bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Systematic Visualization Review of Green Environment and Public Health for 2003-2019 Based on The Co-Citation Bibliometric Analysis Theory
Authors: Liu Yan , Koondhar Mansoor Ahmed , Ya Cheng , Khan Zaid Ashiq 
Published: December 2021

Abstract
Currently, the world is facing challenges of environmental pollution and public health owing to increasing urbanization. Therefore, many researchers from developed and developing countries are considering environmental pollution and public health to be the most important topics for sustainable development alongside a healthy and green environment. Although in the literature many researchers have investigated a pictorial view of green environment by defining the urban green space and blue space effects on public health, the green environments and public health research trend remains unclear. Thus, this study aimed to contribute to the literature by visualizing the bibliometric for green environments and public health, and to identify the missing research pathway. Data for this study was collected from the Web of Science from 2003-2019 in order to facilitate a visualization and bibliometric analysis carried out by CiteSpace. The visualization results reveal the most influential studies, institutions, authors, countries, keywords, and category cloud in the green environments and public health research field. Furthermore, this study suggests that researchers need to pay attention to how the genome changes due to climate change, as well as environmental pollution and its effect on human health. Mental health and research related to green environment and social health is also missing. In addition, there is also a missing link regarding green environment, underground water and public health. Additionally, this study could help authors and publishers make decisions concerning research on green environments and public health and planning for future perspectives to contribute to both academic development and applied methodology.
Risk Assessment of Runoff Generation Using Artificial Neural Network and Field Plots in The Area of Roads and Forest Lands
Authors: Dalir Pejman , Naghdi Ramin , Gholami Vahid , Tavankar Farzam , Latterini Francesco , Venanzi Rachele , Picchio Rodolfo 
Published: December 2021

Abstract
Runoff generation potential (RGP) on hillslopes is an important issue in the forest roads network monitoring process. In this study, the artificial neural network (ANN) was used to predict RGP in forest road hillslopes. We trained, optimized, and tested the ANN by using field plot data from the Shirghalaye watershed located in the southern part of the Caspian Sea (Iran). 45 plots were installed to measure actual runoff volume (RFP) in different environmental conditions including land cover, slope gradient, soil texture, and soil moisture. A multi-layer perceptron (MLP) network was implemented. The runoff volume was the output variable and the ground cover, slope gradient, initial moisture of soil, soil texture (clay, silt, and sand percentage) were the network inputs. The results showed that ANN can predict runoff volume within the values of an appropriate level in the training (R2=0.95, MSE= 0.009) and test stages (R2=0.80, MSE= 0.01). Moreover, the tested network was used to predict the runoff volume on the forest road hillslopes in the study area. Finally, an RGP map was generated based on the results of the prediction of the ANNs and the GIS capabilities. The results showed that using both an ANN and a GIS is a good tool to predict the RGP in the forest road hillslopes.
Characterization and Simulation of Metagenomic Nanopore Sequencing Data with Meta-NanoSim
Authors: Yang Chen , Lo Theodora , Nip Ka Ming , Hafezqorani Saber , Warren René L , Birol Inanc 
Published: December 2021

Abstract
Background: Nanopore sequencing is crucial to metagenomic studies as its kilobase-long reads can contribute to resolving genomic structural differences among microbes. However, sequencing platform-specific challenges, including high base-call error rate, non-uniform read lengths, and the presence of chimeric artifacts, necessitate specifically designed analytical tools, such as microbial abundance estimation and metagenome assembly algorithms. When developing and testing bioinformatics tools and pipelines, the use of simulated datasets with characteristics that are true to the sequencing platform under evaluation is a cost-effective way to provide a ground truth and assess the performance in a controlled environment. Results: Here, we present Meta-NanoSim, a fast and versatile utility that characterizes and simulates the unique properties of nanopore metagenomic reads. It improves upon state-of-the-art methods on microbial abundance estimation through a base-level quantification algorithm. Meta-NanoSim can simulate complex microbial communities composed of both linear and circular genomes, and can stream reference genomes from online servers directly. Simulated datasets showed high congruence with experimental data in terms of read length, error profiles, and abundance levels. We demonstrate that Meta-NanoSim simulated data can facilitate the development of metagenomic algorithms and guide experimental design through a metagenome assembly benchmarking task. Conclusions: The Meta-NanoSim characterization module investigates read features including chimeric information and abundance levels, while the simulation module simulates large and complex multi-sample microbial communities with different abundance profiles. All trained models and the software are freely accessible at Github: https://github.com/bcgsc/NanoSim .
Preoperative Diagnosis of Hepatocellular Carcinoma Patients with Bile Duct Tumor Thrombus using Deep Learning Method
Authors: Liu Jinming , Wu Jiayi , Liu Anran , Bai Yannan , Zhang Hong , Yan Maolin 
Published: December 2021

Abstract
Preoperative diagnosis of bile duct tumor thrombus (BDTT) is clinically important as the surgical prognosis of hepatocellular carcinoma (HCC) patients with BDTT is significantly different from that of patients without BDTT. The current diagnosis of BDTT is usually based on identifying dilated bile ducts (DBDs) on medical images (eg., CT and MRI images). However, it is easy for doctors to ignore DBDs when reporting imaging scan results, leading to a high misdiagnosis rate in practice. The aim of the present study was to develop an artificial intelligence (AI) pipeline for diagnosing HCC patients with BDTT using medical images. The proposed AI pipeline includes two stages. First, the object detection neural network Faster R-CNN is adopted to identify DBDs; then, an HCC patient is diagnosed to have BDTT if the proportion of images with at least one identified DBD exceeds some threshold value. The proposed AI pipeline was applied to a real dataset consisting of 2,611 CT images collected from 34 HCC patients (16 with BDTT and 18 without BDTT). The average true positive rate for identifying DBDs per patient was 0.92, while the patient-level true positive rate for diagnosing BDTT was 0.94. The area under ROC curve for patient-level diagnosis of BDTT was 0.92 (95% CI: 0.83, 1.00), compared with 0.71 (95% CI: 0.52, 0.89) by random forest based on preoperative clinical variables. These results demonstrated that the proposed AI pipeline is successful in the diagnosis of BDTT. The automatic detection of DBDs is a key step in early diagnosis of HCC patients with BDTT, and is helpful in the treatment and prognosis of these patients.
Analytical Study of ZnO-based HEMT for Power Switching
Authors: Kumar Pawan , Chaudhary Sumit , Khan Md Arif , Kumar Sanjay , Mukherjee Shaibal 
Published: December 2021

Abstract
We investigate the power switching mechanism to evaluate the power loss ( P D ) and efficiency ( η ) in MgZnO/ZnO (MZO)-based power high electron mobility transistor (HEMT), and physical parameters responsible for P D in molecular beam epitaxy (MBE) and dual ion beam sputtering (DIBS) grown MZO HEMT and compare the performance with the group III-nitride HEMTs. This work extensively probes all physical parameters such as two-dimensional electron gas (2DEG) density, mobility, switching frequency, and device dimension to study their impact on power switching in MZO HEMT. Results suggest that the MBE and DIBS grown MZO HEMT with the gate width ( W G ) of ∼ 205 and ∼ 280 mm at drain current coefficient (k) of 11 and 15, respectively, will achieve 99.96 and 99.95% of η and 9.03 and 12.53 W of P D , respectively. Moreover, W G value for DIBS-grown MZO HEMT is observed to further reduce in the range of 112-168 mm by using a Y 2 O 3 spacer layer leading to the maximum η in the range of 99.98-99.97% and the minimum P D in the range of 5-7 W. This work is significant for the development of cost-effective HEMTs for power switching applications.
Evaluation of Antioxidant Capacity and Antiproliferative Activity of Fruit Extract of Dry Figs (Ficus carica L.) on MDA MB-468 Cell Line
Authors: Maurya Anurag , Priyadarshini Eepsita , Rajamani Paulraj 
Published: December 2021

Abstract
Fig (Ficus carica L.; Hindi: Anjeer) is one of the the earliest domesticated fruit. Present study investigates its antiproliferative activity against breast cancer (MDA MB-468) cells. Dry figs were mascerated in sixteen solvent-combinations of varying polartiy and extracts were assessed for antiproliferative activity in vitro. Extracts of moderatly polar solvents, particularly 80% aqueous-methanol extract showed maximum activity (IC50 = 17.9 mg IDF/ml). Antiproliferative efficacy of extracts was supported by respective total phenolic content (41-236 mg GAE/100g) and various antioxidant capacities; ABTS (14-354 µM TE/g), DPPH (18-460 µM TE/g), FRAP (28.7-66.5 µM FeSO4 equivalents/g), ORAC (7.9-32.8 µM TE/g), and superoxide radical scavenging activity. Flow cytometry analysis revealed that extracts of lower IC50 induce more cell death. Phenolic compounds (cyanidin 3-O-glucoside, quercetin 3-β-glucoside, rutin, trans-cinnamic acid, ellagic acid and ferulic acid) were analysed by UPLC-PDA technique and their concentrations in extracts were found to be negatively correlated with respective IC50 values. The negative correlation suggests the involvement of phenolics in fig’s antiproliferative mechanism. Therefore, the study advocates fig as a dietary component having anticancer potential.
Development And Identification of 131 SNP Markers In Sthenoteuthis Pteropus (Steenstrup)
Authors: Zhao Yan , Wang Congcong , Liu Bilin , Li Gang , Xu Hao 
Published: December 2021

Abstract
The orangeback flying squid, Sthenoteuthis pteropus, is a species of significant potential value that is widely distributed in the tropical and temperate waters of the Atlantic Ocean. There have been no reports of the population genetics and effective molecular markers for this species due to a lack of reliable information regarding its genetic structure and its many individual differences, as well as its complex and changeable life history. Therefore, the development of auxiliary molecular markers would contribute to the development, sustainable utilization, and protection of the species. In this study, 131 novel single nucleotide polymorphism (SNP) markers were developed by double digest restriction-site associated DNA sequencing (dd-RAD). The observed heterozygosity (Ho) and expected heterozygosity (He) ranged from 0.00 to 0.80 and 0.18 to 0.50, respectively. The polymorphism information content (PIC) value ranged from 0.18 to 0.50. None of the marker locations significantly deviated from the Hardy-Weinberg equilibrium (p >0.05) after a Bonferroni correction. These polymorphic SNPs will be important in the further analysis of the population heredity of S. pteropus and its scientific management.
Molecular Investigation of Association Among Common IL-6 Polymorphism with Cytomegalovirus(CMV) Infection and Recurrent Miscarriage in Iranian Women
Authors: Ardakani Parisa Pourroostaei , Rahimi Bahareh , Panahi Mohammad , Karimian Babak , Rahimi Hamzeh 
Published: December 2021

Abstract
Background: Recurrent pregnancy loss (RPL) is described as two or more spontaneous abortions. Until now, although various factors such as genetic, endocrinology, anatomy, immunology, and microbiology have been distinguished that affect abortions, the precise basic etiology in up to 50% of RPL cases are not determined. Human cytomegalovirus (CMV) infection and host genetic background, like IL-6 SNP polymorphisms play important roles in RPL etiology. Objective: This study aimed to evaluate relationship among single nucleotide polymorphisms (-634C/G and -174 G/C) in the IL-6 gene with CMV infection and risk of RPL for early detection and treatment of RPL. Materials and methods: This case-control study was carried on 80 Iranian females with RPL and 80 healthy females as control group. The extraction of DNA from samples and detection of CMV and IL6 SNPs were determined by Tetra ARMS-PCR. Finally, the statistical analysis for detection CMV and two polymorphisms roles in RPL were analyzed by Epi Info TM software by X2 test. Results: Our results indicated an increased rate of CMV infection in RPL group (44%) versus the control group (25.45%). Also, the prevalence of IL-6 -634C/G genotype among RPL patients with CMV infection was 80%, while the frequency of this genotype among RPL patients without CMV infection was 50%. Furthermore, no substantial relation was found between IL-6 -174 G/C genotypes and RPL (P ≤0.0001). BesidesConclusion: This study not only indicated a significant role of CMV in RPL, but also showed CMV association with allele G in IL6 -634 among Iranian women. In addition, suggested the use of CMV and IL-6 -634 GG genotypes in RPL as diagnostic and prognostic biomarkers in Iranian population.
mTORC1 Signaling Pathway Mediated SIRT6 Overexpression in TGF-β1-Induced Pulmonary Fibrosis
Authors: Zhang Ji , Hu Yi , Huang Huiping , Liu Qun , Du Yang , Wang Guangdong , Gao Dehong , Guo Weixi , Wang Zhanxiang , Ma Aiping 
Published: December 2021

Abstract
Fibroblast-to-myofibroblast transdifferentiation and myofibroblast hyperproliferation play a major role in Idiopathic pulmonary fibrosis (IPF). It was also reported that mTOR signaling pathway and SIRT6 have a critical role in pulmonary fibrosis. However, the mechanisms whether mTOR signaling pathway and SIRT6 affect the myofibroblasts differentiation in IPF remain unclear. The results show that SIRT6 is significantly upregulated by TGF-β1 with a time and concentration-dependent manner in MRC5 line and primary lung fibroblasts isolated from IPF patients. SIRT6 protein is also increased in IPF fibrotic lung tissues and bleomycin-challenged mice lung tissues. Also, the activity of mTOR signaling is activated in MRC5 and primary lung fibroblasts. Furthermore, the inhibitor of mTOR, rapamycin treatment significantly suppress mTORC1 pathway activity and SIRT6 protein expression. SIRT6 siRNA failed to mediate the activity of mTORC1 pathway and autophagy induction. Finally, deficiency of SIRT6 could promote TGF-β1 induced pro-fibrotic cytokines. In summary, the study have suggested that SIRT6 is a downstream of mTORC1 signaling pathway in the pulmonary fibrosis caused by TGF-β1-induced. Deficiency of SIRT6 mediated myofibroblasts differentiation through induced pro-fibrotic cytokines production but not induced-autophagy. It was indicated that manipulations of SIRT6 expression may provide a new therapeutic strategy to reverse the progression of pulmonary fibrosis.
Incidence And Predictors of Relapse After Stopping Antiviral Therapy In Pediatric Chronic Hepatitis B
Authors: Upadhyay Piyush , Lal Bikrant Bihari , Sood Vikrant , Khanna Rajeev , Gupta Ekta , Rastogi Archana , Alam Seema 
Published: December 2021

Abstract
Objective: The objective was to evaluate the incidence of relapse after stopping antiviral therapy and to identify the predictors of relapse. Methods: All HBsAg positive children with who had been on antivirals for at least 2 years with undetectable HBV-DNA and normal alanine-aminotransferase (ALT) on three consecutive occasions over last 12 months were included. Antivirals were stopped if liver biopsy showed histological activity index <5 and fibrosis (metavir) <3. Children were monitored for virological relapse (elevation of HBV-DNA >2000 IU/mL) and biochemical relapse (ALT levels >2 × upper limit of normal (ULN)). Those having biochemical relapse were started on pegylated interferon alpha-2b based sequential therapy. Results: Antivirals were stopped in 31 HBsAg positive children. Virological and biochemical relapse was seen in 12 (38.7%) and 5 (16.1%) children within 12 months of stopping antiviral treatment. Majority of virological relapse occurred within a month and biochemical relapses within 6 months of stopping therapy. HBeAg positive status at the time of stopping antiviral therapy (HR: 7.206, p =0.005) and longer time taken for HBV-DNA to become undetectable while on antivirals (HR: 1.030, p=0.037) were found to be the 2 independent predictors of relapse after stopping antiviral treatment. Conclusion: Discontinuation of antiviral treatment in children with CHB resulted in relapse in one third of the patients. Relapse was more common in those with HBeAg positivity at the time of stopping therapy and in those with longer time taken for HBV-DNA to become undetectable on antivirals.
Modifiable Risk Factors for Incident Dementia and Cognitive Impairment: An Umbrella Review of Evidence
Authors: Zhang Yaru , Xu Wei , Zhang Wei , Wang Hui-Fu , Ou Ya-Nan , Qu Yi , Shen Xue-Ning , Chen Shi-Dong , Wu Kai-Min , Zhao Qian-Hua , Zhang Hai-Ning , Sun Li , Dong Qiang , Tan Lan , Feng Lei , Zhang Can , Evangelou Evangelos , Smith A David , Yu Jin-Tai 
Published: December 2021

Abstract

Dementia and cognitive impairment can be attributed to both genetic and modifiable risk factors. Recently, considerable evidence emerged and urgently require standardized evaluation. To address it, we conducted an umbrella review of prospective studies regarding the associations of dementia and cognitive impairment with modifiable factors to evaluate the strength and validity of the existing evidence. We searched PubMed, Embase, CINAHL and Cochrane Database of Systematic Reviews to identify relevant systematic reviews and meta-analyses of prospective studies. Mendelian randomization studies were reviewed to assess the causality for these associations. For each association, we analyzed the summary effect size, 95% confidence interval, 95% prediction interval, heterogeneity, small study effect and excess significance bias. Based on these estimates, the evidence was graded into levels of convincing, highly suggestive, suggestive, or weak. In total, 12015 articles were identified, of which 118 eligible studies yielded 243 unique associations. Convincing evidence was found for associations of dementia and cognitive impairment with early-life education, midlife to late-life plasma glucose, body mass index, atrial fibrillation, benzodiazepine use, and gait speed. Suggestive to highly suggestive evidence was found for associations of dementia and cognitive impairment with midlife to late-life blood pressure, homocysteine, cerebrovascular diseases, hearing impairment, respiratory illness, anemia, smoking, alcohol consumption, diet, sleep, physical activity and social engagement. Among convincing evidence, Mendelian randomization studies verified genetic predicted causal relationships for education and plasma glucose with Alzheimer's disease. Modifiable factors identified in this study, especially those with high-level evidence, should be considered in dementia prevention. Trial registration: PROSPERO CRD42020195729.
Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Post-traumatic Stress Disorder
Authors: Dai Yingliang , Zhou Zhou , Chen Feng , Zhang Li , Ke Jun , Qi Rongfeng , Lu Guangming , Zhong Yuan 
Published: December 2021

Abstract
BackgroundResearch has been looking into neural pathophysiology of post-traumatic stress disorder (PTSD) and dynamic functioning connectivity (dFC) applying resting state functional magnetic resonance imaging (rs-fMRI). Previous studies showed that PTSD related impairments are associated with alterations distributed across different brain regions and disorganized functional connectivity, especially in Default Mode Network and the cerebellar area. In this study, we specifically looked into dFC on a whole brain level, and we focused on critical regions such as DMN and cerebellum. MethodsTo explore the characteristics of dFC among patients with PTSD, we collected rs-fMRI data from 27 PTSD patients and 30 healthy controls. The study also added a control group of 33 trauma-exposed individuals to further look into trauma impact. Utilizing group spatial independent component analysis (ICA), the dynamic properties on whole brain level were detected with sliding time window approach, and k-means clustering. ResultsTwo reoccurring FC “States” were identified, with connections being more concentrated on a within-network level in one state and more strongly inter-connected in the other state. Abnormalities in dFC were found within DMN, between DMN and cerebellum, and between DMN and visual network. ConclusionsThe findings were in accordance with the study hypothesis that PTSD patients demonstrated deficits in emotional modulation and dysfunctional self-referential thoughts, and the deficits could be indicated in dFC alterations. Abnormalities in dFC among PTSD patients could serve as appropriate indicators of PTSD symptoms including depression and anxiety, hypervigilance, as well as impaired cognitive functioning and self-referential information processing.
How Sensitive Global Observables are to the Event Topology in Heavy-ion Collisions at the Large Hadron Collider: A Case Study
Authors: Prasad Suraj , Mallick Neelkamal , Behera Debadatta , Sahoo Raghunath , Tripathy Sushanta 
Published: December 2021

Abstract
Particle production and event topology are very strongly correlated in high-energy hadronic and nuclear collisions. Event topology is decided by the underlying particle production dynamics and medium effects. Transverse spherocity is an event shape observable, which has been used in pp and heavy-ion collisions to separate the events based on their geometrical shapes. It has the unique capability to distinguish between jetty and isotropic events. In this work, we have implemented transverse spherocity in Pb-Pb collisions at √ sNN = 5.02 TeV using A Multi-Phase Transport Model (AMPT). While awaiting for experimental explorations, we perform a feasibility study of dependence of transverse spherocity on some of the global observables in heavy-ion collisions at the Large Hadron Collider energies. These global observables include the Bjorken energy density (εBj), speed of sound (cs2) in the medium and the kinetic freeze-out properties for different collision centralities. The present study reveals about the usefulness of event topology dependent measurements in heavy-ion collisions in contrast to proton-proton collisions.