bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing Ossiointegration And Corrosion Properties of Ti6Al4V Alloy By Coating With Chitosan – Collagen- Hydroxyapatite For Biomedical Applications
Authors: M.Mahdi Adnan , Essa Abbas F. , Khalf Mohammed Kh. 
Published: November 2021

Abstract
In this research, Ti-6Al-4V alloy samples were coated with 4 gm strontium hydroxyapatite with 2 gm from chitosan and (2,4,6) gm from collagen and the samples heat treated at 150 ºC in muffle furnace for one hour under air atmosphere. The sample were tested by XRD,FTIR,SEM and corrosion test was also achieved. The samples were immersed in a laboratory prepared simulated body fluid (SBF) solution for two weeks, the samples treated at 150 ºC in muffle furnace for one hour under air atmosphere to get more bonding for new layer . The samples tested by XRD,FTIR,SEM and corrosion test was also achieved after immersing . The sample coated with 6 gm collagen showed maximum growth of hydroxyapatite formed from simulated body fluid SBF and corrosion characteristics was much improved.
Correlation between Morphological Features of the Anterior Cruciate Ligament: A Quantitative Study Using a Porcine Model
Authors: Wang Huizhi , Zhang Zhuoyue , Shi Qinyi , Zeng Yi-Ming , Cheng Cheng-Kung 
Published: November 2021

Abstract
Background: Inadequate restoration of the rotational knee stability is often reported after ACL reconstruction, mainly due to insufficient restoration of the morphology of the ACL. This study aimed to explore the quantitative correlation between morphological features of the ACL, thus to provide useful information for improving anatomical reconstruction techniques and designing artificial ligaments. Methods: Porcine model was used in this study mainly because the morphology and function of porcine ACLs have been reported to be similar to those of the human ACL. 19 porcine knees (1 year, male) were fixed at full extension using 10% formalin and were dissected to expose the ACL. ACL lengths were measured using a caliper. Mid-substances of the ACL were cut and scanned using X-ray microscopy, and the cross-sectional area (CSA) was measured at the isthmus. Margins of direct and indirect bone insertion sites were distinguished and marked. Measurements were performed on digital photographs to obtain the areas of bone insertions. Statistical analysis using nonlinear regression was used to identify potential correlations among the measurements. Results: The results showed large individual differences on all of the measurements (e.g. the CSA at ACL isthmus ranged from 44.7 to 87.2 mm2, when the area of its femoral and tibial insertion sites ranged from 188.1 and 233.6 mm2 to 258.4 and 412.0 mm2, respectively). The CSA at the isthmus was significantly correlated with the total area of the bone insertion sites and the area of tibial insertion. The area of the tibial insertion was significantly correlated with the area of its direct insertion site. In contrast, the area of the femoral insertion was significantly correlated with the area of its indirect insertion site. The area of the indirect tibial insertion showed a weak correlation with the length of ACL, whereas the length of the ACL was not able to predict or be predicted by any other parameters.Conclusions: The CSA at the ACL isthmus might be more suitable for assessing the morphology of the ACL. However, ACL length has little correlation with the CSA of the isthmus or bone insertion sites, thus should be evaluated independently before surgery.
Identification of important modules and biomarkers that related to immune cell in severe burns based on weighted gene co-expression network analysis(WGCNA)
Authors: zhang zexin , Wang Peng , Yin Bin , Bao Wu , Cheng Xialin , He Yan , Li Shu , Jia Chiyu 
Published: November 2021

Abstract
Background

Immunosuppression is an important factor inducing infection which is a significant cause of death in severe burns. Nevertheless, the prognostic value of immune-related genes are still unclear. This study was conducted to find biomarkers related to immunosuppression in severe burns.
Methods

Here, we download the gene expression profile and clinical data of 185 burns and 75 healthy samples from GEO database. Immune infiltration analysis and gene set variation analysis were utilized to identify the disorder of circulating immune cells. WGCNA was carried out to select immune-related gene modules. Enrichment analysis and protein-protein interaction (PPI) network was performed to select hub genes. Next, lasso and logistic regression was utilized to construct the hazard regression model. Finally, we explored correlation between high and low risk patients in total burn surface area (TBSA), age, and inhalation injury.
Results

In Gene set variation analysis(GSVA) and immune infiltration analysis, neutrophil increased and T cell decreased in severe burns. In WGCNA, four modular that differently expressed in burns and controls were related with immune cells. Based on PPI and enrichment analysis, 210 immune-related genes were identified mainly involved in T cell inhibited and neutrophil activated. In lasso and logistic regression, we screened out key genes, LCK, SKAP1, GZMB and LY9. They are excellent biomarkers of prognosis in burns with AUC: 0.945. Finally, we discovered that key genes were related with T cells and regression model performed well accompanied by TBSA and age.
Conclusion

We found that LCK, SKAP1, GZMB and LY9 were excellent prognostic biomarkers which were likely function for T cell disorder in post-burn immunosuppression and were potential immunotherapeutic targets to convert T cell dysfunction.
Transcriptome Analysis of Sweet Potato Responses To Potassium Deficiency
Authors: Wang Fang , Tan Wen-Fang , Song Wei , Yang Song-Tao , Qiao Shuai 
Published: November 2021

Abstract
Background: Potassium is one of the three essential nutrients and is regarded as a main limited factor for growth and development in plant. Sweet potato (Ipomoea batatas L.) is one of the seven major food crops grown worldwide, and it is both a nutrient-rich food and a bioenergy crop. Sweet potato is a typical “K-favoring” crop, and the level of potassium ion (K+) supplementation directly influences its production. However, little is known about the transcriptional changes in sweet potato genes under low-K+ condition. To uncover the effect of low-K+ stress, we analyzed the transcriptomic profiles of sweet potato roots in response to K+ deficiency.Result: The roots of sweet potato seedlings with or without K+ treatment were harvested and used for transcriptome analyses. The results showed 559 differently expressed genes (DEGs) in low and high K+ groups. Among the DEGs, 336 were upregulated and 223 downregulated. These DEGs were involved in transcriptional regulation, calcium binding, redox-signaling, biosynthesis, transport, and metabolic process. In the result, some new genes were founded that involved in low-K+ stress, which can be further investigated to improve low K+ tolerance in plant. Confirmation of RNA-seq results using qRT-PCR displayed a high level of consistency between the two experiments. Our analysis showed that many auxin-related genes, ethylene-related genes and jasmonic acid-related genes responsed to K+ deficiency, indicated that these hormones may play more important roles in K+ nutrient signaling in sweetpotato. Conclusions: According to the transcriptome data, fewer sweetpotato genes showed transcriptional changes in response to low-K+ stress. However, the expression level of some kinases, transporters, transcription factors, hormone-related genes, and plant defense related genes were markedly changed, suggesting that they play important roles during K+ deficiency. This study identifes potential genes for genetic improvement of low-K+ stress and provides valuable insight into the molecular mechanisms regulating low K+ tolerance in sweet potato. Further research is required to clarify the founction of these significant changed genes under low-K+ stress.
A Method for the Definition of Immunological Non-response to Antiretroviral Therapy Based on Review Analysis and Supervised Classification Model
Authors: Shuai Yong 
Published: November 2021

Abstract
BackgroundImmunological non-response (INR) accelerated the progression of AIDS disease and brought serious difficulties to the treatment of HIV-1 infected people. The current definition of INR lacked a credible consensus, which affected the diagnosis, treatment and scientific research of INR. MethodWe systematically analyzed the open source INR related references, used visualization techniques and machine learning classification models to propose the features, models and criteria that define INR. ResultWe summarized some consensus on the definition of INR. Among the features that defined INR, CD4+ T-cell absolute number and ART time were the best feature to define INR . The supervised learning classification model had high accuracy in defining INR, and the support vector machine (SVM) had the highest accuracy in the commonly used supervised classification learning model. Based on supervised learning model and visualization technology, we proposed some criteria that could help to reach a consensus on INR definition. ConclusionsThis study provided consensus, features, model and criteria for defining INR.
Improving Membrane Filtration Performance Through Time Series Analysis
Authors: Wu Jun Jie 
Published: November 2021

Abstract
For ultrafiltration, and membrane filtration more generally, the quantitative determination of the modes of fouling remains a subject of great interest. Herein a clear method for determining the modes from a time series of volumetric flux J(t) is given and illustrated with previously published filtration data of bergamot juice (Journal of Membrane Science 524 (2017) 108-116). The emphasis is upon the robust methodology which is of general applicability and offers a straightforward approach to the modelling of flux decline. The method is best viewed as being an empirical method that determines the point at which there is a switch from one mode to another is determined in a clear-cut manner and it yields excellent equations for J(t). For the example chosen, the initial 4 L/m2 generates some pore blocking after which the main mode of fouling is cake build-up. The variation of overall resistance with time is also informative and analysis of this series was used to check the result for the initial phase of fouling as determined from the time series of volumetric flux. A strength of the integral approach is that it enables one to establish whether the initial fouling is different in character from the subsequent fouling. Having this information can improve membrane selection and overall membrane filtration performance.
Effects of calorie intake and sampling time on thyroid stimulating hormone concentration
Authors: Dong Aimei , Huang Youyuan , Huang Yucheng , Jia Bing 
Published: November 2021

Abstract
BackgroundThis study aimed to investigate the effects of blood collected after calorie intake on the level of thyroid stimulating hormone (TSH), comparing with the blood collected in fasting state.MethodsThis study was a prospective, randomized, controlled study. Subjects from the outpatients in the department of endocrinology without evident of thyroid diseases were included and then randomized into the fasting group, diet intake group, and glucose intake group, respectively. Fasting blood was collected from all the subjects at 7:00 am for the measurement of TSH and free thyroxine (FT4). Afterward, the subjects were maintained at fasting state (fasting group), had an intake of the mixed diet with the calories of 400 Kcal (diet intake group), and had an intake of 75 g glucose (glucose intake group), respectively, and blood was acquired again 2 h later (9:00 am on the same day) for TSH and FT4 measurement. The levels between 7:00 am and 9:00 am were compared.ResultsOf the 150 subjects, 146 met the inclusion criteria, of which 48, 48, and 50 were in the diet intake group, glucose intake group, and fasting group, respectively. The TSH in the diet intake group was significantly lower at 9:00 am (TSH9am) than the level at 2h before (TSH7am) (P<0.001), of which the median variation was -0.71 mU/L, and the median variation rate was -32.4%. In the glucose intake group, the TSH9am was also significantly lower than TSH7am (P<0.001), of which the median variation was -0.73 mU/L, and median variation rate was -31.5%. While in the fasting group, the TSH9am decreased slightly but statistically significantly lower than TSH7am (P<0.001), of which the median variation was -0.1 mU/L, and the median variation rate was -5.2%. According to TSH7am, 9 subjects in total (3 subjects in each group) met the diagnostic criteria of subclinical hypothyroidism. However, according toTSH9am, only 2 patients in the fasting group still met the diagnostic criteria of subclinical hypothyroidism.ConclusionComparing with the fasting state, the TSH level at 2h after the calorie intake was decreased by about 30%, which could influence the diagnosis of subclinical hypothyroidism.Trial registrationChiCTR2100047454.
Contribution of the Elevated Thrombosis Risk of Males to the Excess Male Mortality Observed in COVID-19: An Observational Study
Authors: Cohen Kenneth R , BSAE David Anderson , Ren Sheng , Cook David J. 
Published: November 2021

Abstract
Background: The mortality rate of COVID-19 is elevated in males compared to females.Objective: Determine the extent that the elevated thrombotic risk in males relative to females contributes to excess COVID-19 mortality in males.Design: Observational study.Setting: Data sourced from electronic medical records from over 200 US hospital systems.Participants: 60,877 patients hospitalized with COVID-19.Exposure: Exposure variable: biological sex; key variable of interest: thrombosis.Main outcome measures: Primary outcome was COVID-19 mortality. We measured: 1) mortality rate of males relative to females, 2) rate of thrombotic diagnoses occurring during hospitalization for COVID-19 in both sexes, and 3) mortality rate when evidence of thrombosis was present.Results: The COVID-19 mortality rate of males was 29.9% higher than that of females. Males had a 35.8% higher rate of receiving a thrombotic diagnosis compared to females. The mortality rate of all patients with a thrombotic diagnosis was 40.0%— over twice that of COVID-19 patients without a thrombotic diagnosis (adjusted OR 2.50 [2.37 to 2.64], p-value < .001). When defining thrombosis as either a documented thrombotic diagnosis or a D-dimer level ≥ 3.0 μg/mL, 16.4% of the excess mortality in male patients could be explained by increased thrombotic risk. Conclusions and Relevance: Our findings suggest the higher COVID-19 mortality rate in males may be significantly accounted for by the elevated risk for thrombosis among males. Understanding the mechanisms that underlie increased male thrombotic risk may allow for the advancement of effective anticoagulation strategies that reduce COVID-19 mortality in males.
Comparative analysis and epidemiological study of SARS-CoV-2 in first wave among different states of India
Authors: Kaushik Rakesh , Nikita  , Rishabh  , Lugani Yogita , Lata Suman 
Published: November 2021

Abstract
SARS-CoV-2 has now spread worldwide, and various governments are attempting to control the disease's spread before it becomes a global health crisis. Data from 28 Indian states and 8 Union Territories (UTs) provides a detailed look at the transmission pathways and case fatality rate (CFR) of the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). The case fatality ratios were calculated in each zone of India i.e. Central, Eastern, North Eastern, and Northern, Southern and Western zone. Moreover, the CFR was calculated in different periods of month. The CFR wassignificantly higher (P<0.01) in April to June period of 2020. The period of month had significantly different (P<0.01) on CFR. CFR was compared in different zones in India, western zone showed highest CFR as compared to other zones. The effect of Covid-19 was compared with different age groups and co-morbidities patients. This analysis showed that the mortality in Maharashtra was higher because of the poor adherence to the safety norms and due to the most visited and crowded place of India.
Atherogenic index of plasma is an independent predictor of ultrasound-proven nonalcoholic fatty liver disease among non-obese populations.
Authors: Ye Hua-Jun , Chen Xu-Yan , Huang Zhi-Ming , He XiXi 
Published: November 2021

Abstract
Background & Aims: Evidence regarding the association between atherogenic index of plasma (AIP) and the risk of non-alcoholic fatty liver disease (NAFLD) in non-obese populations is limited. Our study aimed to investigate whether AIP predicts NAFLD in non-obese Chinese populations.Methods: The present study was a population-based longitudinal study, including 16 173 non-obese participants who underwent health examinations in a tertiary hospital from January 2010 to December 2014. The primary outcome was developing NAFLD during the follow-up period. Results: The mean age of the included participants was 43.2 ± 15.0 years old, and about 52.5% of them were male. During the follow-up period, 2 322 of 16 173 (14.3%) participants developed NAFLD. In the fully-adjusted model, for every one standard deviation increased in AIP levels, the incidence of NAFLD increased by 52% (1.52, 95%CI 1.43, 1.60). The optimal cut-off point of AIP for incident NAFLD was 0.00 (receiver operator characteristic 0.76 [95% CI 0.75–0.77], sensitivity 0.68, specificity 0.72). Individuals with AIP values in the positive range had two-fold increased odds of developing NALFD compared with those with values in the negative range. After propensity score matching, for every one-SD increased in AIP levels, the incidence of NAFLD increased by 34% (HR 1.34, 95%CI 1.27, 1.41). Conclusion: AIP is an independent predictor of incident NAFLD among Chinese non-obese populations.
Load-Settlement Response of A Footing Over Buried Conduit in A Sloping Terrain: A Numerical Experiment-Based Artificial Intelligent Approach
Authors: Khan Muhammad Umer Arif , Shukla Sanjay Kumar , Raja Muhammad Nouman Amjad 
Published: November 2021

Abstract
Settlement estimation of a footing located over a buried conduit in a sloping terrain is a challenging task for practicing civil/geotechnical engineers. In the recent past, the advent of machine learning technology has made many traditional approaches antiquated. This paper investigates the viability, development, implementation, and comprehensive comparison of five artificial intelligence-based machine learning models, namely, multi-layer perceptron (MLP), Gaussian processes regression (GPR), lazy K-Star (LKS), decision table (DT), and random forest (RF) to estimate the settlement of footing located over a buried conduit within a soil slope. The pertaining dataset of 3600 observations was obtained by conducting large-scale numerical simulations via the finite element modelling framework. After executing the feature selection technique that is correlation-based subset selection, the applied load, total unit weight of soil, constrained modulus of soil, slope angle ratio, hoop stiffness of conduit, bending stiffness of conduit, burial depth of conduit, and crest distance of footing were utilized as the influence parameters for estimating and forecasting the settlement. The predictive strength and accuracy of all models mentioned supra were evaluated using several well-established statistical indices such as Pearson’s correlation coefficient (r), root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), scatter index (SI), and relative percentage difference (RPD). The results showed that among all the models employed in this study, the multi-layer perceptron model has shown better results with r, RMSE, NSE, SI, and RPD values of (0.977, 0.298, 0.937, 0.31, and 4.31) and (0.974, 0.323, 0.928, 0.44 and 3.75) for training and testing dataset, respectively. The sensitivity analysis revealed that all the selected parameters play an important role in determining the output value. However, the applied load, constrained modulus, unit weight, slope angle ratio, hoop stiffness have the highest strength with the relative importance of 18.4%, 16.3% and 15.3%, 13.8%, 11.4%, respectively. Finally, the model was translated into a functional relationship for easy implementation and can prove useful for practitioners and researchers in predicting the settlement of a footing located over a buried conduit in a sloping terrain.
Preloading Effect On The Strength of Cement Mass Mixing Treated Salty Sand
Authors: Alipour Rasoul 
Published: November 2021

Abstract
Existing problematic sub-layers in mixing technologies are a challenge, and for the first time, the effects of salt sub-layers in mass mixing technology have been investigated in this study for sandy salt in the southwest of Iran. This paper discusses the influence of adding various cement contents, Aw, and imposing different preloading values on the salty sand soil. First, salt and sand samples were dried, then, 90 % sand was mixed with 10% salt. After that, 30 % water was mixed thoroughly with the mixture of salty sand to obtain slurries. Cement slurry at a water-cement ratio (w/c) of 0.6 was then added to the sample and thoroughly mixed. The amount of cement in a slurry form that was added to the salty soil was 2, 4, 6, 8, and 10% by mass of dry soil. Each treated soil preloaded by 0, 9, and 45 kPa. After 120 days, the unconfined compressive strength of the sample was determined. Furthermore, by Scanning Electronic Microscope, SEM, the microstructures of treated samples were analyzed. At the end Unconfined Compression Strength, UCS, test results normalized to the non-preloaded treated soil. By increasing cement content, the effect of preloading in increasing UCS will decrease. In the SEM images for Aw=2%, the effect of preloading indicates porous shape for non-preloaded samples. Vice versa by Aw=8%, porous shape in the SEM images will disappear. In the end, treatability studies of pure salt in the thick layer have been investigated.
The Effect of Education Based Health Belife Model on Preventive Behaviors of Mother About Iron Deficiency Anemia in Children: Aneducational Controlled Trial
Authors: larijani Mohammadzadeh , Khorsandi Mahboobeh , Shamsi Mohsen , Ranjbaran Mehdi 
Published: November 2021

Abstract
BackgroundIron deficiency anemia (IDA) is the most common hematological disease in infancy and childhood. Therefore, it is necessary to provide maternal education using models that identify factors affecting behavior. Hence, this study was conducted to evaluate the effect of maternal education based on the health belief model (HBM) on preventive behaviors of IDA in children aged 1-6 years in rural health centers of Babol, Mazandaran Province, Iran in 2015.MethodsIn this randomized controlled trial, 119 mothers were selected through multi-stage random sampling and divided into two groups of intervention and control. The data collection tool was a researcher-made questionnaire whose validity and reliability were studied and confirmed. A pretest was conducted in both groups. Need assessment was done according to the pretest results, and educational intervention was performed in four educational sessions in the intervention group. The same questionnaire was applied for posttest three months after the intervention. SPSS version 20 was used for data analysis.ResultsThere was no significant difference in the mean scores of awareness, HBM constructs, and performance of the mothers between the two groups before the intervention (P>0.05) while the difference was significant after the intervention (P<0.001). The mean score of performance, increased significantly from 80.84 to 88.68 in the intervention group after the intervention (P<0.001).ConclusionEducational intervention, according to the HBM based on a primary needs assessment effectively improves maternal performance about IDA prevention in children. Therefore, it is suggested that these interventions replace conventional educational programs.Trial registration: This trial has been registered at IRCT, IRCT2014082118892N1. Registered on 2014-11-23, https://en.irct.ir/trial/17015