bluuebunny/crossref_metadata_2025_split huggingface dataset:
A new series of benzoxazole‐based SIRT1 modulators for targeted therapy of non‐small‐cell lung cancer
Authors: Sever Belgin , Akalın Çiftçi Gülşen , Altıntop Mehlika Dilek 
Published: January 2021

AbstractIn an attempt to identify potential anticancer agents for non‐small‐cell lung cancer (NSCLC) targeting sirtuin 1 (SIRT1), the synthesis of a new series of benzoxazoles (3a – i) was carried out through a facile and versatile synthetic route. The compounds were evaluated for their cytotoxic effects on A549 human lung adenocarcinoma and NIH/3T3 mouse embryonic fibroblast cells using the MTT assay. 2‐[(5‐Nitro‐1H‐benzimidazol‐2‐yl)thio]‐N‐(2‐methylbenzoxazol‐5‐yl)acetamide (3e) and 2‐[(5‐chloro‐1H‐benzimidazol‐2‐yl)thio]‐N‐(2‐methylbenzoxazol‐5‐yl)acetamide (3g) were the most potent and selective anticancer agents in this series against the A549 cell line, with IC50 values of 46.66 ± 11.54 and 55.00 ± 5.00 µM, respectively. The flow cytometry‐based apoptosis detection assay was performed to determine their effects on apoptosis in A549 cells. Both compounds induced apoptosis in a dose‐dependent manner. The effects of compounds 3e and 3g on SIRT1 activity were determined. On the basis of in vitro studies, it was observed that compound 3g caused a significant decrease in SIRT1 levels in a dose‐dependent manner, whereas compound 3e increased the SIRT1 levels. According to molecular docking studies, the substantial alteration in the type of action could be attributed to the difference between the interactions of compounds 3e and 3g with the same residues in the active site of SIRT1 (PDB code: 4IG9). On the basis of in silico ADME (absorption, distribution, metabolism, and excretion) studies, these compounds are predicted to possess favorable ADME profiles. According to the in vitro and in silico studies, compounds 3e and 3g, small‐molecule SIRT1 modulators, were identified as potential orally bioavailable anticancer agents for the targeted therapy of NSCLC.
In vitro hepatic steatosis model based on gut–liver‐on‐a‐chip
Authors: Jeon Joong‐won , Lee Seung Hwan , Kim Donghyun , Sung Jong Hwan 
Published: January 2021

AbstractHepatic steatosis, also known as fatty liver disease, occurs due to abnormal lipid accumulation in the liver. It has been known that gut absorption also plays an important role in the mechanism underlying hepatic steatosis. Conventional in vitro cell culture models have limitations in recapitulating the mechanisms of hepatic steatosis because it does not include the gut absorption process. Previously, we reported development of a microfluidic gut–liver chip that can recapitulate the gut absorption of fatty acids and subsequent lipid accumulation in liver cells. In this study, we performed a series of experiments to verify that our gut–liver chip reproduces various aspects of hepatic steatosis. The absorption of fatty acids was evaluated under various culture conditions. The anti‐steatotic effect of turofexorate isopropyl (XL‐335) and metformin was tested, and both drugs showed different action mechanisms. In addition, the oxidative stress induced by lipid absorption was evaluated. Our results demonstrate the potential of the gut–liver chip for use as a novel, physiologically realistic in vitro model to study fatty liver disease.
An intelligent learning framework for Industry 4.0 through automated planning
Authors: Yoo John J. , Günay Elif E. , Park Kijung , Tahamtan Siavash , Okudan Kremer Gül E. 
Published: January 2021

AbstractThe fourth industrial revolution, also known as Industry 4.0, has already begun enabling technological innovations in various domains, especially in the manufacturing and service industry. The conditions of the disruptive new product‐service emergence and quickly changing work environments require cultivating a competitive workforce that is equipped with essential knowledge and skills in Industry 4.0. The work presented herein identifies key competencies required for engineers in Industry 4.0 from the extant literature and offers a mechanism to facilitate knowledge and skills acquisition. Specifically, an automated planning software tool, iCoursePlanner, is proposed to recommend an optimized pathway to attain the identified competencies through not only offline courses in a college but also Massive Open Online Courses. This tool is based on a mobile app system in a cloud environment integrated with an optimization model for automated planning. iCoursePlanner uses the initial knowledge and goal knowledge of a learner to suggest a customized course plan. Case studies are conducted for industrial and manufacturing engineering students at Iowa State University and Bradley University to demonstrate how it can be used to help a student to acquire key competencies for Industry 4.0. The originality of the proposed automated course planning tool is rooted in the personalized course plan for each student that considers individual educational background and goal knowledge.
The future of university education: Examination, transcript, and certificate system using blockchain
Authors: Deenmahomed Haïdar A. M. , Didier Micheal M. , Sungkur Roopesh K. 
Published: January 2021

AbstractBlockchain is slowly but surely changing the world. Cryptocurrencies are having a profound effect on the economic landscape. With the advent of COVID‐19, the education sector, just like other sectors, need a complete reinvention or redesign to continue producing graduates that would be able to effectively contribute to an ever‐changing world. Very often, the administrative burden of managing the award of academic qualifications is ignored. With a globalised world and given the actual context of COVID‐19, education is no longer seen as being carried out within the four walls of the classroom. The future of University education lies within the ability to pool resources from different places and to encourage cross‐university collaboration. This can also be seen as the ability to assemble the different building blocks so that the learners are able to acquire the necessary skills and knowledge. This study focuses on the design and implementation of an examination, transcript and certificate system using blockchain. It is meant to provide a completely transparent and effective examination and awards system that can be used to replace the traditional one in place. What has also proposed in this study is a novel light blockchain system composed of a number of modules, which have been built from scratch. With its decentralised approach, the proposed system proved to be very much helpful. Other features, such as security, immutability, availability, and anonymity, of the system are also discussed and yielded highly encouraging results.
Recent Advances in Two‐Photon AIEgens and Their Application in Biological Systems
Authors: Dou Yandong , Zhu Qing , Du Kui 
Published: January 2021

AbstractTwo‐photon fluorescence imaging technology has the advantages of high light stability, little light damage, and high spatiotemporal resolution, which make it a powerful biological analysis method. However, due to the high concentration or aggregation state of traditional organic light‐emitting molecules, the fluorescence intensity is easily reduced or disappears completely, and is not conducive to optimal application. The concept of aggregation‐induced emission (AIE) provides a solution to the problem of aggregation‐induced luminescence quenching (ACQ), and realizes the high fluorescence quantum yield of luminescent molecules in the aggregation state. In addition, two‐photon absorption properties can readily be improved just by increasing the loading content of AIE fluorogen (AIEgen). Therefore, the design and preparation of two‐photon fluorescence probes based on AIEgen to achieve high‐efficiency fluorescence imaging in vitro/in vivo has become a major research hotspot. This review aims to summarize representative two‐photon AIEgens based on triphenylamine, tetraphenylethene, quinoline, naphthalene and other new structures from the past five years, and discuss their great potential in bioimaging applications.
N3‐Kethoxal‐Based Bioorthogonal Intracellular RNA Labeling
Authors: Huang Jinguo , Zhao Ruiqi , Mo Jing , Wang Fang , Weng Xiaocheng , Zhou Xiang 
Published: January 2021

AbstractThere is growing interest in developing intracellular RNA tools. Herein, we describe a strategy for N3‐kethoxal (N3K)‐based bioorthogonal intracellular RNA functionalization. With N3K labeling followed by an in vivo click reaction with DBCO derivatives, RNA can be modified with fluorescent or phenol groups. This strategy provides a new way of labeling RNA inside cells.
Bayesian competing risk analysis: An application to nasopharyngeal carcinoma patients data
Authors: Saroj Rakesh Kumar , Murthy K. Narasimha , Kumar Mukesh , Bhattacharjee Atanu , Patel Kamalesh Kumar 
Published: January 2021

AbstractBackgroundThe Cox proportional hazard (CPH) model is normally used to study the death event data. The presence of competing risk (CR) is often encountered in health data, hence it becomes difficult to manage time to event data in clinical study. Bayesian approach is considered to manage the CR events in clinical data.ObjectivesThe objective of study is to find the predictors associated with overall survival of nasopharyngeal carcinoma (NPC) patients. Further, our purpose is to use a Bayesian model that can analyze time to event data in the presence of CR.MethodsTotal 245 patients with NPC were taken (https://www.ncbi.nlm.nih.gov/geo/). The sociodemographic and clinical variables were considered for analysis purposes. R software and openBUGS were used to overcome the computational problems of CPH and Bayesian models. The Markov chain Monte Carlo (MCMC) method was used to compute the regression coefficients of Bayesian model.ResultsThe study shows that among NPC patients, the covariates chemotherapy, smoking, N‐stage, and tumor site are associated with the higher risk for the deaths occurring in the cancer patients. The posterior mean estimates of proposed Bayesian model for significant factors have been obtained. The posterior mean and standard deviation estimates help to improve the survival of patients in the presence of CR.ConclusionsIt is very difficult to use the CR model with Bayesian approach in health research for nonstatistical researcher due to lack of information. This paper is dedicated to the application of Bayesian approach for CR analysis on NPC data.
Hybrid salp swarm–firefly algorithm‐based routing protocol in wireless multimedia sensor networks
Authors: Srinivasa Gowda Ambareesh , Annamalai Neela Madheswari 
Published: January 2021

SummaryNowadays, there occurs a great demand for effective transmission of video. It is necessary to design an efficient transmission approach to transmit a huge amount of data in wireless multimedia sensor networks (WMSNs). But the routing based on wireless multimedia sensor networks is not much popular like other wireless sensor networks. Due to its peculiar features, it finds few troubles in directly applying the resolutions into the WMSNs. The work outlined in this paper is aimed at minimizing the delay and expected transmission count (ETX) cost of the QoS requirements. Moreover, this paper also proposes a hybrid salp swarm–firefly (HSSFF) approach which is the integration of two algorithms, namely, salp swarm and firefly optimization algorithms. The HSSFF approach employs in obtaining an optimal routing path with minimum end‐to‐end delay and less ETX value. Here, the fitness function for Simulink evaluation is twofold. We also presented the simulation results for two scenarios, and the comparative analysis is carried out to determine the best optimal routing path. Therefore, the simulation results describe that the HSSFF approach provides better performance on various nine test functions.
DeepSense—Deep neural network framework to improve the network lifetime of IoT‐MANETs
Authors: Chandrasekaran Suresh , Kannan Srihari , Subburathinam Karthik 
Published: January 2021

SummaryWith the advancement of Internet of Things (IoT), the devices are allowed to interact with other networks like mobile ad hoc network (MANET). The MANET‐IoT systems often undergo energy balancing problem between the sensor nodes, whereas the MANETs operate on mobile sensor nodes. Hence, proper utilization of battery power is required to maintain the network connectivity during a multi‐hop transmission. In this paper, we propose a DeepSense IoT‐MANET framework that effectively routes the packets from the IoT nodes via mobile sensor nodes in MANETs. The routings between the MANETs are organized by DeepSense interconnected with deep neural network (DNN) learning methods. The performance of the DeepSense DNN method is evaluated against various network metrics to evaluate the efficacy of the model.
RF energy modelling using machine learning for energy harvesting communications systems
Authors: Ye Youjie , Azmat Freeha , Adenopo Idris , Chen Yunfei , Shi Rui 
Published: January 2021

SummaryMachine learning (ML) theories and methods are mainly based on probability theory and statistics. It is a very powerful tool for data modelling. On the other hand, energy harvesting has been regarded as a viable solution to extending battery lifetime of wireless sensor network. Motivated by these, modelling of the radio frequency (RF) energy available to the wireless nodes is required for efficient operation of wireless networks. In this work, we will use different ML algorithms to model the RF energy data for efficient operation of energy harvesting communication systems. Four ML algorithms are studied and compared in terms of the accuracy for RF energy modelling using the energy data in the band between 1805 and 1880 MHz. The results show that linear regression (LR) has the highest accuracy and the most stable performance, while decision tree is the worst model. Also, in terms of the operation efficiency of the system, LR has the best performance, followed by support vector machine and random forest algorithm.
Geographic routing with hybrid firefly algorithm and galactic swarm optimization for efficient ‘void’ handling in mobile ad hoc networks
Authors: Kaliyamurthi Bagirathan , Palanisamy Anandhakumar 
Published: January 2021

SummaryGeographic routing in mobile ad hoc network (MANET) has gained much attention even though it fails to find a route when a node meets a void zone (hole). Therefore, an efficient approach is required to avoid the void issues and to effectively transfer the data packets if a path is available between the source and destination nodes. For such, a hybrid evolutionary algorithm is introduced with geographical routing protocol (GRP) for avoiding the void, which selects the shortest route for routing from the source to the destination by combining firefly (FF) algorithm and galactic swarm optimization (HFFGSO). This proposed algorithm exploits the strengths of both the FF algorithm and galactic swarm mechanisms. In this paper, the cross‐layer design approach is implemented, which contains data link and network layer. The proposed hybrid FFGSO‐GRP algorithm improves the routing process within these layers. The implementation process for this proposed technique is carried out in NS2 simulator. From the simulation results, it is observed that our hybrid protocol when compared with the existing approaches proves its significance in terms of packet delivery ratio (PDR), delay, throughput, energy efficiency, power consumption, routing overhead and hop count.
Insights into short‐ and long‐term crop‐foraging strategies in a chacma baboon (Papio ursinus) from GPS and accelerometer data
Authors: Walton Ben J. , Findlay Leah J. , Hill Russell A. 
Published: January 2021

AbstractCrop‐foraging by animals is a leading cause of human–wildlife “conflict” globally, affecting farmers and resulting in the death of many animals in retaliation, including primates. Despite significant research into crop‐foraging by primates, relatively little is understood about the behavior and movements of primates in and around crop fields, largely due to the limitations of traditional observational methods. Crop‐foraging by primates in large‐scale agriculture has also received little attention. We used GPS and accelerometer bio‐loggers, along with environmental data, to gain an understanding of the spatial and temporal patterns of activity for a female in a crop‐foraging baboon group in and around commercial farms in South Africa over one year. Crop fields were avoided for most of the year, suggesting that fields are perceived as a high‐risk habitat. When field visits did occur, this was generally when plant primary productivity was low, suggesting that crops were a “fallback food”. All recorded field visits were at or before 15:00. Activity was significantly higher in crop fields than in the landscape in general, evidence that crop‐foraging is an energetically costly strategy and that fields are perceived as a risky habitat. In contrast, activity was significantly lower within 100 m of the field edge than in the rest of the landscape, suggesting that baboons wait near the field edge to assess risks before crop‐foraging. Together, this understanding of the spatiotemporal dynamics of crop‐foraging can help to inform crop protection strategies and reduce conflict between humans and baboons in South Africa.
Between T and Y: Asymmetry in the Interaction of LAu(I) with Bipy and β‐Diiminate‐like Ligands
Authors: Cataffo Andrea , de Haas Titus , Ehm Christian , Budzelaar Peter H. M. 
Published: January 2021

AbstractThe combination of an LAu(I) fragment with a potentially chelating ligand
can result in different coordination modes of
: strictly monodentate, symmetrically bidentate, or intermediate with asymmetric bidentate binding of
. Density Functional calculations indicate that for π‐acceptor ancillary ligands L (C2H4, CO) and bis(nitrogen) donors
(bipyridine, phenanthroline, β‐diiminate) symmetric chelate structures are obtained. With primarily σ‐donating ancillary ligands L (Me−, Cl−, MeCN) the asymmetric coordination mode is the norm. Phosphine ancillary ligands L are on the edge and display the highest sensitivity to ligand variation. Asymmetry increases when (a) going from anionic (β‐diiminate) to neutral (bipyridine, phenanthroline) bidentates
; (b) making
less electron‐rich e. g. through having aryl instead of alkyl groups at N or through introduction of CF3 substituents. Inversion of the asymmetry through “gold hopping” is remarkably facile (barrier mostly <6 kcal/mol, often ∼1 kcal/mol). The high‐temperature fluxionality reported for two (PPh3)Au(β‐diiminate) complexes is tentatively assigned to imine inversion (rather than gold hopping) as the rate‐limiting step.
Capturing seizures in clinical trials of antiseizure medications for KCNQ2‐DEE
Authors: Millichap John J. , Harden Cynthia L. , Dlugos Dennis J. , French Jacqueline A. , Butterfield Noam N. , Grayson Celene , Aycardi Ernesto , Pimstone Simon N. 
Published: January 2021

AbstractLiterature review of patients with KCNQ2 developmental and epileptic encephalopathy (KCNQ2‐DEE) reveals, based on 16 reports including 139 patients, a clinical phenotype that includes age‐ and disease‐specific stereotyped seizures. The typical seizure type of KCNQ2‐DEE, focal tonic, starts within 0‐5 days of life and is readily captured by video‐electroencephalography VEEG for clinical and genetic diagnosis. After initial identification, KCNQ2‐DEE seizures are clinically apparent and can be clearly identified without the use of EEG or VEEG. Therefore, we propose that the 2019 recommendations from the International League against Epilepsy (ILAE), the Pediatric Epilepsy Research Consortium (PERC), for capturing and recording seizures for clinical trials (Epilepsia Open, 4, 2019, 537) are suitable for use in KCNQ2‐DEE‒associated antiseizure medicine (ASM) treatment trials. The ILAE/PERC consensus guidance states that a caregiver‐maintained seizure diary, completed by caregivers who are trained to recognize seizures using within‐patient historical recordings, accurately captures seizures prospectively in a clinical trial. An alternative approach historically endorsed by the Food and Drug Administration (FDA) compares seizure counts captured on VEEG before and after treatment. A major advantage of the ILAE/PERC strategy is that it expands the numbers of eligible patients who meet inclusion criteria of clinical trials while maintaining accurate seizure counts (Epilepsia Open, 4, 2019, 537). Three recent phase 3 pivotal pediatric trials investigating ASMs to treat syndromic seizures in patients as young as 2 years of age (N Engl J Med, 17, 2017, 699; Lancet, 21, 2020, 2243; Lancet, 17, 2018, 1085); and ongoing phase 2 open‐label pediatric clinical trial that includes pediatric epileptic syndromes as young as 1 month of age (Am J Med Genet A, 176, 2018, 773), have already used caregiver‐maintained seizure diaries successfully. For determining the outcome of a KCNQ2‐DEE ASM treatment trial, the use of a seizure diary to count seizures by trained observers is feasible because the seizures of KCNQ2‐DEE are clinically apparent. This strategy is supported by successful precedent in clinical trials in similar age groups and has the endorsement of the international pediatric epilepsy community.
Hypolipidemic, anti‐inflammatory, and anti‐atherosclerotic effects of tea before and after microbial fermentation
Authors: Deng Xiujuan , Hou Yan , Zhou Hongjie , Li Yali , Xue Zhiqiang , Xue Xiaoting , Huang Ganghua , Huang Kunlun , He Xiaoyun , Xu Wentao 
Published: January 2021

AbstractBackgroundMicrobial fermentation significantly affects the flavor and efficacy of tea. It is generally believed that fermented tea is more effective in lowering lipids, while unfermented tea can more effectively inhibit inflammation. However, there is not sufficient evidence to support this claim. To systematically compare the hypolipidemic, anti‐inflammatory, and anti‐atherosclerotic effects of tea before and after microbial fermentation, hyperlipidemic rats and inflammatory injury cells were treated with Monascus purpureus‐fermented pu‐erh tea water extract (MPT) and sun‐dried green tea water extract (SGT), respectively.ResultsMPT, with higher levels of theabrownins, flavonoids, gallic acid (GA), and lovastatin, was more effective in reducing serum triglyceride (TG), total cholesterol (TC), low‐density lipoprotein cholesterol (LDL‐C), and inflammatory cytokines (TNF‐α, IL‐1β, and IL‐6), while SGT, with higher levels of tea polyphenols, amino acids, (‐)‐epigallocatechin gallate (EGCG), and theaflavins, was more effective in increasing serum high‐density lipoprotein cholesterol (HDL‐C) in hyperlipidemic rats. The foam cells on the arterial wall of the rats in the MPT group were visibly less, and the thrombosis time was longer than that in the SGT group. Cell experiments showed that MPT was more effective in protecting endothelial cells from damage than SGT.ConclusionSurprisingly, Monascus purpureus‐fermented pu‐erh tea not only had better hypolipidemic and anti‐atherosclerotic effects than its raw material (sun‐dried green tea), but also was superior in anti‐inflammatory effects to the latter, which was possibly attributable to the great changes in functional ingredients during microbial fermentation.