bluuebunny/crossref_metadata_2025_split huggingface dataset:
Critically Ill Coronavirus Disease 2019 Patients Exhibit Hyperactive Cytokine Responses Associated With Effector Exhausted Senescent T Cells in Acute Infection
Authors: Arcanjo Angélica , Guimarães Pinto Kamila , Logullo Jorgete , Leite Paulo Emílio Corrêa , Menezes Camilla Cristie Barreto , Freire-de-Lima Leonardo , Diniz-Lima Israel , Decoté-Ricardo Debora , Nunes Rodrigues-da-Silva Rodrigo , Geraldo Freire-de-Lima Celio , Almeida Filardy Alessandra , Lima-Junior Josué da Costa , Luiz Bertho Alvaro , De Luca Paula Mello , Mauro Granjeiro José , Coutinho Barroso Shana Priscila , Conceição-Silva Fátima , Savino Wilson , Morrot Alexandre 
Published: August 2021

AbstractBackgroundCoronavirus disease 2019 (COVID-19) can progress to severe pneumonia with respiratory failure and is aggravated by the deregulation of the immune system causing an excessive inflammation including the cytokine storm.MethodsIn this study, we report that severe acutely infected patients have high levels of both type-1 and type-2 cytokines.ResultsOur results show abnormal cytokine levels upon T-cell stimulation, in a nonpolarized profile. Furthermore, our findings indicate that this hyperactive cytokine response is associated with a significantly increased frequency of late-differentiated T cells with particular phenotype of effector exhausted/senescent CD28−CD57+ cells. Of note, we demonstrated for the first time an increased frequency of CD3+CD4+CD28−CD57+ T cells with expression of programmed death 1, one of the hallmarks of T-cell exhaustion.ConclusionsThese findings reveal that COVID-19 is associated with acute immunodeficiency, especially within the CD4+ T-cell compartment, and points to possible mechanisms of loss of clonal repertoire and susceptibility to viral relapse and reinfection events.
Safety of intraarticular corticosteroid injection preceding hip and knee arthroplasty: a systematic review and meta-analysis amid resolving COVID-19 arthroplasty restrictions
Authors: Cheok Tim , Jennings Matthew , Aprato Alessandro , Jayasekera Narlaka , Jaarsma Ruurd L 
Published: August 2021

ABSTRACTIntraarticular corticosteroid injection (ICSI) is a widely practiced management for hip and knee osteoarthritis. Imposed delays to arthroplasty during coronavirus disease 2019 pandemic have led us to postulate that many patients have opted for recent ICSI. We compared the odds of prosthetic joint infection (PJI) in patients who were or were not administered ICSI within 12 months prior to hip or knee arthroplasty. A systematic search of PubMed, Embase, The Cochrane Library and Web of Science was performed in February 2021, with studies assessing the effect of ICS on PJI rates identified. All studies, which included patients that received ICSI in the 12 months prior to primary hip and knee arthroplasty, were included. In total 12 studies were included: four studies with 209 353 hips and eight studies with 438 440 knees. ICSI administered in the 12 months prior to hip arthroplasty increased the odds of PJI [odds ratio (OR) = 1.17, P = 0.04]. This was not the case for knees. Subgroup analysis showed significantly higher odds of PJI in both hip [OR = 1.45, P = 0.002] and knee arthroplasty [OR = 2.04; P = 0.04] when ICSI was within the preceding 3 months of surgery. A significantly higher odds of PJI were seen in patients receiving ICSI within the 12 months prior to hip arthroplasty. Subgroup analysis showed increased odds of PJI in both hip and knee arthroplasty, in patients receiving ICSI within 3 months prior to their arthroplasty. We recommend delaying knee arthroplasty for at least 3 months after ICSI and possibly longer for hip arthroplasty.Level of EvidenceLevel III - Systematic Review of Level II and III Studies.
Systemic control of nodule formation by plant nitrogen demand requires autoregulation-dependent and independent mechanisms
Authors: Pervent Marjorie , Lambert Ilana , Tauzin Marc , Karouani Alicia , Nigg Martha , Jardinaud Marie-Françoise , Severac Dany , Colella Stefano , Martin-Magniette Marie-Laure , Lepetit Marc 
Published: August 2021

Abstract
In legumes interacting with rhizobia, the formation of symbiotic organs involved in the acquisition of atmospheric nitrogen gas (N2) is dependent on the plant nitrogen (N) demand. We used Medicago truncatula plants cultivated in split-root systems to discriminate between responses to local and systemic N signaling. We evidenced a strong control of nodule formation by systemic N signaling but obtained no clear evidence of a local control by mineral nitrogen. Systemic signaling of the plant N demand controls numerous transcripts involved in root transcriptome reprogramming associated with early rhizobia interaction and nodule formation. SUPER NUMERIC NODULES (SUNN) has an important role in this control, but we found that major systemic N signaling responses remained active in the sunn mutant. Genes involved in the activation of nitrogen fixation are regulated by systemic N signaling in the mutant, explaining why its hypernodulation phenotype is not associated with higher nitrogen fixation of the whole plant. We show that the control of transcriptome reprogramming of nodule formation by systemic N signaling requires other pathway(s) that parallel the SUNN/CLE (CLAVATA3/EMBRYO SURROUNDING REGION-LIKE PEPTIDES) pathway.
Pivoting during a pandemic: lessons learned from transitioning a multisite randomized controlled trial to a remote protocol in response to COVID-19
Authors: Inverso Hailey , Abadula Fayo , Morrow Troy , LeStourgeon Lauren , Parmar Angelee , Streisand Randi , Jaser Sarah S 
Published: August 2021

Abstract
THR1VE! is an ongoing multisite randomized clinical trial of a positive psychology intervention designed to treat diabetes distress and improve glycemic outcomes in teens with type 1 diabetes. Due to the COVID-19 pandemic restrictions on clinical research and changes in diabetes clinical care, THR1VE! was adapted from an in-person enrollment protocol to a remote protocol through a series of development and testing strategies. We discuss the process of transitioning the protocol and the demonstrated feasibility of ongoing recruitment, enrollment, and retention outcomes. These findings offer support for a remotely transitioned protocol that has larger applications for ongoing and future clinical research.
Nanopore Metagenomic Sequencing for Detection and Characterization of SARS-CoV-2 in Clinical Samples
Authors: Gauthier Nick P.G. , Nelson Cassidy , Bonsall Michael B. , Locher Kerstin , Charles Marthe , MacDonald Clayton , Krajden Mel , Chorlton Samuel D. , Manges Amee R. 
Published: August 2021

AbstractThe COVID-19 pandemic has underscored the need for rapid novel diagnostic strategies to detect and characterize pathogens from clinical specimens. The MinION sequencing device allows for rapid, cost-effective, high-throughput sequencing; useful features for translation to clinical laboratory settings. Metagenomic Next-Generation Sequencing (mNGS) approaches provide the opportunity to examine the entire genomic material of a sample; allowing for detection of emerging and clinically relevant pathogens that may be missed in targeted assays. Here we present a pilot study on the performance of Sequence-Independent Single Primer Amplification (SISPA) to amplify RNA randomly for the detection and characterization of SARS-CoV-2. We designed a classifier that corrects for barcode crosstalk between specimens. Our assay yielded 100% specificity overall and 95.2% sensitivity for specimens with a RT-qPCR cycle threshold value less than 30. We assembled 10 complete (>95% coverage at 20x depth), and one near-complete (>80% coverage at 20x depth) genomes from 20 specimens that were classified as positive by mNGS. We characterized these genomes through phylogenetic analysis and found that 10/11 specimens from British Columbia had a closest relative to another British Columbian specimen. Of five samples that we had both assembled genomes, as well as Variant of Concern (VOC) PCR results, we found 100% concordance between these results. Additionally, our assay was able to distinguish between the Alpha and Gamma variants, which was not possible with our VOC PCR technique. This study supports future work examining the broader feasibility of SISPA as a diagnostic strategy for the detection and characterization of viral pathogens.
DICOM Imaging Router: An Open Deep Learning Framework for Classification of Body Parts from DICOM X-ray Scans
Authors: Pham Hieu H. , Do Dung V. , Nguyen Ha Q. 
Published: August 2021

AbstractX-ray imaging in Digital Imaging and Communications in Medicine (DICOM) format is the most commonly used imaging modality in clinical practice, resulting in vast, non-normalized databases. This leads to an obstacle in deploying artificial intelligence (AI) solutions for analyzing medical images, which often requires identifying the right body part before feeding the image into a specified AI model. This challenge raises the need for an automated and efficient approach to classifying body parts from X-ray scans. Unfortunately, to the best of our knowledge, there is no open tool or framework for this task to date. To fill this lack, we introduce a DICOM Imaging Router that deploys deep convolutional neural networks (CNNs) for categorizing unknown DICOM X-ray images into five anatomical groups: abdominal, adult chest, pediatric chest, spine, and others. To this end, a large-scale X-ray dataset consisting of 16,093 images has been collected and manually classified. We then trained a set of state-of-the-art deep CNNs using a training set of 11,263 images. These networks were then evaluated on an independent test set of 2,419 images and showed superior performance in classifying the body parts. Specifically, our best performing model (i.e., MobileNet-V1) achieved a recall of 0.982 (95% CI, 0.977– 0.988), a precision of 0.985 (95% CI, 0.975–0.989) and a F1-score of 0.981 (95% CI, 0.976–0.987), whilst requiring less computation for inference (0.0295 second per image). Our external validity on 1,000 X-ray images shows the robustness of the proposed approach across hospitals. These remarkable performances indicate that deep CNNs can accurately and effectively differentiate human body parts from X-ray scans, thereby providing potential benefits for a wide range of applications in clinical settings. The dataset, codes, and trained deep learning models from this study will be made publicly available on our project website at https://vindr.ai/datasets/bodypartxr.
Applying the FAIR principles to data in a hospital: challenges and opportunities in a pandemic
Authors: Queralt-Rosinach Núria , Kaliyaperumal Rajaram , Bernabé César H. , Long Qinqin , Joosten Simone A. , van der Wijk Henk Jan , Flikkenschild Erik L.A. , Burger Kees , Jacobsen Annika , Mons Barend , Roos Marco ,   BEAT-COVID Group,   COVID-19 LUMC Group
Published: August 2021

AbstractBackgroundThe COVID-19 pandemic has challenged healthcare systems and research worldwide. Data is collected all over the world and needs to be integrated and made available to other researchers quickly. However, the various heterogeneous information systems that are used in hospitals can result in fragmentation of health data over multiple data ‘silos’ that are not interoperable for analysis. Consequently, clinical observations in hospitalised patients are not prepared to be reused efficiently and timely. There is a need to adapt the research data management in hospitals to make COVID-19 observational patient data machine actionable, i.e. more Findable, Accessible, Interoperable and Reusable (FAIR) for humans and machines. We therefore applied the FAIR principles in the hospital to make patient data more FAIR.ResultsIn this paper, we present our FAIR approach to transform COVID-19 observational patient data collected in the hospital into machine actionable digital objects to answer medical doctors’ research questions. With this objective, we conducted a coordinated FAIRification among stakeholders based on ontological models for data and metadata, and a FAIR based architecture that complements the existing data management. We applied FAIR Data Points for metadata exposure, turning investigational parameters into a FAIR dataset. We demonstrated that this dataset is machine actionable by means of three different computational activities: federated query of patient data along open existing knowledge sources across the world through the Semantic Web, implementing Web APIs for data query interoperability, and building applications on top of these FAIR patient data for FAIR data analytics in the hospital.ConclusionsOur work demonstrates that a FAIR research data management plan based on ontological models for data and metadata, open Science, Semantic Web technologies, and FAIR Data Points is providing data infrastructure in the hospital for machine actionable FAIR digital objects. This FAIR data is prepared to be reused for federated analysis, linkable to other FAIR data such as Linked Open Data, and reusable to develop software applications on top of them for hypothesis generation and knowledge discovery.
Preimmunization correlates of protection shared across malaria vaccine trials in adults
Authors: Neal Maxwell L. , Duffy Fergal J. , Du Ying , Aitchison John D. , Stuart Kenneth D. 
Published: August 2021

AbstractIdentifying preimmunization biological characteristics that promote an effective vaccine response offers opportunities for illuminating the critical immunological mechanisms that confer vaccine-induced protection, for developing adjuvant strategies, and for tailoring vaccination regimens to individuals or groups. In the context of malaria vaccine research, studying preimmunization correlates of protection can help address the need for a widely-effective malaria vaccine, which remains elusive. In this study, common preimmunization correlates of protection were identified using transcriptomic data from four independent, heterogeneous malaria vaccine trials in adults. Systems-based analyses showed that a moderately elevated inflammatory state prior to immunization was associated with protection against malaria challenge. Functional profiling of protection-associated genes revealed the importance of several inflammatory pathways, including TLR signaling. These findings, which echo previous studies that associated enhanced preimmunization inflammation with protection, illuminate common baseline characteristics that set the stage for an effective vaccine response across diverse malaria vaccine strategies in adults.
Spatio-temporal spread of COVID-19: Comparison of the inhomogeneous SEPIR model and data from South Carolina
Authors: Tsori Yoav , Granek Rony 
Published: August 2021

AbstractDuring the COVID-19 pandemic authorities have been striving to obtain reliable predictions for the spreading dynamics of the disease. We recently developed a multi-”sub-populations” (multi-compartments: susceptible, exposed, pre-symptomatic, infectious, recovered) model, that accounts for the spatial in-homogeneous spreading of the infection and shown, for a variety of examples, how the epidemic curves are highly sensitive to location of epicenters, non-uniform population density, and local restrictions. In the present work we test our model against real-life data from South Carolina during the period May 22 to July 22 (2020). During this period, minimal restrictions have been employed, which allowed us to assume that the local basic reproduction number is constant in time. We account for the non-uniform population density in South Carolina using data from NASA, and predict the evolution of infection heat-maps during the studied period. Comparing the predicted heat-maps with those observed, we find high qualitative resemblance. Moreover, the Pearson’s correlation coefficient is relatively high thus validating our model against real-world data. We conclude that the model accounts for the major effects controlling spatial in-homogeneous spreading of the disease. Inclusion of additional sub-populations (compartments), in the spirit of several recently developed models for COVID-19, can be easily performed within our mathematical framework.
Diagnostic evaluation of the presence of residues of glyphosate-AMPA and 2.4D pesticides in urine samples from people living in a rural Brazilian community
Authors: Candiotto Luciano Z. P. , Ferreira Mariane Okamoto , Ferreira Isadora Nunes , Teixeira Géssica Tuani , da Silva Janaína Carla , Tedesco Emanueli Hammes , Gaboardi Shaiane Carla , Panis Carolina 
Published: August 2021

ABSTRACTPesticide contamination in rural communities is a known problem worldwide. In this study, we investigated the levels of pesticide residues in urine samples from residents of a rural community located in the municipality of Francisco Beltrão-Paraná, Brazil. According to the residents’ report obtained through a structured interview, the main form of exposure has been due to the drift of pesticides resulting from the spraying carried out on crops neighboring the community, with one crop existing on the left edge and another on the right edge of the site. The investigation was based on a demand from residents concerned about the frequent occurrence of symptoms after spraying on neighboring crops, such as nausea, headaches, and dizziness. Thus, samples were collected immediately after the occurrence of spraying in the crop surrounding the site. In the collected samples (n=35, 1 sample per family) laboratory analyzes were performed to identify possible pesticide residues. To identify possible contaminating pesticides in the samples, multi-residue analysis was performed by gas chromatography coupled with mass spectrometry (GC-MS/MS). To identify 2.4D residues, an active widely used in the region and not detectable by the technique used for other pesticides, the analyzes were performed using the enzyme immunoassay technique. The results indicate that all urine samples collected showed the presence of 2.4D residues and that 90% of them presented the presence of glyphosate-AMPA residues, without the detection of the other investigated residues. The analysis of data obtained from interviews with residents shows an association between living in the place for longer and having cases of abortion (p<0.05, R=0.43) or feeling unwell after the application of the poison by the neighboring crop (p<0.05, R=0.47). In addition, residents who reported being poisoned with poison also reported having cancer (p<0.05, R=0.42). Assuming that it is unacceptable that urine samples have pesticide residues, it is concluded that the residents of this community are widely contaminated by pesticides potentially coming from the spraying of the neighboring crop, especially by pesticides that have the active ingredients in their formulas. 2,4D and glyphosate-AMPA and that may be impacting the health of these people in the long term.
Federal Vaccine Policy and Interstate Variation in COVID-19 Vaccine Coverage in India
Authors: Mukherjee Kanchan 
Published: August 2021

AbstractIntroductionOn August 13, 2021, India completed 30 weeks of vaccination against COVID-19 for its eligible citizens. While the vaccination has made progress, there has been no study analyzing the federal/union vaccine policy and its effect on vaccination coverage across Indian states. In this context, this study analyses the federal vaccination policy and its effect on interstate variation in vaccine coverage and the correlation of state economy with vaccination coverage.MethodsThe study analyses vaccine policy documents, secondary data on vaccination coverage and state gross domestic product (GDP) available in public domain. ANOVA test has been used to assess the effect of vaccine policy on interstate vaccine coverage and correlation-regression analysis has been conducted to assess the type and strength of association between gross state domestic product and vaccination coverage.ResultsInterstate variation in vaccination coverage in the first 15 weeks was the least (F=3.5), when vaccine procurement and supply was entirely provided by the union/federal government and vaccination was limited to priority groups. However, with the extension of vaccine policy to other groups and reduction in federal government involvement in vaccine procurement, the interstate variation in vaccination coverage increased significantly (F=10.74) by the end of 30 weeks. The highest interstate variation was observed in the period between 23-30 weeks (F=25.31). State GDP was positively and strongly correlated with state vaccination coverage with a high coefficient of correlation (R=0.94) and high coefficient of determination (R2= 0.88).ConclusionsThe study finds that federal procurement and supply of vaccination among prioritized groups has been the best strategy till date to address the inequity in vaccination coverage across the states of India.
The IHME vs Me: Modeling USA CoVID-19 Spread, Early Data to the Fifth Wave
Authors: Eng Genghmun 
Published: August 2021

AbstractEpidemiologists have never had such high-quality real-time pandemic data. Modeling CoVID-19 pandemic data became a predictive tool in-stead of an afterwards analysis. How early CoVID-19 model predictions impacted US Government policies and practices is first reviewed here as an important part of the pandemic history. It spurred independent modeling efforts, such as this, to help develop a better understanding of CoVID-19 spread, and to provide a substitute for the IHME (Institute for Health Metrics & Evaluation, U. Washington) 4-month predictions for the expected pandemic evolution, which they had to revise every couple of weeks. Our alternative model, which was developed over the course of several earlier medrxiv.org preprints, is shown here to provide a good description for the entire USA CoVID-19 pandemic to date, covering: (1) the original CoVID-19 wave [3/21/20-6/07/20], (2) the Summer 2020 Resurgence [6/07/20-9/25/20], (3) the large Winter 2020 Resurgence [9/25/20-3/19/21], (4) a small Spring 2021 “Fourth Wave”, [3/19/21-6/07/21], and (5) the present-day Summer 2021 “Fifth Wave” [6/07/21-present], which the USA is now in the midst of. Our analysis of the initial “Fifth Wave” data shows that this wave presently has the capacity to infect virtually all susceptible non-vaccinated persons who practice NO Mask-Wearing and minimal Social Distancing.