bluuebunny/crossref_metadata_2025_split huggingface dataset:
Similar costs and outcomes for differentiated service delivery models for HIV treatment in Uganda
Authors: Guthrie Teresa , Muheki Charlotte , Rosen Sydney , Kanoowe Shiba , Lagony Stephen , Greener Ross , Miot Jacqueline , Balidawa Hudson , Kiggundu Josen , Calnan Jacqueline , Dejene Seyoum , Xulu Thembi , Sigwebela Ntombi , Long Lawrence C 
Published: June 2021

AbstractBackgroundThis study aimed to measure the total annual cost per patient and total cost per patient virally suppressed (defined as <1000 copies/ml) on antiretroviral therapy in Uganda in five differentiated service delivery models (DSDMs), including facility- and community-based models and the standard of care.MethodsA cost/outcome study was undertaken from the perspective of the service provider, using retrospective patient record review of a cohort of patients over a two-year period, with bottom-up collection of patients’ resource utilization data, top-down collection of above-delivery level and delivery-level providers’ fixed operational costs, and local unit costs.ResultsForty-seven DSDMs located at facilities or community-based points in four regions of Uganda were included in the study, with 653 adults on ART (>18 years old) enrolled in a DSDM. The study found that retention in care was 98% for the sample as a whole [96-100%], and viral suppression, 91% [86%-93%]. The mean cost to the provider (Ministry of Health or NGO implementers) was $152 per annum per patient treated, ranging from $141 to $166. Differences among the models’ costs were largely due to patients’ ARV regimens and proportions of patients on second line regimens. Service delivery costs, excluding ARVs, other medicines and laboratory tests, were modest, ranging from $9.66-16.43 per patient.ConclusionWe conclude that differentiated ART service delivery in Uganda achieved excellent treatment outcomes at a cost similar to the standard of care. While large budgetary savings might not be immediately realized, the reallocation of “saved” staff time could improve health system efficiency as facilities and patients gain more experience with DSD models.
Assay-related Differences in SuPAR Levels: Implications for Measurement and Data Interpretation
Authors: Hayek Salim S. , Raffield Laura M. , Gao Yan , Engstrom Gunnar , Quyyumi Arshed A. , Reiner Alexander P. , Reiser Jochen 
Published: June 2021

ABSTRACTWith the growing interest in studying the role of soluble urokinase plasminogen activator receptor (suPAR) in kidney and other diseases, levels are now being measured in major cohorts across the world through various methods, including immunoassays and through proteomics. Reported suPAR values have however varied dramatically depending on which assay is used. Comparing suPAR assays and their ability to discriminate risk is crucial for the Nephrology and overall research community to guide assay choice and inform interpretation of findings. To that end we measured suPAR in 3 different major cohorts (Malmo Diet and Cancer Study, n=4637; Jackson Heart Study, n=1905; and the Emory Cardiovascular Biobank, n=487) using two different methods in each cohort, encompassing the most commonly used approaches (immunoassays and proteomics). We find dramatic differences between assays; with notably poor correlations between immunoassays and proteomic approaches (r=0.2-0.5). Proteomics-based suPAR measures very poor discriminatory ability for cardiovascular and incident kidney disease. Amongst the immunoassays, the suPARnostic assay reported the highest values and had the strongest discriminatory ability.
Reduced neutralisation of the Delta (B.1.617.2) SARS-CoV-2 variant of concern following vaccination
Authors: Davis Chris , Logan Nicola , Tyson Grace , Orton Richard , Harvey William , Haughney John , Perkins Jon ,   The COVID-19 Genomics UK (COG-UK) Consortium, Peacock Thomas P. , Barclay Wendy S. , Cherepanov Peter , Palmarini Massimo , Murcia Pablo R. , Patel Arvind H. , Robertson David L. , Thomson Emma C. , Willett Brian J. 
Published: June 2021

AbstractVaccines are proving to be highly effective in controlling hospitalisation and deaths associated with SARS-CoV-2 infection but the emergence of viral variants with novel antigenic profiles threatens to diminish their efficacy. Assessment of the ability of sera from vaccine recipients to neutralise SARS-CoV-2 variants will inform the success of strategies for minimising COVID19 cases and the design of effective antigenic formulations. Here, we examine the sensitivity of variants of concern (VOCs) representative of the B.1.617.1 and B.1.617.2 (first associated with infections in India) and B.1.351 (first associated with infection in South Africa) lineages of SARS-CoV-2 to neutralisation by sera from individuals vaccinated with the BNT162b2 (Pfizer/BioNTech) and ChAdOx1 (Oxford/AstraZeneca) vaccines. Across all vaccinated individuals, the spike glycoproteins from B.1.617.1 and B.1.617.2 conferred reductions in neutralisation of 4.31 and 5.11-fold respectively. The reduction seen with the B.1.617.2 lineage approached that conferred by the glycoprotein from B.1.351 (South African) variant (6.29-fold reduction) that is known to be associated with reduced vaccine efficacy. Neutralising antibody titres elicited by vaccination with two doses of BNT162b2 were significantly higher than those elicited by vaccination with two doses of ChAdOx1. Fold decreases in the magnitude of neutralisation titre following two doses of BNT162b2, conferred reductions in titre of 7.77, 11.30 and 9.56-fold respectively to B.1.617.1, B.1.617.2 and B.1.351 pseudoviruses, the reduction in neutralisation of the delta variant B.1.617.2 surpassing that of B.1.351. Fold changes in those vaccinated with two doses of ChAdOx1 were 0.69, 4.01 and 1.48 respectively. The accumulation of mutations in these VOCs, and others, demonstrate the quantifiable risk of antigenic drift and subsequent reduction in vaccine efficacy. Accordingly, booster vaccines based on updated variants are likely to be required over time to prevent productive infection. This study also suggests that two dose regimes of vaccine are required for maximal BNT162b2 and ChAdOx1-induced immunity.
A Cross-Sectional Survey of the Knowledge, Attitudes & Practices of Antimicrobial Users and Providers in an Area of High-Density Livestock-Human Population in Western Kenya
Authors: Kemp Steven A. , Pinchbeck Gina L. , Fèvre Eric M. , Williams Nicola J. 
Published: June 2021

AbstractBackgroundAntimicrobial resistance (AMR) is one of the most important global health crises in recent times and is driven primarily by antimicrobial consumption. In East Africa, there is a paucity of data regarding the knowledge, attitudes and practices related to antimicrobial use (AMU). We investigate the ways in which antimicrobial users in the veterinary sector accessed veterinary antimicrobials, and common behaviours of veterinary antimicrobial users and prescribers associated with AMU and AMR.MethodsIn total, 70 farmers, staff at 49 agricultural-veterinary antimicrobial shops (agrovet staff) and 28 veterinary animal healthcare workers or veterinary surgeons (veterinary professionals) were interviewed in Busia county, western Kenya in 2016 using a standard questionnaire as a framework for structured interviews. Data recorded included participant demographics, level of education, access to and sources of veterinary antimicrobials, prescribing patterns and knowledge of AMR and antimicrobial withdrawal periods.ResultsThe majority of antimicrobials were accessed through informal means, purchased from agroveterinary shops; more than half of staff did not hold nationally mandated qualifications to advise on or sell veterinary antimicrobials. Approximately 40% of veterinary antimicrobials were sold without a prescription and it was noted that both price and customer preference were important factors when selling antimicrobials in almost all agrovet shops. Knowledge of the dangers associated with AMR and AMU were mostly superficial. Treatment failure occurred often, and there was a lack of differentiation between AMR and simply treatment failure.ConclusionIn this study area in East Africa with high-density human and livestock populations, AMU was primarily for maintenance of livestock health. These findings have highlighted several aspects surrounding inappropriate access to antimicrobials, and as such require attention from policy makers concerned with AMR in both livestock and human medicine sectors. Improving prescribing practices and ensuring a minimum level of general education and awareness of prescribers, as well as expanding the role of agrovet staff in antimicrobial stewardship programmes, may help begin to mitigate the maintenance and transmission of AMR, particularly amongst livestock.
Disease Triangle Dynamics of Coccidioidomycosis in Northern Arizona
Authors: Mead Heather L. , Kollath Dan , de Melo Teixeira Marcus , Roe Chandler C. , Keim Paul K. , Plude Carmel , Terriquez Joel , Nandurkar Nivedita , Donohoo Chelsea , O’Connor Brettania L.W. , Barker Bridget M. 
Published: June 2021

AbstractCoccidioides species are the etiological agent of Valley fever (Vf). Disease ranges from pneumonia to extrapulmonary infection. If diagnosis is delayed or missed, the risk of severe disease increases. We investigate the disease triangle (intersection of pathogen, host, and environment) of Vf in Northern Arizona, where the risk of acquiring the disease is lower but prevalent and rising. We inspect reported and hospitalized cases of VF hosts. Then assess pathogen origin by comparing Northern Arizona clinical isolates to isolates from other regions. Lastly, we survey Northern Arizona soils for evidence of Coccidioides. We found that cases of Vf are increasing some requiring hospitalization. The Northern Arizona Coccidioidies isolates were genetically related to Southern Arizona populations. However, we detected Coccidioides DNA in Northern Arizona soils. We expect that cases will continue to increase and suggest increased awareness and screening for the disease is crucial to limit severe illness in Northern Arizona.Article Summary LineOur work is the first description of the Valley fever disease triangle in Northern Arizona, which considers the complex interaction between host, pathogen and environment in the region. Our data suggests that the prevalence of diagnosed cases is rising in the region, some of which are extreme enough to necessitate hospitalization. We present the first evidence of Coccidioides spp. in Northern Arizona soils, suggesting that the pathogen is maintained in the local environment. Until disease prevention is an achievable option via vaccination, we anticipate that incidence of Valley fever will rise in the area. Therefore, enhanced disease awareness and screening for the coccidioidomycosis is vital to the communities of Northern Arizona.
Utility of family history in disease prediction in the era of polygenic scores
Authors: Wolford Brooke N. , Surakka Ida , Graham Sarah E. , Nielsen Jonas B. , Zhou Wei , Gabrielsen Maiken Elvestad , Skogholt Anne Heidi , Brumpton Ben M. , Douville Nicholas , Hornsby Whitney E. , Fritsche Lars G. , Boehnke Michael , Lee Seunggeun , Kang Hyun M. , Hveem Kristian , Willer Cristen J. 
Published: June 2021

AbstractClinicians have historically used family history and other risk prediction algorithms to guide patient care and preventive treatment such as statin therapeutics for coronary artery disease. As polygenic scores move towards clinical use, we have begun to consider the interplay of these scores with other predictors for optimal second generation risk prediction. Here, we assess the use of family history and polygenic scores as independent predictors of coronary artery disease and type 2 diabetes. We highlight considerations for use of family history as a predictor of these two diseases after evaluating their effectiveness in the Trøndelag Health Study and the UK Biobank. From these, we advocate for collection of high resolution family history variables in biobanks for future prediction models.
Cerebello-cerebral Functional Connectivity Networks in Major Depressive Disorder: A CAN-BIND-1 Study Report
Authors: Anteraper Sheeba Arnold , Guell Xavier , Lee Yoon Ji , Raya Jovicarole , Demchenko Ilya , Churchill Nathan W. , Frey Benicio N. , Hassel Stefanie , Lam Raymond W. , MacQueen Glenda M. , Milev Roumen , Schweizer Tom A. , Strother Stephen C. , Whitfield-Gabrieli Susan , Kennedy Sidney H. , Bhat Venkat ,   the CAN-BIND Investigator Team
Published: June 2021

AbstractObjectiveNeuroimaging studies have demonstrated aberrant structure and function of the “cognitive-affective cerebellum” in Major Depressive Disorder (MDD), although the specific role of the cerebello-cerebral circuitry in this population remains largely uninvestigated. The objective of this study was to delineate the role of cerebellar functional networks in depression.MethodsA total of 308 unmedicated participants completed resting-state functional magnetic resonance imaging scans, of which 247 (148 MDD; 99 Healthy Controls, HC) were suitable for this study. Seed-based resting-state functional connectivity (RsFc) analysis was performed using three cerebellar regions of interest (ROIs): ROI1 corresponded to default mode network (DMN) / inattentive processing; ROI2 corresponded to attentional networks including frontoparietal, dorsal attention, and ventral attention; ROI3 corresponded to motor processing. These ROIs were delineated based on prior functional gradient analyses of the cerebellum. A general linear model was used to perform within-group and between-group comparisons.ResultsIn comparison to HC, participants with MDD displayed increased RsFc within the cerebello-cerebral DMN (ROI1) and significantly elevated RsFc between the cerebellar ROI1 and bilateral angular gyrus at a voxel threshold (p < 0.001, two-tailed) and at a cluster level (p < 0.05, FDR-corrected). Group differences were non-significant for ROI2 and ROI3.ConclusionsThese results contribute to the development of a systems neuroscience approach to the diagnosis and treatment of MDD. Specifically, our findings confirm previously reported associations between MDD, DMN, and cerebellum, and highlight the promising role of these functional and anatomical locations for the development of novel imaging-based biomarkers and targets for neuromodulation therapies.
Differentiating amyloid beta spread in autosomal dominant and sporadic Alzheimer’s disease
Authors: Levitis Elizabeth , Vogel Jacob W. , Funck Thomas , Halchinski Vladimir , Gauthier Serge , Voglein Jonathan , Levin Johannes , Benzinger Tammie , Iturria-Medina Yasser , Evans Alan C. ,   for the Dominantly Inherited Alzheimer Network,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: June 2021

AbstractAmyloid-beta (Aβ) deposition is one of the hallmark pathologies in both sporadic Alzheimer’s disease (sAD) and autosomal dominant Alzheimer’s disease (ADAD), the latter of which is caused by mutations in genes involved in Aβ processing. Despite Aβ deposition being a centerpiece to both sAD and ADAD, some differences between these AD subtypes have been observed with respect to the spatial pattern of Aβ. Previous work has shown that the spatial pattern of Aβ in individuals spanning the sAD spectrum can be reproduced with high accuracy using an epidemic spreading model (ESM), which simulates the diffusion of Aβ across neuronal connections and is constrained by individual rates of Aβ production and clearance. However, it has not been investigated whether Aβ deposition in the rarer ADAD can be modeled in the same way, and if so, how congruent the spreading patterns of Aβ across sAD and ADAD are. We leverage the ESM as a data-driven approach to probe individual-level variation in the spreading patterns of Aβ across three different large-scale imaging datasets (2 SAD, 1 ADAD). We applied the ESM separately to the Alzheimer’s Disease Neuroimaging initiative (N=737), the Open Access Series of Imaging Studies (N=510), and the Dominantly Inherited Alzheimer’s Network (N=249), the latter two of which were processed using an identical pipeline. We assessed inter- and intra-individual model performance in each dataset separately, and further identified the most likely epicenter of Aβ spread for each individual. Using epicenters defined in previous work in sAD, the ESM provided moderate prediction of the regional pattern of Aβ deposition across all three datasets. We further find that, while the most likely epicenter for most Aβ-positive subjects overlaps with the default mode network, 13% of ADAD individuals were best characterized by a striatal origin of Aβ spread. These subjects were also distinguished by being younger than ADAD subjects with a DMN Aβ origin, despite having a similar estimated age of symptom onset. Together, our results suggest that most ADAD patients express Aβ spreading patters similar to those of sAD, but that there may be a subset of ADAD patients with a separate, striatal phenotype.
Metabolic resilience is encoded in genome plasticity
Authors: Agudelo Leandro Z. , Tuyeras Remy , Llinares Claudia , Morcuende Alvaro , Park Yongjin , Sun Na , Linna-Kuosmanen Suvi , Atabaki-Pasdar Naeimeh , Ho Li-Lun , Galani Kyriakitsa , Franks Paul W. , Kutlu Burak , Grove Kevin , Femenia Teresa , Kellis Manolis 
Published: June 2021

AbstractMetabolism plays a central role in evolution, as resource conservation is a selective pressure for fitness and survival. Resource-driven adaptations offer a good model to study evolutionary innovation more broadly. It remains unknown how resource-driven optimization of genome function integrates chromatin architecture with transcriptional phase transitions. Here we show that tuning of genome architecture and heterotypic transcriptional condensates mediate resilience to nutrient limitation. Network genomic integration of phenotypic, structural, and functional relationships reveals that fat tissue promotes organismal adaptations through metabolic acceleration chromatin domains and heterotypic PGC1A condensates. We find evolutionary adaptations in several dimensions; low conservation of amino acid residues within protein disorder regions, nonrandom chromatin location of metabolic acceleration domains, condensate-chromatin stability through cis-regulatory anchoring and encoding of genome plasticity in radial chromatin organization. We show that environmental tuning of these adaptations leads to fasting endurance, through efficient nuclear compartmentalization of lipid metabolic regions, and, locally, human-specific burst kinetics of lipid cycling genes. This process reduces oxidative stress, and fatty-acid mediated cellular acidification, enabling endurance of condensate chromatin conformations. Comparative genomics of genetic and diet perturbations reveal mammalian convergence of phenotype and structural relationships, along with loss of transcriptional control by diet-induced obesity. Further, we find that radial transcriptional organization is encoded in functional divergence of metabolic disease variant-hubs, heterotypic condensate composition, and protein residues sensing metabolic variation. During fuel restriction, these features license the formation of large heterotypic condensates that buffer proton excess, and shift viscoelasticity for condensate endurance. This mechanism maintains physiological pH, reduces pH-resilient inflammatory gene programs, and enables genome plasticity through transcriptionally driven cell-specific chromatin contacts. In vivo manipulation of this circuit promotes fasting-like adaptations with heterotypic nuclear compartments, metabolic and cell-specific homeostasis. In sum, we uncover here a general principle by which transcription uses environmental fluctuations for genome function, and demonstrate how resource conservation optimizes transcriptional self-organization through robust feedback integrators, highlighting obesity as an inhibitor of genome plasticity relevant for many diseases.
Where there’s smoke, there’s fuel: dynamic vegetation data improve predictions of wildfire hazard in the Great Basin
Authors: Smith Joseph T. , Allred Brady W. , Boyd Chad S. , Davies Kirk W. , Jones Matthew O. , Kleinhesselink Andrew R. , Maestas Jeremy D. , Naugle David E. 
Published: June 2021

AbstractWildfires are a growing management concern in western US rangelands, where invasive annual grasses have altered fire regimes and contributed to an increased incidence of catastrophic large wildfires. Fire activity in arid, non-forested ecosystems is thought to be largely controlled by interannual variation in fuel amount, which in turn is controlled by antecedent weather. Thus, long-range forecasting of fire activity in rangelands should be feasible given annual estimates of fuel quantity. Using a 32 yr time series of spatial data, we employed machine learning algorithms to predict the relative probability of large (>405 ha) wildfire in the Great Basin based on fine-scale annual and 16-day estimates of cover and production of vegetation functional groups, weather, and multitemporal scale drought indices. We evaluated the predictive utility of these models with a leave-one-year-out cross-validation, building spatial hindcasts of fire probability for each year that we compared against actual footprints of large wildfires. Herbaceous aboveground biomass production, bare ground cover, and long-term drought indices were the most important predictors of burning. Across 32 fire seasons, 88% of the area burned in large wildfires coincided with the upper 3 deciles of predicted fire probabilities. At the scale of the Great Basin, several metrics of fire activity were moderately to strongly correlated with average fire probability, including total area burned in large wildfires, number of large wildfires, and maximum fire size. Our findings show that recent years of exceptional fire activity in the Great Basin were predictable based on antecedent weather-driven growth of fine fuels and reveal a significant increasing trend in fire probability over the last three decades driven by widespread changes in fine fuel characteristics.