{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T13:33:04Z","timestamp":1781616784062,"version":"3.54.5"},"reference-count":46,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T00:00:00Z","timestamp":1743120000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Boston Heart Diagnostics"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nutrients"],"abstract":"<jats:p>Background: Coronary heart disease (CHD) remains a leading cause of death and has been associated with alterations in plasma lipoprotein particles and inflammation markers. This study aimed to evaluate and compare standard and advanced lipid parameters and inflammatory biomarkers in CHD cases and matched control subjects. We hypothesized that incorporating advanced lipid and inflammatory biomarkers into risk models would improve CHD risk prediction beyond the standard lipid measures. Methods: CHD cases (n = 227, mean age 61 years, 47% female) and matched controls (n = 526) underwent fasting blood collection while off lipid-lowering medications. Automated chemistry analyses were performed to measure total cholesterol (TC), triglycerides (TGs), low-density lipoprotein-C (LDL-C), small dense LDL-C (sdLDL-C), apolipoproteins (apos) A-I and B, lipoprotein(a) (Lp(a)), high-sensitivity C-reactive protein (hsCRP), serum amyloid-A (SAA), myeloperoxidase (MPO), and apoA-I in HDL particles (via 2-dimensional electrophoresis and immunoblotting). Univariate, multivariate, and machine learning analyses compared the CHD cases with the controls. Results: The most significant percent differences between male and female cases versus controls were for hsCRP (+78%, +200%), MPO (+109%, +106%), SAA (+84%, +33%), sdLDL-C (+48%; +43%), Lp(a) (+43%,+70%), apoA-I in very large \u03b1-1 HDL (\u221234%, \u221226%), HDL-C (\u221224%, \u221227%), and apoA-I in very small pre\u03b2-1 HDL (+17%; +16%). Total C, non-HDL-C, and direct and calculated LDL-C levels were only modestly higher in the cases. Multivariate models incorporating advanced parameters were statistically superior to a standard model (C statistic: men: 0.913 vs. 0.856; women: 0.903 versus 0.838). Machine learning identified apoA-I in pre\u03b2-1-HDL, \u03b1-2-HDL, \u03b1-1-HDL, \u03b1-3-HDL, MPO, and sdLDL-C as the top predictors of CHD. Conclusions: This study introduces a novel approach to CHD risk assessment by integrating advanced HDL particle analysis and machine learning. By assessing HDL subpopulations (\u03b1-1, \u03b1-2, pre\u03b2-1 HDL), inflammatory biomarkers (MPO, SAA), and small dense LDL, we provide a more refined stratification model. Notably, pre\u03b2-1 HDL, an independent risk factor reflecting impaired cholesterol efflux from the artery wall, is highlighted as a critical marker of CHD risk. Our approach allows for earlier identification of high-risk individuals, particularly those with subtle lipid or inflammatory abnormalities, supporting more personalized interventions. These findings demonstrate the potential of advanced lipid profiling and machine learning to enhance CHD risk prediction.<\/jats:p>","DOI":"10.3390\/nu17071182","type":"journal-article","created":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T13:36:49Z","timestamp":1743169009000},"page":"1182","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["High-Density Lipoprotein Particles, Inflammation, and Coronary Heart Disease Risk"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7085-5790","authenticated-orcid":false,"given":"Eveline O.","family":"Stock","sequence":"first","affiliation":[{"name":"Cardiovascular Research Institute (CVRI) and Department of Medicine, University of California, San Francisco, CA 94143, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bela F.","family":"Asztalos","sequence":"additional","affiliation":[{"name":"Cardiovascular Research Laboratory, Human Nutrition Research Center on Aging, Tufts University, Boston, MA 02111, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John M.","family":"Miller","sequence":"additional","affiliation":[{"name":"J2 Health, New York, NY 10006, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lihong","family":"He","sequence":"additional","affiliation":[{"name":"Boston Heart Diagnostics, Framingham, MA 01702, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1870-4586","authenticated-orcid":false,"given":"Kate Townsend","family":"Creasy","sequence":"additional","affiliation":[{"name":"Cardiovascular Research Institute (CVRI) and Department of Medicine, University of California, San Francisco, CA 94143, USA"},{"name":"Biobehavioral Health Sciences, PenNSAM\u2014Penn Center for Nutrition Science and Medicine, Institute for Diabetes, Obesity, and Metabolism, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rachel","family":"Schwemberger","sequence":"additional","affiliation":[{"name":"Cardiovascular Research Institute (CVRI) and Department of Medicine, University of California, San Francisco, CA 94143, USA"},{"name":"Department of Pediatrics, Alameda Health System, Highland Hospital, Oakland, CA 94602, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander","family":"Quinn","sequence":"additional","affiliation":[{"name":"Cardiovascular Research Institute (CVRI) and Department of Medicine, University of California, San Francisco, CA 94143, USA"},{"name":"Department of Hospital Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Clive R.","family":"Pullinger","sequence":"additional","affiliation":[{"name":"Cardiovascular Research Institute (CVRI) and Department of Medicine, University of California, San Francisco, CA 94143, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mary J.","family":"Malloy","sequence":"additional","affiliation":[{"name":"Cardiovascular Research Institute (CVRI) and Department of Medicine, University of California, San Francisco, CA 94143, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Margaret R.","family":"Diffenderfer","sequence":"additional","affiliation":[{"name":"Boston Heart Diagnostics, Framingham, MA 01702, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John P.","family":"Kane","sequence":"additional","affiliation":[{"name":"Cardiovascular Research Institute (CVRI) and Department of Medicine, University of California, San Francisco, CA 94143, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1161\/CIRCULATIONAHA.123.067626","article-title":"Development and Validation of the American Heart Association\u2019s PREVENT Equations","volume":"149","author":"Khan","year":"2024","journal-title":"Circulation"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1982","DOI":"10.1161\/CIR.0000000000001191","article-title":"Novel Prediction Equations for Absolute Risk Assessment of Total Cardiovascular Disease Incorporating Cardiovascular-Kidney-Metabolic Health: A Scientific Statement from the American Heart Association","volume":"148","author":"Khan","year":"2023","journal-title":"Circulation"},{"key":"ref_3","first-page":"e1082","article-title":"2018 AHA\/ACC\/AACVPR\/AAPA\/ABC\/ACPM\/ADA\/AGS\/APhA\/ASPC\/NLA\/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology\/American Heart Association Task Force on Clinical Practice Guidelines","volume":"139","author":"GGrundy","year":"2019","journal-title":"Circulation"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1001\/jama.297.6.611","article-title":"Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: The Reynolds Risk Score","volume":"297","author":"Ridker","year":"2007","journal-title":"JAMA"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2243","DOI":"10.1161\/CIRCULATIONAHA.108.814251","article-title":"C-reactive protein and parental history improve global cardiovascular risk prediction: The Reynolds Risk Score for men","volume":"118","author":"Ridker","year":"2008","journal-title":"Circulation"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1175","DOI":"10.1016\/S0140-6736(09)60447-5","article-title":"Reduction in C-reactive protein and LDL cholesterol and cardiovascular event rates after initiation of rosuvastatin: A prospective study of the JUPITER trial","volume":"373","author":"Ridker","year":"2009","journal-title":"Lancet"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.1161\/01.ATV.0000163262.83456.6d","article-title":"Myeloperoxidase and cardiovascular disease","volume":"25","author":"Nicholls","year":"2005","journal-title":"Arterioscler. Thromb. Vasc. Biol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"S346","DOI":"10.1194\/jlr.R800086-JLR200","article-title":"Myeloperoxidase, modified lipoproteins, and atherogenesis","volume":"50","author":"Nicholls","year":"2009","journal-title":"J. Lipid Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1595","DOI":"10.1056\/NEJMoa035003","article-title":"Prognostic value of myeloperoxidase in patients with chest pain","volume":"349","author":"Brennan","year":"2003","journal-title":"N. Engl. J. Med."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.jacc.2007.03.033","article-title":"Serum myeloperoxidase levels are associated with the future risk of coronary artery disease in apparently healthy individuals: The EPIC-Norfolk Prospective Population Study","volume":"50","author":"Meuwese","year":"2007","journal-title":"J. Am. Coll. Cardiol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.1001\/jama.2016.13985","article-title":"Association Between Lowering LDL-C and Cardiovascular Risk Reduction Among Different Therapeutic Interventions: A Systematic Review and Meta-analysis","volume":"316","author":"Silverman","year":"2016","journal-title":"JAMA"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.1373\/clinchem.2019.304600","article-title":"Direct Versus Calculated LDL Cholesterol and C-Reactive Protein in Cardiovascular Disease Risk Assessment in the Framingham Offspring Study","volume":"65","author":"Ikezaki","year":"2019","journal-title":"Clin. Chem."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1917","DOI":"10.1001\/jama.1988.03410130125037","article-title":"Low-Density Lipoprotein Subclass Patterns and Risk of Myocardial Infarction","volume":"260","author":"Austin","year":"1988","journal-title":"JAMA"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1161\/01.ATV.12.2.187","article-title":"Low density lipoprotein particle size and coronary artery disease","volume":"12","author":"Campos","year":"1992","journal-title":"Arterioscler. Thromb."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"e019140","DOI":"10.1161\/JAHA.120.019140","article-title":"Small Dense Low-Density Lipoprotein Cholesterol Is the Most Atherogenic Lipoprotein Parameter in the Prospective Framingham Offspring Study","volume":"10","author":"Ikezaki","year":"2021","journal-title":"J. Am. Heart Assoc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.atherosclerosis.2023.01.015","article-title":"Atherosclerotic cardiovascular disease risk and small dense low-density lipoprotein cholesterol in men, women, African Americans and non-African Americans: The pooling project","volume":"367","author":"Schaefer","year":"2023","journal-title":"Atherosclerosis"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.amjcard.2007.08.035","article-title":"Effects of maximal doses of atorvastatin versus rosuvastatin on small dense low-density lipoprotein cholesterol levels","volume":"101","author":"Ai","year":"2008","journal-title":"Am. J. Cardiol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.pcad.2016.08.006","article-title":"Diagnosis and treatment of high-density lipoprotein deficiency","volume":"59","author":"Schaefer","year":"2016","journal-title":"Prog. Cardiovasc. Dis."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1097\/MOL.0b013e328353eef1","article-title":"Prebeta-1 HDL and coronary heart disease","volume":"23","author":"Kane","year":"2012","journal-title":"Curr. Opin. Lipidol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2246","DOI":"10.1194\/jlr.M500187-JLR200","article-title":"Differential effects of HDL subpopulations on cellular ABCA1 and SR-B1-mediated cholesterol efflux","volume":"46","author":"Asztalos","year":"2005","journal-title":"J. Lipid Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1056\/NEJMoa1001689","article-title":"Cholesterol efflux capacity, high-density lipoprotein function, and atherosclerosis","volume":"364","author":"Khera","year":"2011","journal-title":"N. Engl. J. Med."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2383","DOI":"10.1056\/NEJMoa1409065","article-title":"HDL cholesterol efflux capacity and incident cardiovascular events","volume":"371","author":"Rohatgi","year":"2014","journal-title":"N. Engl. J. Med."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2494","DOI":"10.1161\/CIRCULATIONAHA.116.025678","article-title":"Cholesterol Efflux Capacity, High-Density Lipoprotein Particle Number, and Incident Cardiovascular Events: An Analysis From the JUPITER Trial (Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin)","volume":"135","author":"Khera","year":"2017","journal-title":"Circulation"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.atherosclerosis.2022.02.012","article-title":"The role of HDL- and non-HDL-related parameters in cell-cholesterol efflux capacity","volume":"345","author":"Asztalos","year":"2022","journal-title":"Atherosclerosis"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"118565","DOI":"10.1016\/j.atherosclerosis.2024.118565","article-title":"Relationships between HDL subpopulation proteome and HDL function in overweight\/obese people with and without coronary heart disease","volume":"397","author":"Vaisar","year":"2024","journal-title":"Atherosclerosis"},{"key":"ref_26","unstructured":"Feingold, K.R., Anawalt, B., Blackman, M.R., Boyce, A., Chrousos, G., Corpas, E., and de Herder, W.W. (2016). The Measurement of Lipids, Lipoproteins, Apolipoproteins, Fatty Acids, and Sterols, and Next Generation Sequencing for the Diagnosis and Treatment of Lipid Disorders, MDText. com, Inc."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1194\/jlr.RA119000258","article-title":"Composition-function analysis of HDL subpopulations: Influence of lipid composition on particle functionality","volume":"61","author":"Niisuke","year":"2020","journal-title":"J. Lipid Res."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Saharan, S.S., Nagar, P., Creasy, K.T., Stock, E.O., Feng, J., Malloy, M.J., and Kane, J.P. (2021, January 15\u201317). Application of Machine Learning Ensemble Super Learner for analysis of the cytokines transported by high density lipoproteins (HDL) of smokers and nonsmokers. Proceedings of the 2021 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA.","DOI":"10.1109\/CSCI54926.2021.00133"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Saharan, S.S., Nagar, P., Creasy, K.T., Stock, E.O., James, F., Malloy, M.J., and Kane, J.P. (2023, January 13\u201315). Logistic Regression and Statistical Regularization Techniques for Risk Classification of Coronary Artery Disease using Cytokines transported by high density lipoproteins. Proceedings of the 2023 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA.","DOI":"10.1109\/CSCI62032.2023.00114"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/0005-2760(93)90253-6","article-title":"Two-dimensional electrophoresis of plasma lipoproteins: Recognition of new apo A-I-containing subpopulations","volume":"1169","author":"Asztalos","year":"1993","journal-title":"Biochim. Biophys. Acta"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2421","DOI":"10.1194\/jlr.M088203","article-title":"Genetic and secondary causes of severe HDL deficiency and cardiovascular disease","volume":"59","author":"Geller","year":"2018","journal-title":"J. Lipid Res."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.jacl.2017.11.001","article-title":"Levels of prebeta-1 high-density lipoprotein are elevated in 3 phenotypes of dyslipidemia","volume":"12","author":"Stock","year":"2018","journal-title":"J. Clin. Lipidol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1097\/MOL.0000000000000555","article-title":"Emerging roles of HDL in immune function","volume":"29","author":"Creasy","year":"2018","journal-title":"Curr. Opin. Lipidol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2670","DOI":"10.1161\/01.ATV.20.12.2670","article-title":"Distribution of ApoA-I-containing HDL subpopulations in patients with coronary heart disease","volume":"20","author":"Asztalos","year":"2000","journal-title":"Arterioscler. Thromb. Vasc. Biol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1161\/01.ATV.0000066133.32063.BB","article-title":"Change in alpha1 HDL concentration predicts progression in coronary artery stenosis","volume":"23","author":"Asztalos","year":"2003","journal-title":"Arterioscler. Thromb. Vasc. Biol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2181","DOI":"10.1161\/01.ATV.0000146325.93749.a8","article-title":"High-density lipoprotein subpopulation profile and coronary heart disease prevalence in male participants of the Framingham Offspring Study","volume":"24","author":"Asztalos","year":"2004","journal-title":"Arterioscler. Thromb. Vasc. Biol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1016\/j.amjcard.2006.09.117","article-title":"Comparison of the effects of high doses of rosuvastatin versus atorvastatin on the subpopulations of high-density lipoproteins","volume":"99","author":"Asztalos","year":"2007","journal-title":"Am. J. Cardiol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2405","DOI":"10.1194\/jlr.P900015-JLR200","article-title":"Effects of weight loss, induced by gastric bypass surgery, on HDL remodeling in obese women","volume":"51","author":"Asztalos","year":"2010","journal-title":"J. Lipid Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1016\/j.jacl.2018.12.001","article-title":"Effects of weight change on HDL-cholesterol and its subfractions in over 28,000 men and women","volume":"13","author":"Dansinger","year":"2019","journal-title":"J. Clin. Lipidol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/j.amjcard.2011.03.054","article-title":"Relation of increased prebeta-1 high-density lipoprotein levels to risk of coronary heart disease","volume":"108","author":"Guey","year":"2011","journal-title":"Am. J. Cardiol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"e018381","DOI":"10.1161\/JAHA.120.018381","article-title":"Levels of Prebeta-1 High-Density Lipoprotein Are a Strong Independent Positive Risk Factor for Coronary Heart Disease and Myocardial Infarction: A Meta-Analysis","volume":"10","author":"Pullinger","year":"2021","journal-title":"J. Am. Heart Assoc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.metabol.2007.08.009","article-title":"Relation of gemfibrozil treatment and high-density lipoprotein subpopulation profile with cardiovascular events in the Veterans Affairs High-Density Lipoprotein Intervention Trial","volume":"57","author":"Asztalos","year":"2008","journal-title":"Metabolism"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"575","DOI":"10.1161\/ATVBAHA.107.157123","article-title":"Plasma levels of HDL subpopulations and remnant lipoproteins predict the extent of angiographically-defined coronary artery disease in postmenopausal women","volume":"28","author":"Herrington","year":"2008","journal-title":"Arterioscler. Thromb. Vasc. Biol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2185","DOI":"10.1161\/01.ATV.0000183727.90611.4f","article-title":"Value of high-density lipoprotein (HDL) subpopulations in predicting recurrent cardiovascular events in the Veterans Affairs HDL Intervention Trial","volume":"25","author":"Asztalos","year":"2005","journal-title":"Arterioscler. Thromb. Vasc. Biol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"423","DOI":"10.33963\/v.phj.99553","article-title":"Usefulness of myocardial damage biomarkers in predicting cardiogenic shock in patients undergoing heart valve surgery","volume":"82","author":"Duchnowski","year":"2024","journal-title":"Pol. Heart J."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.1016\/j.amjcard.2020.01.025","article-title":"N-terminal Pro B-type Natriuretic Peptide and High-sensitivity Cardiac Troponin as Markers for Heart Failure and Cardiovascular Disease Risks According to Glucose Status (from the Multi-Ethnic Study of Atherosclerosis [MESA])","volume":"125","author":"Nguyen","year":"2020","journal-title":"Am. J. Cardiol."}],"container-title":["Nutrients"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-6643\/17\/7\/1182\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:04:29Z","timestamp":1760029469000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-6643\/17\/7\/1182"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,28]]},"references-count":46,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2025,4]]}},"alternative-id":["nu17071182"],"URL":"https:\/\/doi.org\/10.3390\/nu17071182","relation":{},"ISSN":["2072-6643"],"issn-type":[{"value":"2072-6643","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,28]]}}}