNA is integrated in the genome to establish the viral latency. To prove that HIV productively infects HBECs, we demonstrate: (a) along with CXCR4, HBECs express the HIV-receptor CD4, and are induced to express CCR5 by IL-13 treatment; (b) following infection with HIV, HBECs produce HIV-p24 and contain the latent HIV provirus, which is activated by endotoxin and/or vorinostat; (c) DNA from HIV-1 infected HBECs contains the HIV-specificgagandnefgenes, along withAlusequences, confirming the integration of HIV in the host DNA; (d) the lung epithelial cells of HIV-infected subjects and SHIV-infected cynomolgus macaques are positive for HIV-specific transcripts. Thus, these studies suggest that HIV establishes latency in lung epithelial cells, making them potential HIV reservoirs. The long-living lung epithelial cells, activated by commonly encountered lung infections, might represent an ideal HIV target/reservoir, contributing to OLDs and other HIV-associated lung comorbidities.
Short chain fatty acids enhance expression and activity of the umami taste receptor in enteroendocrine cells via a Gαi/opathway
Authors: Shackley Matilda , Tate Edward W. , Brown Alastair J.H. , Frost Gary , Hanyaloglu Aylin C.
Published: June 2020

The short chain fatty acids (SCFAs) acetate, butyrate and propionate, are produced by the fermentation of non-digestible carbohydrates by the gut microbiota. SCFAs are of interest because they regulate appetite, adiposity, metabolism, glycemic control and immunity. SCFAs act at two distinct G protein-coupled receptors (GPCRs), FFAR2 and FFAR3. These are expressed in intestinal enteroendocrine cells (EECs), where they mediate SCFA-driven anorectic gut hormone release. EECs also express other GPCRs that act as nutrient sensors, in a manner that is plastic and adaptable to the environment. SCFAs may elicit some of their health-promoting effects by altering levels of GPCRs in EECs, thus, enhancing gut sensitivity to dietary molecules. Here, we identified that exposure of the murine EEC STC-1 cell-line to a concentration of SCFAs found in the colon, specifically enhances mRNA levels of the umami taste receptors TASR1 and TASR3, without altering levels of the SCFA GPCRs, FFAR2 and FFAR3. Interestingly, treatment of EECs with propionate or butyrate, but not acetate, increased levels of umami receptor transcripts. This phenomenon was reversed by inhibiting Gαi/osignaling with pertussis toxin, suggesting that SCFAs act through FFAR2/3 to alter gene expression. Surprisingly, neither a FFAR3-nor a FFAR2-selective synthetic ligand could increase TASR1/TASR3 mRNA levels. We assessed the functional impact of increases in TASR1/TASR3 expression using unique pharmacological properties of the umami taste receptor; namely, the potentiation of signaling by inosine monophosphate. We found that the umami taste receptor induced inosine-1-phosphate and calcium signaling in response to L-alanine and L-monosodium glutamate, and that butyrate pretreatment significantly enhanced such signaling. Our study reveals that SCFAs may contribute to EEC adaptation and alter EEC sensitivity to bioactive nutrients.
The knowledge and practice towards COVID-19 pandemic prevention among residents of Ethiopia: An Online Cross-Sectional Study
Authors: Bekele Daniel , Tolossa Tadesse , Tsegaye Reta , Teshome Wondesen
Published: June 2020

Background

The Novel coronavirus disease-2019 (COVID-19) is now the international concerns and a pandemic, since the World Health Organization declared as the outbreaks. The objective of this study to assess the prevention knowledge and practices towards the COVID-19 among the residents of Ethiopia.

Methods

An online cross-sectional study was conducted among the sample of Ethiopian residents via social platforms of the author’s network with the popular media such as Facebook, in Ethiopia from the April 15-22, 2020 and successfully recruited 341 responses. The snowball sampling was employed to recruit the participants. The data were analyzed using STATA version 14. Descriptive statistics were used to summarize the level of knowledge and practices.

Results

The majority of the respondents (80.35%) were male. The overall prevention knowledge of the participants towards the novel coronavirus (COVID-19) was high. About 91.2% of the participant was heard about the novel coronavirus disease and Social Medias’ were the main source of the information. About 90% of the participants had a good prevention knowledge of maintaining social distance and frequent hand washing. The practices of the participants towards the COVID-19 prevention were very low. Out of 341 participants, only 61% and 84% of the participants were practicing social distance and frequent hand washing, respectively.

Conclusions

Majority of the participants had knew the ways of protecting themselves from the novel coronavirus. But, there was deficiencies of changing these prevention knowledge to practice. This indicates that there was gap between knowledge and implementation of prevention strategies in the community. The concerned body should focus on providing education for the community regarding the implementation of the prevention knowledge to practice.
Biological Network Growth in Complex Environments: a Computational Framework
Authors: Paul Torsten Johann , Kollmannsberger Philip
Published: June 2020

Spatial biological networks are abundant on all scales of life, from single cells to ecosystems, and perform various important functions including signal transmission and nutrient transport. These biological functions depend on the architecture of the network, which emerges as the result of a dynamic, feedback-driven developmental process. While cell behavior during growth can be genetically encoded, the resulting network structure depends on spatial constraints and tissue architecture. Since network growth is often difficult to observe experimentally, computer simulations can help to understand how local cell behavior determines the resulting network architecture. We present here a computational framework based on directional statistics to model network formation in space and time under arbitrary spatial constraints. Growth is described as a biased correlated random walk where direction and branching depend on the local environmental conditions and constraints, which are presented as 3D multilayer grid. To demonstrate the application of our tool, we perform growth simulations of a dense network between cells and compare the results to experimental data from osteocyte networks in bone. Our generic framework might help to better understand how network patterns depend on spatial constraints, or to identify the biological cause of deviations from healthy network function.

Author summary

We present a novel modeling approach and computational implementation to better understand the development of spatial biological networks under the influence of external signals. Our tool allows us to study the relationship between local biological growth parameters and the emerging macroscopic network function using simulations. This computational approach can generate plausible network graphs that take local feedback into account and provide a basis for comparative studies using graph-based methods.
SARS-CoV-2 infects and induces cytotoxic effects in human cardiomyocytes
Authors: Bojkova Denisa , Wagner Julian , Shumliakivska Mariana , Aslan Galip , Saleem Umber , Hansen Arne , Luxan Guillermo , Guenther Stefan , Pham Minh Duc , Krishnan Jaya , Harter Patrick , Ermel Utz , Frangakis Achilleas S , Zeiher Andreas , Milting Hendrik , Cinatl Jindrich , Dendorfer Andreas , Eschenhagen Thomas , Ciesek Sandra , Dimmeler Stefanie
Published: June 2020

Background: The coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has emerged as global pandemic. SARS-CoV-2 infection can lead to elevated markers of cardiac injury associated with higher risk of mortality in COVID-19 patients. It is unclear whether cardiac injury may have been caused by direct infection of cardiomyocytes or is mainly secondary to lung injury and inflammation. Here we investigate whether human cardiomyocytes are permissive for SARS-CoV-2 infection.
Methods: Infection was induced by two strains of SARS-CoV-2 (FFM1 and FFM2) in human induced pluripotent stem cells-derived cardiomyocytes (hiPS-CM) and in two models of human cardiac tissue.
Results: We show that SARS-CoV-2 infects hiPS-CM as demonstrated by detection of intracellular double strand viral RNA and viral spike glycoprotein protein expression. Increasing concentrations of virus RNA are detected in supernatants of infected cardiomyocytes, which induced infections in CaCo-2 cell lines documenting productive infections. SARS-COV-2 infection induced cytotoxic and pro-apoptotic effects and abolished cardiomyocyte beating. RNA sequencing confirmed a transcriptional response to viral infection as demonstrated by the up-regulation of genes associated with pathways related to viral response and interferon signaling, apoptosis and reactive oxygen stress. SARS-CoV-2 infection and cardiotoxicity was confirmed in a iPS-derived human 3D cardiosphere tissue models. Importantly, viral spike protein and viral particles were detected in living human heart slices after infection with SARS-CoV-2.
Conclusions: The demonstration that cardiomyocytes are permissive for SARS-CoV-2 infection in vitro warrants the further in depth monitoring of cardiotoxic effects in COVID-19 patients.
Reproducible functional connectivity endophenotype confers high risk of ASD diagnosis in a subset of individuals
Authors: Urchs Sebastian GW. , Nguyen Hien Duy , Moreau Clara , Dansereau Christian , Tam Angela , Evans Alan C. , Bellec Pierre
Published: June 2020

Functional connectivity (FC) analyses of individuals with autism spectrum disorder (ASD) have established robust alterations of brain connectivity at the group level. Yet, the translation of these imaging findings into robust markers of individual risk is hampered by the extensive heterogeneity among ASD individuals. Here, we report an FC endophenotype that confers a greater than 7-fold risk increase of ASD diagnosis, yet is still identified in an estimated 1 in 200 individuals in the general population. By focusing on a subset of individuals with ASD and highly predictive FC alterations, we achieved a greater than 3-fold increase in risk over previous predictive models. The identified FC risk endophenotype was characterized by underconnectivity of transmodal brain networks and generalized to independent data. Our results demonstrate the ability of a highly targeted prediction model to meaningfully decompose part of the heterogeneity of the autism spectrum. The identified FC signature may help better delineate the multitude of etiological pathways and behavioural symptoms that challenge our understanding of the autism spectrum.
Dynamics of RNA polymerase II and elongation factor Spt4/5 recruitment during activator-dependent transcription
Authors: Rosen Grace A. , Baek Inwha , Friedman Larry J. , Joo Yoo Jin , Buratowski Stephen , Gelles Jeff
Published: June 2020

In eukaryotes, RNA polymerase II (RNApII) transcribes messenger RNA from template DNA. Decades of experiments have identified the proteins needed for transcription activation, initiation complex assembly, and productive elongation. However, the dynamics of recruitment of these proteins to transcription complexes, and of the transitions between these steps, are poorly understood. We used multi-wavelength single-molecule fluorescence microscopy to directly image and quantitate these dynamics in a budding yeast nuclear extract that reconstitutes activator-dependent transcription in vitro. A strong activator (Gal4-VP16) greatly stimulated reversible binding of individual RNApII molecules to template DNA, with no detectable involvement of RNApII-containing condensates. Binding of labeled elongation factor Spt4/5 to DNA typically followed RNApII binding, was NTP-dependent, and was correlated with association of mRNA-binding protein Hek2, demonstrating specificity of Spt4/5 binding to elongation complexes. Quantitative kinetic modeling shows that only a fraction of RNApII binding events are productive and implies a rate-limiting step, probably associated with recruitment of general transcription factors, needed to assemble a transcription-competent pre-initiation complex at the promoter. Spt4/5 association with transcription complexes was slowly reversible, with DNA-bound RNApII molecules sometimes binding and releasing Spt4/5 multiple times. The average Spt4/5 residence time was of similar magnitude to the time required to transcribe an average length yeast gene. These dynamics suggest that a single Spt4/5 molecule remains associated during a typical transcription event, yet can dissociate from RNApII to allow disassembly of abnormally long-lived (i.e., stalled) elongation complexes.

Significance Statement

The synthesis of a eukaryotic messenger RNA molecule involves the association of RNA polymerase and dozens of accessory proteins on DNA. We used differently colored fluorescent dyes to tag DNA, RNA polymerase II, and the elongation factor Spt4/5 in yeast nuclear extract, and then observed the assembly and dynamics of individual molecules of the proteins with single DNA molecules by microscopy. The observations quantitatively define an overall pathway by which transcription complexes form and evolve in response to an activator protein. They suggest how molecular complex dynamics may be tuned to optimize efficient RNA production.
Optimizing model comparison for enzymatic mechanism analysis
Authors: Walsh Ryan , Blain Philippe
Published: June 2020

Characterization of enzyme inhibition in drug development is usually limited to a basic analysis with the classical inhibition models or simply the use of IC50 values. However, a better understanding of enzyme physiology and regulation is seen as key to unraveling and treating the processes associated with stubborn disease targets like Alzheimer’s disease. Recently it has been shown that enzyme regulation, through substrate, inhibitor or activator interactions can be modeled using the summation of binding curves. Here we examine the use of the modular equation permutations, that can be produced through binding curve summation, to fit and evaluate the interactions of abietic acid with protein tyrosine phosphatase nonreceptor type 11. This new sort of analysis will allow for improved insight into the physiological role enzymes play and the consequence their modulation may have in disease progression.
Modeling the Covid-19 Epidemic Using Time Series Econometrics
Authors: Goliński Adam , Spencer Peter
Published: June 2020

The classic ‘logistic’ model has provided a realistic model of the behavior of Covid-19 in China and many East Asian countries. Once these countries passed the peak, the daily case count fell back, mirroring its initial climb in a symmetric way, just as the classic model predicts. However, in Italy and Spain, and now the UK and many other Western countries, the experience has been very different. The daily count has fallen back gradually from the peak but remained stubbornly high. The reason for the divergence from the classical model remain unclear. We take an empirical stance on this issue and develop a model that is based upon the statistical characteristics of the time series. With the possible exception of China, the workhorse logistic model is decisively rejected against more flexible alternatives.
Greater risk of severe COVID-19 in non-White ethnicities is not explained by cardiometabolic, socioeconomic, or behavioural factors, or by 25(OH)-vitamin D status: study of 1,326 cases from the UK Biobank
Authors: Raisi-Estabragh Zahra , McCracken Celeste , Bethell Mae S. , Cooper Jackie , Cooper Cyrus , Caulfield Mark J. , Munroe Patricia B. , Harvey Nicholas C. , Petersen Steffen E.
Published: June 2020

Background

We examined whether the greater severity of coronavirus disease 2019 (COVID-19) amongst men and non-White ethnicities is explained by cardiometabolic, socio-economic, or behavioural factors.

Methods

We studied 4,510 UK Biobank participants tested for COVID-19 (positive, n = 1,326). Multivariate logistic regression models including age, sex, and ethnicity were used to test whether addition of: 1)cardiometabolic factors (diabetes, hypertension, high cholesterol, prior myocardial infarction, smoking, BMI); 2)25(OH)-vitamin D; 3)poor diet; 4)Townsend deprivation score; 5)housing (home type, overcrowding); or 6)behavioural factors (sociability, risk taking) attenuated sex/ethnicity associations with COVID-19 status.

Results

There was over-representation of men and non-White ethnicities in the COVID-19 positive group. Non-Whites had, on average, poorer cardiometabolic profile, lower 25(OH)-vitamin D, greater material deprivation, and were more likely to live in larger households and flats/apartments. Male sex, non-White ethnicity, higher BMI, Townsend deprivation score, and household overcrowding were independently associated with significantly greater odds of COVID-19. The pattern of association was consistent for men and women; cardiometabolic, socio-demographic and behavioural factors did not attenuate sex/ethnicity associations.

Conclusions

Sex and ethnicity differential pattern of COVID-19 is not adequately explained by variations in cardiometabolic factors, 25(OH)-vitamin D levels, or socio-economic factors. Investigation of alternative biological pathways and different genetic susceptibilities is warranted.
Effects of adiposity on the human plasma proteome: Observational and Mendelian randomization estimates
Authors: Goudswaard Lucy J. , Bell Joshua A. , Hughes David A. , Corbin Laura J. , Walter Klaudia , Smith George Davey , Soranzo Nicole , Danesh John , Di Angelantonio Emanuele , Ouwehand Willem H. , Watkins Nicholas A. , Roberts David J. , Butterworth Adam S. , Hers Ingeborg , Timpson Nicholas J.
Published: June 2020

Variation in adiposity is associated with cardiometabolic disease outcomes, but the mechanisms leading from this exposure to disease are unclear. This study aimed to estimate effects of adiposity, proxied by body mass index (BMI), on 3,622 unique plasma proteins measured by the SomaLogic platform in 2,737 healthy participants from the INTERVAL study of UK blood donors. We conducted both observational and Mendelian randomization analyses where we used a genetic risk score for BMI as an instrument to estimate effects of BMI on protein levels. Our results suggest that BMI has a broad impact on the human plasma proteome, with estimated effects of BMI appearing strongest on proteins including circulating leptin, sex hormone-binding globulin and fatty acid-binding protein-4. We also provide evidence that proteins most altered by BMI are enriched for genes involved in cardiovascular disease. Altogether, these results help to focus attention onto new potential proteomic signatures of obesity-related disease.
Willingness to Accept Tradeoffs among Covid-19 Cases, Social-Distancing Restrictions, and Economic Impact: A Nationwide US Study
Authors: Reed Shelby , Gonzalez Juan Marcos , Johnson F. Reed
Published: June 2020

We designed a discrete-choice experiment to quantify the extent to which US adults would accept greater risk of infection with SARS-CoV-2 in return for lifting social-distancing restrictions and diminishing the economic impact of the COVID-19 pandemic. 5953 adults representing all 50 states had 4 distinctly different preference patterns. About 37% were risk minimizers reluctant to accept any increases in risk of contracting the virus. Another group (26%) was primarily concerned about time required for economic recovery, accepting increases in COVID-19 risk levels up to 16% to shorten recovery from 3 to 2 years. The remaining two groups diverged on the relative importance of reopening nonessential businesses. The larger group (26%) strongly preferred delaying reopening while the smaller group (13%) would accept COVID-19 risks well beyond 20% to avoid a delay in reopening. Political affiliation, race, household income and employment status were predictive of group membership.
Diagnosis of Metabolic Syndrome using Machine Learning, Statistical and Risk Quantification Techniques: A Systematic Literature Review
Authors: Kakudi Habeebah Adamu , Loo Chu Kiong , Moy Foong Ming
Published: June 2020

Metabolic syndrome (MetS), known to substantially lower the quality of life is associated with the increased incidence of non-communicable diseases (NCDs) such as type II diabetes mellitus, cardiovascular diseases and cancer. Evidence suggests that MetS accounts for the highest global mortality rate. For the early and accurate diagnosis of MetS, various statistical and ML techniques have been developed to support its clinical diagnosis. We performed a systematic review to investigate the various statistical and machine learning techniques (ML) that have been used to support the clinical diagnoses of MetS from the earliest studies to January 2020. Published literature relating to statistical and ML techniques for the diagnosis of MetS were identified by searching five major scientific databases: PubMed, Science Direct, IEEE Xplore, ACM digital library, and SpringerLink. Fifty-three primary studies that met the inclusion criteria were obtained after screening titles, abstracts and full text. Three main types of techniques were identified: statistical (n = 10), ML (n = 40), and risk quantification (n = 3). Standardized Z-score is the only statistical technique identified while the ML techniques include principal component analysis, confirmatory factory analysis, artificial neural networks, multiple logistics regression, decision trees, support vector machines, random forests, and Bayesian networks. The areal similarity degree risk quantification, framingham risk score and simScore were the three risk quantification techniques identified. Evidence suggests that evaluated ML techniques, with accuracy ranging from 75.5% to 98.9%, can more accurately diagnose MetS than both statistical and risk quantification techniques. The standardised Z-score is the most frequent statistical technique identified. However, highlighted proof based on performance measures indicate that the decision tree and artificial neural network ML techniques have the highest predictive performance for the prediction of MetS. Evidence suggests that more accurate diagnosis of MetS is required to evaluate the predictive performance of the statistical and ML techniques.
Etiologies and sequelae of extreme thrombocytosis in a large pediatric hospital
Authors: Thom Christopher S , Echevarria Emily , Osborne Ashley D , Carr Leah , Rubey Kathryn , Salazar Elizabeth , Callaway Danielle , Pawlowski Thomas , Devine Matt , Kleinman Stacey , Flibotte John , Lambert Michele P
Published: June 2020

Extreme thrombocytosis (ET, platelet count >1000 × 103/ul) is an uncommon clinical finding 1. Primary ET is associated with myeloproliferative disorders, such as essential thrombocythemia 2. Secondary ET is more common and occurs in reaction to infection, inflammation, or iron deficiency. Bleeding and thrombotic complications more frequently arise in primary ET cases 1, but have been reported with secondary ET in adults 3. Etiologies and complications associated with ET in children are less well-defined, as prior pediatric studies have been relatively small or restricted to specialized patient populations 4,5. We aimed to characterize ET in a large, single-center pediatric cohort.
Predictors to use mobile apps for monitoring COVID-19 symptoms and contact tracing: A survey among Dutch citizens
Authors: Jansen– Kosterink Stephanie , Hurmuz Marian , den Ouden Marjolein , van Velsen Lex
Published: June 2020

Introduction

eHealth applications have been recognized as a valuable tool to reduce COVID-19’s effective reproduction number. In this paper, we report on an online survey among Dutch citizens with the goal to identify antecedents of acceptance of a mobile application for COVID-19 symptom recognition and monitoring, and a mobile application for contact tracing.

Methods

Next to the demographics, the online survey contained questions focussing on perceived health, fear of COVID-19 and intention to use. We used snowball sampling via posts on social media and personal connections. To identify antecedents of acceptance of the two mobile applications we conducted multiple linear regression analyses.

Results

In total, 238 Dutch adults completed the survey. Almost 60% of the responders were female and the average age was 45.6 years (SD±17.4). For the symptom app, the final model included the predictors age, attitude towards technology and fear of COVID-19. The model had an R2 of 0.141. The final model for the tracing app included the same predictors and had an R2 of 0.156. The main reason to use both mobile applications was to control the spread of the COVID-19 virus. Concerns about privacy was mentioned as the main reason not to use the mobile applications.

Discussion

Age, attitude towards technology and fear of COVID-19 are important predictors of the acceptance of COVID-19 mobile applications for symptom recognition and monitoring and for contact tracing. These predictors should be taken into account during the development and implementation of these mobile applications to secure acceptance.
Monocyte class switch and hyperinflammation characterise severe COVID-19 in type 2 diabetes
Authors: Alzaid Fawaz , Julla Jean-Baptiste , Diedisheim Marc , Potier Charline , Potier Louis , Velho Gilberto , Gaborit Bénédicte , Manivet Philippe , Germain Stéphane , Vidal-Trecan Tiphaine , Roussel Ronan , Riveline Jean-Pierre , Dalmas Elise , Venteclef Nicolas , Gautier Jean-François
Published: June 2020

Background

Early in the COVID-19 pandemic type 2 diabetes (T2D) was marked as a risk factor of severe disease and mortality. Inflammation is central to the aetiology of both conditions where variations in immune responses have the potential to mitigate or aggravate disease course. Identifying at risk groups based on immuno-inflammatory signatures is valuable in directing personalised care and developing potential targets for precision therapy.

Methods

This study characterised immunophenotypic variation associated with COVID-19 severity in type 2 diabetes. Broad-spectrum immunophenotyping quantified 15 leukocyte populations in peripheral circulation from a cohort of 45 hospitalised COVID-19 patients with and without type 2 diabetes.

Results

Morphological anomalies in the monocyte pool, monocytopenia specific to quiescent monocytes, and a decreased frequency of cytotoxic lymphocytes were associated with severe COVID-19 in patients with type 2 diabetes requiring intensive care. An aggravated inflammatory gene expression profile, reminiscent of the type-1 interferon pathway, underlaid the immunophenotype associated with severe disease in T2D.

Conclusion

Shifts in T-cell and monocyte dynamics underpin a maladaptive response to SARSCoV-2. These alterations may impact type-1 interferon signalling which is the likely source of the hyperinflammation that increases voracity of COVID-19. These findings allow the identification of type 2 diabetic patients at risk of severe disease as well as providing evidence that the type-1 interferon pathway may be an actionable therapeutic target for future studies.

Trial registration

NCT02671864

Funding

French National Agency of Research (ANR); European Foundation for the study of diabetes (EFSD); European Research Council (ERC); Francophone Society for Diabetes (SFD)

Brief summary

Maladapted monocyte responses including class switch, morphological anomalies and systemic hyperinflammation put patients with type 2 diabetes at higher risk of severe COVID-19

GRAPHICAL ABSTRACT
Crystal structure of (1,4-diphenyl-4H-1,2,4-triazol-3-yl)phenylamine difluorophosphate, and a survey of the difluorophosphate anion (PO2F2
−)
Authors: Weil Matthias , Fürst Markus
Published: June 2020

Nitron is the trivial name of (1,4-diphenyl-4H-1,2,4-triazol-3-yl)phenylamine (C20H16N4), a triazole derivative used as an analytical reagent for gravimetric analysis of the nitrate anion. The crystal structure of the difluorophosphate salt of Nitron, 3-anilino-1,4-diphenyl-1H-1,2,4-triazol-4-ium difluorophosphate, C20H17N4
+·PO2F2
−, is reported here. Within the protonated Nitron molecule, the triazole ring, one of the phenyl rings and the NHPh moiety are virtually co-planar, with the third phenyl ring inclined to the least-squares plane of the other three rings by 56.07 (3)°. Intermolecular N—H...O and C—H...O hydrogen bonds between cations and difluorophosphate anions lead to the formation of a three-dimensional network that is consolidated by additional π–π stacking interactions between the triazole ring and one of the phenyl rings. Database surveys on inorganic, metal–organic and organic structures comprising the tetrahedral PO2F2 group reveal mean bond lengths of P—O = 1.459 (27) Å, P—F = 1.530 (21) Å, and angles of O—P—O = 121.2 (2.9)°, O—P—F = 108.7 (6)°, and F—P—F = 98.5 (2.6)°, using a dataset of 67 independent PO2F2
− anions or PO2F2 entities.
Determinants of household income of micro-finance women participants: a quantile regression approach
Authors: Duasa Jarita , Zainal Nur Hidayah
Published: June 2020

Purpose

The purpose of this study is to adopt quantile regression to investigate the impact of several factors on per capita income of participants of micro-financing scheme (Amanah Ikhtiar Malaysia [AIM]), who are mostly women at different point on the income distributions.

Design/methodology/approach

This study uses data collected from a survey on respondents who are the participants of AIM program using convenience sampling in Perak and Kelantan.

Findings

The empirical results show that the value of asset, value of loan, household size, ratio of spending to income and dummy state are consistently giving similar impacts on per capita income of participants at different quantiles.

Originality/value

However, age negatively and significantly affects per capita income only at middle and lower quantiles but not at higher quantile of per capita income.