bluuebunny/crossref_metadata_2025_split huggingface dataset:
How does spinal movement variability change in people with low back pain?: protocol for a systematic review
Authors: Saito Hiroki , takasaki Hiroshi , Watanabe Yoshiteru , Kutsuna Toshiki , Futohashi Toshihiro , Kubo Masayoshi , Kusumoto Yasuaki , Tiba Hiroki 
Published: April 2020

AbstractLow back pain(LBP) is the number one cause of disability worldwide. One factor which might potentially contribute to ongoing pain is impaired spinal movement variability. It is uncertain how movement variability changes during trunk movements in the presence of LBP. In this protocol, we will systematically investigate and compare both the amount and structure of spinal movement variability during repeated trunk motions between people with and without LBP. The results will be reported in line with the PRISMA(Preferred Reporting Items for Systematic Review and Meta-Analysis). Searches will be conducted on CENTRAL, PubMed, MEDLINE, EMBASE, and CINAHL databases, along with a comprehensive review of grey literature and key journals.Three pairs of two independent reviewers will screen potential studies and two independent reviewers assess the risk of bias within studies which meet the inclusion criteria. The Newcastle-Ottawa risk of bias tool will be used to assess the quality of the data.
ADNC-RS, a clinical-genetic risk score, predicts Alzheimer’s pathology in autopsy-confirmed Parkinson’s Disease and Dementia with Lewy Bodies
Authors: Dai David L , Tropea Thomas F , Robinson John L , Suh Eunran , Hurtig Howard , Weintraub Daniel , Van Deerlin Vivianna , Lee Edward B. , Trojanowski John Q , Chen-Plotkin Alice S 
Published: April 2020

ABSTRACTGrowing evidence suggests overlap between Alzheimer’s disease (AD) and Parkinson’s disease (PD) pathophysiology in a subset of patients. Indeed, 50-80% of autopsy cases with a primary clinicopathological diagnosis of Lewy body disease (LBD) – most commonly manifesting during life as PD – have concomitant amyloid-beta and tau pathology, the defining pathologies of AD. Here we evaluated common genetic variants in genome-wide association with AD as predictors of concomitant AD pathology in the brains of people with a primary clinicopathological diagnosis of PD or Dementia with Lewy Bodies (DLB), diseases both characterized by neuronal Lewy bodies. 208 consecutive autopsy-confirmed cases of PD or DLB were assessed for AD neuropathological change (ADNC), and these same cases were genotyped at 20 single nucleotide polymorphisms (SNPs) found by genome-wide association study to associate with risk for AD. In a training set of the first 127 individuals, we developed a logistic regression model predicting the presence of ADNC, using backward stepwise regression for model selection and 10-fold cross-validation to estimate performance. We then assessed model performance in a separate test set of the next 81 individuals. The best-fit model generated a risk score for ADNC (ADNC-RS) based on age at disease onset and genotype at three SNPs (APOE, BIN1, and SORL1 loci). In the training set, the area under the receiver operating curve (AUC) for this model was 0.751. In the test set, the AUC was 0.781. Individuals with ADNC-RS in the top quintile had four-fold likelihood of having AD pathology at autopsy compared with those in each of the lowest two quintiles. In patients with autopsy-confirmed PD or DLB a simple model incorporating three AD-risk SNPs and age at disease onset substantially enriches for concomitant AD pathology at autopsy, with implications for identifying LBD patients in which targeting amyloid-beta or tau is a therapeutic strategy.
A simple method to quantify country-specific effects of COVID-19 containment measures
Authors: Pedersen Morten Gram , Meneghini Matteo 
Published: April 2020

AbstractMost of the world is currently fighting to limit the impact of the COVID-19 pandemic. Italy, the Western country with most COVID-19 related deaths, was the first to implement drastic containment measures in early March, 2020. Since then most other European countries, the USA, Canada and Australia, have implemented similar restrictions, ranging from school closures, banning of recreational activities and large events, to complete lockdown. Such limitations, and softer promotion of social distancing, may be more effective in one society than in another due to cultural or political differences. It is therefore important to evaluate the effectiveness of these initiatives by analyzing country-specific COVID-19 data. We propose to model COVID-19 dynamics with a SIQR (susceptible – infectious – quarantined – recovered) model, since confirmed positive cases are isolated and do not transmit the disease. We provide an explicit formula that is easily implemented and permits us to fit official COVID-19 data in a series of Western countries. We found excellent agreement with data-driven estimation of the day-of-change in disease dynamics and the dates when official interventions were introduced. Our analysis predicts that for most countries only the more drastic restrictions have reduced virus spreading. Further, we predict that the number of unidentified COVID-19-positive individuals at the beginning of the epidemic is ∼10 times the number of confirmed cases. Our results provide important insight for future planning of non-pharmacological interventions aiming to contain spreading of COVID-19 and similar diseases.
Systematic review of distribution models for Amblyomma ticks and Rickettsial group pathogens
Authors: Lippi Catherine A. , Gaff Holly D. , White Alexis L. , Ryan Sadie J. 
Published: April 2020

AbstractThe rising prevalence of tick-borne diseases in humans in recent decades has called attention to the need for more information on geographic risk for public health planning. Species distribution models (SDMs) are an increasingly utilized method of constructing potential geographic ranges.There are many knowledge gaps in our understanding of risk of exposure to tick-borne pathogens, particularly for those in the rickettsial group. Here, we conducted a systematic review of the SDM literature for rickettsial pathogens and tick vectors in the genus Amblyomma. Of the 174 reviewed papers, only 24 studies used SDMs to estimate the potential extent of vector and/or pathogen ranges. The majority of studies (79%) estimated only tick distributions using vector presence as a proxy for pathogen exposure. Studies were conducted at different scales and across multiple continents. Few studies undertook original data collection, and SDMs were mostly built with presence-only datasets from public database or surveillance sources. While we identify agap in knowledge, this may simply reflect a lag in new data acquisition and a thorough understanding of the tick-pathogen ecology involved.
Exploring gendered patterns of interaction within an inter-professional health care network
Authors: Aguirre Nelson , Carswell Peter , Kenealy Tim 
Published: April 2020

ABSTRACTBackgroundNumerous studies have shown gender-based similarity affects interactions in organizational contexts. However, studies in the health care arena have shown contradictory findings.ObjectiveTo explore gender homophily in an inter-professional network comprising doctors and nurses across the primary and secondary care interface in diabetes care.MethodsA Social Network Analysis was conducted with primary and secondary care clinicians responsible for diabetes care in Auckland New Zealand. Three different methods were used to test gender affinity in 40 health professionals (GPs, endocrinologist and specialist nurses). First, a metric analysis of homophily ranking corrected for potential differences in gender proportions was conducted. Homophily ranking is scored between −1 (perfect heterophily) and 1 (perfect homophily). We also examined the ego-net composition and measured the density of interactions among men and women in the network.ResultsGender homophily was close to 0, indicated that network members were likely to interact with males and females without preferences, a result that was confirmed through ego-net composition.ConclusionsThis study in diabetes managed care network found little evidence to support the impact of gender homophily on communication exchange. This contrasts with other studies in the health care context. Other influences need to be explored at this context.
Appropriate intensification of diabetes-related therapy by general practitioners: cross sectional study
Authors: Aguirre Nelson , Carswell Peter , Kenealy Tim 
Published: April 2020

ABSTRACTAimTo measure intensification of therapy (the inverse of clinical inertia) by general practitioners in the management of hyperglycaemia, hypertension and dyslipidaemia in patients with diabetes.MethodsWe analysed clinical practices results for Hb1c, blood pressure, lipids and pharmacy records for prescriptions according to the guidelines. We identified whether medication was increased at each patient visit when the goals for glycosylated haemoglobin (<= 64 mmol/mol), systolic blood pressure (<=130 mmHg) and LDL cholesterol (<=3.5 mmol/L) had not been reached at the time of the visit. The study was conducted between January 2009 and December 2011 in South Auckland, New Zealand.ResultsData from 314 patients with diabetes included 2398 prescriptions. Appropriate intensification of therapy was seen in 31% of 457 visits when HbA1c was raised, 11% of 375 visits when systolic blood pressure was raised and 2% of 51 visits when LDL cholesterol was raised.ConclusionsThere are clear differences in intensification therapy in terms of the co-morbidity addressed. Clinical inertia may be one important and changeable contributor to diabetes complications. New Zealand has replaced “get Checked” programme for Diabetes Care Improvement Package, which is a primary care based programme seeking to improve outcomes for people with diabetes. This new programme is based on coordination of diabetes care, therefore a further analysis measuring clinical inertia may show improvements in quality, consistency and direction of care for people with diabetes in New Zealand.HighlightsWe measure intensification of therapy by general practitioners.Management of hyperglycaemia, hypertension and dyslipidaemia were tested.There are differences in intensification therapy in terms of each co-morbidity.Clinical inertia may be one changeable contributor to diabetes complications.
BioLaboro: A bioinformatics system for detecting molecular assay signature erosion and designing new assays in response to emerging and reemerging pathogens
Authors: Holland Mitchell , Negrón Daniel , Mitchell Shane , Dellinger Nate , Ivancich Mychal , Barrus Tyler , Thomas Sterling , Jennings Katharine W. , Goodwin Bruce , Sozhamannan Shanmuga 
Published: April 2020

AbstractBackgroundEmerging and reemerging infectious diseases such as the novel Coronavirus disease, COVID-19 and Ebola pose a significant threat to global society and test the public health community’s preparedness to rapidly respond to an outbreak with effective diagnostics and therapeutics. Recent advances in next generation sequencing technologies enable rapid generation of pathogen genome sequence data, within 24 hours of obtaining a sample in some instances. With these data, one can quickly evaluate the effectiveness of existing diagnostics and therapeutics usingin silicoapproaches. The propensity of some viruses to rapidly accumulate mutations can lead to the failure of molecular detection assays creating the need for redesigned or newly designed assays.ResultsHere we describe a bioinformatics system named BioLaboro to identify signature regions in a given pathogen genome, design PCR assays targeting those regions, and then test the PCR assaysin silicoto determine their sensitivity and specificity. We demonstrate BioLaboro with two use cases: Bombali Ebolavirus (BOMV) and the novel Coronavirus 2019 (SARS-CoV-2). For the BOMV, we analyzed 30 currently available real-time reverse transcription-PCR assays against the three available complete genome sequences of BOMV. Only two met ourin silicocriteria for successful detection and neither had perfect matches to the primer/probe sequences. We designed five new primer sets against BOMV signatures and all had true positive hits to the three BOMV genomes and no false positive hits to any other sequence. Four assays are closely clustered in the nucleoprotein gene and one is located in the glycoprotein gene. Similarly, for the SARS-CoV-2, we designed five highly specific primer sets that hit all 145 whole genomes (available as of February 28, 2020) and none of the near neighbors.ConclusionsHere we applied BioLaboro in two real-world use cases to demonstrate its capability; 1) to identify signature regions, 2) to assess the efficacy of existing PCR assays to detect pathogens as they evolve over time, and 3) to design new assays with perfectin silicodetection accuracy, all within hours, for further development and deployment. BioLaboro is designed with a user-friendly graphical user interface for biologists with limited bioinformatics experience.
Access to routinely collected health data for clinical trials – review of successful data requests to UK registries
Authors: Lensen Sarah , Macnair Archie , Love Sharon B , Yorke-Edwards Victoria , Noor Nurulamin M , Martyn Meredith , Blenkinsop Alexandra , Diaz-Montana Carlos , Powell Graham , Williamson Elizabeth , Carpenter James , Sydes Matthew R 
Published: April 2020

ABSTRACTBackgroundClinical trials generally each collect their own data despite routinely-collected health data (RCHD) increasing in quality and breadth. Our aim is to quantify UK-based randomised controlled trials (RCTs) accessing RCHD for participant data, characterise how these data are used and thereby recommend how more trials could use RCHD.MethodsWe conducted a systematic review of RCTs accessing RCHD from at least one registry in the UK between 2013-2018, for the purposes of informing or supplementing participant data. A list of all registries holding RCHD in the UK was compiled. In cases where registries published release registers, these were searched for RCTs accessing RCHD. Where no release register was available, registries were contacted to request a list of RCTs. For each identified RCT, information was collected from all publicly available sources (release registers, websites, protocol etc.). The search and data extraction was undertaken between Jan-2019 and May-2019.ResultsWe identified 160 RCTs accessing RCHD between 2013 and 2018 from a total of 22 registries; this corresponds to only a very small proportion of all UK RCTs (approximately 3%). RCTs accessing RCHD were generally large (median sample size 1590), commonly evaluating treatments for cancer or cardiovascular disease. Most of the included RCTs accessed RCHD from NHS Digital (68%), and the most frequently accessed datasets were mortality (76%) and hospital visits (55%). RCHD was used to inform the primary trial (82%) and long-term follow-up (57%). There was substantial variation in how RCTs used RCHD to inform participant outcome measures. A limitation was the lack of information and transparency from registries and RCTs with respect to which datasets have been accessed and for what purposes.ConclusionsIn the last five years, only a small minority of UK-based RCTs have accessed RCHD to inform participant data. We ask for improved accessibility, confirmed data quality and joined up thinking between the registries and the regulatory authorities.RegistrationPROSPERO CRD42019123088
Artificial intelligence applied on chest X-ray can aid in the diagnosis of COVID-19 infection: a first experience from Lombardy, Italy
Authors: Castiglioni Isabella , Ippolito Davide , Interlenghi Matteo , Monti Caterina Beatrice , Salvatore Christian , Schiaffino Simone , Polidori Annalisa , Gandola Davide , Messa Cristina , Sardanelli Francesco 
Published: April 2020

AbstractObjectivesWe tested artificial intelligence (AI) to support the diagnosis of COVID-19 using chest X-ray (CXR). Diagnostic performance was computed for a system trained on CXRs of Italian subjects from two hospitals in Lombardy, Italy.MethodsWe used for training and internal testing an ensemble of ten convolutional neural networks (CNNs) with mainly bedside CXRs of 250 COVID-19 and 250 non-COVID-19 subjects from two hospitals. We then tested such system on bedside CXRs of an independent group of 110 patients (74 COVID-19, 36 non-COVID-19) from one of the two hospitals. A retrospective reading was performed by two radiologists in the absence of any clinical information, with the aim to differentiate COVID-19 from non-COVID-19 patients. Real-time polymerase chain reaction served as reference standard.ResultsAt 10-fold cross-validation, our AI model classified COVID-19 and non COVID-19 patients with 0.78 sensitivity (95% confidence interval [CI] 0.74–0.81), 0.82 specificity (95% CI 0.78–0.85) and 0.89 area under the curve (AUC) (95% CI 0.86–0.91). For the independent dataset, AI showed 0.80 sensitivity (95% CI 0.72–0.86) (59/74), 0.81 specificity (29/36) (95% CI 0.73–0.87), and 0.81 AUC (95% CI 0.73– 0.87). Radiologists’ reading obtained 0.63 sensitivity (95% CI 0.52–0.74) and 0.78 specificity (95% CI 0.61–0.90) in one centre and 0.64 sensitivity (95% CI 0.52–0.74) and 0.86 specificity (95% CI 0.71–0.95) in the other.ConclusionsThis preliminary experience based on ten CNNs trained on a limited training dataset shows an interesting potential of AI for COVID-19 diagnosis. Such tool is in training with new CXRs to further increase its performance.Key pointsArtificial intelligence based on convolutional neural networks was preliminary applied to chest-X-rays of patients suspected to be infected by COVID-19.Convolutional neural networks trained on a limited dataset of 250 COVID-19 and 250 non-COVID-19 were tested on an independent dataset of 110 patients suspected for COVID-19 infection and provided a balanced performance with 0.80 sensitivity and 0.81 specificity.Training on larger multi-institutional datasets may allow this tool to increase its performance.
Purely data-driven exploration of COVID-19 pandemic after three months of the outbreak
Authors: Kadyrov Shirali , Saydaliev Hayot Berk 
Published: April 2020

AbstractIt has been three months since the novel coronavirus (COVID-19) pandemic outbreak. Many research studies were carried to understand its epidemiological characteristics in the early phase of the disease outbreak. The current study is yet another contribution to better understand the disease properties by parameter estimation of mathematical SIR epidemic modeling. The authors use Johns Hopkins University’s dataset to estimate the basic reproduction number of COVID-19 for representative countries (Japan, Germany, Italy, France, and Netherlands) selected using cluster analysis. As a by-product, the authors estimate transmission, recovery, and death rates for each selected country and carry statistical tests to see if there are any significant differences.
Hydroxychloroquine (HCQ): an observational cohort study in primary and secondary prevention of pneumonia in an at-risk population
Authors: Vanasse Alain , Courteau Josiane , Chiu Yohann , Cantin André , Leduc Richard 
Published: April 2020

ABSTRACTBackgroundRecent studies suggest that hydroxychloroquine (HCQ) could be effective against COVID-19. It is reasonable to expect that if HCQ can prevent or reduce the adverse effects of influenza, it may also reduce the effects of COVID-19 in humans. The objective of this study was to test whether HCQ can prevent or reduce the risk and severity of influenza.MethodsThis is an observational cohort study using medico-administrative data from Québec. Patients included had at least one emergency department (ED) visit in 2012 or 2013, with a prior diagnosis of chronic conditions, and were admissible to the public drug insurance plan. Two sub-cohorts were considered depending on reasons for ED visit: other than influenza or pneumonia (primary prevention) and influenza or pneumonia (secondary prevention).ResultsIn the primary prevention analysis (n=417,353), patients taking HCQ (n=3,659) had an increased risk of hospitalization for pneumonia in the following year compared to those who did not (5.2% vs. 2.9%; adjusted OR=1.25, p=0.0079). In the secondary prevention analysis (n=27,152), patients taking HCQ (n=392), compared to those who did not had a modest and non-significant increased risk of hospitalization for pneumonia after 30 days (25.8% vs. 22.6%; adjusted OR=1.14, p=0.3177).InterpretationBased on the assumption that HCQ has similar effects on the COVID-19 as those observed on influenza, we can infer that it will not have positive effects on COVID-19. We should therefore act cautiously before initiating prospective interventional studies on the use of HCQ to reduce adverse effects of COVID-19.
Phosphorylation of Threonine 107 by Calcium/Calmodulin dependent Kinase II δ Regulates the Detoxification Efficiency and Proteomic Integrity of Glyoxalase 1
Authors: Morgenstern Jakob , Katz Sylvia , Krebs-Haupenthal Jutta , Chen Jessy , Saadatmand Alireza , Cortizo Fabiola Garcia , Moraru Alexandra , Zemva Johanna , Campos Marta Campos , Teleman Aurelio , Backs Johannes , Nawroth Peter , Fleming Thomas 
Published: April 2020

AbstractThe glyoxalase system is a ubiquitously expressed enzyme system with narrow substrate specificity and is responsible for the detoxification of harmful methylglyoxal (MG), a spontaneous by-product of energy metabolism. Glyoxalase 1 (Glo1) is the first and therefore rate limiting enzyme of this protective system. In this study we were able to show that a phosphorylation of threonine-107 in the Glo1 protein, mediated by Ca2+/Calmodulin-dependent Kinase II delta (CamKIIδ), is associated with elevated catalytic efficiency of Glo1. In fact, Michaelis-Menten kinetics of Glo1 mutants revealed that a permanent phosphorylation of Glo1 was associated with increased Vmax(1.23 µmol/min/mg) and decreased Km(0.19 mM HTA), whereas the non-phosphorylatable Glo1 showed significantly lower Vmax(0.66 µmol/min/mg) and increased Km(0.31 mM HTA). This was also confirmed with human recombinant Glo1 (Vmax(Glo1phos) = 999 µmol/min/mg; Km(Glo1phos) = 0.09 mM HTA vs. Vmax(Glo1red) = 497 µmol/min/mg; Km(Glo1red) = 0.12 mM HTA). Additionally, proteasomal degradation of non-phosphorylated Glo1 via ubiquitination occurred more rapidly as compared to native Glo1. The absence of the responsible kinase CamKIIδ was associated with poor MG detoxification capacity and decreased protein content of Glo1 in a murine CamKIIδ knock-out model. Furthermore, this regulatory mechanism is also related to an altered Glo1 status in cancer, diabetes and during aging. In summary, phosphorylation of threonine-107 in the Glo1 protein by CamKIIδ is a quick and precise mechanism regulating Glo1 activity.
Structural basis for the inhibition of SARS-CoV-2 main protease by antineoplastic drug Carmofur
Authors: Jin Zhenming , Zhao Yao , Sun Yuan , Zhang Bing , Wang Haofeng , Wu Yan , Zhu Yan , Zhu Chen , Hu Tianyu , Du Xiaoyu , Duan Yinkai , Yu Jing , Yang Xiaobao , Yang Xiuna , Yang Kailin , Liu Xiang , Guddat Luke W. , Xiao Gengfu , Zhang Leike , Yang Haitao , Rao Zihe 
Published: April 2020

AbstractThe antineoplastic drug Carmofur was shown to inhibit SARS-CoV-2 main protease (Mpro). Here the X-ray crystal structure of Mproin complex with Carmofur reveals that the carbonyl reactive group of Carmofur is covalently bound to catalytic Cys145, whereas its fatty acid tail occupies the hydrophobic S2 subsite. Carmofur inhibits viral replication in cells (EC50= 24.30 μM) and it is a promising lead compound to develop new antiviral treatment for COVID-19.