bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mindsets Predict Physical Activity and Relate to Chosen Management Strategies in Individuals with Knee Osteoarthritis
Authors: Boswell Melissa A. , Evans Kris M. , Zion Sean R. , Boles Danielle Z. , Hicks Jennifer L. , Delp Scott L. , Crum Alia J. 
Published: April 2021

AbstractObjectivesWe compared mindsets about physical activity among those with and without knee osteoarthritis and investigated if these mindsets relate to physical activity level and symptom management.MethodsParticipants with (n=150) and without (n=152) knee osteoarthritis completed an online survey at study enrollment (T1). Participants with knee osteoarthritis repeated the survey three weeks later (T2; n=62). The mindset questionnaire, scored from 1-4, assessed the extent to which individuals associate the process of exercising with less appeal-focused qualities (e.g., boring, painful, isolating, and depriving) vs. appeal-focused (e.g., fun, pleasurable, social, and indulgent)versus. Using linear regression, we examined the relationship between mindset and having knee osteoarthritis, and, in the subgroup of participants with knee osteoarthritis, the relationship between mindset at T1 and physical activity (via the Physical Activity Scale for the Elderly) at T2. We also compared mindsets between those who use medication for management and those who use exercise.ResultsA less appeal-focused mindset regarding physical activity was marginally associated with having knee osteoarthritis (β=-0.125,P=0.096). Within the knee osteoarthritis group, a more appeal-focused mindset predicted higher future physical activity (β=20.68,P=0.039), controlling for current physical activity, demographics, and health. Individuals that used exercise with or without pain medication or injections had more appeal-focused process mindsets than those who used medication or injections without exercise (P<0.001). Further, the process mindset inventory demonstrated strong internal consistency (α=0.92 at T1 for n=150 and α=0.92 at T2 for n=62) and test-retest reliability (ICC>0.841,P<0.001) within the knee osteoarthritis population.ConclusionIn individuals with knee osteoarthritis, mindsets predict future physical activity levels and relate to an individual’s management strategy. Mindsets are a reliable and malleable construct and may be a valuable target for increasing physical activity and improving adherence to rehabilitation strategies involving exercise among individuals with knee osteoarthritis.
Exploring the causal effect of maternal pregnancy adiposity on offspring adiposity: Mendelian randomization using polygenic risk scores
Authors: Bond Tom A , Richmond Rebecca C , Karhunen Ville , Cuellar-Partida Gabriel , Borges Maria Carolina , Zuber Verena , Alves Alexessander Couto , Mason Dan , Yang Tiffany C , Gunter Marc J , Dehghan Abbas , Tzoulaki Ioanna , Sebert Sylvain , Evans David M , Lewin Alex M , O’Reilly Paul F , Lawlor Deborah A , Järvelin Marjo-Riitta 
Published: April 2021

AbstractBackgroundGreater maternal adiposity before or during pregnancy is associated with greater offspring adiposity throughout childhood, but the extent to which this is due to causal intrauterine or periconceptional mechanisms remains unclear. Here we use Mendelian Randomization (MR) with polygenic risk scores (PRS) to investigate whether associations between maternal pre-/early pregnancy body mass index (BMI) and offspring adiposity from birth to adolescence are causal.MethodsWe undertook confounder adjusted multivariable (MV) regression and MR using mother-offspring pairs from two UK cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC) and Born in Bradford (BiB). In ALSPAC and BiB the outcomes were birthweight (BW; N = 9339) and BMI at age 1 and 4 years (N = 8659 to 7575). In ALSPAC only we investigated BMI at 10 and 15 years (N = 4476 to 4112) and dual-energy X-ray absorptiometry (DXA) determined fat mass index (FMI) from age 10–18 years (N = 2659 to 3855). We compared MR results from several PRS, calculated from maternal non-transmitted alleles at between 29 and 80,939 single nucleotide polymorphisms (SNPs).ResultsMV and MR consistently showed a positive association between maternal BMI and BW, supporting a moderate causal effect. For adiposity at most older ages, although MV estimates indicated a strong positive association, MR estimates did not support a causal effect. For the PRS with few SNPs, MR estimates were statistically consistent with the null, but had wide confidence intervals so were often also statistically consistent with the MV estimates. In contrast, the largest PRS yielded MR estimates with narrower confidence intervals, providing strong evidence that the true causal effect on adolescent adiposity is smaller than the MV estimates (Pdifference = 0.001 for 15 year BMI). This suggests that the MV estimates are affected by residual confounding, therefore do not provide an accurate indication of the causal effect size.ConclusionsOur results suggest that higher maternal pre-/early-pregnancy BMI is not a key driver of higher adiposity in the next generation. Thus, they support interventions that target the whole population for reducing overweight and obesity, rather than a specific focus on women of reproductive age.
Wide application of minimally processed saliva on multiple RT-qPCR kits for SARS-CoV-2 detection in Indonesia
Authors: Mahendra Caroline , Kaisar Maria Mardalena Martini , Vasandani Suraj Rajan , Surja Sem Samuel , Tjoa Enty , Chriestya Febie , Junusmin Kathleen Irena , Widowati Tria Asri , Irwanto Astrid , Ali Soegianto 
Published: April 2021

AbstractSaliva as a sample matrix has been an attractive alternative for the detection of SARS-CoV-2. However, due to potential variability in collection and processing steps, evaluating a proposed workflow amongst the local population is recommended. Here, we aim to validate the collection and treatment of human saliva as a direct specimen for RT-qPCR-based detection of SARS-CoV-2 in Indonesia. We demonstrated that SARS-CoV-2 target genes were detected in saliva specimens and remained stable for five days refrigerated or room temperature storage. The method of processing saliva specimens described in this report bypasses the need for an RNA-extraction process, thereby reducing the cost, time, and manpower required for processing samples. The developed method was tested across nine commercial kits, including the benchmark, to demonstrate its wide applicability on multiple existing workflows. Our developed method achieved 86% overall agreement rate compared to paired nasopharyngeal and oropharyngeal swab specimens (NPOP). With the assistance of a saliva sampling device, the collection was found to be more convenient for individuals and improved the overall agreement rate to 97%.
Diversity and within-host evolution of parasites from VL and VL/HIV patients in Northern Ethiopia
Authors: Franssen Susanne U. , Takele Yegnasew , Adem Emebet , Sanders Mandy J. , Müller Ingrid , Kropf Pascale , Cotton James A. 
Published: April 2021

AbstractVisceral leishmaniasis (VL) is a fatal disease and a growing public health problem in East Africa, where Ethiopia has one of the highest VL burdens. The largest focus of VL in Ethiopia is driven by high prevalence in migrant agricultural workers and associated with a high rate of co-infection with HIV. This co-infection makes VL more difficult to treat successfully, and is associated with a high rate of relapse, with VL/HIV patients frequently experiencing many relapses of VL before succumbing to this infection. We present genome-wide data on Leishmania donovani isolates from a longitudinal study of cohorts of VL and VL/HIV patients reporting to a single clinic in Ethiopia. Extensive clinical data allows us to investigate the influence of co-infection and relapse on the populations of parasites infecting these patients. We find that the same parasite population is responsible for both VL and VL/HIV infections, and that in most cases, disease relapse is caused by recrudescence of the population of parasites that caused primary VL. Complex, multi-clonal infections are present in both primary and relapse cases, but the infrapopulation of parasites within a patient loses genetic diversity between primary disease presentation and subsequent relapses, presumably due to a population bottleneck induced by treatment. These data suggest that VL/HIV relapses are not caused by genetically distinct parasite infections, nor by re-infection. Treatment of VL does not lead to sterile cure, and in VL/HIV the infecting parasites are able to re-establish after clinically successful treatment, leading to repeated relapse of VL.ImportanceVisceral leishmaniasis (VL) is the second largest cause of deaths due to parasite infections, and a growing problem in East Africa. In Ethiopia, it is particularly associated with migrant workers moving from non-endemic regions for seasonal agricultural work, and frequently found as a co-infection with HIV, which leads to frequent VL relapse following treatment. Insight into the process of relapsing in these patients is thus key to controlling the VL epidemic in Ethiopia. We show that there is little genetic differentiation between the parasites infecting HIV positive and HIV negative VL patients. Moreover, we provide evidence that relapses are caused by the initially infecting parasite population, and that treatment induces a loss of genetic diversity in this population. We propose that restoring functioning immunity and improving anti-parasitic treatment may be key in breaking the cycle of relapsing VL in VL/HIV patients.
Unsupervised Learning for Large Scale Data: The ATHLOS Project
Authors: Barmpas Petros , Tasoulis Sotiris , Vrahatis Aristidis G. , Anagnostou Panagiotis , Georgakopoulos Spiros , Prina Matthew , Ayuso-Mateos José Luis , Bickenbach Jerome , Bayes Ivet , Bobak Martin , Caballero Francisco Félix , Chatterji Somnath , Egea-Cortés Laia , García-Esquinas Esther , Leonardi Matilde , Koskinen Seppo , Koupil Ilona , Pająk Andrzej , Prince Martin , Sanderson Warren , Scherbov Sergei , Tamosiunas Abdonas , Galas Aleksander , MariaHaro Josep , Sanchez-Niubo Albert , Plagianakos Vassilis P. , Panagiotakos Demosthenes 
Published: April 2021

1AbstractRecent technological advancements in various domains, such as the biomedical and health, offer a plethora of big data for analysis. Part of this data pool is the experimental studies that record various and several features for each instance. It creates datasets having very high dimensionality with mixed data types, with both numerical and categorical variables. On the other hand, unsupervised learning has shown to be able to assist in high-dimensional data, allowing the discovery of unknown patterns through clustering, visualization, dimensionality reduction, and in some cases, their combination. This work highlights unsupervised learning methodologies for large-scale, high-dimensional data, providing the potential of a unified framework that combines the knowledge retrieved from clustering and visualization. The main purpose is to uncover hidden patterns in a high-dimensional mixed dataset, which we achieve through our application in a complex, real-world dataset. The experimental analysis indicates the existence of notable information exposing the usefulness of the utilized methodological framework for similar high-dimensional and mixed, real-world applications.
Single Site performance of AI software for stroke detection and Triage
Authors: Paz Dan , Yagoda Daniel , Wein Theodore 
Published: April 2021

AbstractBackgroundRecently developed software utilizing artificial intelligence for fast detection and triage of stroke cases has the potential to accelerate stroke care and improve patient outcomes. We performed this analysis to evaluate the performance and time-to-notification of one such software - RAPID LVO.MethodsWe created a database of 151 consecutive acute stroke patients for whom CT scans were processed by the RAPID LVO software over a period of eight months. The LVO notification and time to notification of the software were collected, alongside patient information and the CTA findings.ResultsRAPID LVO achieved a sensitivity of 63.6% and specificity of 85.8% for large vessel occlusion, with an average time to notification of 32.53 minutes.ConclusionsRAPID LVO has low sensitivity, moderate specificity and high time-to-notification performance. Our study data demonstrated in particular low overall sensitivity (63%) for distal occlusions (M2-3). The disparity between the observed performance and the performance reported in RAPID LVO’s FDA clearance demonstrates the importance of independent, multi-center evaluation. The gap between the performance in this study compared to published records of RAPID AI may be due to differences in imaging hardware, software implementation, connectivity or clinical definitions.
Humoral response to Pfizer mRNA vaccine against SARS CoV2, in patients with autoimmune inflammatory rheumatic diseases and the impact on the rheumatic disease activity
Authors: Braun-Moscovici Yolanda , Kaplan Marielle , Markovits Doron , Giryes Samy , Toledano Kochava , Tavor Yonit , Dolnikov Katya , Balbir-Gurman Alexandra 
Published: April 2021

AbstractBackgroundThe registration trials of mRNA vaccines against SARS CoV2 did not address patients with autoimmune inflammatory rheumatoid diseases (AIRD).AimsTo assess the humoral response to mRNA vaccine against SARS CoV2, in AIRD patients treated with immunomodulating drugs and the impact on AIRD activity.MethodsConsecutive patients treated at the rheumatology institute who received their first SARS-CoV-2 (Pfizer) vaccine were recruited to the study, at their routine visit. The patients were invited for serology test 4-6 weeks after receiving the second dose of vaccine. IgG Antibodies (Ab) against SARS COV2 virus were detected using the SARS-Cov-2 IgG II Quant (Abbott) assayResultsOne hundred fifty-six consecutive patients (76% females) treated at a single rheumatology center (mean age (range) 59.1 (21-83) years), mean (range) disease duration 10.8 (1-55) years), were recruited to the study. Thirty-five percents of patients received conventional synthetic (cs)DMARDs only, 64% biological/targeted synthetic (b/ts) DMARDs, 34% received combined treatment with csDMARDs and b/tsDMARDs and 32% corticosteroids (mean dose(range) 5.8mg(2.5-20mg) prednisone). One hundred thirty-seven patients (88%) were seropositive for IgG Ab against SARS CoV2 virus (median 2832.5 AU/ml, range 58-29499). Nineteen (12%) patients had negative tests, 11/19 were treated with B cell depleting agents. The reported side effects of the vaccine were minor (muscle sore, headache, low grade fever). The rheumatic disease remained stable in all patients.ConclusionsThe vast majority of AIRD patients developed a significant humoral response following the administration of the second dose of the Pfeizer mRNA vaccine against SARS CoV2 virus. Only minor side effects were reported and no apparent impact on AIRD activity was noted.
Spatio-temporal analysis and prediction of malaria cases using remote sensing meteorological data in Diébougou health district, Burkina Faso, 2016-2017
Authors: Bationo Cédric S. , Gaudart Jean , Dieng Sokhna , Cissoko Mady , Taconet Paul , Ouedraogo Boukary , Somé Anthony , Zongo Issaka , Soma Dieudonné D. , Tougri Gauthier , Dabiré Roch K. , Koffi Alphonsine , Pennetier Cédric , Moiroux Nicolas 
Published: April 2021

AbstractBackgroundMalaria control and prevention programs are more efficient and cost-effective when they target hotspots or select the best periods of year to implement interventions. This study aimed to identify the spatial distribution of malaria hotspots at the village level in Diébougou health district, Burkina Faso, and to model the temporal dynamics of malaria cases as a function of meteorological conditions and of the distance between villages and health centers (HCs).MethodsCase data for 27 villages were collected in 13 HCs using continuous passive case detection. Meteorological data were obtained through remote sensing. Two synthetic meteorological indicators (SMIs) were created to summarize meteorological variables. Spatial hotspots were detected using the Kulldorf scanning method. A General Additive Model was used to determine the time lag between cases and SMIs and to evaluate the effect of SMIs and distance to HC on the temporal evolution of malaria cases. The multivariate model was fitted with data from the epidemic year to predict the number of cases in the following outbreak.ResultsOverall, the incidence rate in the area was 429.13 cases per 1,000 person-year with important spatial and temporal heterogeneities. Four spatial hotspots, involving 7 of the 27 villages, were detected, for an incidence rate of 854.02 cases per 1,000 person-year. The hotspot with the highest risk (relative risk = 4.06) consisted of a single village, with an incidence rate of 1,750.75 cases per 1,000 person-years. The multivariate analysis found greater variability in incidence between HCs than between villages linked to the same HC. The epidemic year was characterized by a major peak during the second part of the rainy season and a secondary peak during the dry-hot season. The time lag that generated the better predictions of cases was 9 weeks for SMI1 (positively correlated with precipitation variables and associated with the first peak of cases) and 16 weeks for SMI2 (positively correlated with temperature variables and associated with the secondary peak of cases). Euclidian distance to HC was not found to be a predictor of malaria cases recorded in HC. The prediction followed the overall pattern of the time series of reported cases and predicted the onset of the following outbreak with a precision of less than 3 weeks.ConclusionsOur spatio-temporal analysis of malaria cases in Diébougou health district, Burkina Faso, provides a powerful prospective method for identifying and predicting high-risk areas and high-transmission periods that could be targeted in future malaria control and prevention campaigns.
Quantitative SARS-CoV-2 viral-load curves in paired saliva and nasal swabs inform appropriate respiratory sampling site and analytical test sensitivity required for earliest viral detection
Authors: Savela Emily S. , Winnett Alexander , Romano Anna E. , Porter Michael K. , Shelby Natasha , Akana Reid , Ji Jenny , Cooper Matthew M. , Schlenker Noah W. , Reyes Jessica A. , Carter Alyssa M. , Barlow Jacob T. , Tognazzini Colten , Feaster Matthew , Goh Ying-Ying , Ismagilov Rustem F. 
Published: April 2021

AbstractEarly detection of SARS-CoV-2 infection is critical to reduce asymptomatic and pre-symptomatic transmission, curb the spread of variants by travelers, and maximize treatment efficacy. Low-sensitivity nasal-swab testing (antigen and some nucleic-acid-amplification tests) is commonly used for surveillance and symptomatic testing, but the ability of low-sensitivity nasal-swab tests to detect the earliest stages of infection has not been established. In this case-ascertained study, initially-SARS-CoV-2-negative household contacts of individuals diagnosed with COVID-19 prospectively self-collected paired anterior-nares nasal-swab and saliva samples twice daily for viral-load quantification by high-sensitivity RT-qPCR and digital-RT-PCR assays. We captured viral-load profiles from the incidence of infection for seven individuals and compared diagnostic sensitivities between respiratory sites. Among unvaccinated persons, high-sensitivity saliva testing detected infection up to 4.5 days before viral loads in nasal swabs reached the limit of detection of low-sensitivity nasal-swab tests. For most participants, nasal swabs reached higher peak viral loads than saliva, but were undetectable or at lower loads during the first few days of infection. High-sensitivity saliva testing was most reliable for earliest detection. Our study illustrates the value of acquiring early (within hours after a negative high-sensitivity test) viral-load profiles to guide the appropriate analytical sensitivity and respiratory site for detecting earliest infections. Such data are challenging to acquire but critical to design optimal testing strategies in the current pandemic and will be required for responding to future viral pandemics. As new variants and viruses emerge, up-to-date data on viral kinetics are necessary to adjust testing strategies for reliable early detection of infections.
Dysconnectivity of a brain functional network was associated with blood inflammatory markers in depression
Authors: Aruldass Athina R. , Kitzbichler Manfred G. , Morgan Sarah E. , Lim Sol , Lynall Mary-Ellen , Turner Lorinda , Vertes Petra ,   Wellcome Trust Consortium for Neuroimmunology of Mood Disorders and Alzheimer’s Disease (NIMA), Cavanagh Jonathan , Cowen Phil , Pariante Carmine M. , Harrison Neil A. , Bullmore Edward T. 
Published: April 2021

AbstractObjectiveThere is increasing evidence for a subgroup of major depressive disorder (MDD) associated with heightened peripheral blood inflammatory markers. In this study, the authors sought to understand the mechanistic brainimmune axis in inflammation-linked depression by investigating associations between functional connectivity (FC) of brain networks and peripheral inflammation in depression.MethodsResting-state functional magnetic resonance imaging (fMRI) and peripheral blood immune marker data (C-reactive protein; CRP, interleukin-6; IL-6 and immune cells) were collected on N=46 healthy controls (HC; CRP ≤ 3mg/L) and N=83 cases of MDD, stratified further into low CRP (loCRP MDD; ≤ 3 mg/L; N=50) and high CRP (hiCRP MDD; > 3 mg/L; N=33). In a two-part analysis, network-based statistics (NBS) was firstly performed to ascertain FC differences via HC vs hiCRP MDD comparison. Association between this network of interconnected brain regions and peripheral CRP (N=83), IL-6 (N=72), neutrophils and CD4+ T-cells (N=36) were then examined in MDD cases only.ResultsCase-control NBS testing revealed a single network of abnormally attenuated FC in hiCRP MDD, chiefly comprising default mode network (DMN) and ventral attentional network (VA) coupled regions, anatomically connecting the insula/frontal-operculum and posterior cingulate cortex (PCC). Across all MDD cases, FC within the identified network scaled negatively with CRP, IL-6, and neutrophils.ConclusionsThe findings suggest that inflammation is associated with attenuation of functional connectivity within a brain network deemed critical for interoceptive signalling, e.g. accurate communication of peripheral bodily signals such as immune states to the brain, with implications for the etiology of inflammation-linked depression.