bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proteomic characterisation of serum proteins from Atlantic salmon (Salmo salar L.) from an outbreak with Cardiomyopathy Syndrome
Authors: Costa Janina , Pozo Jorge del , McLean Kevin , Inglis Neil , Sourd Philippe , Bordeianu Andrei , Thompson Kim D. 
Published: July 2021

Abstract
Cardiomyopathy syndrome (CMS), caused by piscine myocarditis virus (PMCV), is a serious challenge to Atlantic salmon (Salmo salar L.) aquaculture. Regrettably, husbandry techniques are the only tool to manage CMS outbreaks, and no prophylactic measures are available at present. Early diagnosis of CMS is therefore desirable, preferably with non-lethal diagnostic methods, such as serum biomarkers. To identify candidate biomarkers for CMS, the protein content of pools of sera (4 fish/pool) from salmon a CMS outbreak (3 pools) and from clinically healthy salmon (3 pools) were compared using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Overall, seven proteins were uniquely identified in the sera of clinically healthy fish, while twenty seven proteins were unique to the sera of CMS fish. Of the latter, 24 have been associated with cardiac disease in humans. These were grouped as leakage enzymes (creatine kinase, lactate dehydrogenase, glycogen phosphorylase and carbonic anhydrase); host reaction proteins (acute phase response proteins - haptoglobin, fibrinogen, α2-macroglobulin, ceruloplasmin; and complement-related proteins); and regeneration/remodelling proteins (fibronectin, lumican and retinol). Clinical evaluation of the suitability of these proteins as biomarkers of CMS, either individually or as part of a panel, is a logical next step for the development of early diagnostic tools for CMS.
Initial Experience of Video-Assisted Thoracic Surgery Lobectomy After Neoadjuvant Chemotherapy Plus Toripalimab in a Patient with Locally Advanced Non-Small Cell Lung Cancer: A Case Report
Authors: Li Wei , Zhai Chunbo , Che Jianpeng , Wang Weiqian , Liu Bingchun 
Published: July 2021

Abstract
Background: Immune checkpoint inhibitors were used for patients with advanced non-small cell lung cancer (NSCLC) more and more frequently and the effects were thrilling. Toripalimab as a new immune checkpoint inhibitor has been shown to be effective in patients with advanced NSCLC. However, data regarding the safety and feasibility of surgical resection after treatment with toripalimab for NSCLC remain scarce. Here, we present a case with locally advanced NSCLC that received video-assisted thoracic surgery (VATS) lobectomy after treatment with toripalimab in combination with chemotherapy.Case presentation: A 62-year-old male patient with a history of coronary artery stenting operation for two times was found a 3.4 × 3.2cm cavity mass in the upper lobe of the left lung and enlarged left hilar and mediastinal lymph nodes. Pathological results identified squamous cell carcinoma. The patient was diagnosed with a locally advanced NSCLC and received VATS left upper lobectomy and lymph node dissection after neoadjuvant chemotherapy plus toripalimab for 3 cycles. The postoperative pathological results showed complete tumor remission. Short-term follow-up results were excellent, and long-term results remain to be revealed.Conclusions: Our preliminary results showed that the use of neoadjuvant toripalimab and chemotherapy for the locally advanced NSCLC before surgical resection is safe and feasible.
Facile Preparation of All Cellulose Self-reinforced Nanocomposites from Bamboo Shoot Fibers
Authors: Yang Yinzhi , Fan Fangwei , Fang Kaiyang , Xie Jinpeng , Zhang Zhen , Deng Zhongmin , Cao Xinwang 
Published: July 2021

Abstract
Herein, a novel and facile fabrication method of self-reinforced all cellulose nanocomposite based on 2,2,6,6-tetramethylpiperidine-1-oxy (TEMPO) mediated oxidized bamboo shoot shell fibers was introduced. The composites were thoughtfully characterized. Cellulose nanowhiskers from the bamboo shoot fibers with the diameter of 60–90 nm and a large number of micropores were evenly distributed on the surface of the nanocomposite. Compared with the original fiber, the crystallinity of the composites increased, while the thermal stability decreased. The composite also showed good mechanical property and dimensional stability. It provides a promising and convenient route to obtain firm sheet-materials with micro- or nano- structures from nature cellulose fibers.
Diagnostic Value of PET/CT and Maximum Standardized Uptake Value in Patients with Primary Lymphoma
Authors: Zhu Lin , Nie Kai , Chen Yinan , Liu Jing , Xiao Yongxing , Yu Hong 
Published: July 2021

Abstract
Objective: Although the application of PET/CT in lymphomas has been the focus of many studies, the relationship between fluorodeoxyglucose uptake and biological indicators is complex and still incompletely understood, and there is a significant unmet need for more insightful differential diagnosis of PET/CT among different lymphoma subtypes. In present study, the diagnostic accuracy of 18F-PET/CT was assessed in patients with primary lymphoma and the clinical application value of SUVmax was determined. Methods: The diagnostic accuracy of a total of 97 patients with initial 18F-PET/CT scans between January 2015 and February 2020 were assessed, and the SUVmax was compared according to the different pathological subtypes. The relationship between SUVmax and immunophenotype, clinical characteristics, and genetic types were estimated. Results: According to the pathological results, 10 cases were misdiagnosed by PET/CT, and the accuracy was about 90%. Statistical analysis of SUVmax did not reveal a significant difference between Hodgkin’s lymphoma (HL) and non-Hodgkin’s lymphoma (NHL) (p=0.9071). Among NHL, the average SUVmax was statistically different between diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) (p=0.0004), FL and natural killer/T-cell lymphoma (p=0.0078), FL and peripheral T-cell lymphoma (PTCL) (p=0.0117), DLBCL and mantle cell lymphoma (MCL) (p=0.0294). In patients with DLBCL, SUVmax was correlated with the expression level of proliferation index Ki-67 (r=0.33, p=0.018), while average SUVmax shows no difference between various immunophenotype expression levels, ages, gender, skeletal invasion situations, clinical grade stages, international prognostic index (IPI) score, and different gene types (germinal center B cell-like (GCB) and non-GCB). Conclusion: 18F-PET/CT had a marked diagnostic value in patients with primary lymphoma, but some misdiagnosis was probable. The SUVmax is valuable in the differential diagnosis of different pathological types of NHL. Simultaneously, the SUVmax of patients with DLBCL correlated with Ki-67 might reflect the tumor invasiveness, thereby revealing a prognostic value.
Application of Artificial Intelligence in Agrometeorology
Authors: Faghih Homayoun , Behmanesh Javad , Rezaie Hossein , Khalili Keivan 
Published: July 2021

Abstract
Replacing irrigated with rainfed crops and sustainable production of major rainfed plants (such as wheat) can be an efficient strategy to restore water resources that are drying up. Identifying plant response to climate is essential to advancing this strategy and planning for precision agriculture. Wheat is the main plant of Saqez in the Lake Urmia basin of Iran, whose yield is associated with severe fluctuations. This study was conducted to investigate the climate effect on wheat yield fluctuation. For this purpose, the method of growing degree days (GDDs) and the Zadoks scale were used to divide the wheat growth period into seven stages. Forty-seven climatic variables of the first six stages were used to do factor analysis and to develop the model for forecasting pre-harvest yield. Gene expression programming (GEP), artificial neural networks (ANNs), and multivariate linear regression (MLR) methods were applied to develop the model. The results showed that 90.7% of the total variance of 47 variables can be explained by 10 factors. Eighty-two percent of yield variations were modeled by these 10 factors (r = 0.91). The mean absolute percentage error (MAPE) for the models developed by the GEP and ANN methods was 26%, and its amount for the MLR model was 35%. In this study, for the first time, the GEP method was used to model rainfed wheat yield. Comparison with MLR and ANN methods shows that GEP is suitable for modeling in this field.
Spatial-temporal change in water table depth for the conterminous United States over three decades
Authors: Munro Holly , Montes Cristian 
Published: July 2021

Abstract
The subtle equilibrium between supply and demand of freshwater is constantly changing due to anthropogenic activities and shifts in land use and climate. These freshwater resources are crucial for food and water security, and the sustainability of natural and managed systems. The spatial-temporal properties of groundwater are often overlooked, despite these subsurface reservoirs being linked to aboveground water use and ecosystem processes. In this study, we assessed the spatial-temporal changes of water table depth in the conterminous United States (U.S.) over the last three decades (1989-2019). National Ground-Water Monitoring Network water table depth data were paired with climate and terrain features. Interpolated maps were created by combining machine learning (i.e., gradient boosted regression trees) with traditional interpolation methods (i.e., Kriging). Water table depth is shallower in the eastern U.S., as compared to western U.S., except for high elevation locals which consistently had deeper water tables. The overall change in depth to water table for the conterminous U.S. was ~1m indicating that on average the water is getting deeper. Of the 56 aquifer systems, 41 are in areas where the water table has gotten deeper. These results highlight current “hotspots” of possible depletion where water management efforts should focus. Management of this crucial resource is essential for mitigating negative impacts of depletion, which may ultimately feedback further amplifying changes in climate.
Infective Endocarditis, Predictors of Mortality and Morbidity
Authors: Eranki Aditya , Saxena Akshat , Ali Umar , Slimani Eric 
Published: July 2021

Abstract
Objectives:

Infective endocarditis is a disease with high mortality and morbidity. The primary outcome of this study is to assess factors associated with in-hospital mortality in patients undergoing valvular surgery for infective endocarditis. The secondary outcome of this study is to assess the incidence and factors associated with post-operative morbidity; namely post-operative stroke, renal failure and dialysis, complete heart block and return to theatre for bleeding or tamponade.
Methods

Between the years of 2015 to 2019, a total of 89 patients underwent surgery for infective endocarditis at Fiona Stanley Hospital. Data was collected from the Australia and New Zealand Cardiac Surgery Database from 2015 to 2019 as well as patients electronic medical record (EMR). A number of preoperative and perioperative factors were assessed in relation to patient mortality and morbidity. Univariate and multivariate logistical regression analysis was done to assess for the association between factors and in-hospital mortality and morbidity
Results:

A total of 89 patients underwent surgery for infective endocarditis, affecting 101 valves. The mean age of patients was 53.7. A total of 79 patients had a positive blood culture pre-operatively, with Staphylococcus Aureus being the most frequently cultured organism (39%). Fourteen patients (16%) were deemed emergent and underwent surgery within 24 hours of review. A total of five patients died within their hospital stay postoperatively. Variables significantly associated with mortality on univariate analysis were intravenous drug use, emergent surgery, perioperative dialysis, perioperative inotropes, cardiopulmonary bypass (CPB) time and cross clamp time (CCT). Only CBP time was significantly associated with mortality on multivariate analysis. A total of 19 patients (21%) required hemodialysis after surgery, 10 patients sustained a postoperative stroke (11%), 15 patients required to return to theatre (17%) and 11 patients developed a complete heart block post operatively (12%).
Conclusion

There are a number of factors associated with mortality and morbidity in patients undergoing surgery with infective endocarditis. Our study demonstrates a lower mortality rate in these patients than previously quoted in literature. Exposure of prolonged CBP times was the only factor significantly associated with increased mortality on multivariate analysis, although a critical perioperative state was highly significant on univariate analysis.
Ambrosia: Reduction in Data Transfer from Sensor to Server for Increased Lifetime of IoT Sensor Nodes
Authors: Suryavansh Shikhar , Benna Abu , Guest Chris , Chaterji Somali 
Published: July 2021

Abstract
Data transmission accounts for significant energy consumption in wireless sensor networks where streaming data is generated by the sensors. This impedes their use in many settings, including livestock monitoring over large pastures (which forms our target application). We present Ambrosia, a lightweight protocol that utilizes a window-based timeseries forecasting mechanism for data reduction. Ambrosia employs a configurable error threshold to ensure that the accuracy of end applications is unaffected by the data transfer reduction. Experimental evaluations using LoRa and BLE on a real livestock monitoring deployment demonstrate 60% reduction in data transmission and a 2X increase in battery lifetime.
The Role of Proximate Determinants and Distal Variables On Recent Fertility in Dabat Health and Demographic Surveillance System Site, Northwest Ethiopia: A Mediation Analysis
Authors: Alazbih Nega Mihret , Kaya Assefa Hailemariam , Mengistu Mezgebu Yitayal , Gelaye Kassahun Alemu 
Published: July 2021

Abstract
Background

In Ethiopia, previous studies have explored the role of the proximate determinants for recent fertility decline at national and regional levels. However, none of these studies have examined the role of socioeconomic factors on the observed fertility decline through these proximate variables. This study aimed to estimate the effects of proximate determinants of fertility and the contribution of distal variables in recent fertility in Dabat Health and Demographic Surveillance Site, northwest Ethiopia.
Methods

A community based cross-sectional survey was carried out in 2020 among 1649 women of reproductive age group. Data were collected using structured and interviewer administered questionnaire. Generalized structural equation model was employed for the mediation analysis to estimate the relationships among distal and mediating variables with outcome variable, children ever born, simultaneously. A difference approach was used to test whether the effects of predictor variables were mediated.
Results

The Total Fertility Rate (TFR) for the three years preceding the survey was estimated at 3.4 children per woman. The Age Specific Fertility Rate (ASFR) in the study area reached its peak in the age group of 25–29 with 191 children per 1000 women. Among the proximate determinants, only marriage was a significant proximate determinant of recent fertility. The probability of having birth was more than fivefold higher among currently married women (IRR = 5.6 with a P-value = 0.000) than their unmarried counterparts. Age of women, occupation of women, household wealth status, ideal number of children, and experiencing child death had a significant total effect on recent fertility that were decomposed to direct and indirect or mediated effects of variables.
Conclusion

Marriage was the only proximate determinant that stood out as a significant mediated variable through which the distal variables affected fertility. Findings also clearly indicated that female participation in non-agricultural occupation affected the recent fertility. Hence, women's level of employment should be raised to increase their economic independence that will reduce the desirability of early marriage which in turn lower the number of children. In addition, the prevailing strategies on family planning programs should be improved to enhance the prevalence of contraceptive use among married women that will accelerate the current fertility transition.
Clinical Features and Prognostic Factors of Elderly Patients with Gallbladder Cancer: A Population-Based Study
Authors: Shuai Jin , Deyu Li , Tao Lianyuan , Haibo Yu , Guanjing Tian 
Published: July 2021

Abstract
Background: Elderly patients with gallbladder cancer (GBC) may be a special group of individuals. The present study aimed to explore the clinical features and prognostic factors of elderly patients with GBC and establish nomogram to predict their overall survival (OS). Methods: Patients diagnosed with GBC from 2010 to 2015 were identified from the Surveillance Epidemiology and End Results database. Clinical characteristics and prognostic factors in elderly GBC patients were examined. Results: Elderly patients and young patients with GBC differed in many aspects, including race, marital status, AJCC stage, T stage, N stage, M stage, surgery, lymph node dissection, radiation, chemotherapy, and OS (P<0.05). Analysis of prognostic factors showed that chemotherapy and surgery with lymph node dissection (radical surgery), as the main treatment for elderly patients, can significantly improve prognosis. Other factors, including being unmarried, higher grade of histological type and AJCC stage, had a negative effect on OS. Nomogram was developed based on the above prognostic factors. The C-indexes of 1-year survival and 3-year survival nomogram were 0.73 and 0.736 and AUCs at 1 and 3 years were 0.789 and 0.780, respectively. Conclusions: Elderly patients with GBC comprise a distinct group of individuals whose clinical characteristics differ from those of young patients, and the nomogram constructed accurately predicted OS in elderly patients with GBC.
Evaluation of Historical CMIP6 Model Simulations and Future Projections of Temperature Over the Pan-Third Pole Region
Authors: Fan Xuewei , Duan Qingyun , Shen Chenwei , Wu Yi , Xing Chang 
Published: July 2021

Abstract
The Pan-Third Pole (PTP) region, which encompasses the Eurasian highlands and their surroundings, has experienced unprecedented, accelerated warming during the past decades. This study evaluates the performance of historical simulation runs of the Coupled Model Intercomparison Project (CMIP6) in capturing spatial patterns and temporal variations observed over the PTP region for mean and extreme temperatures. In addition, projected changes in temperatures under four Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2‐4.5, SSP3-7.0, and SSP5‐8.5) are also reported. Four indices were used to characterize changes in temperature extremes: the annual maximum value of daily maximum temperature (TXx), the annual minimum value of daily minimum temperature (TNn), and indices for the percentage of warm days (TX90p) and warm nights (TN90p). Results indicate that most CMIP6 models generally capture the characteristics of the observed mean and extreme temperatures over the PTP region, but there still are slight cold biases in the Tibetan Plateau. Future changes of mean and extreme temperatures demonstrate that a strong increase will occur for the entire PTP region during the twenty-first century under all four SSP scenarios. Between 2015 and 2099, ensemble area-averaged annual mean temperatures are projected to increase by 1.24°C/100 year, 3.28°C/100 year, 5.57°C/100 year, and 7.40°C/100 year for the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. For TXx and TNn, the most intense warming is projected in Central Asia. The greatest number of projected TX90p and TN90p will occur in the Tibetan Plateau and Southeast Asia subregions, respectively.
Usefulness of Lung Ultrasound in Older Patients with Asymptomatic COVID-19 Pneumonia: Bicentric 3-month Follow-up Study
Authors: Okoye Chukwuma , Calsolaro Valeria , Fabbri Alessandra , Franchi Riccardo , Antognoli Rachele , Zisca Ludovica , Bianchi Camilla , Calabrese Alessia Maria , Rogani Sara , Monzani Fabio 
Published: July 2021

Abstract
BACKGROUND: Clinical and prognosticdifferencesbetweensymptomatic and asymptomaticolderpatients with COVID-19 are of greatinterestsincefrailpatientsoften show atypicalpresentation of illness.LungUltrasound (LUS) hasbeenproven to be a reliable tool for detectingearly-phase COVID-19 pneumonicalterations. The current study aimed to compare LUS score and 3-month overall mortalitybetweenasymptomatic and symptomaticolderpatients with COVID-19, according to frailty status.METHODS: Bicentric prospective study onolder patients with asymptomatic and symptomaticCOVID-19 disease.Patients were stratified according to LUS score tertiles and Clinical Frailty Scale categories.Survival rate was assessed by telephone interviews 3months afterdischarge.RESULTS: 64 symptomatic (24women, aged 80.0±10.8 years) and46asymptomatic (31 women; aged 84.3±8.8 years) were consecutively enrolled. LUS score resulted an independent predictor of 3-month mortality [OR2.27 (CI95%: 1.09-4.8), p=0.03], andthe highest mortality rate was observed in symptomatic and asymptomatic pre-frail and frail patients (70.6% and 66.7%, respectively)withgreater LUS abnormalities (3rdtertile).CONCLUSIONS: LUS identified an acute interstitiallunginvolvement in most of the older asymptomatic patients.Mortality rate progressively increasedaccording to clinical frailty and LUS score degree, resulting a reliable prognostic tool inboth symptomatic and asymptomatic patients.
COVID-19 and The Impact of Climatic Parameters: A Case Study of Bangladesh
Authors: Parvin Rehana 
Published: July 2021

Abstract
This study examines the relationship between climatic factors and the prevalence of COVID-19 in Bangladesh. Pearson correlation coefficient, Spearman correlation coefficient, and Kendall's correlation coefficient have all been put to use to assess the intensity and direction of the relationship between climatic factors and COVID-19. The lagged effects of climatic parameters on COVID-19 daily-confirmed cases from Bangladesh are being looked into using the Auto Regressive Distributed Lag (ARDL) model. As a result, two non-climatic variables, such as population density and the human development index, are taken into account as control variables. As climatic variables, average temperature (°C), average humidity (percent), average PM 2.5, and average wind speed (km/h) were well chosen. The time series data used in this analysis was from May 1, 2020 to April 14, 2021. The findings of correlation analysis indicate that there is an important, significant, and positive relationship between COVID-19 widespread and temperature (°C), humidity (percent), and wind speed (km/h), whereas there is a negative, weak, and significant relationship between PM 2.5 and COVID-19 widespread. In addition, the ARDL findings suggested that temperature (°C), PM 2.5, and wind speed (km/h) have major lagged effects on COVID-19 in Bangladesh, while humidity (percent) has negligible lagged effects. For policymakers and investors alike, the consequences of this study are important in Bangladesh.