bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functionalization of zirconia ceramic with fibronectin proteins enhanced bioactivity and osteogenic response of osteoblast-like cells
Authors: Aung Lwin Moe , Lin Jerry Chin-Yi , Salamanca Eisner , Wu Yi-Fan , Pan Yu-Hwan , Teng Nai-Chia , Huang Haw-Ming , Sun Ying-Sui , Chang Wei-Jen 
Published: April 2023

Introduction: To overcome the genuine bioinert properties of zirconia ceramic, functionalization of the surface with the bioactive protein fibronectin was conducted.Methods: Glow discharge plasma (GDP)-Argon was first used to clean the zirconia surface. Then allylamine was treated at three different powers of 50 W, 75 W, and 85 W and immersed into 2 different fibronectin concentrations (5 µg/ml and 10 µg/ml).Results and Discussion: After surface treatment, irregularly folded protein-like substances were attached on the fibronectin coated disks, and a granular pattern was observed for allylamine grafted samples. Infrared spectroscopy detected C-O, N-O, N-H, C-H, and O-H functional groups for fibronectin treated samples. Surface roughness rose and hydrophilicity improved after the surface modification, with MTT assay showing the highest level of cell viability for the A50F10 group. Cell differentiation markers also showed that fibronectin grafted disks with A50F10 and A85F10 were the most active, which in turn encouraged late-stage mineralization activity on 21d. Up-regulation of osteogenic related mRNA expression from 1d to 10d can be observed in RT-qPCR data for ALP, OC, DLX5, SP7, OPG and RANK biomarkers. These physical and biological properties clearly indicate that an allylamine and fibronectin composite grafted surface significantly stimulated the bioactivity of osteoblast-like cells, and can be utilized for future dental implant applications.
The interaction between changes of muscle activation and cortical network dynamics during isometric elbow contraction: a sEMG and fNIRS study
Authors: Wang Xiaohan , Luo Zichong , Zhang Mingxia , Zhao Weihua , Xie Songyun , Wong Seng Fat , Hu Huijing , Li Le 
Published: April 2023

Objective: The relationship between muscle activation during motor tasks and cerebral cortical activity remains poorly understood. The aim of this study was to investigate the correlation between brain network connectivity and the non-linear characteristics of muscle activation changes during different levels of isometric contractions.Methods: Twenty-one healthy subjects were recruited and were asked to perform isometric elbow contractions in both dominant and non-dominant sides. Blood oxygen concentrations in brain from functional Near-infrared Spectroscopy (fNIRS) and surface electromyography (sEMG) signals in the biceps brachii (BIC) and triceps brachii (TRI) muscles were recorded simultaneously and compared during 80% and 20% of maximum voluntary contraction (MVC). Functional connectivity, effective connectivity, and graph theory indicators were used to measure information interaction in brain activity during motor tasks. The non-linear characteristics of sEMG signals, fuzzy approximate entropy (fApEn), were used to evaluate the signal complexity changes in motor tasks. Pearson correlation analysis was used to examine the correlation between brain network characteristic values and sEMG parameters under different task conditions.Results: The effective connectivity between brain regions in motor tasks in dominant side was significantly higher than that in non-dominant side under different contractions (p &lt; 0.05). The results of graph theory analysis showed that the clustering coefficient and node-local efficiency of the contralateral motor cortex were significantly varied under different contractions (p &lt; 0.01). fApEn and co-contraction index (CCI) of sEMG under 80% MVC condition were significantly higher than that under 20% MVC condition (p &lt; 0.05). There was a significant positive correlation between the fApEn and the blood oxygen value in the contralateral brain regions in both dominant or non-dominant sides (p &lt; 0.001). The node-local efficiency of the contralateral motor cortex in the dominant side was positively correlated with the fApEn of the EMG signals (p &lt; 0.05).Conclusion: In this study, the mapping relationship between brain network related indicators and non-linear characteristic of sEMG in different motor tasks was verified. These findings provide evidence for further exploration of the interaction between the brain activity and the execution of motor tasks, and the parameters might be useful in evaluation of rehabilitation intervention.
Facades-as-a-Service: Systemic managerial, financial, and governance innovation to enable a circular economy for buildings. Lessons learnt from a full-scale pilot project in the Netherlands
Authors: Azcárate-Aguerre Juan F. , den Heijer Alexandra C. , Arkesteijn Monique H. , Vergara d’Alençon Luz María , Klein Tillmann 
Published: April 2023

Introduction: The challenge of the energy transition in the built environment has, in recent years, been exacerbated by rising awareness of the material resource limitations we face on the path towards sustainable development. In this context the concepts of Circular Economy (CE) and Product-Service Systems (PSS) have emerged as potentially complementary industrial and business strategies to overcome the interdependent material resource and clean energy challenges.Research significance: Research in the field of circular and PSS-based construction frequently centres on the design and engineering of products, mainly through technical strategies such as design for disassembly and adaptability, and the use of the different “R’s” (Reuse, Repair, Remanufacturing, etc.) to extend and/or reset the service lives of building materials and components. Such an approach often ignores the fact that these strategies require changes in the management, financing, and governance aspects of products and therefore buildings, throughout their entire service-lives. This paper will focus on the systemic administrative (i.e. management, financing, and governance) challenges of the circular and servitisation transitions in the building and construction sector, to enable products which are “Circular by Design”, to effectively support regenerative processes.Research question: The paper asks how traditional building products’ management, financing, and governance processes prevent or delay the implementation of CE and PSS models. It explores the demand side’s perspective (commissioners, building owners and facility managers), taking a systemic view to the search for new practical, strategic, and scalable administrative models.Methodology: The research method applies the DAS model (De Jonge et al., 2009; Van der Zwart et al., 2009; den Heijer, 2011; den Heijer et al., 2016) to data gathered from focus group discussion and co-design sessions involving multidisciplinary teams of experts from both academy and industry, as well as literature. The research was conducted within the context of the TU Delft Facades-as-a-Service full-scale pilot project.Results: The research has shown that, while PSS models to enable material circularity can be partially implemented within the current managerial, financial, and governance framework, this implementation is not efficient, effective, or scalable. This is because standard modes of operation in these disciplines are misaligned with that goal. The practical barriers resulting from this misalignment increase the complexity, risk perception, and therefore cost of PSS alternatives, and thus prevent their organic adoption despite increasing market interest. Recommendations are made for policymakers, financiers, suppliers, and building owners to overcome these barriers.
Evaluating the efficiency of a nomogram based on the data of neurosurgical intensive care unit patients to predict pulmonary infection of multidrug-resistant Acinetobacter baumannii
Authors: Wu Di , Sha Zhuang , Fan Yibing , Yuan Jiangyuan , Jiang Weiwei , Liu Mingqi , Nie Meng , Wu Chenrui , Liu Tao , Chen Yupeng , Feng Jiancheng , Dong Shiying , Li Jin , Sun Jian , Pang Chongjie , Jiang Rongcai 
Published: April 2023

BackgroundPulmonary infection caused by multidrug-resistant Acinetobacter baumannii (MDR-AB) is a common and serious complication after brain injury. There are no definitive methods for its prediction and it is usually accompanied by a poor prognosis. This study aimed to construct and evaluate a nomogram based on patient data from the neurosurgical intensive care unit (NSICU) to predict the probability of MDR-AB pulmonary infection.MethodsIn this study, we retrospectively collected patient clinical profiles, early laboratory test results, and doctors’ prescriptions (66 variables). Univariate and backward stepwise regression analyses were used to screen the variables to identify predictors, and a nomogram was built in the primary cohort based on the results of a logistic regression model. Discriminatory validity, calibration validity, and clinical utility were evaluated using validation cohort 1 based on receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). For external validation based on predictors, we prospectively collected information from patients as validation cohort 2.ResultsAmong 2115 patients admitted to the NSICU between December 1, 2019, and December 31, 2021, 217 were eligible for the study, including 102 patients with MDR-AB infections (102 cases) and 115 patients with other bacterial infections (115 cases). We randomly categorized the patients into the primary cohort (70%, N=152) and validation cohort 1 (30%, N=65). Validation cohort 2 consisted of 24 patients admitted to the NSICU between January 1, 2022, and March 31, 2022, whose clinical information was prospectively collected according to predictors. The nomogram, consisting of only six predictors (age, NSICU stay, Glasgow Coma Scale, meropenem, neutrophil to lymphocyte ratio, platelet to lymphocyte ratio), had significantly high sensitivity and specificity (primary cohort AUC=0.913, validation cohort 1 AUC=0.830, validation cohort 2 AUC=0.889) for early identification of infection and had great calibration (validation cohort 1,2 P=0.3801, 0.6274). DCA confirmed that the nomogram is clinically useful.ConclusionOur nomogram could help clinicians make early predictions regarding the onset of pulmonary infection caused by MDR-AB and implement targeted interventions.
Late-onset doxorubicin-induced congestive heart failure in an elderly cancer survivor: A case report
Authors: Suto Hirotaka , Suto Makiko , Inui Yumiko , Okamura Atsuo 
Published: April 2023

BackgroundRecently, the survival rate of patients with cancer has improved annually due to advancements in cancer diagnosis and treatment technologies. Meanwhile, late-onset complications associated with cancer treatment significantly affect survival and quality of life. However, different from pediatric cancer survivors, there is no unified view on the follow-up of late complications in elderly cancer survivors. We reported a case of congestive heart failure as a late-onset complication of doxorubicin (DXR) in an elderly cancer survivor.Case reportThe patient is an 80-year-old woman with hypertension and chronic renal failure. She received six cycles of chemotherapy for Hodgkin's lymphoma that started in January 201X-2. The total dose of DXR was 300 mg/m2, and a transthoracic echocardiogram (TTE) performed in October 201X-2, showed good left ventricular wall motion (LVWM). In April 201X, she suddenly developed dyspnea. Upon arrival at the hospital, a physical examination revealed orthopnea, tachycardia, and leg edema. A chest radiograph showed cardiac enlargement and pleural effusion. A TTE showed diffusely reduced LVWM and a left ventricular ejection fraction in the 20% range. After close examination, the patient was diagnosed with congestive heart failure due to late-onset DXR-induced cardiomyopathy.ConclusionLate-onset DXR-induced cardiotoxicity is considered high-risk from 250 mg/m2 or higher. Elderly cancer survivors are at higher risk of cardiotoxicity than non-elderly cancer survivors and may require closer follow-up.
Cardiovascular outcomes of cancer patients in rural Australia
Authors: Williams Trent D. , Kaur Amandeep , Warner Thomas , Aslam Maria , Clark Vanessa , Walker Rhonda , Ngo Doan T. M. , Sverdlov Aaron L. 
Published: April 2023

BackgroundCancer and heart disease are the two most common health conditions in the world, associated with high morbidity and mortality, with even worse outcomes in regional areas. Cardiovascular disease is the leading cause of death in cancer survivors. We aimed to evaluate the cardiovascular outcomes of patients receiving cancer treatment (CT) in a regional hospital.MethodsThis was an observational retrospective cohort study in a single rural hospital over a ten-year period (17th February 2010 to 19th March 2019). Outcomes of all patients receiving CT during this period were compared to those who were admitted to the hospital without a cancer diagnosis.Results268 patients received CT during the study period. High rates of cardiovascular risk factors: hypertension (52.2%), smoking (54.9%), and dyslipidaemia (38.4%) were observed in the CT group. Patients who had CT were more likely to be readmitted with ACS (5.9% vs. 2.8% p = 0.005) and AF (8.2% vs. 4.5% p = 0.006) when compared to the general admission cohort. There was a statistically significant difference observed for all cause cardiac readmission, with a higher rate observed in the CT group (17.1% vs. 13.2% p = 0.042). Patients undergoing CT had a higher rate of mortality (49.5% vs. 10.2%, p ≤ 0.001) and shorter time (days) from first admission to death (401.06 vs. 994.91, p ≤ 0.001) when compared to the general admission cohort, acknowledging this reduction in survival may be driven at least in part by the cancer itself.ConclusionThere is an increased incidence of adverse cardiovascular outcomes, including higher readmission rate, higher mortality rate and shorter survival in people undergoing cancer treatment in rural environments. Rural cancer patients demonstrated a high burden of cardiovascular risk factors.
Risk factors for in-hospital death in 2,179 patients with acute aortic dissection
Authors: Yuan Yue , Xia Zhiyu , Wang Lei , Sun Qi , Wang Wendan , Chai Chen , Wang Tiantian , Zhang Xiaowei , Wu Long , Tang Zehai 
Published: April 2023

BackgroundThis study aims to investigate the risk factors for in-hospital death in patients with acute aortic dissection (AAD) and to provide a straightforward prediction model to assist clinicians in determining the outcome of AAD patients.MethodsRetrospective analysis was carried out on 2,179 patients admitted for AAD from March 5, 1999 to April 20, 2018 in Wuhan Union Hospital, China. The risk factors were investigated with univariate and multivariable logistic regression analysis.ResultsThe patients were divided into two groups: Group A, 953patients (43.7%) with type A AAD; Group B, 1,226 patients (56.3%) with type B AAD. The overall in-hospital mortality rate was 20.3% (194/953) and 4% (50/1,226) in Group A and B respectively. The multivariable analysis included the variables that were statistically significant predictors of in-hospital death (P &lt; 0.05). In Group A, hypotension (OR = 2.01, P = 0.001) and liver dysfunction (OR = 12.95, P &lt; 0.001) were independent risk factors. Tachycardia (OR = 6.08, P &lt; 0.001) and liver dysfunction (OR = 6.36, P &lt; 0.05) were independent risk factors for Group B mortality. The risk factors of Group A were assigned a score equal to their coefficients, and the score of −0.5 was the best point of the risk prediction model. Based on this analysis, we derived a predictive model to help clinicians determine the prognosis of type A AAD patients.ConclusionsThis study investigate the independent factors associated with in-hospital death in patients with type A or B aortic dissection, respectively. In addition, we develop the prediction of the prognosis for type A patients and assist clinicians in choosing treatment strategies.
Prediction models for major adverse cardiovascular events following ST-segment elevation myocardial infarction and subgroup-specific performance
Authors: Chen Weiyao , Tan Xin , Du Xiaoyu , Li Qin , Yuan Meng , Ni Hui , Wang Yuan , Du Jie 
Published: April 2023

BackgroundST-segment elevation myocardial infarction (STEMI) patients are at a high residual risk of major adverse cardiovascular events (MACEs) after revascularization. Risk factors modify prognostic risk in distinct ways in different STEMI subpopulations. We developed a MACEs prediction model in patients with STEMI and examined its performance across subgroups.MethodsMachine-learning models based on 63 clinical features were trained in patients with STEMI who underwent PCI. The best-performing model (the iPROMPT score) was further validated in an external cohort. Its predictive value and variable contribution were studied in the entire population and subgroups.ResultsOver 2.56 and 2.84 years, 5.0% and 8.33% of patients experienced MACEs in the derivation and external validation cohorts, respectively. The iPROMPT score predictors were ST-segment deviation, brain natriuretic peptide (BNP), low-density lipoprotein cholesterol (LDL-C), estimated glomerular filtration rate (eGFR), age, hemoglobin, and white blood cell (WBC) count. The iPROMPT score improved the predictive value of the existing risk score, with an increase in the area under the curve to 0.837 [95% confidence interval (CI): 0.784–0.889] in the derivation cohort and 0.730 (95% CI: 0.293–1.162) in the external validation cohort. Comparable performance was observed between subgroups. The ST-segment deviation was the most important predictor, followed by LDL-C in hypertensive patients, BNP in males, WBC count in females with diabetes mellitus, and eGFR in patients without diabetes mellitus. Hemoglobin was the top predictor in non-hypertensive patients.ConclusionThe iPROMPT score predicts long-term MACEs following STEMI and provides insights into the pathophysiological mechanisms for subgroup differences.
Quantifying bubble-mediated transport by ebullition from aquatic sediments
Authors: Schwarz Michael , Marcon Lediane , Lorke Andreas 
Published: April 2023

The widespread release of gas bubbles from aquatic sediments (ebullition) has been receiving growing scientific interest because of its globally relevant contribution to methane emissions. Besides being an efficient transport pathway for methane and other gases to the atmosphere, these bubbles have the potential to mobilize resources and pollutants previously buried in the sediment by carrying solutes and particles on their surface. The phenomenon of bubbles transporting substances other than gases is well studied in open water and widely used in technical applications, such as froth flotation or dissolved air floatation. Research on the transport capabilities of natural bubbles forming in, and being released from, aquatic sediments is exceedingly rare. Ebullition resulting from biogenic gas production in sediments is characterized by large spatial and temporal variability and bubble sizes exceed those typically used in technical applications. Here we summarize the current state of research concerning bubble mediated transport (BMT) from aquatic sediments and develop a perspective based on these findings and own experimental results. We present measurements from a shallow reservoir to explore methods to monitor BMT and gather data on ebullition over 1 year. We found consistent bubble size spectra, despite large temporal variations of ebullition fluxes. We highlight some of the inherent difficulties of research in this area and argue that more experiments are needed for improving empirical and mechanistic understanding of BMT.
Optogenetic stimulation of the brainstem dorsal motor nucleus ameliorates acute pancreatitis
Authors: Thompson Dane A. , Tsaava Tea , Rishi Arvind , Nadella Sandeep , Mishra Lopa , Tuveson David A. , Pavlov Valentin A. , Brines Michael , Tracey Kevin J. , Chavan Sangeeta S. 
Published: April 2023

IntroductionInflammation is an inherently self-amplifying process, resulting in progressive tissue damage when unresolved. A brake on this positive feedback system is provided by the nervous system which has evolved to detect inflammatory signals and respond by activating anti-inflammatory processes, including the cholinergic anti-inflammatory pathway mediated by the vagus nerve. Acute pancreatitis, a common and serious condition without effective therapy, develops when acinar cell injury activates intrapancreatic inflammation. Prior study has shown that electrical stimulation of the carotid sheath, which contains the vagus nerve, boosts the endogenous anti-inflammatory response and ameliorates acute pancreatitis, but it remains unknown whether these anti-inflammatory signals originate in the brain.MethodsHere, we used optogenetics to selectively activate efferent vagus nerve fibers originating in the brainstem dorsal motor nucleus of the vagus (DMN) and evaluated the effects on caerulein-induced pancreatitis.ResultsStimulation of the cholinergic neurons in the DMN significantly attenuates the severity of pancreatitis as indicated by reduced serum amylase, pancreatic cytokines, tissue damage, and edema. Either vagotomy or silencing cholinergic nicotinic receptor signaling by pre-administration of the antagonist mecamylamine abolishes the beneficial effects.DiscussionThese results provide the first evidence that efferent vagus cholinergic neurons residing in the brainstem DMN can inhibit pancreatic inflammation and implicate the cholinergic anti-inflammatory pathway as a potential therapeutic target for acute pancreatitis.
Token-Selective Vision Transformer for fine-grained image recognition of marine organisms
Authors: Si Guangzhe , Xiao Ying , Wei Bin , Bullock Leon Bevan , Wang Yueyue , Wang Xiaodong 
Published: April 2023

IntroductionThe objective of fine-grained image classification on marine organisms is to distinguish the subtle variations in the organisms so as to accurately classify them into subcategories. The key to accurate classification is to locate the distinguishing feature regions, such as the fish’s eye, fins, or tail, etc. Images of marine organisms are hard to work with as they are often taken from multiple angles and contain different scenes, additionally they usually have complex backgrounds and often contain human or other distractions, all of which makes it difficult to focus on the marine organism itself and identify its most distinctive features.Related workMost existing fine-grained image classification methods based on Convolutional Neural Networks (CNN) cannot accurately enough locate the distinguishing feature regions, and the identified regions also contain a large amount of background data. Vision Transformer (ViT) has strong global information capturing abilities and gives strong performances in traditional classification tasks. The core of ViT, is a Multi-Head Self-Attention mechanism (MSA) which first establishes a connection between different patch tokens in a pair of images, then combines all the information of the tokens for classification.MethodsHowever, not all tokens are conducive to fine-grained classification, many of them contain extraneous data (noise). We hope to eliminate the influence of interfering tokens such as background data on the identification of marine organisms, and then gradually narrow down the local feature area to accurately determine the distinctive features. To this end, this paper put forwards a novel Transformer-based framework, namely Token-Selective Vision Transformer (TSVT), in which the Token-Selective Self-Attention (TSSA) is proposed to select the discriminating important tokens for attention computation which helps limits the attention to more precise local regions. TSSA is applied to different layers, and the number of selected tokens in each layer decreases on the basis of the previous layer, this method gradually locates the distinguishing regions in a hierarchical manner.ResultsThe effectiveness of TSVT is verified on three marine organism datasets and it is demonstrated that TSVT can achieve the state-of-the-art performance.