Publications by authors named "Kuo Yang"

119 Publications

Eliminating nonspecific binding sites for highly reliable immunoassay via super-resolution multicolor fluorescence colocalization.

Nanoscale 2021 Apr 29;13(13):6624-6634. Epub 2021 Mar 29.

Advanced Photonics Center, Southeast University, Nanjing 210096, China.

Non-specific adsorption in immunoassays has always been a major problem that affects the reliability of assay results. Despite the emergence of various methods that can reduce nonspecific adsorption, a universal and effective method to reduce the influence of nonspecific adsorption is still lacking. Hence, we propose here an optical super-resolution imaging based immunoassay strategy, named super-resolution multicolor fluorescence colocalization (SR-MFC), which can generate a low false-positive rate. Taking advantages of the high spatial resolution of single-molecule localization microscopy (SMLM), SR-MFC can directly visualize the assay results and thus effectively exclude the nonspecific binding sites. In other words, even if nonspecific interactions do happen, SR-MFC ensures that the nonspecific reaction sites are visualized and abandoned, which has never been achieved before. To verify its practicability, exosomes, which are important cancer biomarkers, were used as model targets and detected using SR-MFC. Compared with common immunofluorescence assay, the accuracy and reliability of the detection results are greatly improved. The detection limit of exosomes was 38 particles per μL. More importantly, the SR-MFC method can also be generalized for the detection of other biomarkers (e.g. proteins, DNAs, etc.), which is a significant and promising new strategy for immunoassay based diagnosis.
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http://dx.doi.org/10.1039/d0nr08103eDOI Listing
April 2021

The regulatory module MdBT2-MdMYB88/MdMYB124-MdNRTs regulates nitrogen usage in apple.

Plant Physiol 2021 Apr;185(4):1924-1942

State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, Shaanxi 712100, China.

Less than 40% of the nitrogen (N) fertilizer applied to soil is absorbed by crops. Thus, improving the N use efficiency of crops is critical for agricultural development. However, the underlying regulation of these processes remains largely unknown, particularly in woody plants. By conducting yeast two-hybrid assays, we identified one interacting protein of MdMYB88 and MdMYB124 in apple (Malus × domestica), namely BTB and TAZ domain protein 2 (MdBT2). Ubiquitination and protein stabilization analysis revealed that MdBT2 ubiquitinates and degrades MdMYB88 and MdMYB124 via the 26S proteasome pathway. MdBT2 negatively regulates nitrogen usage as revealed by the reduced fresh weight, dry weight, N concentration, and N usage index of MdBT2 overexpression calli under low-N conditions. In contrast, MdMYB88 and MdMYB124 increase nitrate absorption, allocation, and remobilization by regulating expression of MdNRT2.4, MdNRT1.8, MdNRT1.7, and MdNRT1.5 under N limitation, thereby regulating N usage. The results obtained illustrate the mechanism of a regulatory module comprising MdBT2-MdMYB88/MdMYB124-MdNRTs, through which plants modulate N usage. These data contribute to a molecular approach to improve the N usage of fruit crops under limited N acquisition.
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http://dx.doi.org/10.1093/plphys/kiaa118DOI Listing
April 2021

Add-On Chinese Medicine for Coronavirus Disease 2019 (ACCORD): A Retrospective Cohort Study of Hospital Registries.

Am J Chin Med 2021 5;49(3):543-575. Epub 2021 Mar 5.

Hepatic Disease Institute, Hubei Key Laboratory of Theoretical and Applied, Research of Liver and Kidney in Traditional Chinese Medicine, Hubei Provincial Hospital of Traditional Chinese Medicine, Wuhan 430061, P. R. China.

Chinese medicine (CM) was extensively used to treat COVID-19 in China. We aimed to evaluate the real-world effectiveness of add-on semi-individualized CM during the outbreak. A retrospective cohort of 1788 adult confirmed COVID-19 patients were recruited from 2235 consecutive linked records retrieved from five hospitals in Wuhan during 15 January to 13 March 2020. The mortality of add-on semi-individualized CM users and non-users was compared by inverse probability weighted hazard ratio (HR) and by propensity score matching. Change of biomarkers was compared between groups, and the frequency of CMs used was analyzed. Subgroup analysis was performed to stratify disease severity and dose of CM exposure. The crude mortality was 3.8% in the semi-individualized CM user group and 17.0% among the non-users. Add-on CM was associated with a mortality reduction of 58% (HR = 0.42, 95% CI: 0.23 to 0.77, [Formula: see text] = 0.005) among all COVID-19 cases and 66% (HR = 0.34, 95% CI: 0.15 to 0.76, [Formula: see text] = 0.009) among severe/critical COVID-19 cases demonstrating dose-dependent response, after inversely weighted with propensity score. The result was robust in various stratified, weighted, matched, adjusted and sensitivity analyses. Severe/critical patients that received add-on CM had a trend of stabilized D-dimer level after 3-7 days of admission when compared to baseline. Immunomodulating and anti-asthmatic CMs were most used. Add-on semi-individualized CM was associated with significantly reduced mortality, especially among severe/critical cases. Chinese medicine could be considered as an add-on regimen for trial use.
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http://dx.doi.org/10.1142/S0192415X21500257DOI Listing
April 2021

Quantitative proteomics identifies FOLR1 to drive sorafenib resistance via activating autophagy in hepatocellular carcinoma cells.

Carcinogenesis 2021 Mar 3. Epub 2021 Mar 3.

Zhang Dayu School of Chemistry, Dalian University of Technology, Dalian, China.

Sorafenib is commonly used to treat advanced human hepatocellular carcinoma (HCC). However, clinical efficacy has been limited by drug resistance. In this study, we used label-free quantitative proteomic analysis to systematically investigate the underlying mechanisms of sorafenib resistance in HCC cells. A total of 1709 proteins were confidently quantified. Among them, 89 were differentially expressed, and highly enriched in the processes of cell-cell adhesion, negative regulation of apoptosis, response to drug and metabolic processes involving in sorafenib resistance. Notably, folate receptor α (FOLR1) was found to be significantly upregulated in resistant HCC cells. In addition, in-vitro studies showed that overexpression of FOLR1 decreased the sensitivity of HCC cells to sorafenib, whereas siRNA-directed knockdown of FOLR1 increased the sensitivity of HCC cells to sorafenib. Immunoprecipitation-mass spectrometry analysis suggested a strong link between FOLR1 and autophagy related proteins. Further biological experiments found that FOLR1-related sorafenib resistance was accompanied by the activation of autophagy, whereas inhibition of autophagy significantly reduced FOLR1-induced cell resistance. These results suggest the driving role of FOLR1 in HCC resistance to sorafenib, which may be exerted through FOLR1-induced autophagy. Therefore, this study may provide new insights into understanding the mechanism of sorafenib resistance.
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http://dx.doi.org/10.1093/carcin/bgab019DOI Listing
March 2021

Ultra-sensitive surface enhanced Raman spectroscopy sensor for in-situ monitoring of dopamine release using zipper-like ortho-nanodimers.

Biosens Bioelectron 2021 May 18;180:113100. Epub 2021 Feb 18.

Advanced Photonics Center, School of Electronic Science and Engineering, Southeast University, Nanjing, 210096, Jiangsu, China.

Accurate quantitative detection of dopamine (DA) in blood is essential for the early diagnosis and the pathogenesis analysis of dopaminergic dysfunction, which still remains a great challenge because of the extremely low concentration in patients. Using our previously reported DNA-assisted synthesis of ortho-nanodimers (DaSON) strategy, a microfluidic surface enhanced Raman spectroscopy (SERS) biosensor for the ultrasensitive and reliable detection of DA in serum was demonstrated by modifying SERS probes with DA aptamers in a specific orientation to form zipper-like ortho-nanodimers. The uniform 1-nm gap in zipper-like ortho-nanodimers endows the SERS sensor with ultrahigh sensitivity and high accuracy for the detection of DA. The limit of detection is as low as 10 aM in phosphate buffer saline and 10 fM in serum, which is about two orders of magnitude lower than that of previous methods. Using a single microfluidic chip containing a 3D cell culture unit, quantitatively in-situ monitoring of extracellular DA released from living neurons under different medications was first realized. Quantification of DA in human blood samples was also achieved with the recoveries ranging from 87.5% to 123.7%. Given the difficulty of DA quantification in complex physiological samples, our developed SERS sensor provides an appealing tool for in-vitro investigating of neurological processes and clinical examination of dopaminergic disorders.
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http://dx.doi.org/10.1016/j.bios.2021.113100DOI Listing
May 2021

Pentadecanoic acid promotes basal and insulin-stimulated glucose uptake in C2C12 myotubes.

Food Nutr Res 2021 22;65. Epub 2021 Jan 22.

School of Life Sciences, East China Normal University, Shanghai, China.

Background: Saturated fatty acids (SFAs) generally have been thought to worsen insulin-resistance and increase the risk of developing type 2 diabetes mellitus (T2DM). Recently, accumulating evidence has revealed that SFAs are not a single homogeneous group, instead different SFAs are associated with T2DM in opposing directions. Pentadecanoic acid (C15:0, PA) is directly correlated with dairy products, and a negative association between circulating PA and metabolic disease risk was observed in epidemiological studies. Therefore, the role of PA in human health needs to be reinforced. Whether PA has a direct benefit on glucose metabolism and insulin sensitivity needs further investigation.

Objective: The present study aimed to investigate the effect and potential mechanism of action of PA on basal and insulin stimulated glucose uptake in C2C12 myotubes.

Methods: Glucose uptake was determined using a 2-(N-[7-nitrobenz-2-oxa-1,3-diazol-4-yl] amino)-2-deoxyglucose (2-NBDG) uptake assay. Cell membrane proteins were isolated and glucose transporter 4 (GLUT4) protein was detected by western blotting to examine the translocation of GLUT4 to the plasma membrane. The phosphorylation levels of proteins involved in the insulin and 5'-adenosine monophosphate-activated protein kinase (AMPK) pathways were examined by western blotting.

Results: We found that PA significantly promoted glucose uptake and GLUT4 translocation to the plasma membrane. PA had no effect on the insulin-dependent pathway involving insulin receptor substrate 1 (Tyr632) and protein kinase B (PKB/Akt), but increased phosphorylation of AMPK and Akt substrate of 160 kDa (AS160). Compound C (an AMPK inhibitor) blocked PA-induced AMPK activation and reversed PA-induced GLUT4 translocation, indicating that PA promotes glucose uptake via the AMPK pathway . Moreover, PA significantly promoted insulin-stimulated glucose uptake in myotubes. Under insulin stimulation, PA did not affect the insulin-dependent pathway, but still activated AMPK.

Conclusion: PA, an odd-chain SFA, significantly stimulates glucose uptake via the AMPK-AS160 pathway and exhibits an insulin-sensitizing effect in myotubes.
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http://dx.doi.org/10.29219/fnr.v65.4527DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869443PMC
January 2021

Network Patterns of Herbal Combinations in Traditional Chinese Clinical Prescriptions.

Front Pharmacol 2020 20;11:590824. Epub 2021 Jan 20.

Medical Intelligence Institute, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China.

As a well-established multidrug combinations schema, traditional Chinese medicine (herbal prescription) has been used for thousands of years in real-world clinical settings. This paper uses a complex network approach to investigate the regularities underlying multidrug combinations in herbal prescriptions. Using five collected large-scale real-world clinical herbal prescription datasets, we construct five weighted herbal combination networks with herb as nodes and herbal combinational use in herbal prescription as links. We found that the weight distribution of herbal combinations displays a clear power law, which means that most herb pairs were used in low frequency and some herb pairs were used in very high frequency. Furthermore, we found that it displays a clear linear negative correlation between the clustering coefficients and the degree of nodes in the herbal combination network (HCNet). This indicates that hierarchical properties exist in the HCNet. Finally, we investigate the molecular network interaction patterns between herb related target modules (i.e., subnetworks) in herbal prescriptions using a network-based approach and further explore the correlation between the distribution of herb combinations and prescriptions. We found that the more the hierarchical prescription, the better the corresponding effect. The results also reflected a well-recognized principle called "" in TCM formula theories. This also gives references for multidrug combination development in the field of network pharmacology and provides the guideline for the clinical use of combination therapy for chronic diseases.
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http://dx.doi.org/10.3389/fphar.2020.590824DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7854460PMC
January 2021

A network-based machine-learning framework to identify both functional modules and disease genes.

Hum Genet 2021 Jun 7;140(6):897-913. Epub 2021 Jan 7.

School of Computer and Information Technology, Institute of Medical Intelligence, Beijing Jiaotong University, Beijing, 100044, China.

Disease gene identification is a critical step towards uncovering the molecular mechanisms of diseases and systematically investigating complex disease phenotypes. Despite considerable efforts to develop powerful computing methods, candidate gene identification remains a severe challenge owing to the connectivity of an incomplete interactome network, which hampers the discovery of true novel candidate genes. We developed a network-based machine-learning framework to identify both functional modules and disease candidate genes. In this framework, we designed a semi-supervised non-negative matrix factorization model to obtain the functional modules related to the diseases and genes. Of note, we proposed a disease gene-prioritizing method called MapGene that integrates the correlations from both functional modules and network closeness. Our framework identified a set of functional modules with highly functional homogeneity and close gene interactions. Experiments on a large-scale benchmark dataset showed that MapGene performs significantly better than the state-of-the-art algorithms. Further analysis demonstrates MapGene can effectively relieve the impact of the incompleteness of interactome networks and obtain highly reliable rankings of candidate genes. In addition, disease cases on Parkinson's disease and diabetes mellitus confirmed the generalization of MapGene for novel candidate gene identification. This work proposed, for the first time, an integrated computing framework to predict both functional modules and disease candidate genes. The methodology and results support that our framework has the potential to help discover underlying functional modules and reliable candidate genes in human disease.
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http://dx.doi.org/10.1007/s00439-020-02253-0DOI Listing
June 2021

Topological Analysis of the Language Networks of Ancient Traditional Chinese Medicine Books.

Evid Based Complement Alternat Med 2020 10;2020:8810016. Epub 2020 Dec 10.

Beijing Key Lab of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China.

This study aims to explore the topological regularities of the character network of ancient traditional Chinese medicine (TCM) book. We applied the 2-gram model to construct language networks from ancient TCM books. Each text of the book was separated into sentences and a TCM book was generated as a directed network, in which nodes represent Chinese characters and links represent the sequential associations between Chinese characters in the sentences (the occurrence of identical sequential associations is considered as the weight of this link). We first calculated node degrees, average path lengths, and clustering coefficients of the book networks and explored the basic topological correlations between them. Then, we compared the similarity of network nodes to assess the specificity of TCM concepts in the network. In order to explore the relationship between TCM concepts, we screened TCM concepts and clustered them. Finally, we selected the binary groups whose weights are greater than 10 in (ICH, ) and (TCPD, ), hoping to find the core differences of these two ancient TCM books through them. We found that the degree distributions of ancient TCM book networks are consistent with power law distribution. Moreover, the average path lengths of book networks are much smaller than random networks of the same scale; clustering coefficients are higher, which means that ancient book networks have small-world patterns. In addition, the similar TCM concepts are displayed and linked closely, according to the results of cosine similarity comparison and clustering. Furthermore, the core words of and have essential differences, which might indicate the significant differences of language and conceptual patterns between theoretical and clinical books. This study adopts language network approach to investigate the basic conceptual characteristics of ancient TCM book networks, which proposes a useful method to identify the underlying conceptual meanings of particular concepts conceived in TCM theories and clinical operations.
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http://dx.doi.org/10.1155/2020/8810016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7748907PMC
December 2020

Insights on Substitution Preference of Pb Ions in Sulfoaluminate Cement Clinker Phases.

Materials (Basel) 2020 Dec 24;14(1). Epub 2020 Dec 24.

Henan Key Laboratory of Materials on Deep-Earth Engineering, School of Materials Science and Engineering, Henan Polytechnic University, Jiaozuo 454003, China.

The doping behaviors of Pb in sulfoaluminate cement (SAC) clinker phases were systematically studied combined with density functional theoretical simulations and experiments. The results present that, in the three composed minerals of CAS, CS, and CAF, Pb ions prefer to incorporate into CAS by substituting Ca ions. Further analyses from partial density of states, electron density difference, and local distortions show that such doping preference can be attributed to the small distortions as Pb introduced at Ca sites of CAS. The results and clear understandings on the doping behaviors of Pb ions may provide valuable information in guiding the synthesis of Pb-bearing SAC clinker, thus should draw broad interests in fields from sustainable production of cement and environmental protection.
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http://dx.doi.org/10.3390/ma14010044DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7796364PMC
December 2020

Revealing the substitution preference of zinc in ordinary Portland cement clinker phases: A study from experiments and DFT calculations.

J Hazard Mater 2021 May 9;409:124504. Epub 2020 Nov 9.

Henan Key Laboratory of Materials on Deep-Earth Engineering, School of Materials Science and Engineering, Henan Polytechnic University, Jiaozuo 454003, China. Electronic address:

Ordinary Portland cement (OPC) clinker mainly consist four minerals, tricalcium silicate (CS), dicalcium silicate (CS,), tricalcium aluminate (CA), and tetracalcium aluminoferrite (CAF). To learn the doping behaviors of Zn in OPC clinker, a series of samples were prepared by calcinating the mixtures of CaCO, SiO, AlO, FeO, and ZnO. Our results from energy-dispersive spectroscopy, X-ray diffraction and density functional theoretical simulations show that a small amount of ZnO enter CS and CS by replacing Ca ions while most incorporate into CAF by substituting Fe atoms, resulting in a decrease of CA in OPC as dosage increases. Further analyses from partial density of states and distributions of bond order-bond length indicate that the doping preference can be ascribed to the similar electron contributions and small structure distortions between host and guest ions. Unlike the strong Fe‒O bond, the newly formed Zn‒O is much weaker. The weak Zn‒O may be responsible for the limited solubility of Zn in CAF. These results provide a possibility of increasing solubility of Zn in OPC clinker by increasing the contents of CA and CAF, thus will be very meaningful in the synthesis of OPC clinker by utilizing Zn-bearing alternative raw materials.
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http://dx.doi.org/10.1016/j.jhazmat.2020.124504DOI Listing
May 2021

The BTB-TAZ protein MdBT2 negatively regulates the drought stress response by interacting with the transcription factor MdNAC143 in apple.

Plant Sci 2020 Dec 22;301:110689. Epub 2020 Sep 22.

State Key Laboratory of Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, Shandong Collaborative Innovation Center of Fruit & Vegetable Quality and Efficient Production, Tai-An, 271018, Shandong, China. Electronic address:

Drought stress is a severe source of abiotic stress that can affect apple yield and quality, yet the underlying molecular mechanism of the drought stress response and the role of MdBT2 in the process remain unclear. Here, we find that MdBT2 negatively regulates the drought stress response. Both in vivo and in vitro assays indicated that MdBT2 interacted physically with and ubiquitinated MdNAC143, a member of the NAC TF family that is a positive regulator under drought stress. In addition, MdBT2 promotes the degradation of MdNAC143 via the 26S proteasome system. A series of transgenic assays in apple calli and Arabidopsis verify that MdBT2 confers susceptibility to drought stress at least in part by the regulation of MdNAC143. Overall, our findings provide new insight into the mechanism of MdBT2, which functions antagonistically to MdNAC143 in regulating drought stress by regulating the potential downstream target protein MdNAC143 for proteasomal degradation in apple.
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http://dx.doi.org/10.1016/j.plantsci.2020.110689DOI Listing
December 2020

Peroxidase-like recyclable SERS probe for the detection and elimination of cationic dyes in pond water.

J Hazard Mater 2021 Apr 29;408:124426. Epub 2020 Oct 29.

Advanced Photonics Center, Southeast University, Nanjing 210096, China. Electronic address:

A peroxidase-like MOF coated magnetic surface-enhanced Raman scattering (SERS) probe as Ni@Mil-100(Fe)@Ag nanowires (NMAs) was developed, which can detect multiple cationic dyes with a good recyclability and a high sensitivity. Specifically, Mil-100(Fe) with peroxidase-like activity was fabricated on the magnetic prickly Ni nanowires through layer-by-layer (LBL) method. With the presence of 10 mM HO, hydroxyl radical (•OH) produced by peroxidase-like catalytic reaction of Mil-100(Fe) layer can easily eliminate the pollution molecules within 1 min without any requirement for expensive equipment or complicated process. The magnetic NMAs can provide a rapid refreshment for at least 10 times. In addition, carboxyl-functionalized Mil-100(Fe) can not only increase the decoration efficiency of Tollens but also promote the selective enrichment of the cationic dyes, which endows the probe with a greatly improved sensitivity with a limit of detection (LOD) as low as 10 M for crystal violet (CV). Following the erasure by HO, multiple cationic fishery drugs in pond water can be sequentially detected. Such a recyclable SERS probe holds a great potential in various applications as aquaculture, biomedicine and chemical analysis.
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http://dx.doi.org/10.1016/j.jhazmat.2020.124426DOI Listing
April 2021

A comprehensive update on early gastric cancer: defining terms, etiology, and alarming risk factors.

Expert Rev Gastroenterol Hepatol 2021 Mar 9;15(3):255-273. Epub 2020 Nov 9.

Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital , Tianjin, PR, China.

Introduction: Early gastric cancer (EGC) is a well-defined gastric malignancy that is limited to the mucosa or submucosa, irrespective of lymph node metastasis. At an early stage, gastric cancer often does not cause symptoms until it becomes advanced, and it is a heterogeneous disease and usually encountered in its late stages.

Area Covered: This comprehensive review will provide a novel insight into the evaluation of EGC epidemiology, defining terms, extensive etiology and risk factors, and timely diagnosis since prevention is an essential approach for controlling this cancer and reducing its morbidity and mortality.

Expert Opinion: The causative manner of EGC is complex and multifactorial. In recent years, researchers have made significant contributions to understanding the etiology and pathogenesis of EGC, and standardization in the evaluation of disease activity. Though the incidence of this cancer is steadily declining in some advanced societies owing to appropriate interventions, there remains a serious threat to health in developing nations. Early detection of resectable gastric cancer is crucial for better patient outcomes.
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http://dx.doi.org/10.1080/17474124.2021.1845140DOI Listing
March 2021

Lamin B1 promotes tumor progression and metastasis in primary prostate cancer patients.

Future Oncol 2021 Feb 28;17(6):663-673. Epub 2020 Oct 28.

Department of Urology, Tianjin Union Medical Center, Tianjin 300121, China.

To determine the role of lamin B1 (LMNB1) in the progression and metastasis of primary prostate cancer (PC). Two PC cohorts were used to investigate the clinical relationship between expression and tumor progression and metastasis. The qRT-PCR results revealed that expression was markedly increased in patients with aggressive features and was associated with worse prognosis. Logistic regression analyses indicated that expression is an independent risk factor for distant metastasis. Kaplan-Meier analysis showed that increased LMNB1 levels were related to poor disease-free survival in the primary PC cohort. This study reveals that upregulation of is associated with cancer metastasis and poor survival outcomes in primary PC patients.
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http://dx.doi.org/10.2217/fon-2020-0825DOI Listing
February 2021

SERS-fluorescence-superresolution triple-mode nanoprobe based on surface enhanced Raman scattering and surface enhanced fluorescence.

J Mater Chem B 2020 09;8(36):8459-8466

Advanced Photonics Center, Southeast University, Nanjing 210096, Jiangsu, China.

Multifunctional nanoprobes play important roles in cell imaging and sensing. Here, we present a novel optical nanoprobe based on surface enhanced Raman scattering (SERS) and surface enhanced fluorescence (SEF), which can realize the SERS-fluorescence and superresolution triple-mode imaging of cancer cells. Compared with other previously reported multifunctional nanoprobes, the proposed nanoprobe holds two exquisite properties. The first one is that, in addition to normal SERS and fluorescence imaging, the nanoprobe can also be used for single molecule localization microscopy (SMLM) imaging, which helps compensate for the diffraction limited spatial resolution of normal SERS and fluorescence imaging. The second one is that, other than simple fluorescence, SEF is used in the nanoprobe to produce a stronger signal for fluorescence imaging and, more importantly, better photo-switching for SMLM imaging. In the experiment, we optimized the structure of the nanoprobe to obtain the best SEF effect. With the optimal structure, the triple-mode imaging of a breast cancer cell line (SKBR3) is realized. Since such triple-mode imaging of cancer cells has never been achieved before, we believe that the presented nanoprobe holds great potential for cancer cell targeting or the investigation of cell-nanomaterial interactions.
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http://dx.doi.org/10.1039/d0tb01211dDOI Listing
September 2020

PDGNet: Predicting Disease Genes Using a Deep Neural Network with Multi-view Features.

IEEE/ACM Trans Comput Biol Bioinform 2020 Jun 16;PP. Epub 2020 Jun 16.

The knowledge of phenotype-genotype associations is crucial for the understanding of disease mechanisms. Numerous studies have focused on developing efficient and accurate computing approaches to predict disease genes. However, owing to the sparseness and complexity of medical data, developing an efficient deep neural network model to identify disease genes remains a huge challenge. Therefore, we develop a novel deep neural network model that fuses the multi-view features of phenotypes and genotypes to identify disease genes (termed PDGNet). Our model integrated the multi-view features of diseases and genes and leveraged the feedback information of training samples to optimize the parameters of deep neural network and obtain the deep vector features of diseases and genes. The evaluation experiments on a large data set indicated that PDGNet obtained higher performance than the state-of-the-art method (precision and recall improved by 9.55% and 9.63%). The analysis results for the candidate genes indicated that the predicted genes have strong functional homogeneity and dense interactions with known genes. We validated the top predicted genes of Parkinson's disease based on external curated data and published medical literatures, which indicated that the candidate genes have a huge potential to guide the selection of causal genes in the 'wet experiment'.
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http://dx.doi.org/10.1109/TCBB.2020.3002771DOI Listing
June 2020

A Novel Surface Electromyographic Signal-Based Hand Gesture Prediction Using a Recurrent Neural Network.

Sensors (Basel) 2020 Jul 17;20(14). Epub 2020 Jul 17.

School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China.

Surface electromyographic signal (sEMG) is a kind of bioelectrical signal, which records the data of muscle activity intensity. Most sEMG-based hand gesture recognition, which uses machine learning as the classifier, depends on feature extraction of sEMG data. Recently, a deep leaning-based approach such as recurrent neural network (RNN) has provided a choice to automatically learn features from raw data. This paper presents a novel hand gesture prediction method by using an RNN model to learn from raw sEMG data and predict gestures. The sEMG signals of 21 short-term hand gestures of 13 subjects were recorded with a Myo armband, which is a non-intrusive, low cost, commercial portable device. At the start of the gesture, the trained model outputs an instantaneous prediction for the sEMG data. Experimental results showed that the more time steps of data that were known, the higher instantaneous prediction accuracy the proposed model gave. The predicted accuracy reached about 89.6% when the data of 40-time steps (200 ms) were used to predict hand gesture. This means that the gesture could be predicted with a delay of 200 ms after the hand starts to perform the gesture, instead of waiting for the end of the gesture.
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http://dx.doi.org/10.3390/s20143994DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7412393PMC
July 2020

A SERS-colorimetric dual-mode aptasensor for the detection of cancer biomarker MUC1.

Anal Bioanal Chem 2020 Sep 6;412(23):5707-5718. Epub 2020 Jul 6.

Advanced Photonics Center, School of Electronic Science and Engineering, Southeast University, Nanjing, 210096, Jiangsu, China.

Human mucin-1 (MUC1) has attracted considerable attention owing to its overexpression in diverse malignancies. Here, for the rapid and efficient detection of MUC1, we present a SERS-colorimetric dual-mode aptasensor, by integrating SERS probes with magnetic separation, which has several distinctive advantages. Using such a dual-mode aptasensor, the colorimetric functionality is distinguishable by the naked eye, providing a fast and straightforward screening ability for the detection of MUC1. Moreover, SERS-based detection greatly improves the detection sensitivity, reaching a limit of detection of 0.1 U/mL. In addition, the combination of SERS and colorimetric method holds the advantages of these two techniques and thereby increases the reliability and efficiency of MUC1 detection. On the one hand, the magnetic nanobeads functionalized with MUC1-specific aptamer were utilized as an efficient capturing substrate for separating MUC1 from biological complex medium. On the other hand, the gold-silver core-shell nanoparticles modified with Raman reporters and the complementary sequences of MUC1 were used as the signal indicator, which could simultaneously report the SERS signal and colorimetric change. This strategy can achieve a good detection range and realize MUC1 analysis in real patients' samples. Thus, we anticipate that this kind of aptasensor would provide promising potential applications in the diagnosis and prognosis of cancers. Graphical abstract.
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http://dx.doi.org/10.1007/s00216-020-02790-7DOI Listing
September 2020

Quaternary-Ammonium-Modulated Surface-Enhanced Raman Spectroscopy Effect: Discovery, Mechanism, and Application for Highly Sensitive Sensing of Acetylcholine.

Anal Chem 2020 07 9;92(14):9706-9713. Epub 2020 Jul 9.

Advanced Photonics Center, Southeast University, Nanjing, Jiangsu 210096, China.

Quaternary ammonium (QA) plays multiple roles in biological functions, whose dysregulation may result in multiple diseases. However, how to efficiently detect QA-based materials such as acetylcholine (ACh) still remains a great challenge, especially in complex biological environments. Here, a new effect [called quaternary-ammonium-modulated surface-enhanced Raman spectroscopy (QAM-SERS) effect] is discovered, showing that the existence of QA will modulate the intensity of SERS signals in a concentration-dependent manner. When the QAM-SERS effect is used, a new method is easily developed for detection of ACh with an extremely high sensitivity and an ultrawide dynamic range. Particularly, the linear dynamic range can be freely tuned to adapt for various physiological samples. As a proof-of-concept experiment, the time-dependent secretion of ACh from PC12 cells was successfully monitored using the QAM-SERS method, which were under either the stimulation of potassium ions or the incubation of drugs. The discovery of the QAM-SERS effect provides an easy and universal strategy for detecting ACh as well as other QA-contained molecules, which can also inspire new insights into the roles that QA could play in biology and chemistry.
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http://dx.doi.org/10.1021/acs.analchem.0c01061DOI Listing
July 2020

Integrated network analysis of symptom clusters across disease conditions.

J Biomed Inform 2020 07 11;107:103482. Epub 2020 Jun 11.

Institute of Medical Intelligence, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China; Data Center of Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China. Electronic address:

Identifying the symptom clusters (two or more related symptoms) with shared underlying molecular mechanisms has been a vital analysis task to promote the symptom science and precision health. Related studies have applied the clustering algorithms (e.g. k-means, latent class model) to detect the symptom clusters mostly from various kinds of clinical data. In addition, they focused on identifying the symptom clusters (SCs) for a specific disease, which also mainly concerned with the clinical regularities for symptom management. Here, we utilized a network-based clustering algorithm (i.e., BigCLAM) to obtain 208 typical SCs across disease conditions on a large-scale symptom network derived from integrated high-quality disease-symptom associations. Furthermore, we evaluated the underlying shared molecular mechanisms for SCs, i.e., shared genes, protein-protein interaction (PPI) and gene functional annotations using integrated networks and similarity measures. We found that the symptoms in the same SCs tend to share a higher degree of genes, PPIs and have higher functional homogeneities. In addition, we found that most SCs have related symptoms with shared underlying molecular mechanisms (e.g. enriched pathways) across different disease conditions. Our work demonstrated that the integrated network analysis method could be used for identifying robust SCs and investigate the molecular mechanisms of these SCs, which would be valuable for symptom science and precision health.
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http://dx.doi.org/10.1016/j.jbi.2020.103482DOI Listing
July 2020

Hydrophobic Plasmonic Nanoacorn Array for a Label-Free and Uniform SERS-Based Biomolecular Assay.

ACS Appl Mater Interfaces 2020 Jul 22;12(26):29917-29927. Epub 2020 Jun 22.

Advanced Photonics Center, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, China.

A surface-enhanced Raman scattering (SERS) aptasensor based on a hydrophobic assembled nanoacorn (HANA) was developed with improved reproducibility and reduced nonspecific binding effect. In the fabrication process, a hexagonal-packed gold film over nanosphere (AuFON) arrays was first obtained and used as a hydrophobic plasmonic substrate. Then, a uniform sub-3 nm molecular spacer array (containing Raman reporters) was prepared by patterning nanometric hydrophilic ultrathin patches onto the hydrophobic AuFON, in which the hydrophilic thin layer is composed of polymers and aptamers. During the sensing process, the HANA aptasensor smartly impedes the adsorption of SERS probes as Au@Ag nanocubes (Au@Ag NCs) in the absence of targets. In the presence of targets, the displacement of aptamers occurs due to the specific interaction between the targets and the aptamers, and the Au@Ag NCs can be assembled onto the hydrophilic patches on AuFON through electrostatic interactions with polymers. Thus, SERS signals of reporter molecules inside the spacer can be dramatically enhanced due to the formation of a nanoparticle-on-mirror (NPoM) array. In such a SERS aptasensor, the well-ordered distribution of SERS probes ensures excellent repeatability, while the precise subnanometer junctions guarantee high sensitivity. More importantly, since the hydrophobic surface can greatly reduce nonspecific adsorption, the tedious process of nonspecific blocking that is employed in traditional biosensors is no longer needed. Using such a SERS HANA platform, human epidermal growth factor receptor 2 (HER2) and three exosomal proteins were analyzed with high sensitivity and good reproducibility (RSD < 7%) in whole-blood samples.
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http://dx.doi.org/10.1021/acsami.0c03993DOI Listing
July 2020

Important role of surface plasmon coupling with the quantum wells in a surface plasmon enhanced color-converting structure of colloidal quantum dots on quantum wells.

Opt Express 2020 Apr;28(9):13352-13367

To improve the color-conversion efficiency based on a quantum-well (QW) light-emitting diode (LED), a more energy-saving strategy is needed to increase the energy transfer efficiency from the electrical input power of the LED into the emission of over-coated color-converter, not just from LED emission into converted light. In this regard, the efficiency of energy transfer of any mechanism from LED QW into the color-converter is an important issue. By overlaying blue-emitting QW structures and GaN templates with both deposited metal nanoparticles (DMNPs) and color-converting quantum dot (QD) linked synthesized metal nanoparticles (SMNPs) of different localized surface plasmon (LSP) resonance wavelengths for producing multiple surface plasmon (SP) coupling mechanisms with the QW and QD, we study the enhancement variations of their internal quantum efficiencies and photoluminescence decay times. By comparing the QD emission efficiencies between the samples with and without QW, one can observe the advantageous effect of QW coupling with LSP resonances on QD emission efficiency. Also, with the LSP resonance wavelengths of both DMNPs and SMNPs close to the QW emission wavelength for producing strong SP coupling with the QW and hence QD absorption, a higher QD emission or color-conversion efficiency can be obtained.
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http://dx.doi.org/10.1364/OE.390478DOI Listing
April 2020

Identification of herbal categories active in pain disorder subtypes by machine learning help reveal novel molecular mechanisms of algesia.

Pharmacol Res 2020 06 8;156:104797. Epub 2020 Apr 8.

Beijing University of Chinese Medicine, Beijing, 100029, China. Electronic address:

Chronic pain is highly prevalent and poorly controlled, of which the accurate underlying mechanisms need be further elucidated. Herbal drugs have been widely used for controlling various pain disorders. The systematic integration of pain herbal data resources might be promising to help investigate the molecular mechanisms of pain phenotypes. Here, we integrated large-scale bibliographic literatures and well-established data sources to obtain high-quality pain relevant herbal data (i.e. 426 pain related herbs with their targets). We used machine learning method to identify three distinct herb categories with their specific indications of symptoms, targets and enriched pathways, which were characterized by the efficacy of treatment to the chronic cough related neuropathic pain, the reproduction and autoimmune related pain, and the cancer pain, respectively. We further detected the novel pathophysiological mechanisms of the pain subtypes by network medicine approach to evaluate the interactions between herb targets and the pain disease modules. This work increased the understanding of the underlying molecular mechanisms of pain subtypes that herbal drugs are participating and with the ultimate aim of developing novel personalized drugs for pain disorders.
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http://dx.doi.org/10.1016/j.phrs.2020.104797DOI Listing
June 2020

Spatial range of the plasmonic Dicke effect in an InGaN/GaN multiple quantum well structure.

Nanotechnology 2020 May 8;31(29):295001. Epub 2020 Apr 8.

Institute of Photonics and Optoelectronics, and Department of Electrical Engineering, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan.

The plasmonic Dicke effect means a cooperative emission mechanism of multiple light emitters when they are simultaneously coupled with the same surface plasmon (SP) mode of a metal nanostructure to achieve a higher collective emission efficiency. Here, we compare the enhancements of emission efficiency among a series of SP-coupled InGaN/GaN quantum-well (QW) structures of different QW period numbers to show an emission behavior consistent with the plasmonic Dicke effect. The relative enhancement of overall emission efficiency increases with QW period number until it reaches a critical value, beyond which the enhancement starts to decrease. This critical QW period number corresponds to the effective depth range of the plasmonic Dicke effect in a multiple-QW system. It also represents an optimized QW structure for maximizing the SP coupling effect. Internal quantum efficiency and time-resolved photoluminescence are measured for comparing the enhanced emission efficiencies of blue and green QW structures with different QW period numbers through SP coupling induced by surface Ag nanoparticles.
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http://dx.doi.org/10.1088/1361-6528/ab87ccDOI Listing
May 2020

PKMYT1 is associated with prostate cancer malignancy and may serve as a therapeutic target.

Gene 2020 Jun 29;744:144608. Epub 2020 Mar 29.

Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China. Electronic address:

Prostate cancer (PCa) is the third most common malignancy worldwide. Novel and effective therapeutic targets are needed for PCa. The purpose of this study was to discover novel therapeutic targets for PCa by performing advanced analysis on PCa RNA sequencing (RNAseq) data from The Cancer Genome Atlas (TCGA). Weighted correlation-network analysis (WGCNA) was performed on the RNAseq data of tumor samples, and the module most relevant to the Gleason score was identified. Combining differential gene-expression analysis and survival analysis, we narrowed down potential therapeutic target genes and found that PKMYT1 might be one. Subsequently, functional studies (i.e., cell-proliferation assays, cell cycle analysis, and colony-formation assays) demonstrated that knockdown of PKMYT1 significantly inhibited the growth of PCa cells. Further investigation illustrated that PKMYT1 promoted the growth of PCa cells through targeting CCNB1 and CCNE1 expression. In addition, fostamatinib, an inhibitor of PKMYT1, effectively inhibited the proliferation of PCa cells. Taken together, our results suggest that PKMYT1 is a gene associated with malignancy of PCa and is a novel therapeutic target.
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http://dx.doi.org/10.1016/j.gene.2020.144608DOI Listing
June 2020

FTX contributes to cell proliferation and migration in lung adenocarcinoma via targeting miR-335-5p/NUCB2 axis.

Cancer Cell Int 2020 23;20:89. Epub 2020 Mar 23.

1Department of Oncology, The Second Hospital of Tianjin Medical University, No. 23 Pingjiang Road, Hexi District, Tianjin, 300211 China.

Background: Extensive studies revealed that long non-coding RNAs (lncRNAs) could act as a regulator in tumors, including lung adenocarcinoma (LUAD). LncRNA FTX transcript, XIST regulator (FTX) has been reported to regulate the biological behaviors of some cancers. Nevertheless, its functional role and molecular mechanism remain obscure in LUAD. Our current study concentrates on exploring the biological function of FTX in LUAD.

Methods: RT-qPCR was used to test the expression of FTX, miR-335-5p or NUCB2 in LUAD cells. The effect of FTX on LUAD progression was investigated by colony formation, EdU, flow cytometry, TUNEL, transwell and western blot assays. The interaction between microRNA-335-5p (miR-335-5p) and FTX or nucleobindin 2 (NUCB2) was confirmed by luciferase reporter assay.

Results: RT-qPCR showed that FTX expression was up-regulated in LUAD cell lines. Loss-of-function assay indicated that FTX accelerated cell proliferation, migration and invasion, while inhibited cell apoptosis in LUAD. Besides, miR-335-5p, lowly expressed in LUAD cells, was discovered to be sponged by FTX. Subsequently, NUCB2 was identified as a target gene of miR-335-5p. Additionally, it was confirmed that NUCB2 functioned as an oncogene in LUAD. Rescue assays indicated that LUAD progression inhibited by FTX knockdown could be restored by NUCB2 up-regulation.

Conclusion: FTX played an oncogenic role in LUAD and contributed to cancer development via targeting miR-335-5p/NUCB2 axis.
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http://dx.doi.org/10.1186/s12935-020-1130-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7092578PMC
March 2020

TACC3 promotes prostate cancer cell proliferation and restrains primary cilium formation.

Exp Cell Res 2020 05 7;390(2):111952. Epub 2020 Mar 7.

Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Pingjiang Road 23, Hexi District, Tianjin, 300211, China. Electronic address:

Although primary cilia abnormalities have been frequently observed in multiple cancers, including prostate cancer (PCa), the molecular mechanisms underlying primary ciliogenesis repression in PCa cells remain unclear. Transforming acidic coiled-coil protein-3 (TACC3), whose deregulation has been implicated in the pathogenesis of several types of cancer, is a key centrosomal protein that plays a crucial role in centrosome/microtubule dynamics, potentially impacting primary cilium generation. Here, we showed that TACC3 was markedly upregulated in PCa and that knockdown of TACC3 restrained tumorigenesis and tumor growth in vitro and in vivo. Additionally, we found that TACC3 interacts with filamin A, and elevated levels of TACC3 disrupted the interaction between filamin A and meckelin, thereby restraining primary cilium formation in PCa cells.
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http://dx.doi.org/10.1016/j.yexcr.2020.111952DOI Listing
May 2020

Disease phenotype synonymous prediction through network representation learning from PubMed database.

Artif Intell Med 2020 01 19;102:101745. Epub 2019 Nov 19.

School of Computer and Information Technology and Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China. Electronic address:

Synonym mapping between phenotype concepts from different terminologies is difficult because terminology databases have been developed largely independently. Existing maps of synonymous phenotype concepts from different terminology databases are highly incomplete, and manually mapping is time consuming and laborious. Therefore, building an automatic method for predictive mapping of synonymous phenotypes is of special importance. We propose a classifier-based phenotype mapping prediction model (CPM) to predict synonymous relationships between phenotype concepts from different terminology databases. The model takes network semantic representations of phenotypes as input and predicts synonymous relationships by training binary classifiers with a voting strategy. We compared the performance of the CPM with a similarity-based phenotype mapping prediction model (SPM), which predicts mapping based on the ranked cosine similarity of candidate mapping concepts. Based on a network representation N2V-TFIDF, with a majority voting strategy method MV, the CPM achieved accuracy of 0.943, which was 15.4% higher than that of the SPM using the cosine similarity method (0.789) and 23.8% higher than that of the SSDTM method (0.724) proposed in our previous work.
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http://dx.doi.org/10.1016/j.artmed.2019.101745DOI Listing
January 2020

In Situ Visualization and SERS Monitoring of the Interaction between Tumor and Endothelial Cells Using 3D Microfluidic Networks.

ACS Sens 2020 01 13;5(1):208-216. Epub 2020 Jan 13.

Advanced Photonics Center , Southeast University , Nanjing 210096 , China.

A multifunctional microfluidic platform was demonstrated to monitor the interaction between tumor cells and endothelial cells by integrating a three-dimensional (3D) cell culture unit with a protein detection unit. In such a chip, breast cancer cells MCF7 were seeded into the collagen to form a 3D tumor environment while human umbilical vein endothelial cells (HUVECs) are seeded in the channel next to the collagen matrix. Thus, an in situ growth of angiogenic sprouting can be visualized through fluorescence in the 3D collagen matrix after a coculture of MCF7 and HUVEC after 4 days, which cannot be observed in the 2D culture environment. On the other hand, gold@silver core-shell nanorods were used as surface-enhanced Raman scattering (SERS) immunoprobes for the detection of the secretion of cytokine (vascular endothelial growth factor, VEGF). The limit of detection of the VEGF is 100 pg/mL. Further, as LiCl and bevacizumab can act as a promoter and an inhibitor of VEGF, the dynamic change of the concentration of VEGF under the stimulation of them was monitored by SERS signals. Thus, this integrated SERS microfluidic platform creates opportunity for the fundamental research of interaction between tumors and endothelial cells.
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http://dx.doi.org/10.1021/acssensors.9b02085DOI Listing
January 2020