{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T00:08:27Z","timestamp":1791590907322,"version":"4.3.4"},"reference-count":66,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T00:00:00Z","timestamp":1772668800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T00:00:00Z","timestamp":1776038400000},"content-version":"vor","delay-in-days":39,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100004829","name":"Science and Technology Department of Sichuan Province","doi-asserted-by":"publisher","award":["2024YFHZ0043"],"award-info":[{"award-number":["2024YFHZ0043"]}],"id":[{"id":"10.13039\/501100004829","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004829","name":"Science and Technology Department of Sichuan Province","doi-asserted-by":"publisher","award":["2024YFFK0184"],"award-info":[{"award-number":["2024YFFK0184"]}],"id":[{"id":"10.13039\/501100004829","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004829","name":"Science and Technology Department of Sichuan Province","doi-asserted-by":"publisher","award":["2024NSFSC0563"],"award-info":[{"award-number":["2024NSFSC0563"]}],"id":[{"id":"10.13039\/501100004829","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100016107","name":"Science and Technology Department of Tibet Autonomous Region","doi-asserted-by":"publisher","award":["XZ202301ZY0049G"],"award-info":[{"award-number":["XZ202301ZY0049G"]}],"id":[{"id":"10.13039\/501100016107","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Project of Institute of Health New Productivity","award":["HN240302C"],"award-info":[{"award-number":["HN240302C"]}]},{"name":"the Discipline Revitalization Project of Public Health Laboratory Sciences","award":["2023SY-04"],"award-info":[{"award-number":["2023SY-04"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Microbiol"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Osteoporosis and bone loss (OP&amp;BL) are major public health challenges, especially in high-altitude environments with chronic hypoxia. Current diagnostic methods, based on low-altitude populations, are impractical for large-scale screening in resource-limited, high-altitude settings. This study developed a machine learning-based predictive model for OP&amp;BL by integrating oral microbiota data with clinical and questionnaire variables.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed data from 560 Tibetan adults residing at high altitudes. Bone health status (OP&amp;BL vs. normal) was determined by dual-energy X-ray absorptiometry. Oral microbiota profiles were characterized via 16\u00a0S rRNA sequencing. After feature selection using elastic net regression, five machine learning models, namely Logistic Regression (LR), Na\u00efve Bayes (NB), Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGB), were trained (60%, 337\/560) and validated (40%, 223\/560).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Feature selection identified nine predictors: Age, Gender, BMI, oral microbial genera\n                      <jats:italic>Abiotrophia<\/jats:italic>\n                      , Frequency of spicy food consumption (H23), Tooth brushing frequency (J5), Frequency of sweet-drink consumption (J3b), Current marital status (Separated\/Divorced, A5_3), and frequency of numbing food consumption (H27). The LR model demonstrated good and stable performance with an AUC of 0.885 (95% CI: 0.823\u20130.937) on the test set, along with good calibration and the highest net clinical benefit. SHAP analysis indicated that oral factors\n                      <jats:italic>Abiotrophia<\/jats:italic>\n                      and Tooth brushing frequency together accounted for nearly 10% of the model\u2019s total predictive contribution.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We developed a machine learning model integrating oral microbiota and clinical data for predicting OP&amp;BL in people living above 3500\u00a0m. This model could offer a promising non-invasive tool for early screening in resource-limited settings and highlights the potential role of oral factors in high-altitude bone health.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12866-026-04718-0","type":"journal-article","created":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T09:19:01Z","timestamp":1772702341000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Machine learning model integrating oral microbiota and clinical features for predicting osteoporosis and bone loss in high-altitude populations"],"prefix":"10.1186","volume":"26","author":[{"given":"Jian","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fen","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sifan","family":"Hao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changchao","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunru","family":"Tian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihang","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shujuan","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiong","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianli","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8311-7006","authenticated-orcid":false,"given":"Haojiang","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaofang","family":"Pei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xing","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,5]]},"reference":[{"key":"4718_CR1","doi-asserted-by":"publisher","DOI":"10.1177\/1759720X221083541","volume":"14","author":"G Adami","year":"2022","unstructured":"Adami G, Fassio A, Gatti D, Viapiana O, Benini C, Danila MI, et al. Osteoporosis in 10 years time: a glimpse into the future of osteoporosis. Ther Adv Musculoskelet Dis. 2022;14:1759720X221083541. https:\/\/doi.org\/10.1177\/1759720X221083541.","journal-title":"Ther Adv Musculoskelet Dis"},{"issue":"1","key":"4718_CR2","doi-asserted-by":"publisher","DOI":"10.1038\/s41413-025-00432-1","volume":"13","author":"XQ Zheng","year":"2025","unstructured":"Zheng XQ, Guan ZY, Zhang YD, Song CL. Different role of the gut microbiota in postmenopausal and senile osteoporosis. Bone Res. 2025;13(1):63. https:\/\/doi.org\/10.1038\/s41413-025-00432-1.","journal-title":"Bone Res"},{"key":"4718_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.arr.2023.102130","volume":"93","author":"C Ruggiero","year":"2024","unstructured":"Ruggiero C, Baroni M, Xenos D, Parretti L, Macchione IG, Bubba V, et al. Dementia, osteoporosis and fragility fractures: intricate epidemiological relationships, plausible biological connections, and twisted clinical practices. Ageing Res Rev. 2024;93:102130. https:\/\/doi.org\/10.1016\/j.arr.2023.102130.","journal-title":"Ageing Res Rev"},{"issue":"7","key":"4718_CR4","doi-asserted-by":"publisher","DOI":"10.1096\/fj.202302368R","volume":"38","author":"Q Li","year":"2024","unstructured":"Li Q, Yang Z, Zhu M, Zhang W, Chen L, Chen H, et al. Hypobaric hypoxia aggravates osteoarthritis via the alteration of the oxygen environment and bone remodeling in the subchondral zone. FASEB J. 2024;38(7):e23594. https:\/\/doi.org\/10.1096\/fj.202302368R.","journal-title":"FASEB J"},{"issue":"8","key":"4718_CR5","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2024-087142","volume":"14","author":"F Zhang","year":"2024","unstructured":"Zhang F, Chen Y, Wang S, Shi Z, Zhong Y, Zhu S, et al. Impact of altitude on the development of low bone mineral density and osteoporosis in individuals aged 50 years and older: protocol for a multicentre prospective cohort study. BMJ Open. 2024;14(8):e087142. https:\/\/doi.org\/10.1136\/bmjopen-2024-087142.","journal-title":"BMJ Open"},{"key":"4718_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.bone.2021.116258","volume":"154","author":"MB Brent","year":"2022","unstructured":"Brent MB. A review of the skeletal effects of exposure to high altitude and potential mechanisms for hypobaric hypoxia-induced bone loss. Bone. 2022;154:116258. https:\/\/doi.org\/10.1016\/j.bone.2021.116258.","journal-title":"Bone"},{"issue":"Pt 2","key":"4718_CR7","doi-asserted-by":"publisher","first-page":"114206","DOI":"10.1016\/j.envres.2022.114206","volume":"215","author":"H Zuo","year":"2022","unstructured":"Zuo H, Zheng T, Wu K, Yang T, Wang L, Nima Q, et al. High-altitude exposure decreases bone mineral density and its relationship with gut microbiota: results from the China multi-ethnic cohort (CMEC) study. Environ Res. 2022;215(Pt 2):114206. https:\/\/doi.org\/10.1016\/j.envres.2022.114206.","journal-title":"Environ Res"},{"issue":"1","key":"4718_CR8","doi-asserted-by":"publisher","DOI":"10.1186\/s12903-025-07059-y","volume":"25","author":"Y Xiang","year":"2025","unstructured":"Xiang Y, Wang G, Cheng Y, Zhang Y, Zhao J, Dong B, et al. Oral-sarcopenia nexus in health disparities: chewing and blood mediated pathways in a Chinese aging cohort. BMC Oral Health. 2025;25(1):1710. https:\/\/doi.org\/10.1186\/s12903-025-07059-y.","journal-title":"BMC Oral Health"},{"key":"4718_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.tmaid.2023.102660","volume":"56","author":"T Dorji","year":"2023","unstructured":"Dorji T, Giri S, Tshering U, LeVine S, Tshering U, Chhetri S, et al. Challenges in the management of high-altitude illnesses and emergencies in Bhutan and Nepal. Travel Med Infect Dis. 2023;56:102660. https:\/\/doi.org\/10.1016\/j.tmaid.2023.102660.","journal-title":"Travel Med Infect Dis"},{"key":"4718_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.eclinm.2025.103244","volume":"83","author":"J Yang","year":"2025","unstructured":"Yang J, Zeng Y, Yu W. Criteria for osteoporosis diagnosis: a systematic review and meta-analysis of osteoporosis diagnostic studies with DXA and QCT. EClinicalMedicine. 2025;83:103244. https:\/\/doi.org\/10.1016\/j.eclinm.2025.103244.","journal-title":"EClinicalMedicine"},{"issue":"5","key":"4718_CR11","doi-asserted-by":"publisher","first-page":"e0134724","DOI":"10.1128\/msystems.01347-24","volume":"10","author":"Q Zhao","year":"2025","unstructured":"Zhao Q, Hao D, Wang S, Chen S, Zhou C, Fan C, et al. Exposure to high altitude leads to disturbances in host metabolic homeostasis: study of the effects of hypoxia-reoxygenation and the associations between the Microbiome and metabolome. mSystems. 2025;10(5):e0134724. https:\/\/doi.org\/10.1128\/msystems.01347-24.","journal-title":"mSystems"},{"issue":"1","key":"4718_CR12","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-023-30963-8","volume":"13","author":"M Kumari","year":"2023","unstructured":"Kumari M, Bhushan B, Eslavath MR, Srivastava AK, Meena RC, Varshney R, et al. Impact of high altitude on composition and functional profiling of oral microbiome in Indian male population. Sci Rep. 2023;13(1):4038. https:\/\/doi.org\/10.1038\/s41598-023-30963-8.","journal-title":"Sci Rep"},{"key":"4718_CR13","doi-asserted-by":"publisher","DOI":"10.34133\/hds.0165","volume":"4","author":"M Zhang","year":"2024","unstructured":"Zhang M, Zheng Y, Maidaiti X, Liang B, Wei Y, Sun F. Integrating machine learning into statistical methods in disease risk prediction modeling: a systematic review. Health Data Sci. 2024;4:0165. https:\/\/doi.org\/10.34133\/hds.0165.","journal-title":"Health Data Sci"},{"issue":"1","key":"4718_CR14","doi-asserted-by":"publisher","DOI":"10.1186\/s12967-025-06308-6","volume":"23","author":"L Abualigah","year":"2025","unstructured":"Abualigah L, Alomari SA, Almomani MH, Zitar RA, Saleem K, Migdady H, et al. Artificial intelligence-driven translational medicine: a machine learning framework for predicting disease outcomes and optimizing patient-centric care. J Transl Med. 2025;23(1):302. https:\/\/doi.org\/10.1186\/s12967-025-06308-6.","journal-title":"J Transl Med"},{"key":"4718_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.bonr.2025.101826","volume":"24","author":"WC Huang","year":"2025","unstructured":"Huang WC, Chen IS, Yu HC, Chen CS, Wu FZ, Hsu CL, et al. A simple and user-friendly machine learning model to detect osteoporosis in health examination populations in Southern Taiwan. Bone Rep. 2025;24:101826. https:\/\/doi.org\/10.1016\/j.bonr.2025.101826.","journal-title":"Bone Rep"},{"issue":"1","key":"4718_CR16","doi-asserted-by":"publisher","DOI":"10.1186\/s12905-025-03669-4","volume":"25","author":"M Je","year":"2025","unstructured":"Je M, Hwang S, Lee S, Kim Y. Development and evaluation of a machine learning model for osteoporosis risk prediction in Korean women. BMC Womens Health. 2025;25(1):146. https:\/\/doi.org\/10.1186\/s12905-025-03669-4.","journal-title":"BMC Womens Health"},{"issue":"12","key":"4718_CR17","doi-asserted-by":"publisher","first-page":"e5097","DOI":"10.1210\/clinem\/dgab462","volume":"106","author":"J Wu","year":"2021","unstructured":"Wu J, Guo B, Guan H, Mi F, Xu J, Basang, et al. The association between Long-term exposure to ambient air pollution and bone strength in China. J Clin Endocrinol Metab. 2021;106(12):e5097\u2013108. https:\/\/doi.org\/10.1210\/clinem\/dgab462.","journal-title":"J Clin Endocrinol Metab"},{"issue":"3","key":"4718_CR18","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1093\/ije\/dyaa185","volume":"50","author":"X Zhao","year":"2021","unstructured":"Zhao X, Hong F, Yin J, Tang W, Zhang G, Liang X, et al. Cohort Profile: the China Multi-Ethnic Cohort (CMEC) study. Int J Epidemiol. 2021;50(3):721. https:\/\/doi.org\/10.1093\/ije\/dyaa185.","journal-title":"Int J Epidemiol"},{"issue":"1","key":"4718_CR19","doi-asserted-by":"publisher","DOI":"10.1186\/s12889-023-15224-7","volume":"23","author":"J Chen","year":"2023","unstructured":"Chen J, Zuo H, Wu X, Zhang Y, Tan Q, Yu Z, et al. Diverse associations between adiposity and blood pressure among 80,000 multi-ethnic Chinese adults. BMC Public Health. 2023;23(1):298. https:\/\/doi.org\/10.1186\/s12889-023-15224-7.","journal-title":"BMC Public Health"},{"key":"4718_CR20","doi-asserted-by":"publisher","DOI":"10.3389\/fcimb.2020.514943","volume":"10","author":"HJ Zuo","year":"2020","unstructured":"Zuo HJ, Fu MR, Zhao HL, Du XW, Hu ZY, Zhao XY, et al. Study on the Salivary Microbial Alteration of Men With Head and Neck Cancer and Its Relationship With Symptoms in Southwest China. Front Cell Infect Microbiol. 2020;10:514943. https:\/\/doi.org\/10.3389\/fcimb.2020.514943.","journal-title":"Front Cell Infect Microbiol"},{"issue":"1","key":"4718_CR21","doi-asserted-by":"publisher","DOI":"10.1186\/s12885-022-10329-5","volume":"22","author":"A Wei","year":"2022","unstructured":"Wei A, Zhao H, Cong X, Wang L, Chen Y, Gou J, et al. Oral mycobiota and pancreatic ductal adenocarcinoma. BMC Cancer. 2022;22(1):1251. https:\/\/doi.org\/10.1186\/s12885-022-10329-5.","journal-title":"BMC Cancer"},{"key":"4718_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.envint.2022.107216","volume":"163","author":"K Wu","year":"2022","unstructured":"Wu K, Guo B, Guo Y, Han M, Xu H, Luo R, et al. Association between residential greenness and gut microbiota in chinese adults. Environ Int. 2022;163:107216. https:\/\/doi.org\/10.1016\/j.envint.2022.107216.","journal-title":"Environ Int"},{"key":"4718_CR23","doi-asserted-by":"publisher","DOI":"10.1186\/s12885-025-14986-0","volume":"25","author":"J Gou","year":"2025","unstructured":"Gou J, Hu Z, Cai M, Zhang S, Zhou S, Feng X, et al. Microbial biomarkers and sex-associated gut microbiota characteristics of thyroid cancer. BMC Cancer. 2025;25:1688. https:\/\/doi.org\/10.1186\/s12885-025-14986-0.","journal-title":"BMC Cancer"},{"issue":"1","key":"4718_CR24","doi-asserted-by":"publisher","DOI":"10.1186\/s12995-023-00377-3","volume":"18","author":"L Xie","year":"2023","unstructured":"Xie L, Zhang X, Gao X, Wang L, Cheng Y, Zhang S, et al. Microbiota and mycobiota in bronchoalveolar lavage fluid of silicosis patients. J Occup Med Toxicol. 2023;18(1):10. https:\/\/doi.org\/10.1186\/s12995-023-00377-3.","journal-title":"J Occup Med Toxicol"},{"key":"4718_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2023.163577","volume":"884","author":"S Li","year":"2023","unstructured":"Li S, Guo B, Dong K, Huang S, Wu J, Zhou H, et al. Association of long-term exposure to ambient PM2.5 and its constituents with gut microbiota: evidence from a China cohort. Sci Total Environ. 2023;884:163577. https:\/\/doi.org\/10.1016\/j.scitotenv.2023.163577.","journal-title":"Sci Total Environ"},{"issue":"2","key":"4718_CR26","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1620\/tjem.254.129","volume":"254","author":"K Dong","year":"2021","unstructured":"Dong K, Wu K, Zheng T, Yue J, Wang W, Luo R, et al. Comparative study of oral bacteria and fungi microbiota in Tibetan and Chinese Han living at different altitude. Tohoku J Exp Med. 2021;254(2):129\u201339. https:\/\/doi.org\/10.1620\/tjem.254.129.","journal-title":"Tohoku J Exp Med"},{"key":"4718_CR27","doi-asserted-by":"publisher","DOI":"10.3389\/fmicb.2024.1345045","volume":"15","author":"L Zhou","year":"2024","unstructured":"Zhou L, Ye Q, Zhou Q, Wang J, Li G, Xiang J, et al. Antimicrobial resistance and genomic investigation of Salmonella isolated from retail foods in Guizhou, China. Front Microbiol. 2024;15:1345045. https:\/\/doi.org\/10.3389\/fmicb.2024.1345045.","journal-title":"Front Microbiol"},{"issue":"1","key":"4718_CR28","doi-asserted-by":"publisher","DOI":"10.1111\/jfs.13015","volume":"43","author":"X Kong","year":"2022","unstructured":"Kong X, Chen J, Yang Y, Li M, Wang J, Jia Q, et al. Phenotypic and genotypic characterization of Salmonella Enteritidis isolated from two consecutive food-poisoning outbreaks in Sichuan, China. J Food Saf. 2022;43(1):e13015. https:\/\/doi.org\/10.1111\/jfs.13015.","journal-title":"J Food Saf"},{"issue":"1","key":"4718_CR29","doi-asserted-by":"publisher","DOI":"10.1186\/s12866-023-02947-1","volume":"23","author":"K Dong","year":"2023","unstructured":"Dong K, Li W, Xu Q, Hong Z, Zhang S, Zhang B, et al. Exploring the correlation of metabolites changes and microbial succession in solid-state fermentation of Sichuan sun-dried vinegar. BMC Microbiol. 2023;23(1):197. https:\/\/doi.org\/10.1186\/s12866-023-02947-1.","journal-title":"BMC Microbiol"},{"issue":"1","key":"4718_CR30","doi-asserted-by":"publisher","DOI":"10.1186\/s12866-020-01795-7","volume":"20","author":"S Claassen-Weitz","year":"2020","unstructured":"Claassen-Weitz S, Gardner-Lubbe S, Mwaikono KS, du Toit E, Zar HJ, Nicol MP. Optimizing 16S rRNA gene profile analysis from low biomass nasopharyngeal and induced sputum specimens. BMC Microbiol. 2020;20(1):113. https:\/\/doi.org\/10.1186\/s12866-020-01795-7.","journal-title":"BMC Microbiol"},{"issue":"11","key":"4718_CR31","doi-asserted-by":"publisher","first-page":"1490","DOI":"10.1017\/S0007114524002733","volume":"132","author":"H Zhang","year":"2024","unstructured":"Zhang H, Zuo H, Xiang Y, Cai J, Zhang N, Yang F, et al. Associations of various healthy dietary patterns with biological age acceleration and the mediating role of gut microbiota: results from the China multi-ethnic cohort study. Br J Nutr. 2024;132(11):1490\u2013502. https:\/\/doi.org\/10.1017\/S0007114524002733.","journal-title":"Br J Nutr"},{"issue":"17","key":"4718_CR32","doi-asserted-by":"publisher","first-page":"i884","DOI":"10.1093\/bioinformatics\/bty560","volume":"34","author":"S Chen","year":"2018","unstructured":"Chen S, Zhou Y, Chen Y, Gu J. Fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34(17):i884\u201390. https:\/\/doi.org\/10.1093\/bioinformatics\/bty560.","journal-title":"Bioinformatics"},{"issue":"21","key":"4718_CR33","doi-asserted-by":"publisher","first-page":"2957","DOI":"10.1093\/bioinformatics\/btr507","volume":"27","author":"T Magoc","year":"2011","unstructured":"Magoc T, Salzberg SL. Flash: fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011;27(21):2957\u201363. https:\/\/doi.org\/10.1093\/bioinformatics\/btr507.","journal-title":"Bioinformatics"},{"issue":"7","key":"4718_CR34","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1038\/nmeth.3869","volume":"13","author":"BJ Callahan","year":"2016","unstructured":"Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13(7):581. https:\/\/doi.org\/10.1038\/nmeth.3869.","journal-title":"Nat Methods"},{"issue":"8","key":"4718_CR35","doi-asserted-by":"publisher","first-page":"852","DOI":"10.1038\/s41587-019-0209-9","volume":"37","author":"E Bolyen","year":"2019","unstructured":"Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37(8):852. https:\/\/doi.org\/10.1038\/s41587-019-0209-9.","journal-title":"Nat Biotechnol"},{"issue":"11","key":"4718_CR36","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1009442","volume":"17","author":"H Mallick","year":"2021","unstructured":"Mallick H, Rahnavard A, McIver LJ, Ma S, Zhang Y, Nguyen LH, et al. Multivariable association discovery in population-scale meta-omics studies. PLoS Comput Biol. 2021;17(11):e1009442. https:\/\/doi.org\/10.1371\/journal.pcbi.1009442.","journal-title":"PLoS Comput Biol"},{"issue":"1","key":"4718_CR37","doi-asserted-by":"publisher","DOI":"10.1038\/s41522-025-00721-x","volume":"11","author":"L Zeng","year":"2025","unstructured":"Zeng L, Yu B, Zeng P, Duoji Z, Zuo H, Lian J, et al. Mediation effect and metabolic pathways of gut microbiota in the associations between lifestyles and dyslipidemia. NPJ Biofilms Microbiomes. 2025;11(1):90. https:\/\/doi.org\/10.1038\/s41522-025-00721-x.","journal-title":"NPJ Biofilms Microbiomes"},{"key":"4718_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2025.105888","volume":"199","author":"Y Lu","year":"2025","unstructured":"Lu Y, Li Y, Chi S, Feng Y, Li G, Lin X, et al. Comparison of machine learning and logistic regression models for predicting emergence delirium in elderly patients: a prospective study. Int J Med Inform. 2025;199:105888. https:\/\/doi.org\/10.1016\/j.ijmedinf.2025.105888.","journal-title":"Int J Med Inform"},{"key":"4718_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2023.105084","volume":"175","author":"S Jahandideh","year":"2023","unstructured":"Jahandideh S, Ozavci G, Sahle BW, Kouzani AZ, Magrabi F, Bucknall T. Evaluation of machine learning-based models for prediction of clinical deterioration: a systematic literature review. Int J Med Inform. 2023;175:105084. https:\/\/doi.org\/10.1016\/j.ijmedinf.2023.105084.","journal-title":"Int J Med Inform"},{"key":"4718_CR40","doi-asserted-by":"publisher","unstructured":"Tingley D, Yamamoto T, Hirose K, Keele L, Imai K. Mediation:RPackage for causal mediation analysis. J Stat Softw. 2014;59(5). https:\/\/doi.org\/10.18637\/jss.v059.i05.","DOI":"10.18637\/jss.v059.i05"},{"key":"4718_CR41","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.envsoft.2019.01.012","volume":"114","author":"A Saltelli","year":"2019","unstructured":"Saltelli A, Aleksankina K, Becker W, Fennell P, Ferretti F, Holst N, et al. Why so many published sensitivity analyses are false: a systematic review of sensitivity analysis practices. Environ Model Softw. 2019;114:29\u201339. https:\/\/doi.org\/10.1016\/j.envsoft.2019.01.012.","journal-title":"Environ Model Softw"},{"key":"4718_CR42","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2025.105953","volume":"201","author":"L Chen","year":"2025","unstructured":"Chen L, Lin CP, Chung CH, Lee JJ. Using longitudinal data and deep learning models to enhance resource allocation in home-based medical care. Int J Med Inform. 2025;201:105953. https:\/\/doi.org\/10.1016\/j.ijmedinf.2025.105953.","journal-title":"Int J Med Inform"},{"issue":"4","key":"4718_CR43","doi-asserted-by":"publisher","first-page":"122","DOI":"10.21315\/mjms2018.25.4.12","volume":"25","author":"MA Bujang","year":"2018","unstructured":"Bujang MA, Sa\u2019at N, Sidik T, Joo LC. Sample size guidelines for logistic regression from observational studies with large population: emphasis on the accuracy between statistics and parameters based on real life clinical data. Malays J Med Sci. 2018;25(4):122\u201330. https:\/\/doi.org\/10.21315\/mjms2018.25.4.12.","journal-title":"Malays J Med Sci"},{"issue":"12","key":"4718_CR44","doi-asserted-by":"publisher","first-page":"1373","DOI":"10.1016\/s0895-4356(96)00236-3","volume":"49","author":"P Peduzzi","year":"1996","unstructured":"Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996;49(12):1373\u20139. https:\/\/doi.org\/10.1016\/s0895-4356(96)00236-3.","journal-title":"J Clin Epidemiol"},{"key":"4718_CR45","doi-asserted-by":"publisher","unstructured":"Wang J, Lu S, Lian H, Yang Y, Huang W, Yuan Q, et al. A stratified genomic framework for salmonella serotype prediction: evaluation of MLST, SeqSero, SeqSero2, SeqSero2S, and SISTR in Southwest China. J Vis Exp. 2026;(227):e69117. https:\/\/doi.org\/10.3791\/69117.","DOI":"10.3791\/69117"},{"issue":"1","key":"4718_CR46","doi-asserted-by":"publisher","DOI":"10.1038\/s41378-025-01057-4","volume":"11","author":"S Kim","year":"2025","unstructured":"Kim S, Shrestha K, Cho G. Towards practical point-of-care quick, ubiquitous, integrated, cost-efficient molecular diagnostic kit (QUICK) PCR for future pandemic response. Microsyst Nanoeng. 2025;11(1):204. https:\/\/doi.org\/10.1038\/s41378-025-01057-4.","journal-title":"Microsyst Nanoeng"},{"key":"4718_CR47","doi-asserted-by":"publisher","DOI":"10.1016\/j.bonr.2024.101750","volume":"20","author":"AE Smit","year":"2024","unstructured":"Smit AE, Meijer OC, Winter EM. The multi-faceted nature of age-associated osteoporosis. Bone Rep. 2024;20:101750. https:\/\/doi.org\/10.1016\/j.bonr.2024.101750.","journal-title":"Bone Rep"},{"issue":"12","key":"4718_CR48","doi-asserted-by":"publisher","first-page":"e873","DOI":"10.1016\/S2665-9913(25)00105-5","volume":"7","author":"Collaborators GBDLBMD","year":"2025","unstructured":"Collaborators GBDLBMD. The global, regional, and national burden attributable to low bone mineral density, 1990\u20132020: an analysis of a modifiable risk factor from the Global Burden of Disease Study 2021. Lancet Rheumatol. 2025;7(12):e873\u201394. https:\/\/doi.org\/10.1016\/S2665-9913(25)00105-5.","journal-title":"Lancet Rheumatol"},{"issue":"Suppl 1","key":"4718_CR49","doi-asserted-by":"publisher","first-page":"8655","DOI":"10.1073\/pnas.0701985104","volume":"104","author":"CM Beall","year":"2007","unstructured":"Beall CM. Two routes to functional adaptation: Tibetan and Andean high-altitude natives. Proc Natl Acad Sci U S A. 2007;104(Suppl 1):8655\u201360. https:\/\/doi.org\/10.1073\/pnas.0701985104.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"4718_CR50","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2024.1510932","volume":"15","author":"WD Seifu","year":"2024","unstructured":"Seifu WD, Bekele-Alemu A, Zeng C. Genomic and physiological mechanisms of high-altitude adaptation in Ethiopian highlanders: a comparative perspective. Front Genet. 2024;15:1510932. https:\/\/doi.org\/10.3389\/fgene.2024.1510932.","journal-title":"Front Genet"},{"issue":"1","key":"4718_CR51","doi-asserted-by":"publisher","DOI":"10.1038\/s41413-024-00320-0","volume":"12","author":"H Kang","year":"2024","unstructured":"Kang H, Strong AL, Sun Y, Guo L, Juan C, Bancroft AC, et al. The HIF-1\u03b1\/PLOD2 axis integrates extracellular matrix organization and cell metabolism leading to aberrant musculoskeletal repair. Bone Res. 2024;12(1):17. https:\/\/doi.org\/10.1038\/s41413-024-00320-0.","journal-title":"Bone Res"},{"issue":"1","key":"4718_CR52","doi-asserted-by":"publisher","DOI":"10.1038\/s41413-025-00460-x","volume":"13","author":"S Tan","year":"2025","unstructured":"Tan S, Sun Y, Li S, Wu H, Ding Y. The impact of mitochondrial dysfunction on osteoarthritis cartilage: current insights and emerging mitochondria-targeted therapies. Bone Res. 2025;13(1):77. https:\/\/doi.org\/10.1038\/s41413-025-00460-x.","journal-title":"Bone Res"},{"issue":"1","key":"4718_CR53","doi-asserted-by":"publisher","DOI":"10.1038\/s41413-024-00375-z","volume":"12","author":"Z Han","year":"2024","unstructured":"Han Z, Wang K, Ding S, Zhang M. Cross-talk of inflammation and cellular senescence: a new insight into the occurrence and progression of osteoarthritis. Bone Res. 2024;12(1):69. https:\/\/doi.org\/10.1038\/s41413-024-00375-z.","journal-title":"Bone Res"},{"issue":"1","key":"4718_CR54","doi-asserted-by":"publisher","DOI":"10.1038\/s41413-023-00313-5","volume":"12","author":"F Fang","year":"2024","unstructured":"Fang F, Yang J, Wang J, Li T, Wang E, Zhang D, et al. The role and applications of extracellular vesicles in osteoporosis. Bone Res. 2024;12(1):4. https:\/\/doi.org\/10.1038\/s41413-023-00313-5.","journal-title":"Bone Res"},{"issue":"1","key":"4718_CR55","doi-asserted-by":"publisher","DOI":"10.1186\/s12903-021-01590-4","volume":"21","author":"AG Barbe","year":"2021","unstructured":"Barbe AG, Al-Barwari A, Hamacher S, Deinzer R, Weik U, Noack MJ. Effectiveness of brushing teeth in patients with reduced oral hygiene by laypeople: a randomized, controlled study. BMC Oral Health. 2021;21(1):225. https:\/\/doi.org\/10.1186\/s12903-021-01590-4.","journal-title":"BMC Oral Health"},{"key":"4718_CR56","doi-asserted-by":"publisher","DOI":"10.3390\/microorganisms12091797","author":"JJ Rajasekaran","year":"2024","unstructured":"Rajasekaran JJ, Krishnamurthy HK, Bosco J, Jayaraman V, Krishna K, Wang T, et al. Oral microbiome: a review of its impact on oral and systemic health. Microorganisms. 2024. https:\/\/doi.org\/10.3390\/microorganisms12091797.","journal-title":"Microorganisms"},{"issue":"1","key":"4718_CR57","doi-asserted-by":"publisher","DOI":"10.1080\/20002297.2024.2355823","volume":"16","author":"S Liu","year":"2024","unstructured":"Liu S, Wang S, Zhang N, Li P. The oral microbiome and oral and upper gastrointestinal diseases. J Oral Microbiol. 2024;16(1):2355823. https:\/\/doi.org\/10.1080\/20002297.2024.2355823.","journal-title":"J Oral Microbiol"},{"issue":"7","key":"4718_CR58","doi-asserted-by":"publisher","first-page":"720","DOI":"10.1016\/j.tim.2024.03.009","volume":"32","author":"SR West","year":"2024","unstructured":"West SR, Suddaby AB, Lewin GR, Ibberson CB. Rothia. Trends Microbiol. 2024;32(7):720\u20131. https:\/\/doi.org\/10.1016\/j.tim.2024.03.009.","journal-title":"Trends Microbiol"},{"key":"4718_CR59","doi-asserted-by":"publisher","DOI":"10.1128\/mSystems.00161-20","author":"CC Uranga","year":"2020","unstructured":"Uranga CC, Arroyo P Jr., Duggan BM, Gerwick WH, Edlund A. Commensal oral Rothia mucilaginosa produces enterobactin, a metal-chelating siderophore. mSystems. 2020. https:\/\/doi.org\/10.1128\/mSystems.00161-20.","journal-title":"mSystems"},{"issue":"5","key":"4718_CR60","doi-asserted-by":"publisher","first-page":"1490","DOI":"10.1038\/s41396-020-00865-y","volume":"15","author":"A Hoare","year":"2021","unstructured":"Hoare A, Wang H, Meethil A, Abusleme L, Hong BY, Moutsopoulos NM, et al. A cross-species interaction with a symbiotic commensal enables cell-density-dependent growth and in vivo virulence of an oral pathogen. ISME J. 2021;15(5):1490\u2013504. https:\/\/doi.org\/10.1038\/s41396-020-00865-y.","journal-title":"ISME J"},{"key":"4718_CR61","doi-asserted-by":"publisher","DOI":"10.3390\/nu16183167","author":"DL Avila","year":"2024","unstructured":"Avila DL, Fernandes-Braga W, Silva JL, Santos EA, Campos G, Leocadio PCL, et al. Capsaicin improves systemic inflammation, atherosclerosis, and macrophage-derived foam cells by stimulating PPAR gamma and TRPV1 receptors. Nutrients. 2024. https:\/\/doi.org\/10.3390\/nu16183167.","journal-title":"Nutrients"},{"key":"4718_CR62","doi-asserted-by":"publisher","DOI":"10.12659\/MSM.942485","volume":"30","author":"MB Bingul","year":"2024","unstructured":"Bingul MB, Gul M, Dundar S, Tanik A, Artas G, Polat ME. Enhanced bone healing through systemic capsaicin administration: an experimental study on Wistar rats. Med Sci Monit. 2024;30:e942485. https:\/\/doi.org\/10.12659\/MSM.942485.","journal-title":"Med Sci Monit"},{"key":"4718_CR63","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopha.2024.116995","volume":"177","author":"F Liu","year":"2024","unstructured":"Liu F, Wang X, He Y, Han R, Wang T, Guo Y. Jaw osteoporosis: challenges to oral health and emerging perspectives of treatment. Biomed Pharmacother. 2024;177:116995. https:\/\/doi.org\/10.1016\/j.biopha.2024.116995.","journal-title":"Biomed Pharmacother"},{"issue":"24","key":"4718_CR64","doi-asserted-by":"publisher","first-page":"3806","DOI":"10.1016\/j.scib.2024.11.008","volume":"69","author":"S Wang","year":"2024","unstructured":"Wang S, Hong Q, Zheng Y, Duan S, Cai G, Chen X. Epigenetics in high-altitude adaptation and disease. Sci Bull (Beijing). 2024;69(24):3806\u201311. https:\/\/doi.org\/10.1016\/j.scib.2024.11.008.","journal-title":"Sci Bull (Beijing)"},{"issue":"8","key":"4718_CR65","doi-asserted-by":"publisher","first-page":"1225","DOI":"10.1038\/s41440-022-00955-8","volume":"45","author":"X Zhang","year":"2022","unstructured":"Zhang X, Zhang Z, Ye R, Meng Q, Chen X. Prevalence of hypertension and its relationship with altitude in Highland areas: a systematic review and meta-analysis. Hypertens Res. 2022;45(8):1225\u201339. https:\/\/doi.org\/10.1038\/s41440-022-00955-8.","journal-title":"Hypertens Res"},{"issue":"21","key":"4718_CR66","doi-asserted-by":"publisher","first-page":"5409","DOI":"10.1113\/JP285454","volume":"602","author":"JC Tremblay","year":"2024","unstructured":"Tremblay JC. Mountains of research: where and whom high-altitude physiology has overlooked. J Physiol. 2024;602(21):5409\u201317. https:\/\/doi.org\/10.1113\/JP285454.","journal-title":"J Physiol"}],"container-title":["BMC Microbiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12866-026-04718-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12866-026-04718-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12866-026-04718-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T19:24:36Z","timestamp":1781637876000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s12866-026-04718-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,5]]},"references-count":66,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["4718"],"URL":"https:\/\/doi.org\/10.1186\/s12866-026-04718-0","relation":{},"ISSN":["1471-2180"],"issn-type":[{"value":"1471-2180","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,5]]},"assertion":[{"value":"16 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 January 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 March 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study was carried out according to the ethical principles of the Declaration of Helsinki and approved by the ethics committees of Sichuan University (K2016038 and K2020022). Written informed consent was obtained from all participants before data collection.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"337"}}