bluuebunny/crossref_metadata_2025_split huggingface dataset:
FDMine: a graph mining approach to predict and evaluate food-drug interactions
Authors: Rahman Md Mostafizur , Vadrev Srinivas Mukund , Magana-Mora Arturo , Levman Jacob , Soufan Othman 
Published: June 2021

Abstract
Food-drug interactions (FDIs) arise when nutritional dietary consumption regulates biochemical mechanisms involved in drug metabolism. These interactions can create unexpected adverse pharmacological effects. By contrast, particular foods can aid in the recovery process of a patient. Towards characterizing the nature of food’s influence on pharmacological treatment, it is essential to detect all possible FDIs. In this study, we propose FDMine, a novel systematic framework that models the FDI problem as a homogenous graph. In this graph, all nodes representing drug, food and food composition are referenced as chemical structures. This homogenous representation enables us to take advantage of reported drug-drug interactions for accuracy evaluation, especially when accessible ground truth for FDIs is lacking. Our dataset consists of 788 unique approved small molecule drugs with metabolism-related drug-drug interactions (DDIs) and 320 unique food items, composed of 563 unique compounds with 179 health effects. The potential number of interactions is 87,192 and 92,143 when two different versions of the graph referred to as disjoint and joint graphs are considered, respectively. We defined several similarity subnetworks comprising food-drug similarity (FDS), drug-drug similarity (DDS), and food-food similarity (FFS) networks, based on similarity profiles. A unique part of the graph is the encoding of the food composition as a set of nodes and calculating a content contribution score to re-weight the similarity links. To predict new FDI links, we applied the path category-based (path length 2 and 3) and neighborhood-based similarity-based link prediction algorithms. We calculated the precision@top (top 1%, 2%, and 5%) of the newly predicted links, the area under the receiver operating characteristic curve, and precision-recall curve. We have performed three types of evaluations to benchmark results using different types of interactions. The shortest path-based method has achieved a precision 84%, 60% and 40% for the top 1%, 2% and 5% of FDIs identified, respectively. We validated the top FDIs predicted using FDMine to demonstrate its applicability and we relate therapeutic anti-inflammatory effects of food items informed by FDIs. We hypothesize that the proposed framework can be used to gain new insights on FDIs. FDMine is publicly available to support clinicians and researchers.
Attenuation of Energy-based Demand Parameters
Authors: SARI ALI , MANUEL Lance 
Published: June 2021

Abstract
The intensity of ground shaking and the demand on structures during earthquakes have been generally characterized using parameters such as peak ground acceleration as well as strength-based parameters such as response spectrum ordinates (e.g., spectral acceleration) that represent the maximum amplitude of shaking for structures with specified natural period and damping values. It has long been recognized that to assess the demands on structures during earthquakes, one might employ an energy-based approach (as an alternative to the more common strength-based one), especially when there is an interest in assessing damage potential of ground motions. An energy spectrum, obtained with the same level of effort required to construct a conventional response spectrum, is a convenient single-parameter description of both amplitude and duration of ground motion and can serve as a useful means by which to describe the performance of structures with different natural periods and damping ratios.In this study, attenuation models for Northwestern Turkey are developed for two parameters (defined herein) that are related to input energy and absorbed energy. The empirical models developed take advantage of the recent increase in the database on strong motion data for Northwestern Turkey. A total of 195 recordings from 17 recent seismic events are included in this database. The ground-motion prediction equations developed are for the geometric mean of the two horizontal components of the 5-percent damped energy parameters (elastic and inelastic input energy-equivalent acceleration, Ai, and absorbed energy-equivalent velocity, Aa) at various periods. Predictions of the energy-based parameters from the proposed attenuation model are compared with (strength-based) spectral acceleration levels predicted by Özbey et al [Soil Dyn. & Earthq. Eng., 24 (2004), pp. 115-125]. It is found that the energy demand parameters were generally greater with elastic Ai demands highest. In addition, the predicted energy-based parameter levels are compared with available Western U.S. attenuation model predictions for the same energy-based parameters. Western U.S. models predict similar energy demands to those with the proposed model. Finally, amplification factors for the energy-based parameters are proposed as a function of site class; these factors can be thought of as analogous to amplification factors for spectral acceleration as given in the NEHRP Seismic Provisions. The patterns related to the amplification are similar as with spectral acceleration in NEHRP (2001). A comparison of soil amplification effects for strength- and energy-based parameters is also discussed.
The Role of HOX Genes as Potential Biomarkers in Colorectal Cancer: A Systematic Review
Authors: Martinou Eirini , Falgari Giulia , Angelidi Angeliki , Simpson Guy , Bagwan Izhar , Meira Lisiane , Karanjia Nariman 
Published: June 2021

Abstract
Background: Colorectal cancer (CRC) is worldwide the third leading cause of cancer-related death, and despite therapeutic advances, survival remains low. Emerging evidence shows that Homeobox (HOX) genes are important in carcinogenesis, and their dysregulation has been linked with metastatic potential and poor prognosis. This systematic review aims to present the current evidence on the role of HOX genes as biomarkers in CRC and the impact of their modulation in tumour growth and progression. Methods: MEDLINE, EMBASE, Web of Science and Cochrane databases were searched by following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. Eligible studies investigated two research questions: a) the clinicopathological and prognostic significance of HOX gene dysregulation in patients with CRC and b) the functional role of HOX genes in CRC progression. This study was registered in the international prospective register of systematic reviews (PROSPERO), CRD42020190953. Results: Twenty-five studies enrolling 3003 patients with stage I-IV CRC, showed that 26 out of 39 HOX genes were dysregulated in cancerous versus normal colon. Aberrant expression of HOX proteins was significantly related to tumour depth, nodal invasion, distant metastases, advanced stage and poor prognosis. Twenty-two preclinical studies showed that HOX proteins are crucially related to tumour growth and metastatic potential by affecting cell proliferation and altering the expression of epithelial-mesenchymal transition modulators. Conclusions: In conclusion, our findings suggest that HOX proteins play vital roles in CRC progression and significantly affect survival. Further research, though, is required to elucidate their potential role as biomarkers in CRC.
De novo biosynthesis of paracetamol from glucose by metabolically engineered Escherichia coli
Authors: Guo Daoyi , Fu Xiao , Kong Sijia , Sun Yue , Pan Hong 
Published: June 2021

Abstract
Background: Paracetamol is among the most commonly used of all medications, widely accepted as a safe and effective analgesic/antipyretic for mild-to-moderate pain and fever. The biosynthesis of paracetamol from renewable sugars has not been reported so far, due to the lack of natural biosynthetic pathways. Results: In this study, we demonstrated for the first time the development of an E. coli cell factory for production of paracetamol from glucose. First, p-aminobenzoic acid, an intermediate of folic acid in microorganism, is selected as precursor substrates for the production of paracetamol. Second, a monooxygenase MNX1 from Candida parapsilosis CBS604 that can efficiently catalyze the decarboxylation and hydroxylation of p-aminobenzoic acid into corresponding p-aminophenol and another N-acetyltransferase PANAT from Pseudomonas aeruginosa that can efficiently catalyze the esterification of acetyl-CoA and p-aminophenol to form paracetamol were discovered. Finally, an engineered E. coli that allows production of paracetamol from simple carbon sources was established. Conclusions: The present study opens up a new direction for engineering microbial production of paracetamol from cheap and readily-available renewable raw materials such as sugars and cellulose in the future.
Lockdown fatigue: The diminishing effects of quarantines on the spread of COVID-19
Authors: Goldstein Patricio , Yeyati Eduardo Levy , Sartorio Luca 
Published: June 2021

Abstract
Non-Pharmaceutical Interventions (NPIs) have been for most countries the key policy instrument utilized to contain the impact of the COVID-19 pandemic. In this article, we conduct an empirical analysis of the impact of these policies on the virus’ transmission and death toll, for a panel of 152 countries, from the start of the pandemic through December 31, 2020. We find that lockdowns tend to significantly reduce the spread of the virus and the number of related deaths. We also show that this benign impact declines over time: after four months of strict lockdown, NPIs have a significantly weaker contribution in terms of their effect in reducing COVID-19 related fatalities. Part of the fading effect of quarantines could be attributed to an increasing non-compliance with mobility restrictions, as reflected in our estimates of a declining effect of lockdowns on measures of actual mobility. However, we additionally find that a reduction in de facto mobility also exhibits a diminishing effect on health outcomes, which suggests that lockdown fatigues may have introduce broader hurdles to containment policies.
LncRNA XIST alters the balance of peripheral blood immune cells in systemic lupus erythematosus by regulating the miR-17-92, OFLM4 and CEACAM8 axis
Authors: Cheng Qi , Xu Jieying , Chen Mo , Chen Xin , Zhang Peiyu , Wu Huaxiang , Du Yan 
Published: June 2021

Abstract
BackgroundX-inactive-specific transcript (XIST) has been shown to silence linked genes on the X chromosome that may be related to the pathogenesis of systemic lupus erythematosus (SLE) in female patients. However, the function of XIST in SLE at other levels remains unclear. The present study aimed to clarify the correlations between XIST expression and SLE clinical features and the contribution of XIST to SLE pathogenesis at the transcriptome level.MethodsExpression of XIST in 79 SLE patients and 23 healthy controls was detected by quantitative-polymerase chain reaction. Bioinformatics methods were used to explore the function and regulatory mechanism of XIST.ResultsExpression of XIST was significantly upregulated in SLE patients compared with healthy controls, and had a high diagnostic value for SLE. Importantly, SLE patients with high expression of XIST tended to have elevated levels of total T cells and CD8 + T cells, but reduced levels of Treg cells and NK cells. Bioinformatics analyses suggested that XIST may regulate the expression of OLFM4 and CEACAM8 by acting as a spongy body for miR-20a, miR-92a, miR-106a, and miR-449a. Furthermore, OLFM4 and CEACAM8 are significantly upregulated in SLE patients and had significant positive correlations with expression of XIST.ConclusionsWe propose that XIST may alter the balance of peripheral blood immune cells in SLE by acting as a spongy body for the miR-17-92 cluster and promoting the expression of OLFM4 and CEACAM8, resulting in immune dysregulation and tissue damage in SLE.
Continuous monitoring system for safe managements of CO2 storage and geothermal reservoirs
Authors: Tsuji Takeshi , Ikeda Tatsunori , Matsuura Ryosuke , Mukumoto Kota , Lawrens Hutapea , Kimura Tsunehisa , Yamaoka Koshun , Shinohara Masanao 
Published: June 2021

Abstract
We have developed a new continuous monitoring system based on small seismic sources and distributed acoustic sensing (DAS). The source system generates continuous waveforms with a wide frequency range. Because the signal timing is accurately controlled, stacking continuous waveforms enhances the signal-to-noise ratio, allowing the use of a small seismic source to monitor extensive areas (multi-reservoir). Our field experiments demonstrated that the monitoring signal was detected at a distance of ~80 km, and temporal variations of the monitoring signal (i.e., seismic velocity) were identified with >99.9% accuracy. Through the monitoring, we identified pore pressure variations due to geothermal operations and rains. When we used seafloor cable for DAS measurements, we identified the monitoring signals at >10 km far from the source in high-spatial resolution. This study demonstrates that multi-reservoir in an extensive area can be continuously monitored at a relatively low cost by combining our seismic source and DAS technology.
The use of computers in teaching clinical laboratory science
Authors: Miller T.E. , Smith P.J. , Gross S. , Guerlain S. , Rudmann S. , Strohm P.L. , Smith J.W. , Svirbely J.R. 
Published: June 2021

Abstract
The Transfusion Medicine Tutor (TMT) has been designed to study the use of computers in teaching concepts and problemsolving skills important in the field of clinical laboratory science. This system provides students with an opportunity to gain experience by solving a wide range of actual cases, and coaches these students when they are having difficulties. This system is designed specifically to detect and respond to a variety of errors that students may make while solving cases, and to suggest more advanced problem-solving methods when appropriate. This article describes the concepts behind the design of TMT.
Immunohematology
1993;9:22.
Investigation of artificial neural network performance in the aerosol properties retrieval
Authors: Srivastava Nishi , Vignesh D. , Saxena Nisheeth 
Published: June 2021

AbstractAerosols are an integral part of Earth's climate system and their effect on climate makes this field a relevant research problem. The artificial neural network (ANN) technique is an upcoming technique in different research fields. In the current work, we have evaluated the performance of an ANN with its parameters in simulating the aerosol's properties. ANN evaluation is performed over three sites (Kanpur, Jaipur, and Gandhi College) in the Indian region. We evaluated the performance of ANN for model's hyperparameter (number of hidden layers) and optimizer's hyperparameters (learning rate and number of iterations). The optical properties of aerosols from AERONET (AErosol RObotic NETwork) are used as input to ANN to estimate the aerosol optical depth (AOD) and Angstrom exponent. Results emphasized the need for optimal learning rate values and the number of iterations to get accurate results with low computational cost and to avoid overfitting. We observed a 23–25% increase in computational time with an increase in iteration. Thus, a meticulous selection of these parameters should be made for accurate estimations. The result indicates that the developed ANN can be utilized to derive AOD, which is not assessed at AERONET stations.
Application of low temperature soaking liquid in combined freezing-based desalination processes in summer
Authors: Yang Hui , Jiang Yuanfei , Fu Mengxiao , Wang Rui 
Published: June 2021

Abstract
In our previous study, it was noticed that the combined freezing, soaking and centrifugal desalination (FSCD) process is unsuitable to be applied in summer, because very little pure ice can be produced when the temperature of raw seawater used as soaking liquid reaches 27 °C. Therefore, two main efforts on the process optimization were made in this paper. One is that low-temperature seawater served as soaking liquid in all the experiments. In real industrial practice, the low-temperature soaking liquid can be obtained through melting pure ice products or recovering cold energy from cold concentrated brine. The effects of centrifugal parameters and soaking time on salt removal efficiency and ice yield rate were investigated. Second, the gravity-induced method was combined to form freezing, soaking, gravity-induced and centrifugal desalination (FSGCD) processes for further improvement of the salt removal efficiency. The influence of melting time of gravity-induced process was studied by keeping the samples ambient with an air temperature of 30 °C. Finally, the performance among different processes was compared. Results showed that the salt removal efficiency of the FSGCD process can reach up to 97.03%. The study is helpful to improve the process performance of soaking treatment in summer application.
Recent Advances in the Discovery of Antiviral Metabolites from Fungi
Authors: Deshmukh Sunil K. , Agrawal Shivankar , Gupta Manish Kumar , Patidar Rajesh K. , Ranjan Nihar 
Published: June 2021

Abstract:
As the world manages the impact of a global pandemic caused by COVID-19, the discovery of new antiviral agents has become way more relevant and urgent. Viruses are submicroscopic infectious agents that replicate inside the living cells of different organisms. These viruses use nucleic acids (both DNA and RNA) for further replication and maturity inside the cells. Some of the viruses responsible for various human and plant diseases belong to the classes of Picornaviridae, Retroviridae, Orthomyxoviri-dae, Flaviviridae, Pneumoviridae, Virgaviridae, and Hepadnaviridae, and their treatment options are lim-ited or non-existent. The consistent reemergence and resistance development in the viral strains demand the discovery and development of new antiviral drugs possessing better efficacy. Bio-active compounds isolated from fungi can be the source of new compounds with enhanced potency and new mechanisms of action. Fungi are known to produce a diverse lot of secondary metabolites due to their existence in harsh and testing climates which are often inhabitable for many organisms. Because of these unique environ-ments, fungi produce a variety of secondary metabolites of different chemical classes like alkaloids, qui-nones, furanone, pyrones, benzopyranoids, xanthones, terpenes, steroids, peptides, and many acyclic com-pounds. Fungal metabolites are known to display a wide range of bioactive attributes, i.e., anticancer, antibacterial, antifungal, and anti-Alzheimer's, along with antiviral properties. In this review article, we report over 300 antiviral compounds from fungal sources during the period of 2009 to 2019. The source of these compounds is marine and endophytic fungi and they are arranged based on their antiviral action against different viral families. These compounds offer promise for their use and development as future antiviral drugs.
Recent Development in the Management of Osteoarthritis – Overview of
Nanoformulation Approaches
Authors: Sagar Sakshi , Singh Dilpreet , Gupta GD 
Published: June 2021

Aim/Objectives:
Osteoarthritis (OA) is a degenerative disease of joints affecting over
7% of the world population, especially females, contributing to 2% of years lived with disability
(YLD’s) globally due to pain and impaired movement of limbs viz. hip, shoulder, and knee joint.
The present review explores the nano-formulation approaches to improve the therapeutic efficacy
of drugs for the treatment of osteoarthritis.

Results and Discussion:
The high treatment cost of osteoarthritis not only includes medication but
also physiotherapy, adaptive aids, and devices or even surgery that further amounts to the loss of
work hours. These medications are only treated symptomatically. Various nanocarriers have created
interest of reasearchers in improving the bioavailability of active drugs, thereby, therapeutically
improving the action and possible reduction of dose and side effects. Various nanocarriers are available
viz. liposome, noisome, transferosome, hydrogel, microemulsion, and nanoparticle formulations
for intraarticular, topical, and oral delivery for osteoarthritis treatment.

Conclusion:
This article focuses on novel approaches, such as lipid-based formulations and nanoor
microparticles as treatment strategies to minimize side effects by using carriers viz. liposome,
noisome, transferosome, hydrogel, microemulsion, and nanoparticle formulations for intraarticular,
topical, and even oral delivery.
Performance Evaluation of Enhanced Manhattan Mobility Model Over
GM, RWP, Manhattan Grid, SLAW, and TLW Mobility Models in
MANETs
Authors: Kour Satveer , Singh Jagpal 
Published: June 2021

:
The mobility model is the basis of simulation experiments in the Mobile Ad-hoc
Network. A composite model for mobility for city scenarios which includes a realistic model of
obstacle avoidance, and movement in the vertical direction, is proposed. The comparison of its
performance with those of other available mobility models is encouraging. We believe that it can
upgrade the routing performance. Here, we discuss the synthetic mobility models (Gauss-Markov,
Random Waypoint, Manhattan Grid), and trace-based mobility models (Truncated Levy Walk,
Self-Similar Least Action Walk). Then we propose a new mobility model by replacing a speed
calculating formula using Bonnmotion-3.0.1 on simulator NS2. The proposed mobility model,
named Enhanced Manhattan Mobility Model, is compared with the existing Manhattan Grid
mobility model in a tabulated form. AODV, DSR, and DSDV are analysed for above-mentioned
mobility models against the proposed one. Furthermore, the accuracy of the best protocol over the
best mobility model is investigated through Packet Delivery Ratio (PDR), throughput, average
end-to-end delay, packet overhead, and packet drop rate performance metrics. Due to the smooth
movements created by the proposed model, it shows an improvement of 1 percent to 7 percent in
throughput, 0.8 percent to 1.7 percent in packet overhead, 1 percent to 7 percent in PDR, and 1
percent in dropped packets.
Mathematics Learning Community: A Case Study
Authors: Sian Hoon Teoh , Mohd Yusof Mohammad Mubarrak , Mohd Rasid Nor Syazwani , Mohamed Siti Rosiah , Mohd Ainun Hafizah 
Published: June 2021

Abstract: The desire to equip students with 21st-century skills has prompted teachers to find alternative ways to promote real learning of mathematics. One of these ways includes building communities of best practices, with the collaborative efforts of parents. This study aims to investigate how mathematics teaching communities develop mathematical knowledge and skills in students. This study interviewed four teachers for insights into their teaching practices, specifically, how they built a learning community to foster the learning of mathematics. The findings showed that the teachers, working with parents, provided substantial support to develop students’ knowledge of mathematics and 21st-century skills, such as life skills. This study shows how mathematical knowledge and skills can be developed within a community with little access to advanced technology and how students can be supported to acquire life-long learning skills.

Keywords: Community, Mathematics, Parents, Teachers.