bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic System of&nbsp;&nbsp;Cucumis&nbsp;sativus var. hardwickii (Royle) Alef. –&nbsp;&nbsp;&nbsp;(wild cucumber) in Jammu, J&amp;K, India
Authors: Sharma Priya , Devi Jayoti , Sharma Namrata 
Published: March 2021

Abstract
A small population of Cucumis sativus var. hardwickii (wild cucumber) has been localized for the first time from Billawar, Kathua (District) in UT of J&K. This variety as expected is monoecious in sex expression, but shows unique pattern of development of male and female flowers on the vine throughout its blooming period. Keeping provision for both both self and cross pollination, it is found to be self compatible, insect pollinated taxa with high reproductive output and a stable diploid complement (2n = 14). Small proportion of cells (9.92%) shows tetraploidy (2n = 28). The species exhibits high and healthy fruit set on open pollination as well as on manual self and cross pollination.
Identification of Key Immune-Related Genes, Molecular Pathways and Immune Infiltration as Diagnostic and Therapeutic Candidate Targets for RA: an integrated bioinformatics-based analysis
Authors: Fang Sheng , Fang Xiao , Xu Xin , Zhong Lin , Wang An-quan , Gao Wei-lu , yin Zong-Sheng 
Published: March 2021

Abstract
Relevance

Rheumatoid arthritis (RA) is a systemic autoimmune disease with an aggressive, chronic synovial inflammation as the main pathological change. However, the specific etiology, pathogenesis, and related biomarkers in diagnosis and treatment are still not fully elucidated. This study attempts to provide new perspectives and insights into RA at the genetic, molecular, and cellular levels through the tenet of personalized medicine.
Methods

Gene expression profiles of four individual knee synovial tissues were downloaded from a comprehensive gene expression database, R language was used to screen for significantly differentially expressed genes (DEGs), Gene Ontology Enrichment Analysis, Kyoto Gene Encyclopedia, and Gene Set Enrichment Analysis were performed to analyze the biological functions and signaling pathways of these DEGs, STRING online database was used to establish protein-protein interaction networks, Cytoscape software to obtain ten hub genes, Goplot to get six inflammatory immune-related hub genes, and CIBERSORT algorithm to impute immune infiltration.
Results

Molecular pathways that play important roles in RA were obtained: Toll-like receptors, AMPK, MAPK, TNF, FoxO, TGF-beta, PI3K and NF-κB pathways, Ten hub genes: Ccr1, Ccr2, Ccr5, Ccr7, Cxcl5, Cxcl6, Cxcl13, Ccl13, Adcy2, and Pnoc. among which Adcy2 and Pnoc have not been reported in RA studies, suggesting that they may be worthy targets for further study. It was also found that among the synoviocytes in RA, the proportions of plasma cells, CD8 T cells, follicular helper T cells, monocytes, γ delta T cells, and M0 macrophages were higher, while the proportions of CD4 memory resting T cells, regulatory T cells (Tregs), activated NK cells, resting dendritic cells, M1 macrophages, eosinophils, activated mast cells, resting mast cells were lower in proportion, and each cell played an important role in RA.
Conclusions

This study may help understand the key genes, molecular pathways, the role of inflammatory immune infiltrating cells in RA’s pathogenesis and provide new targets and ideas for the diagnosis and personalized treatment of RA.
Extraction and Characterization of Nanocellulose from Eragrostis Teff Straw
Authors: Bacha Ebise Getacho , Demsash Hundessa Dessalegn 
Published: March 2021

Abstract
This work presents the extraction and characterization of nanocellulose from agricultural waste (Eragrostis Teff) straw. The proximate analysis of the straw was done with three triplicates and the average value was recorded. The moisture, ash, volatile matter, and fixed carbon content were 6.4%, 5.1%, 74.2%, and 15.6%, respectively. The extractives, lignin, hemicellulose, and cellulose content were found to be 8.5%, 17.5%, 29.5%, 36.5%, respectively. The cellulose was extracted from teff straw by hot water treatment, acid-chlorite delignification, and alkaline hydrolysis process respectively. The values of process parameters such as temperature, time, and sodium hydroxide concentration for alkaline hydrolysis were 57.6 \(℃\) , 1hour, and 4(w/v) % respectively to obtain a cellulose yield of 78.7%. The nano cellulose particles were extracted from the cellulose by acid hydrolysis process (48%v/v sulfuric acid) at 35\(℃\) for 30 min and the yield was 42.8%. The characterization of nano cellulose was done by using Fourier-transform infrared spectroscopy, dynamic light scattering, x-ray diffraction, and thermogravimetry analysis/ derivative thermogravimetry analysis to determine the functional group, particle size distribution, crystallinity, and thermal stability respectively. The Fourier-transform infrared spectroscopy result shows that the reduction and total removal of lignin, hemicellulose, and other amorphous parts found in teff straw. The average particle size was found to be 101.6 nm with a polydispersity index of 0.047. The crystallinity index of teff straw and nano cellulose was 47.7 and 77.1% respectively. The thermogravimetry analysis shows the thermal stability of the nanocellulose sample was lower than that of cellulose and teff straw samples.
Co-variance nexus between ultraviolet index and tropospheric ozone during COVID-19 lockdown over megacities of India
Authors: Bera Biswajit , Bhattacharjee Sumana , Shit Pravat Kumar , Sengupta Nairita , Saha Soumik 
Published: March 2021

Abstract
Worldwide spread out of COVID-19 in a short-time has brought a significant decline of road traffic, tourist flow and industrial ventures. During this emergency period, the restricted human dealings with nature have appeared as blessing for health of the total environment. The variation of atmospheric O3 may modulate the range of UV index (UVI) at any region of the earth. The objective of the study is to examine the alteration of UV index over the megacities of India with respect to tropospheric O3 level modification during COVID-19 lockdown. The spatiotemporal data of UVI, over the major megacities of India (New Delhi, Mumbai, Kolkata, and Chennai) have been extracted from Tropospheric Emission Monitoring Internet Service. The monthly average surface ozone concentration throughout the time frame of 2019 and 2020 has been obtained from NASA Earth Observatory (NEO) hub. The meteorological or environmental data (temperature in °C, gust in km/h, wind speed km/h, relative humidity in %, air pressure in mb and cloud cover in okta) of four selective megacities of India (Kolkata, Chennai, Delhi, Mumbai) during and pre lockdown period have been acquired from world weather online. The descriptive statistical applications i.e. standard deviation, standard errors and K-means clustering have been done through standard statistical software. The result shows that the four major megacities in India namely New Delhi, Mumbai, Kolkata and Chennai have experienced the vibrant diminution in terms of the concentration of UV index with slightly increasing the tropospheric O3 level during the lockdown phase. In the meantime, the prominent reduction of NOx during the lockdown period decreases the titration impact to O3 and this mechanism helps to revitalize the ozone concentration level. The uniqueness of the current study is highlighted the ground reality regarding reduction of UV index and amplification of tropospheric O3 concentration during lockdown phase. This study definitely assists to make new environmental policy, act and law for recover the health of the total environment.
A Novel Large Animal Model of Smoke Inhalation-Induced Acute Respiratory Distress Syndrome
Authors: Leiphrakpam Premila , Weber Hannah , McCain Andrea , Matas Roser Romaguera , Duarte Ernesto Martinez , Buesing Keely 
Published: March 2021

Abstract
Background
Acute respiratory distress syndrome (ARDS) is multifactorial and can result from sepsis, trauma, or pneumonia, amongst other primary pathologies. It is one of the major causes of death in critically ill patients with a reported mortality rate up to 45%. The present study focuses on the development of a large animal model of smoke inhalation-induced ARDS in an effort to provide the scientific community with a reliable, reproducible large animal model of isolated toxic inhalation injury-induced ARDS.
Methods
Animals (n = 21) were exposed to smoke under general anesthesia for 1 to 2 hours (median smoke exposure = 0.5 to 1 liter of oak wood smoke) after the ultrasound-guided placement of carotid, pulmonary, and femoral artery catheters. Peripheral oxygen saturation (SpO2), vital signs, and ventilator parameters were monitored throughout the procedure. Chest x-ray, carotid, femoral and pulmonary artery blood samples were collected before, during, and after smoke exposure. Animals were euthanized and lung tissue collected for analysis 48 hours after smoke inhalation.
Results
Animals developed ARDS 48 hours after smoke inhalation as reflected by a decrease in SpO2 by approximately 31%, PaO2/FiO2 ratio by approximately 208, and development of bilateral, diffuse infiltrates on chest x-ray. Study animals also demonstrated a significant increase in IL-6 level, lung tissue injury score and wet/dry ratio, as well as changes in other arterial blood gas (ABG) parameters.
Conclusions
This study reports, for the first time, a novel large animal model of isolated smoke inhalation-induced ARDS without confounding variables such as cutaneous burn injury. Use of this unique model may be of benefit in studying the pathophysiology of inhalation injury or for development of novel therapeutics.
Impact of exposures to persistent endocrine disrupting compounds on the sperm methylome in regions associated with neurodevelopmental disorders
Authors: Maggio Angela G. , Shu Henry T. , Laufer Benjamin I. , Hwang Hyeyeon , Bi Chongfeng , Lai Yinglei , LaSalle Janine M. , Hu Valerie W. 
Published: March 2021

Abstract
Background: Although autism spectrum disorder (ASD) is among the most heritable of neurodevelopmental disorders, the rapidly rising prevalence of ASD suggests that environmental factors may contribute to epigenetic modifications that can influence risk for ASD. Endocrine disrupting compounds (EDCs), such as the long-lived organochlorines, are of particular interest with respect to risk for autism because of their ability to interfere with sex hormones that have been implicated in ASD. Methods: Whole genome bisulfite sequencing was used to identify genome-wide differentially methylated regions (DMRs) in a total of 52 sperm samples from a cohort of Faroese men who were equally divided into high and low exposure groups based on their serum levels of the long-lived organochlorine 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE). Inhabitants of the Faroe Islands, who as a group are considered a genetic isolate, may be exposed to higher than average levels of such persistent EDCs because of their native diet that is enriched in pilot whale meat and blubber. Gene ontology and pathway analyses were used to determine enrichment in ASD-relevant pathways and functions among the DMR-associated genes. Results: DMRs were enriched in autism risk genes and could also discriminate between samples in high and low exposure groups. Functional and pathway analyses of these DMR-associated genes show significant enrichment for neurodevelopmental processes frequently impacted by ASD. Of note, the DMR-associated genes significantly overlap with those previously identified in sperm from fathers of children with ASD versus fathers of neurotypical children, thus suggesting a potential environmental mechanism for introducing ASD-associated epigenetic changes in the sperm methylome. Limitations: A limitation of this study is the relatively low number of samples, although this is somewhat offset by the use of a genetic isolate which reduces the genetic heterogeneity that is often a major challenge in epigenetic studies. Another limitation is the lack of a completely unexposed set of samples for comparisons since persistent EDCs can be detected in a majority of individuals. Conclusion: Results of this study show that elevated exposure to certain organochlorines is associated with genome-wide DNA methylation patterns in sperm affecting genes involved in neurological functions and developmental disorders, including ASD.
Biodegradable composites from bamboo Fibers - Mechanical and Morphological Study
Authors: Rasheed Masrat , Jawaid Mohammad , Parveez Bisma 
Published: March 2021

Abstract
Realizing the need for conservation of environment due to contamination caused as a result of disposal of non-biodegradable waste. It has compelled researchers to search a new green material as a substitute to these toxic materials. The present research work focused on particularly the effective usage of Cellulose nanocrystalline (CNC) extracted from bamboo fibers as reinforcement in PLA/PBS polymeric blend. Polymer blend composites were fabricated using the hot-pressing technique with varying CNC contents. The morphological and mechanical properties of the composite samples with varying CNC contents were investigated. The results revealed that there was a positive effect of incorporation of CNC (extracted from bamboo fibers) on the properties of the polymer matrix.
Distribution of dyslipidemia in Chinese early breast cancer patients at diagnosis and comparison of dyslipidemia incidence following different endocrine therapies: a population-based cohort study
Authors: Wang Junren , Yin Jin , Qiu Jiajun , Jiang Jingwen , Hu Yao , Zheng Hong , Luo Ting , Zhong Xiaorong 
Published: March 2021

Abstract
Background

Dyslipidemia increases the risk of cardiovascular disease death in breast cancer (BC). Based on the large West China Hospital (WCH) BC cohort, we aimed to clarify dyslipidemia prevalence at diagnosis and compare the risk of dyslipidemia induced by different endocrine and menopause status.
Methods

5917 EBC female patients recorded in WCH BC cohort, diagnosed between 2008.10 and 2017.04, were included for baseline analysis. 1883 patients receiving endocrine therapy (selective estrogen receptor modulator (SERM) or aromatase inhibitor (AI), with or without ovarian function suppression) with initial normal blood lipids were included for comparison study. Dyslipidemia was defined as abnormality of cholesterol/LDL/ HDL/triglyceride. Risk accumulation function was used to calculate the incidence of dyslipidemia to assess absolute risk, and the multivariate COX regression model was used to calculate the relative risk of dyslipidemia between groups.
Results

16.5% of EBC patients had dyslipidemia at diagnosis. Among EBC patients receiving endocrine therapy, the accumulated incidence of dyslipidemia within 5 years in menopausal patients was higher than that in premenopausal patients (Adjusted HR [95%CI], 1.29 [1.04–1.59], 42.6 % vs 32.6%, P = 0.0186). In premenopausal patients, the risk of abnormal TC in OFS + AI group was significantly higher than SERM group (adjusted HR, 3.50 [ 1.74–7.02], P < 0.001, 5-year abnormal rate 22.0% vs 3.5%), and that of abnormal LDL-C was also increased(adjusted HR, 6.71 [ 3.16–14.26], P < 0.001, 5-year abnormal rate 12.2% vs 1.4%). In menopausal patients, the risk of abnormal TC or LDL-C showed the similar trend in AI group compared to SERM group.
Conclusions

Dyslipidemia is common concomitant disease in Chinese BC patients and needs to be closely monitored. Irrespective of menopause, AIs treatment causes higher risk of TC/LDL-C dyslipidemia than SERM.
Time Series Modeling of Road Traffic Accidents in Amhara Region
Authors: Alemtsega Kidane 
Published: March 2021

Abstract
Road traffic accidents are commonly encountered incidents that can cause injuries, death, and property damage to members of society. Ethiopia is one of the highest incident rates of road traffic accidents. Report of Transport and Communication from 2012–2014, shows an increment in the number of traffic accidents in Ethiopia. Amhara region accounted for 27.3% of the total road traffic accident-related deaths in Ethiopia during the year 2008/9, which is the highest share among all regions. The current research aims to model the trend of injury, fatal and total road traffic accidents in the Amhara region from September 2013 to May 2017. Monthly reported traffic accidents were obtained from traffic police offices and other concerned governmental organizations at the zonal and regional levels. The most universal class of models for forecasting time series data called Auto-regressive Integrated Moving Averages models are applied to model the trends and patterns of road traffic accident cases in the Amhara region. The average number of observed injury RTA, fatal RTA, and total RTA were 27.2, 14, and 78.2 per month respectively. It was observed that a relatively large number of RTA’S are reported on Tuesday, Thursday, and Saturday relative to other days of the week. The data also reveals that more than 60% of accidents involve drivers between the ages of 18–30 years. ARIMA (2,0,0) (1,0,0) ARIMA (2,0,0) and ARIMA (2,0,0) (1,1,0) were fitted as the best model for total injury accidents, fatal RTA and total RTA data respectively. A 48 months forecast was made based on the fitted models and it can be concluded that road traffic accident cases would continue at the non-decreasing rate in the Amhara region for the predicted periods. Therefore, the findings of this study draw attention to the importance of implementing improved better policies and close monitoring of road trafficking to change the existing trend of road traffic accidents in the region.
Adjusting spatial dependence of climate model outputs with Cycle-Consistent Adversarial Networks
Authors: François Bastien , Thao Soulivanh , Vrac Mathieu 
Published: March 2021

Abstract
Climate model outputs are commonly corrected using statistical univariate bias correction methods. Most of the time, those 1d-corrections do not modify the ranks of the time series to be corrected. This implies that biases in the spatial or inter-variable dependences of the simulated variables are not adjusted. Hence, over the last few years, some multivariate bias correction (MBC) methods have been developed to account for inter-variable structures, inter-site ones, or both. As proof-of-concept, we propose to adapt a computer vision technique used for Image-to-Image translation tasks (CycleGAN) for the adjustment of spatial dependence structures of climate model projections. The proposed algorithm, named MBC-CycleGAN, aims to transfer simulated maps (seen as images) with inappropriate spatial dependence structure from climate model outputs to more realistic images with spatial properties similar to the observed ones. For evaluation purposes, the method is applied to adjust maps of temperature and precipitation from climate simulations through two cross-validation approaches. The first one is designed to assess two different post-processing schemes (Perfect Prognosis and Model Output Statistics). The second one assesses the influence of nonstationary properties of climate simulations on the performance of MBC-CycleGAN to adjust spatial dependences. Results are compared against a popular univariate bias correction method, a ``quantile-mapping'' method, which ignores inter-site dependencies in the correction procedure, and two state-of-the-art multivariate bias correction algorithms aiming to adjust spatial correlation structure. In comparison with these alternatives, the MBC-CycleGAN algorithm reasonably corrects spatial correlations of climate simulations for both temperature and precipitation, encouraging further research on the improvement of this approach for multivariate bias correction of climate model projections.
Additive Manufacturing of AISI 420 Stainless Steel: processes validation, defects analysis and mechanical characterization in different process and post-process conditions.
Authors: Liverani Erica , Fortunato Alessandro 
Published: March 2021

Abstract
Stainless steel (SS) alloys produced by Laser-based Powder Bed Fusion (LPBF) process offers comparable and sometime improved mechanical properties respect to conventionally processed materials. Some of these steels have been extensively studied in the last decade, however additively manufactured martensitic SS, as AISI 420, need further research in characterizing their post built quality and mechanical behaviour. This lack of information on martensitic SS is not consistent with their growing demand in the automotive, medical and aerospace industries due to their good corrosion resistance, high hardness and good tensile properties. Selection of the appropriate process parameters and post treatments plays a fundamental role in determining final properties. For this reason, the effect of LPBF process parameters and different heat treatments on density, defects characteristics and location, roughness and mechanical properties of AISI 420 were investigated in this paper. A first experimental campaign was carried out to establish different set of suitable process parameters for industrial applications. Starting from this result, the detected defects properties was investigated by Computed Tomography (CT) scans. Dimensions, sphericity and distributions of defects inside the volume were analysed and compared between samples manufactured with different parameters. In the second part of the paper, the influence of process and post process conditions on mechanical properties was investigated. The final presented results establish a correlation between the involved production cycle and the resulting properties of LPBF AISI 420 specimens.
Public Trust, Information Sources and Vaccine Willingness Related to the COVID-19&nbsp;Pandemic in a Caribbean Country
Authors: Freitas Loren De , Basdeo Damion , Wang Han-i 
Published: March 2021

Abstract
BackgroundEvaluating public trust and vaccine willingness may contribute to the effectiveness of pandemic response policies and plans. This is particularly important in developing countries, such as those in the Caribbean region. This study aimed to evaluate public trust in information sources, confidence in institutions and COVID-19 vaccine willingness in Trinidad and Tobago. MethodsA cross-sectional online survey was conducted amongst the general population in Trinidad and Tobago from November 10th to December 7th 2020. The survey instrument was a validated questionnaire developed by the World Health Organisation (WHO) and adapted to the local setting. Descriptive statistics and regression analyses were used to analyse the data. ResultsOf the 623 responses analysed, 46.2% thought they were likely to contract COVID-19 while 37.7% considered themselves at high risk of contracting the illness. The most trusted sources of information included health workers (53.9%) and the ministry of health (42.4%). Each one unit increase in trust in the medical sector lowered the odds of believing misinformation and conspiracy theories. Overall, 62.6% of respondents said they would take the COVID-19 vaccine if available and recommended. Regression analyses showed those who agreed that everyone should adhere to the national immunization schedule and those who would take the flu vaccine, were 2.92 (p<0.001) and 3.68 times (p<0.001) as likely to take the vaccine, respectively.ConclusionOur study found that increasing trust in health sources, confidence in medical sector, adherence to the national immunisation schedule and acceptance of the flu vaccine may increase COVID-19 vaccine willingness rates. These results may guide public health response activities and identify areas for prioritisation and improvement.