bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bridging Adsorption Analytics and Catalytic Kinetics for Metal-Exchanged Zeolites
Authors: Xie Pengfei , Pu Tiancheng , Aranovich Gregory , Guo Jiawei , Donohue Marc , Kulkarni Ambarish , Wang Chao 
Published: September 2020

Abstract
Metal-exchanged zeolites have been widely used in industrial catalysis and separation, but fundamental understanding of their structure-property relationships has remained challenging, largely due to the lack of quantitative information concerning the atomic structures and reaction-relevant adsorption properties of the embedded metal active sites. We report on the use of low-temperature chemisorption to titrate Cu-exchanged ZSM5. Quantitative descriptors of the atomic structures and adsorption properties of Cu-ZSM5 are established by combining atomistic simulation, DFT calculations, operando molecular spectroscopy, chemisorption and titration measurements. These descriptors are then applied to interpret the catalytic performance of Cu-ZSM5 for NO decomposition. Linear correlations are established to bridge the low-temperature adsorption analytics and high-temperature reaction kinetics, which are demonstrated to be generally applicable for understanding the structure-property relationships of metal exchanged zeolites and foregrounded for guiding the development of advanced catalytic materials.
Post-treatment work patterns amongst survivors of lymphoma treated with high-dose chemotherapy with autologous stem-cell transplantation
Authors: Hernaes Kjersti Helene , Smeland Knut Halvor Bjøro , Fagerli Unn Merete , Kiserud Cecilie Essholt 
Published: September 2020

Abstract
BackgroundThis study describes post-treatment work patterns in lymphoma survivors treated with high-dose chemotherapy with autologous stem-cell transplantation (HDT-ASCT). It aims to identify determinants for labour force participation and exclusion after HDT-ASCT.MethodsEligible patients were survivors of HDT-ASCT for lymphoma in Norway between 1995 and 2008, aged >= 18 years at HDT-ASCT. We divide survivors by current employment status (working (full vs. part-time) and unemployed). Main outcomes are current employment status, work hours and work ability. Withdrawals are patients who were employed when diagnosed but not before HDT-ASCT.ResultsOf the 274 who completed the survey, 82% (N=225) were included in the final analyses. Mean age at survey was 52 years, 39% were female, 85% were employed when diagnosed, 77% before HDT-ASCT and 69% at survey. Employment before HDT-ASCT corresponds with a higher probability of employment at survey for a given symptom burden. In the most extensive statistical model, it increases with 37.3 percentage points. Work hours amongst withdrawals plummet after HDT-ASCT while work ability shows a rebound effect. The potential economic gain from their re-enter into the work force equals 2/3 of the average annual wage in Norway in 2012.ConclusionsFor a given symptom burden, staying employed throughout diagnosis and treatment is associated with a higher probability of future employment. These results favour policies for labour force inclusion past diagnosis and treatment increasing cancer survivors’ probability of future employment. However, we need more research on withdrawal mechanisms, and on policy measures that promote inclusion.
The physicochemical and phylogenetic properties of twelve spike glycoprotein models for SARS-CoV-2 from China, Iran, and Tunisia
Authors: Odhaib Samih A. , Al-Aubaidy Hayder 
Published: September 2020

Abstract
Background

The coronavirus spike glycoprotein is a trimeric structural surface protein that facilitates the viral adhesion through attaching receptors on the human cell surface. This study aims to analyse and compare the genomic and phylogenetic properties of these spike glycoproteins from China, Iran, and Tunisia.
Methods

This is a descriptive cross-sectional comparative study for the different properties of S glycoprotein from 12 SARS-CoV-2 specimens from GenBank. Clustal Omega was used to study model sequences alignment, residual conservation, phylogeny, and identity matrix. SWISS-MODEL developed and validated the 3D models for three protein sequences with the highest model quality. The different physicochemical characteristics of different models were assessed by ExPASy proteomics.
Results

The Chinese and the Iranian sequences share 100% identity, although they have a different amino acids number, and 25-29.27% identity to the Tunisian sequences. The 12 models are monophyletic, with varying stages of evolutionary divergence. There are six fully, three highly, and five lowly conserved residues across the sequences. The resulting three highly reliable 3D models were of different global qualities, being the lowest for the Tunisian, and the highest for the Iranian models. All the models are highly hydrophilic. The Tunisian models were unstable in comparison to the relatively stable other models with different physicochemical characteristics.
Conclusion

The models had different N-terminal residues and side groups polarity and charge. The S glycoproteins are not identical nor unique in model structure nor the physicochemical profiles in different parts of the world. The Tunisian models are drastically biodiverse from the Chinese and Iranian models.
Metabolic and Behavioral Features of Acute Hyperpurinergia and the Connection to Autism Spectrum Disorder
Authors: Zolkipli-Cunningham Zarazuela , Naviaux Jane C. , Nakayama Tomohiro , Hirsch Charlotte M. , Monk Jonathan M. , Li Kefeng , Wang Lin , Le Thuy P. , Meinardi Simone , Blake Donald , Naviaux Robert K. 
Published: September 2020

Abstract
Background. Since 2012, studies in mice, rats, and humans have suggested that abnormalities in purinergic signaling may be a final common pathway for many genetic and environmental causes of autism spectrum disorder (ASD). The current study in mice was conducted to characterize the bioenergetic, metabolomic, breathomic, and behavioral features of acute hyperpurinergia triggered by systemic injection of the purinergic agonist and danger signal, extracellular ATP (eATP). Methods. Responses were studied in C57BL/6J mice with ASD-like behaviors in the maternal immune activation (MIA) model and controls. Basal metabolic rates, respiratory exchange ratios (RER = VCO2/VO2), and locomotor activity were measured in CLAMS cages. Plasma metabolomics measured 401 metabolites. Breathomics measured 98 volatile organic compounds. Results. A 0.5 µmol/g dose of ATP dropped whole body oxygen consumption by 74% ± 6% (mean ± SEM, 5,303 to 1,382 ml/kg/hr, p<0.0001) and rectal temperature by 6.2˚ ± 0.3˚C (p<0.0001) in 30 minutes. Over 200 metabolites from 37 different biochemical pathways where changed. MIA animals were hypersensitive to the metabolic and behavioral responses triggered by eATP and poly(IC). Breathomic and metabolomic analysis revealed changes in folate-methylation-1-carbon, purines, pyrimidines, acyl-carnitines, glycolysis, aromatic and branch-chain amino acids, Krebs cycle, glutathione, urea cycle, phospholipids, sphingolipids, eicosanoids, cholesterol, bile acids, vitamins, and microbiome metabolism similar to children with ASD. Limitations. The responses to ATP were studied in only a single genetic strain of mice (C57BL/6J). Although similar to metabolic results reported in FVB mice and a small clinical trial in children with ASD, the generalizability of these results to larger studies in humans is unknown. The chronic effects of repeated postnatal ATP exposures were not tested. Conclusions. Acute hyperpurinergia produced metabolic and behavioral changes in mice that were similar to those found in children with ASD. These behaviors and metabolic changes were associated with mitochondrial functional changes that were profound but reversible.
Ocular abnormalities in a large Western China patient cohort with Retinitis Pigmentosa
Authors: Tan Lian , Long Yanling , Li Ziyang , Ying Xi , Ren Jiayun , Sun Cheng , Meng Xiaohong , Li Shiying 
Published: September 2020

Abstract
Background: To report the prevalence of ocular abnormalities and investigate visual acuity in a large Western China cohort of retinitis pigmentosa (RP) patients.Methods: A retrospective study was performed, reviewing the medical records and ophthalmic examination reports of 2,127 eyes from 1,065 RP patients in one eye hospital. The authors investigated the prevalence of ocular abnormalities and the relationship between best corrected visual acuity (BCVA) and macular abnormalities.Results: Nyctalopia (58.2%) and blurred vision (27.1%) were the leading consultation causes. BCVA measurements in the better eyes at first clinical presentation showed that 304 patients (28.5%) were categorised as blind and 220 patients (20.7%) as low vision. The most common ocular abnormalities were cataracts (43.1%) and macular abnormalities (59.7%), including epiretinal membranes (51.1%), cystoid macular oedema (18.4%), vitreomacular traction syndrome (2.4%), macular holes (2.3%) and choroidal neovascular membranes (0.05%). Glaucoma was found in 35 eyes (1.6%). The proportions of epiretinal membranes (P = 0.001) and macular holes (P = 0.008) increased significantly with age. The proportions of vitreomacular traction syndrome (P = 0.003) and epiretinal membranes (P < 0.001) in pseudophakia and aphakia eyes were significantly higher than in eyes that had not received operations (including cataracts and clear lens). Cystoid macular oedema was significantly associated with poorer visual acuity in RP patients with clear lens (P = 0.002).Conclusion: Cataracts and macular abnormalities are common in RP patients. In the macular abnormalities, cystoid macular oedema may have a negative effect on BCVA in RP patients with clear lens.
A Novel “Three-Port” Trocar Placement Technique for Laparoscopic Radical Prostatectomy
Authors: Xu Ben , Song Hai-feng , Luo Cheng , Zhang Qian 
Published: September 2020

Abstract
Background: To introduce a novel “three-port” trocar placement technique for laparoscopic radical prostatectomy (LRP) in prostate cancer (PCa) patients.Methods: We retrospectively reviewed 300 patients with PCa who received surgical treatment between November 2010 and June 2015 at our institution. They were divided into group A: three-port LRP, group B: conventional four-five port LRP, group C: open RP (ORP) and group D: robotic-assisted RP (RARP). A learning curve was analyzed by dividing patients of group A into the early and late stages.Results: All groups were comparable with regard to the preoperative characteristics except for the relatively smaller prostate volume in group A. The three-port LRP operations were performed successfully with only 8 cases conversion to the conventional LRP. None of any severe complications or conversion to ORP occurred. In group A, the mean operative time (OT) duration was 113.8 min, the mean estimated blood loss (EBL) was 94.2 ml, the mean drainage days was 4.0d, the mean hospitalization was 5.1 d, and 27.8% of the prostate specimen margins (PSM) were positive. The differences of OT, EBL, drainage days, hospitalization and transfusion in group A were statistically significant among the majority of the other groups (p<0.05). After undergoing the early stages of a learning curve analysis in three-port LRP, the EBL was obviously decreased.Conclusions: Three-port LRP is a novel technique that exhibits superior intraoperative advantages to the conventional LRP. Due to its less OT, EBL, drainage days, hospitalization and transfusion with a shorter learning curve, it should be recommended and popularized in the clinical practice!
Career-computer simulation increases perceived importance of learning about rare diseases
Authors: Sarrafpour Babak , Hegde Shwetha , Delamare Eduardo , Weeks Ruth , Denham Rebecca A , Thoeming Alix , Zoellner Hans 
Published: September 2020

Abstract
Background
Rare diseases may be defined as occurring in less than 1 in 2,000 patients. Such conditions are, however, so numerous that up to 5.9% of the population is afflicted by a rare disease. The gambling industry attests that few people have native skill evaluating probabilities. We believe that both students and academics, under-estimate the likelihood of encountering rare diseases. This combines with pressure on curriculum time, to reduce both student interest in studying rare diseases, and academic content preparing students for clinical practice. Underestimation of rare diseases, may also contribute to unhelpful blindness to considering such conditions in the clinic.
Methods
We first developed a computer simulation, modelling the number of cases of increasingly rare conditions encountered by a cohort of clinicians. The simulation captured results for each year of practice, for each clinician throughout the entirety of their careers. 462 theoretical conditions were considered, with prevalence ranging from 1 per million people through to 64.1% of the population. We then delivered a class with two in-class on-line surveys evaluating student perception of the importance of learning about rare diseases, one before and the other after, an in-class real-time computer simulation. Key simulation variables were drawn from the student group, so students could see a projection of their own careers.
Results
The in-class computer simulation revealed that all graduating clinicians from that class would frequently encounter rare conditions. Comparison of results of the in-class survey conducted before and after the computer simulation, revealed a significant increase in the perceived importance of learning about rare diseases (p < 0.005).
Conclusions
The computer career simulation appeared to affect student perception. Because the computer simulation demonstrated clinicians frequently encounter patients with rare diseases, we further suggest this should be considered by academics during curriculum review and design.
Dynamic Prognosis Model for Predicting Survival in Severe and Critically Ill COVID-19 Patients Using Machine Learning
Authors: Wei Yongyue , He Jieyu , Chen Jiao , Zhu Ying , Chen Jiajin , Ding Jingjing , Wang Hao , Hu Yahua , Huang Yingzi , Jiang Yue , Pan Zoucheng , Shen Sipeng , Zhao Wei , Gao Wei , Chen Feng , Lu Xiang 
Published: September 2020

Abstract
Background Novel coronavirus disease (COVID-19) is an emerging, rapidly evolving situation. At present, the prognosis of severe and critically ill patients has become an important focus of attention. We strived to develop a prognostic prediction model for severe and critically ill COVID-19 patients.MethodsTo assess the factors associated with the prognosis of those patients, we retrospectively investigated the clinical, laboratory characteristics of confirmed 112 cases of COVID-19 admitted between 21 January to 6 March 2020 from Huangshi Central Hospital, Huangshi Hospital of Traditional Chinese Medicine, and Daye People’s Hospital. We applied machine learning method (survival random forest) to select predictors for 28-day survival and taken into account the dynamic trajectory of laboratory indicators. Results Fifteen candidate prognostic features, including 11 baseline measures (including platelet count (PLT), urea, creatine kinase (CK), fibrinogen, creatine kinase isoenzyme activity, aspartate aminotransferase (AST), activation of partial thromboplastin time (APTT), albumin, standard deviation of erythrocyte distribution width (RBC-SD), neutrophils (%) and red blood cell count (RBC)) and 4 trajectory clusters (changes during hospitalization in the white blood cell (WBC), PLT large cell ratio (P-LCR), PLT distribution width (PDW) and AST), combined with covariates achieved 100% (95%CI: 99%-100%) AUC and reached 87% (95%CI: 84%-91%) AUC in an external validation set. Conclusions Taking advantage of random forest technique and laboratory dynamic measures, we developed a forest model to predict survival outcome of COVID-19 patients, which achieved 87% AUC in the external validation set. Our online tool will help to facilitate the early recognition of patients with high risk.
The Value of Neutrophil/monocyte Ratio in Early Diagnosis of Children Mycoplasma Pneumoniae Pneumonia
Authors: Yao Shasha , Xie Yao , Chen Fei , Chen Xiao , Zhang Miao , Li Yan 
Published: September 2020

Abstract
Background:To investigate the value of blood cell analysis in early diagnosis of mycoplasma pneumoniae pneumonia (MP). Methods:The clinical parameters, including patient characteristics, clinical symptoms, imaging characteristics and laboratory examination data of the patients hospitalized in the Department of Pediatrics, Nanjing Jiangning Hospital from January 2018 to March 2020 due to community-acquired pneumonia were collected for retrospective analysis. The data were analyzed by SPSS 22.0 software for statistical analysis. P<0.05 was considered statistically significant.Results:The levels of white blood cell count (WBC), absolute neutrophil count (NEU), absolute monocyte count (MON), platelet count (PLT), neutrophil/lymphocyte ratio(NLR), mean platelet volume/platelet count (MPV/PLT) and neutrophil/monocyte ratio (NMR) in children with bacterial pneumonia (BP)were significantly higher than those of children withMP and children withviral pneumonia (VP), the NMR level in children withMP was higher than that of children with VP,the NMR levelsin the three groups of children were significantly different (P<0.05).Combined with the NMR level, the children’s age andpulmonary consolidation information,the AUC areas of MP, BP and VP had high accuracy fordifferential diagnosis of MP. Conclusion:As a comprehensive indicator of neutrophils and monocytes, NMR may differentiate pneumonia caused by mycoplasma pneumoniae, bacterial and viral infections, which provides new direction for early differential diagnosis of pneumonia.
Bursty Topic Detection in Cancer Field Based on Multi-features of Burst Words
Authors: gong xiaocui , an xinying , shan lianhui , hao yingxin , li yifei 
Published: September 2020

Abstract
Background:With the increase in the amounts and types of medical information resources and the interdisciplinarity of the related works,it has become increasingly challenging for researchers and information personnel to grasp the theme development.Considering the prominent position of cancer field among all the subject areas in scientific research, and in order to carry out a new bursty topic detection method, the author proposes a method based on the multi-features of burst words and demonstrates its operating process. Methods:The main stages in the process include concept mapping,topic words extraction,burst words extraction,burst topics identification.This paper continues to take the study of breast neoplasms treatment research as a field to test the new method for identifying burst topics in medical research. Result:With this method,we identified four burst topics in breast neoplasms treatment research, including Molecular Targeted Therapy of Triple Negative Breast Neoplasms,molecular pharmacology of Triple Negative Breast Neoplasms,Immunological Antineoplastic Agents therapeutic use of Breast Neoplasms and Surgery therapy of Breast Neoplasms. Conclusion:The test results are highly concordant with authoritative literature reviews in the field and are further confirmed by interviews with the field’s leading experts,thus verifying the reliability of the techniques and approaches proposed by the study.
Dexmedetomidine protects against burn-induced intestinal barrier injury via the MLCK/p-MLC signalling pathway
Authors: Qin Chao , Jiang Yi , Chen Xing , Bian Yingxue , Wang Yaoqi , Xie Keliang , Yu Yonghao 
Published: September 2020

Abstract
Background Dexmedetomidine, a potent α2-adrenoceptor agonist with analgesic, sedative, anti-inflammatory, and anti-apoptotic effects, is commonly used in patients with critical illness in intensive care units. Accumulating evidence indicates that dexmedetomidine can protect against intestinal dysfunction. However, the specific mechanisms of its protective effects against burn-induced intestinal barrier injury remain unclear. Here, we aimed to explore the possible positive effects of dexmedetomidine on burn-induced intestinal barrier injury and the role of the myosin light chain kinase (MLCK)/phosphorylated myosin light chain (p-MLC) signalling pathway in an experimental model of burn injury.Methods In this study, the intestinal permeability of burn-induced intestinal barrier damage was assessed by estimating the plasma concentration of 4.4 kDa fluorescein isothiocyanate-labelled dextran (FITC-dextran). Histological changes were evaluated using haematoxylin and eosin (HE) staining. Tight junction proteins were evaluated by western blot and immunofluorescence analyses to assess the structural integrity of intestinal tight junctions. The level of inflammation was determined by enzyme-linked immunosorbent assay (ELISA).Results Our findings demonstrated that the increase in intestinal permeability caused by burn injury is accompanied by histological damage to the intestine, decreases in the expression of the tight junction proteins Zonula Occludens-1 (ZO-1) and Occludin, increases in inflammatory cytokine levels and elevation of both MLCK protein expression and MLC phosphorylation. After dexmedetomidine treatment, the burn-induced changes were ameliorated.Conclusions In conclusion, dexmedetomidine exerted an anti‑inflammatory effect and protected tight junction complexes against burn‑induced intestinal barrier damage by inhibiting the MLCK/p-MLC signalling pathways, suggesting that it may be an effective drug in the treatment of burn-induced intestinal injury.Trial registration Not appliance.
Analysis of cesarean section rates using Robson Ten Group Classification System in a tertiary teaching hospital, Addis Ababa, Ethiopia: a cross-sectional study
Authors: Abubeker Ferid A. , Gashawbeza Biruck , Gebre Thomas Mekuria , Wondafrash Mekitie , Teklu Alula M. , Degu Demis , Bekele Delayehu 
Published: September 2020

Abstract
Background: Cesarean section (CS) is an important indicator of access to, and quality of maternal health services. The World Health Organization recommends the Robson ten group classification system as a global standard for assessing, monitoring and comparing CS rates at all levels. This study aimed to assess the rate of CS and perform an analysis based on Robson classification system.Methods: A facility-based cross-sectional study was conducted at a tertiary hospital in Addis Ababa, Ethiopia. Data were collected from medical charts of all women who delivered from January-June 2018. The overall CS rate was calculated then women were categorized into one of the ten Robson groups. Relative size of each group, contribution of each group to the overall CS rate, and CS rate within each group were calculated.Results: A total of 4,200 deliveries were analyzed. Of these 1,459 (34.7%) were CS. The largest contributors to the overall CS rate were Group 10 (19.1%), Group 2 (18.3%), Group 5 (17.1%), and Group 4 (15.8%). There was also a high rate of pre-labor CS in Group 2, Group 4, and Group 10.Conclusion: Through implementation of the Robson ten group classification system, we identified the contribution of each group to the overall CS rate as well as the CS rate within each group. Group 10 was the leading contributor to the overall CS rate. This study also revealed a high rate of CS among low-risk groups. These target groups require more in-depth analysis to identify possible modifiable factors and to apply specific interventions to reduce the CS rate. Evaluation of existing management protocols and further studies into indications of CS and outcomes are needed to design tailored strategies and improve outcomes.