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  1. Fulltext Momordica charantia Suppresses Inflammation and Glycolysis in Lipopolysaccharide-Activated RAW264.7 Macrophages
    Lee SY, Wong WF, Dong J, Cheng KK
    Molecules, 2020 Aug 20;25(17).
    PMID: 32825228 DOI: 10.3390/molecules25173783
    Macrophage activation is a key event that triggers inflammatory response. The activation is accompanied by metabolic shift such as upregulated glucose metabolism. There are accumulating evidences showing the anti-inflammatory activity of Momordica charantia. However, the effects of M. charantia on inflammatory response and glucose metabolism in activated macrophages have not been fully established. The present study aimed to examine the effect of M. charantia in modulating lipopolysaccharide (LPS)-induced inflammation and perturbed glucose metabolism in RAW264.7 murine macrophages. The results showed that LPS-induced NF-κB (p65) nuclear translocation was inhibited by M. charantia treatment. In addition, M. charantia was found to reduce the expression of inflammatory genes including IL6, TNF-α, IL1β, COX2, iNOS, and IL10 in LPS-treated macrophages. Furthermore, the data showed that M. charantia reduced the expression of GLUT1 and HK2 genes and lactate production (-28%), resulting in suppression of glycolysis. Notably, its effect on GLUT1 gene expression was found to be independent of LPS-induced inflammation. A further experiment also indicated that the bioactivities of M. charantia may be attributed to its key bioactive compound, charantin. Taken together, the study provided supporting evidences showing the potential of M. charantia for the treatment of inflammatory disorders.
  2. Design and development of novel hyaluronate-modified nanoparticles for combo-delivery of curcumin and alendronate: fabrication, characterization, and cellular and molecular evidences of enhanced bone regeneration
    Dong J, Tao L, Abourehab MAS, Hussain Z
    Int J Biol Macromol, 2018 Sep;116:1268-1281.
    PMID: 29782984 DOI: 10.1016/j.ijbiomac.2018.05.116
    Osteoporosis is a medical condition of fragile bones with an increased susceptibility to fracture. Despite having availability of a wide range of pharmacological agents, prevalence of osteoporosis is continuously escalating. Owing to excellent biomedical achievements of nanomedicines in the last few decades, we aimed combo-delivery of bone anti-resorptive agent, alendronate (ALN), and bone density enhancing drug, curcumin (CUR) in the form of polymeric nanoparticles. To further optimize the therapeutic efficacy, the prepared ALN/CUR nanoparticles (NPs) were decorated with hyaluronic acid (HA) which is a well-documented biomacromolecule having exceptional bone regenerating potential. The optimized nanoformulation was then evaluated for bone regeneration efficacy by assessing time-mannered modulation in the proliferation, differentiation, and mineralization of MC3T3-E1 cells, a pre-osteoblastic model. Moreover, the time-mannered expression of various bone-forming protein biomarkers such as bone morphogenetic protein, runt related transcription factor 2, and osteocalcin were assessed in the cell lysates. Results revealed that HA-ALN/CUR NPs provoke remarkable increase in the proliferation, differentiation, and mineralization in the ECM of MC3T3-E1 cells which ultimately leads to enhanced bone formation. This new strategy of employing simultaneous delivery of anti-resorptive and bone forming agents would open new horizons for scientists as an efficient alternative pharmacotherapy for the management of osteoporosis.
  3. Purification of Plasmodium and Babesia- infected erythrocytes using a non-woven fabric filter
    Tao ZY, Liu WP, Dong J, Feng XX, Yao DW, Lv QL, et al.
    Trop Biomed, 2020 Dec 01;37(4):911-918.
    PMID: 33612745 DOI: 10.47665/tb.37.4.911
    The purification of parasite-infected erythrocytes from whole blood containing leucocytes is crucial for many downstream genetic and molecular assays in parasitology. Current methodologies to achieve this are often costly and time consuming. Here, we demonstrate the successful application of a cheap and simple Non-Woven Fabric (NWF) filter for the purification of parasitized red blood cells from whole blood. NWF filtration was applied to the malaria-parasitized blood of three strains of mice, and one strain of rat, and to Babesia gibsoni parasitized dog blood. Before and after filtration, the white blood cell (WBC) removal rates and red blood cell (RBC) recovery rates were measured. After NWF filter treatment of rodent malaria-infected blood, the WBC removal rates and RBC recovery rates were, for Kunming mice: 99.51%±0.30% and 86.12%±8.37%; for BALB/C mice: 99.61%±0.15% and 80.74%±7.11%; for C57 mice: 99.71%±0.12% and 84.87%±3.83%; for Sprague-Dawley rats: 99.93%±0.03% and 83.30%±2.96%. Microscopy showed WBCs were efficiently removed from infected dog blood samples, and there was no obvious morphological change of B. gibsoni parasites. NWF filters efficiently remove leukocytes from malaria parasite-infected mouse and rat blood, and are also suitable for filtration of B. gibsoni-infected dog blood.
  4. Fulltext 1H NMR-based metabolomics investigation of copper-laden rat: a model of Wilson's disease
    Xu J, Jiang H, Li J, Cheng KK, Dong J, Chen Z
    PLoS One, 2015;10(4):e0119654.
    PMID: 25849323 DOI: 10.1371/journal.pone.0119654
    Wilson's disease (WD), also known as hepatoleticular degeneration (HLD), is a rare autosomal recessive genetic disorder of copper metabolism, which causes copper to accumulate in body tissues. In this study, rats fed with copper-laden diet are used to render the clinical manifestations of WD, and their copper toxicity-induced organ lesions are studied. To investigate metabolic behaviors of 'decoppering' process, penicillamine (PA) was used for treating copper-laden rats as this chelating agent could eliminate excess copper through the urine. To date, there has been limited metabolomics study on WD, while metabolic impacts of copper accumulation and PA administration have yet to be established.
  5. Fulltext Deciphering the metabolic perturbation in hepatic alveolar echinococcosis: a 1H NMR-based metabolomics study
    Lin C, Chen Z, Zhang L, Wei Z, Cheng KK, Liu Y, et al.
    Parasit Vectors, 2019 Jun 13;12(1):300.
    PMID: 31196218 DOI: 10.1186/s13071-019-3554-0
    BACKGROUND: Hepatic alveolar echinococcosis (HAE) is caused by the growth of Echinococcus multilocularis larvae in the liver. It is a chronic and potentially lethal parasitic disease. Early stage diagnosis for this disease is currently not available due to its long asymptomatic incubation period. In this study, a proton nuclear magnetic resonance (1H NMR)-based metabolomics approach was applied in conjunction with multivariate statistical analysis to investigate the altered metabolic profiles in blood serum and urine samples obtained from HAE patients. The aim of the study was to identify the metabolic signatures associated with HAE.

    RESULTS: A total of 21 distinct metabolic differences between HAE patients and healthy individuals were identified, and they are associated with perturbations in amino acid metabolism, energy metabolism, glyoxylate and dicarboxylate metabolism. Furthermore, the present results showed that the Fischer ratio, which is the molar ratio of branched-chain amino acids to aromatic amino acids, was significantly lower (P 

  6. DeepPSP: A Global-Local Information-Based Deep Neural Network for the Prediction of Protein Phosphorylation Sites
    Guo L, Wang Y, Xu X, Cheng KK, Long Y, Xu J, et al.
    J Proteome Res, 2021 01 01;20(1):346-356.
    PMID: 33241931 DOI: 10.1021/acs.jproteome.0c00431
    Identification of phosphorylation sites is an important step in the function study and drug design of proteins. In recent years, there have been increasing applications of the computational method in the identification of phosphorylation sites because of its low cost and high speed. Most of the currently available methods focus on using local information around potential phosphorylation sites for prediction and do not take the global information of the protein sequence into consideration. Here, we demonstrated that the global information of protein sequences may be also critical for phosphorylation site prediction. In this paper, a new deep neural network model, called DeepPSP, was proposed for the prediction of protein phosphorylation sites. In the DeepPSP model, two parallel modules were introduced to extract both local and global features from protein sequences. Two squeeze-and-excitation blocks and one bidirectional long short-term memory block were introduced into each module to capture effective representations of the sequences. Comparative studies were carried out to evaluate the performance of DeepPSP, and four other prediction methods using public data sets The F1-score, area under receiver operating characteristic curves (AUROC), and area under precision-recall curves (AUPRC) of DeepPSP were found to be 0.4819, 0.82, and 0.50, respectively, for S/T general site prediction and 0.4206, 0.73, and 0.39, respectively, for Y general site prediction. Compared with the MusiteDeep method, the F1-score, AUROC, and AUPRC of DeepPSP were found to increase by 8.6, 2.5, and 8.7%, respectively, for S/T general site prediction and by 20.6, 5.8, and 18.2%, respectively, for Y general site prediction. Among the tested methods, the developed DeepPSP method was also found to produce best results for different kinase-specific site predictions including CDK, mitogen-activated protein kinase, CAMK, AGC, and CMGC. Taken together, the developed DeepPSP method may offer a more accurate phosphorylation site prediction by including global information. It may serve as an alternative model with better performance and interpretability for protein phosphorylation site prediction.
  7. Fulltext Identifying Significant Metabolic Pathways Using Multi-Block Partial Least-Squares Analysis
    Deng L, Guo F, Cheng KK, Zhu J, Gu H, Raftery D, et al.
    J Proteome Res, 2020 05 01;19(5):1965-1974.
    PMID: 32174118 DOI: 10.1021/acs.jproteome.9b00793
    In metabolomics, identification of metabolic pathways altered by disease, genetics, or environmental perturbations is crucial to uncover the underlying biological mechanisms. A number of pathway analysis methods are currently available, which are generally based on equal-probability, topological-centrality, or model-separability methods. In brief, prior identification of significant metabolites is needed for the first two types of methods, while each pathway is modeled separately in the model-separability-based methods. In these methods, interactions between metabolic pathways are not taken into consideration. The current study aims to develop a novel metabolic pathway identification method based on multi-block partial least squares (MB-PLS) analysis by including all pathways into a global model to facilitate biological interpretation. The detected metabolites are first assigned to pathway blocks based on their roles in metabolism as defined by the KEGG pathway database. The metabolite intensity or concentration data matrix is then reconstructed as data blocks according to the metabolite subsets. Then, a MB-PLS model is built on these data blocks. A new metric, named the pathway importance in projection (PIP), is proposed for evaluation of the significance of each metabolic pathway for group separation. A simulated dataset was generated by imposing artificial perturbation on four pre-defined pathways of the healthy control group of a colorectal cancer study. Performance of the proposed method was evaluated and compared with seven other commonly used methods using both an actual metabolomics dataset and the simulated dataset. For the real metabolomics dataset, most of the significant pathways identified by the proposed method were found to be consistent with the published literature. For the simulated dataset, the significant pathways identified by the proposed method are highly consistent with the pre-defined pathways. The experimental results demonstrate that the proposed method is effective for identification of significant metabolic pathways, which may facilitate biological interpretation of metabolomics data.
  8. Whistles emitted by Indo-Pacific humpback dolphins (Sousa chinensis) in Zhanjiang waters, China
    Dong L, Caruso F, Lin M, Liu M, Gong Z, Dong J, et al.
    J Acoust Soc Am, 2019 06;145(6):3289.
    PMID: 31255103 DOI: 10.1121/1.5110304
    Whistles emitted by Indo-Pacific humpback dolphins in Zhanjiang waters, China, were collected by using autonomous acoustic recorders. A total of 529 whistles with clear contours and signal-to-noise ratio higher than 10 dB were extracted for analysis. The fundamental frequencies and durations of analyzed whistles were in ranges of 1785-21 675 Hz and 30-1973 ms, respectively. Six tonal types were identified: constant, downsweep, upsweep, concave, convex, and sine whistles. Constant type was the most dominant tonal type, accounting for 32.51% of all whistles, followed by sine type, accounting for 19.66% of all whistles. This paper examined 17 whistle parameters, which showed significant differences among the six tonal types. Whistles without inflections, gaps, and stairs accounted for 62.6%, 80.6%, and 68.6% of all whistles, respectively. Significant intraspecific differences in all duration and frequency parameters of dolphin whistles were found between this study and the study in Malaysia. Except for start frequency, maximum frequency and the number of harmonics, all whistle parameters showed significant differences between this study and the study conducted in Sanniang Bay, China. The intraspecific differences in vocalizations for this species may be related to macro-geographic and/or environmental variations among waters, suggesting a potential geographic isolation among populations of Indo-Pacific humpback dolphins.
  9. Sparse PLS-Based Method for Overlapping Metabolite Set Enrichment Analysis
    Deng L, Ma L, Cheng KK, Xu X, Raftery D, Dong J
    J Proteome Res, 2021 06 04;20(6):3204-3213.
    PMID: 34002606 DOI: 10.1021/acs.jproteome.1c00064
    Metabolite set enrichment analysis (MSEA) has gained increasing research interest for identification of perturbed metabolic pathways in metabolomics. The method incorporates predefined metabolic pathways information in the analysis where metabolite sets are typically assumed to be mutually exclusive to each other. However, metabolic pathways are known to contain common metabolites and intermediates. This situation, along with limitations in metabolite detection or coverage leads to overlapping, incomplete metabolite sets in pathway analysis. For overlapping metabolite sets, MSEA tends to result in high false positives due to improper weights allocated to the overlapping metabolites. Here, we proposed an extended partial least squares (PLS) model with a new sparse scheme for overlapping metabolite set enrichment analysis, named overlapping group PLS (ogPLS) analysis. The weight vector of the ogPLS model was decomposed into pathway-specific subvectors, and then a group lasso penalty was imposed on these subvectors to achieve a proper weight allocation for the overlapping metabolites. Two strategies were adopted in the proposed ogPLS model to identify the perturbed metabolic pathways. The first strategy involves debiasing regularization, which was used to reduce inequalities amongst the predefined metabolic pathways. The second strategy is stable selection, which was used to rank pathways while avoiding the nuisance problems of model parameter optimization. Both simulated and real-world metabolomic datasets were used to evaluate the proposed method and compare with two other MSEA methods including Global-test and the multiblock PLS (MB-PLS)-based pathway importance in projection (PIP) methods. Using a simulated dataset with known perturbed pathways, the average true discovery rate for the ogPLS method was found to be higher than the Global-test and the MB-PLS-based PIP methods. Analysis with a real-world metabolomics dataset also indicated that the developed method was less prone to select pathways with highly overlapped detected metabolite sets. Compared with the two other methods, the proposed method features higher accuracy, lower false-positive rate, and is more robust when applied to overlapping metabolite set analysis. The developed ogPLS method may serve as an alternative MSEA method to facilitate biological interpretation of metabolomics data for overlapping metabolite sets.
  10. 1H NMR-Based Metabolic Profiles Delineate the Anticancer Effect of Vitamin C and Oxaliplatin on Hepatocellular Carcinoma Cells
    Lin C, Dong J, Wei Z, Cheng KK, Li J, You S, et al.
    J Proteome Res, 2020 02 07;19(2):781-793.
    PMID: 31916767 DOI: 10.1021/acs.jproteome.9b00635
    Hepatocellular carcinoma (HCC) is a leading cause of cancer death worldwide. Because of its high recurrence rate and heterogeneity, effective treatment for advanced stage of HCC is currently lacking. There are accumulating evidences showing the therapeutic potential of pharmacologic vitamin C (VC) on HCC. However, the metabolic basis underlying the anticancer property of VC remains to be elucidated. In this study, we used a high-resolution proton nuclear magnetic resonance-based metabolomics technique to assess the global metabolic changes in HCC cells following VC treatment. In addition, the HCC cells were also treated with oxaliplatin (OXA) to explore the potential synergistic effect induced by the combined VC and OXA treatment. The current metabolomics data suggested different mechanisms of OXA and VC in modulating cell growth and metabolism. In general, VC treatment led to inhibition of energy metabolism via NAD+ depletion and amino acid deprivation. On the other hand, OXA caused significant perturbation in phospholipid biosynthesis and phosphatidylcholine biosynthesis pathways. The current results highlighted glutathione metabolism, and pathways related to succinate and choline may play central roles in conferring the combined effect between OXA and VC. Taken together, this study provided metabolic evidence of VC and OXA in treating HCC and may contribute toward the potential application of combined VC and OXA as complementary HCC therapies.
  11. Fulltext NMF-Based Approach for Missing Values Imputation of Mass Spectrometry Metabolomics Data
    Xu J, Wang Y, Xu X, Cheng KK, Raftery D, Dong J
    Molecules, 2021 Sep 24;26(19).
    PMID: 34641330 DOI: 10.3390/molecules26195787
    In mass spectrometry (MS)-based metabolomics, missing values (NAs) may be due to different causes, including sample heterogeneity, ion suppression, spectral overlap, inappropriate data processing, and instrumental errors. Although a number of methodologies have been applied to handle NAs, NA imputation remains a challenging problem. Here, we propose a non-negative matrix factorization (NMF)-based method for NA imputation in MS-based metabolomics data, which makes use of both global and local information of the data. The proposed method was compared with three commonly used methods: k-nearest neighbors (kNN), random forest (RF), and outlier-robust (ORI) missing values imputation. These methods were evaluated from the perspectives of accuracy of imputation, retrieval of data structures, and rank of imputation superiority. The experimental results showed that the NMF-based method is well-adapted to various cases of data missingness and the presence of outliers in MS-based metabolic profiles. It outperformed kNN and ORI and showed results comparable with the RF method. Furthermore, the NMF method is more robust and less susceptible to outliers as compared with the RF method. The proposed NMF-based scheme may serve as an alternative NA imputation method which may facilitate biological interpretations of metabolomics data.
  12. Metabolic Effect of Dietary Taurine Supplementation on Nile Tilapia (Oreochromis nilotictus) Evaluated by NMR-Based Metabolomics
    Shen G, Huang Y, Dong J, Wang X, Cheng KK, Feng J, et al.
    J Agric Food Chem, 2018 Jan 10;66(1):368-377.
    PMID: 29215281 DOI: 10.1021/acs.jafc.7b03182
    Taurine is indispensable in aquatic diets that are based solely on plant protein, and it promotes growth of many fish species. However, the physiological and metabolome effects of taurine on fish have not been well described. In this study, 1H NMR-based metabolomics approaches were applied to investigate the metabolite variations in Nile tilapia (Oreochromis nilotictus) muscle in order to visualize the metabolic trajectory and reveal the possible mechanisms of metabolic effects of dietary taurine supplementation on tilapia growth. After extraction using aqueous and organic solvents, 19 taurine-induced metabolic changes were evaluated in our study. The metabolic changes were characterized by differences in carbohydrate, amino acid, lipid, and nucleotide contents. The results indicate that taurine supplementation could significantly regulate the physiological state of fish and promote growth and development. These results provide a basis for understanding the mechanism of dietary taurine supplementation in fish feeding. 1H NMR spectroscopy, coupled with multivariate pattern recognition technologies, is an efficient and useful tool to map the fish metabolome and identify metabolic responses to different dietary nutrients in aquaculture.
  13. Fulltext 1H NMR-based Investigation of Metabolic Response to Electro-Acupuncture Stimulation
    Lin C, Wei Z, Cheng KK, Xu J, Shen G, She C, et al.
    Sci Rep, 2017 07 28;7(1):6820.
    PMID: 28754994 DOI: 10.1038/s41598-017-07306-5
    Acupuncture is a traditional Chinese medicine therapy that has been found useful for treating various diseases. The treatments involve the insertion of fine needles at acupoints along specific meridians (meridian specificity). This study aims to investigate the metabolic basis of meridian specificity using proton nuclear magnetic resonance (1H NMR)-based metabolomics. Electro-acupuncture (EA) stimulations were performed at acupoints of either Stomach Meridian of Foot-Yangming (SMFY) or Gallbladder Meridian of Foot-Shaoyang (GMFS) in healthy male Sprague Dawley (SD) rats. 1H-NMR spectra datasets of serum, urine, cortex, and stomach tissue extracts from the rats were analysed by multivariate statistical analysis to investigate metabolic perturbations due to EA treatments at different meridians. EA treatment on either the SMFY or GMFS acupoints induced significant variations in 31 metabolites, e.g., amino acids, organic acids, choline esters and glucose. Moreover, a few meridian-specific metabolic changes were found for EA stimulations on the SMFY or GMFS acupoints. Our study demonstrated significant metabolic differences in response to EA stimulations on acupoints of SMFY and GMFS meridians. These results validate the hypothesis that meridian specificity in acupuncture is detectable in the metabolome and demonstrate the feasibility and effectiveness of a metabolomics approach in understanding the mechanism of acupuncture.
  14. iMSEA: A Novel Metabolite Set Enrichment Analysis Strategy to Decipher Drug Interactions
    Wang Y, Liu X, Dong L, Cheng KK, Lin C, Wang X, et al.
    Anal Chem, 2023 Apr 18;95(15):6203-6211.
    PMID: 37023366 DOI: 10.1021/acs.analchem.2c04603
    Drug combinations are commonly used to treat various diseases to achieve synergistic therapeutic effects or to alleviate drug resistance. Nevertheless, some drug combinations might lead to adverse effects, and thus, it is crucial to explore the mechanisms of drug interactions before clinical treatment. Generally, drug interactions have been studied using nonclinical pharmacokinetics, toxicology, and pharmacology. Here, we propose a complementary strategy based on metabolomics, which we call interaction metabolite set enrichment analysis, or iMSEA, to decipher drug interactions. First, a digraph-based heterogeneous network model was constructed to model the biological metabolic network based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Second, treatment-specific influences on all detected metabolites were calculated and propagated across the whole network model. Third, pathway activity was defined and enriched to quantify the influence of each treatment on the predefined functional metabolite sets, i.e., metabolic pathways. Finally, drug interactions were identified by comparing the pathway activity enriched by the drug combination treatments and the single drug treatments. A data set consisting of hepatocellular carcinoma (HCC) cells that were treated with oxaliplatin (OXA) and/or vitamin C (VC) was used to illustrate the effectiveness of the iMSEA strategy for evaluation of drug interactions. Performance evaluation using synthetic noise data was also performed to evaluate sensitivities and parameter settings for the iMSEA strategy. The iMSEA strategy highlighted synergistic effects of combined OXA and VC treatments including the alterations in the glycerophospholipid metabolism pathway and glycine, serine, and threonine metabolism pathway. This work provides an alternative method to reveal the mechanisms of drug combinations from the viewpoint of metabolomics.
  15. Fulltext The reciprocal relationships between meaning in life and smartphone addiction among Chinese college students: evidence from a three-wave cross-lagged panel model
    Zhao H, Song T, Rafik-Galea S, Dong J, Fitriana M, Ji Y, et al.
    Front Public Health, 2023;11:1202741.
    PMID: 37521981 DOI: 10.3389/fpubh.2023.1202741
    BACKGROUND: Previous cross-sectional studies have shown that meaning in life (MIL) is closely associated with college students' smartphone addiction (SA), but the causal relationship between MIL and college students' SA is uncertain. Therefore, conducting a longitudinal study to explore their relationship is very necessary. Furthermore, some studies have implied possible gender differences in the relationship between MIL and SA and the relationship between SA and MIL. Therefore, it is necessary to further examine whether there are gender differences in the above relationships.

    METHODS: The present study constructed a three-wave cross-lag panel model to explore the relationships between MIL and college students' SA. Three waves of data were collected from 705 college students (male: 338; female: 367) in China for three consecutive years, and the interval of data collection was 1 year. These college students completed the same online questionnaire regarding MIL and SA.

    RESULTS: (1) The MIL of male college students was significantly stronger than that of female college students at time 1, time 2, and time 3, (2) Female college students' SA at time 1, time 2, and time 3 was more serious than that of male college students, (3) There were reciprocal relationships between MIL and college students' SA, (4) The influence of MIL on female college students' SA was significantly stronger than that of male college students, and (5) The influence of SA on female college students' MIL was significantly stronger than that of male college students.

    CONCLUSION: This study showed reciprocal relationships between MIL and SA among male college students and female college students. The findings further deepen our understanding of the relationship between MIL and SA and provide a gender perspective for preventing or intervening with college students' SA.

  16. Differential Correlations Informed Metabolite Set Enrichment Analysis to Decipher Metabolic Heterogeneity of Disease
    Lin G, Dong L, Cheng KK, Xu X, Wang Y, Deng L, et al.
    Anal Chem, 2023 Aug 22;95(33):12505-12513.
    PMID: 37557184 DOI: 10.1021/acs.analchem.3c02246
    Metabolic pathways are regarded as functional and basic components of the biological system. In metabolomics, metabolite set enrichment analysis (MSEA) is often used to identify the altered metabolic pathways (metabolite sets) associated with phenotypes of interest (POI), e.g., disease. However, in most studies, MSEA suffers from the limitation of low metabolite coverage. Random walk (RW)-based algorithms can be used to propagate the perturbation of detected metabolites to the undetected metabolites through a metabolite network model prior to MSEA. Nevertheless, most of the existing RW-based algorithms run on a general metabolite network constructed based on public databases, such as KEGG, without taking into consideration the potential influence of POI on the metabolite network, which may reduce the phenotypic specificities of the MSEA results. To solve this problem, a novel pathway analysis strategy, namely, differential correlation-informed MSEA (dci-MSEA), is proposed in this paper. Statistically, differential correlations between metabolites are used to evaluate the influence of POI on the metabolite network, so that a phenotype-specific metabolite network is constructed for RW-based propagation. The experimental results show that dci-MSEA outperforms the conventional RW-based MSEA in identifying the altered metabolic pathways associated with colorectal cancer. In addition, by incorporating the individual-specific metabolite network, the dci-MSEA strategy is easily extended to disease heterogeneity analysis. Here, dci-MSEA was used to decipher the heterogeneity of colorectal cancer. The present results highlight the clustering of colorectal cancer samples with their cluster-specific selection of differential pathways and demonstrate the feasibility of dci-MSEA in heterogeneity analysis. Taken together, the proposed dci-MSEA may provide insights into disease mechanisms and determination of disease heterogeneity.
  17. Spinal Cord Injury: From MicroRNAs to Exosomal MicroRNAs
    Xu X, Liu R, Li Y, Zhang C, Guo C, Zhu J, et al.
    Mol Neurobiol, 2024 Jan 23.
    PMID: 38261255 DOI: 10.1007/s12035-024-03954-7
    Spinal cord injury (SCI) is an unfortunate experience that may generate extensive sensory and motor disabilities due to the destruction and passing of nerve cells. MicroRNAs are small RNA molecules that do not code for proteins but instead serve to regulate protein synthesis by targeting messenger RNA's expression. After SCI, secondary damage like apoptosis, oxidative stress, inflammation, and autophagy occurs, and differentially expressed microRNAs show a function in these procedures. Almost all animal and plant cells release exosomes, which are sophisticated formations of lipid membranes. These exosomes have the capacity to deliver significant materials, such as proteins, RNAs and lipids, to cells in need, regulating their functions and serving as a way of communication. This new method offers a fresh approach to treating spinal cord injury. Obviously, the exosome has the benefit of conveying the transported material across performing regulatory activities and the blood-brain barrier. Among the exosome cargoes, microRNAs, which modulate their mRNA targets, show considerable promise in the pathogenic diagnosis, process, and therapy of SCI. Herein, we describe the roles of microRNAs in SCI. Furthermore, we emphasize the importance of exosomal microRNAs in this disease.
  18. Genetic characteristics of human enterovirus 71 and coxsackievirus A16 circulating from 1999 to 2004 in Shenzhen, People's Republic of China
    Li L, He Y, Yang H, Zhu J, Xu X, Dong J, et al.
    J Clin Microbiol, 2005 Aug;43(8):3835-9.
    PMID: 16081920
    The genetic and phylogenetic characteristics of human enterovirus 71 (EV71) and coxsackievirus A16 (CA16) sampled from children with hand, foot, and mouth disease in Shenzhen, People's Republic of China, over a 6-year period (1999 to 2004) were examined with reverse transcription-PCR and DNA sequencing. Out of 147 stool specimens, 60 showed positive signals when screened with EV71- and CA16-specific primers. EV71 was identified in 19 specimens, and CA16 was identified in 41 specimens; coinfection by EV71 and CA16 was not observed. Phylogenetic analysis of all EV71 strains isolated from the mainland Chinese samples established C4 as the predominant genotype. Only one other known strain (3254-TAI-98; AF286531), isolated in Taiwan in 1998, was identified as belonging to genotype C4. Phylogenetic analysis of CA16 strains allowed us to identify three new genetic lineages (A, B, and C), with lineage C recently predominating in Asian countries, such as the People's Republic of China, Malaysia, and Japan. These new observations indicate that CA16 circulating in the People's Republic of China is genetically diverse, and additional surveillance is warranted.
  19. Fulltext Metabolic Response in Rats following Electroacupuncture or Moxibustion Stimulation
    Xu J, Lin X, Cheng KK, Zhong H, Liu M, Zhang G, et al.
    Evid Based Complement Alternat Med, 2019;2019:6947471.
    PMID: 31186665 DOI: 10.1155/2019/6947471
    Electroacupuncture and moxibustion are traditional Chinese medicine practices that exert therapeutic effects through stimulation of specific meridian acupoints. However, the biological basis of the therapies has been difficult to establish; thus the current practices still rely on ancient TCM references. Here, we used a rat model to study perturbations in cortex, liver, and stomach metabolome and plasma hormones following electroacupuncture or moxibustion treatment on either stomach meridian or gallbladder meridian acupoints. All treatment groups, regardless of meridian and mode of treatment, showed perturbation in cortex metabolome and increased phenylalanine, tyrosine, and branched-chain amino acids in liver. In addition, electroacupuncture was found to increase ATP in cortex, creatine, and dimethylglycine in stomach and GABA in liver. On the other hand, moxibustion increased plasma enkephalin concentration, as well as betaine and fumarate concentrations in stomach. Furthermore, we had observed meridian-specific changes including increased N-acetyl-aspartate in liver and 3-hydroxybutyrate in stomach for gallbladder meridian stimulation and increased noradrenaline concentration in blood plasma following stimulation on stomach meridian. In summary, the current findings may provide insight into the metabolic basis of electroacupuncture and moxibustion, which may contribute towards new application of acupoint stimulation.
  20. Fulltext (1) H NMR Metabolic Profiling of Biofluids from Rats with Gastric Mucosal Lesion and Electroacupuncture Treatment
    Xu J, Cheng KK, Yang Z, Wang C, Shen G, Wang Y, et al.
    Evid Based Complement Alternat Med, 2015;2015:801691.
    PMID: 26170882 DOI: 10.1155/2015/801691
    Gastric mucosal lesion (GML) is a common gastrointestinal disorder with multiple pathogenic mechanisms in clinical practice. In traditional Chinese medicine (TCM), electroacupuncture (EA) treatment has been proven as an effective therapy for GML, although the underlying healing mechanism is not yet clear. Here, we used proton nuclear magnetic resonance- ((1)H NMR-) based metabolomic method to investigate the metabolic perturbation induced by GML and the therapeutic effect of EA treatment on stomach meridian (SM) acupoints. Clear metabolic differences were observed between GML and control groups, and related metabolic pathways were discussed by means of online metabolic network analysis toolbox. By comparing the endogenous metabolites from GML and GML-SM groups, the disturbed pathways were partly recovered towards healthy state via EA treated on SM acupoints. Further comparison of the metabolic variations induced by EA stimulated on SM and the control gallbladder meridian (GM) acupoints showed a quite similar metabolite composition except for increased phenylacetylglycine, 3,4-dihydroxymandelate, and meta-hydroxyphenylacetate and decreased N-methylnicotinamide in urine from rats with EA treated on SM acupoints. The current study showed the potential application of metabolomics in providing further insight into the molecular mechanism of acupuncture.
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