bluuebunny/crossref_metadata_2025_split huggingface dataset:
WITHDRAWN: Comparative study of the effect of sliver and selenium nanoparticles on bacterial and viral hepatic infection via modulating oxidative stress and DNA fragmentation
Authors: Gad Sameh S. , ibrahim sherine , Ismail Sameh H. , Abdelrahim Dina S. 
Published: May 2021

Abstract
Background: Nanoparticles are recently playing a potential role in improving drug uptake and the and treatment of diseases. A variety of nanoparticles, such as selenium nanoparticles (SeNPs) and Silver nanoparticles (AgNPs) have been used as drug carriers in various ways for treatment of cancers and liver diseases. Our aim in this study is to investigate the ability of AgNPs and SeNPs to target and treat the viral and bacterial infection of liver in rats and cell lines.Methods: For assessment of antioxidant activity of silver nanoparticles, six adult male albino rats were included in this study, liver slices were taken and assigned to 6 groups. Markers of hepatic functions, oxidative stress and inflammation in liver slices are carried out. While for assessment of antiviral activity of SeNPs, HBV-replicating human cell line HepG2 and normal human cell lines were used, hepatic and inflammatory alterations are determined through quantitative polymerase chain reaction (PCR) and comet assay techniques.Results: The effect of Ag-NPs on interleukin-6 (IL-6) and tumor necrosis factor (TNF-α) levels were reduced in different treated groups with Ag-NPs compared with the control and diseased groups. On the other hand, SeNPs revealed significant alterations in the inflammatory markers as well as DNA damage in the treated HBV- human cell line HepG2 compared to the diseased ones.Conclusion: Silver nanoparticles have the ability for producing various hepatic alterations and can inhibit the proliferation of hepatic stellate cells (HSCs) in a dose and size dependent manner. On the other hand, SeNPs showed excellent selectivity towards viral cells in the HepG2 cell lines. Both Ag-NPs and SeNPs might be a promising drug design for treating viral and bacterial liver diseases.
Clinical and CT scan findings in patients with COVID-19 pneumonia: A comparison based on disease severity
Authors: Hesam-Shariati Sonia , Mohammadi Susan , Abouzaripour Morteza , Mohsenpour Behzad , Zareie Bushra , Fathi Fardin , Sheikholeslomzadeh Hana , Rajabi Fahimeh , Shariati Mohammad Bakhtiar Hesam 
Published: May 2021

Abstract
Background

The SARS-CoV-2 can cause severe pneumonia and highly impact general health. We aimed to investigate different clinical features and CT scan findings of patients with COVID-19 based on disease severity to have a better understanding of this disease.
Methods

90 patients with coronavirus were divided into three categories based on the severity of the disease: mild/moderate, severe, and very severe. Clinical, laboratory and CT scan findings of the patients were examined retrospectively. Any association between these features and disease severity were assessed.
Results

The mean age and duration of hospitalization of patients increased with increasing the severity of disease. The most common clinical symptoms were shortness of breath, cough, and fever. As the severity of the disease increased from mild/moderate to very severe, there was an increase in neutrophile counts and a decrease in lymphocytes and white blood cells (WBC) showing excessive inflammation associated with severe forms of COVID-19. Subpleural changes (81%) and ground-glass opacification/opacity (GGO) lesions (73%) of the lung were the most common features among CT images of COVID-19 patients, and interlobular septal thickening (10%) was the lowest CT feature among patients. Regarding the affected parts of the lung in COVID-19 patients, bilaterial, peripheral and multiple lesions had the highest prevalence.
Conclusions

It has been shown that clinical, laboratory and CT scan findings varied in COVID-19 patients based on disease severity, which need to be considered carefully in timely diagnosis and treatment of this illness.
Effects of medication knowledge on medication adherence among hypertensive patients at Matero level one hospital, Lusaka City, Zambia: A cross sectional study
Authors: Kampamba Martin , Abanur Farhiyyah , Hikaambo Christabel Nang’andu , Mudenda Steward , Saini Kennedy , Kaonga Patrick 
Published: May 2021

Abstract
Background: Medication adherence is the mainstay to good treatment outcomes. Failure to adhere to medication in hypertensive patients may lead to considerable deterioration of the disease resulting in increased costs of healthcare and mortality. Knowledge about the name of the drug, indications and side effects may enhance medication adherence. Therefore, the aim of this study was to assess effects of medication knowledge on medication adherence among hypertensive patients. Methods: This was a cross-sectional study that involved 120 hypertensive patients. A structured questionnaire was used to collect data on demographic characteristics. Adherence was assessed using the 8-item Morisky Medication Adherence Scale while patient’s medication knowledge was assessed using a 7-item scale. Multiple logistic regression was used to assess factors associated with medication adherence. Results: The mean age of participants was 59 years (SD ±14.9) and 10 (8.3%), 42 (35%) and 68(56.7%) had adequate, average and poor medication knowledge respectively. The prevalence of adherence in this study was 37.5%. In multivariable logistic regression analysis, uncontrolled blood pressure (BP) (AOR: 0.38, CI: 0.16-0.90) was associated with lower likelihood of adhering to medication.Conclusion: The adherence level to treatment was low and medication knowledge of hypertensive patients was generally poor. Uncontrolled BP was associated with non-adherence. Patients with uncontrolled hypertension should be given health education and counselling regarding their condition to improve medication adherence.
Evaluating the Potential of Respiratory-sinus-arrhythmia Biofeedback for Reducing Physiological Stress in Adolescents With Autism: Study Protocol for a Randomized Controlled Trial
Authors: Thoen Anoushka , Steyaert Jean , Alaerts Kaat , Damme Tine Van 
Published: May 2021

Abstract
Background: Prior evidence points towards lower cardiac vagal modulation in individuals with Autism Spectrum Disorder (ASD) as compared to control groups. A cross-sectional phase in this study will gather more evidence concerning this topic. A longitudinal phase will explore the efficacy of a biofeedback intervention based on Respiratory Sinus Arrhythmia (RSA) in adolescents with ASD. Finally, a feasibility study will focus on a non-supervised RSA biofeedback intervention in this population.Methods: The cross-sectional phase includes the comparison of adolescents with ASD (n=38) and age and gender matched typically developing peers. A standardized assessment will be used which contains physiological, cortisol and behavioral measurements. The longitudinal phase contains a randomized, single-blinded and sham-controlled design to determine the efficacy of supervised RSA biofeedback in adolescents with ASD (n=128). A follow-up phase of 5 weeks is included to evaluate the presence of retention effects. During the latter, a feasibility study will focus on a non-supervised intervention (n=64). Assessments as described previously are scheduled after the intervention and the follow-up phase. Discussion: First, more conclusive evidence will be provided for the presence of lower cardiac vagal modulation in adolescents with ASD as well as the association between these lower values and physiological and behavioral indices. Second, the supervised intervention in adolescents with ASD is hypothesized to upregulate this cardiac vagal modulation and positively change behavioral and physiological parameters. Third, evidence regarding the feasibility and acceptability of a non-supervised intervention may open novel avenues for home-based interventions in this population. Trial registration: ClinicalTrials.gov, NCT04628715. Registered on 13 November 2020. https://clinicaltrials.gov/ct2/show/NCT04628715
Influence of Extrusion Temperature on Property of Graphene Oxide-carbon Fiber Hybrid Reinforced Resin Matrix Composites
Authors: Ma Yuqin , Li Fei , Xu Wei , Yan Long , Guo Haiyin , Li Yatao , Cui Mingtao , Jin Hao 
Published: May 2021

Abstract
The graphene oxide-carbon fiber hybrid reinforced resin matrix (GO-CF/EP) composites were prepared by vacuum infiltration hot-pressing molding process. The effects of extrusion temperature on the microstructure, fracture mechanism and mechanical properties of GO-CF/EP composites were investigated by setting different extrusion temperatures. In the experiments, the extrusion temperature was controlled as 30℃, 40℃, 50℃, 60℃ and 70℃ respectively. It was found that the best mechanical property of composites and infiltration effect of matrix in the fiber gap were obtained at the temperature of 50℃. The bending strength of the material reached 977 MPa through the performance test. The results showed the matrix viscosity was high and the fluidity was poor when the extrusion temperature was low. Poor penetration of the matrix resulted in a large number of fibers failing to bond together. The stress was difficult to transfer to other fibers through the matrix and the strengthening effect of graphene oxide (GO) was weak when the composite was subjected to external force. This phenomenon led to poor mechanical properties of composites. Under the condition of higher temperature, the flow speed of the matrix and the curing speed of composites could be improved. As a result, some of the matrix was solidified in advance while being pressed out, which led to cracks and other defects in the process of loading and affects the mechanical properties of the composites. However, the mechanical properties of the composites with higher extrusion temperature were better than those with lower extrusion temperature due to the existence of graphene oxide in the fiber gap.
Synchrotron mechanism of X-ray and gamma-ray emissions in lightning and spark discharges
Authors: Petrov Nikolai 
Published: May 2021

Abstract
X-ray and γ-ray emissions observed in lightning and long sparks are usually connected with the bremsstrahlung of high-energy runaway electrons. Here, an alternative physical mechanism for producing X-ray and gamma-ray emissions caused by the polarization current and associated electromagnetic field moving with relativistic velocity along a curved discharge channel has been proposed. The existence of fast electromagnetic surface waves propagating along the lightning discharge channel at a speed close to the speed of light in vacuum is shown. The possibility of the production of microwave, X-ray and gamma-ray emissions by a polarization current pulse moving along a curved path via synchrotron radiation mechanism is pointed out. The existence of long tails in the power spectrum is shown, which explains observations of photon energies in the range of 10-100 MeV in the TGF, as well as measured power spectrum of laboratory spark discharge.
Application of Variance Components Modelling Approach to Tanzania Demographic and Health Survey Data; Identifying Determinants of Modern Contraceptive Uptake
Authors: Safari Oliva , Bishanga Dunstan R. , Sailon Isambi 
Published: May 2021

Abstract
Background: Over time, Demographic and Health Survey (DHS) data remain valuable to examine variables relating to nationally representative population for low- and middle-income countries. In Tanzania, there are very limited DHS-based studies on the uptake of Modern Contraceptive Use (MCU). Present studies were focused on individuals’ levels measurements, yet research have shown the MCU variations still exists to other levels of populations. In this study, we aimed to use the variance component modelling approach to explore variation on MCU at PSU and region levels while considering survey sample weighting. Methods: Using DHS 2016-2017 in Tanzania, we study various variance structure and the respective variation on MCU to more than 5174 Women of Reproductive Age (WRA) 15-49 years. Firstly, a single variance component was used, followed by its extension to random coefficient model and we tracked changes in the models. Results: There was an influence of random variations on MCU on the levels of populations much explained by PSU-level clustering than region. On the fixed part, age of a woman, education level, husband education level, desire to have children, exposure to media and wealth index were the important determinant for MCU among WRA in Tanzania. For example, the odds of MCU among middle ages women (20-29 and 30-39) were 29% and 90%. Also, odds of MCU increases with an increase to media exposure and primary and secondary school women had higher chances for MCU. We also found assessing effects of covariates at two different nested levels eventually resulted in different estimates.Conclusion: This study highlighted on utility of accounting for variance structures in addressing various sources of variations on MCU while using DHS national level data. Apart from MCU, the TDHS data has been widely applied to examined other variables pertaining to public health issue. Thus, this approach could be considered a better modelling technique for the DHS studies.
Study on Preparation of Brick Blocks by Using Construction Waste and Sludge
Authors: Vaithiyasubramanian Raguraman , Sriniva Deepasree , Kanagarajan Arul Kumar 
Published: May 2021

Abstract
Sewage waste is a crucial factor in the disposal and also harmful to the environment. The growing demand for waste utilization is construction and demolition waste. This study aims in preparing a brick using construction and demolition waste and sludge waste. The materials such as fly-ash, cement, construction, and demolition waste, and sludge waste are used. The sludge content was added at constant percentage of 30%, 40% and 50% with different proportions such of fly-ash, cement and demolition waste of 3:2:2, 1:3:2, 2:1:2, 2:3:2, 2:3:1, 2:2:1, 2:2:3, 3:2:1, and 1.5:1.5:2 respectively. The physical characteristics such as compressive strength, bulk density, and chemical characterization such as water absorption, pH, and detection of heavy metals were carried out. The test results infer that increase in the content of sludge, the strength decreased. Maximum compressive strength of 14.5 Mpa was achieved for the ratio of 2:3:2 at 30% of sludge. The maximum bulk density was achieved at 30% of sludge. This was attributed due to the presence of organic properties in the brick. Moreover, the water absorption increases with an increase in the percentage of sludge.
Effect of Aqueous Extract of Trigonella Foenum-Graecum L. Seeds On Acetic Acid- Induced Ulcerative Colitis In Rats
Authors: Fathima Aqsa , Gangachannaiah Shivaprakash , Bose Ujjal , K Shama Prasada , Chakraborty Rituparna , E Praveen Kumar S , Udupa Padmanabha E G , Yadav Rachagolla Sai Pratap , Monappa Vidya 
Published: May 2021

Abstract
Ulcerative colitis is an inflammatory disorder affecting colonic mucosa, characterized by intense inflammation and mucosal damage. The currently available medical treatment is not completely safe and effective in alleviating the disease manifestations and its complications. The present study aimed to evaluate the protective effect of herbal product Trigonella foenum-graecum L. (TFG) seeds in acetic acid induced Ulcerative colitis (UC) in rats. The TFG extract was administered orally at two doses of 500 and 1000 mg/kg body weight. Compared to UC group, the TFG treated group showed significantly reduced severity of the disease as indicated by decreased Disease Activity Index (DAI) and decreased intensity of mucosal inflammation as indicated by macroscopic and histological scoring. Furthermore, biochemical assessment showed increased total protein, reduced glutathione (GSH), catalase (CAT), superoxide dismutase (SOD), and decreased malonaldehyde (MDA) and pro-inflammatory cytokine TNF-α levels in TFG treated group compared to the UC group. The study demonstrates the beneficial effect of TFG in UC by its natural anti-inflammatory and antioxidant properties.
Observation of Anderson localization beyond the spectrum of the disorder
Authors: Dikopoltsev Alex , Weidermann Sebastian , Kremer Mark , Steinfurth Andrea , Sheinfux Hanan Herzig , Szameit Alexander , Segev Mordechai (Moti) 
Published: May 2021

Abstract
Anderson localization is a fundamental wave phenomenon predicting that transport in a 1D uncorrelated disordered system comes to a complete halt, experiencing no transport whatsoever. However, in reality, a disordered physical system is always correlated, because it must have a finite spectrum. Common wisdom in the field states that localization is dominant only for wavepackets whose spectral extent resides within the region of the wavenumber span of the disorder. Here, we experimentally observe that Anderson localization can occur and even be dominant for wavepackets residing entirely outside the spectral extent of the disorder. We study the evolution of waves in synthetic photonic lattices containing bandwidth-limited (correlated) disorder, and observe Anderson localization for wavepackets of high wavenumbers centered around twice the mean wavenumber of the disorder spectrum. Likewise, we predict and observe Anderson localization at low wavenumbers, also outside the spectral extent of the disorder, and find that localization there can be as strong as for first-order transitions. This feature is universal, common to all Hermitian wave systems, implying that low-wavenumber wavepackets localize with a short localization length even when the disorder is strictly at high wavenumbers. This understanding suggests that disordered media should be opaque for long-wavelengths even when the disorder is strictly at much shorter length scales. Our results shed light on fundamental aspects of physical disordered systems and offer avenues for employing spectrally-shaped disorder for controlling transport in systems containing disorder.
Numerical Simulations of Carrier-selective Contact Silicon Solar Cells: Role of Surface Passivation and Carrier-Selective Layers Electronic Properties
Authors: SINGH KRISHNA , Singh Dipak Kumar , Komarala Vamsi K. 
Published: May 2021

Abstract
Ag/ITO/MoOx/n-Si/LiFx/Al carrier-selective contact (CSC) solar cell structures are modelled and numerically simulated based on the experimental data using an industrial quality base silicon wafer by the Sentaurus TCAD software. The role of (1) electron-selective lithium fluoride (LiFx) layer and its thickness, (2) hole-selective molybdenum oxide (MoOx) work function variation, and (3) front contact (MoOx/n-Si) surface passivation interlayer are explored on the device performance. The electron-selective LiFx layer at the rear side is led to the strong enhancement in device photocurrent by providing the electrical barrier to the minority carriers (holes) and slight improvement in open-circuit voltage, but the thickness of the layer is sensitive to efficient extraction of the majority carriers (electrons). The hole-selective MoOx layer work function needs to engineer for inducing the strong inversion layer with better built-in potential at the MoOx/n-Si junction to achieve high open-circuit voltage from a cell. A thin SiOx interlayer at the MoOx/n-Si junction has enhanced the device open-circuit voltage significantly by minimizing the minority carrier recombination at the interface.
A prehospital diagnostic algorithm for strokes using machine learning: a prospective observational study
Authors: Hayashi Yosuke , Shimada Tadanaga , Hattori Noriyuki , Shimazui Takashi , Yoshida Yoichi , Miura Rie E. , Yamao Yasuo , Abe Ryuzo , Kobayashi Eiichi , Iwadate Yasuo , Nakada Taka-aki 
Published: May 2021

Abstract
High precision is optimal in prehospital diagnostic algorithms for strokes and large vessel occlusions (LVOs). We hypothesized that prehospital diagnostic algorithms for strokes and their subcategories using machine learning could have high predictive value. Consecutive adult patients with suspected stroke as per emergency medical service personnel were enrolled in a prospective multicenter observational study in 12 hospitals in Japan. Five diagnostic algorithms using machine learning, including logistic regression, random forest, support vector machine, and eXtreme Gradient Boosting (XGBoost), were evaluated for stroke and subcategories including acute ischemic stroke (AIS) with/without LVO, intracranial hemorrhage (ICH), and subarachnoid hemorrhage (SAH). Of the 1446 patients in the analysis, 1156 (80%) were randomly included in the training cohort and 290 (20%) were included in the test cohort. In the diagnostic algorithms for strokes using XGBoost had the highest diagnostic value (test data, area under the receiver operating curve [AUROC] 0.980, confidence interval [CI; 0.962–0.994]). In the diagnostic algorithms for the subcategories using XGBoost had a high predictive value (test data, AUROC [CI], AIS with LVO 0.898 [0.848–0.939], AIS without LVO 0.882 [0.836–0.923], ICH 0.866 [0.817–0.911], SAH 0.926 [0.874–0.971]). Prehospital diagnostic algorithms using machine learning had high predictive value for strokes and their subcategories.
Does Obesity Affect Patient-Reported Outcomes Following Total Knee Arthroplasty?
Authors: Baghbani-Nagadehi Fatemeh , Armijo-Olivo Susan , Prado Carla M , Gramlich Leah , Woodhouse Linda J. 
Published: May 2021

Abstract
Background: Obesity is a common risk factor for the onset and progression of osteoarthritis (OA). There is also an existing perception that obesity has a negative impact on clinical outcomes following total knee arthroplasty (TKA). We investigated the association between different obesity classes with patient-reported outcomes among patients who underwent TKA.Methods: We performed retrospective secondary analyses on data extracted from Alberta, Canada, total joint replacement data repository. Patients who underwent primary unilateral TKA between 2012–2016 and who completed the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index (N = 7,714), and the patient reported EuroQol-5D (EQ-5D; N = 3,848) were included in the study. Patients had WOMAC and EQ5D scores measured at baseline in addition to 3 and/or 12 months following TKA. Patients were stratified into five body mass index (BMI) groups of normal, overweight, BMI class I, BMI class II, and BMI class III. The association between BMI and mean changes in WOMAC subscales (pain, function, and stiffness) and EQ-5D-5L index over the time intervals of baseline to 3 months or 3 to 12 months was assessed using linear mixed-effects models that were adjusted for age, sex, length of surgery, comorbidities, and zone of the service.Results: Mean age was 65.5 years (SD = 8.7). Postoperatively, there was a significant improvement (p < 0.001) in WOMAC subscales of patient-reported pain, function, and stiffness, as well as EQ-5D-5L regardless of BMI group. Although, patients in BMI class II and class III reported significantly improved pain 3 months after TKA compared to those with normal BMI, all BMI groups attained similar level of pain reduction at 12 months. The greatest improvement in all WOMAC subscales, as well as EQ5D index, occurred between baseline and 3 months (adjusted p < 0.0001).Conclusion: The findings indicate that patients reported improved pain, function, and stiffness across all BMI groups following TKA. Patients with BMI classified as obese reported similar benefits to those with BMI classified as normal weight. These results may help health care providers to discuss expectations regarding the TKA recovery in terms of pain, function, and quality of life improvements with their TKA candidates.