bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis and characterization of Metal-mercaptoacetate hybrids and its application towards ring opening polymerization of ε-caprolactone: A comparative study
Authors: Kannammal L. , Meeenarathi B. , Parthasarathy V. , Anbarasan Ramasamy 
Published: March 2021

Abstract
The Mn2+ and Mo6+ based Metal-mercaptoacetate (Metal-MA) hybrids were prepared by a simple acid-base titration method. The prepared Metal-MA hybrids were analysed by FT-IR spectroscopy, UV-visible spectroscopy, SEM, particle size analyser (PSA), XRD and EDX. The prepared Metal-MA hybrids were investigated to assess their catalytic activity for ring-opening polymerization (ROP) of ε-caprolactone (CL) in the absence of an initiator at 160 oC in N2 atmosphere by varying the catalyst concentration and temperature. The catalytic activity of the Metal-MA hybrid towards the ROP of CL was concluded by the FTIR-RI method. The % yield, degradation temperature (Td), melting temperature (Tm) and molecular weight (Mw) of poly(ε-caprolactone) (PCL) were also investigated. The structure of PCL was comprehended by analysing its NMR spectrum. The activation energy (Ea) for the ROP of CL was determined as 10,363 Kcal/mol. A linear increase in Mw of PCL with the increasing [M0/I0] ratio was also noticed.
An external validation of the Candiolo nomogram in a cohort of prostate cancer patients treated by external-beam radiotherapy
Authors: Gabriele Domenico , Guarneri Alessia , Bartoncini Sara , Munoz Fernando , Tamponi Matteo , Russo Filippo , Stamatakos Georgios , Guiot Caterina , Regge Daniele , Ricardi Umberto 
Published: March 2021

Abstract
Backgroundthe aim of this study is to perform an external validation for the Candiolo nomogram, a predictive algorithm of biochemical and clinical recurrences in prostate cancer patients treated by radical Radiotherapy, published in 2016 on the journal “Radiation Oncology”.Methods561 patients, treated by Radiotherapy with curative intent between 2003 and 2012, were classified according to the five risk-classes of the Candiolo nomogram and the three risk-classes of the D’Amico classification for comparison. Patients were treated with a mean prostatic dose of 77.7 Gy and a combined treatment with Androgen-Deprivation-Therapy in 76% of cases. The end-points of the study were biochemical-Progression-Free-Survival (bPFS) and clinical-Progression-Free-Survival (cPFS). With a median follow-up of 50 months, 56 patients (10%) had a biochemical relapse, and 30 patients (5.4%) a clinical progression. The cases were divided according to D’Amico in low-risk 21%, intermediate 40%, high-risk 39%; according to Candiolo very-low-risk 24%, low 37%, intermediate 24%, high 10%, very-high-risk 5%. Statistically, the Kaplan-Meier survival curves were processed and compared using Log-Rank tests and Harrell-C concordance index.ResultsThe 5-year bPFS for the Candiolo risk-classes range between 98% and 38%, and the 5-year cPFS between 98% and 50% for very-low and very-high-risk, respectively. The Candiolo nomogram is highly significant for the stratification of both bPFS and cPFS (P < 0.0001), as well as the D’Amico classification (P = 0.004 and P = 0.001, respectively). For the Candiolo nomogram, the C indexes for bPFS and cPFS are 75% and 80%, respectively, while for D'Amico classification they are 64% and 69%, respectively. The Candiolo nomogram can identify a greater number of patients with low and very-low-risk prostate cancer (61% versus 21% according to D'Amico) and it better picks out patients with high and very-high-risk of recurrence, equal to only 15% of the total cases but subject to 48% (27/56) of biochemical relapses and 63% (19/30) of clinical progressions.Conclusionsthe external validation of the Candiolo nomogram was overall successful with C indexes approximately 10% higher than the D'Amico control classification for bPFS and cPFS. Therefore, its clinical use is justified in prostate cancer patients before radical Radiotherapy.Trial registrationretrospectively registered.
Appraising groundwater potential zones using geospatial and multi-criteria decision analysis (MCDA) techniques in Andasa-Tul watershed, Upper Blue Nile basin, Ethiopia
Authors: Anteneh Zelalem Leyew , Alemu Melkam Meseret , Bawoke Getnet Taye , Kehali Alebachew Tareke , Fenta Mulugeta Chanie , Desta Minyahl Teferi 
Published: March 2021

Abstract
Ever increase in population growth and drastic climatic changes augment the demand and exploration of groundwater from time to time. An integrated approach of remote sensing (RS), geographic information system (GIS) and multicriteria decision analysis (MCDA) of analytical hierarchical process (AHP) were applied to delineate groundwater potential (GWP) zones in Andasa-Tul watershed, Upper Blue Nile Basin, Ethiopia. For this purpose, nine GWP influencing thematic layers comprising lithology, lineament density, geomorphology, slope, soil, drainage density, land use/land cover, rainfall and depth to groundwater level were used. The thematic layers and classes within them were given scale values based on literature and experts’ decision and calculated using Satty’s AHP. The thematic layers have been integrated via their weights/rates using weighted overlay spatial function tool of ArcGIS to provide GWP map. The result shows that GWP map comprises very good (13.4%), good (7%), moderate (23.6 %), poor (35.4%) and very poor (20.5%) zones. Validation of the GWP map with existing water point yields shows 84.21 % agreement indicating good accuracy of the method. The map removal sensitivity analysis result reveals that GWP is more sensitive to lithology (mean variation index, 1.92 %) and less sensitive to geomorphology (mean variation index, 0.59 %). Similarly, from the single layer sensitivity analysis, lithology and slope are found to be more effective parameters, whereas rainfall and depth to groundwater level are less effective variables.
Eco Friendly Zinc Oxide Wurtzite Nanostructures and their Efficacy for Photocatalysis, Photoluminescence and Fluorescence Resonance Energy Transfer
Authors: Wijesinghe Udari , Thiripuranathar Gobika , Iqbal Haroon , Menaa Farid , Razaaq Anam 
Published: March 2021

Abstract
In recent years, biosynthesized zinc oxide nanoparticles (ZnO NPs) are gaining importance due to their unique properties and tremendous applications. This study aimed to fabricate ZnO NPs by using extracts from various parts (i.e. stems, leaves, and inflorescences) of the traditional medicinal plant Heliotropium indicum (H. indicum) and to identify their photocatalysis, photoluminescence, and fluorescence resonance energy transfer (FRET) efficacy. The Ultraviolet-Visible (UV-Vis) spectrum was used to monitor the nanoparticles (NPs) formation, which exhibited a hypsochromic shifted absorption band between 360-370 nm. Fourier transform infrared (FTIR) analysis was carried out for the plant extracts and NPs to identify possible functional groups involved in the capping process. Transmission electron microscopy (TEM) analysis revealed NPs were spherical in shape and X-ray diffraction (XRD) results shown their wurtzite, hexagonal crystalline nature. Further, TEM and XRD consistently determined the average particle size ranging from 19 to 53 nm with more accuracy than scanning electron microscope (SEM). Dynamic light scattering (DLS) showed that the particles were well distributed and monodispersed. The maximum photocatalytic degradation of 95% was evaluated for biogenic ZnO NPs spectrophotometrically by monitoring the degradation of methylene blue (MB) dye (λmax = 662.8 nm) under solar irradiation. Photoluminescence (PL) analysis, revealed differentiated spectra with high-intensity emission peaks for biogenic ZnO NPs compared to chemically synthesized ZnO NPs. Eventually, the highest efficiency of FRET (80%) was found in ZnO NPs synthetized from the leaves. This remains the first attempt to synthesize multifunctional ZnO NPs using H. indicum for potential environmental and biomedical applications.
Absolute Lymphocyte Count Changes During Neoadjuvant Chemotherapy are Associated with Prognosis of HER2-Positive Breast Cancer Patients
Authors: Miyamoto Naoki , Inoue Hiroaki , Inui Tomohiro , Sasa Soichiro , Aoyama Mariko , Okumura Kazumasa , Toba Hiroaki , Takizawa Hiromitsu , Tangoku Akira 
Published: March 2021

Abstract
Purpose: To investigate the relation of absolute lymphocyte count (ALC) changes during neoadjuvant chemotherapy for human epidermal growth factor receptor-2 (HER2)-positive breast cancer patients and their prognosis.Methods: From January 2010 to December 2019, patients diagnosed with HER2-positive breast cancer and treated with trastuzumab-based neoadjuvant chemotherapy (NAC) were included in this retrospective cohort study. The ALC ratio was Blood cell count estimates before and after NAC were evaluated to calculate the ALC ratio. The optimal cut-off for the ALC ratio was identified using the receiver operating characteristic (ROC) curve analysis and Youden’s index. The relationship between the ALC ratio and disease-free survival (DFS) was measured using the Kaplan–Meier method. Univariate and multivariate analyses were performed using the Cox proportional hazards model.Results: 71 HER2 breast cancer patients were analyzed. The cut-off value of the ALC ratio was decided as 1.109. The median follow-up period was 53.1 (range: 5.1-111.5) months. The high-ALC ratio group showed superior survival rates to the low-ALC ratio group (p=0.0242). The 5-year DFS rates were 89.1% and 63.3% in the high- and low-ALC ratio group, respectively. The ALC ratio was nominated as an independent prognostic factor in multivariate Cox proportional hazards analysis (p=0.0052).Conclusion: HER2-positive breast cancer patients who showed a higher ALC ratio during trastuzumab-based neoadjuvant chemotherapy were associated to better survival.
Effect Modification by Age and Comorbidities on the Association Between Periodontitis and Female Breast Cancer: A Population-based Case-control Study
Authors: Chen Chien-Chih , Ho Wei-Li , Lin Ching-Heng , Chen Hsin-Hua 
Published: March 2021

Abstract
Background: The association between periodontitis and female breast cancer is not clear. The purpose of this study is to assess that periodontitis was associated with the risk of female breast cancer.Methods: Using claims data taken from the 1997–2013 Taiwanese National Health Insurance Research Database (NHIRD), we identified 60,756 newly-diagnosed female breast cancer patients during the period 2003–2013 from all beneficiaries. We then randomly selected 243,024 women without breast cancer matching (1:4) for age and the year of the index date during 1997–2013 from a one million representative population acting as the control group. A conditional logistic regression analysis was used to examine the association between periodontitis and the risk of breast cancer, shown as an odds ratio (OR) with a 95% confidence interval (CI) after adjustments for the Charlson Comorbidity Index (CCI), geographic region and level of urbanization.Results: The mean ± standard deviation age was 53 ± 14 years. After adjusting for potential confounders, the risk of female breast cancer was found to be associated with a history of periodontitis (OR, 1.12; 95% CI, 1.10-1.14). Such an association was significantly different between patients aged < 65 years (OR, 1.09; 95% CI, 1.06–1.11) and patients aged ≥ 65 years (OR, 1.23; 95% CI, 1.18–1.28; p for interaction <0.001), as well as between patients where the CCI = 0 (OR, 1.17; 95% CI, 1.15–1.20) and patients with CCI > 0 (OR, 0.99; 95% CI, 0.96–1.03; p for interaction <0.001). The highest level of urbanization was also associated with the risk of breast cancer.Conclusions: This nationwide, population-based case-control study demonstrated that periodontitis was significantly associated with the risk of female breast cancer and such an association was modified by both age and comorbidities.
Using a Machine Learning Approach to Identify Key Prognostic Molecules for Esophageal Squamous Cell Carcinoma
Authors: Li Meng-Xiang , Sun Xiao-Meng , Cheng Wei-Gang , Ruan Hao-Jie , Liu Ke , Chen Pan , Xu Hai-Jun , Gao She-Gan , Feng Xiao-Shan , Qi Yi-Jun 
Published: March 2021

Abstract
ObjectiveA plethora of prognostic biomarkers for esophageal squamous cell carcinoma (ESCC) that have hitherto been reported are challenged with low reproducibility due to high molecular heterogeneity of ESCC. The purpose of this study is to identify the optimal biomarkers for ESCC using machine learning algorithms.MethodsBiomarkers related to clinical survival, recurrence or therapeutic response of patients with ESCC were determined through literature database searching. Forty-eight biomarkers linked to prognosis of ESCC were used to construct a molecular interaction network based on NetBox and then to identify the functional modules. Publicably available mRNA transcriptome data of ESCC downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets included GSE53625 and TCGA-ESCC. Five machine learning algorithms, including logical regression (LR), support vector machine (SVM), artificial neural network (ANN), random forest (RF) and XGBoost, were used to develop classifiers for prognostic classification for feature selection. The area under ROC curve (AUC) was used to evaluate the performance of the prognostic classifiers. The importances of these 17 molecules were ranked by their occurrence frequencies in the prognostic classifiers. Kaplan-Meier survival analysis and log-rank test were performed to determine the statistical significance of overall survival.ResultsA total of 48 clinical proven molecules associated with ESCC progression were used to construct a molecular interaction network with 3 functional modules comprising 17 component molecules. The 131071 prognostic classifiers using these 17 molecules were built for each machine learning algorithm. Using the occurrence frequencies in the prognostic classifiers with AUCs greater than the mean value of all 131,071 AUCs to rank importances of these 17 molecules, stratifin encoded by SFN was identified as the optimal prognostic biomarker for ESCC, whose performance was further validated in another 2 independent cohorts.ConclusionThe occurrence frequencies across various feature selection approaches reflect the degree of clinical importance and stratifin is an optimal prognostic biomarker for ESCC.
Effects of chronic voluntary alcohol consumption on PDE10A availability: a longitudinal behavioural and [18F]JNJ42259152 PET study in rats
Authors: Laat Bart de , Klingl Yvonne E. , Schroyen Gwen , Ooms Maarten , Hooker Jacob M , Bormans Guy , Laere Koen Van , Ceccarini Jenny 
Published: March 2021

Abstract
Purpose

Phosphodiesterase 10A (PDE10A) is a dual substrate enzyme highly enriched in dopamine-receptive striatal medium spiny neurons, which are involved in psychiatric disorders such as alcohol use disorders (AUD). Although preclinical studies suggest a correlation of PDE10A mRNA expression in neuronal and behavioral responses to alcohol intake, little is known about the effects of alcohol exposure on in vivo PDE10A activity in relation to apparent risk factors for AUD such as decision-making and anxiety.
Methods

We performed a longitudinal [18F]JNJ42259152 microPET study to evaluate PDE10A changes over a 9-week intermittent access to alcohol model, including 6 weeks of alcohol exposure, 2 weeks of abstinence followed by 1 week relapse. Parametric PDE10A binding potential (BPND) images were generated using a Logan reference tissue model with cerebellum as reference region and were analyzed using both a volume-of-interest and voxel-based approach. Moreover, individual decision-making and anxiety levels were assessed with the rat Iowa Gambling Task and open field test over the IAE model.
Results

We observed an increased alcohol preference especially in those animals that exhibited poor initial decision-making. The first 2-weeks of alcohol exposure resulted in an increased striatal PDE10A binding (> 10%). Comparing PDE10A binding potential after 2- versus 4-weeks of exposure, showed a significant decreased PDE10A in the caudate-putamen and nucleus accumbens (pFWEcorrected<0.05). This striatal PDE10A decrease was related to alcohol consumption and preference. Normalization of striatal PDE10A to initial levels was observed after 1 week of relapse, apart from the globus pallidus.
Conclusion

This study shows that chronic voluntary alcohol consumption induces a reversible increased PDE10A enzymatic availability in the striatum, which is related to the amount of alcohol preference. Thus, PDE10A-mediated signaling plays an important role in modulating the reinforcing effects of alcohol, and the data suggest that PDE10A inhibition may have beneficial behavioral effects on alcohol intake.
Care Networks of Home-dwelling Older Persons in the Netherlands: Proof of Concept of a Network Typology
Authors: Kemper-Koebrugge Wendy , Adriaansen Marian , Laurant Miranda , Wensing Michel 
Published: March 2021

Abstract
Background Studies on care networks of home-dwelling older persons often focus on network constellation. However, looking at network interaction can be helpful to improve the support generated by the care network. A European study on diabetes patients found network types based on the interaction within a network, which can be beneficial (generative, proxy) or detrimental (struggling, avoidant) to support. This study explored whether these network types are present in care networks of home-dwelling older persons in the Netherlands and how these network types manifest in constellation or ways of interaction (negotiation, navigation and contagion). Methods The present study is a secondary analysis of a cross‐sectional qualitative study of 16 care networks with home‐dwelling older persons, informal caregivers and formal care providers conducted between March and September 2016. First, navigation, negotiation and contagion were analysed for each network; then the network type was determined for each network. ResultsWe found nine proxy networks, four generative networks, two avoidant networks and one struggling network. In the proxy networks, all negotiation and navigation were centralised by the proxy. In generative networks, negotiation was possible if the older person could be reciprocal and the network supported this. In avoidant networks, informal and formal caregivers had to deal with an older person who refused support. In the struggling network, the underlying problem could not be addressed. Furthermore, two networks seemed to show a transition process from generative to proxy network.ConclusionWe concluded that the network typology on interaction offered extra information about the functioning of the care network. It seems that the network type can change over time, but more research is needed to confirm this. This study suggests that interventions in avoidant or struggling networks are difficult. Also actions were aimed at developing proxy networks. Interventions maintaining or developing generative networks seem underused.
A Continuum Deformation Approach for Growth Analysis of COVID-19 in the United States
Authors: Hemmati Sadra , Rastgoftar Hossein 
Published: March 2021

Abstract
The COVID-19 global pandemic has significantly impacted every aspect of life all over the world. The United States is reported to have suffered more than 20% of the global casualties from this pandemic. It is imperative to investigate the growth dynamics of the disease in the US based on varying geographical and governmental factors that best manifest itself in each state of the country. This paper utilizes a hybrid machine learning and continuum deformation-based approach for analyzing the stability of the rapid COVID-19 growth. The proposed continuum deformation model is used to learn the parameters of pandemic growth based on the training data of total cases, deaths, and recoveries in each state of the United States from March 12, 2020 to January 28, 2021. Using this approach, multiple periods of the nationwide and State-level pandemic growth patterns are discovered and analyzed.
A General Fruit Acid Chelation Route for Eco-friendly and Ambient 3D Printing of Metals
Authors: Cho Soo Young , Ho Dong Hae , Choi Yoon Young , Lim Soomook , Lee Sungjoo , Suk Ji Won , Cho Jeong Ho 
Published: March 2021

Abstract
Recent advances in metal additive manufacturing (AM) have provided new opportunities for the design of prototypes of metal-based products and personalization of products for the fourth industrial revolution. Although metal AM, which enables fabrication of varied and sophisticated objects, is in the spotlight as a next-generation printing method, environmental issues arising during the printing process need to be addressed before it can be commercialized. Here, we demonstrate a novel mechanism for binder jetting three-dimensional (3D) printing of metals that is based on chelation triggered by an eco-friendly binding agent. Sodium salts of fruit acid chelators are used to form stable metal-chelate bridges between metal particles, which enable elaborate metal 3D printing. The strength of the 3D-printed object is improved by post-treatment, through a reduction in the porosity between the metal particles. Finally, the compatibility of the novel printing mechanism with a variety of metals is demonstrated via successful 3D printing of objects of various shapes using various metal powders. The proposed mechanism for metal 3D printing is expected to open up new avenues for the development of domestic-scale desktop 3D printing of metals.
Geometrically Stabilized Skyrmionic Vortex in FeGe Tetrahedral Nanoparticles
Authors: Niitsu Kodai , Liu Yizhou , Booth Alexander , Yu Xiuzhen , Mathur Nitish , Stolt Matthew , Shindo Daisuke , Jin Song , Zang Jiadong , Nagaosa Naoto , Tokura Yoshinori 
Published: March 2021

Abstract
The concept of topology has dramatically expanded the landscape of magnetism, leading to the discovery of numerous magnetic textures with intriguing topological properties. A magnetic skyrmion is an emergent topological magnetic texture with a string-like structure in three dimensions and a disk-like structure in one and two dimensions. Skyrmions in zero dimensions have remained elusive owing to challenges from many competing orders. Herein, by integrating electron holography and micromagnetic simulations, we uncover the real-space magnetic configurations of a novel skyrmionic vortex structure confined in a B20-type FeGe tetrahedral nanoparticle. This texture shows excellent robustness against temperature without applying a magnetic field; an isolated skyrmionic vortex forms at the ground state. These findings shed light on zero-dimensional geometrical confinement as a route to engineer and manipulate individual skyrmionic metastructures.