Publications by authors named "Chunhua Yang"

136 Publications

Lipidomic metabolism associated with acetic acid priming-induced salt tolerance in Carex rigescens.

Plant Physiol Biochem 2021 Sep 1;167:665-677. Epub 2021 Sep 1.

Department of Turfgrass Science and Engineering, College of Grassland Science and Technology, China Agricultural University, Beijing, 100193, PR China. Electronic address:

Acetic acid priming may mitigate salt stress to plants by modulating lipid metabolism. Carex rigescens is a stress-tolerant turfgrass species with a widespread distribution in north China. The objective of this study was to figure out whether modification of lipid profiles, including the contents, compositions and saturation levels of leaf lipids, may contribute to acetic acid modulated salt tolerance in C. rigescens. Plants of C. rigescens were primed with or without acetic acid (30 mM) and subsequently exposed to salt stress (300 mM NaCl) for 15 days. Salt stress affected the physiological performance of C. rigescens, while acetic acid-primed plants showed significantly lower malondialdehyde content, proline content, and electrolyte leakage than non-primed plants under salt stress. Acetic acid priming enhanced the contents of phospholipids and glycolipids involved in membrane stabilization and stress signaling (phosphatidic acid, phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol, digalactosyl diacylglycerol, monogalactosyl diacylglycerol, and sulfoquinovosyldiacylglycerol), reduced the content of toxic lipid intermediates (free fatty acids) during subsequent exposure to salt stress. Furthermore, expression levels of genes involved in lipid metabolism such as CK and PLDα changed due to acetic acid priming. These results demonstrated that acetic acid priming could enhance salt tolerance of C. rigescens by regulating lipid metabolism. The lipids could be used as biomarkers to select for salt-tolerant grass germplasm.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.plaphy.2021.08.045DOI Listing
September 2021

Comparison of Sericins from Different Sources as Natural Therapeutics against Ulcerative Colitis.

ACS Biomater Sci Eng 2021 09 1;7(9):4626-4636. Epub 2021 Sep 1.

School of Materials and Energy, Southwest University, 2 Tiansheng Road, Beibei, Chongqing 400715, P. R. China.

Sericin has become a promising natural anti-inflammatory protein. However, the biological functions of sericins largely depend on their origins; no study has yet been carried out to comparatively investigate the therapeutic effects of sericins from different sources against inflammatory diseases. Herein, we extracted and purified three kinds of sericins, namely silkworm sericin (SS), tussah sericin (TS), and castor silk sericin (CSS). These sericins showed negligible cytotoxicities against colitis-associated cells (colon epitheliums and activated macrophages). Further investigations displayed that these sericins could remarkably downregulate the secreted amounts of TNF-α, promote the recovery of the damaged colonic epithelial barrier, and eliminate endogenous reactive oxygen species in Raw 264.7 macrophages and . experiments demonstrated that chitosan/alginate hydrogel-encapsulating SS could achieve efficient accumulation of SS in the colitis tissues and thereby play a more effective role in relieving ulcerative colitis (UC) than TS and CSS. Our findings collectively demonstrate that SS can be extracted, formulated, and used as a robust therapeutic agent for the oral treatment of UC.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/acsbiomaterials.1c00256DOI Listing
September 2021

6 Circulating miRNAs can be used as Non-invasive Biomarkers for the Detection of Cervical Lesions.

J Cancer 2021 22;12(17):5106-5113. Epub 2021 Jun 22.

Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, P.R. China.

Cervical cancer is the most common malignant tumor in the female reproductive system, while the efficacy of routine screening strategy is unsatisfied. New molecular tests need to be developed. miRNAs participate in many pathologic processes, and circulating miRNAs are promising non-invasive biomarkers in tumors. This study aimed to identify the circulating miRNAs associated with both cervical cancer and cervical intraepithelial neoplasia (CIN), and establish a non-invasive classifier for cervical lesions using circulating miRNAs. This study consisted of 5 steps: miRNAs screening, miRNAs validation, classifier establishment, independent validation and analyses. Three cohorts were included in our study: In screening stage, 24 samples including 14 cases and 10 controls were retrieved; In validation stage, 380 samples including 200 cases and 180 controls were recruited; In independent validation stage, 47 samples comprising 26 cases and 21 controls were included. miRNAs were quantified by RT-qPCR. A classifier was built with random forest algorithm using validation samples and selected miRNAs, which were then validated in an independent cohort. To explore the function of selected miRNAs, analyses were performed. Target genes of selected miRNAs were predicted by the overlap of three online tools. Enrichment analyses were executed with predicted target genes. Differential analysis of target genes was carried out with open access expression assay datasets of cervical tissues. 6 miRNAs (hsa-miR-26b-5p, hsa-miR-146b-5p, hsa-miR-191-5p, hsa-miR-484, hsa-miR-574-3p, hsa-miR-625-3p) were screened out from 754 miRNAs. They were associated with cervical lesions and were selected to establish a classifier. The accuracy of the classifier were 0.7218 (0.7117, 0.7319) in validation samples, which was 0.7021 in the independent cohort. 958 target genes were predicted and enriched in 23 pathways (MAPK, human papillomavirus infection and Wnt signaling pathway, etc.). 55 genes were identified as the most likely target genes by differential analysis. The 6 circulating miRNAs were related to cervical lesions and could serve as non-invasive biomarkers.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.7150/jca.51141DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8317520PMC
June 2021

Oral delivery of natural active small molecules by polymeric nanoparticles for the treatment of inflammatory bowel diseases.

Adv Drug Deliv Rev 2021 09 24;176:113887. Epub 2021 Jul 24.

State Key Laboratory of Silkworm Genome Biology, College of Sericulture, Textile, and Biomass Sciences, Southwest University, Beibei, Chongqing 400715, China. Electronic address:

The incidence of inflammatory bowel disease (IBD) is rapidly rising throughout the world. Although tremendous efforts have been made, limited therapeutics are available for IBD management. Natural active small molecules (NASMs), which are a gift of nature to humanity, have been widely used in the prevention and alleviation of IBD; they have numerous advantageous features, including excellent biocompatibility, pharmacological activity, and mass production potential. Oral route is the most common and acceptable approach for drug administration, but the clinical application of NASMs in IBD treatment via oral route has been seriously restricted by their inherent limitations such as high hydrophobicity, instability, and poor bioavailability. With the development of nanotechnology, polymeric nanoparticles (NPs) have provided a promising platform that can efficiently encapsulate versatile NASMs, overcome multiple drug delivery barriers, and orally deliver the loaded NASMs to targeted tissues or cells while enhancing their stability and bioavailability. Thus, NPs can enhance the preventive and therapeutic effects of NASMs against IBD. Herein, we summarize the recent knowledge about polymeric matrix-based carriers, targeting ligands for drug delivery, and NASMs. We also discuss the current challenges and future developmental directions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.addr.2021.113887DOI Listing
September 2021

Deep Neural Network-Embedded Stochastic Nonlinear State-Space Models and Their Applications to Process Monitoring.

IEEE Trans Neural Netw Learn Syst 2021 Jul 26;PP. Epub 2021 Jul 26.

Process complexities are characterized by strong nonlinearities, dynamics, and uncertainties. Monitoring such a complex process requires a high-quality model describing the corresponding nonlinear dynamic behavior. The proposed model is constructed using deep neural networks (DNNs) to represent the state transition and observation generation, both of which constitute a stochastic nonlinear state-space model. A new bidirectional recurrent neural network (RNN), creating a connection of the hidden layer between a forward RNN and a backward RNN, is proposed to generate the filtering estimation and the smoothing estimation of process states which further generate observations with DNN-based process models. The smoothing estimator and the process model are first learned offline with all collected samples. Then the filtering estimator is fine-tuned by the learned smoother and process models to achieve real-time monitoring since the filter state is estimated based on the past and the current observations. Two indices are designed based on the learned model for monitoring the process anomaly. The proposed process monitoring model can deal with complex nonlinearities, process dynamics, and process uncertainties, all of which can be very challenging for the existing methods, such as kernel mapping and stacked auto-encoder. Two case studies validate that the effectiveness of the proposed method outperforms the other comparative methods by at least 10% when using the averaged fault detection rate in the industrial experimental data.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1109/TNNLS.2021.3086323DOI Listing
July 2021

iPCPA: Interval permutation combination population analysis for spectral wavelength selection.

Anal Chim Acta 2021 Aug 14;1171:338635. Epub 2021 May 14.

School of Automation, Central South University, 410083, Changsha, China.

As one of the most important preprocessing procedures in spectral detection, wavelength selection approaches play an irreplaceable role in reducing the model overfitting and prediction errors. In this paper, we propose a two-step wavelength selection method called interval permutation combination population analysis (iPCPA), which improves the selective performance by combining three different wavelength selection algorithms. First, interval partial least squares (iPLS) is used as the rough selection step to efficiently exclude the uninformative variables in the spectrum, which reduces the variable space and ensures that the following selection step can focus on selecting informative variables. Then, permutation combination population analysis (PCPA) is proposed, which introduces the core idea of permutation analysis into the variable combination population analysis (VCPA) and hence improves its ability in evaluating the importance of informative variables. Six state-of-the-art wavelength selection methods are used to compare with iPCPA and their performances are tested by using three real spectral datasets: corn, beer, and soil datasets. The final experimental results prove that iPCPA has the best predictive abilities, combined with a good selective performance.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.aca.2021.338635DOI Listing
August 2021

Fault Diagnosis of Hydraulic Systems Based on Deep Learning Model With Multirate Data Samples.

IEEE Trans Neural Netw Learn Syst 2021 Jun 10;PP. Epub 2021 Jun 10.

Hydraulic systems are a class of typical complex nonlinear systems, which have been widely used in manufacturing, metallurgy, energy, and other industries. Nowadays, the intelligent fault diagnosis problem of hydraulic systems has received increasing attention for it can increase operational safety and reliability, reduce maintenance cost, and improve productivity. However, because of the high nonlinear and strong fault concealment, the fault diagnosis of hydraulic systems is still a challenging task. Besides, the data samples collected from the hydraulic system are always in different sampling rates, and the coupling relationship between the components brings difficulties to accurate data acquisition. To solve the above issues, a deep learning model with multirate data samples is proposed in this article, which can extract features from the multirate sampling data automatically without expertise, thus it is more suitable in the industrial situation. Experiment results demonstrate that the proposed method achieves high diagnostic and fault pattern recognition accuracy even when the imbalance degree of sample data is as large as 1:100. Moreover, the proposed method can increase about 10% diagnosis accuracy when compared with some state-of-the-art methods.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1109/TNNLS.2021.3083401DOI Listing
June 2021

Causal augmented ConvNet: A temporal memory dilated convolution model for long-sequence time series prediction.

ISA Trans 2021 May 19. Epub 2021 May 19.

State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, PR China. Electronic address:

A number of deep learning models have been proposed to capture the inherent information in multivariate time series signals. However, most of the existing models are suboptimal, especially for long-sequence time series prediction tasks. This work presents a causal augmented convolution network (CaConvNet) and its application for long-sequence time series prediction. First, the model utilizes dilated convolution with enlarged receptive fields to enhance global feature extraction in time series. Secondly, to effectively capture the long-term dependency and to further extract multiscale features that represent different operating conditions, the model is augmented with a long-short term memory network. Thirdly, the CaConvNet is further optimized with a dynamic hyperparameter search algorithm to reduce uncertainties and the cost of manual hyperparameter selection. Finally, the model is extensively evaluated on a predictive maintenance task using the turbofan aircraft engine run-to-failure prognostic benchmark dataset (C-MAPSS). The performance of the proposed CaConvNet is also compared with four conventional deep learning models and seven different state-of-the-art predictive models. The evaluation metrics show that the proposed CaConvNet outperforms other models in most of the prognostic tasks. Moreover, a comprehensive ablation study is performed to provide insights into the contribution of each sub-structure of the CaConvNet model to the observed performance. The results of the ablation study as well as the performance improvement of CaConvNet are discussed in this paper.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.isatra.2021.05.026DOI Listing
May 2021

Atomic Force Microscopy to Characterize Ginger Lipid-Derived Nanoparticles (GLDNP).

Bio Protoc 2021 Apr 5;11(7):e3969. Epub 2021 Apr 5.

Institute for Biomedical Sciences, Center for Diagnostics and Therapeutics, Digestive Disease Research Group, Georgia State University, Atlanta, GA, USA.

We have demonstrated that a specific population of ginger-derived nanoparticles (GDNP-2) could effectively target the colon, reduce colitis, and alleviate colitis-associated colon cancer. Naturally occurring GDNP-2 contains complex bioactive components, including lipids, proteins, miRNAs, and ginger secondary metabolites (gingerols and shogaols). To construct a nanocarrier that is more clearly defined than GDNP-2, we isolated lipids from GDNP-2 and demonstrated that they could self-assemble into ginger lipid-derived nanoparticles (GLDNP) in an aqueous solution. GLDNP can be used as a nanocarrier to deliver drug candidates such as 6-shogaol or its metabolites (M2 and M13) to the colon. To characterize the nanostructure of GLDNP, our lab extensively used atomic force microscopy (AFM) technique as a tool for visualizing the morphology of the drug-loaded GLDNP. Herein, we provide a detailed protocol for demonstrating such a process.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.21769/BioProtoc.3969DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8054207PMC
April 2021

Consensus for Second-Order Discrete-Time Agents With Position Constraints and Delays.

IEEE Trans Cybern 2021 Apr 19;PP. Epub 2021 Apr 19.

This article addresses a consensus problem of second-order discrete-time agents in general directed networks with nonuniform position constraints, switching topologies, and communication delays. A projection operation is performed to ensure the agents stay in some given convex sets, and a distributed algorithm is employed for the consensus achievement of all agents. The analysis approach is to use a linear transformation to convert the original system into an equivalent system and then merge the nonlinear error term into the convex null of the agents' states so as to prove the consensus convergence of the system based on the properties of the non-negative matrices. It is shown that all agents finally converge to a consensus point while their positions stay in the corresponding constraint sets as long as the union of the communication graphs among each certain time interval is strongly connected even when the communication delays are considered. Finally, numerical simulation examples are given to show the theoretical results.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1109/TCYB.2021.3052775DOI Listing
April 2021

PepT1-knockout mice harbor a protective metabolome beneficial for intestinal wound healing.

Am J Physiol Gastrointest Liver Physiol 2021 05 24;320(5):G888-G896. Epub 2021 Mar 24.

Institute for Biomedical Sciences, Digestive Diseases Research Group, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia.

Genetic knockout (KO) of peptide transporter-1 (PepT1) protein is known to provide resistance to acute colitis and colitis-associated cancer (CAC) in mouse models. However, it was unclear which molecule(s) or pathway(s) formed the basis for these protective effects. Recently, we demonstrated that the PepT1 microbiota is sufficient to protect against colitis and CAC. Given that PepT1 KO alters the gut microbiome and thereby changes the intestinal metabolites that are ultimately reflected in the feces, we investigated the fecal metabolites of our PepT1 KO mice. Using a liquid chromatography-mass spectrometry (LC-MS)-based untargeted-metabolomics technique, we found that the fecal metabolites were significantly different between the KO and normal wild-type (WT) mice. Among the altered fecal metabolites, tuberonic acid (TA) was sevenfold higher in KO mouse feces than in WT mouse feces. Accordingly, we studied whether the increased TA could direct an anti-inflammatory effect. Using in vitro models, we discovered that TA not only prevented lipopolysaccharide (LPS)-induced inflammation in macrophages but also improved the epithelial cell healing processes. Our results suggest that TA, and possibly other fecal metabolites, play a crucial role in the pathway(s) associated with the anticolitis effects of PepT1 KO. Fecal metabolites were significantly different between the KO and normal wild-type (WT) mice. One fecal metabolite, tuberonic acid (TA), was sevenfold higher in KO mouse feces than in WT mouse feces. TA prevented lipopolysaccharide (LPS)-induced inflammation in macrophages and improved the epithelial cell healing process.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1152/ajpgi.00299.2020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8202197PMC
May 2021

Complex networks identification using Bayesian model with independent Laplace prior.

Chaos 2021 Jan;31(1):013107

School of Automation, Central South University, Changsha 410083, China.

Identification of complex networks from limited and noise contaminated data is an important yet challenging task, which has attracted researchers from different disciplines recently. In this paper, the underlying feature of a complex network identification problem was analyzed and translated into a sparse linear programming problem. Then, a general framework based on the Bayesian model with independent Laplace prior was proposed to guarantee the sparseness and accuracy of identification results after analyzing influences of different prior distributions. At the same time, a three-stage hierarchical method was designed to resolve the puzzle that the Laplace distribution is not conjugated to the normal distribution. Last, the variational Bayesian was introduced to improve the efficiency of the network reconstruction task. The high accuracy and robust properties of the proposed method were verified by conducting both general synthetic network and real network identification tasks based on the evolutionary game dynamic. Compared with other five classical algorithms, the numerical experiments indicate that the proposed model can outperform these methods in both accuracy and robustness.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1063/5.0031134DOI Listing
January 2021

Novel Potent Selective Orally Active S1P5 Receptor Antagonists.

ACS Med Chem Lett 2021 Mar 15;12(3):351-355. Epub 2021 Jan 15.

Université Lyon 1, Lyon 69007, France.

S1P5 is one of the five sphingosine-1-phosphate (S1P) receptors which play important roles in immune and CNS cell homeostasis, growth, and differentiation. Little is known about the effect of modulation of S1P5 due to the lack of S1P5 specific modulators with suitable druglike properties. Here we describe the discovery and optimization of a novel series of potent selective S1P5 antagonists and the identification of an orally active brain-penetrant tool compound .
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/acsmedchemlett.0c00631DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7957944PMC
March 2021

Graph Convolutional Network-Based Method for Fault Diagnosis Using a Hybrid of Measurement and Prior Knowledge.

IEEE Trans Cybern 2021 Mar 12;PP. Epub 2021 Mar 12.

Deep-neural network-based fault diagnosis methods have been widely used according to the state of the art. However, a few of them consider the prior knowledge of the system of interest, which is beneficial for fault diagnosis. To this end, a new fault diagnosis method based on the graph convolutional network (GCN) using a hybrid of the available measurement and the prior knowledge is proposed. Specifically, this method first uses the structural analysis (SA) method to prediagnose the fault and then converts the prediagnosis results into the association graph. Then, the graph and measurements are sent into the GCN model, in which a weight coefficient is introduced to adjust the influence of measurements and the prior knowledge. In this method, the graph structure of GCN is used as a joint point to connect SA based on the model and GCN based on data. In order to verify the effectiveness of the proposed method, an experiment is carried out. The results show that the proposed method, which combines the advantages of both SA and GCN, has better diagnosis results than the existing methods based on common evaluation indicators.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1109/TCYB.2021.3059002DOI Listing
March 2021

Characteristics of planktonic and sediment bacterial communities in a heavily polluted urban river.

PeerJ 2021 24;9:e10866. Epub 2021 Feb 24.

Chongqing Academy of Ecology and Environmental Sciences, Chongqing, China.

Urban rivers represent a unique ecosystem in which pollution occurs regularly, altering the biogeochemical characteristics of waterbodies and sediments. However, little is presently known about the spatiotemporal patterns of planktonic and sediment bacterial community diversities and compositions in urban rivers. Herein, Illumina MiSeq high-throughput sequencing was performed to reveal the spatiotemporal dynamics of bacterial populations in Liangtan River, a heavily polluted urban river in Chongqing City (China). The results showed the richness and diversity of sediment bacteria were significantly higher than those of planktonic bacteria, whereas a strong overlap (46.7%) in OTUs was identified between water and sediment samples. Bacterial community composition remarkably differed in waters and sediments. Planktonic bacterial communities were dominated by , and , while sediment bacterial communities mainly included and . Additionally, several taxonomic groups of potential bacterial pathogens showed an increasing trend in water and sediment samples from residential and industrial areas (RI). Variation partition analysis (VPA) indicated that temperature and nutrient were identified as the main drivers determining the planktonic and sediment bacterial assemblages. These results highlight that bacterial communities in the polluted urban river exhibit spatiotemporal variation due to the combined influence of environmental factors associated with sewage discharge and hydropower dams.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.7717/peerj.10866DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7912603PMC
February 2021

Combination of oncolytic adenovirus targeting SATB1 and docetaxel for the treatment of castration-resistant prostate cancer.

J Cancer 2021 25;12(6):1846-1852. Epub 2021 Jan 25.

Jiangsu Key Laboratory of Biological Cancer Therapy, Xuzhou Medical College, Xuzhou 221002, China.

Oncolytic viral therapy is a new strategy for tumor eradication which combines the advantages of viral therapy and gene therapy. Silencing SATB1 exhibits strong inhibitory effect on the growth of prostate cancer. Docetaxel (DTX) is the gold standard for chemotherapy of prostate cancer, but its side effects decrease the life quality of patients. Therefore, it is urgent to develop combination therapy to increase its anti-tumor effect. Oncolytic adenovirus targeting SATB1 was constructed and named ZD55-SATB1. Human prostatic cancer cells DU145 and PC-3 and human prostatic stromal cells WPMY-1 were treated with ZD55-SATB1 or/and DTX. cell proliferation, migration, invasion, apoptosis were detected. In addition, PC-3 cells were injected subcutaneously into nude mice, which were treated with ZD55-SATB1 or/and DTX. Tumor growth was monitored . ZD55-SATB1 combined with DTX inhibited proliferation, migration and invasion of DU145 and PC-3 cells, while promoted apoptosis of DU145 and PC-3 cells more efficiently than monotherapy. ZD55-SATB1 had no cytotoxicity on WPMY-1 cells. In animal models, the combined treatment of ZD55-SATB1+DTX and endocrine therapy effectively inhibited the growth of xenograft tumor, accompanied by increased expression of caspase-3 and caspase-8, and decrease expression of Bcl-2 and angiogenesis marker CD31 compared to other treatment groups. The combination of oncolytic adenovirus ZD55-SATB1 and chemotherapy provides a novel approach to effective therapy of prostate cancer.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.7150/jca.46868DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890306PMC
January 2021

Adaptive process monitoring via online dictionary learning and its industrial application.

ISA Trans 2021 Aug 29;114:399-412. Epub 2020 Dec 29.

School of Automation, Central South University, Changsha 410083, China.

For industrial processes, one common drawback of conventional process monitoring methods is that they would make an increasing number of false alarms in cases of various factors such as catalyst deactivation, seasonal fluctuation and so forth. To address this issue, the present work proposes an online dictionary learning method, which can fulfill the process monitoring and fault diagnosis task adaptively. The proposed method would incorporate currently available information to update the dictionary and control limit, instead of keeping a fixed monitoring model. The online dictionary learning method are more superior than conventional methods. Firstly, compared with some traditional offline methods based on small amounts of historical data, the proposed method can augment train data with online dictionary updating, thus it copes with time-varying processes well. Secondly, the proposed method enjoys a lower computational complexity than the offline learning method with mass data, which is appealing in the era of industrial big data. Thirdly, the proposed method performs more reliably than the existing recursive principal component analysis-based methods because it can resolve the anomaly of principal component or non-orthogonality of eigenvectors problem which was often confronted in the recursive principal component analysis-based methods. Finally, some experiments were designed and carried out to demonstrate the advantage of the online dictionary learning.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.isatra.2020.12.046DOI Listing
August 2021

Reconstruction of Tree Network via Evolutionary Game Data Analysis.

IEEE Trans Cybern 2021 Feb 4;PP. Epub 2021 Feb 4.

As one of the most effective technologies for network reconstruction, compressive sensing can recover signals from a small amount of observed data through sparse search or greedy algorithms in the assumption that the unknown signal is sufficiently sparse on a specific basis. However, there often occurs loss of precision even failure in the process of reconstruction without enough prior information. Therefore, the purpose of this article is to solve the problem of low reconstruction accuracy by mining implicit structural information in the network. Specifically, we propose a novel and efficient algorithm (MCM_TRA) for reconstructing the structure of the K-forked tree network. Based on evolutionary game dynamics, the modified clustering method (MCM) classifies all nodes into two sets, then a two-stage reconstruction algorithm (TRA) is illustrated to recover the node signals in different sets. The experimental results demonstrate that the MCM_TRA enhances the reconstruction accuracy prominently than previous algorithms. Moreover, extensive sensitivity analysis shows that the reconstruction effect can be promoted for a broad range of parameters, which further indicates the superiority of the proposed method.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1109/TCYB.2020.3043227DOI Listing
February 2021

Efficacy based ginger fingerprinting reveals potential antiproliferative analytes for triple negative breast cancer.

Sci Rep 2020 11 5;10(1):19182. Epub 2020 Nov 5.

Department of Biology, Georgia State University, Atlanta, GA, 30303, USA.

Ginger (Zingiber officinale) is one of the most widely consumed dietary supplements worldwide. Its anticancer potential has been demonstrated in various studies. However, ginger roots obtained from different geographical locations showed extensive variability in their activities, mainly due to differences in the levels of bioactive compounds. Here we evaluated the effect of these differences on the anticancer activity of ginger by performing efficacy-based fingerprinting. We characterized the fingerprint profiles of 22 ginger samples using liquid chromatography-mass spectroscopy, followed by a principal component analysis (PCA) and pearson correlation analysis. We also evaluated the anti-proliferative effects (IC) of these samples on triple-negative breast cancer cells using the MTT assays. The supervised PCA identified a subset of analytes whose abundance strongly associated with the IC values of the ginger extracts, providing a link between ginger extract composition and in vitro anticancer efficacy. This study demonstrated that variation in the ginger fingerprint profiles resulting from differences in their chemical composition could have a significant impact on efficacy and bioactivity of ginger extracts. Also, this first-of-a-kind efficacy-based fingerprinting approach proposed here can identify potent anticancer candidates from the ginger fingerprint without the need for isolating individual components from the extracts.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-020-75707-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644756PMC
November 2020

In Vitro and In Vivo Models for Evaluating the Oral Toxicity of Nanomedicines.

Nanomaterials (Basel) 2020 Oct 31;10(11). Epub 2020 Oct 31.

Center for Diagnostics and Therapeutics, Digestive Disease Research Group, Institute for Biomedical Sciences, Petite Science Center, Suite 754, 100 Piedmont Ave SE, Georgia State University, Atlanta, GA 30303, USA.

Toxicity studies for conventional oral drug formulations are standardized and well documented, as required by the guidelines of administrative agencies such as the US Food & Drug Administration (FDA), the European Medicines Agency (EMA) or European Medicines Evaluation Agency (EMEA), and the Japanese Pharmaceuticals and Medical Devices Agency (PMDA). Researchers tend to extrapolate these standardized protocols to evaluate nanoformulations (NFs) because standard nanotoxicity protocols are still lacking in nonclinical studies for testing orally delivered NFs. However, such strategies have generated many inconsistent results because they do not account for the specific physicochemical properties of nanomedicines. Due to their tiny size, accumulated surface charge and tension, sizeable surface-area-to-volume ratio, and high chemical/structural complexity, orally delivered NFs may generate severe topical toxicities to the gastrointestinal tract and metabolic organs, including the liver and kidney. Such toxicities involve immune responses that reflect different mechanisms than those triggered by conventional formulations. Herein, we briefly analyze the potential oral toxicity mechanisms of NFs and describe recently reported in vitro and in vivo models that attempt to address the specific oral toxicity of nanomedicines. We also discuss approaches that may be used to develop nontoxic NFs for oral drug delivery.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/nano10112177DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7694082PMC
October 2020

The utility of MEWS for predicting the mortality in the elderly adults with COVID-19: a retrospective cohort study with comparison to other predictive clinical scores.

PeerJ 2020 28;8:e10018. Epub 2020 Sep 28.

Department of Critical Care Medicine, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China.

Background: Older adults have been reported to be a population with high-risk of death in the COVID-19 outbreak. Rapid detection of high-risk patients is crucial to reduce mortality in this population. The aim of this study was to evaluate the prognositc accuracy of the Modified Early Warning Score (MEWS) for in-hospital mortality in older adults with COVID-19.

Methods: A retrospective cohort study was conducted in Wuhan Hankou Hospital in China from 1 January 2020 to 29 February 2020. Receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of MEWS, Acute Physiology and Chronic Health Evaluation II (APACHE II), Sequential Organ Function Assessment (SOFA), quick Sequential Organ Function Assessment (qSOFA), Pneumonia Severity Index (PSI), Combination of Confusion, Urea, Respiratory Rate, Blood Pressure, and Age ≥65 (CURB-65), and the Systemic Inflammatory Response Syndrome Criteria (SIRS) for in-hospital mortality. Logistic regression models were performed to detect the high-risk older adults with COVID-19.

Results: Among the 235 patients included in this study, 37 (15.74%) died and 131 (55.74%) were male, with an average age of 70.61 years (SD 8.02). ROC analysis suggested that the capacity of MEWS in predicting in-hospital mortality was as good as the APACHE II, SOFA, PSI and qSOFA (Difference in AUROC: MEWS vs. APACHE II, -0.025 (95% CI [-0.075 to 0.026]); MEWS vs. SOFA, -0.013 (95% CI [-0.049 to 0.024]); MEWS vs. PSI, -0.015 (95% CI [-0.065 to 0.035]); MEWS vs. qSOFA, 0.024 (95% CI [-0.029 to 0.076]), all > 0.05), but was significantly higher than SIRS and CURB-65 (Difference in AUROC: MEWS vs. SIRS, 0.218 (95% CI [0.156-0.279]); MEWS vs. CURB-65, 0.064 (95% CI [0.002-0.125]), all < 0.05). Logistic regression models implied that the male patients (≥75 years) had higher risk of death than the other older adults (estimated coefficients: 1.16, = 0.044). Our analysis further suggests that the cut-off points of the MEWS score for the male patients (≥75 years) subpopulation and the other elderly patients should be 2.5 and 3.5, respectively.

Conclusions: MEWS is an efficient tool for rapid assessment of elderly COVID-19 patients. MEWS has promising performance in predicting in-hospital mortality and identifying the high-risk group in elderly patients with COVID-19.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.7717/peerj.10018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528814PMC
September 2020

Highly Biocompatible Functionalized Layer-by-Layer Ginger Lipid Nano Vectors Targeting P-selectin for Delivery of Doxorubicin to Treat Colon Cancer.

Adv Ther (Weinh) 2019 Dec 18;2(12). Epub 2019 Sep 18.

Institute for Biomedical Sciences, Center for Diagnostics and Therapeutics, Digestive Disease Research Group, Georgia State University, Atlanta, Georgia, 30302, United States.

A biocompatible natural nanoparticle drug delivery system that has specific cancer-targeting function holds vast promise for cancer therapy. Here, a fucoidan/poly-lysine-functionalized layer-by-layer ginger-derived lipid vector (LbL-GDLV) was designed to target P-selectin (overexpressed by endothelial cells) and deliver a loaded drug into vascularized colon cancer. , LbL-GDLVs selectively bound to P-selectin, and the degradation of the fucoidan outer layer in a milieu similar to the cancer microenvironment resulted in rapid attachment of the cancer cell and internalization of the remaining positively charged poly-lysine coated-GDLVs. Upon enzymolysis of the poly-lysine layer inside the cancer cell, the GDLV core released loaded doxorubicin (Dox) which had the expected effects. bio-distribution studies showed that intravenously injected LbL-GDLVs exhibited enhanced accumulation at the vascularized tumor site (~ 4.4-fold higher than control vesicles), presumably due to P-selectin-mediated targeting plus the enhanced permeability and retention effect (EPR). In two animal models used to screen anti-cancer efficacy (Luc-HT-29 and HCT-116 xenografts), Dox-loaded LbL-GDLVs (LbL-GDLVs/Dox) significantly inhibited tumor growth and demonstrated much better therapeutic efficiency than free Dox. More importantly, LbL-GDLVs/Dox exhibited excellent biocompatibility, and LbL-GDLVs encapsulation largely reduced the cardiotoxicity of free Dox and avoided the notorious drug resistance of colon cells against free Dox. Together, these findings demonstrate the potential of our newly designed and highly biocompatible plant-derived LbL nanoparticles and their precise colon cancer drug delivery function.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/adtp.201900129DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7546358PMC
December 2019

Assessment of the Learning Curve of Supercapsular Percutaneously Assisted Total Hip Arthroplasty in an Asian Population.

Biomed Res Int 2020 7;2020:5180458. Epub 2020 Sep 7.

Department of Orthopedics, The First Hospital of Changsha, Changsha, 410005 Hunan, China.

The supercapsular percutaneously assisted total hip (SuperPATH) approach is a microinvasive approach that was developed to minimize surgical disruption of soft tissue during routine total hip arthroplasty (THA). This study was aimed at assessing early outcomes and learning curves of the SuperPATH approach in one Chinese hospital's experience. Early outcomes of the first consecutive 78 SuperPATH cases (80 hips) performed by the same surgeon were evaluated. The patients were divided into 4 groups according to the surgical order. The incision, intraoperative blood loss, hospital stay, Harris hip score, and complication occurrence in each group were evaluated. Learning curves were assessed using operative time and intraoperative blood loss as surrogates. The operation time and intraoperative blood loss of groups A and B were more than those of groups C and D, and the difference was statistically significant ( < 0.05); however, there was no statistically significant difference between the two groups (group A vs. group B, = 0.426; group A vs. group B, = 0.426). There was no statistically significant difference in terms of incision length and hospital stay, and Harris hip score at the last follow-up was increased with statistically significant difference when compared with that preoperatively among the 4 groups. One case of periprosthetic fracture occurred in group A. No other complication, such as joint dislocation, sciatic nerve injury, prosthesis loosening, periprosthetic infection, and deep vein thromboembolism, occurred in the 4 groups. In summary, for surgeons who are familiar with the standard posterolateral approach, they could achieve more familiarity with SuperPATH after 40 cases of surgery.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1155/2020/5180458DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7492896PMC
April 2021

System biology analysis reveals the role of voltage-dependent anion channel in mitochondrial dysfunction during non-alcoholic fatty liver disease progression into hepatocellular carcinoma.

Cancer Sci 2020 Nov 6;111(11):4288-4302. Epub 2020 Oct 6.

Binzhou Medical University, Yantai, China.

Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of hepatocellular carcinoma (HCC), but the underlying mechanisms behind the correlation of NAFLD with HCC are unclear. We aimed to uncover the genes and potential mechanisms that drive this progression. This study uncovered the genes and potential mechanisms through a multiple 'omics integration approach. Quantitative proteomics combined with phenotype-association analysis was performed. To investigate the potential mechanisms, a comprehensive transcriptome/lipidome/phenome-wide association analysis was performed in genetic reference panel BXD mice strains. The quantitative proteomics combined with phenotype-association results showed that VDAC1 was significantly increased in tumor tissues and correlated with NAFLD-related traits. Gene co-expression network analysis indicated that VDAC1 is involved in mitochondria dysfunction in the tumorigenic/tumor progression. The association between VDAC1 and mitochondria dysfunction can be explained by the fact that VDAC1 was associated with mitochondria membrane lipids cardiolipin (CL) composition shift. VDAC1 was correlated with the suppression of mature specie CL(LLLL) and elevation level of nascent CL species. Such profiling shift was supported by the significant positive correlation between VDAC1 and PTPMT1, as well as negative correlation with CL remodeling enzyme Tafazzin (TAZ). This study confirmed that the expression of VADC1 was dysregulated in NAFLD-driven HCC and associated with NAFLD progression. The VDAC1-driven mitochondria dysfunction is associated with cardiolipin composition shift, which causes alteration of mitochondria membrane properties.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1111/cas.14651DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7648023PMC
November 2020

Simultaneous Determination of Metal Ions in Zinc Sulfate Solution Using UV-Vis Spectrometry and SPSE-XGBoost Method.

Sensors (Basel) 2020 Aug 31;20(17). Epub 2020 Aug 31.

School of Automation, Central South University, Changsha 410083, China.

Excessive discharge of heavy metal ions will aggravate environment pollution and threaten human health. Thus, it is of significance to real-time detect metal ions and control discharge in the metallurgical wastewater. We developed an accurate and rapid approach based on the singular perturbation spectrum estimator and extreme gradient boosting (SPSE-XGBoost) algorithms to simultaneously determine multi-metal ion concentrations by UV-vis spectrometry. In the approach, the spectral data is expanded by multi-order derivative preprocessing, and then, the sensitive feature bands in each spectrum are extracted by feature importance (VI score) ranking. Subsequently, the SPSE-XGBoost model are trained to combine multi-derivative features and to predict ion concentrations. The experimental results indicate that the developed "Expand-Extract-Combine" strategy can not only overcome problems of background noise and spectral overlapping but also mine the deeper spectrum information by integrating important features. Moreover, the SPSE-XGBoost strategy utilizes the selected feature subset instead of the full-spectrum for calculation, which effectively improves the computing speed. The comparisons of different data processing methods are conducted. It outcomes that the proposed strategy outperforms other routine methods and can profoundly determine the concentrations of zinc, copper, cobalt, and nickel with the lowest RMSEP. Therefore, our developed approach can be implemented as a promising mean for real-time and on-line determination of multi-metal ion concentrations in zinc hydrometallurgy.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/s20174936DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506957PMC
August 2020

CircRSF1 contributes to endothelial cell growth, migration and tube formation under ox-LDL stress through regulating miR-758/CCND2 axis.

Life Sci 2020 Oct 10;259:118241. Epub 2020 Aug 10.

Department of Cardiovascular Medicine, Zhoukou Central Hospital, Zhoukou, Henan, China.

Aims: Compelling evidences demonstrate that informative RNAs play essential role in therapy of atherosclerosis. Here, we attempted to study the role of hsa_circ_0000345 (circRSF1) in endothelial cell damage through competing endogenous RNA pathway.

Materials And Methods: Expression of circRSF1, miRNA-758-3p (miR-758) and cyclin D2 (CCND2) was detected using RT-qPCR and western blotting, and the cross-talk among them was identified using dual-luciferase reporter assay and RNA immunoprecipitation. The low-density lipoprotein cholesterol (LDL-C) level was measured with enzyme-linked immunosorbent assay. Cell growth was measured by MTS assay, flow cytometry and caspase-3 activity assay kit. Migration and tube formation were determined by scratch migration assay and tube formation assay, respectively.

Key Findings: CircRSF1 and CCND2 were downregulated, whereas miR-758 was upregulated in serum of patients with atherosclerosis and oxidized low-density lipoprotein (ox-LDL)-treated human aortic endothelial cells (HAECs). Moreover, levels of circRSF1, miR-758 and CCND2 were correlated with circulating LDL-C level. Restoring circRSF1 and silencing miR-758 could improve cell viability, tube formation and migration of HAECs under ox-LDL treatment, as well as attenuated apoptotic rate and caspase-3 activity. However, miR-758 upregulation counteracted the promotion of circRSF1 on cell growth, migration and tube formation in ox-LDL-induced HAECs; so did CCND2 deletion on effect of miR-758 silence. Notably, circRSF1 and CCND2 could competitively bound to miR-758, and circRSF1 positively regulated CCND2 expression via miR-758.

Significance: CircRSF1 could protect against ox-LDL-induced endothelial cell injury in vitro via miR-758/CCND2 axis, suggesting circRSF1 as a potential target for the treatment of atherosclerosis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.lfs.2020.118241DOI Listing
October 2020

Preparation and Characterization of Ginger Lipid-derived Nanoparticles for Colon-targeted siRNA Delivery.

Bio Protoc 2020 Jul;10(14)

Institute for Biomedical Science, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA, USA.

Synthetic nanoparticle-based drug delivery system is widely known for its ability to increase the efficacy and specificity of loaded drugs, but it often suffers from relatively higher immunotoxicity and higher costs as compared to traditional drug formulations. Contrarily, plant-derived nanoparticles appear to be free from these limitations of synthetic nanoparticles; they are naturally occurring biocompatible vesicles that do not generate immunotoxicity and are easy to obtain. Additionally, lipids isolated from plant-derived nanoparticles have shown the capability of assembling themselves to spherical nano-sized liposomal particles. Herein, we employ lipids extracted from ginger-derived nanoparticles and load them with therapeutic siRNA (CD98-siRNA) to create CD98-siRNA/ginger-lipid nanoparticles. Characterization of the CD98-siRNA/ginger-lipid nanoparticles showed that they present a spherical shape, with a diameter of around 189.5 nm. The surface zeta potential of the nanoparticles varies from -18.1 to -18.4 mV. Furthermore, in recent research, the CD98-siRNA/ginger-lipid nanoparticles have shown specific colon targeting capability and excellent anti-inflammatory efficacy in a Dextran Sodium Sulfate (DSS) induced mouse model of colitis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.21769/bioprotoc.3685DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7416531PMC
July 2020

Lipid-Based Drug Delivery Nanoplatforms for Colorectal Cancer Therapy.

Nanomaterials (Basel) 2020 Jul 21;10(7). Epub 2020 Jul 21.

Institute for Biomedical Sciences, Center for Diagnostics and Therapeutics, Digestive Disease Research Group, Georgia State University, Atlanta, GA 30302, USA.

Colorectal cancer (CRC) is a prevalent disease worldwide, and patients at late stages of CRC often suffer from a high mortality rate after surgery. Adjuvant chemotherapeutics (ACs) have been extensively developed to improve the survival rate of such patients, but conventionally formulated ACs inevitably distribute toxic chemotherapeutic drugs to healthy organs and thus often trigger severe side effects. CRC cells may also develop drug resistance following repeat dosing of conventional ACs, limiting their effectiveness. Given these limitations, researchers have sought to use targeted drug delivery systems (DDSs), specifically the nanotechnology-based DDSs, to deliver the ACs. As lipid-based nanoplatforms have shown the potential to improve the efficacy and safety of various cytotoxic drugs (such as paclitaxel and vincristine) in the clinical treatment of gastric cancer and leukemia, the preclinical progress of lipid-based nanoplatforms has attracted increasing interest. The lipid-based nanoplatforms might be the most promising DDSs to succeed in entering a clinical trial for CRC treatment. This review will briefly examine the history of preclinical research on lipid-based nanoplatforms, summarize the current progress, and discuss the challenges and prospects of using such approaches in the treatment of CRC.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/nano10071424DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7408503PMC
July 2020

Impact of PepT1 deletion on microbiota composition and colitis requires multiple generations.

NPJ Biofilms Microbiomes 2020 07 21;6(1):27. Epub 2020 Jul 21.

Institute for Biomedical Sciences, Center for Inflammation, Immunity and Infection, Digestive Disease Research Group, Georgia State University, Atlanta, GA, USA.

Numerous studies of knockout mice find impacts on microbiota composition that influence host phenotype. However, such differences can vanish when KO mice are compared directly to WT littermates, suggesting these differences do not reflect the genetic deletion per se but microbiota composition drifting over generations. Hence, our hypothesis that absence of di/tri-peptide transporter PepT1 altered microbiota composition resulting in resistance to colitis compelled scrutiny. In this study, we used PepT1 and WT founder mice bred separately for multiple generations. Such mice were then bred to each other to generate F1 PepT1 and WT littermates, which were then bred within their genotype to generate F2, F3, and F4, offspring. Here we report that founder PepT1 mice were, relative to their WT counterparts, resistant to DSS colitis. Such resistance was associated with alterations in gut microbiota, which, when transplanted to germfree mice, was sufficient to transfer resistance to colitis. Such differences were not observed when comparing F1 PepT1 to F1 WT littermates but rather, returned gradually over subsequent generations such that, relative to their F4 WT controls, F4 PepT1 displayed microbiota composition and colitis-resistant phenotype nearly identical to the founder PepT1 mice. Our findings indicate a role for PepT1 in influencing microbiota composition and, consequently, proneness to colitis and cancer. Overall, our study indicates that littermate-controlled experiments can be insufficient for assessing microbiota-dependent phenotypes and prevent a full comprehension of genotype-driven phenomena. Rather, impact of a single genetic alteration on microbiota and host phenotype may take generations to manifest.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41522-020-0137-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374158PMC
July 2020

Highly sensitive detection of Pb and Cu based on ZIF-67/MWCNT/Nafion-modified glassy carbon electrode.

Anal Chim Acta 2020 Aug 14;1124:166-175. Epub 2020 May 14.

State Key Laboratory on Integrated Optoelectronics, Key Laboratory of Gas Sensors, Jilin Province, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun, 130012, China. Electronic address:

A series of different facile modification layers (MLs) was designed to gradually increase the electrochemical sensing performance of glassy carbon electrode (GCE) for simultaneously detecting Pb and Cu. ML designs were mainly a different combination of ZIF-67, MWCNT and Nafion, and their different electrochemical sensing performances were investigated by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), square wave stripping voltammetry (SWSV) and chronocoulometry. The fabricated sensor, which modified with ZIF-67/MWCNT and Nafion layer, exhibited the biggest response peak current to Pb and Cu. In addition, it displayed a wide linear detection range of 1.38 nM-5 μM for Pb and 1.26 nM-5 μM for Cu, a detection accuracy of about 1 nM for both Pb and Cu, and an excellent stability for both Pb and Cu. We also analyzed the real water sample taken from Changchun's Sanjia Lake and Yan Lake. We believe this ML design provides instruction for building high-performance electrochemical sensing systems.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.aca.2020.05.023DOI Listing
August 2020
-->