bluuebunny/crossref_metadata_2025_split huggingface dataset:
Examining Unit Costs for COVID-19 Case Management in Kenya
Authors: Barasa Edwine , Kairu Angela , Nganga Wangari , Maritim Marybeth , Were Vincent , Akech Samuel , Mwangangi Mercy 
Published: October 2020

AbstractIntroductionCase management for COVID-19 patients is one of key interventions in country responses to the pandemic. Countries need information on the costs of case management to inform resource mobilization, planning and budgeting, purchasing arrangements, and assessments of the cost-effectiveness of interventions. We estimated unit costs for COVID-19 case management for patients with asymptomatic, mild to moderate, severe, and critical COVID-19 disease in Kenya.MethodsWe estimated per patient per day unit costs of COVID-19 case management for patients that are asymptomatic and those that have mild to moderate, severe, and critical symptoms. For asymptomatic and mild to moderate patients, we estimated unit costs for home-based care and institutional (hospitals and isolation centers). We used an ingredients approach, adopted a health system perspective and patient episode of care as our time horizon. We obtained data on inputs and their quantities from COVID-19 case management guidelines, home based care guidelines, and human resource guidelines, and augmented this with data provided by three public covid-19 treatment hospitals in Kenya. We obtained input prices for services from a recent costing survey of 20 hospitals in Kenya and for pharmaceuticals, non-pharmaceuticals, devices and equipment from market price databases for Kenya.ResultsPer day per patient unit cost for asymptomatic patients and patients with mild to moderate COVID-19 disease under home based care are KES 1,993.01 (USD 18.89) and 1995.17 (USD 18.991) respectively. When these patients are managed in an isolation center of hospital, the same unit costs for asymptomatic patients and patients with mild to moderate disease are 7,415.28 (USD 70.29) and 7,417.44 (USD 70.31) respectively. Per day unit costs for patients with severe COVID-19 disease managed in general hospital wards and those with critical COVID-19 disease admitted in intensive care units are 12,570.75 (USD 119.16) and 59,369.42 (USD 562.79).ConclusionCOVID-19 case management costs are substantial. Unit costs for asymptomatic and mild to moderate COVID-19 patients in home-based care is 4-fold lower compared institutional care of the same patients. Kenya will not only need to mobilize substantial resources to finance COVID-19 case management but also explore additional service delivery adaptations that will reduce unit costs.
Functional connectivity directionality between large-scale resting-state networks in children and adolescence from the Healthy Brain Network sample
Authors: Lund Martina J. , Alnæs Dag , Rokicki Jaroslav , Schwab Simon , Andreassen Ole A. , Westlye Lars T. , Kaufmann Tobias 
Published: October 2020

AbstractMental disorders often emerge during adolescence and have been associated with age-related differences in connection strengths of brain networks (static functional connectivity), manifesting in non-typical trajectories of brain development. However, little is known about the direction of information flow (directed functional connectivity) in this period of functional brain progression. We employed dynamic graphical models (DGM) to estimate directed functional connectivity from resting state functional magnetic resonance imaging data on 1143 participants, aged 6 to 17 years from the healthy brain network (HBN) sample. We tested for effects of age, sex, cognitive abilities and psychopathology on estimates of direction flow. Across participants, we show a pattern of reciprocal information flow between visual-medial and visual-lateral connections, in line with findings in adults. Investigating directed connectivity patterns between networks, we observed a positive association for age and direction flow from the cerebellar to the auditory network, and for the auditory to the sensorimotor network. Further, higher cognitive abilities were linked to lower information flow from the visual occipital to the default mode network. Additionally, examining the degree networks overall send and receive information to each other, we identified age-related effects implicating the right frontoparietal and sensorimotor network. However, we did not find any associations with psychopathology. Our results revealed that the directed functional connectivity of large-scale brain networks is sensitive to age and cognition during adolescence, warranting further studies that may explore trajectories of development in more fine-grained network parcellations and in different populations.
Characterization of presumptive vancomycin-resistant enterococci recovered during infection control surveillance in Dallas, Texas
Authors: Ping Sara , Mayorga-Reyes Nancy , Price Valerie J. , Onuoha Michelle , Bhardwaj Pooja , Rodrigues Marinelle , Owen Jordan , Araya Dennise Palacios , Akins Ronda L. , Palmer Kelli L. 
Published: October 2020

AbstractEnterococcus faecalis and E. faecium are Gram-positive bacteria that normally inhabit the human gastrointestinal tract. They are also opportunistic pathogens and can cause nosocomial infection outbreaks. To prevent the spread of nosocomial infections, hospitals may rely on screening methods to identify patients colonized with multidrug-resistant organisms including vancomycin-resistant enterococci (VRE). Spectra VRE agar (Remel) contains vancomycin and other medium components that select for VRE and phenotypically differentiate between faecalis and faecium species by colony color. We obtained 66 de-identified rectal swab cultures on Spectra VRE agar that were obtained during routine patient admission surveillance at a Dallas, Texas hospital. We analyzed 90 presumptive VRE from 61 of the Spectra VRE agar cultures using molecular and culture methods. Using ddl typing, 55 were found to be E. faecium and 32 were found to be E. faecalis. While most of the E. faecium were positive for the vanA gene by PCR (52 of 55 strains), few of the E. faecalis were positive for either vanA or vanB (5 of 32 strains). The 27 E. faecalis vanA- and vanB-negative strains could not be recultured on Spectra VRE agar. Overall, we found that Spectra VRE agar performed robustly for the identification of vancomycin-resistant E. faecium, but presumptive false positives were obtained for vancomycin-resistant E. faecalis.
Peripheral Blood DNA Methylation Changes after Omega-3 Fatty Acid Treatment Indicate Anti-inflammatory Effects and Individual Variability
Authors: Frankhouser David E , Steck Sarah , Sovic Michael G , Belury Martha A , Bundschuh Ralf , Yan Pearlly S , Yee Lisa D 
Published: October 2020

AbstractBackgroundOmega-3 or n-3 polyunsaturated fatty acids (PUFAs) are widely studied for health benefits based on potential anti-inflammatory effects. However, the factors involved in mediating the anti-inflammatory responses to n-3 PUFAs are not fully understood; furthermore, many effects from n-3 PUFA treatment are not well characterized in humans. Of interest is the role of DNA methylation (DNAm) in mediating the effects of n-3 PUFAs on inflammation.ObjectiveWe aimed to characterize the effects of n-3 PUFA treatment on DNAm in inflammation-related signaling pathways in PBMCs of women at high risk of breast cancerMethodsPBMCs of women at high risk of breast cancer were obtained at 0 and 6 months of n-3 PUFA treatment in a previously reported dose finding trial (n=10 matched pairs in the 5 g/day EPA+DHA dose arm).[53] DNA methylation of PBMCs were assayed using reduced representation bisulfite sequencing to obtain genome-wide methylation profiles on a single nucleotide level. Analyses were performed to investigate the effects of n-3 PUFA treatment on DNAm both genome-wide and within a set of candidate genes.ResultsA large number of differentially methylated CpGs (DMCs) in gene promoters (24,842 DMCs in 5507 genes) showed significant enrichment for hypermethylation in both the candidate gene and genome-wide analyses. Using these DNAm changes, pathway analysis identified significantly hypermethylated signaling networks after n-3 PUFA treatment, such as the Toll-like Receptor pathway. Based on analyses of data per individual, DNAm changes from n-3 PUFA treatment appear highly variable between study participants.ConclusionsDietary n-3 PUFA supplementation for six months is associated with DNAm changes in PBMCs with potential for anti-inflammatory effects. PBMC DNAm profiles may offer a novel means of assessing individual response to n-3 PUFAs. This observation warrants further investigation in future n-3 PUFA intervention studies.
COVID-19 serological survey using micro blood sampling
Authors: Matthews Melissa M. , Kim Tae Gyun , Shibata Satoshi , Shibata Noriko , Butcher Christian , Hyun Jaekyung , Kim Keon Young , Robb Theodore , Jheng Siang Sheng , Narita Masashi , Mori Tomoari , Collins Mary , Wolf Matthias 
Published: October 2020

AbstractDuring August 2020, we carried out a serological survey among students and employees at the Okinawa Institute of Science and Technology Graduate University (OIST), Japan, testing for the presence of antibodies against SARS-CoV-2, the causative agent of COVID-19. We used a FDA-authorized 2-step ELISA protocol (1, 2) in combination with at-home self-collection of blood samples using a custom low-cost finger prick-based capillary blood collection kit. Although our survey did not find any COVID-19 seropositive individuals among the OIST cohort, it reliably detected all positive control samples obtained from a local hospital and excluded all negatives controls. We found that high serum antibody titers can persist for at least up to 6.5 months post infection. Among our controls, we found strong cross-reactivity of antibodies in samples from a serum pool from two MERS patients in the anti-SARS-CoV-2-S ELISA. Here we show that a centralized ELISA in combination with patient-based capillary blood collection using as little as one drop of blood can reliably assess the seroprevalence among communities. Anonymous sample tracking and an integrated website created a stream-lined procedure. Major parts of the workflow were automated on a liquid handler, demonstrating scalability. We anticipate this concept to serve as a prototype for reliable serological testing among larger populations.
Development and validation of the 4C Deterioration model for adults hospitalised with COVID-19
Authors: Gupta Rishi K , Harrison Ewen M , Ho Antonia , Docherty Annemarie B , Knight Stephen R , van Smeden Maarten , Abubakar Ibrahim , Lipman Marc , Quartagno Matteo , Pius Riinu , Buchan Iain , Carson Gail , Drake Thomas M , Dunning Jake , Fairfield Cameron J , Gamble Carrol , Green Christopher A , Halpin Sophie , Hardwick Hayley E , Holden Karl A , Horby Peter W , Jackson Clare , Mclean Kenneth A , Merson Laura , Nguyen-Van-Tam Jonathan S , Norman Lisa , Olliaro Piero L , Pritchard Mark G , Russell Clark D , Scott-Brown James , Shaw Catherine A , Sheikh Aziz , Solomon Tom , Sudlow Cathie , Swann Olivia V , Turtle Lance , Openshaw Peter JM , Baillie J Kenneth , Semple Malcolm G , Noursadeghi Mahdad 
Published: October 2020

AbstractPrognostic models to predict the risk of clinical deterioration in acute COVID-19 are required to inform clinical management decisions. Among 75,016 consecutive adults across England, Scotland and Wales prospectively recruited to the ISARIC Coronavirus Clinical Characterisation Consortium (ISARIC4C) study, we developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) using 11 routinely measured variables. We used internal-external cross-validation to show consistent measures of discrimination, calibration and clinical utility across eight geographical regions. We further validated the final model in held-out data from 8,252 individuals in London, with similarly consistent performance (C-statistic 0.77 (95% CI 0.75 to 0.78); calibration-in-the-large 0.01 (−0.04 to 0.06); calibration slope 0.96 (0.90 to 1.02)). Importantly, this model demonstrated higher net benefit than using other candidate scores to inform decision-making. Our 4C Deterioration model thus demonstrates unprecedented clinical utility and generalisability to predict clinical deterioration among adults hospitalised with COVID-19.
Mathematical formulation and application of kernel tensor decomposition based unsupervised feature extraction
Authors: Taguchi Y-h. , Turki Turki 
Published: October 2020

ABSTRACTIn this work, we extended the recently developed tensor decomposition (TD) based unsupervised feature extraction (FE) to a kernel-based method through a mathematical formulation. Subsequently, the kernel TD (KTD) based unsupervised FE was applied to two synthetic examples as well as real data sets, and the findings were compared with those obtained previously using the TD-based unsupervised FE approaches. The KTD-based unsupervised FE outperformed or performed comparably with the TD-based unsupervised FE inlarge p small nsituations, which are situations involving a limited number of samples with many variables (observations). Nevertheless, the KTD-based unsupervised FE outperformed the TD-based unsupervised FE in nonlarge p small nsituations. In general, although the use of the kernel trick can help the TD-based unsupervised FE gain more variations, a wider range of problems may also be encountered. Considering the outperformance or comparable performance of the KTD-based unsupervised FE compared to the TD-based unsupervised FE when applied tolarge p small nproblems, it is expected that the KTD-based unsupervised FE can be applied in the genomic science domain, which involves manylarge p small nproblems, and, in which, the TD-based unsupervised FE approach has been effectively applied.
A Mathematical Model and Optimal Control for Listeriosis Disease from Ready-to-Eat Food Products
Authors: Chukwu Williams , Nyabadza Farai 
Published: October 2020

AbstractReady-to-eat food (RTE) are foods that are intended by the producers for direct human consumption without the need for further preparation. The primary source of human Listeriosis is mainly through ingestion of contaminated RTE food products. Thus, implementing control strategies for Listeriosis infectious disease is vital for its management and eradication. In the present study, a deterministic model of Listeriosis disease transmission dynamics with control measures was analyzed. We assumed that humans are infected with Listeriosis either through ingestion of contaminated food products or directly with Listeria Monocytogenes in their environment. Equilibrium points of the model in the absence of control measures were determined, and their local asymptotic stability established. We formulate an optimal control problem and analytically give sufficient conditions for the optimality and the transversality conditions for the model with controls. Numerical simulations of the optimal control strategies were performed to illustrate the results. The numerical findings suggest that constant implementation of the joint optimal control measures throughout the modelling time will be more efficacious in controlling or reducing the Listeriosis disease. The results of this study can be used as baseline measures in controlling Listeriosis disease from ready-to-eat food products.
Conservation status, threats, and information needs of small mammals in Alaska
Authors: Droghini A. , Christie K. S. , Kelty R. R. , Schuette P. , Gotthardt T. A. 
Published: October 2020

ABSTRACTDespite their diversity and ecological importance, small mammals are under-represented in conservation research relative to other mammals. We evaluated the conservation status of 36 small mammal species in Alaska, U.S.A. using a ranking system that we previously developed, the Alaska Species Ranking System (ASRS). We compared results from the ASRS with NatureServe’s subnational rankings. Finally, we surveyed taxonomic experts to identify recommended conservation actions and research priorities for 5 species of high conservation concern. In general, the ASRS and NatureServe agreed on the rankings of species in the highest and lowest risk categories. Species of highest conservation concern were taxa endemic to the state, including 2 island-endemic shrews, and taxa from the orders Chiroptera and Eulipotyphla. Because the ASRS includes information needs in its assessment, 15 of the 20 species considered lowest concern by NatureServe were considered intermediate concern by the ASRS. In the ASRS, most species (n= 24) were assessed to have low biological vulnerabilities, but high information needs. Population size and trends were unknown for all species; distributional limits and understanding of population dynamics were incomplete for all species except 4. Disease and climate change effects on habitat were perceived as important threats, but affected only 8 species. Taxonomic experts identified addressing data deficiencies and protecting habitat as important conservation actions; they identified monitoring population trends, modeling habitat, and researching species’ genetic diversity and adaptive capacity as high priorities. Conservation assessments that require accurate and current data on population trends or threats may lead to bias against data deficient groups such as small mammals. Our findings demonstrate the importance of accounting for data deficiencies in conservation status ranks to avoid conflation of sparse information with low conservation concern.
Light transport modeling in highly complex tissues using implicit mesh-based Monte Carlo algorithm
Authors: Yuan Yaoshen , Yan Shijie , Fang Qianqian 
Published: October 2020

AbstractThe mesh-based Monte Carlo (MMC) technique has grown tremendously since its initial publication nearly a decade ago. It is now recognized as one of the most accurate Monte Carlo (MC) methods, providing accurate reference solutions for the development of novel biophotonics techniques. In this work, we aim to further advance MMC to address a major challenge in biophotonics modeling, i.e. light transport within highly complex tissues, such as dense microvascular networks, porous media and multi-scale tissue structures. Although the current MMC framework is capable of simulating light propagation in such media given its generality, the run-time and memory usage grow rapidly with increasing media complexity and size. This greatly limits our capability to explore complex and multi-scale tissue structures. Here, we propose a highly efficient implicit mesh-based Monte Carlo (iMMC) method that incorporates both mesh- and shape-based tissue representations to create highly complex yet memory efficient light transport simulations. We demonstrate that iMMC is capable of providing accurate solutions for dense vessel networks and porous tissues while reducing memory usage by greater than a hundred- or even thousand-fold. In a sample network of microvasculature, the reduced shape complexity results in nearly 3x speed acceleration. The proposed algorithm is now available in our open-source MMC software athttp://mcx.space/#mmc.
Discovery of the first selective M4muscarinic acetylcholine receptor antagonists within vivoanti-parkinsonian and anti-dystonic efficacy
Authors: Moehle Mark S. , Bender Aaron M. , Dickerson Jonathan W. , Foster Daniel J. , Donsante Yuping , Peng Weimin , Bryant Zoey , Bridges Thomas M. , Chang Sichen , Watson Katherine J. , O’Neill Jordan C. , Engers Julie L. , Peng Li , Rodriguez Alice L. , Niswender Colleen M. , Lindsley Craig W. , Hess Ellen J. , Conn P. Jeffrey , Rook Jerri M. 
Published: October 2020

AbstractNon-selective antagonists of muscarinic acetylcholine receptors (mAChRs) that broadly inhibit all five mAChR subtypes provide an efficacious treatment for some movement disorders, including Parkinson disease and dystonia. Despite their efficacy in these and other central nervous system disorders, anti-muscarinic therapy has limited utility due to severe adverse effects that often limit their tolerability by patients. Recent advances in understanding the roles that each mAChR subtype plays in disease pathology suggest that highly selective ligands for individual subtypes may underlie the anti-parkinsonian and anti-dystonic efficacy observed with the use of non-selective anti-muscarinic therapeutics. Our recent work has indicated that the M4muscarinic acetylcholine receptor has several important roles in opposing aberrant neurotransmitter release, intracellular signaling pathways, and brain circuits associated with movement disorders. This raises the possibility that selective antagonists of M4may recapitulate the efficacy of non-selective anti-muscarinic therapeutics and may decrease or eliminate the adverse effects associated with these drugs. However, this has not been directly tested due to lack of selective antagonists of M4. Here we utilize genetic mAChR knockout animals in combination with non-selective mAChR antagonists to confirm that the M4receptor underlies the locomotor-stimulating and anti-parkinsonian efficacy in rodent models. We also report the synthesis, discovery, and characterization of the first-in-class selective M4antagonists VU6013720, VU6021302, and VU6021625 and confirm that these optimized compounds have anti-parkinsonian and anti-dystonic efficacy in pharmacological and genetic models of movement disorders.
Conservation of dynamic characteristics of transcriptional regulatory elements in periodic biological processes
Authors: Motta Francis C. , Moseley Robert C. , Cummins Bree , Deckard Anastasia , Haase Steven B. 
Published: October 2020

AbstractCell and circadian cycles control a large fraction of cell and organismal physiology by regulating large periodic transcriptional programs that encompass anywhere from 15-80% of the genome. The gene-regulatory networks (GRNs) controlling these programs were largely identified by genetics and chromosome mapping approaches in model systems, yet it is unlikely that we have identified all of the core GRN components. Moreover, large periodic transcriptional programs controlling a variety of processes certainly exist in important non-model organisms where genetic approaches to identifying networks are expensive, time-consuming or intractable. Ideally, the core network components could be identified using data-driven approaches on the transcriptome dynamics data already available. Previous work used dynamic gene expression features to identify sets of genes with periodic behavior; our work goes further to distinguish genes by role: core versus their non-regulatory outputs. Here we present a quantitative approach that can identify nodes of GRNs controlling cell or circadian cycles across taxa. There are practical applications of the approach for network biologists, but our findings reveal something unexpected—that there are quantifiable and fundamental shared features of these unrelated GRNs controlling disparate periodic phenotypes.Author summaryCircadian rhythms, cellular division, and the developmental cycles of a multitude of living creatures, including those responsible for infectious diseases, are among the many dynamic phenomena in the natural world that are known to be the eventual output of gene regulatory networks. Identifying the small number of specialized genes that control these dynamic behaviors is of fundamental importance to our understanding of life, and our treatment of disease, but is difficult because of the sheer size of the genomes. We show that the core genes in organisms separated by millions of years of evolution have remarkable similarities that can be used to identify them.