bluuebunny/crossref_metadata_2025_split huggingface dataset:
Therapeutic approach with commercial supplements for pantothenate kinase-associated neurodegeneration with residual PANK2 expression levels.
Authors: Álvarez-Córdoba Mónica , Reche-López Diana , Cilleros-Holgado Paula , Talaverón-Rey Marta , Villalón-García Irene , Povea-Cabello Suleva , Suárez-Rivero Juan M , Suárez-Carrillo Alejandra , Munuera-Cabeza Manuel , Piñero-Pérez Rocío , Sánchez-Alcázar José A 
Published: May 2022

Abstract
Blackground: Neurodegeneration with brain iron accumulation (NBIA) is a group of rare neurogenetic disorders frequently associated with iron accumulation in the basal nuclei of the brain characterized by progressive spasticity, dystonia, muscle rigidity, neuropsychiatric symptoms, and retinal degeneration or optic nerve atrophy. Pantothenate kinase-associated neurodegeneration (PKAN) is one of the most widespread NBIA subtypes. It is caused by mutations in the gene of pantothenate kinase 2 (PANK2) that result in dysfunction in PANK2 enzyme activity, with consequent deficiency of coenzyme A (CoA) biosynthesis, as well as low levels of essential metabolic intermediates such as 4′-phosphopantetheine, a necessary cofactor for essential cytosolic and mitochondrial proteins. Methods: In this manuscript, we examined the therapeutic effectiveness of pantothenate, panthetine, antioxidants (vitamin E and omega 3) and mitochondrial function boosting supplements (L-carnitine and thiamine) in mutant PANK2 cells with residual expression levels. Results: Commercial supplements, pantothenate, pantethine, vitamin E, omega 3, carnitine and thiamine were able to eliminate iron accumulation, increase PANK2, mtACP, and NFS1 expression levels and improve pathological alterations in mutant cells with residual PANK2 expression levels.Conclusion: Our results suggest that several commercial compounds are indeed able to significantly correct the mutant phenotype in cellular models of PKAN. These compounds alone or in combinations are of common use in clinical practice and may be useful for the treatment of PKAN patients with residual enzyme expression levels.
Robust record high Tc elemental superconductivity in titanium
Authors: Zhang Changling , He Xin , Liu Chang , Li Zhiwen , Lu Ke , Zhang Sijia , Feng Shaomin , WANG Xiancheng , Peng Yi , Long Youwen , Yu Richeng , Wang Luhong , Prakapenka Vitali , Chariton Stella , Li Quan , Liu Haozhe , Chen Changfeng , Jin Changqing 
Published: May 2022

Abstract
Searching for superconductivity in single element with high Tc is of great interest both for fundamental science & potential applications due to the easy recipe. It is especially interesting to explore high Tc superconductivity in transition metal elements wherein the conventional BCS theories suggest that d electrons are not favorable to form high Tc superconducting state. Here we report discovery of surprisingly robust superconductivity up to 310 GPa with almost constant Tc above 20K in a wide pressure range from 108GPa to 240 GPa in titanium. The maximum Tconset above 26 K and zero-resistance Tczero of 21 K are record-high values hitherto achieved among elemental superconductors. This finding is in sharp contrast to the theoretical predications based on the pristine electron-phonon coupling scenario. Measured normal state conductivity reveals significant s-d scattering. Quantum calculations show strong s-d transfer and d-band dominance, indicating correlation driven contributions to the robust high-Tc superconductivity seen in dense titanium. Different from most high-Tc superconductors that are either complex ceramic or intermetallic compounds, titanium metal is much easier to process and hosts notably higher and more robust Tc and critical magnetic field Hc compared to the widely used superconducting NbTi alloy. This study opens a fresh promising avenue for rational design and discovery of high-Tc superconductors among simple materials via pressure tuned unconventional mechanism.
Effect of Co2 on Growth Parameters and Lipid Production in Dunaliella Sp. ABRIINW-I1 (Chlorophyceae) Isolated from Urmia Lake, NW Iran
Authors: Mirzahasanlou Jamileh Panahy , Hejazi Mohammad Amin 
Published: May 2022

Abstract
Today, using CO2 in microalgae cultures has been increasing for different purposes. In addition, there are many indigenous strains of algae with the advantage of adaptation to the regional climate condition. The main objective of this study was to evaluate the CO2 effect on growth pattern and biochemical composition of Dunaliella sp. ABRIINW-I1 native to Urmia Lake. Results showed that using CO2 in culture not only affects the biomass concentration (1.06 g.l− 1 AFDW vs 0.54 g.l− 1 in control experiment) and growth period (reaching to the stationary phase in 7 days rather than 14 days in control experiment), but also affect the chemical composition. It seems that during the cultivation time, the lipid content increased in cost of carbohydrates (33.1%DW). Fatty acid analysis revealed optimal combination of saturated and unsaturated acids with the dominance of C16 and C18 fatty acids. Our results confirmed the biodiesel potential and nutritional values of the studied strain especially in treatment with CO2. Results demonstrated that the cost and energy demand could be reduced via CO2 application in algal culture.
Using Google Earth Engine for the complete pipeline of temporal analysis of NDVI in Chitwan National Park of Nepal
Authors: PRASAI RITIKA 
Published: May 2022

Abstract
Advent of cloud computing and Google Earth Engine has completely changed the way we acquire, manage and process large satellite data. Here, we analyze temporal dynamics of vegetation productivity in Chitwan National Park, Nepal (CNP) for the period of 1988 to 2020 using Google Earth Engine (GEE) Python API, without using local computer for data storage or analysis. Specifically, we computed normalized difference vegetation index (NDVI) from Landsat data and analyzed the time-series NDVI using a Thiel Sen estimator and by decomposing it to the trend and season components We completed remote sensing analyses including image retrieval, image analysis, classification and report generation in GEE Python API, which is a free resource. Our results showed that NDVI in CNP increased at the rate of 0.0006/year (p<0.05, R2= 0.66). We observed variation in NDVI during pre-monsoon (p<0.05, R2=0.79) and monsoon (p<0.05, R2=0.79) seasons which were 0.0005/ year and 0.0007/year, respectively. An annual increase in NDVI value in CNP indicates an increase in primary productivity that is assumed to support higher animal species richness. Using NDVI in GEE Python API proved to be an effective and efficient tool for monitoring the primary productivity of ecologically important sites such as protected areas.
A novel diagnostic model for insulinoma
Authors: Wang Feng , Yang Zhe , Chen XiuBing , Peng Yiling , Jiang HaiXing , Qin ShanYu 
Published: May 2022

Abstract
The aim is to describe a simple and feasible model for the diagnosis of insulinoma. This retrospective study enrolled 37 patients with insulinoma and 44 patients with hypoglycemia not due to insulinoma at the First Affiliated Hospital of Guangxi Medical University. General demographic and clinical characteristics; hemoglobin A1c (HbA1c), insulin and C-peptide concentrations; and the results of 2-hour oral glucose tolerance tests (OGTT) were recorded, and a logistic regression model predictive of insulinoma was determined. Body mass index (BMI), HbA1c concentration, 0-hour C-peptide concentration, and 0-hour and 1-hour plasma glucose concentrations (P < 0.05 each) were independently associated with insulinoma. A regression prediction model was established through multivariate logistics regression analysis: Logit p = 7.399+(0.310×BMI) - (1.851×HbA1c) - (1.467×0-hour plasma glucose) + (1.963×0-hour C-peptide) - (0.612×1-hour plasma glucose). Using this index to draw a receiver operating characteristic (ROC) curve, the area under the curve (AUC) was found to be 0.957. The optimal cut-off value was − 0.17, which had a sensitivity of 89.2% and a specificity of 86.4%. Logit P≥-0.17 can be used as a diagnostic marker for predicting insulinoma in patients with hypoglycemia.
Tunable plasmonic tweezers based on graphene nano-taper for neuroblastoma extracellular vesicles manipulation
Authors: Khorami Ali Asghar , Barahimi Behdad , Vatani Sare , Javanmard Athar Sadat 
Published: May 2022

Abstract
We take advantage of graphene nano-taper plasmons to design tunable plasmonic tweezers for neuroblastoma extracellular vesicles manipulation. It consists of Si/SiO2/Graphene stack topped by a microfluidic chamber. Using plasmons of isosceles-triangle-shaped graphene nano-taper with a resonance frequency of 6.25 THz, the proposed device can efficiently trap the nanoparticles. The plasmons of graphene nano-taper generate a large field intensity in the deep sub-wavelength area around the vertices of the triangle. We show that by engineering the dimensions of the graphene nano-taper and an appropriate choice of its Fermi energy, the desired near-field gradient force for trapping can be generated under relatively low-intensity illumination of the THz source when the nanoparticles are placed near the front vertex of the nano-taper. Our results show that the designed system with graphene nano-taper of L = 1200 nm length and W = 600 nm base size and THz source intensity of I = 2 mW/µm2, can trap polystyrene nanoparticles with diameters of D = 140, 73, and 54 nm, and with trap stiffnesses of ky = 9.9 fN/nm, ky = 23.77 fN/nm, and ky = 35.51 fN/nm at Fermi energies of Ef = 0.4, 0.5, and 0.6 eV, respectively. It is well known that the plasmonic tweezer as a high-precision and non-contact means of control has potential applications in biology. Our investigations demonstrate that the proposed tweezing device with L = 1200 nm, W = 600 nm, and Ef = 0.6 eV can be utilized to manipulate the nano-bio-specimens. So that, at the given source intensity, it can trap the neuroblastoma extracellular vesicles, which are released by neuroblastoma cells and play an important role in modulating the function of neuroblastoma cells and other cell populations, as small as 88 nm at the front tip of isosceles-triangle-shaped graphene nano-taper. The trap stiffness for the given neuroblastoma extracellular vesicle is obtained as ky = 17.92 fN/nm.
In silico analysis of regulatory elements of the bldD gene of antibiotic-producing Streptomyces species
Authors: Demisie Sisay , Tafess Ketema 
Published: May 2022

Abstract
Background: Streptomyces are known for their ability to produce a great variety of antibiotics and other bioactive compounds. The production of these molecules is temporally and genetically coordinated with the bacterial morphological changes. These changes are controlled by transcriptional regulators which coincide with antibiotics production. The bldD gene is identified as one of the key players in the complex morphogenesis and activator of antibiotic production in Streptomyces. Besides the laboratory-based experimental works, Genome mining and in silico analysis of transcription start sites, promoter regions, transcription factors, and their binding sites, CpG islands of the bldD gene of antibiotic-producing Streptomyces species are the fundamental steps to understanding the regulatory mechanisms and its impact on the antibiotic production. Results: Our study identified the most important promoters in the upstream coding regions of the bldD gene of the 13 antibiotic-producing Streptomyces species. All, 13/13 (100%) of bldD genes have a single transcription start site (TSS) flanking the coding regions. The MEME algorithm revealed five motifs (MtS1-5), of which Motif 1 (MtS1) has the lowest E value and the key regulatory motifs for bldD genes among the discovered motifs. Using the TOMTOM web program, we identified 13 transcription factors with a capacity to bind MtS1. The analysis of the CpG Island of the bldD gene of the antibiotic-producing Streptomyces species indicated the presence of lower CpG islands. Phylogenetic analysis identified that bldD genes of antibiotic-producing species considered in this study are very closely related to other groups of Streptomyces. Conclusions Our study showed that the regulatory elements of bldD genes in antibiotic-producing Streptomyces are located closely upstream of the genes. A detailed understanding of these regulatory elements of the gene that encodes the key activator of antibiotic biosynthesis in Streptomyces species will in enhance the laboratory-based experiments for the production of the antibiotic.
Study on Fish Species Diversity and Water Quality Analysis in Zhalong Wetland
Authors: Chai Yihan , Cao Zhao 
Published: May 2022

Abstract
Zhalong wetland is one of the most important wetland reserves in the world. Endangered wild animals and plants such as red crowned cranes and wild soybeans live here. In order to understand the structural characteristics of fish community in Zhalong wetland and its relationship with water environmental factors, 24 sampling points were set up in Zhalong wetland for three times in May, August and October 2021. A total of 22 species, 20 genera, 8 families and 4 orders were caught, which were divided into 7 functional groups, of which PI functional group was significantly dominant. In addition, the fish species diversity Shannon-Wiener index of Zhalong wetland is the highest in autumn, which is 1.95. The second highest in summer is 1.86. The lowest level is 1.65 in spring. Pielou evenness index reached its peak in autumn, 0.64, reached its lowest level in summer, 0.59 and 0.61 in spring. Through RDA analysis, five-day biochemical oxygen demand and nitrate nitrogen are the main positive correlation environmental factors, Cl−, conductivity, total phosphorus, dissolved oxygen and total nitrogen are the main negative correlation environmental factors, and other factors are also correlated, but relatively insignificant.
XPS and AFM-IR correlative analysis of a ziggurat-structured ZDDP tribofilm
Authors: Lyon Stuart , Despotelis Kostas , Morsch Suzanne , Spencer Ben 
Published: May 2022

Abstract
Dynamic single asperity contact, using Atomic Force Microscope (AFM) probe tips, have been recently shown to be a powerful tool for investigating the tribological properties of surfaces. Here, we demonstrate a novel in-situ approach that produces a multilayer, ziggurat-structured, tribofilm developed over time. On a single sample produced during one uninterrupted experiment, each distinct layer uniquely represents a different stage of tribofilm development arising from decomposition of zinc dialkyl-dithiophosphate (ZDDP). We were able to successfully analyse the structure of the most developed inner layers, which reached a thickness of more than 130 nm, and the less developed outer regions, which were just a few nm thick, as well as intermediate layers. Thus, selected area X-ray photoelectron spectroscopy, measured a shift in the composition of zinc, sulphur and phosphorus, and a decrease in the sulphide:sulphate and ZnS:ZnO ratios as the film developed. Furthermore, AFM-IR, used in this application for the first time, directly identified S = O groups in the early stage of tribofilm growth as well as in the thermofilm. However, during later stages of growth, and particularly in the most developed central layers of the ‘ziggurat’, structure (poly)phosphates were detected (P = O, P-O-P, P-O-C). This confirms the previously suspected changes in the chemistry of such tribofilms as they develop.
Spiritual care needs attributes among hospitalized patients with breast cancer based on Kano model approach: a descriptive cross-sectional study
Authors: Wang Zhangyi , Zhao Haomei , Zhu Yue , Piao Jingjing , Xiao Luwei , Yang Zhihua , Zhang Yajun 
Published: May 2022

Abstract
Purpose To qualitatively analyze spiritual care needs attributes among hospitalized patients with breast cancer based on Kano model approach, in order to provide a reference for formulating intervention measures to meet their spiritual care needs.Methods A descriptive design was implemented, and the STROBE Checklist was used as the foundation of the study. The sociodemographic characteristics questionnaire, and an questionnaire on spiritual care needs attributes among hospitalized patients with breast cancer based on Kano model approach were used. A total of 357 hospitalized patients with breast cancer from three tertiary grade-A hospitals in China were investigated by using convenience sampling. Descriptive, maximum frequency, importance-satisfaction matrix, and blue-sea strategy analyses were used to analyze the data.Results Among the 12 items of spiritual care needs among hospitalized patients with breast cancer, 3 items (25.0%) were attractive attributes, all of which were located in reserving zone IV; 5 items (41.7%) were one-dimensional attributes, of which 3 were located in predominance zone I, 2 were located in improving zone II; 2 items (16.7%) were must-be attributes, all of which were located in improving zone II; 2 items (16.7%) were indifference attributes, all of which were located in secondary improving zone III. Conclusion The must-be and one-dimensional attributes of spiritual care needs among 357 hospitalized patients with breast cancer mainly focus on creating a good atmosphere and sharing self-perception dimensions, while attractive attributes of needs mainly focus on sharing self-perception and helping thinking dimensions. It is suggested that hospital managers should develop and innovate attractive attributes of needs on the basis of maintaining and perfecting must-be and one-dimensional attributes of needs, and objectively analyze and optimize indifference attributes of needs.
Development and validation of a risk prediction algorithm for evaluating the efficacy of postoperative adjuvant TACE therapy for hepatocellular carcinoma: a retrospective study
Authors: Tao Jie , Shi Xiaoli , Feng Xu , Wu Xinhua , Qi Shiguai , Feng Guoying , Yang Xu , Zhao Yufei , Zuo Hangjia , Shi Zhengrong 
Published: May 2022

Abstract
Background and purpose
There is a lack of a reliable outcome prediction model for patients evaluating the feasibility of postoperative adjuvant transarterial chemoembolization (PA-TACE) therapy. Our goal was to develop an easy-to-use tool specifically for these patients.
Methods
From January 2013 to June 2017, patients with liver cancer from the Liver Center of the First Affiliated Hospital of Chongqing Medical University received postoperative adjuvant Transarterial chemoembolization (TACE) therapy after liver cancer resection. A Cox’s proportional hazards model was established for these patients, followed by internal validation (enhanced bootstrap resampling technique) to further evaluate the predictive performance and discriminance, and compare with other predictive models. The prognostic factors considered included tumour number, maximum tumor diameter, Edmondson-Steiner (ES) grade, Microvascular invasion (MVI) grade, Ki67, age, sex, hepatitis B surface antigen, cirrhosis, Alpha-fetoprotein(AFP), Albumin-bilirubin (ALBI) grade, Child-pugh grade, body mass inex (BMI), Neutrophil-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR).
Results
The end point of the study was overall survival. The median overall survival was 31.8 (95%CI: 30.0-33.6 ) months, with 1-year, 2-year and 3-year survival rates being 96.3%, 84.0% and 75.3%, respectively. Tumour number, MVI grade, and BMI was incorporated into the model, which had good differentiation and accuracy. Internal validation (enhanced bootstrap ) suggested that Harrell’s C statistic is 0.72 (a measure of discrimination, with higher values indicating better discrimination). The model consistently outperforms other currently available models.
Conclusions
This model may be an easy-to-use tool for screening patients suitable for PA-TACE treatment and guiding the selection of clinical protocols. But further research and external validation are required.
Computing with two quantum reservoirs connected via optimized two-qubit non-selective measurements
Authors: Vintskevich Stephen , Grigoriev Dmitry 
Published: May 2022

Abstract
Currently, quantum reservoir computing is one of the most promising and experimentally accessible techniques for hybrid, quantum-classical machine learning. However, its applications are limited due to practical restrictions on the size of quantum systems and the influence of noise. Here we propose a novel approach to connect two quantum reservoirs in a network to overcome these issues and enhance their computing performance. To transfer information between quantum reservoirs, we perform optimized two-qubit non-selective measurements. We suggest a general heuristic optimization strategy based on tensor network language and matrix representation of two-qubit quantum channels specified for quantum reservoir computing. In addition, we introduce a single qubit purification channel and its optimization for further enhancement of quantum reservoir computing. We also demonstrate that the optimized channels applied to a seven-qubit network can efficiently transfer information between its parts with the resulting performance comparable to a network up to twenty-five qubits connected via a classical information link.
An analysis of the heat source contribution of ball screw based on WNN and PSO
Authors: Wu Huayang , Li Jiejing , Zuo Dunwen 
Published: May 2022

Abstract
Fundamentally, the heat source in the ball screw feed system accounts for the thermal behavior of the ball screw. Based on the analysis of the contribution of each heat source in the system to the thermal deformation of the ball screw, this paper sets out to provide a new method for thermal error compensation. It aims to explore the thermal deformation of ball screw and optimize the distribution of heat source contribution so as to provide theoretical guidance for the cooling of ball screw heat source. Firstly, the relationship between heat source and temperature, temperature and thermal deformation is analyzed theoretically, for the sake of illuminating the relationship between heat source and thermal deformation and the further deduction of the implicit mathematical expression of heat source contribution. Secondly, the network model of ball screw thermal deformation and temperature at the heat source is constructed based on wavelet neural network (WNN). Combined with the mathematical analysis results, the explicit mathematical expression of thermal deformation and heat source under this working condition is deduced, and the explicit mathematical expression of heat source contribution is further obtained. After that, keeping the total heat source contribution constant under this working condition, the particle swarm optimization (PSO) algorithm is used to determine the heat source contribution distribution that can minimize the thermal deformation of the ball screw. Finally, the simulation results of ball screw temperature field and thermal deformation before and after optimization are analyzed to examine the rationality and accuracy of the optimization results.