bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alkaline N-GQDs fluorescent probe for the ultrasensitive detection of creatinine
Authors: Ravi Pavithra Verthikere , Subramaniyam Vinodhini , Saravanakumar Neha , Pichumani Moorthi 
Published: July 2022

Abstract
Creatinine (Crn) is an important excretory product of the human body. Medical laboratory technology has improved over years and brought many advancements in clinical diagnostics equipment, and testing techniques and made the tests more efficient. Yet, the quantitative analysis of Crn is still carried out by the classical Jaffe’s reaction (using Picric acid (PA) with NaOH) method. Since PA is hazardous to human health, alternative solutions such as; nanoparticles and surface-modified nanoparticles can be used. Exploring the optoelectronic properties of carbon-based quantum dots for biomolecule sensing is of current interest among researchers. Nitrogen functionalized graphene quantum dots (Alk-NGQDs) measured featured Crn easier and reduced the time taken for the test carried out in laboratories. The synthesized Alk-NGQDs optical, structural, morphological properties, surface and compositions are studied through XPS, HRTEM, XRD, FTIR, and spectroscopic techniques. Alk-NGQDs at alkaline conditions (pH 9.5) form a stable complex with Crn through intermolecular charge transfer (ICT). The fluorescence titration method is used to sense Crn in commercial Crn samples and human blood serum. To understand the efficacy of sensing creatinine using Alk-NGQDs, working concentration, fluorescence quantum yield, the limit of detection, and quenching constant are calculated using the Stern-Volmer plot. The emission property of Alk-NGQDs is aimed to bring an alternative to the traditional colorimetric Jaffe’s reaction.
Surface state change influence’s theoretical approach of pressed iron on hollow cathode discharge characteristics: first results of plasma heating reproducibility for sintering purposes
Authors: Brunatto Silvio Francisco 
Published: July 2022

Abstract
In this work first results of the plasma heating process reproducibility for sintering purposes of pressed iron powder sample was investigated analyzing changes on the current-voltage characteristics of pulsed direct current (dc) Ar + H2 hollow cathode discharges sequentially carried out. For this purpose, the temperature of a sample acting as central cathode was varied by changing the switched-on time (duty cycle) of the pulse, via plasma species bombardment (ions and fast neutrals), which typically occurs in both cathode cylindrical surfaces that constitute the annular (hollow cathode) glow discharge, and measured by a thermocouple inserted in the central cathode sample holder. After two sequential plasma heating experiments, the third one practically reproduced the measured plasma parameters evidenced in the second heating, and the respective heating curves as a function of the time have led to similar current-voltage characteristics suggesting the iron sample sintering in non-isothermal way. Principles comprising plasma-surface interface and metallurgical-physical-chemical reactions, powder surface aspects, thermodynamic properties, metallurgical transformation of the pressed sample, and hollow cathode discharge properties are presented and discussed. The main points considered in the present approach are related to plasma (oxygen-affected plasma ionization, high ionization and excitation rate, and the intense light radiation of the annular glow discharge), thermodynamics (oxidation-reduction reactions, electron work function, sintering driving force, and surface energy), and powder (particle size distribution, morphology, specific surface, and iron recrystallization). To the best of the author’s knowledge, it is the first time that it is brought to the light the changes on hollow cathode discharge characteristics while an iron sample acting as the central cathode of an annular glow discharge is subjected to distinct heating steps on the temperature range of 20 to ∼1250 °C, leading it to have its sintering initiated.
Developing natural film for seasoning packaging of instant noodles
Authors: Ratchawet Anodar , Taokhum Pronpimol , Chaijalern Yuttana 
Published: July 2022

Abstract
This research aims to develop films from natural materials to be used as seasoning packaging for instant noodles. Natural materials such as bananas and konjac are used as raw materials for film-forming. There were 27 formulations of film-forming, including 9 formulas from the banana starch film, 9 formulas from banana starch blended with konjac powder 0.5% w/w, and 9 formulas from banana starch blended with konjac powder 1.0% w/w. The mechanical and physical properties of various formulation films were tested. When selecting a formulation film that meets the packaging requirements for 2 formulations by selecting one banana starch film and one banana starch film blended with konjac powder, it was found that the film formula B4Gly20 (banana 4% W/V and glycerol 20% V/V) and formula K05/4Gly20 (konjac 0.5% W/V blended with banana 4% W/V and Glycerol 20% V/V) have the best fit. They had properties close to specifications such as thickness and water permeability, not significantly different at 0.05%, and high tensile strength of 4.015 and 5.172 N.mm−2. The flexibility was 27.67 and 22.22 percent, and the water vapor permeability was 0.0063 and 0.0021 g. hr−1.cm -2, respectively., resistance to acidic solutions, and can be formed into strong packaging film, etc. When applying these two film formulas to the seasoning packaging of instant noodles, it was found that both film formulations did not prevent moisture in the air. The film formula B4Gly20 effectively prevented oil leakage. And also, B4Gly20 was more resistant to oxygen penetration into the cooking oil than K05/4Gly20 formulation film, but film formulation B4Gly20 was dissolved in hot water 100 ± 10 °C slower than K05/4Gly20. The results showed that the film formulation B4Gly20 was suitable for application in the seasoning packaging of instant noodles.
Effect of polymer amount on the mechanical behavior of polymer-infiltrated zirconia-ceramic composite at different pre-sintering temperatures
Authors: Alao Abdur-Rasheed , Rafiuddin Eliza Md Nur Adi Syafi , Rahman Ahmad Shamil Abd 
Published: July 2022

Abstract
Polymer-infiltrated zirconia-ceramic composite (PIZC) comprises a pre-sintered zirconia-ceramic matrix and a polymer. In this work, pre-sintered zirconia-ceramic was infiltrated with varied amounts of methacrylate-based polymer. Therefore, this paper reports the effect of polymer amount on the mechanical behavior of PIZC at 1100 °C–1300 °C pre-sintering temperatures. Conventional mechanical tests were performed to obtain the elastic modulus and fracture toughness while Vickers micro-indentations were employed to extract the Vickers hardness. Advanced mechanical behaviour analysis was characterized by plastic deformation resistance, elastic and plastic deformation components and brittleness index. Increasing the amount of polymer from 0 to 42% led to the corresponding decrease in elastic modulus, hardness and fracture toughness by at least 78, 85 and 75%, respectively. As the temperature was increased, both elastic modulus and hardness increased while the fracture toughness initially increased but decreased at higher temperature. Mechanical properties and polymer amount were well modelled by connected-grain models which usefully explained the densification process occurring at higher temperatures. Plastic deformation resistance and component and brittleness index confirmed better plastic properties for PIZC at higher polymer amounts and lower temperature. Therefore, in order to utilize the plastic properties of PIZC during the CAD/CAM process, these findings recommended the processing of PIZC at not-lower-than 26% polymer amount and 1100 °C, which could greatly facilitate its precision ductile machining mode realization. Finally, the results provide a technical guidance for the selection of appropriate polymer amount when fabricating dental restorations from this novel ceramic-composite.
Quantum solvability of a nonlinear δ-type mass profile system: coupling constant quantization
Authors: Chithiika Ruby V , Chandrasekar V K , Lakshmanan M 
Published: July 2022

Abstract
In this paper, we discuss the quantum dynamics of a nonlinear system that admits temporally localized solutions at the classical level. We consider a general ordered position-dependent mass Hamiltonian in which the ordering parameters of the mass term are treated as arbitrary. The mass function here is singular at the origin. We observe that the quantum system admits bounded solutions but importantly the coupling parameter of the system gets quantized which has also been confirmed by the semiclassical study as well.
Use of Debye–Hückel–Henry charge measurements in early antibody development elucidates effects of non-specific association
Authors: Laber Joshua R , Laue Thomas M , Filoti Dana I 
Published: July 2022

Abstract
The diffusion interaction parameter (kD) has been demonstrated to be a high-throughput technique for characterizing interactions between proteins in solution. kD reflects both attractive and repulsive interactions, including long-ranged electrostatic repulsions. Here, we plot the mutual diffusion coefficient (Dm) as a function of the experimentally determined Debye–Hückel–Henry surface charge (ZDHH) for seven human monoclonal antibodies (mAbs) in 15 mM histidine at pH 6. We find that graphs of Dm versus ZDHH intersect at ZDHH, ~ 2.6, independent of protein concentration. The same data plotted as kD versus ZDHH show a transition from net attractive to net repulsive interactions in the same region of the ZDHH intersection point. These data suggest that there is a minimum surface charge necessary on these mAbs needed to overcome attractive interactions.
Increasing Representation of Epidemiologists From Around the World in the Society for Epidemiologic Research: The Case of Mexico
Authors: Jimenez Marcia P , Gutierrez Tonatiuh Barrientos , Soria-Contreras Diana C , Abdel Magid Hoda S , Kaufman Jay S , Committee of the Society for Epidemiologic Research on behalf of the Diversity and Inclusion 
Published: July 2022

Abstract
Mexico has a population of 129 million and is considered one of the most unequal countries in the world, suffering from widespread health disparities. There is a pressing need to strengthen epidemiologic capacity in Mexico, to help solve the complex health problems the country faces and to reduce health inequities. However, the representation of Mexican epidemiologists in the largest epidemiologic society in North America is low, despite the short distance to the United States. In this commentary, we discuss the barriers to higher representation of Mexican epidemiologists within the Society for Epidemiologic Research (SER), including language barriers, costs, and regional necessities. We also discuss opportunities to expand Mexican SER representation and collaboration. Overall, we hope that this is a call towards expanding SER global participation and starting a conversation on a common agenda for epidemiologic research.
Elevated COVID-19 Case Rates of Government Employees, District of Columbia, 2020–2022
Authors: Hua Xinyi , Yin Jingjing , Fung Isaac C H 
Published: July 2022

Abstract

Objectives
To estimate the rate ratio (RR) of reported Coronavirus Disease 2019 (COVID-19) cases among governmental employees from seven District of Columbia (D.C.) departments from March 2020 to February 2022.

Methods
Poisson regression models were used to estimate the RR by department, using D.C. residents as the reference and the person-day as the offset. The COVID-19 surveillance data and the full-time equivalent hours for each department were obtained from the D.C. governmental websites.

Results
Five of the seven departments had statistically significant higher COVID-19 case rates than D.C. residents. Stratified by four pandemic stages, RR of Fire and Emergency Medical Services (FEMS), Office of Unified Communication (OUC), and Metropolitan Police Department (MPD) were consistently &gt;1: FEMS: 3.34 (95% confidence interval, CI [2.94, 3.77]), 2.39 (95% CI [2.06, 2.75]), 2.48 (95% CI [2.06, 2.95]), and 3.90 (95% CI [3.56, 4.26]), respectively; OUC: 1.47 (95% CI [0.92, 2.18]), 2.72 (95% CI [1.93, 3.69]), 1.85 (95% CI [1.09, 2.92]), and 2.18 (95% CI [1.62, 2.85]), respectively; and MPD: 2.33 (95% CI [2.11, 2.58]), 1.96 (95% CI [1.75, 2.18]), 1.52 (95% CI [1.29, 1.77]), and 1.76 (95% CI [1.60, 1.92]), respectively.

Conclusions
The results suggested higher case rates for emergency responders and frontline personnel than for general population in D.C.
Changes in physiological responses of OsCaM1-1 overexpression in the transgenic rice under dehydration stress
Authors: Sangchai Pun , Buaboocha Teerapong , Sirikantaramas Supaart , Wutipraditkul Nuchanat 
Published: July 2022

ABSTRACT
Calmodulin, a primary calcium sensor in eukaryotes, binds calcium and regulates the activity of effector proteins in response to calcium signals that evoked in response to abiotic and biotic stress. To identify physiological responses associated with improved tolerance under dehydration stress that may be regulated by calmodulin in rice, the transgenic rice overexpressing OsCaM1-1, the control, and the wild-type KDML105 differing in their dehydration tolerance were compared 24 h after exposure to dehydration stress. The results demonstrated a greater increase in relative water content, relative growth rate, abscisic acid, photosynthetic pigment and proline contents, and antioxidant activities in the transgenic rice plants, whereas Na/K and Na/Ca ratio, lipid peroxidation, and electrolytic leakage decreased. The OsCaM1-1 gene overexpression in the transgenic rice showed greater tolerance to dehydration stress than non-transgenic rice, suggesting that OsCaM1-1 might play an important role in mitigating dehydration stress.
A systematic review of analytical methods used in genetic association analysis of the X-chromosome
Authors: Keur Nick , Ricaño-Ponce Isis , Kumar Vinod , Matzaraki Vasiliki 
Published: July 2022

Abstract
Genetic association studies have been very successful at elucidating the genetic background of many complex diseases/traits. However, the X-chromosome is often neglected in these studies because of technical difficulties and the fact that most tools only utilize genetic data from autosomes. In this review, we aim to provide an overview of different practical approaches that are followed to incorporate the X-chromosome in association analysis, such as Genome-Wide Association Studies and Expression Quantitative Trait Loci Analysis. In general, the choice of which test statistics is most appropriate will depend on three main criteria: (1) the underlying X-inactivation model, (2) if Hardy–Weinberg equilibrium holds and sex-specific allele frequencies are expected and (3) whether adjustment for confounding variables is required. All in all, it is recommended that a combination of different association tests should be used for the analysis of X-chromosome.
Prediction of biomarker–disease associations based on graph attention network and text representation
Authors: Yang Minghao , Huang Zhi-An , Gu Wenhao , Han Kun , Pan Wenying , Yang Xiao , Zhu Zexuan 
Published: July 2022

AbstractMotivationThe associations between biomarkers and human diseases play a key role in understanding complex pathology and developing targeted therapies. Wet lab experiments for biomarker discovery are costly, laborious and time-consuming. Computational prediction methods can be used to greatly expedite the identification of candidate biomarkers.ResultsHere, we present a novel computational model named GTGenie for predicting the biomarker–disease associations based on graph and text features. In GTGenie, a graph attention network is utilized to characterize diverse similarities of biomarkers and diseases from heterogeneous information resources. Meanwhile, a pretrained BERT-based model is applied to learn the text-based representation of biomarker–disease relation from biomedical literature. The captured graph and text features are then integrated in a bimodal fusion network to model the hybrid entity representation. Finally, inductive matrix completion is adopted to infer the missing entries for reconstructing relation matrix, with which the unknown biomarker–disease associations are predicted. Experimental results on HMDD, HMDAD and LncRNADisease data sets showed that GTGenie can obtain competitive prediction performance with other state-of-the-art methods.AvailabilityThe source code of GTGenie and the test data are available at: https://github.com/Wolverinerine/GTGenie.
CoGO: a contrastive learning framework to predict disease similarity based on gene network and ontology structure
Authors: Chen Yuhao , Hu Yanshi , Hu Xiaotian , Feng Cong , Chen Ming 
Published: July 2022

AbstractMotivationQuantifying the similarity of human diseases provides guiding insights to the discovery of micro-scope mechanisms from a macro scale. Previous work demonstrated that better performance can be gained by integrating multiview data sources or applying machine learning techniques. However, designing an efficient framework to extract and incorporate information from different biological data using deep learning models remains unexplored.ResultsWe present CoGO, a Contrastive learning framework to predict disease similarity based on Gene network and Ontology structure, which incorporates the gene interaction network and gene ontology (GO) domain knowledge using graph deep learning models. First, graph deep learning models are applied to encode the features of genes and GO terms from separate graph structure data. Next, gene and GO features are projected to a common embedding space via a nonlinear projection. Then cross-view contrastive loss is applied to maximize the agreement of corresponding gene-GO associations and lead to meaningful gene representation. Finally, CoGO infers the similarity between diseases by the cosine similarity of disease representation vectors derived from related gene embedding. In our experiments, CoGO outperforms the most competitive baseline method on both AUROC and AUPRC, especially improves 19.57% in AUPRC (0.7733). The prediction results are significantly comparable with other disease similarity studies and thus highly credible. Furthermore, we conduct a detailed case study of top similar disease pairs which is demonstrated by other studies. Empirical results show that CoGO achieves powerful performance in disease similarity problem.Availability and implementationhttps://github.com/yhchen1123/CoGO.
Astrocyte immunometabolic regulation of the tumour microenvironment drives glioblastoma pathogenicity
Authors: Perelroizen Rita , Philosof Bar , Budick-Harmelin Noga , Chernobylsky Tom , Ron Ariel , Katzir Rotem , Shimon Dor , Tessler Adi , Adir Orit , Gaoni-Yogev Anat , Meyer Tom , Krivitsky Avivit , Shidlovsky Nuphar , Madi Asaf , Ruppin Eytan , Mayo Lior 
Published: July 2022

Abstract
Malignant brain tumours are the cause of a disproportionate level of morbidity and mortality among cancer patients, an unfortunate statistic that has remained constant for decades. Despite considerable advances in the molecular characterization of these tumours, targeting the cancer cells has yet to produce significant advances in treatment. An alternative strategy is to target cells in the glioblastoma microenvironment, such as tumour-associated astrocytes. Astrocytes control multiple processes in health and disease, ranging from maintaining the brain’s metabolic homeostasis, to modulating neuroinflammation. However, their role in glioblastoma pathogenicity is not well understood. Here we report that depletion of reactive astrocytes regresses glioblastoma and prolongs mouse survival. Analysis of the tumour-associated astrocyte translatome revealed astrocytes initiate transcriptional programmes that shape the immune and metabolic compartments in the glioma microenvironment. Specifically, their expression of CCL2 and CSF1 governs the recruitment of tumour-associated macrophages and promotes a pro-tumourigenic macrophage phenotype. Concomitantly, we demonstrate that astrocyte-derived cholesterol is key to glioma cell survival, and that targeting astrocytic cholesterol efflux, via ABCA1, halts tumour progression. In summary, astrocytes control glioblastoma pathogenicity by reprogramming the immunological properties of the tumour microenvironment and supporting the non-oncogenic metabolic dependency of glioblastoma on cholesterol. These findings suggest that targeting astrocyte immunometabolic signalling may be useful in treating this uniformly lethal brain tumour.
Longitudinal Immune Response to 3 Doses of Messenger RNA Vaccine Against Coronavirus Disease 2019 (COVID-19) in Pediatric Patients Receiving Chemotherapy for Cancer
Authors: Lehrnbecher Thomas , Sack Ulrich , Speckmann Carsten , Groll Andreas H , Boldt Andreas , Siebald Benjamin , Hettmer Simone , Demmerath Eva-Maria , Reemtsma Judith , Schenk Barbara , Ciesek Sandra , Klusmann Jan-Henning , Jassoy Christian , Hoehl Sebastian 
Published: July 2022

Abstract
Our study in 21 pediatric cancer patients demonstrates that 3 doses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) messenger RNA vaccine (BioNTech/Pfizer) elicited both humoral and cellular immunity in most patients during chemotherapy. Immunity was stronger in children with solid tumors and during maintenance therapy compared to those with hematological malignancies or during intensive chemotherapy.
Clinical Trials Registration.ȃGerman Registry for Clinical Trials (DRKS00025254).
An international multi-sectoral approach to financialisation
Authors: Torchinsky Landau Matías 
Published: July 2022

Abstract
Many studies attempted to measure the degree of financialisation of an economy, generally on a country-by-country basis, given the heterogeneity of indicators and data availability. In this paper, a simple but common measure of financialisation of non-financial corporations (NFCs) is developed, namely, the participation of services provided by the financial sector (both directly and indirectly) on their value-added creation process, inspired by the methodology developed by Dávila-Fernández and Punzo (2020). To do this, we use the inter-country input-output (ICIO) matrices built by the OECD, which allow us to understand the role played by the financial sector (local or foreign) in the ‘value-added production function’ of NFCs from 45 industries, in 67 countries for the period 1995–2018. We find three main stylised facts. First, the financial sector plays a relevant role in the value-added creation process of NFCs, and its importance has increased during the last years, although there is high diversity among countries. Second, this process has been heterogeneous when different productive sectors are considered. Primary industries evidenced a low degree of financialisation, while manufacturing and the service sector generally presented a higher reliance on finance. Third, between 1995 and the global financial crisis, NFCs increased their dependence on foreign financial value-added, followed by a partial reversion of this process. Moreover, the origin of these exports of financial services changed: while some traditional financial hubs such as the UK, Switzerland and Japan decreased their importance as providers of financial value-added to NFCs, China, Russia and India became important global players.