Displaying publications 41 - 60 of 69 in total

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  1. Utilising standard samples instead of randomly collected food waste in composting: Implementation strategy and feasibility evaluation
    Wang J, Li C, Awasthi MK, Nyambura SM, Zhu Z, Li H, et al.
    J Environ Manage, 2024 Feb 27;353:120182.
    PMID: 38278112 DOI: 10.1016/j.jenvman.2024.120182
    Randomly collected food waste results in inaccurate experimental data with poor reproducibility for composting. This study investigated standard food waste samples as replacements for randomly collected food waste. A response surface methodology was utilised to analyse data from a 28-day compost process optimisation experiment using collected food waste, and the optimal combination of composting parameters was derived. Experiments using different standard food waste samples (high oil and salt, high oil and sugar, balanced diet, and vegetarian) were conducted for 28 days under optimal conditions. The ranking of differences between the standard samples and collected food waste was vegetarian > balanced diet > high oil and sugar > high oil and salt. Statistical analysis indicated t-tests for increased oil and salt samples and collected food waste were not significant, and Cohen's d effect values were minimal. High oil and salt samples can be used as replacements for collected food waste in composting experiments.
  2. Medicinal uses, phytochemistry and pharmacology of the genus Uncaria
    Zhang Q, Zhao JJ, Xu J, Feng F, Qu W
    J Ethnopharmacol, 2015 Sep 15;173:48-80.
    PMID: 26091967 DOI: 10.1016/j.jep.2015.06.011
    The genus Uncaria belongs to the family Rubiaceae, which mainly distributed in tropical regions, such as Southeast Asia, Africa and Southeast America. Their leaves and hooks have long been thought to have healing powers and are already being tested as a treatment for asthma, cancer, cirrhosis, diabetes, hypertension, stroke and rheumatism. The present review aims to provide systematically reorganized information on the ethnopharmacology, phytochemistry and pharmacology of the genus Uncaria to support for further therapeutic potential of this genus. To better understanding this genus, information on the stereo-chemistry and structure-activity relationships in indole alkaloids is also represented.
  3. Yishen Tongluo formula alleviates diabetic kidney disease through regulating Sirt6/TGF-β1/Smad2/3 pathway and promoting degradation of TGF-β1
    Zhang X, Zhao L, Xiang S, Sun Y, Wang P, Chen JJ, et al.
    J Ethnopharmacol, 2023 May 10;307:116243.
    PMID: 36791927 DOI: 10.1016/j.jep.2023.116243
    ETHNOPHARMACOLOGICAL RELEVANCE: Yishen Tongluo formula (YSTLF) is formulated based on traditional Chinese medicine theory for the treatment of Diabetic kidney disease (DKD) and has been shown to be effective in improving the symptoms of DKD according to the clinical observation.

    AIM OF THE STUDY: To explore the effect of YSTLF on DKD and figure out whether its effects were due to the regulation Sirt6/TGF-β1/Smad2/3 pathway and promoting degradation of TGF-β1.

    MATERIALS AND METHODS: The extract of YSTLF at 1, 2.5 and 5 g/kg was orally administered to C57BLKS/J (db/db) mice for 8 weeks and db/db mice were given valsartan as a positive control. The littermate db/m and db/db mice were given vehicle as the control and model group, respectively. Blood urea nitrogen and serum creatinine were detected and the urinary albumin excretion, urea albumin creatinine ratio was calculated. The histopathological change of renal tissues in each group was determined. Simultaneously, the levels of fibrosis-related proteins and messenger RNA (mRNA) in kidney and high glucose (HG)-induced SV40-MES-13 cells were detected. The roles of YSTLF in regulating of Sirt6/TGF-β1/Smad2/3 signaling pathway were investigated in HG-stimulated SV40-MES-13 cells and validated in db/db mice. Furthermore, the effect of YSTLF on TGF-β1 degradation was investigated in HG-stimulated SV40-MES-13 cells.

    RESULTS: YSTLF significantly improved the renal function in DKD mice. YSTLF dose-dependently attenuated pathological changes and suppressed the expression of type I collagen, alpha smooth muscle actin, type IV collagen, and fibronectin in vitro and in vivo, resulting in ameliorating of renal fibrosis. YSTLF positively regulated Sirt6 expression, while inhibited the activating of TGF-β1/Smad2/3 signaling pathway. TGF-β1 was steady expressed in HG-stimulated SV40-MES-13 cells, whereas was continuously degraded under YSTLF treatment.

    CONCLUSIONS: YSTLF significantly ameliorates renal damages and fibrosis may via regulating Sirt6/TGF-β1/Smad2/3 signaling pathway as well as promoting the degradation of TGF-β1.

  4. Development and characterization of 33 microsatellite loci for the tiger frog Hoplobatrachus rugulosus (Wiegmann 1834) through transcriptome sequencing
    Chen Z, Ding G, Wang Y, Xu J, Lin Z
    J Genet, 2018 Nov 14;97(5):e147-e151.
    PMID: 30574879
    The tiger frog Hoplobatrachus rugulosus (Wiegmann 1834) is a large robust dicroglossid frog widely distributed in southern China, Malaysia, Myanmar, Vietnam and Thailand. The escaped bred tiger frog introduced from Thailand hybridized with Chinese native population may have affected the genetic diversity of local Chinese tiger frogs. However, previous microsatellite loci of this species do not offer enough information to construct the genetic map. Here, we reported 33 new microsatellite loci from transcriptome sequencing for H. rugulosus. Alleles ranged between 1 and 10 per locus and only one locus (HRT001) was monomorphic. The polymorphic information content, observed and expected heterozygosity were 0-0.794, 0-0.969 and 0-0.831, respectively. None of the loci was observed in linkage disequilibrium and two loci (HRT023 and HRT068) deviated from Hardy-Weinberg equilibrium after Bonferroni correction for multiple tests. These transcriptome-derived microsatellite markers will be usedto study the genetic divergence and construct the genetic map in H. rugulosus.
  5. Fulltext Setting research priorities for global pandemic preparedness: An international consensus and comparison with ChatGPT's output
    Song P, Adeloye D, Acharya Y, Bojude DA, Ali S, Alibudbud R, et al.
    J Glob Health, 2024 Feb 16;14:04054.
    PMID: 38386716 DOI: 10.7189/jogh.14.04054
    BACKGROUND: In this priority-setting exercise, we sought to identify leading research priorities needed for strengthening future pandemic preparedness and response across countries.

    METHODS: The International Society of Global Health (ISoGH) used the Child Health and Nutrition Research Initiative (CHNRI) method to identify research priorities for future pandemic preparedness. Eighty experts in global health, translational and clinical research identified 163 research ideas, of which 42 experts then scored based on five pre-defined criteria. We calculated intermediate criterion-specific scores and overall research priority scores from the mean of individual scores for each research idea. We used a bootstrap (n = 1000) to compute the 95% confidence intervals.

    RESULTS: Key priorities included strengthening health systems, rapid vaccine and treatment production, improving international cooperation, and enhancing surveillance efficiency. Other priorities included learning from the coronavirus disease 2019 (COVID-19) pandemic, managing supply chains, identifying planning gaps, and promoting equitable interventions. We compared this CHNRI-based outcome with the 14 research priorities generated and ranked by ChatGPT, encountering both striking similarities and clear differences.

    CONCLUSIONS: Priority setting processes based on human crowdsourcing - such as the CHNRI method - and the output provided by ChatGPT are both valuable, as they complement and strengthen each other. The priorities identified by ChatGPT were more grounded in theory, while those identified by CHNRI were guided by recent practical experiences. Addressing these priorities, along with improvements in health planning, equitable community-based interventions, and the capacity of primary health care, is vital for better pandemic preparedness and response in many settings.

  6. Phillyrin: an adipose triglyceride lipase inhibitor supported by molecular docking, dynamics simulation, and pharmacological validation
    Zhou C, Yan L, Xu J, Hamezah HS, Wang T, Du F, et al.
    J Mol Model, 2024 Feb 13;30(3):68.
    PMID: 38347278 DOI: 10.1007/s00894-024-05875-7
    CONTEXT: Adipose triglyceride lipase (ATGL), a key enzyme responsible for lipolysis, catalyzes the first step of lipolysis and converts triglycerides to diacylglycerols and free fatty acids (FFA). Our previous work suggested that phillyrin treatment improves insulin resistance in HFD-fed mice, which was associated with ATGL inhibition. In this study, using docking simulation, we explored the binding pose of phillyrin and atglistatin (a mouse ATGL inhibitor) to ATGL in mouse. From the docking results, the interactions with Ser47 and Asp166 were speculated to have caused phillyrin to inhibit ATGL in mice. Further, molecular dynamics simulation of 100 ns and MM-GBSA were conducted for the protein-ligand complex, which indicated that the system was stable and that phillyrin displayed a better affinity to ATGL than did atglistatin throughout the simulation period. Moreover, the results of pharmacological validation were consistent with those of the in silico simulations. In summary, our study illustrates the potential of molecular docking to accurately predict the binding protein produced by AlphaFold and suggests that phillyrin is a potential small molecule that targets and inhibits ATGL enzymatic activity.

    METHODS: The ATGL-predicted protein structure, verified by PROCHECK, was determined using AlphaFold. Molecular docking, molecular dynamics simulation, and prime molecular mechanic-generalized born surface area were performed using LigPrep, Desmond, and prime MM-GBSA modules of Schrödinger software release 2021-2, respectively. For pharmacological validation, immunoblotting was performed to assess ATGL protein expression. The fluorescence intensity and glycerol concentration were quantified to evaluate the efficiency of phillyrin in inhibiting ATGL.

  7. Four new clerodane diterpenoids from Callicarpa pentandra
    Xu J, Harrison LJ, Vittal JJ, Xu YJ, Goh SH
    J Nat Prod, 2000 Aug;63(8):1062-5.
    PMID: 10978198
    Leaf extracts of Callicarpa pentandra provided four new clerodane-type diterpenoids (1-4), of which 1, 2, and 4 have ring-A-contracted structures. Their structures and stereochemistry were established by spectral data interpretation, and for 3 also by single-crystal X-ray diffraction.
  8. 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.
  9. Fulltext Determination of the embedded electronic states at nanoscale interface via surface-sensitive photoemission spectroscopy
    Wang HQ, Xu J, Lin X, Li Y, Kang J, Zheng JC
    Light Sci Appl, 2021 Jul 27;10(1):153.
    PMID: 34315859 DOI: 10.1038/s41377-021-00592-9
    The fabrication of small-scale electronics usually involves the integration of different functional materials. The electronic states at the nanoscale interface plays an important role in the device performance and the exotic interface physics. Photoemission spectroscopy is a powerful technique to probe electronic structures of valence band. However, this is a surface-sensitive technique that is usually considered not suitable for the probing of buried interface states, due to the limitation of electron-mean-free path. This article reviews several approaches that have been used to extend the surface-sensitive techniques to investigate the buried interface states, which include hard X-ray photoemission spectroscopy, resonant soft X-ray angle-resolved photoemission spectroscopy and thickness-dependent photoemission spectroscopy. Especially, a quantitative modeling method is introduced to extract the buried interface states based on the film thickness-dependent photoemission spectra obtained from an integrated experimental system equipped with in-situ growth and photoemission techniques. This quantitative modeling method shall be helpful to further understand the interfacial electronic states between functional materials and determine the interface layers.
  10. Seaweed and climate change: A mapping review
    Segaran TC, Azra MN, Handayani KS, Lananan F, Xu J
    Mar Environ Res, 2023 Nov;192:106216.
    PMID: 37891025 DOI: 10.1016/j.marenvres.2023.106216
    Seaweed has garnered increasing interest due to its capacity to mitigate climate change by curbing carbon emissions from agriculture, as well as its potential to serve as a supplement or alternative for dietary, livestock feed, or fuel source production. Moreover, seaweed is regarded as one of the earliest plant forms to have evolved on Earth. Owing to the extensive body of literature available and the uncertainty surrounding the future trajectory of seaweed research under evolving climate conditions, this review scrutinizes the structure, dynamics, and progression of the literature pertaining to seaweed and climate change. This analysis is grounded in the Web of Science Core Collection database, augmented by CiteSpace software. Furthermore, we discuss the productivity and influence of individual researchers, research organizations, countries, and scientific journals. To date, there have been 8047 articles published globally (after a series of filters and exclusions), with a notable upswing in publication frequency since 2018. The USA, China, and Australia are among the leading countries contributing to this research area. Our findings reveal that current research on seaweed and climate change encompasses 13 distinct research clusters, including "marine heatwave", "temperate estuary", "ocean acidification", and "macroalgal bloom". The most frequently cited keywords are "climate change", "biomass", "community", and "photosynthesis". The seaweed species most commonly referenced in relation to climate change include Gracilaria sp., Sargassum sp., Ecklonia maxima, and Macrocystis pyrifera. These results provide valuable guidance for shaping the direction of specialized topics concerning marine biodiversity under shifting climate conditions. We propose that seaweed production may be compromised during prolonged episodes of reduced water availability, emphasizing the need to formulate strategies to guarantee its continued viability. This article offers fresh perspectives on the analysis of seaweed research in the context of impending climate change.
  11. Assessment of heavy metal pollution in surficial sediments from a tropical river-estuary-shelf system: A case study of Kelantan River, Malaysia
    Wang AJ, Bong CW, Xu YH, Hassan MHA, Ye X, Bakar AFA, et al.
    Mar Pollut Bull, 2017 Dec 15;125(1-2):492-500.
    PMID: 28807422 DOI: 10.1016/j.marpolbul.2017.08.010
    To understand the source-to-sink of pollutants in the Kelantan River estuary and the adjacent shelf area in Malaysia, a total of 42 surface sediment samples were collected in the Kelantan River-estuary-shelf system to analyze for grain size, total organic carbon (TOC) content, Al and heavy metals (Cr, Ni, Cu, Zn, Cd and Pb). The surficial sediments were mainly composed of clayey silt and the TOC content in sediments decreased from the river to the shelf. The surficial sediments experienced Pb pollution; Cr only showed a certain level of pollution in the coastal area of the estuary but not in other areas, and Ni, Cu, Zn, and Cd showed no pollution. The heavy metals mainly originated from natural weathering and erosion of rocks and soils in the catchment and enriched near the river mouth. Total organic carbon can promote the enrichment of heavy metals in sediments.
  12. 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.
  13. Fulltext Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants
    Dadaev T, Saunders EJ, Newcombe PJ, Anokian E, Leongamornlert DA, Brook MN, et al.
    Nat Commun, 2018 06 11;9(1):2256.
    PMID: 29892050 DOI: 10.1038/s41467-018-04109-8
    Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
  14. Fulltext Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci
    Schumacher FR, Al Olama AA, Berndt SI, Benlloch S, Ahmed M, Saunders EJ, et al.
    Nat Genet, 2018 07;50(7):928-936.
    PMID: 29892016 DOI: 10.1038/s41588-018-0142-8
    Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.
  15. Author Correction: Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci
    Schumacher FR, Olama AAA, Berndt SI, Benlloch S, Ahmed M, Saunders EJ, et al.
    Nat Genet, 2019 02;51(2):363.
    PMID: 30622367 DOI: 10.1038/s41588-018-0330-6
    In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.
  16. Publisher Correction: Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
    Conti DV, Darst BF, Moss LC, Saunders EJ, Sheng X, Chou A, et al.
    Nat Genet, 2021 Mar;53(3):413.
    PMID: 33473200 DOI: 10.1038/s41588-021-00786-2
  17. Fulltext Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
    Conti DV, Darst BF, Moss LC, Saunders EJ, Sheng X, Chou A, et al.
    Nat Genet, 2021 Jan;53(1):65-75.
    PMID: 33398198 DOI: 10.1038/s41588-020-00748-0
    Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.
  18. Fulltext Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants
    Wang A, Shen J, Rodriguez AA, Saunders EJ, Chen F, Janivara R, et al.
    Nat Genet, 2023 Dec;55(12):2065-2074.
    PMID: 37945903 DOI: 10.1038/s41588-023-01534-4
    The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
  19. Surface Modification of lactose carrier particles using a fluid bed coater to improve fine particle fraction for dry powder inhalers
    Gong QQ, Tay JYS, Veronica N, Xu J, Heng PWS, Zhang YP, et al.
    Pharm Dev Technol, 2023 Feb;28(2):164-175.
    PMID: 36683577 DOI: 10.1080/10837450.2023.2171434
    Surface roughness of carrier particles can impact dry powder inhaler (DPI) performance. There are opposing views on the effect of roughness on DPI performance. Hence, a systematic approach is needed to modify carrier surfaces and evaluate the impact on drug delivery. Carrier particle surfaces were modified by fluid bed coating with saturated lactose containing micronized lactose of different sizes (2, 5 and 8 μm) and coated to different levels (20, 40, 60 and 80%). Their drug delivery performance was assessed by the fine particle fraction (FPF). Roughness parameters, mean arithmetic roughness (Ra) and arithmetic mean height (Sa), of the carrier particles, were also evaluated using optical profilometry and scanning laser microscopy. Generally, particles of higher Ra had higher FPF. Higher Sa resulted in higher FPF only for particles with 60 and 80% coat levels. Reduced contact surface area between the drug particle and rougher carrier particle resulted in easier drug detachment during aerosolization. The 5 µm micronized lactose produced optimal carrier particles with respect to FPF and surface roughness. The study highlighted that with the ideal particles for surface roughening and coating level, surface roughening could be efficiently achieved by fluid bed coating for superior DPI performance.
  20. Preventive mechanisms of Chinese Tibetan medicine Triphala against nonalcoholic fatty liver disease
    Jiang Y, Zhao L, Ma J, Yang Y, Zhang B, Xu J, et al.
    Phytomedicine, 2024 Jan;123:155229.
    PMID: 38006804 DOI: 10.1016/j.phymed.2023.155229
    BACKGROUND: Triphala (TLP), as a Chinese Tibetan medicine composing of Emblica officinalis, Terminalia chebula and Terminalia bellirica (1.2:1.5:1), exhibited hepatoprotective, hypolipidemic and gut microbiota modulatory effects. Nonetheless, its roles in prevention of high-fat diet (HFD)-induced nonalcoholic fatty liver disease (NAFLD) and the related mechanistic insights involving the interplay of gut microbiota and hepatic inflammation are not known.

    PURPOSE: The present study seeks to determine if TLP would prevent HFD-induced NAFLD in vivo and its underlying mechanisms from the perspectives of gut microbiota, metabolites, and hepatic inflammation.

    METHODS: TLP was subjected to extraction and chemo-profiling, and in vivo evaluation in HFD-fed rats on hepatic lipid and inflammation, intestinal microbiota, short-chain fatty acids (SCFAs) and permeability, and body weight and fat content profiles.

    RESULTS: The TLP was primarily constituted of gallic acid, corilagin and chebulagic acid. Orally administered HFD-fed rats with TLP were characterized by the growth of Ligilactobacillus and Akkermansia, and SCFAs (acetic/propionic/butyric acid) secretion which led to increased claudin-1 and zonula occludens-1 expression that reduced the mucosal permeability to migration of lipopolysaccharides (LPS) into blood and liver. Coupling with hepatic cholesterol and triglyceride lowering actions, the TLP mitigated both inflammatory (ALT, AST, IL-1β, IL-6 and TNF-α) and pro-inflammatory (TLR4, MYD88 and NF-κB P65) activities of liver, and sequel to histopathological development of NAFLD in a dose-dependent fashion.

    CONCLUSION: TLP is promisingly an effective therapy to prevent NAFLD through modulating gut microbiota, mucosal permeability and SCFAs secretion with liver fat and inflammatory responses.

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