bluuebunny/crossref_metadata_2025_split huggingface dataset:
Online Clinical Pathway for Chronic Kidney Disease Management in Primary Care: A Retrospective Cohort Study
Authors: Donald Maoliosa , Smekal Michelle D. , Elliot Meghan J , McBrien Kerry , Weaver Robert , Manns Braden J. , Tonelli Marcello , Bello Aminu , Strauss Sharon E. , Scott-Douglas Nairne , Jindal Kailash , Hemmelgarn Brenda R. 
Published: June 2021

Abstract
BackgroundClinical pathways aim to improve patient care. We sought to determine whether an online chronic kidney disease (CKD) clinical pathway was associated with improvements in CKD management. MethodsWe conducted a retrospective pre/post population-based cohort study using linked health data from Alberta, Canada. We included adults 18 years or older with mean estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73m2. The primary outcome was measurement of an outpatient urine albumin creatinine ratio (ACR) in a 28-day period, among people without a test in the prior year. Secondary outcomes included use of guideline-recommended drug therapies (angiotensin-converting enzyme inhibitors, angiotensin receptor blockers and statins). Results The study period spanned October 2010 to March 2017. There were 84 independent 28-day periods (53 pre, 31 post pathway implementation) including 345,058 adults. The population was predominantly female (56%) with median age 77 years; most had category 3A CKD (67%) and hypertension (82%). In adjusted segmented regression models, the increase in the rate of change of ACR testing was greatest in Calgary zone (adjusted OR 1.19 per year, 95% CI 1.16-1.21), where dissemination of the pathway was strongest; this increase was more pronounced in those without diabetes (adjusted OR 1.25 per year, 95% CI 1.21–1.29). Small improvements in guideline-concordant medication use were also observed. Conclusions: Following implementation of an online CKD clinical pathway, improvements in ACR testing were evident in regions where the pathway was most actively used, particularly among individuals without diabetes.
Comparative Transcriptomic and Metagenomic Analysis Reveal the Key Factors on the Growth Rate in Red Swamp Crayfish (Procambarus Clarkii)
Authors: Chen Duanduan , Guo Leifeng , Wang Hui 
Published: June 2021

Abstract
Background: Although red swamp crayfish (Procambarus clarkii) is one of the most important species in aquaculture, the factors that influence differences in growth and development between individual siblings are still not fully understood. To address this lack of knowledge, we designed experiments to elucidate factors contributing to individual differences by comparing the hepatopancreatic transcriptome and gut flora structure of individuals with differences in sibling crayfish size under the same rearing conditions and attempted to find links between gut flora and host transcriptome information. Result: In total, 300691028 high-quality reads were obtained that were used to assemble 60637958 unigenes. Comparison of the expression profiles of the hepatopancreas of crayfish of different sizes revealed 497 differentially expressed genes (P<0.05). A total of 32 KEGG signaling pathways were found to be enriched after the KEGG database and GO functional annotation analyses, with the highest number of unigene enrichments related to organismal metabolism. Additionally, we found that proteobacteria, tenericutes, actinobacteria, and bacteroidetes made up a larger portion of the microbiome of larger individuals, suggesting that crayfish microbiota adapts to rapid growth, which may promote accelerated development by regulating the expression level of relevant genes.Conclusions: This work has accumulated data to support the potential impact of structural alterations in gut flora under equivalent feeding conditions in explaining the differential expression of transcriptomic genes among differentially developing individuals of sibling crayfish. These results further elucidate how the intestinal environment affects the rapid development of invertebrate crustaceans and provide a reference for further understanding of the regulatory mechanisms of the host's in vivo environment.
Update on Prevalence of Diagnosed Systemic Lupus Erythematosus (SLE) by Major Health Insurance Types in the US
Authors: Wang Yiting , Hester Laura L , Lofland Jennifer , Rose Shawn , Karyekar Chetan S , Kern David M , Blacketer Margaret , Davis Kourtney , Shields-Tuttle Kimberly 
Published: June 2021

Abstract
ObjectiveTo provide current estimates of the number of patients with prevalent systemic lupus erythematosus (SLE) by major health insurance types in the US and describe patient characteristics. Four large US health insurance claims databases were analyzed to represent different types of insurance coverage, including private insurance, Medicaid, and Medicare Supplemental. ResultsOverall unadjusted SLE prevalence per 100,000 persons in the US ranged from 150.1 (private insurance) to 252.9 (Medicare Supplemental insurance). Extrapolating to the US civilian population in 2016, we estimated roughly 345,000 to 404,000 prevalent SLE patients with private/Medicare insurance, and 99,000 prevalent SLE patients with Medicaid insurance.Comorbidities, including renal failure/dialysis were commonly observed across multiple organ systems in SLE patients (8.4-21.1%). We estimated a larger number of prevalent SLE cases in the US civilian population than previous reports and observed extensive disease burden based on a 1-year cross-sectional analysis.
An Integrated CUT&amp;RUN Quality Control Workflow for Histone Modifications and Transcription Factors
Authors: Boyd Joseph , Rodriguez Princess , Schjerven Hilde , Frietze Seth 
Published: June 2021

Abstract
ObjectiveAmong the different methods to profile the genome-wide patterns of transcription factor binding and histone modifications in cells and tissues, CUT&RUN has emerged as a more efficient approach that allows for a higher signal-to-noise ratio using fewer number of cells compared to ChIP-seq. The results from CUT&RUN and other related sequence enrichment assays requires comprehensive quality control (QC) and comparative analysis of data quality across replicates. While several computational tools currently exist for read mapping and analysis, a systematic reporting of data quality is lacking. Our aims were to 1) compare methods for using frozen versus fresh cells for CUT&RUN and 2) to develop an easy-to-use pipeline for assessing data quality.ResultsWe compared a workflow for CUT&RUN with fresh and frozen samples, and present an R package called ssvQC for quality control and comparison of data quality derived from CUT&RUN and other enrichment-based sequence data. Using ssvQC, we evaluate results from different CUT&RUN protocols for transcription factors and histone modifications from fresh and frozen tissue samples. Overall, this process facilitates evaluation of data quality across datasets and permits inspection of peak calling analysis, replicate analysis of different data types. The package ssvQC is readily available at https://github.com/FrietzeLabUVM/ssvQC.
Studies on the structure, optical, ac conduction mechanism by OLPT model and impedance spectroscopy of La-doped Ba2SnO4 Ruddlesden Popper Oxide
Authors: Kumar Upendra , Maurya Ram Sundar , Cheema Harshpreet , Yadav Vedika , Kumar Aditya , Alvi P. A. 
Published: June 2021

Abstract
The conventional ceramic route has been used to prepare the La-doped Ba2SnO4 samples by heat-treatment at 1000oC and sintered at 1250oC. The phase identification was carried out using XRD and found to be single phase up to 4 atoms %. The solubility of La at Ba-site were further reconfirmed using FTIR and Raman analysis. The AC conductivity spectra of all samples follow universal Johnscher’s power law; however, the thermal dependence of suggest Arrhenius type conduction within the sample. Further, the scaled conductivity and frequency at all temperatures superimposes on a single master curve, indicates the invariance of conduction mechanism. The impedance spectroscopy studies suggest the major contribution of grain in the conduction and relaxation. The present material could be potentially used in semiconductor device, UV-detector, and mixed ionic and electronic conductor (MIECs) by utilizing absorption states and thermo-curves as metastable state.
Malignant Clinical Course of Histologically Benign Ovarian Struma: case report and literature review
Authors: Asaturova Aleksandra , Magnaeva A. , Tregubova A. , Kometova V. , Karamurzin E. , Martynov S. , Lipatenkova Yu. , Adamyan L. 
Published: June 2021

Abstract
BackgroundStruma ovarii is a variant of monodermal teratoma, consisting of morphologically benign, atypical, or frankly malignant thyroid tissue. Morphologic features may or may not correlate with biologic behavior. Albeit this case report is not unique, ovarian tumor developed with peritoneal dissemination and bone metastasis, which is highly unlikely clinical complication. Additionally, we summarized previously cases of struma ovarii with an emphasis on correlation between morphological appearances, clinical course and providing treatment. Case presentationWe present the 38-year-old patient who was hospitalized for ovarian tumor. The diagnostic laparoscopy revealed lesions of peritoneum, sigmoid serosa and omentum and left ovarian mass. We diagnosed left ovarian mature teratoma without struma tissue and metastatic lesions with struma morphology which can be related to her history of left ovarian struma in 2016. Taking into account the metastatic lesions revealed in 2020, the tumor removed in 2016 was assessed as highly differentiated follicular carcinoma arising in struma ovarii. ConclusionsPrediction of biologic behavior of struma ovarii is still to be to diagnostic challenge, therefore multidisciplinary approach including clinical a n d laboratory findings, radiologic details and histopathological features is required. Providing additional data, the present case report contributes to expending the knowledge of these peculiar neoplasms.
Web crawling and mRNA sequencing analyze mechanisms of photobiomodulation
Authors: Wu Hao , Meng Caiyun , Xia Qing , Liu Hailiang , Zhang Fengmin , Song Wuqi 
Published: June 2021

Abstract
Background Photobiomodulation (PBM) is praised as a promising physical therapy, which has many advantages, such as noninvasive, painless. However, the mechanisms are not fully elucidated. Methods Using web crawling, mRNA sequence and bioinformatics analysis to select genes, functional annotation, and mechanisms. The expressions of inflammatory cytokines were measured using RT-qPCR. Results A total of 146 human genes and 57 pathways were identified about PBM. The 630nm LED-stimulated-MH7A cells were sequenced for further analyzing the mechanism of PBM. 2950 differentially expressed genes were identified, and the gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to better understand functions and pathways. The 12 pathways were matched with the KEGG results of PBM and MH7A cells. A protein-protein interaction network was performed among genes in 12 pathways, and 10 outstanding proteins were identified. Importantly, the 9 genes were predicted with potential research value.And we also demonstrated that expression of inflammatory factors (IL-6, IL-1β, IL-8, and MMP-3) was reduced; meanwhile, the expression of anti-inflammatory factor IL-10 was promoted after 630nm LED. In conclusion, using web crawling, bioinformatics analysis, and mRNA sequence, we obtained 9 key genes and 10 important pathways about PBM. Importantly, we demonstrated the anti-inflammatory effect of 630nm LED red light by RT-qPCR.
Semi-Markovian approach to optimizing the time of systematic preventive maintenance and the level of maintenance over a finite horizon
Authors: MBOGNE David Jaures FOTSA , Fonkou Armand , Nzie Wolfgang , Marquez Adolfo Crespo 
Published: June 2021

Abstract
This work is concerned with the problem of optimizing maintenance policies in terms of economical rewards and availability. We consider a system with multiple states in terms of healthy mode (good state, degraded state and failure state) and maintenance action (running state, stopped for maintenance). The level of maintenance (perfect or not) is also taken into account. We propose semi-Markovian model highlighting the eﬀects of dwell times and transitions on economical rewards. We determine an optimal policy conditionally upon the current state according to eight decision parameters related to time intervals between two preventive maintenances and the level of maintenance. We show through a sensitive analysis that decision parameters have nonlocal eﬀects that imply a multiple objective function. Hence, we propose a compromise by optimizing the asymptotic average reward.
Validation of a semiautomatic image analysis software for the quantification of musculoskeletal tissues
Authors: Imani Mahdi , Hassan Ebrahim Bani , Vogrin Sara , Ch'Ng Aaron Samuel Tze Nor , Lane Nancy E. , Cauley Jane A. , Duque Gustavo 
Published: June 2021

Abstract
Background: Accurate quantification of bone, muscle, and their components is still an unmet need in the musculoskeletal field. Current methods to quantify tissue volumes in 3D images are expensive, labor-intensive, and time-consuming; thus, a reliable, valid, and quick application is highly needed.Methods: Tissue Compass is a standalone software for semiautomatic segmentation and automatic quantification of musculoskeletal organs. To validate the software, cross-sectional micro-CT scans images of rat femur (n=19), and CT images of hip and abdomen (n=100) from the Osteoporotic Fractures in Men (MrOS) Study were used to quantify bone, hematopoietic marrow (HBM), and marrow adipose tissue (MAT) using commercial manual software as a comparator. Also, abdominal CT scans (n=100) were used to quantify psoas muscle volumes and intermuscular adipose tissue (IMAT) using the same software. We calculated Pearson's correlation coefficients, individual intra-class correlation coefficients (ICC), and Bland-Altman limits of agreement together with Bland-Altman plots to show the inter- and intra-observer agreement between Tissue Compass and commercially available software.Results: In the animal study, the agreement between Tissue Compass and commercial software was r>0.93 and ICC>0.93 for rat femur measurements. Bland-Altman limits of agreement was -720.89 (-1.5e+04, 13074.00) for MAT, 4421.11 (-1.8e+04, 27149.73) for HBM and -6073.32 (-2.9e+04, 16388.37) for bone. The inter-observer agreement for QCT human study between two observers was r>0.99 and ICC>0.99. Bland-Altman limits of agreement was 0.01 (-0.07, 0.10) for MAT in hip, 0.02 (-0.08, 0.12) for HBM in hip, 0.05 (-0.15, 0.25) for bone in hip, 0.02 (-0.18, 0.22) for MAT in L1, 0.00 (-0.16, 0.16) for HBM in L1, 0.02 (-0.23, 0.27) for bone in L1. The intra-observer agreement for QCT human study between two applications was r>0.997 and ICC>0.99. Bland-Altman limits of agreement was 0.03 (-0.13, 0.20) for MAT in hip, 0.05 (-0.08, 0.18) for HBM in hip, 0.05 (-0.24, 0.34) for bone in hip, -0.02 (-0.34, 0.31) for MAT in L1, -0.14 (-0.44, 0.17) for HBM in L1, -0.29 (-0.62, 0.05) for bone in L1, 0.03 (-0.08, 0.15) for IMAT in psoas, and 0.02 (-0.35, 0.38) for muscle in psoas. Conclusion: Compared to a conventional application, Tissue Compass demonstrated high accuracy and non-inferiority while also facilitating easier analyses. Tissue Compass could become the tool of choice to diagnose tissue loss/gain syndromes in the future by requiring a small number of CT sections to detect tissue volumes and fat infiltration.
Hospital-prepared low-dose atropine eye drops for myopia progression control using atropine sulfate injection diluted in normal saline and lubricants
Authors: Wongwirawat Nuthida , Kuchonthara Nirachorn , Boontanomwong Sorrawit , Pongpirul Krit 
Published: June 2021

Abstract
BackgroundAs commercial low-dose atropine eye-drops for myopia progression control are available in some countries, in-house preparation by diluting the 0.1% atropine eye-drop with sterile water or normal saline has been a common practice. Atropine injection is readily available and could be a more feasible alternative.ObjectiveTo assess the properties of the in-house low-dose atropine eye-drops prepared by diluting the atropine injection in two solvents and tested in two temperature conditions.MethodThe 0.01% atropine eye-drops (15ml) were prepared by diluting atropine sulfate injection with normal saline and lubricant eye-drops and stored at room temperature and in a refrigerator. All samples were daily dropped for 12 weeks to mimic real-life use, one of which was assessed every two weeks for the biological contamination and chemical properties. The active substance was compared with freshly prepared samples at the 12th week.ResultsThe 0.01% atropine eye-drops contains no bacteria, fungi, or particulate matter. The levels of atropine sulfate on all samples were comparable to the freshly prepared samples at the 12th week, regardless of the solvents used or storage conditions.ConclusionThe low-dose atropine eye-drops prepared from readily available atropine sulfate injection at healthcare facilities could be alternative to commercial products
A Hybrid Approach for Predition of Machining Performances of Glass Fiber Reinforced Plastic (Epoxy) Composites
Authors: Raveendran P. , Alagarsamy S. V. , Chanakyan C. , Meignanamoorthy M. , Ravichandran M. , Sakthivelu S. 
Published: June 2021

Abstract
In recent years, Glass Fiber Reinforced Plastic (GFRP) composites are more potential materials for usage in various structural applications in aerospace and automobile industries, owing to its favorable properties, such as light weight, specific strength, high elastic modulus and excellent corrosion resistance. This paper presents a new hybrid approach for multi-objective optimization of machining parameters on GFRP composite using Taguchi coupled grey relational (GR) and desirability function (DF) approach. The end milling of GFRP composite was performed as per Taguchi’s L16 orthogonal array by considering three input parameters: viz. cutting speed (V), feed rate (F) and depth of cut (D), each at four levels. The material removal rate (MRR), surface roughness (SR) and tool wear (TW) were chosen as output responses. The main effect plot was used to determine the optimum level of machining parameters on the multiple responses. Moreover, analysis of variance (ANOVA) were applied to examine the significance of the parameters. Based on the ANOVA results, it was been proved that the depth of cut was the most remarkable parameter, trailed by feed rate and cutting speed, respectively. Finally, the confirmation tests exhibited that the DA approach was employed better in terms of determining the optimum level of machining parameters as compared to GR analysis.
Simulating the behaviour of Glioblastoma Multiforme based on patient MRI during treatments
Authors: Alonzo Flavien , Saad Mazen , Serandour Aurelien 
Published: June 2021

Abstract
Glioblastoma Multiforme is a brain cancer that still show poor prognosis for patients despite the active researches for new treatments. In this work the goal is to model and simulate the evolution of tumour associated angiogenesis and the therapeutic response of the Glioblastoma Multiforme. Multiple phenomena are modelled in order to fit different biological pathways, such as, the cellular cycle, apoptosis, hypoxia or angiogenesis.This results in a nonlinear system with 4 equations and 4 unknowns: the density of tumour cells, the $O_{2}$ concentration, the density of endothelial cells and the vascular endothelial growth factor concentration.This system is solved numerically on a 2D-slice of Magnetic Resonance Imaging, using a nonlinear control volume finite element scheme on a mesh fitting the geometry of the brain and the tumour of a patient.We show that this implicit volume finite element numerical scheme is positive and we give energy estimates on the discrete solution to ensure convergence.The numerical scheme is implicit in time.Numerical simulations of this scheme have been done using the different standard treatments: surgery, chemotherapy and radiotherapy, in order to understand the behaviour of tumour in response to treatments.
Neural networks for computing the continuous nonlinear Fourier spectrum in focusing nonlinear Schrodinger equation: NFT-Net
Authors: Sedov Egor V. , Freire Pedro J. , Seredin Vladimir V. , Kolbasin Vladyslav A. , Kamalian-Kopae Morteza , Chekhovskoy Igor S. , Turitsyn Sergei K. , Prilepsky Jaroslaw E. 
Published: June 2021

Abstract
We combine the nonlinear Fourier transform (NFT) signal processing with machine learning methods for solving the direct spectral problem associated with the nonlinear Schrödinger equation. The latter is one of the core nonlinear science models emerging in a range of applications. Our focus is on the unexplored problem of computing the continuous nonlinear Fourier spectrum associated with decaying profiles, using a specially-structured deep neural network which we coined NFT-Net. The Bayesian optimisation is utilised to find the optimal neural network architecture. The benefits of using the NFT-Net as compared to the conventional numerical NFT methods becomes evident when we deal with noise-corrupted signals, where the neural networks-based processing results in effective noise suppression. This advantage becomes more pronounced when the noise level is sufficiently high, and we train the neural network on the noise-corrupted field profiles. The maximum restoration quality corresponds to the case where the signal-to-noise ratio of the training data coincides with that of the validation signals. Finally, we also demonstrate that the NFT b-coefficient important for optical communication applications can be recovered with high accuracy and denoised by the neural network with the same architecture.
Emergence of Urban Growth Patterns from Human Movements
Authors: Xu Fengli , Li Yong , Jin Depeng , Lu Jianhua , Song Chaoming 
Published: June 2021

Abstract
Cities grow in a bottom-up manner, leading to fractal-like urban morphology characterized by scaling laws. Correlated percolation has succeeded in modeling urban geometries by imposing strong spatial correlations. However, the origin of such correlations remains largely unknown. Very recently, our understanding of human movements has been revolutionized thanks to the increasing availability of large-scale human mobility data. This paper designs a novel computational urban growth model that offers a micro-foundation in human mobility behavior. We compare the proposed model with three empirical datasets, which evidences that strong social couplings and long-memory effect are two fundamental principles responsible for the mystical spatial correlations. The model not only accounts for the empirically observed scaling laws, but also allows us to understand the city evolution dynamically.