bluuebunny/crossref_metadata_2025_split huggingface dataset:
Continuous Infusion of Lidocaine in Pediatric Colonoscopy: A Randomized Placebo-Controlled Study
Authors: Yuan Chao , Wang Chengli , Wu Jiayao , Gao Ningyang , Li Kuiwei , Li Yongle , Huang Xizhao , Huang Wei , Hu Zurong 
Published: November 2020

Abstract
Background: To investigate the effect of intravenous lidocaine on perioperative propofol and sufentanil dosage, pulse oxygen saturation, postoperative pain score and recovery time during pediatric colonoscopy.Methods: We designed a randomized placebo-controlled study and enrolled 80 children aged from 3 to 10 years old who were received colonoscopy. After titration of propofol to achieve unconsciousness, patients were given intravenous lidocaine (1.5 mg kg-1 then 2 mg kg-1 h-1) or the same volume of saline. Sedation was standardized and combined propofol with sufentanil. The primary outcome variables were intraoperative propofol and sufentanil requirements and number of oxygen desaturation episodes. Secondary outcome variables were recovery time after colonoscopy and post-colonoscopy pain.Results: Lidocaine infusion resulted in a significant reduction in propofol requirements: mean (SD) 44.3 (9.9) vs 74.5 (12.0) mg, respectively; P<0.001) and sufentanil requirements: mean (SD) 1.5 (0.3) vs 2.6 (0.6) ug respectively; p<0.001). The number of subjects who experienced oxygen desaturation below 95% in the lidocaine group was also significantly less than that in the control group: 2 vs 8 (P=0.04). The mean (SD) recovery time was significantly shorter in lidocaine group: 19.2 (2.6) vs 13.3 (2.6) min respectively; p<0.001). There were no significant difference regarding post-colonoscopy pain.Conclusions: Continuous infusion of lidocaine resulted in reduction of propofol and sufentanil dose, recovery time and risk of hypoxemia during pediatric colonoscopy.Trial Registration: Chinese Clinical Trials Registry, ChiCTR2000028927, 8 January, 2020, prospectively registered.
Characterization of a Clinical Enterobacter hormaechei Strain Belonging to Epidemic Clone ST418 Co-carrying blaNDM-1, blaIMP-4 and mcr-9.1
Authors: Chen Wei , Hu Zhiliang , Wang Shiwei , Huang Doudou , Wang Weixiao , Cao Xiaoli , Zhou Kai 
Published: November 2020

Abstract
An Enterobacter hormaechei isolate (ECL-90) simultaneously harboring blaNDM-1, blaIMP-4 and mcr-9.1 was recovered from the secretion specimen of a 24-year-old male patient in a tertiary hospital in China. The whole genome sequencing of this isolate was complete, and 4 circular plasmids with variable sizes were detected. Multi-locus sequence typing (MLST) analysis assigned the isolate to ST418, known as a carbapenemase-producing epidemic clone in China. blaIMP-4 and mcr-9.1 genes were co-carried on an IncHI2/2A plasmid (pECL-90-2) and blaNDM-1 was harbored by an IncX3 plasmid (pECL-90-3). The genetic context of mcr-9.1 was identified as a prevalent structure, “rcnR-rcnA-pcoE-pcoS-IS903-mcr-9-wbuC”, which is a relatively unitary model involved in the mobilization of mcr-9. Meanwhile, blaNDM-1 gene was detected within a globally widespread structure known as NDM-GE-U.S (“ISAba125–blaNDM-1–blaMBL”). Our study warrants that the convergence of genes mediating resistance to last-resort antibiotics in epidemic clones would largely facilitate their widespread in clinical settings, thus representing a potential challenge to clinical treatment and public health.
Development, Popularization and Application of An Online OvAge Calculator Based on Subject Self-reporting System
Authors: Xu Wenwen , Zhu Zheng , Wang Quan , Jin Jing , Zhao Haiyang , Shao Fang , Ren Qingling , Wang Hui 
Published: November 2020

Abstract
Background: At present, there are many clinical markers and models to assess ovarian reserve, but none of them are ideal. The number of clinical samples is a key factor limiting the specificity and sensitivity of the markers and models, and traditional methods of subject recruitment are time and vigor. In addition, the model of ovarian reserve assessment for Chinese women need to be further explored.Objective: To explore the possibility of self-reporting for subjects through the WeChat mini program, and provide more data support for further optimization of the OvAge model, and to develop a predictive model of ovarian reserve that is specific to Chinese women.Methods: In this paper, with reference to the existing OvAge model, we developed an online OvAge calculator based on the WeChat mini program for data collection, and then applied the generalized linear model theory to obtain a predictive model of ovarian reserve which is in line with the characteristics of Chinese women.Results: Compared to traditional recruiting methods, the online OvAge calculator is able to collect a large number of samples in a short period of time, which is efficient and convenient. Optimized model of estimated OvAge =exp (3.5254-0.001*PRL-0.0231*AMH). This model showed a high statistical significance for each marker included in the equation. We applied the final equation on diminished ovarian reserve and polycystic ovary syndrome datasets and obtained a mean of predicted ovarian age significantly different from the mean of chronological age in both groups.Conclusions: The OvAge calculator based on the WeChat mini program is a novel online subject self-reporting system that can collect a large number of samples in a short period of time, continuously optimize the model and update the mini program version, which is economical, time-saving and efficient., and is worthy of promotion. In addition, the optimized OvAge model is suitable for Chinese women and provides a reference for clinical assessment of ovarian reserve.
Developing Traﬃc Congestion Detection Model Using Deep Learning Approach: A Case Study of Addis Ababa City Road
Authors: Bekele Bedada , Kekeba Kula 
Published: November 2020

Abstract
The traﬃc system is one of the core requirements of a civilized world and the development of the country depends on it in many aspects. In Ethiopia, the number of vehicles and pedestrians is increasing at a high rate from time to time. Excessive numbers of traﬃc on roads and improper control of traﬃc create traﬃc congestion. Uncontrolled traﬃc congestion hinders the transportation of goods and commuters from place to place and increases the volume of carbon emitted into the air. It can also either hampers or stagnates schedule, business, and commerce. Many images and video processing approaches have been researched in the literature on how to detect traﬃc congestion. One such approach is that of using background and foreground subtraction, convolutional neural network, and Average frame diﬀerence and deep learning method used to detect traﬃc congestion from diﬀerent video sources. From the review one-stage object detector identiﬁed as the best methods to detect traﬃc congestion with acceptable accuracy and speed. In this study one-stage object detectors are used to detect traﬃc congestion from recorded video. Data is collected from diﬀerent video footage and frames extracted from videos to prepare a dataset for the thesis. The extracted frames were labeled manually as congested and uncongested. To train, the models pre-trained weights were used. YOLOV3 and YOLOV5 model used for experimentation. Accuracy and speed metrics used to evaluate the performance of the models. A YOLOV3 model achieved 41.6 FPS and 68.6 % mAP on a testing dataset.
Skeleton Based Perpendicularly Scanning -&nbsp;A New Scanning Strategy for Additive Manufacturing: Modeling and Optimization
Authors: Jai Mostapha El , AKHRIF Iatimad , Saidou Nourddin 
Published: November 2020

Abstract
In this paper, the authors propose a novel strategy of 2D scanning that might be adapted for any additive manufacturing process. The featured novelty corresponds to a Skeleton Based Perpendicularly (SBP) of the 2D shape of each slice. Thus, it is proposed to minimize the total production time of a given layer under some constraints. In other word, it is proposed to study the competitiveness conditions of the new scanning technique regarding the classical chess scanning strategy from a productivity perspective. In order to introduce this new technique, the paper treats the case of a rectangular layer. The competitiveness of the proposed technique was discussed according to chess decomposition parameters, the hatch space distance, and the dimensions of the primitive rectangle layer to analyze. The indicators introduced corresponds to “the gain of production time” and “the specific gain of production time per surface unit”; then, these latter were computed and discussed in two separated cases of study. The findings show that, by the adoption of the SBP technique instead the chess scanning strategy, it is possible to save about 3% to 45% of production time gain for the first case of study. The gain of production time per surface unit was analyzed in the second case of study. The correspondent analysis permitted to highlight the percentage of gain of time related to the area to scan. Indeed, the gain per surface unit varies between 4.32×10-6%/mm2 and 6.96×10-05%/mm2. In one hand, these indicators depend linearly on the decomposition strategy of the central area of the SBP technique and also according to the rectangle dimensions. In addition, for the lowest values of hatch space, around 25µm, the two techniques in competition present quasi-similar production time, where the variations between them is minimal. Nevertheless, starting from 65µm, the SBP scanning strategy present considerable less time of production judged as exponentially decreasing according to the hatch space distance. Finally, one can see that the scanning model proposed could present major contributions in other scientific and technical fields that use surface control as territorial security, water adduction and distribution, telecommunication, etc. by varying and adapting the decision variables according to each field of study.
Disentangling Archaeal and Bacterial Biogeography and Co-occurrence Networks in Subtropical Mangrove Sediments Under Spartina Alterniflora Invasion
Authors: Chen Weidong , Wen Donghui 
Published: November 2020

Abstract
Background: Mangrove ecosystems are vulnerable due to the exotic Spartina alterniflora invasion in China. Large knowledge gaps remain with regard to archaeal and bacterial communities assembly processes and microbial interactions under S. alterniflora invasion. Here, using 16S rRNA gene amplicon sequencing, we investigated the assembly processes and co-occurrence relationships of the archaeal and bacterial communities under S. alterniflora invasion along the coastlines of Fujian province, southeast China.Results: We found that the overall archaeal and bacterial communities were driven predominantly by stochastic processes, and the relative role of stochasticity was stronger for bacteria than archaea. Co-occurrence network analysis showed that the network structure of bacteria was more complex than that of the archaea. Putative keystone taxa often had low relative abundances (conditionally rare taxa), suggesting conditionally rare taxa or low abundances taxa may significantly contribute to network stability. Moreover, we found that S. alterniflora invasion changed the microbial communities assembly and co-occurrence patterns, indicating that S. alterniflora affected the composition and stability of the microbial community.Conclusions: This study provides the first comparison in the biogeography and co-occurrence patterns of both archaea and bacteria in mangrove ecosystem. And this is the first exploration about the effect of S. alterniflora invasion on archaeal and bacterial ecological processes and co-occurrence patterns. Our study considers that the control of S. alterniflora invasion is important for mangrove ecosystem function and service.
Disease-induced Changes in Plant Microbiome Assembly and Functional Adaptation
Authors: Gao Min , Xiong Chao , Gao Cheng , Tsui Clement K.M. , Zhou Xin , Wang Meng-Meng , Zhang Ai-Min , Cai Lei 
Published: November 2020

Abstract
Background: Plant microbiome is an integral part of the host influencing its growth and health. The increasing evidence indicates that plant rhizosphere may recruit beneficial microbes to suppress soil-borne pathogen, but the ecological mechanisms that govern plant microbiome assembly and functions under disease in both below and aboveground compartments are not fully understood. Here we examined both bacterial and fungal communities from soils (rhizosphere and bulk soil) and multiple plant compartments (e.g. root, stem, and fruit) of chili pepper (Capsicum annuum L.) at two pepper production sites, and explored how Fusarium wilt disease (FWD) affect the assembly, co-occurrence patterns, and ecological functions of plant-associated microbiomes. Results: Our data demonstrated that FWD had less impact on reproductive organ (fruit) than on vegetative organs (root and stem), with the strongest impact in the stem upper epidermis. Fungal intra-kingdom networks presented lower stabilities and their communities were more sensitive to FWD than the bacterial communities. Moreover, the diseased pepper was more susceptible to colonization by other pathogenic fungi, but they may recruit potential beneficial bacteria to facilitate host or offspring survival, and FWD may enhance the ecological importance of fungal taxa in the interkingdom network. Further, metagenomic analysis revealed that several potential protective functional genes encoding detoxify and biofilm formation were significantly enriched in the diseased pepper.Conclusion: Together, these results significantly advance our understanding of pepper microbiome assembly and functions under biotic stress. Our work highlights the diseased plant and the aboveground compartments harbor a potential of beneficial microbiomes and functions that, in concert, can provide potential critical data for harnessing the plant microbiome for sustainable agriculture.
Candidate Biomarkers for the Detection of Serious Infections in Children: A Prospective Clinical Study
Authors: Pellegrin Maria Chiara , Penco Arturo , Amadio Leonardo , Naviglio Samuele , De Leo Luigina , Radillo Oriano , Biolo Gianni , Fiotti Nicola , Mearelli Filippo , Rabusin Marco , Barbi Egidio , Monasta Lorenzo 
Published: November 2020

Abstract

BACKGROUND: Serious bacterial infections (SBI) in children are still associated with considerable morbidity and mortality. Early identification of SBI in children presenting with fever and/or signs of systemic inflammatory response (SIRS) remains challenging, as clinical presentation may be subtle, and the role of laboratory markers is still debated. The purpose of the present study is to evaluate the diagnostic role of established and candidate blood biomarkers for the early discrimination of SBI in pediatric patients presenting with fever and/or SIRS criteria.METHODS: Children who met SIRS criteria and had the clinical indication to perform blood sampling at the first medical evaluation were consecutively enrolled. A panel of biomarkers was performed at enrolment, including C-reactive protein, procalcitonin, white blood cell count (WBC), absolute neutrophil count (ANC), interleukin (IL)-6, IL-8, IL-10, human terminal complement complex (C5b-9), Plasmalemma-Vesicle-associated protein 1 (PV-1), Intercellular Adhesion Molecule-1 (ICAM-1), and Phospholipase A2 (PLA2). Bivariate logistic regression models were created to identify significant predictors of SBI. RESULTS: Among 103 patients (median age 2.9 years, 60% males), 39 had a diagnosis of SBI (38%). Significant predictors of SBI were CRP (p=0.001) and ICAM-1 (p=0.043). In the subgroup of patients who were not immunocompromised because of a pre-existing medical condition or therapy (e.g. children with cancer and chemotherapy-induced neutropenia), significant predictors of SBI, were CRP (p=0.001) and ICAM-1 (p=0.037), WBC (p=0.035), ANC (p=0.012) and ANC/WBC ratio (p=0.015). The diagnostic performance of each variable as evaluated by means of ROC curves revealed suboptimal performance for all variables. A model combining CRP and ANC/WBC ratio, however, had a greater diagnostic accuracy than each one of the two variables. CONCLUSION: This study confirmed the limited usefulness of blood biomarkers for early diagnosis of SBI. WBC, ANC, ANC/WBC ratio, CRP and ICAM-1 showed the best, albeit moderate, diagnostic accuracy as single marker. At present, clinical judgement remains the mainstay for the diagnosis of SBIs in children.
The Construction and Exploration of the ceRNA Network and Patterns of Tumor-Infiltrating Immune Cells in Kidney Renal Clear Cell Carcinoma
Authors: Jia Weiwei , Li Pengjia , Ma Mingxia , Niu Xiaochen , Bai Lina , Hao Haihu , Wang Xiaohui , Wang Li 
Published: November 2020

Abstract
Background: Kidney renal clear cell carcinoma is the malignant tumor with the highest incidence and poor prognosis in renal cell carcinoma. In view of its limited diagnostic strategies and poor prognosis, bioinformatics analysis has been used to explore the possible mechanisms of renal clear cell carcinoma and effective prognostic-related biomarkers.Method: The sequencing information of 3 types of RNA (mRNA, lncRNA and miRNA) in 539 cases of kidney renal clear cell carcinoma tumor tissues and 72 cases of normal tissues is obtained from the TCGA database. Heat map and volcano map of differentially expressed genes were drawn through R language; The CeRNA network was visualized by Cytoscape software (version 3.7.2). Methods such as univariate Cox regression analysis, lasso regression screening, and multivariate Cox regression analysis were used to construct a prognostic model based on the CeRNA network. The CIBERSORT algorithm was used to analyze the degree of infiltration of 22 kinds of immune cells from each sample of kidney renal clear cell carcinoma. Construction of a prognostic model based on tumor-infiltrating immune cells, The R "corrplot" software package was used for co-expression analysis based on the CeRNA network and tumor-infiltrating immune cells model.Results: There are 3074 differentially expressed mRNAs (1055 upregulated and 2019 downregulated), and 359 differentially expressed lncRNAs (71 upregulated and 280 downregulated) and 132 differentially expressed miRNAs (70 upregulated and 62 downregulated) that have been identified through differential analysis. A complete mRNA-miRNA-lncRNA (SIX1-hsa-miR-200b-3p-MALAT1) network was obtained based on the CeRNA network-based prognostic model construction. 2 immune cells (Mast cells resting, T cells follicular helper) were identified by constructing a prognostic model based on tumor-infiltrating immune cells. There was a negative correlation between lncRNA MALAT1 and Mast cells resting (R= -0.27, P<0.001); while there was a positive correlation between lncRNA MALAT1 and T cells follicular helper (R=0.23, P<0.001).Conclusion: Based on CeRNA network and tumor-infiltrating immune cells, we explored the possible mechanism of kidney renal clear cell carcinoma and obtained effective biomarkers for predicting prognosis by Bioinformatics analysis in this study.
Molecular Characterization and Clinical Relevance of m6A RNA Methylation Regulators in Cervical Cancer
Authors: Chen Jin , He Ji , Ma Xiaolei , Guo Xia 
Published: November 2020

Abstract
Background: RNA modification, such as methylation of N6 adenosine (m6A), plays a critical role in many biological processes. However, the role of m6A RNA modification in cervical cancer (CC) remains largely unknown. Methods: The present study systematically investigated the molecular signatures and clinical relevance of 20 m6A RNA methylation regulators (writers, erasers, readers) in CC. The mRNA expression and clinical significance of m6A-related genes were investigated using data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) cervical cancer cohort. Mutations, copy number variation (CNV), differential expression, gene ontology analysis and the construction of a mRNA-microRNA regulatory network were performed to investigate the underlying mechanisms involved in the abnormal expression of m6A-related genes. Results: We found inclusive genetic information alterations among the m6A regulators and that their transcript expression levels were significantly associated with cancer hallmark-related pathways activity, such as the PI3K-AKT signaling pathway, microRNAs in cancer and the focal adhesion pathway, which were significantly enriched. Moreover, m6A regulators were found to be potentially useful for prognostic stratification and we identified FMR1 and ZC3H13 as potential prognostic risk oncogenes by LASSO regression. The ROC curves of 3, 5 and 10 years were 0.685, 0.726 and 0.741, respectively. The specificity for 3, 5 and 10 years were 0.598, 0.631 and 0.833, the sensitivity were 0.707, 0.752 and 0.811, respectively. Conclusions: Multivariable Cox regression analysis revealed that the risk score is an independent prognostic marker and can be used to predict the clinical and pathological features of CC.
Patients’ treatment limitations as predictive factor for mortality in COVID-19: Results from hospitalized patients of a hotspot region for SARS-CoV-2 infections
Authors: Budweiser Stephan , Bas Sevki , Jörres Rudolf , Engelhardt Sebastian , Delius Stefan von , Deerberg Jens , Bauer Andreas , Lenherr Katharina 
Published: November 2020

Abstract
Background: In hospitalized patients with SARS-CoV-2 infection, outcomes markedly differ between locations, regions and countries. For this, patients’ treatment limitations (PTL) could be of major relevance. We thus studied their role as predictor for mortality in a population of hospitalized patients with COVID-19.Methods: In a region with high incidence of SARS-CoV-2 infection, adult hospitalized patients with PCR-confirmed SARS-CoV-2 infection were prospectively registered and characterized regarding sex, age, vital signs, symptoms, comorbidities (including Charlson Comorbidity Index (CCI)), transcutaneous pulse oximetry (SpO2) and laboratory values upon admission, as well as ICU-stay including respiratory support, discharge, transfer to another hospital and death. PTL assessed by routine clinical procedures comprised the acceptance of ICU-therapy, orotracheal intubation and/or cardiopulmonary resuscitation.Results: Among 526 patients included (median [quartiles] age 73 [57; 82] years, 47% female), 226 (43%) had at least one treatment limitation. Each limitation was associated with age, dementia and eGFR (p<0.05 each), that regarding resuscitation additionally with Charlson comorbidity index (CCI) and cardiac disease. Overall mortality was 27% and lower (p<0.001) in patients without treatment limitation (12%) compared to those with any limitation (47%). In univariate analyses, age and comorbidities (diabetes, cardiac, cerebrovascular, renal, hepatic, malignant disease, dementia), SpO2, hemoglobin, leucocyte numbers, estimated glomerular filtration rate (eGFR), C-reactive protein (CRP), Interleukin-6 and LDH were predictive for death (p<0.05 each). In multivariate analyses, the presence of any treatment limitation was an independent predictor of death (OR 4.34, 95%-CI 2.10-12.30; p=0.001), in addition to CCI, eGFR <55 ml/min, neutrophil number >5 G/l, CRP >7 mg/l and SpO2 <93% (p<0.05 each).Conclusion: In hospitalized patients with SARS-CoV-2, the percentage of patients with treatment limitations was high. PTL were linked to age, comorbidities and eGFR assessed upon admission and strong, independent risk factors for mortality. These findings might be useful for further understanding of COVID-19 mortality and its regional variations.