bluuebunny/crossref_metadata_2025_split huggingface dataset:
S100A8 Promotes Inflammation via Toll-Like Receptor 4 After Experimental Traumatic Brain Injury
Authors: He Guoyuan , Han Yan-Ling , Wu Degang , Cheng Hao , Sun Le-An , Di Guangfu , Zhou Meng-Liang , Jiang Xiaochun 
Published: May 2020

Abstract
Background: S100A8 is involved in the pathological processes of a variety of central nervous system(CNS) diseases related to inflammation including traumatic brain injury (TBI). However, the underlying mechanism for the induction of inflammation in the brain by S100A8 after TBI remains unclear, which was investigated in the present study.Methods: The weight-drop TBI model was used in this study. The mice were randomly assigned into 5 groups: the Sham, S100A8, S100A8 + TAK-242, TBI, and TBI + TAK-242 groups. In the S100A8 + TAK-242 and TBI + TAK-242 groups, mice were treated with TAK-242, an inhibitor of Toll-like receptor (TLR) 4, intraperitoneally at half an hour before TBI. In the S100A8 and S100A8 + TAK-242 groups, S100A8 recombinant protein was injected into the lateral ventricle of the brain. To explore the relationship between S100A8 and TLR4, Western Blot (WB), immunofluorescence, enzyme-linked immunosorbent assay (ELISA) and Nissl staining were employed. Neurological score and the brain water content were also assessed. Additionally, BV-2 microglial cells were stimulated with lipopolysaccharide (LPS) or S100A8 recombinant protein with/without TAK-242 in vitro. The expressions of the related proteins were subsequently detected with WB or ELISA.Results: The levels of S100A8 protein and pro-inflammatory cytokines were significantly increased after TBI. After intracerebroventricular administration of S100A8, the neurological scores of non-TBI animals were decreased remarkably with severe brain edema. Furthermore, the levels of TLR4, p-p65 and myeloid differentiation factor 88(MyD88) were all increased after S100A8 administration or TBI, which could be restored by TAK-242. Meanwhile, p-p65 and MyD88 were upregulated after S100A8 or LPS stimulation in vitro, which also could be suppressed by TAK-242.Conclusions: The present study demonstrated that TLR4-MyD88 pathway was activated by S100A8, which was essential to the development of inflammation in the brain after TBI.
A Systematic Review of Patient Prioritization Tools in Non-Emergency Healthcare Services
Authors: Dery Julien , Ruiz Angel , Routhier François , Bélanger Valérie , Côté André , Ait-Kadi Daoud , Gagnon Marie-Pierre , Deslauriers Simon , Pecora Ana Tereza Lopes , Redondo Eduardo , Allaire Anne-Sophie , Lamontagne Marie-Eve 
Published: May 2020

Abstract
Background: Patient prioritization is a strategy used to manage access to healthcare services. Patient prioritization tools (PPT) contribute to supporting the prioritization decision process, and to its transparency and fairness. Patient prioritization tools can take various forms and are highly dependent on the particular context of application. Consequently, the sets of criteria change from one context to another, especially when used in non-emergency settings. This paper systematically synthesizes and analyzes the published evidence concerning the development and challenges related to the validation and implementation of PPTs in non-emergency settings. Methods: We conducted a systematic mixed studies review. We searched evidence in five databases to select articles based on eligibility criteria, and information of included articles was extracted using an extraction grid. The methodological quality of the studies was assessed by using the Mixed Methods Appraisal Tool. The article selection process, data extraction, and quality appraisal were performed by at least two reviewers independently. Results: We included 47 studies listing 33 different patient prioritization tools. Most of them are designed for managing access to elective surgeries in hospital settings. Two thirds of the tools were investigated based on reliability or validity. Inconclusive results were found regarding the impact of PPTs on patient waiting times. Advantages associated with PPT use were found mostly in relationship to acceptability of the tools by clinicians and increased transparency and equity for patients. Conclusions: This review describes the development and validation processes of PPTs used in non-urgent healthcare settings. Despite the large number of PPTs studied, implementation into clinical practice seems to be an open challenge. Based on the findings of this review, recommendations are proposed to develop, validate, and implement such tools in clinical settings. Systematic review registration: PROSPERO CRD42018107205
Bio-specific immobilization of enzymes on electrospun PHB nanofibers
Authors: Jang Sun Ah , Park Ji Hyun , Lim Hye Jin , Oh Joon Young , Bae Ki Hyeon , Lee Kyung Jin , Song Jae Kwang , Kim Dong-Myung 
Published: May 2020

Abstract
Background Oriented immobilization of enzymes provides substantial advantages in terms of improving the efficiency of enzymatic process as well as enhancing the reusability of enzymes. Phasins have high binding affinity to PHA, and thus can potentially be used as a fusion partner to immobilize enzymes onto PHA supports. However, presently available PHA supports of granular configuration have low surface-area-to-volume ratio, which limits enzyme loading on the supports. In this study, we explored the use of electrospun PHB nanofibers as an alternative support for high density immobilization of a phasin-fused lipase in directed orientations.Results The electrospun PHB nanofibers were successfully used for selective immobilization of the phasin-fused enzyme, and could anchor 120-fold more enzyme than PHB granules of the same weight. The enzyme immobilized onto the PHB nanofibers exhibited exceptionally high stability. Furthermore, via oriented immobilization of the enzymes, PHB nanofibers loaded with the phasin-fused lipase provided 3- to 10-fold higher enzyme activity than the conventional immobilization supports.Conclusions Our approach combines the advantageous features of nanofibrous materials and the regio-specificity of biomolecular interactions for the efficient immobilization of enzymes, which can be widely adopted in the development of various enzymatic processes.
Diagnostic Performance of a Blood Urea Nitrogen to Creatinine Ratio-Based Nomogram for Predicting in-Hospital Mortality in COVID-19 Patients
Authors: Liu Qingquan , Wang Yiru , Zhao Xuecheng , Wang Lixuan , Liu Feng , Lv Yongman , Wang Tao , Ye Dawei 
Published: May 2020

Abstract
Background: The novel coronavirus disease (COVID-19) is leading to high morbidity and mortality. This study aimed to test whether blood urea nitrogen-to-creatinine ratios (BCR) is a predictor of poor prognosis in patients with COVID-19. Method: From 9,165 generally healthy subjects, we calculated ranges of “normal” BCR values. 416 COVID-19 patients were randomly assigned to training cohort and validation cohort contained 337, 79 patients, respectively. The prognostic ability of abnormal BCR range was assessed using a Logistic regression. Development a nomogram for predicting in-hospital mortality incorporated age, sex and BCR. The model discrimination was assessed using the calibration curves and concordance index in training and validation cohort. The predictive accuracy and clinical values of the nomogram was measured by decision curve analysis (DCA) and clinical impact curve analysis (CICA). Results: Among 337 COVID-19 patients, 13.4% and 11.3% were classified into higher and lower than normal range group, respectively. The BCR was identified as an independent risks factor for death in COVID-19 patients (P<0.0001), with area under the curve (AUC) 0.768; 95%CI: 0.717-0.819). Kaplan-Meier curves for all-cause mortality outcomes showed that patients with above normal range of BCR had worse prognosis (p<0.0001). Logistic regression analysis revealed that BCR above the normal range was independently associated with death in COVID-19 patients (Odds ratio 7.54; 95%CI: 1.55-36.66; P=0.012). ROC curves showed that the nomogram had good discrimination in the training cohort (AUC 0.838; 95%CI 0.795–0.880) and the validation cohort (AUC 0.929; 95%CI 0.869-0.989). Using maximum Youden index, the cutoff values of 59.8 points, the sensitivity and specificity were 75.4% and 81%. The calibration curves showed good agreement between nomogram prediction and actual observation. DCA and CICA indicated the clinical usefulness of the prediction nomogram. Conclusion: BCR was a useful prognostic factor for COVID-19 patients. Development of an individualized prediction nomogram BCR-based, which can effectively predict the risk of mortality, and then, help clinicians to improve individual treatment, make clinical decisions timely and early.
Type of discrepancy between glycosylated hemoglobin and fasting plasma glucose is associated with in-hospital outcomes in patients with acute coronary syndrome and diabetes: findings from the Improving Care for Cardiovascular Disease in China - Acute Coronary Syndrome (CCC-ACS) Project
Authors: Ye Nan , Yang Lijiao , Wang Guoqin , Bian Weijing , Xu Fengbo , Ma Changsheng , Zhao Dong , Liu Jing , Hao Yongchen , Liu Jun , Yang Na , Cheng Hong 
Published: May 2020

Abstract
Background
The discrepancy between glycosylated hemoglobin (HbA1c) and fasting plasma glucose (FPG) in clinical practice may be related to factors such as acute stress, renal dysfunction, and anemia, and its relationship with in-hospital outcomes is uncertain. The aim of this study is to investigate the association between the type of discrepancy between HbA1c and FPG and in-hospital outcomes in patients with acute coronary syndrome (ACS) and diabetes.
Methods
The Improving Care for Cardiovascular Disease in China - Acute Coronary Syndrome (CCC-ACS) project is a national, hospital-based quality improvement project with an ongoing database. Patients with ACS, diabetes and complete HbA1c and FBG values at admission were included. The consistent group included patients with HbA1c < 6.5% and FBG < 7.0 mmol/L or HbA1c ≥ 6.5% and FBG ≥ 7.0 mmol/L. The discrepancy group included patients with HbA1c ≥ 6.5% and FBG < 7.0 mmol/L (increased HbA1c group) or HbA1c < 6.5% and FBG ≥ 7.0 mmol/L (increased FBG group).
Results
A total of 7,762 patients were included in this study. The numbers of patients in the consistent group and discrepancy group were 5,490 and 2,272 respectively. In the discrepancy group, increased HbA1c accounted for 77.5% of discrepancies, and increased FPG accounted for 22.5% of discrepancies. After adjusting for confounders, patients in the increased FPG group had a 1.6-fold increased risk of heart failure (OR, 1.62; 95% CI, 1.08–2.44), a 1.6-fold increased risk of composite cardiovascular death and heart failure (OR, 1.63; 95% CI, 1.09–2.43), and a 1.6-fold increased risk of composite major adverse cardiovascular and cerebrovascular events (MACCEs) and heart failure (OR, 1.56; 95% CI, 1.08–2.24).
Conclusions
Patients with an increased FPG but normal HbA1c had a higher risk of in-hospital adverse outcomes than those with increased HbA1c but normal FPG. This result may indicate that when HbA1c and FPG are inconsistent in patients with ACS and diabetes, the increased FPG that may be caused by stress hyperglycemia may have a more substantial adverse effect than increased HbA1c, which may be caused by chronic hyperglycemia. These high-risk patients should be given more attention and closer monitoring in clinical practice.
B-type Natriuretic Peptide Ability to Predict Mortality After Transcatheter Aortic Valve Replacement
Authors: Lehtola Heidi , Piuhola Jarkko , Niemelä Matti , Tauriainen Tuomas , Junttila Juhani , Mäkikallio Timo , Juvonen Tatu , Biancari Fausto 
Published: May 2020

Abstract
Background: Preoperative risk assessment is a cornerstone of patient’s selection for transcatheter aortic valve replacement (TAVR) for severe aortic valve stenosis.Hypothesis: In this study, we evaluated whether B-type natriuretic peptide (BNP) has a prognostic impact in these patients. Methods: Data on baseline BNP was available in 348 patients who underwent TAVR. The outcome measures of this study were 30-day and 3-year mortality.Results: In multivariate analysis, baseline BNP was an independent risk factor for 30-day (logarithmically transformed, OR 2.564, 95%CI 1.288-5.102) and 3-year mortality (logarithmically transformed, HR 1.685, 95%CI 1.280-2.218). According to the Youden’s test, the best cutoff of baseline BNP for 30-day mortality was 690 pg/mL (11.7% vs. 1.7%, adjusted OR 7.156, 1.872-27.358), and for 3-year mortality was 290 pg/mL (30.2% vs. 13.4%, adjusted HR 2.094, 95%CI 1.223-3.585). Harrell’s C and Somer’s D tests showed that baseline BNP improved the predictive ability of the STS score (p=0.040), but not that of the EuroSCORE II (p=0.115), for prediction of 3-year mortality. Conclusions: BNP is an independent predictor of outcome in patients undergoing TAVR and may be useful in guiding patient’s selection and treatment timing. Further studies are needed to assess its potential in increasing the performance of current risk scoring methods. Clinical Trial Registration: ClinicalTrials.gov, identifier NCT03385915 (https://clinicaltrials.gov/ct2/show/NCT03385915)
Cardiac computed tomography improves prediction of long-term cardiovascular events: a retrospective cohort study of type 2 diabetic with higher cardiovascular risk
Authors: Jian Zhijie , Liu Zhe , Zhou Li , Ding Ningning , Zhang Hui , Liu Peining , Li Bolin , Wu Yue , Yan Ge , Zhang Yun , Yu Bolang , Yang Jian 
Published: May 2020

Abstract
Background: The value of cardiac computed tomography (CT) for screening and risk stratification in patients with type 2 diabetes mellitus (DM) who are at a higher cardiovascular risk is unclear. Thus, this study aim s to investigate the efficacy of cardiac CT in predicting long-term cardiovascular events (CVEVs) in this subset of patients. Methods: Type 2 diabetic with a higher cardiovascular risk who underwent cardiac CT between 2012 and 2014 were included in this study. Cardiac CT was performed, and coronary artery calcium score, location and extent of lesion, stenosis severity, plaque composition, and epicardial adipose tissue (EAT) volume were assessed. The endpoints were a composite of CVEVs (cardiac death, non-fatal myocardial infarction, or coronary revascularization,non-fatal stroke, hospitalization for unstable angina, and hospitalization for congestive heart failure). Potential predictors of CVEVs were identified. Predictive models were created and compared. Results: CVEVs occurred in 26.8% of the patients. Independent predictors of CVEVs included diabetes duration (odds ratio [OR]=10.003), mean creatinine level (OR=3.845), hypertension (OR=3.844), atheroma burden obstructive score (OR=14.060), segment stenosis score (OR=7.912), and EAT volume (OR=7.947). The model including cardiac CT data and clinical parameters improved the prediction of CVEVs, with an area under the receiver operating characteristic curve of 0.912 (95% confidence interval 0.829–0.963; p<0.05) for the prediction of the study endpoints. Conclusion: Cardiac CT showed a great value in risk stratification for patients with diabetes with higher cardiovascular risk. Cardiac CT data may help predict CVEVs and potentially improve outcomes.
Patterns of Pesticides Usage in Agriculture in Rural Tanzania Call for Integrating Agricultural and Public Health Practices in Managing Insecticide-resistance in Malaria Vectors
Authors: Matowo Nancy S. , Tanner Marcel , Munhenga Givemore , Mapua Salum A. , Finda Marceline , Utzinger Jürg , Ngowi Vera , Okumu Fredros O. 
Published: May 2020

Abstract
Background: Unrestricted use of pesticides inagricultureis likely toincreaseinsecticide resistance in malaria mosquitoes. Unfortunately, strategies for managing insecticide resistance in agriculture and public health sectors lack integration. This study explored types of agricultural pesticides, the usage, awareness and management practicesamong retailers and farmers in Ulanga and Kilombero districts in south-eastern Tanzania, where malaria mosquitoes are resistant to pyrethroids.Methods: An exploratory sequential mixed-methods approach was used. First, a survey to characterise pesticide stockswas conducted in agricultural and veterinary (agrovet) retail stores. Interviews to assess general knowledge and practices regarding agricultural pesticideswere done with 17 retailers and 30 farmers followed by an in-depth survey involving 427 farmers.Concurrently, field observations were done to validate the results.Results: Lambda-cyhalothrin, cypermethrin and neonicotinoid imidacloprids were the most common agricultural insecticides sold to farmers. The herbicide glyphosate (amino-phosphonates)(59%) and the fungicides dithiocarbamate and acylalanine (54.5%) and organochlorine (27.3%) were also readily available in the agrovet shops and widely used by farmers. Although both retailers and farmers had at least primary-level education and recognized pesticides by their trade names,they lacked knowledge on pest control orproper usage of these pesticides. Mostof the farmers (n=316, 54.4%) relied on instructions from pesticides dealers. Overall, 93.7% (n = 400)farmers practiced pesticides mixing in their farms, often nearby water sources. One-third of the farmers disposedof their pesticide leftovers (n=128, 30.0%), and most of them discarded empty pesticide containers into rivers or nearby bushes (n = 238, 55.7%).Conclusion: Similarities of active ingredients used in agriculture and malaria vector control, poor pesticides management practices and low-levels of awareness among farmers and pesticides retailers might enhance the selection of insecticide resistance in malaria vectors. This study emphasises the need forimproving awareness among retailers and farmers on usage and management of pesticides, and highlights the needfor an integrated approach in the management of insecticide resistance inagricultural and public health sectors.
Online Readability of COVID-19 Health Information
Authors: Worrall Amy P , Connolly Mary J , O'Neill Aine , O'Doherty Murray , Thornton Kenneth P , McNally Cora , McConkey Samuel J , de Barra Eoghan 
Published: May 2020

Abstract
Introduction: The internet is now the first line source of health information for many people worldwide. In the current Coronavirus Disease 2019 (COVID-19) global pandemic, health information is being produced, revised, updated and disseminated at an increasingly rapid rate. The general public are faced with a plethora of misinformation regarding COVID-19 and the readability of online information has an impact on their understanding of the disease. The accessibility of online healthcare information relating to COVID-19 is unknown.Methods: The Google® search engine was used to collate the first twenty webpage URLs for three individual searches for ‘COVID’, ‘COVID-19’, and ‘coronavirus’ from Ireland, the United Kingdom, Canada and the United States. The Gunning Fog Index (GFI), Flesch-Kincaid Grade (FKG) Score, Flesch Reading Ease Score (FRES), Simple Measure of Gobbledygook (SMOG) score were calculated to assess the readability.Results: There were poor levels of readability webpages reviewed, with only 17.2% of webpages at a universally readable level. There was a significant difference in readability between the different webpages based on their information source (p <0.01). Public Health organisations and Government organisations provided the most readable COVID-19 material, while digital media sources were significantly less readable. There were no significant differences in readability between regions.Conclusion: Much of the general public have relied on online information during the pandemic. Information on COVID-19 should be made more readable, and those writing webpages and information tools should ensure universal accessibility is considered in their production. Governments and healthcare practitioners should have an awareness of the online sources of information available, and ensure that readability of our own productions is at a universally readable level which will increase understanding and adherence to health guidelines.
Comparison of Gray Values of Cone-beam Computed Tomography With Hounsfield Units of Multislice Computed Tomography Using a U-net Based Network
Authors: Wang Jingbo , Xiaofeng Tao , Liang Zhao , Jing Yuan , Chang Liu , Shuaining Xie , Xin Dou , Ling Zhu 
Published: May 2020

Abstract
Background：Dental departments generally employ cone-beam computed tomography (CBCT) instead of conventional computed tomography (CT), due to its lower price, smaller dosage, and high spatial resolution. During the corona virus disease 2019 (COVID-19) outbreak, CBCT is highly recommended to replace intraoral radiography because it greatly reduces the risk of exposure to salivary droplets. However, CBCT's inability to quantitatively measure tissue attenuation limits its application in differential diagnosis. Methods:We employed a U-Net based network to generate synthetic CT from dental CBCT. The deep neural network can be trained end-to-end to learn the complex mapping between CBCT and CT values. By the U-Net architecture, low-level and high-level features are both utilized to get fine detailed synthetic CT. We applied our method on the collected dataset contains 62 patients. Results:Experimental results on four metrics -- mean absolute error (MAE), root-mean-square error (RMSE), structural similarity index (SSIM), and peak-signal-to-noise ratio (PSNR) -- showed significant improvement of the synthetic CT compared to the original CBCT data. The MAE and RMSE improvement percentages are 64.44% and 66.44%.The MAE level of synthetic CT for most of the tissues are small enough to separate most important tissues,including dentin and cancellous bone, dentin and root canal，implants and cortical bone.Conclusions:CBCT and synthetic CT values can be used to distinguish different high-attenuation structures that are of interest to dentists. The application of CBCT assisted by this U-net based network in medical imaging of other parts of the body is promising.