bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of epidural analgesia on cancer prognosis after colon cancer resection: a single-centre cohort study in Taiwan
Authors: Wu Hsiang-Ling , Tai Ying-Hsuan , Mandell Mercedes Susan , Tsou Mei-Yung , Yang Shung-Haur , Chen Tony Hsiu-Hsi , Chang Kuang-Yi 
Published: October 2020

ObjectivesWhether epidural analgesia affects cancer outcomes remains controversial. Most previous investigations ignored the confounding potential of important pathological factors on cancer outcomes. This study aimed to assess the association between epidural analgesia and cancer recurrence or death after resections for colon cancer.DesignRetrospective cohort study.SettingA single-medical centre in Taiwan.ParticipantsPatients with stage I through III colon cancer undergoing bowel resection and receiving either epidural analgesia or intravenous opioid analgesia from 2005 to 2014.Primary and secondary outcome measuresPrimary outcome was postoperative recurrence-free survival and secondary outcome was overall survival.ResultsA total of 2748 and 1218 patients were analysed before and after propensity score matching. Cox regression analyses did not demonstrate any association between epidural analgesia and recurrence or death after matching (HR 0.89, 95% CI 0.65 to 1.21 for recurrence; 0.72, 95% CI 0.48 to 1.09 for death). Independent prognostic factors for cancer recurrence and death were higher level of preoperative carcinoembryonic antigen, perioperative blood transfusion, advanced cancer stage and pathological lymphovascular invasion.ConclusionsNo definite association was found between epidural analgesia and risk of recurrence or death in patients undergoing colon cancer resection.
Development and internal validation of prognostic models to predict negative health outcomes in older patients with multimorbidity and polypharmacy in general practice
Authors: Müller Beate S , Uhlmann Lorenz , Ihle Peter , Stock Christian , von Buedingen Fiona , Beyer Martin , Gerlach Ferdinand M , Perera Rafael , Valderas Jose Maria , Glasziou Paul , van den Akker Marjan , Muth Christiane 
Published: October 2020

BackgroundPolypharmacy interventions are resource-intensive and should be targeted to those at risk of negative health outcomes. Our aim was to develop and internally validate prognostic models to predict health-related quality of life (HRQoL) and the combined outcome of falls, hospitalisation, institutionalisation and nursing care needs, in older patients with multimorbidity and polypharmacy in general practices.MethodsDesign: two independent data sets, one comprising health insurance claims data (n=592 456), the other data from the PRIoritising MUltimedication in Multimorbidity (PRIMUM) cluster randomised controlled trial (n=502).Population: ≥60 years, ≥5 drugs, ≥3 chronic diseases, excluding dementia.Outcomes: combined outcome of falls, hospitalisation, institutionalisation and nursing care needs (after 6, 9 and 24 months) (claims data); and HRQoL (after 6 and 9 months) (trial data).Predictor variables in both data sets: age, sex, morbidity-related variables (disease count), medication-related variables (European Union-Potentially Inappropriate Medication list (EU-PIM list)) and health service utilisation.Predictor variables exclusively in trial data: additional socio-demographics, morbidity-related variables (Cumulative Illness Rating Scale, depression), Medication Appropriateness Index (MAI), lifestyle, functional status and HRQoL (EuroQol EQ-5D-3L).Analysis: mixed regression models, combined with stepwise variable selection, 10-fold cross validation and sensitivity analyses.ResultsMost important predictors of EQ-5D-3L at 6 months in best model (Nagelkerke’s R² 0.507) were depressive symptoms (−2.73 (95% CI: −3.56 to −1.91)), MAI (−0.39 (95% CI: −0.7 to −0.08)), baseline EQ-5D-3L (0.55 (95% CI: 0.47 to 0.64)). Models based on claims data and those predicting long-term outcomes based on both data sets produced low R² values. In claims data-based model with highest explanatory power (R²=0.16), previous falls/fall-related injuries, previous hospitalisations, age, number of involved physicians and disease count were most important predictor variables.ConclusionsBest trial data-based model predicted HRQoL after 6 months well and included parameters of well-being not found in claims. Performance of claims data-based models and models predicting long-term outcomes was relatively weak. For generalisability, future studies should refit models by considering parameters representing well-being and functional status.
Impact of non-pharmaceutical interventions for reducing transmission of COVID-19: a systematic review and meta-analysis protocol
Authors: Regmi Krishna , Lwin Cho Mar 
Published: October 2020

IntroductionImplementing non-pharmaceutical interventions (NPIs) protect the public from COVID-19. However, the impact of NPIs has been inconsistent and remains unclear. This study, therefore, aims to measure the impact of major NPIs (social distancing, social isolation and quarantine) on reducing COVID-19 transmission.Methods and analysisWe will conduct a systematic review and meta-analysis research of both randomised and non-randomised controlled trials. We will undertake a systematic search of: MEDLINE, Embase, Allied & Complementary Medicine, COVID-19 Research, WHO database on COVID-19, ClinicalTrails.Gov for clinical trials on COVID-19, Cochrane Resources on Coronavirus (COVID-19), Oxford COVID-19 Evidence Service and Google Scholar for published and unpublished literatures on COVID-19 including preprint engines such as medRxiv, bioRxiv, Litcovid and SSRN for unpublished studies on COVID-19 and will be reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Outcomes of interest for impact analysis will include the reduction of COVID-19 transmission, avoiding crowds and restricting movement, isolating ill and psychological impacts. The Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols checklist has been used for this protocol. For quality of included studies, we will use the Cochrane Collaboration’s tool for assessing risk of bias for randomised controlled trials and the Newcastle-Ottawa Scale for observational studies. The Grading of Recommendations Assessment, Development and Evaluation approach will grade the certainty of the evidence for all outcome measures across studies. Random-effects model for meta-analysis will measure the effect size of NPIs or the strengths of relationships. For quantitative data, risk ratio or OR, absolute risk difference (for dichotomous outcome data), or mean difference or standardised mean difference (for continuous data) and their 95% CIs will be calculated. Where statistical pooling is not possible, a narrative synthesis will be conducted for the included studies. To assess the heterogeneity of effects, I2together with the observed effects will be evaluated to provide the true effects in the analysis.Ethics and disseminationFormal ethical approval from an institutional review board or research ethics committee is not required as primary data will not be collected. The final results of this study will be published in an open-access peer-reviewed journal, and abstract will be presented at suitable national/international conferences or workshops. We will also share important information with public health authorities as well as with the WHO. In addition, we may post the submitted manuscript under review to medRxiv, or other relevant preprint servers.Trial registration numberCRD42020207338.
Swallowing dysfunction after minimally invasive oesophagectomy
Authors: Mann Della , Benbow Jennifer H , Gower Nicole L , Trufan Sally , Watson Michael , Colcord Madison E , Squires Malcolm H , Raj Vishwa S , Hill Joshua S , Salo Jonathan C 
Published: October 2020

ObjectivesPatients undergoing oesophagectomy frequently experience malnutrition, which in combination with the catabolic effects of surgery can result in loss of muscle mass and function. Safe swallowing requires preservation of muscle mass. Swallowing dysfunction puts postoperative patients at risk for aspiration and pneumonia. Modified Barium Swallow Study (MBSS) enables assessment of postoperative swallowing impairments. The current study assessed incidence and risk factors associated with swallowing dysfunction and restricted diet at discharge in patients after oesophagectomy in a high-volume surgical centre.MethodsPatients with an MBSS after oesophagectomy were identified between March 2015 to April 2020 at a high-volume surgical centre. Swallowing was quantitatively evaluated on MBSS with the Rosenbek Penetration-Aspiration Scale (PAS). Muscle loss was evaluated clinically with preoperative hand grip strength (HGS). Univariable and multivariable logistic and linear regression analyses were performed.Results129 patients (87% male; median age 66 years) underwent oesophagectomy with postoperative MBSS. Univariate analysis revealed older age, preoperative feeding tube, lower preoperative HGS and discharge to non-home were associated with aspiration or penetration on MBSS. Age and preoperative feeding tube remained as independent predictors in the multivariable analysis. Both univariate and multivariable analyses revealed increased age and preoperative feeding tube were associated with diet restrictions at discharge.ConclusionsSwallowing dysfunction after oesophagectomy is correlated with increased age and need for preoperative enteral feeding tube placement. Further research is needed to understand the relationship between muscle loss and aspiration with the goal of enabling preoperative physiological optimisation and patient selection.
Collinear electroweak radiation in antenna parton showers
Authors: Kleiss Ronald , Verheyen Rob 
Published: October 2020

AbstractWe present a first implementation of collinear electroweak radiation in the Vincia parton shower. Due to the chiral nature of the electroweak theory, explicit spin dependence in the shower algorithm is required. We thus use the spinor-helicity formalism to compute helicity-dependent branching kernels, taking special care to deal with the gauge relics that may appear in computation that involve longitudinal polarizations of the massive electroweak vector bosons. These kernels are used to construct a shower algorithm that includes all possible collinear final-state electroweak branchings, including those induced by the Yang–Mills triple vector boson coupling and all Higgs couplings, as well as vector boson emissions from the initial state. We incorporate a treatment of features particular to the electroweak theory, such as the effects of bosonic interference and recoiler effects, as well as a preliminary description of the overlap between electroweak branchings and resonance decays. Some qualifying results on electroweak branching spectra at high energies, as well as effects on LHC physics are presented. Possible future improvements are discussed, including treatment of soft and spin effects, as well as issues unique to the electroweak sector.
Surface tension and heat of the surface formation of liquids
Authors: Eyvazov E. A. , Ibrahimli A. B. 
Published: October 2020

By the potential method, it was determined that regardless of the nature of the liquid, the surface tension coefficient is determined by [Formula: see text]. In this expression, [Formula: see text] is the specific heat of the surface formation, [Formula: see text] is the critical temperature. According to our approach, the specific heat of the surface formation (SHS) also depends on temperature: [Formula: see text] ([Formula: see text] — the specific heat of the surface formation at the mealting temperature, [Formula: see text] — thermal coefficent of SHS). In this research work, the temperature dependence of the surface tension coefficient was calculated for seven dissimilar liquids. It was revealed that the calculated values of [Formula: see text] are in satisfactory agreement with the available experimental values.
Will post COVID-19 education be digital?
Authors: Delic Kemal A. , Riley Jeff A. 
Published: October 2020

The world is experiencing large-scale social and behavioral changes in response to the COVID-19 pandemic. These changes have the potential to cause a fundamental and profound shift in the way we conduct our lives, which could have both positive and negative consequences.
The need to function, both socially and at work, while sheltering at home and social distancing has led to the widespread realization that online meetings and remote working is viable. Digital education is particularly important, as millions of pupils and students worldwide struggle to continue studies in these difficult circumstances.
We have posed four questions to our fellow Ubiquity editors, garnering a balanced view from academia and industry, from STEM and business (MBA) perspective, aiming to seed a follow-up debate from other editors, culminating in a free, one-hour webinar.
Tumor Fibroblast–Derived FGF2 Regulates Expression of SPRY1 in Esophageal Tumor–Infiltrating T Cells and Plays a Role in T-cell Exhaustion
Authors: Chen Qing-yun , Li Yi-ni , Wang Xin-yue , Zhang Xu , Hu Yi , Li Lei , Suo Da-qin , Ni Ke , Li Zhuo , Zhan Jia-rong , Zeng Ting-ting , Zhu Ying-hui , Li Yan , Ma Li-jia , Guan Xin-Yuan 
Published: October 2020

Abstract

T-cell exhaustion was initially identified in chronic infection in mice and was subsequently described in humans with cancer. Although the distinct signature of exhausted T (TEX) cells in cancer has been well investigated, the molecular mechanism of T-cell exhaustion in cancer is not fully understood. Using single-cell RNA sequencing, we report here that TEX cells in esophageal cancer are more heterogeneous than previously clarified. Sprouty RTK signaling antagonist 1 (SPRY1) was notably enriched in two subsets of exhausted CD8+ T cells. When overexpressed, SPRY1 impaired T-cell activation by interacting with CBL, a negative regulator of ZAP-70 tyrosine phosphorylation. Data from the Tumor Immune Estimation Resource revealed a strong correlation between FGF2 and SPRY1 expression in esophageal cancer. High expression of FGF2 was evident in fibroblasts from esophageal cancer tissue and correlated with poor overall survival. In vitro administration of FGF2 significantly upregulated expression of SPRY1 in CD8+ T cells and attenuated T-cell receptor–triggered CD8+ T-cell activation. A mouse tumor model confirmed that overexpression of FGF2 in fibroblasts significantly upregulated SPRY1 expression in TEX cells, impaired T-cell cytotoxic activity, and promoted tumor growth. Thus, these findings identify FGF2 as an important regulator of SPRY1 expression involved in establishing the dysfunctional state of CD8+ T cells in esophageal cancer.

Significance:
These findings reveal FGF2 as an important regulator of SPRY1 expression involved in establishing the dysfunctional state of CD8+ T cells and suggest that inhibition of FGF2 has potential clinical value in ESCC.
Defining an Upstream VEGF (Vascular Endothelial Growth Factor) Priming Signature for Downstream Factor-Induced Endothelial Cell-Pericyte Tube Network Coassembly
Authors: Bowers Stephanie L.K. , Kemp Scott S. , Aguera Kalia N. , Koller Gretchen M. , Forgy Joshua C. , Davis George E. 
Published: October 2020

Objective:
In this work, we have sought to define growth factor requirements and the signaling basis for different stages of human vascular morphogenesis and maturation.

Approach and Results:
Using a serum-free model of endothelial cell (EC) tube morphogenesis in 3-dimensional collagen matrices that depends on a 5 growth factor combination, SCF (stem cell factor), IL (interleukin)-3, SDF (stromal-derived factor)-1α, FGF (fibroblast growth factor)-2, and insulin (factors), we demonstrate that VEGF (vascular endothelial growth factor) pretreatment of ECs for 8 hours (ie, VEGF priming) leads to marked increases in the EC response to the factors which includes; EC tip cells, EC tubulogenesis, pericyte recruitment and proliferation, and basement membrane deposition. VEGF priming requires VEGFR2, and the effect of VEGFR2 is selective to the priming response and does not affect factor-dependent tubulogenesis in the absence of priming. Key molecule and signaling requirements for VEGF priming include RhoA, Rock1 (Rho-kinase), PKCα (protein kinase C α), and PKD2 (protein kinase D2). siRNA suppression or pharmacological blockade of these molecules and signaling pathways interfere with the ability of VEGF to act as an upstream primer of downstream factor-dependent EC tube formation as well as pericyte recruitment. VEGF priming was also associated with the formation of actin stress fibers, activation of focal adhesion components, upregulation of the EC factor receptors, c-Kit, IL-3Rα, and CXCR4 (C-X-C chemokine receptor type 4), and upregulation of EC-derived PDGF (platelet-derived growth factor)-BB, PDGF-DD, and HB-EGF (heparin-binding epidermal growth factor) which collectively affect pericyte recruitment and proliferation.

Conclusions:
Overall, this study defines a signaling signature for a separable upstream VEGF priming step, which can activate ECs to respond to downstream factors that are necessary to form branching tube networks with associated mural cells.
Use of Cardiac Noninvasive Testing After Emergency Department Discharge: Association of Hospital Network Testing Intensity and Outcomes in Ontario, Canada
Authors: Roifman Idan , Han Lu , Koh Maria , Wijeysundera Harindra C. , Austin Peter C. , Douglas Pamela S. , Ko Dennis T. 
Published: October 2020

Background
The relationship between noninvasive cardiac diagnostic testing intensity and downstream clinical outcomes is unclear. Our objective was to examine the relationship between hospital network noninvasive cardiac diagnostic testing intensity and downstream clinical outcomes in patients who were discharged from the emergency department after assessment for chest pain.

Methods and Results
We employed a retrospective cohort study design of 387 809 patients evaluated for chest pain in the emergency department between April 1, 2010 and March 31, 2016. Hospital networks were divided into tertiles based on usage of noninvasive cardiac diagnostic testing. The primary outcome was a composite of acute myocardial infarction or all‐cause mortality. Adjusted Cox proportional hazards models were used to compare the hazard of the composite outcome of myocardical infarction and/or all‐cause mortality between the tertiles. After adjustment for clinically relevant covariates, patients evaluated for chest pain in intermediate noninvasive cardiac diagnostic testing usage tertile hospital networks did not have significantly different hazards of the composite outcome when compared with those evaluated in low usage tertile hospital networks >90 days (hazard ratio [HR], 1.00; 95% CI, 0.83–1.21), 6 months (HR, 1.07; 95% CI, 0.92–1.24), and 1 year (HR, 1.03; 95% CI, 0.94–1.14). Patients evaluated in the high usage tertile also did not have significantly different hazards of the composite outcome compared with those evaluated in the low usage tertile at 90 days (HR, 0.98; 95% CI, 0.80–1.19), 6 months (HR, 1.01; 95% CI, 0.87–1.17); and 1 year (HR, 0.95; 95% CI, 0.86–1.05).

Conclusions
Our population‐based study demonstrated that high noninvasive cardiac diagnostic testing use intensity was not associated with reductions in downstream myocardial infarction or all‐cause mortality.
Assessing Predictive Potential Associated with the MJO during the Boreal Winter
Authors: Kumar Arun , Zhu Jieshun , Wang Wanqiu 
Published: October 2020

AbstractIn this paper, the question of potential predictability in meteorological variables associated with skillful prediction of the Madden–Julian oscillation (MJO) during boreal winter is analyzed. The analysis is motivated by the fact that dynamical prediction systems are now capable of predicting MJO up to 30 days or earlier (measured in terms of anomaly correlation for RMM indices). Translating recent gains in MJO prediction skill and relating them back to potential for predicting meteorological variables—for example, precipitation and surface temperature—is not straightforward because of a chain of steps that go into the computation and evaluation of RMM indices. This paper assesses potential predictability in meteorological variables that could be attributed to skillful prediction of the MJO. The analysis is based on the observational data alone and assesses the upper limit of MJO-associated predictability that could be achieved.
A Deep-Learning Model for Automated Detection of Intense Midlatitude Convection Using Geostationary Satellite Images
Authors: Cintineo John L. , Pavolonis Michael J. , Sieglaff Justin M. , Wimmers Anthony , Brunner Jason , Bellon Willard 
Published: October 2020

AbstractIntense thunderstorms threaten life and property, impact aviation, and are a challenging forecast problem, particularly without precipitation-sensing radar data. Trained forecasters often look for features in geostationary satellite images such as rapid cloud growth, strong and persistent overshooting tops, U- or V-shaped patterns in storm-top temperature (and associated above-anvil cirrus plumes), thermal couplets, intricate texturing in cloud albedo (e.g., “bubbling” cloud tops), cloud-top divergence, spatial and temporal trends in lightning, and other nuances to identify intense thunderstorms. In this paper, a machine-learning algorithm was employed to automatically learn and extract salient features and patterns in geostationary satellite data for the prediction of intense convection. Namely, a convolutional neural network (CNN) was trained on 0.64-μm reflectance and 10.35-μm brightness temperature from the Advanced Baseline Imager (ABI) and flash-extent density (FED) from the Geostationary Lightning Mapper (GLM) on board GOES-16. Using a training dataset consisting of over 220 000 human-labeled satellite images, the CNN learned pertinent features that are known to be associated with intense convection and skillfully discriminated between intense and ordinary convection. The CNN also learned a more nuanced feature associated with intense convection—strong infrared brightness temperature gradients near cloud edges in the vicinity of the main updraft. A successive-permutation test ranked the most important predictors as follows: 1) ABI 10.35-μm brightness temperature, 2) ABI GLM flash-extent density, and 3) ABI 0.64-μm reflectance. The CNN model can provide forecasters with quantitative information that often foreshadows the occurrence of severe weather, day or night, over the full range of instrument-scan modes.