Showing papers by "Kangwon National University published in 2021"
TL;DR: In this article, a snapshot of the current scenario regarding the miRNAs as biopharmaceuticals have been discussed, and the current status of preclinical/clinical trials about miRNA therapeutics have been reviewed.
200 citations
TL;DR: Two novel deep learning algorithms, the recurrent neural network (RNN) and convolutional Neural Network (CNN), are applied for national-scale landslide susceptibility mapping of Iran to generate landslide susceptibility maps of Iran.
Abstract: The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses. In this study, we applied two novel deep learning algorithms, the recurrent neural network (RNN) and convolutional neural network (CNN), for national-scale landslide susceptibility mapping of Iran. We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors (altitude, slope degree, profile curvature, distance to river, aspect, plan curvature, distance to road, distance to fault, rainfall, geology and land-sue) to construct a geospatial database and divided the data into the training and the testing dataset. We then developed RNN and CNN algorithms to generate landslide susceptibility maps of Iran using the training dataset. We calculated the receiver operating characteristic (ROC) curve and used the area under the curve (AUC) for the quantitative evaluation of the landslide susceptibility maps using the testing dataset. Better performance in both the training and testing phases was provided by the RNN algorithm (AUC=0.88) than by the CNN algorithm (AUC=0.85). Finally, we calculated areas of susceptibility for each province and found that 6% and 14% of the land area of Iran is very highly and highly susceptible to future landslide events, respectively, with the highest susceptibility in Chaharmahal and Bakhtiari Province (33.8%). About 31% of cities of Iran are located in areas with high and very high landslide susceptibility. The results of the present study will be useful for the development of landslide hazard mitigation strategies.
166 citations
University of Basel1, Kangwon National University2, University of Pavia3, Karlsruhe Institute of Technology4, Federal University of Mato Grosso do Sul5, Wageningen University and Research Centre6, University of Ljubljana7, National Research Council8, University of Valencia9, University of New England (Australia)10, National Taipei University of Technology11, International Crops Research Institute for the Semi-Arid Tropics12, University Corporation for Atmospheric Research13, Czech University of Life Sciences Prague14, Augsburg College15, University of Turin16, University of Bari17, Leibniz Association18, Tottori University19, University of Orléans20, University of Adelaide21, Free University of Bozen-Bolzano22, Yazd University23, Spanish National Research Council24, Beijing Normal University25, University of Twente26, University of Leicester27, Julius Kühn-Institut28, Ludwig Maximilian University of Munich29, Agricultural Research Service30, Council for Scientific and Industrial Research31, University of Nebraska–Lincoln32, University of Rouen33, Romanian Academy34, Universidade do Estado de Minas Gerais35, Université catholique de Louvain36, University of Pisa37, University of Tehran38, University of Milan39, University of Alaska Fairbanks40, Wuhan Institute of Technology41, University of Maryland, College Park42, Aristotle University of Thessaloniki43, University of Aveiro44, Northwest A&F University45
TL;DR: This database intends to support the upcoming country-based United Nations global soil-erosion assessment in addition to helping to inform soil erosion research priorities by building a foundation for future targeted, in-depth analyses.
145 citations
TL;DR: In this article, the structural changes that occur after metabolic reactions in polyphenols (curcumin, quercetin, and catechins) and their effect on GM composition were investigated.
Abstract: Polyphenols (PPs) are the naturally occurring bioactive components in fruits and vegetables, and they are the most abundant antioxidant in the human diet. Studies are suggesting that ingestion of PPs might be helpful to ameliorate metabolic syndromes that may contribute in the prevention of several chronic disorders like diabetes, obesity, hypertension, and colon cancer. PPs have structural diversity which impacts their bioavailability as they accumulate in the large intestine and are extensively metabolized through gut microbiota (GM). Intestinal microbiota transforms PPs into their metabolites to make them bioactive. Interestingly, not only GM act on PPs to metabolize them but PPs also modulate the composition of GM. Thus, change in GM from pathogenic to beneficial ones may be helpful to ameliorate gut health and associated diseases. However, to overcome the low bioavailability of PPs, various approaches have been developed to improve their solubility and transportation through the gut. In this review, we present evidence supporting the structural changes that occur after metabolic reactions in PPs (curcumin, quercetin, and catechins) and their effect on GM composition that leads to improving overall gut health and helping to ameliorate metabolic disorders.
118 citations
TL;DR: In this paper, a de novo-designed protein-based biosensors are presented, which can be used to detect proteins such as SARS-CoV-2 and anti-SARS-antibodies.
Abstract: Naturally occurring protein switches have been repurposed for the development of biosensors and reporters for cellular and clinical applications1. However, the number of such switches is limited, and reengineering them is challenging. Here we show that a general class of protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which the binding of a peptide key triggers biological outputs of interest2. The designed sensors are modular molecular devices with a closed dark state and an open luminescent state; analyte binding drives the switch from the closed to the open state. Because the sensor is based on the thermodynamic coupling of analyte binding to sensor activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We create biosensors that can sensitively detect the anti-apoptosis protein BCL-2, the IgG1 Fc domain, the HER2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac troponin I and an anti-hepatitis B virus antibody with the high sensitivity required to detect these molecules clinically. Given the need for diagnostic tools to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)3, we used the approach to design sensors for the SARS-CoV-2 spike protein and antibodies against the membrane and nucleocapsid proteins. The former, which incorporates a de novo designed spike receptor binding domain (RBD) binder4, has a limit of detection of 15 pM and a luminescence signal 50-fold higher than the background level. The modularity and sensitivity of the platform should enable the rapid construction of sensors for a wide range of analytes, and highlights the power of de novo protein design to create multi-state protein systems with new and useful functions. A modular de novo designed biosensor platform consisting of a cage and key molecule is developed, and used to create sensors for seven distinct proteins including the spike protein from SARS-CoV-2 and anti-SARS antibodies.
113 citations
TL;DR: In this paper, the teaching-learning-based optimization (TLBO) and satin bowerbird optimizer (SBO) algorithms were applied to optimize the adaptive neuro-fuzzy inference system (ANFIS) model for landslide susceptibility mapping.
Abstract: As threats of landslide hazards have become gradually more severe in recent decades, studies on landslide prevention and mitigation have attracted widespread attention in relevant domains. A hot research topic has been the ability to predict landslide susceptibility, which can be used to design schemes of land exploitation and urban development in mountainous areas. In this study, the teaching-learning-based optimization (TLBO) and satin bowerbird optimizer (SBO) algorithms were applied to optimize the adaptive neuro-fuzzy inference system (ANFIS) model for landslide susceptibility mapping. In the study area, 152 landslides were identified and randomly divided into two groups as training (70%) and validation (30%) dataset. Additionally, a total of fifteen landslide influencing factors were selected. The relative importance and weights of various influencing factors were determined using the step-wise weight assessment ratio analysis (SWARA) method. Finally, the comprehensive performance of the two models was validated and compared using various indexes, such as the root mean square error (RMSE), processing time, convergence, and area under receiver operating characteristic curves (AUROC). The results demonstrated that the AUROC values of the ANFIS, ANFIS-TLBO and ANFIS-SBO models with the training data were 0.808, 0.785 and 0.755, respectively. In terms of the validation dataset, the ANFIS-SBO model exhibited a higher AUROC value of 0.781, while the AUROC value of the ANFIS-TLBO and ANFIS models were 0.749 and 0.681, respectively. Moreover, the ANFIS-SBO model showed lower RMSE values for the validation dataset, indicating that the SBO algorithm had a better optimization capability. Meanwhile, the processing time and convergence of the ANFIS-SBO model were far superior to those of the ANFIS-TLBO model. Therefore, both the ensemble models proposed in this paper can generate adequate results, and the ANFIS-SBO model is recommended as the more suitable model for landslide susceptibility assessment in the study area considered due to its excellent accuracy and efficiency.
109 citations
TL;DR: In this article, the authors analyzed the land degradation footprint on global arable lands, using complex geospatial data on certain major degradation processes, i.e. aridity, soil erosion, vegetation decline, soil salinization and soil organic carbon decline.
104 citations
TL;DR: In this paper, a human brain extracellular matrix was used to provide brain-specific cues and a microfluidic device with periodic flow to improve the survival and reduce the variability of organoids.
Abstract: Brain organoids derived from human pluripotent stem cells provide a highly valuable in vitro model to recapitulate human brain development and neurological diseases. However, the current systems for brain organoid culture require further improvement for the reliable production of high-quality organoids. Here, we demonstrate two engineering elements to improve human brain organoid culture, (1) a human brain extracellular matrix to provide brain-specific cues and (2) a microfluidic device with periodic flow to improve the survival and reduce the variability of organoids. A three-dimensional culture modified with brain extracellular matrix significantly enhanced neurogenesis in developing brain organoids from human induced pluripotent stem cells. Cortical layer development, volumetric augmentation, and electrophysiological function of human brain organoids were further improved in a reproducible manner by dynamic culture in microfluidic chamber devices. Our engineering concept of reconstituting brain-mimetic microenvironments facilitates the development of a reliable culture platform for brain organoids, enabling effective modeling and drug development for human brain diseases.
104 citations
TL;DR: This comprehensive review paper discusses the origin of CRISPR-Cas9 systems and their therapeutic potential against various genetic disorders, including cancer, allergy, immunological disorders, Duchenne muscular dystrophy, cardiovascular disorders, neurological disorders, liver-related disorders, cystic fibrosis, blood- related disorders, eye-related Disorders, and viral infection.
90 citations
University of Liège1, Katholieke Universiteit Leuven2, University of Córdoba (Spain)3, University of Pavia4, Kangwon National University5, Universidad Pública de Navarra6, Universidad Autónoma de San Luis Potosí7, Tottori University8, Maria Curie-Skłodowska University9, Université catholique de Louvain10, University of Palermo11, Instituto Politécnico Nacional12, Anglia Ruskin University13, Moscow State University14, Russian Academy of Sciences15, Alexandru Ioan Cuza University16, University of Grenoble17, University of Belgrade18, Comenius University in Bratislava19, University of Flensburg20, Commonwealth Scientific and Industrial Research Organisation21, University of Central Asia22, University of the Sunshine Coast23
TL;DR: In this article, a review of >590 scientific articles and policy documents is presented to assess and simulate gully erosion and its impacts at regional to continental scales, and a series of recommendations for further research and policy development are provided.
83 citations
TL;DR: 3D-printed hybrid biodegradable hydrogels composed of alginate, gelatin, and cellulose nanocrystals were prepared to provide a favorable environment for cell proliferation, adhesion, nutrients exchange, and matrix mineralization for bone tissue engineering applications and have the potential to explore as a biomaterial for tissue engineering.
TL;DR: Multiple hybrid machine-learning models were developed to address parameter optimization limitations and enhance the spatial prediction of landslide susceptibility models to confirm the ability of metaheuristic algorithms to improve model performance.
Abstract: In this study, we developed multiple hybrid machine-learning models to address parameter optimization limitations and enhance the spatial prediction of landslide susceptibility models. We created a geographic information system database, and our analysis results were used to prepare a landslide inventory map containing 359 landslide events identified from Google Earth, aerial photographs, and other validated sources. A support vector regression (SVR) machine-learning model was used to divide the landslide inventory into training (70%) and testing (30%) datasets. The landslide susceptibility map was produced using 14 causative factors. We applied the established gray wolf optimization (GWO) algorithm, bat algorithm (BA), and cuckoo optimization algorithm (COA) to fine-tune the parameters of the SVR model to improve its predictive accuracy. The resultant hybrid models, SVR-GWO, SVR-BA, and SVR-COA, were validated in terms of the area under curve (AUC) and root mean square error (RMSE). The AUC values for the SVR-GWO (0.733), SVR-BA (0.724), and SVR-COA (0.738) models indicate their good prediction rates for landslide susceptibility modeling. SVR-COA had the greatest accuracy, with an RMSE of 0.21687, and SVR-BA had the least accuracy, with an RMSE of 0.23046. The three optimized hybrid models outperformed the SVR model (AUC = 0.704, RMSE = 0.26689), confirming the ability of metaheuristic algorithms to improve model performance.
TL;DR: In this paper, the authors present a review of different bio and nanosensors employed for monitoring agricultural ecosystems and also highlight the factor affecting their implementation from proof-of-concept to the commercialization stage.
Abstract: Previous decades have witnessed a lot of challenges that have provoked a dire need of ensuring global food security. The process of augmenting food production has made the agricultural ecosystems to face a lot of challenges like the persistence of residual particles of different pesticides, accretion of heavy metals, and contamination with toxic elemental particles which have negatively influenced the agricultural environment. The entry of such toxic elements into the human body via agricultural products engenders numerous health effects such as nerve and bone marrow disorders, metabolic disorders, infertility, disruption of biological functions at the cellular level, and respiratory and immunological diseases. The exigency for monitoring the agroecosystems can be appreciated by contemplating the reported 220,000 annual deaths due to toxic effects of residual pesticidal particles. The present practices employed for monitoring agroecosystems rely on techniques like gas chromatography, high-performance liquid chromatography, mass spectroscopy, etc. which have multiple constraints, being expensive, tedious with cumbersome protocol, demanding sophisticated appliances along with skilled personnel. The past couple of decades have witnessed a great expansion of the science of nanotechnology and this development has largely facilitated the development of modest, quick, and economically viable bio and nanosensors for detecting different entities contaminating the natural agroecosystems with an advantage of being innocuous to human health. The growth of nanotechnology has offered rapid development of bio and nanosensors for the detection of several composites which range from several metal ions, proteins, pesticides, to the detection of complete microorganisms. Therefore, the present review focuses on different bio and nanosensors employed for monitoring agricultural ecosystems and also trying to highlight the factor affecting their implementation from proof-of-concept to the commercialization stage.
TL;DR: DLIR significantly reduced the image noise in chest LDCT scan images compared with ASiR-V 30% while maintaining superior image quality.
Abstract: OBJECTIVE Iterative reconstruction degrades image quality. Thus, further advances in image reconstruction are necessary to overcome some limitations of this technique in low-dose computed tomography (LDCT) scan of the chest. Deep-learning image reconstruction (DLIR) is a new method used to reduce dose while maintaining image quality. The purposes of this study was to evaluate image quality and noise of LDCT scan images reconstructed with DLIR and compare with those of images reconstructed with the adaptive statistical iterative reconstruction-Veo at a level of 30% (ASiR-V 30%). MATERIALS AND METHODS This retrospective study included 58 patients who underwent LDCT scan for lung cancer screening. Datasets were reconstructed with ASiR-V 30% and DLIR at medium and high levels (DLIR-M and DLIR-H, respectively). The objective image signal and noise, which represented mean attenuation value and standard deviation in Hounsfield units for the lungs, mediastinum, liver, and background air, and subjective image contrast, image noise, and conspicuity of structures were evaluated. The differences between CT scan images subjected to ASiR-V 30%, DLIR-M, and DLIR-H were evaluated. RESULTS Based on the objective analysis, the image signals did not significantly differ among ASiR-V 30%, DLIR-M, and DLIR-H (p = 0.949, 0.737, 0.366, and 0.358 in the lungs, mediastinum, liver, and background air, respectively). However, the noise was significantly lower in DLIR-M and DLIR-H than in ASiR-V 30% (all p < 0.001). DLIR had higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) than ASiR-V 30% (p = 0.027, < 0.001, and < 0.001 in the SNR of the lungs, mediastinum, and liver, respectively; all p < 0.001 in the CNR). According to the subjective analysis, DLIR had higher image contrast and lower image noise than ASiR-V 30% (all p < 0.001). DLIR was superior to ASiR-V 30% in identifying the pulmonary arteries and veins, trachea and bronchi, lymph nodes, and pleura and pericardium (all p < 0.001). CONCLUSION DLIR significantly reduced the image noise in chest LDCT scan images compared with ASiR-V 30% while maintaining superior image quality.
TL;DR: It is suggested that exogenously administered long-acting nanoparticulate DNase-1 can effectively reduce cfDNA levels and neutrophil activities and may be used as a potential therapeutic intervention for life-threatening SARS-CoV-2-mediated illnesses.
TL;DR: This review aims to introduce a self-sustainable MEC technology by combining conventional MECs with advanced carbon-neutral technologies, such as solar-, microbial-, osmotic-, and thermoelectric-powers (and their combinations).
TL;DR: In this article, the origin, shape, impact, and mitigation strategies of soil and groundwater microplastics are reviewed and found that littering is the main origin of microplastic in global topsoils, while greenhouses are the main source of micro-plastics in South Korea.
Abstract: Plastic particles of less than 5 mm size, referred as microplastics, have recently become a major environmental issue. While microplastics are well known in marine and lake systems, there have been less investigations in soils and groundwater. Here we review the origin, shape, impact, and mitigation strategies of soil and groundwater microplastics. We found that littering is the main origin of microplastics in global topsoils, while greenhouses are the main source of microplastics in South Korea. Fibers and pellets are dominant microplastic shapes in soil and groundwater. Microplastic contamination of soil and groundwater is detrimental to human health, plants, nematodes, earthworms, and soil properties. Remediation methods include pyrolysis, replacing plastics by biodegradable plastics, plastic filtration, and subsequent chemical or biological degradation.
TL;DR: In this article, a variety of metallurgical methods for improving both strength and trade-offs have been exploited through the morphological control of microstructure of metal together with improving its trade-off properties of ductility, formability and conductivity.
TL;DR: In this article, a 96-well assay that integrates the enrichment of EVs by antibody-coated magnetic beads and the electrochemical detection, in less than one hour of total assay time, of EV-bound proteins after enzymatic amplification was presented.
Abstract: Assays for cancer diagnosis via the analysis of biomarkers on circulating extracellular vesicles (EVs) typically have lengthy sample workups, limited throughput or insufficient sensitivity, or do not use clinically validated biomarkers. Here we report the development and performance of a 96-well assay that integrates the enrichment of EVs by antibody-coated magnetic beads and the electrochemical detection, in less than one hour of total assay time, of EV-bound proteins after enzymatic amplification. By using the assay with a combination of antibodies for clinically relevant tumour biomarkers (EGFR, EpCAM, CD24 and GPA33) of colorectal cancer (CRC), we classified plasma samples from 102 patients with CRC and 40 non-CRC controls with accuracies of more than 96%, prospectively assessed a cohort of 90 patients, for whom the burden of tumour EVs was predictive of five-year disease-free survival, and longitudinally analysed plasma from 11 patients, for whom the EV burden declined after surgery and increased on relapse. Rapid assays for the detection of combinations of tumour biomarkers in plasma EVs may aid cancer detection and patient monitoring.
TL;DR: The COVID-19 pandemic has caused dramatic changes on a global scale as mentioned in this paper, and the restricted movement that has arisen from the pandemic is a major threat to tourism.
Abstract: The COVID-19 pandemic has caused dramatic changes on a global scale. According to the United Nations World Tourism Organization (2020), the restricted movement that has arisen from the pandemic is ...
TL;DR: The calculated thermodynamic parameters demonstrated that the competitive adsorption of pharmaceuticals on the NaOH-activated SCW biochar compared to pristine SCWBiochar occurred more spontaneously over the entire pH (5.0-11.0) and ionic strength (NaCl: 0-0.125 M) ranges.
TL;DR: In this article, it was shown that intestine-derived HDL traverses the portal vein in the HDL3 subspecies form, in complex with lipopolysaccharide (LPS)-binding protein (LBP), preventing LPS binding to and inflammatory activation of liver macrophages and instead supported extracellular inactivation of LPS.
Abstract: The biogenesis of high-density lipoprotein (HDL) requires apoA1 and the cholesterol transporter ABCA1. Although the liver generates most of the HDL in the blood, HDL synthesis also occurs in the small intestine. Here, we show that intestine-derived HDL traverses the portal vein in the HDL3 subspecies form, in complex with lipopolysaccharide (LPS)-binding protein (LBP). HDL3, but not HDL2 or low-density lipoprotein, prevented LPS binding to and inflammatory activation of liver macrophages and instead supported extracellular inactivation of LPS. In mouse models involving surgical, dietary, or alcoholic intestinal insult, loss of intestine-derived HDL worsened liver injury, whereas outcomes were improved by therapeutics that elevated and depended upon raising intestinal HDL. Thus, protection of the liver from injury in response to gut-derived LPS is a major function of intestinally synthesized HDL.
TL;DR: In this article, the authors discuss the role of GM dysbiosis in Alzheimer's disease and potential therapeutic strategies to modulate GM in AD, including diet, probiotics, or fecal microbiota transplantation.
Abstract: The gut microbiota (GM) represents a diverse and dynamic population of microorganisms and about 100 trillion symbiotic microbial cells that dwell in the gastrointestinal tract. Studies suggest that the GM can influence the health of the host, and several factors can modify the GM composition, such as diet, drug intake, lifestyle, and geographical locations. Gut dysbiosis can affect brain immune homeostasis through the microbiota–gut–brain axis and can play a key role in the pathogenesis of neurodegenerative diseases, including dementia and Alzheimer’s disease (AD). The relationship between gut dysbiosis and AD is still elusive, but emerging evidence suggests that it can enhance the secretion of lipopolysaccharides and amyloids that may disturb intestinal permeability and the blood–brain barrier. In addition, it can promote the hallmarks of AD, such as oxidative stress, neuroinflammation, amyloid-beta formation, insulin resistance, and ultimately the causation of neural death. Poor dietary habits and aging, along with inflammatory responses due to dysbiosis, may contribute to the pathogenesis of AD. Thus, GM modulation through diet, probiotics, or fecal microbiota transplantation could represent potential therapeutics in AD. In this review, we discuss the role of GM dysbiosis in AD and potential therapeutic strategies to modulate GM in AD.
Ajou University1, University of Ulsan2, Chung-Ang University3, Ewha Womans University4, Seoul National University Hospital5, Hanyang University6, Kangwon National University7, Sungkyunkwan University8, Samsung Medical Center9, Catholic University of Korea10, Chonnam National University11, Jeju National University12, Korea University13, Soonchunhyang University14, St Mary's Hospital15, Yonsei University16
TL;DR: The Korean Society of Thyroid Radiology (KSThR) published consensus recommendations for US-based management of thyroid nodules in 2011 and revised them in 2016 as mentioned in this paper, which has contributed to the rapidly rising incidence of low risk papillary thyroid carcinoma over the last 20 years.
Abstract: Incidental thyroid nodules are commonly detected on ultrasonography (US). This has contributed to the rapidly rising incidence of low-risk papillary thyroid carcinoma over the last 20 years. The appropriate diagnosis and management of these patients is based on the risk factors related to the patients as well as the thyroid nodules. The Korean Society of Thyroid Radiology (KSThR) published consensus recommendations for US-based management of thyroid nodules in 2011 and revised them in 2016. These guidelines have been used as the standard guidelines in Korea. However, recent advances in the diagnosis and management of thyroid nodules have necessitated the revision of the original recommendations. The task force of the KSThR has revised the Korean Thyroid Imaging Reporting and Data System and recommendations for US lexicon, biopsy criteria, US criteria of extrathyroidal extension, optimal thyroid computed tomography protocol, and US follow-up of thyroid nodules before and after biopsy. The biopsy criteria were revised to reduce unnecessary biopsies for benign nodules while maintaining an appropriate sensitivity for the detection of malignant tumors in small (1-2 cm) thyroid nodules. The goal of these recommendations is to provide the optimal scientific evidence and expert opinion consensus regarding US-based diagnosis and management of thyroid nodules.
TL;DR: In this article, the capability of convolutional neural network and recurrent neural network (NNETC) models for flood hazard mapping in urban environments was evaluated. And the prediction quality of the models was validated using the area under the receiver operating characteristic curve (AUC) and root mean square error (RMSE).
TL;DR: In this article, a review of magnetic nanoparticles in hyperthermia treatment by an external alternating magnetic field is presented, where the authors build a bridge between the synthesis/coating of magnetic nano-articles and their practical application in magnetic hyper-thermia.
Abstract: The activation of magnetic nanoparticles in hyperthermia treatment by an external alternating magnetic field is a promising technique for targeted cancer therapy. The external alternating magnetic field generates heat in the tumor area, which is utilized to kill cancerous cells. Depending on the tumor type and site to be targeted, various types of magnetic nanoparticles, with variable coating materials of different shape and surface charge, have been developed. The tunable physical and chemical properties of magnetic nanoparticles enhance their heating efficiency. Moreover, heating efficiency is directly related with the product values of the applied magnetic field and frequency. Protein corona formation is another important parameter affecting the heating efficiency of MNPs in magnetic hyperthermia. This review provides the basics of magnetic hyperthermia, mechanisms of heat losses, thermal doses for hyperthermia therapy, and strategies to improve heating efficiency. The purpose of this review is to build a bridge between the synthesis/coating of magnetic nanoparticles and their practical application in magnetic hyperthermia.
TL;DR: In this article, a pH and over-expressed nucleolin receptor responsive nano-drug delivery system (nDDS) composed by bio-synthesized gold nanoparticles (Au NPs), chitosan (CS) with aptamer (Apt) and doxorubicin (Dox) was developed for the improved glioblastoma treatment.
University of Ljubljana1, Kangwon National University2, University of Basel3, Karlsruhe Institute of Technology4, Federal University of Mato Grosso do Sul5, University of São Paulo6, Wageningen University and Research Centre7, National Research Council8, University of Valencia9, University of New England (Australia)10, National Taipei University of Technology11, International Crops Research Institute for the Semi-Arid Tropics12, University Corporation for Atmospheric Research13, Czech University of Life Sciences Prague14, Augsburg College15, University of Turin16, University of Bari17, Leibniz Association18, Tottori University19, Jiangxi University of Finance and Economics20, University of Adelaide21, Free University of Bozen-Bolzano22, Yazd University23, Spanish National Research Council24, Beijing Normal University25, University of Twente26, University of Pavia27, University of Leicester28, Julius Kühn-Institut29, École Normale Supérieure30, Agricultural Research Service31, Council for Scientific and Industrial Research32, University of Nebraska–Lincoln33, University of Rouen34, Romanian Academy35, Universidade do Estado de Minas Gerais36, Université catholique de Louvain37, University of Pisa38, University of Tehran39, University of Milan40, University of Alaska Fairbanks41, Wuhan Institute of Technology42, University of Maryland, College Park43, Aristotle University of Thessaloniki44, University of Aveiro45, Northwest A&F University46
TL;DR: In this article, the authors investigated the impact of the number of authors, the publication type and the selected journal on the citation count of soil erosion modeling research papers and found that the selection of the soil erosion model has the largest impact on the publication citations, followed by the modelling scale and the publication's CiteScore.
TL;DR: In this paper, the macro properties (residual compressive strength), meso properties (mesoscopic images), and micro properties (reaction products and pore structures) of paste specimens with various limestone and calcined clay contents at elevated temperatures (20, 300, 550, and 900 ǫ) are experimentally investigated.
Abstract: In this study, the macro properties (residual compressive strength), meso properties (mesoscopic images), and micro properties (reaction products and pore structures) of paste specimens with various limestone and calcined clay contents at elevated temperatures (20, 300, 550, and 900 °C) are experimentally investigated. According to the experimental results, (1) the strengths of all samples increase at 300 °C, while those of the LC3 ternary blended pastes increase more significantly because of the formation of katoite and the further hydration of binders. After the treatments at 550 and 900 °C, the reduction in the strengths of the LC3 samples is greater than that of the plain paste. (2) With further increasing temperature, all samples generate more meso cracks. (3) At 900 °C, a large gehlenite crystalline phase is formed in the samples with calcined clay. In summary, the microscopic explanation for the macroscopic and mesoscopic properties of LC3 paste at elevated temperature is investigated.
TL;DR: In this article, a composite nanopaper with high peroxidase (POD)-like activity was prepared by a rapid microwave-assisted method and immobilized on cellulose nanofibrils (CNF) to produce a composite nanozyme, which was evaluated by the oxidation of 3,3′,5,5′-tetramethylbenzidine (TMB).
Abstract: Fe-doped carbon dots (FeCDs) with high peroxidase (POD)-like activity were prepared by a rapid microwave-assisted method and immobilized on cellulose nanofibrils (CNF) to produce a composite nanopaper. The POD activity of the nanopaper was evaluated by the oxidation of 3,3′,5,5′-tetramethylbenzidine (TMB) and applied to the colorimetric detections of hydrogen peroxide (H2O2) and glucose. CNF acted as a support for the nanozyme, thus imparting it with reusability. It also adsorbed the chromogen during the reaction to induce a color change, thus acting as a test strip for portable on-site detection. A smartphone was employed to monitor this color change which made the whole detection process simple and economical. Under optimal conditions, this method afforded linear ranges of 6–42 μM and 10–70 μM and detection limits of 0.93 and 1.73 μM for the H2O2 and glucose, respectively. The results of the quantification of glucose in human serum samples were comparable to those of the standard glucose oxidase (GOD)–POD method. Further, the nanopaper was potentially reused for ten cycles and presented over a month of shelf life.