索引超出了数组界限。
[1] 程晓光, 袁慧书, 程敬亮, 等. 骨质疏松的影像学与骨密度诊断专家共识[J]. 中华骨科杂志, 2020, 40(6): 1039-1046.
[2] 程晓光, 王亮, 曾强, 等. 中国定量CT(QCT)骨质疏松症诊断指南(2018)[J]. 中国骨质疏松杂志, 2019, 25(6): 733-737.
[3] 程晓光, 董剩勇, 王亮, 等. 应用双能X线骨密度仪调查中国人群骨密度水平和骨质疏松症患病率—多中心大样本体检人群调查[J]. 中华健康管理学杂志, 2019, 13(1): 51-58.
[4] 李彦东, 吴琪. 代谢组学技术在临床诊断中的研究进展[J]. 天津医药, 2015, 43(8): 942-945.
[5] 唐惠儒, 王玉兰. 代谢组学:一个迅速发展的新兴学科[J]. 生物化学与生物物理进展, 2006, 33(5): 401-417.
[6] Zhang A, Sun H, Wang X. Serum metabolomics as a novel diagnostic approach for disease: a systematic review[J]. Anal Bioanal Chem, 2012, 404(4): 1239-1245.
[7] Jang C, Li C, Rabinowitz JD. Metabolomics and isotope tracing[J]. Cell, 2018, 173(4): 822-837.
[8] James EM, Parkinson EK. Serum metabolomics in animal models and human disease[J]. Curr Opin Clin Nutr, 2015, 18(5): 478-483.
[9] Oresic M. Metabolomics, a novel tool for studies of nutrition, metabolism and lipid dysfunction[J]. Nutr Metab Cardiovasc Dis, 2009, 19(11): 816-824.
[10] 孙志坚, 邱贵兴, 赵宇. 代谢组学在骨科领域的应用及研究进展[J]. 中华外科杂志, 2015, 53(6): 476-480.
[11] Gong AGW, Duan R, Wang HY, et al. Calycosin orchestrates osteogenesis of danggui buxue tang in cultured osteoblasts: evaluating the mechanism of action by omics and chemical knock-out methodologies[J]. Front Pharmacol, 2018, 9: 36.
[12] 黄月, 武晓, 薄云海, 等. 基于RP-UPLC-MS和HILIC-UPLC-MS的骨疏丹对糖皮质激素性骨质疏松模型大鼠干预作用的尿液代谢组学研究[J]. 中国药学杂志, 2016, 51(23): 2045-2052.
[13] Wu X, Huang Y, Sun J, et al. A HILIC-UHPLC–MS/MS untargeted urinary metabonomics combined with quantitative analysis of five polar biomarkers on osteoporosis rats after oral administration of Gushudan[J]. J Chromatogr B Analyt Technol Biomed Life Sci, 2018, 1072: 40-49.
[14] Yuan X, Wen J, Jia H, et al. Integrated metabolomic analysis for intervention effects of Gushudan on glucocorticoid-induced osteoporostic rat plasma based on RP/HILIC-UHPLC-Q-Orbitrap HRMS[J]. Anal Biochem, 2020, 591: 113559.
[15] Huang Y, Bo Y, Wu X, et al. An intergated serum and urinary metabonomic research based on UPLC-MS and therapeutic effects of Gushudan on prednisolone-induced osteoporosis rats[J]. J Chromatogr B Analyt Technol Biomed Life Sci, 2016, 1027: 119-130.
[16] Xue L, Jiang Y, Han T, et al. Comparative proteomic and metabolomic analysis reveal the antiosteoporotic molecular mechanism of icariin from Epimedium brevicornu maxim[J]. J Ethnopharmacol, 2016, 192: 370-381.
[17] Zhao J, Xu J, Xu Y, et al. High-throughput metabolomics method for discovering metabolic biomarkers and pathways to reveal effects and molecular mechanism of ethanol extract from Epimedium against osteoporosis[J]. Front Pharmacol, 2020, 11: 1318.
[18] Pan S, Chen A, Han Z, et al. 1H NMR-based metabonomic study on the effects of Epimedium on glucocorticoid-induced osteoporosis[J]. J Chromatogr B Analyt Technol Biomed Life Sci, 2016, 1038: 118-126.
[19] Jiang Y, Li Y, Zhou L, et al. UPLC-MS metabolomics method provides valuable insights into the effect and underlying mechanisms of Rhizoma Drynariae protecting osteoporosis[J]. J Chromatogr B Analyt Technol Biomed Life Sci, 2020, 1152: 122262.
[20] 王方杰, 王婷, 罗芳梅, 等. 基于GC-MS代谢组学技术的杜仲抗骨质疏松作用研究[J]. 中国中药杂志, 2020, 45(22): 5555-5560.
[21] 盛玲玲, 李先娜, 霍金海, 等. 基于尿液代谢组学研究豆豉抗骨质疏松作用机制[J]. 中国药理学通报, 2020, 36(2): 182-190.
[22] Ye M, Zhang C, Jia W, et al. Metabolomics strategy reveals the osteogenic mechanism of yak(Bos grunniens)bone collagen peptides on ovariectomy-induced osteoporosis in rats[J]. Food Funct, 2020, 11(2): 1498-1512.
[23] Zhang M, Wang Y, Zhang Q, et al. UPLC/Q-TOF-MS-based metabolomics study of the anti-osteoporosis effects of Achyranthes bidentata polysaccharides in ovariectomized rats[J]. Int J Biol Macromol, 2018, 112: 433-441.
[24] Xia T, Dong X, Jiang Y, et al. Metabolomics profiling reveals Rehmanniae radix preparata extract protects against glucocorticoid-induced osteoporosis mainly via intervening steroid hormone biosynthesis[J]. Molecules, 2019, 24(2): 253
[25] Xia T, Dong X, Lin L, et al. Metabolomics profiling provides valuable insights into the underlying mechanisms of Morinda officinalis on protecting glucocorticoid-induced osteoporosis[J]. J Pharmaceut Biomed, 2019, 166: 336-346.
[26] Luo D, Li J, Chen K, et al. Untargeted metabolomics reveals the protective effect of Fufang Zhenshu Tiaozhi(FTZ)on aging-induced osteoporosis in mice[J]. Front Pharmacol, 2019, 9: 1483.
[27] Zhang A, Ma Z, Sun H, et al. High-throughput metabolomics evaluate the efficacy of total lignans from Acanthophanax senticosus stem against ovariectomized osteoporosis rat[J]. Front Pharmacol, 2019, 10: 553.
[28] Xu Y, Chen S, Yu T, et al. High-throughput metabolomics investigates anti-osteoporosis activity of oleanolic acid via regulating metabolic networks using ultra-performance liquid chromatography coupled with mass spectrometry[J]. Phytomedicine, 2018, 51: 68-76.
[29] Si Z, Zhou S, Shen Z, et al. High-throughput metabolomics discovers metabolic biomarkers and pathways to evaluating the efficacy and exploring potential mechanisms of osthole against osteoporosis based on UPLC/Q-TOF-MS coupled with multivariate data analysis[J]. Front Pharmacol, 2020, 11: 741.
[30] Zhao H, Li X, Zhang D, et al. Integrative bone metabolomics-lipidomics strategy for pathological mechanism of postmenopausal osteoporosis mouse model[J]. Sci Rep, 2018, 8(1): 16456.
[31] Cabrera D, Kruger M, Wolber FM, et al. Association of plasma lipids and polar metabolites with low bone mineral density in Singaporean-Chinese menopausal women: a pilot study[J]. Int J Env Res Public Health, 2018, 15(5): 1045
[32] Pontes TA, Barbosa AD, Silva RD, et al. Osteopenia-osteoporosis discrimination in postmenopausal women by 1H NMR-based metabonomics[J]. PLoS One,2019, 14(5): e0217348.
[33] Miyamoto T, Hirayama A, Sato Y, et al. A serum metabolomics-based profile in low bone mineral density postmenopausal women[J]. Bone, 2017, 95: 1-4.
[34] Miyamoto T, Hirayama A, Sato Y, et al. Metabolomics-based profiles predictive of low bone mass in menopausal women[J]. Bone Rep, 2018, 9: 11-18.
[35] Qi H, Bao J, An G, et al. Association between the metabolome and bone mineral density in pre- and post-menopausal Chinese women using GC-MS[J]. Mol Biosyst, 2016, 12(7): 2265-2275.
[36] Wang J, Yan D, Zhao A, et al. Discovery of potential biomarkers for osteoporosis using LC-MS/MS metabolomic methods[J]. Osteoporosis Int, 2019, 30(7): 1491-1499.