{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T19:38:43Z","timestamp":1758397123238,"version":"3.41.2"},"reference-count":52,"publisher":"IMR Press","issue":"7","license":[{"start":{"date-parts":[[2023,7,4]],"date-time":"2023-07-04T00:00:00Z","timestamp":1688428800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Front. Biosci. (Landmark Ed)"],"abstract":"<jats:p>Objective: Preeclampsia (PE) is a significant cause of maternal and offspring mortality and morbidity. The purpose of this study is to identify the potential diagnostic signatures of autophagy-related genes (ATGs) in pregnancies with preeclampsia. Methods: The expression profile of mRNA was obtained from GSE75010 (placenta samples) and GSE48424 dataset (blood samples). The potential differentially expressed ATGs of PE were screened by R software. The gene-ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, correlation analysis, and protein-protein interactions (PPI) were applied for the differentially expressed ATGs. The diagnostic markers of PE were then screened based on least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination (SVM-RFE). Receiver operating characteristic (ROC) analysis was used to investigate the predictive value of these diagnostic markers. Target miRNAs were predicted based on the miRDB, DIANA-micro T, Targetscan, and miRWalk databases, and were further validated in GSE84260. Results: A total of 20 differentially expressed ATGs were identified between PE and healthy pregnancies. Functional analysis of differentially expressed ATGs indicated several enriched terms related to autophagy, apoptosis, angiogenesis, inflammation, immune response, hypoxia-inducible factor 1 (HIF-1), forkhead box O (FoxO) and AMP-activated protein kinase (AMPK) signaling pathway. A total of 12 ATGs were recognized based on LASSO and SVM-RFE, which made an excellent distinction in both the placenta tissues (area under the curve [AUC] = 0.903) and the blood samples (AUC = 0.972). Furthermore, four feature ATGs (leptin [LEP], ERO1-like [ERO1L], phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit beta [PIK3CB], and mitogen-activated protein kinase 8 [MAPK8]) were screened and also shown an excellent diagnostic efficacy (AUC = 0.869 in placenta samples, and AUC = 0.914 in blood samples). Additionally, 81 target miRNAs were predicted according to the 4 feature ATGs. After evaluating the miRNA expression pattern of GSE84260, 11 miRNAs were selected. Finally, a miRNA-mRNA regulatory network was constructed, which may participate in the development of PE. Conclusions: We established an autophagy-related-gene based signature that may predict pregnancies with PE. And we also constructed a miRNA-mRNA regulatory network, which may deepen our understanding of the molecular mechanism underlying the development of PE.<\/jats:p>","DOI":"10.31083\/j.fbl2807132","type":"journal-article","created":{"date-parts":[[2023,7,7]],"date-time":"2023-07-07T08:48:30Z","timestamp":1688719710000},"source":"Crossref","is-referenced-by-count":3,"title":["A Potential Autophagy-Related-Gene Based Signature in Patients with Preeclampsia"],"prefix":"10.31083","volume":"28","author":[{"given":"Jiayu","family":"Shen","sequence":"first","affiliation":[{"name":"Department of Obstetrics, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009 Hangzhou, Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyuan","family":"Teng","sequence":"first","affiliation":[{"name":"Department of Obstetrics, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009 Hangzhou, Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiayao","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Obstetrics, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009 Hangzhou, Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanling","family":"Feng","sequence":"first","affiliation":[{"name":"Department of Obstetrics, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009 Hangzhou, Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liquan","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Obstetrics, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009 Hangzhou, Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"16242","published-online":{"date-parts":[[2023,7,4]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","unstructured":"Behram M, O\u011flak SC. The expression of angiogenic protein Cyr61 significantly increases in the urine of early-onset preeclampsia patients. Journal of Contemporary Medicine. 2021; 11: 605\u2013609.","DOI":"10.16899\/jcm.945345"},{"key":"ref2","doi-asserted-by":"crossref","unstructured":"Say L, Chou D, Gemmill A, Tun\u00e7alp \u00d6, Moller AB, Daniels J, et al. Global causes of maternal death: a WHO systematic analysis. The Lancet. Global Health. 2014; 2: e323\u201333.","DOI":"10.1016\/S2214-109X(14)70227-X"},{"key":"ref3","doi-asserted-by":"crossref","unstructured":"Brown MA, Magee LA, Kenny LC, Karumanchi SA, McCarthy FP, Saito S, et al. Hypertensive Disorders of Pregnancy: ISSHP Classification, Diagnosis, and Management Recommendations for International Practice. Hypertension (Dallas, Tex.: 1979). 2018; 72: 24\u201343.","DOI":"10.1161\/HYPERTENSIONAHA.117.10803"},{"key":"ref4","doi-asserted-by":"crossref","unstructured":"O\u011flak SC, Bademk\u0131ran MH, Obut M. Predictor variables in the success of slow-release dinoprostone used for cervical ripening in intrauterine growth restriction pregnancies. Journal of Gynecology Obstetrics and Human Reproduction. 2020; 49: 101739.","DOI":"10.1016\/j.jogoh.2020.101739"},{"key":"ref5","doi-asserted-by":"crossref","unstructured":"Cheng SB, Sharma S. Preeclampsia and health risks later in life: an immunological link. Seminars in Immunopathology. 2016; 38: 699\u2013708.","DOI":"10.1007\/s00281-016-0579-8"},{"key":"ref6","doi-asserted-by":"crossref","unstructured":"Barrett PM, McCarthy FP, Evans M, Kublickas M, Perry IJ, Stenvinkel P, et al. Hypertensive disorders of pregnancy and the risk of chronic kidney disease: A Swedish registry-based cohort study. PLoS Medicine. 2020; 17: e1003255.","DOI":"10.1371\/journal.pmed.1003255"},{"key":"ref7","doi-asserted-by":"crossref","unstructured":"Feig DS, Shah BR, Lipscombe LL, Wu CF, Ray JG, Lowe J, et al. Preeclampsia as a risk factor for diabetes: a population-based cohort study. PLoS Medicine. 2013; 10: e1001425.","DOI":"10.1371\/journal.pmed.1001425"},{"key":"ref8","doi-asserted-by":"crossref","unstructured":"Helmo FR, Lopes AMM, Carneiro ACDM, Campos CG, Silva PB, Dos Reis Monteiro MLG, et al. Angiogenic and antiangiogenic factors in preeclampsia. Pathology, Research and Practice. 2018; 214: 7\u201314.","DOI":"10.1016\/j.prp.2017.10.021"},{"key":"ref9","doi-asserted-by":"crossref","unstructured":"Karumanchi SA. Angiogenic Factors in Preeclampsia: From Diagnosis to Therapy. Hypertension (Dallas, Tex.: 1979). 2016; 67: 1072\u20131079.","DOI":"10.1161\/HYPERTENSIONAHA.116.06421"},{"key":"ref10","doi-asserted-by":"crossref","unstructured":"Gude NM, Roberts CT, Kalionis B, King RG. Growth and function of the normal human placenta. Thrombosis Research. 2004; 114: 397\u2013407.","DOI":"10.1016\/j.thromres.2004.06.038"},{"key":"ref11","doi-asserted-by":"crossref","unstructured":"Steegers EAP, von Dadelszen P, Duvekot JJ, Pijnenborg R. Pre-eclampsia. Lancet (London, England). 2010; 376: 631\u2013644.","DOI":"10.1016\/S0140-6736(10)60279-6"},{"key":"ref12","doi-asserted-by":"crossref","unstructured":"Sharp AN, Heazell AEP, Crocker IP, Mor G. Placental apoptosis in health and disease. American Journal of Reproductive Immunology (New York, N.Y.: 1989). 2010; 64: 159\u2013169.","DOI":"10.1111\/j.1600-0897.2010.00837.x"},{"key":"ref13","doi-asserted-by":"crossref","unstructured":"Raguema N, Moustadraf S, Bertagnolli M. Immune and Apoptosis Mechanisms Regulating Placental Development and Vascularization in Preeclampsia. Frontiers in Physiology. 2020; 11: 98.","DOI":"10.3389\/fphys.2020.00098"},{"key":"ref14","doi-asserted-by":"crossref","unstructured":"Galluzzi L, Baehrecke EH, Ballabio A, Boya P, Bravo-San Pedro JM, Cecconi F, et al. Molecular definitions of autophagy and related processes. The EMBO Journal. 2017; 36: 1811\u20131836.","DOI":"10.15252\/embj.201796697"},{"key":"ref15","doi-asserted-by":"crossref","unstructured":"Lv X, Li K, Hu Z. Chronic Obstructive Pulmonary Disease and Autophagy. Advances in Experimental Medicine and Biology. 2020; 1207: 559\u2013567.","DOI":"10.1007\/978-981-15-4272-5_39"},{"key":"ref16","doi-asserted-by":"crossref","unstructured":"Huang T, Wan X, Alvarez AA, James CD, Song X, Yang Y, et al. MIR93 (microRNA -93) regulates tumorigenicity and therapy response of glioblastoma by targeting autophagy. Autophagy. 2019; 15: 1100\u20131111.","DOI":"10.1080\/15548627.2019.1569947"},{"key":"ref17","doi-asserted-by":"crossref","unstructured":"Li Y, Zhao X, He B, Wu W, Zhang H, Yang X, et al. Autophagy Activation by Hypoxia Regulates Angiogenesis and Apoptosis in Oxidized Low-Density Lipoprotein-Induced Preeclampsia. Frontiers in Molecular Biosciences. 2021; 8: 709751.","DOI":"10.3389\/fmolb.2021.709751"},{"key":"ref18","doi-asserted-by":"crossref","unstructured":"Nakashima A, Yamanaka-Tatematsu M, Fujita N, Koizumi K, Shima T, Yoshida T, et al. Impaired autophagy by soluble endoglin, under physiological hypoxia in early pregnant period, is involved in poor placentation in preeclampsia. Autophagy. 2013; 9: 303\u2013316.","DOI":"10.4161\/auto.22927"},{"key":"ref19","doi-asserted-by":"crossref","unstructured":"Hung TH, Hsieh TT, Chen SF, Li MJ, Yeh YL. Autophagy in the human placenta throughout gestation. PLoS ONE. 2013; 8: e83475.","DOI":"10.1371\/journal.pone.0083475"},{"key":"ref20","doi-asserted-by":"crossref","unstructured":"Gao L, Qi HB, Kamana KC, Zhang XM, Zhang H, Baker PN. Excessive autophagy induces the failure of trophoblast invasion and vasculature: possible relevance to the pathogenesis of preeclampsia. Journal of Hypertension. 2015; 33: 106\u2013117.","DOI":"10.1097\/HJH.0000000000000366"},{"key":"ref21","doi-asserted-by":"crossref","unstructured":"Maiuri MC, Zalckvar E, Kimchi A, Kroemer G. Self-eating and self-killing: crosstalk between autophagy and apoptosis. Nature Reviews. Molecular Cell Biology. 2007; 8: 741\u2013752.","DOI":"10.1038\/nrm2239"},{"key":"ref22","doi-asserted-by":"crossref","unstructured":"Aoki A, Nakashima A, Kusabiraki T, Ono Y, Yoshino O, Muto M, et al. Trophoblast-Specific Conditional Atg7 Knockout Mice Develop Gestational Hypertension. The American Journal of Pathology. 2018; 188: 2474\u20132486.","DOI":"10.1016\/j.ajpath.2018.07.021"},{"key":"ref23","doi-asserted-by":"crossref","unstructured":"Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, et al. NCBI GEO: archive for functional genomics data sets\u2013update. Nucleic Acids Research. 2013; 41: D991\u2013D995.","DOI":"10.1093\/nar\/gks1193"},{"key":"ref24","doi-asserted-by":"crossref","unstructured":"Leavey K, Benton SJ, Grynspan D, Kingdom JC, Bainbridge SA, Cox BJ. Unsupervised placental gene expression profiling identifies clinically relevant subclasses of human preeclampsia. Hypertension. 2016; 68: 137\u2013147.","DOI":"10.1161\/HYPERTENSIONAHA.116.07293"},{"key":"ref25","doi-asserted-by":"crossref","unstructured":"Textoris J, Ivorra D, Ben Amara A, Sabatier F, M\u00e9nard JP, Heckenroth H, et al. Evaluation of current and new biomarkers in severe preeclampsia: a microarray approach reveals the VSIG4 gene as a potential blood biomarker. PLoS One. 2013; 8: e82638.","DOI":"10.1371\/journal.pone.0082638"},{"key":"ref26","doi-asserted-by":"crossref","unstructured":"Smid M, Dorssers LCJ, Jenster G. Venn Mapping: clustering of heterologous microarray data based on the number of co-occurring differentially expressed genes. Bioinformatics (Oxford, England). 2003; 19: 2065\u20132071.","DOI":"10.1093\/bioinformatics\/btg282"},{"key":"ref27","doi-asserted-by":"crossref","unstructured":"Cieslak MC, Castelfranco AM, Roncalli V, Lenz PH, Hartline DK. t-Distributed Stochastic Neighbor Embedding (t-SNE): A tool for eco-physiological transcriptomic analysis. Marine Genomics. 2020; 51: 100723.","DOI":"10.1016\/j.margen.2019.100723"},{"key":"ref28","doi-asserted-by":"crossref","unstructured":"Gaudet P, Logie C, Lovering RC, Kuiper M, L\u00e6greid A, Thomas PD. Gene Ontology representation for transcription factor functions. Biochimica et Biophysica Acta. Gene Regulatory Mechanisms. 2021; 1864: 194752.","DOI":"10.1016\/j.bbagrm.2021.194752"},{"key":"ref29","doi-asserted-by":"crossref","unstructured":"Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Research. 2017; 45: D353\u2013D361.","DOI":"10.1093\/nar\/gkw1092"},{"key":"ref30","doi-asserted-by":"crossref","unstructured":"Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research. 2019; 47: D607\u2013D613.","DOI":"10.1093\/nar\/gky1131"},{"key":"ref31","doi-asserted-by":"crossref","unstructured":"Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Research. 2003; 13: 2498\u20132504.","DOI":"10.1101\/gr.1239303"},{"key":"ref32","doi-asserted-by":"crossref","unstructured":"Tibshirani R. Regression shrinkage and selection via the Lasso. Journal of the Royal Statistical Society.1996; 58: 267\u2013288.","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"ref33","doi-asserted-by":"crossref","unstructured":"Lin X, Li C, Zhang Y, Su B, Fan M, Wei H. Selecting Feature Subsets Based on SVM-RFE and the Overlapping Ratio with Applications in Bioinformatics. Molecules (Basel, Switzerland). 2017; 23: 52.","DOI":"10.3390\/molecules23010052"},{"key":"ref34","doi-asserted-by":"crossref","unstructured":"Chen Y, Wang X. miRDB: an online database for prediction of functional microRNA targets. Nucleic Acids Research. 2020; 48: D127\u2013D131.","DOI":"10.1093\/nar\/gkz757"},{"key":"ref35","doi-asserted-by":"crossref","unstructured":"Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005; 120: 15\u201320.","DOI":"10.1016\/j.cell.2004.12.035"},{"key":"ref36","doi-asserted-by":"crossref","unstructured":"Paraskevopoulou MD, Georgakilas G, Kostoulas N, Vlachos IS, Vergoulis T, Reczko M, et al. DIANA-microT web server v5.0: service integration into miRNA functional analysis workflows. Nucleic Acids Research. 2013; 41: W169\u2013W173.","DOI":"10.1093\/nar\/gkt393"},{"key":"ref37","doi-asserted-by":"crossref","unstructured":"Sticht C, De La Torre C, Parveen A, Gretz N. miRWalk: An online resource for prediction of microRNA binding sites. PLoS ONE. 2018; 13: e0206239.","DOI":"10.1371\/journal.pone.0206239"},{"key":"ref38","doi-asserted-by":"crossref","unstructured":"\u00d6lmez F, O\u011flak SC, Gedik \u00d6zk\u00f6se Z. Increased maternal serum aquaporin-9 expression in pregnancies complicated with early-onset preeclampsia. The Journal of Obstetrics and Gynaecology Research. 2022; 48: 647\u2013653.","DOI":"10.1111\/jog.15129"},{"key":"ref39","doi-asserted-by":"crossref","unstructured":"Li L, Tan J, Miao Y, Lei P, Zhang Q. ROS and Autophagy: Interactions and Molecular Regulatory Mechanisms. Cellular and Molecular Neurobiology. 2015; 35: 615\u2013621.","DOI":"10.1007\/s10571-015-0166-x"},{"key":"ref40","doi-asserted-by":"crossref","unstructured":"Ma Y, Ye Y, Zhang J, Ruan CC, Gao PJ. Immune imbalance is associated with the development of preeclampsia. Medicine. 2019; 98: e15080.","DOI":"10.1097\/MD.0000000000015080"},{"key":"ref41","doi-asserted-by":"crossref","unstructured":"Iriyama T, Wang W, Parchim NF, Song A, Blackwell SC, Sibai BM, et al. Hypoxia-independent upregulation of placental hypoxia inducible factor-1\u03b1 gene expression contributes to the pathogenesis of preeclampsia. Hypertension (Dallas, Tex.: 1979). 2015; 65: 1307\u20131315.","DOI":"10.1161\/HYPERTENSIONAHA.115.05314"},{"key":"ref42","doi-asserted-by":"crossref","unstructured":"Bellot G, Garcia-Medina R, Gounon P, Chiche J, Roux D, Pouyss\u00e9gur J, et al. Hypoxia-induced autophagy is mediated through hypoxia-inducible factor induction of BNIP3 and BNIP3L via their BH3 domains. Molecular and Cellular Biology. 2009; 29: 2570\u20132581.","DOI":"10.1128\/MCB.00166-09"},{"key":"ref43","doi-asserted-by":"crossref","unstructured":"Ge Y, Zhou M, Chen C, Wu X, Wang X. Role of AMPK mediated pathways in autophagy and aging. Biochimie. 2022; 195: 100\u2013113.","DOI":"10.1016\/j.biochi.2021.11.008"},{"key":"ref44","doi-asserted-by":"crossref","unstructured":"Fitzwalter BE, Thorburn A. FOXO3 links autophagy to apoptosis. Autophagy. 2018; 14: 1467\u20131468.","DOI":"10.1080\/15548627.2018.1475819"},{"key":"ref45","doi-asserted-by":"crossref","unstructured":"Correa PJ, Palmeiro Y, Soto MJ, Ugarte C, Illanes SE. Etiopathogenesis, prediction, and prevention of preeclampsia. Hypertension in Pregnancy. 2016; 35: 280\u2013294.","DOI":"10.1080\/10641955.2016.1181180"},{"key":"ref46","doi-asserted-by":"crossref","unstructured":"Cai H, Li D, Wu J, Shi C. miR-519d downregulates LEP expression to inhibit preeclampsia development. Open Medicine (Warsaw, Poland). 2021; 16: 1215\u20131227.","DOI":"10.1515\/med-2021-0244"},{"key":"ref47","doi-asserted-by":"crossref","unstructured":"Molvarec A, Szarka A, Walentin S, Beko G, Kar\u00e1di I, Proh\u00e1szka Z, et al. Serum leptin levels in relation to circulating cytokines, chemokines, adhesion molecules and angiogenic factors in normal pregnancy and preeclampsia. Reproductive Biology and Endocrinology: RB&E. 2011; 9: 124.","DOI":"10.1186\/1477-7827-9-124"},{"key":"ref48","doi-asserted-by":"crossref","unstructured":"He W, Wang Q, Xu J, Xu X, Padilla MT, Ren G, et al. Attenuation of TNFSF10\/TRAIL-induced apoptosis by an autophagic survival pathway involving TRAF2- and RIPK1\/RIP1-mediated MAPK8\/JNK activation. Autophagy. 2012; 8: 1811\u20131821.","DOI":"10.4161\/auto.22145"},{"key":"ref49","doi-asserted-by":"crossref","unstructured":"Zhang X, Zhang W, Ma SF, Desai AA, Saraf S, Miasniakova G, et al. Hypoxic response contributes to altered gene expression and precapillary pulmonary hypertension in patients with sickle cell disease. Circulation. 2014; 129: 1650\u20131658.","DOI":"10.1161\/CIRCULATIONAHA.113.005296"},{"key":"ref50","doi-asserted-by":"crossref","unstructured":"Steiner MK, Syrkina OL, Kolliputi N, Mark EJ, Hales CA, Waxman AB. Interleukin-6 overexpression induces pulmonary hypertension. Circulation Research. 2009; 104: 236\u201344, 28p following 244.","DOI":"10.1161\/CIRCRESAHA.108.182014"},{"key":"ref51","doi-asserted-by":"crossref","unstructured":"Yang N, Wang Q, Ding B, Gong Y, Wu Y, Sun J, et al. Expression profiles and functions of ferroptosis-related genes in the placental tissue samples of early- and late-onset preeclampsia patients. BMC Pregnancy and Childbirth. 2022; 22: 87.","DOI":"10.1186\/s12884-022-04423-6"},{"key":"ref52","doi-asserted-by":"crossref","unstructured":"Xiong J, Ding N, Gao T, Wang Y, Guo W, Zhang H, et al. Hypermethylation of endoplasmic reticulum disulfide oxidase 1\u03b1 leads to trophoblast cell apoptosis through endoplasmic reticulum stress in preeclampsia. Journal of Cellular Biochemistry. 2018; 119: 8588\u20138599.","DOI":"10.1002\/jcb.27101"}],"container-title":["Frontiers in Bioscience-Landmark"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.imrpress.com\/journal\/FBL\/28\/7\/10.31083\/j.fbl2807132","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T12:58:16Z","timestamp":1732712296000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.imrpress.com\/journal\/FBL\/28\/7\/10.31083\/j.fbl2807132"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,4]]},"references-count":52,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2023]]}},"alternative-id":["S2768-6701(23)00916-4"],"URL":"https:\/\/doi.org\/10.31083\/j.fbl2807132","relation":{},"ISSN":["2768-6701","2768-6698"],"issn-type":[{"type":"print","value":"2768-6701"},{"type":"electronic","value":"2768-6698"}],"subject":[],"published":{"date-parts":[[2023,7,4]]},"article-number":"132"}}