Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Basic Science Article
  • Published:

Sex differences in metabolic adaptation in infants with cyanotic congenital heart disease

Abstract

Background

Female infants with congenital heart disease (CHD) face significantly higher postoperative mortality rates after adjusting for cardiac complexity. Sex differences in metabolic adaptation to cardiac stressors may be an early contributor to cardiac dysfunction. In adult diseases, hypoxic/ischemic cardiomyocytes undergo a cardioprotective metabolic shift from oxidative phosphorylation to glycolysis which appears to be regulated in a sexually dimorphic manner. We hypothesize sex differences in cardiac metabolism are present in cyanotic CHD and detectable as early as the infant period.

Methods

RNA sequencing was performed on blood samples (cyanotic CHD cases, n = 11; controls, n = 11) and analyzed using gene set enrichment analysis (GSEA). Global plasma metabolite profiling (UPLC-MS/MS) was performed using a larger representative cohort (cyanotic CHD, n = 27; non-cyanotic CHD, n = 11; unaffected controls, n = 12).

Results

Hallmark gene sets in glycolysis, fatty acid metabolism, and oxidative phosphorylation were significantly enriched in cyanotic CHD females compared to male counterparts, which was consistent with metabolomic differences between sexes. Minimal sex differences in metabolic pathways were observed in normoxic patients (both controls and non-cyanotic CHD cases).

Conclusion

These observations suggest underlying differences in metabolic adaptation to chronic hypoxia between males and females with cyanotic CHD.

Impact

  • Children with cyanotic CHD exhibit sex differences in utilization of glycolysis vs. fatty acid oxidation pathways to meet the high-energy demands of the heart in the neonatal period.

  • Transcriptomic and metabolomic results suggest that under hypoxic conditions, males and females undergo metabolic shifts that are sexually dimorphic. These sex differences were not observed in neonates in normoxic conditions (i.e., non-cyanotic CHD and unaffected controls).

  • The involved metabolic pathways are similar to those observed in advanced heart failure, suggesting metabolic adaptations beginning in the neonatal period may contribute to sex differences in infant survival.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Comparison of differential expression of genes between cyanotic CHD females vs. males.
Fig. 2: Comparison of differential expression of genes between sexes.
Fig. 3: Overall group effects in plasma metabolic profiling between study groups.
Fig. 4: Normalized metabolite peak area levels among study groups of cyanotic congenital heart defect (C-CHD) and non-cyanotic CHD (NC-CHD) by sex (F, female; M, male).
Fig. 5: Comparison of metabolic levels in fold of change (FC) between cyanotic and non-cyanotic congenital heart defect patients by sex (F, female; M, male) in interrelated metabolic pathways (glycolysis, citric acid or TCA cycle, fatty acid oxidation, and glutamine metabolism).

Similar content being viewed by others

Data availability

The datasets generated during and/or analyzed during the current study are available in the Gene Expression Omnibus (GEO) link pending.

References

  1. Liu, Y. et al. Global birth prevalence of congenital heart defects 1970-2017: updated systematic review and meta-analysis of 260 studies. Int. J. Epidemiol. 48, 455–463, https://doi.org/10.1093/ije/dyz009 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Ohye, R. G., Schranz, D. & D’Udekem, Y. Current therapy for hypoplastic left heart syndrome and related single ventricle lesions. Circulation 134, 1265–1279, https://doi.org/10.1161/CIRCULATIONAHA.116.022816 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Oster, M. E. et al. Temporal trends in survival among infants with critical congenital heart defects. Pediatrics 131, e1502–e1508, https://doi.org/10.1542/peds.2012-3435 (2013).

    Article  PubMed  Google Scholar 

  4. Gilboa, S. M., Salemi, J. L., Nembhard, W. N., Fixler, D. E. & Correa, A. Mortality resulting from congenital heart disease among children and adults in the United States, 1999 to 2006. Circulation 122, 2254–2263, https://doi.org/10.1161/CIRCULATIONAHA.110.947002 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Kochilas, L. K., Vinocur, J. M. & Menk, J. S. Age-dependent sex effects on outcomes after pediatric cardiac surgery. J. Am. Heart Assoc. 3, e000608, https://doi.org/10.1161/JAHA.113.000608 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Chang, R. K. R., Chen, A. Y. & Klitzner, T. S. Female sex as a risk factor for in-hospital mortality among children undergoing cardiac surgery. Circulation 106, 1514–1522, https://doi.org/10.1161/01.CIR.0000029104.94858.6F (2002).

    Article  PubMed  Google Scholar 

  7. Seifert, H. A., Howard, D. L., Silber, J. H. & Jobes, D. R. Female gender increases the risk of death during hospitalization for pediatric cardiac surgery. J. Thorac. Cardiovasc. Surg. 133, 668–675, https://doi.org/10.1016/j.jtcvs.2006.11.014 (2007).

    Article  PubMed  Google Scholar 

  8. Puente, B. N. et al. The oxygen-rich postnatal environment induces cardiomyocyte cell-cycle arrest through DNA damage response. Cell 157, 565–579, https://doi.org/10.1016/j.cell.2014.03.032 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Semenza, G. L., Roth, P. H., Fang, H. M. & Wang, G. L. Transcriptional regulation of genes encoding glycolytic enzymes by hypoxia-inducible factor 1. J. Biol. Chem. 269, 23757–23763, https://doi.org/10.1016/S0021-9258(17)31580-6 (1994).

    Article  CAS  PubMed  Google Scholar 

  10. Semenza, G. L. et al. Hypoxia response elements in the aldolase A, enolase 1, and lactate dehydrogenase a gene promoters contain essential binding sites for hypoxia-inducible factor 1. J. Biol. Chem. 271, 32529–32537, https://doi.org/10.1074/JBC.271.51.32529 (1996).

    Article  CAS  PubMed  Google Scholar 

  11. Wang, G. L., Jiang, B. H., Rue, E. A. & Semenza, G. L. Hypoxia-inducible factor 1 is a basic-helix-loop-helix-PAS heterodimer regulated by cellular O2 tension. Proc. Natl Acad. Sci. USA 92, 5510–5514, https://doi.org/10.1073/pnas.92.12.5510 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Karwi, Q. G., Uddin, G. M., Ho, K. L. & Lopaschuk, G. D. Loss of metabolic flexibility in the failing heart. Front. Cardiovasc. Med. 5, 68, https://doi.org/10.3389/fcvm.2018.00068 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Lee, J. W., Ko, J., Ju, C. & Eltzschig, H. K. Hypoxia signaling in human diseases and therapeutic targets. Exp. Mol. Med. 51, 1–13, https://doi.org/10.1038/s12276-019-0235-1 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Lopaschuk, G. D., Collins-Nakai, R. L. & Itoi, T. Developmental changes in energy substrate use by the heart. Cardiovasc. Res. 26, 1172–1180, https://doi.org/10.1093/cvr/26.12.1172 (1992).

    Article  CAS  PubMed  Google Scholar 

  15. Eckersley, L. G. et al. The perinatal transition and early neonatal period in hypoplastic left heart syndrome is associated with reduced systemic and cerebral perfusion. Can. J. Cardiol. 37, 1923–1933, https://doi.org/10.1016/j.cjca.2021.07.002 (2021).

    Article  PubMed  Google Scholar 

  16. Neely, J. R. & Morgan, H. E. Relationship between carbohydrate and lipid metabolism and the energy balance of heart muscle. Annu. Rev. Physiol. 36, 413–459, https://doi.org/10.1146/annurev.ph.36.030174.002213 (1974).

    Article  CAS  PubMed  Google Scholar 

  17. Cole, M. A. et al. On the pivotal role of PPARa in adaptation of the heart to hypoxia and why fat in the diet increases hypoxic injury. FASEB J. 30, 2684–2697, https://doi.org/10.1096/fj.201500094R (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Murphy, E., Amanakis, G., Fillmore, N., Parks, R. J. & Sun, J. Sex differences in metabolic cardiomyopathy. Cardiovasc. Res. 113, 370–377, https://doi.org/10.1093/cvr/cvx008 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Kim, J. W., Tchernyshyov, I., Semenza, G. L. & Dang, C. V. HIF-1-mediated expression of pyruvate dehydrogenase kinase: A metabolic switch required for cellular adaptation to hypoxia. Cell Metab. 3, 177–185, https://doi.org/10.1016/J.CMET.2006.02.002 (2006).

    Article  PubMed  Google Scholar 

  20. Naumenko, N. et al. PGC-1α deficiency reveals sex-specific links between cardiac energy metabolism and EC-coupling during development of heart failure in mice. Cardiovasc. Res. 118, 1520–1534, https://doi.org/10.1093/cvr/cvab188 (2022).

    Article  CAS  PubMed  Google Scholar 

  21. Murphy, E. & Steenbergen, C. Gender-based differences in mechanisms of protection in myocardial ischemia-reperfusion injury. Cardiovasc. Res. 75, 478–486, https://doi.org/10.1016/j.cardiores.2007.03.025 (2007).

    Article  CAS  PubMed  Google Scholar 

  22. Broderick, T. L. & Glick, B. Effect of gender and fatty acids on ischemic recovery of contractile and pump function in the rat heart. Gend. Med. 1, 86–99, https://doi.org/10.1016/s1550-8579(04)80014-7 (2004).

    Article  PubMed  Google Scholar 

  23. Wang, T. et al. Estrogen-related receptor α (ERRα) and ERRγ are essential coordinators of cardiac metabolism and function. Mol. Cell Biol. 35, 1281–1298, https://doi.org/10.1128/MCB.01156-14 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Watson, P. A. et al. Cardiac-specific overexpression of dominant-negative CREB leads to increased mortality and mitochondrial dysfunction in female mice. Am. J. Physiol. Heart Circ. Physiol. 299, 2056–2068, https://doi.org/10.1152/ajpheart.00394.2010.-Cardiac (2010).

    Article  Google Scholar 

  25. Pagano, E. et al. Alterations in metabolites associated with hypoxemia in neonates and infants with congenital heart disease. Congenit. Heart Dis. 15, 251–265, https://doi.org/10.32604/CHD.2020.012219 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Correia, G. D. S. et al. Metabolic profiling of children undergoing surgery for congenital heart disease. Crit. Care Med. 43, 1467–1476, https://doi.org/10.1097/CCM.0000000000000982 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Heibel, J. et al. Perioperative metabolites are associated with adverse neonatal congenital heart disease surgical outcomes. J. Am. Heart Assoc. J. Am. Heart Assoc. 11, 24996, https://doi.org/10.1161/JAHA.121.024996 (2022).

    Article  Google Scholar 

  28. Davidson, J. A. et al. Metabolomic fingerprinting of infants undergoing cardiopulmonary bypass: changes in metabolic pathways and association with mortality and cardiac intensive care unit length of stay. J. Am. Heart Assoc. 7, e010711, https://doi.org/10.1161/JAHA.118.010711 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Davidson, J. A. et al. Serum metabolic profile of postoperative acute kidney injury following infant cardiac surgery with cardiopulmonary bypass. Pediatr. Nephrol. 36, 3259–3269, https://doi.org/10.1007/s00467-021-05095-8/Published (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10–12, http://www-huber.embl.de/users/an- (2011).

    Article  Google Scholar 

  31. Dobin, A. et al. Sequence analysis STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21, https://doi.org/10.1093/bioinformatics/bts635 (2013).

    Article  CAS  PubMed  Google Scholar 

  32. Anders, S. & Huber, W. Differential expression analysis for sequence count data. Genome Biol. 11, R106, https://doi.org/10.1186/gb-2010-11-10-r106 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550, https://doi.org/10.1073/pnas.0506580102 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Mootha, V. K. et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat. Genet. 34, 267–273, https://doi.org/10.1038/ng1180 (2003).

    Article  CAS  PubMed  Google Scholar 

  35. Liberzon, A. et al. The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst. 1, 417–425, https://doi.org/10.1016/j.cels.2015.12.004 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Shi, M. W. et al. SAGD: a comprehensive sex-associated gene database from transcriptomes. Nucleic Acids Res. 47, D835–D840, https://doi.org/10.1093/nar/gky1040 (2019).

    Article  CAS  PubMed  Google Scholar 

  37. Montaigne, D., Butruille, L. & Staels, B. PPAR control of metabolism and cardiovascular functions. Nat. Rev. Cardiol. 18, 809–823, https://doi.org/10.1038/s41569-021-00569-6 (2021).

    Article  CAS  PubMed  Google Scholar 

  38. Palekar, A. G., Tate, S. S., Meister, A. Formation of 5-Oxoproline from Glutathione in Erythrocytes by the 7-Glutamyltranspeptidase-Cyclotransferase Pathway (Pyroglutamate/Pyrrolidone Carboxylate/7y-Glutamyl Cycle/-y-Glutamyl Cyclotransferase). Vol 71.; 1974. https://www.pnas.org

  39. Rogatzki, M. J., Ferguson, B. S., Goodwin, M. L. & Gladden, L. B. Lactate is always the end product of glycolysis. Front. Neurosci. 9, 22, https://doi.org/10.3389/fnins.2015.00022 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Watanabe, K. et al. Critical role of glutamine metabolism in cardiomyocytes under oxidative stress. Biochem. Biophys. Res. Commun. 534, 687–693, https://doi.org/10.1016/j.bbrc.2020.11.018 (2021).

    Article  CAS  PubMed  Google Scholar 

  41. Angelini, A. et al. PHDs/CPT1B/VDAC1 axis regulates long-chain fatty acid oxidation in cardiomyocytes. Cell Rep. 37, 109767, https://doi.org/10.1016/j.celrep.2021.109767 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Makrecka-Kuka, M. et al. Plasma acylcarnitine concentrations reflect the acylcarnitine profile in cardiac tissues. Sci. Rep. 7, 17528, https://doi.org/10.1038/s41598-017-17797-x (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Krishnan, J. et al. Activation of a HIF1α-PPARγ axis underlies the integration of glycolytic and lipid anabolic pathways in pathologic cardiac hypertrophy. Cell Metab. 9, 512–524, https://doi.org/10.1016/j.cmet.2009.05.005 (2009).

    Article  CAS  PubMed  Google Scholar 

  44. Fuhrmann, D. C. et al. Chronic hypoxia enhances β-oxidation-dependent electron transport via electron transferring flavoproteins. Cells 8, 1–18, https://doi.org/10.3390/cells8020172 (2019).

    Article  CAS  Google Scholar 

  45. Wittnich, C., Quaglietta, D., Tan, L. & Belanger, M. P. Sex differences in newborn myocardial metabolism and response to ischemia. Pediatr. Res 70, 148–152, https://doi.org/10.1203/PDR.0b013e3182218c6c (2011).

    Article  CAS  PubMed  Google Scholar 

  46. Trexler, C. L., Odell, A. T., Jeong, M. Y., Dowell, R. D. & Leinwand, L. A. Transcriptome and functional profile of cardiac myocytes is influenced by biological sex. Circ. Cardiovasc. Genet. 10, e001770, https://doi.org/10.1161/CIRCGENETICS.117.001770 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Ritterhoff, J. et al. Increasing fatty acid oxidation elicits a sex-dependent response in failing mouse hearts. J. Mol. Cell Cardiol. 158, 1–10, https://doi.org/10.1016/j.yjmcc.2021.05.004 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Smith, K. L. M. et al. Chronic developmental hypoxia alters mitochondrial oxidative capacity and reactive oxygen species production in the fetal rat heart in a sex-dependent manner. J. Pineal Res. https://doi.org/10.1111/jpi.12821 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Neary, M. T. et al. Hypoxia signaling controls postnatal changes in cardiac mitochondrial morphology and function. J. Mol. Cell Cardiol. 74, 340–352, https://doi.org/10.1016/j.yjmcc.2014.06.013 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Tan, M. et al. Glutathione system enhancement for cardiac protection: pharmacological options against oxidative stress and ferroptosis. Cell Death Dis. 14, 131, https://doi.org/10.1038/s41419-023-05645-y (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Ip, W. T. K. et al. Dietary omega-6 fatty acid replacement selectively impairs cardiac functional recovery after ischemia in female (but not male) rats. Am. J. Physiol. Heart Circ. Physiol. 311, H768–H780, https://doi.org/10.1152/ajpheart.00690.2015 (2016).

    Article  PubMed  Google Scholar 

  52. Harrington, J. et al. A systems biology approach to investigating sex differences in cardiac hypertrophy. J. Am. Heart Assoc. 6, e005838, https://doi.org/10.1161/JAHA.117.005838 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Djouadi, F. et al. A gender-related defect in lipid metabolism and glucose homeostasis in peroxisome proliferator-activated receptor α-deficient mice. J. Clin. Investig. 102, 1083–1091, https://doi.org/10.1172/JCI3949 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Sihag, S., Cresci, S., Li, A. Y., Sucharov, C. C. & Lehman, J. J. PGC-1α and ERRα target gene downregulation is a signature of the failing human heart. J. Mol. Cell Cardiol. 46, 201–212, https://doi.org/10.1016/j.yjmcc.2008.10.025 (2009).

    Article  CAS  PubMed  Google Scholar 

  55. Xu, X. et al. Uncompensated mitochondrial oxidative stress underlies heart failure in an iPSC-derived model of congenital heart disease. Cell Stem Cell 29, 840–855.e7, https://doi.org/10.1016/j.stem.2022.03.003 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Dong, S. et al. Metabolic profile of heart tissue in cyanotic congenital heart disease. Am. J. Transl. Res. 13, 4224–4232 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Liu, Y. et al. Suppression of myocardial hypoxia-inducible factor-1α compromises metabolic adaptation and impairs cardiac function in patients with cyanotic congenital heart disease during puberty. Circulation 143, 2254–2272, https://doi.org/10.1161/CIRCULATIONAHA.120.051937 (2021).

    Article  CAS  PubMed  Google Scholar 

  58. Liu, J. et al. Metabolic variation dictates cardiac pathogenesis in patients with tetralogy of fallot. Front. Pediatr. 9, 819195, https://doi.org/10.3389/fped.2021.819195 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Najm, H. K. et al. Does the degree of cyanosis affect myocardial adenosine triphosphate levels and function in children undergoing surgical procedures for congenital heart disease? J. Thorac. Cardiovasc. Surg. 119, 515–524, https://doi.org/10.1067/mtc.2000.104339 (2000).

    Article  CAS  PubMed  Google Scholar 

  60. Jain, P. N. et al. Altered metabolic and inflammatory transcriptomics after cardiac surgery in neonates with congenital heart disease. Sci. Rep. 11, 4965, https://doi.org/10.1038/s41598-021-83882-x (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Bruder, E. D. & Raff, H. Cardiac and plasma lipid profiles in response to acute hypoxia in neonatal and young adult rats. Lipids Health Dis. 9, 3, https://doi.org/10.1186/1476-511X-9-3 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Harris, P. A. et al. Research electronic data capture (REDCap) - A metadata-driven methodology and workflow process for providing translational research informatic support. J. Biomed. Inf. 42, 377–381, https://doi.org/10.1016/j.jbi.2008.08.010 (2009).

    Article  Google Scholar 

Download references

Acknowledgements

We thank the technical support from the Cancer Prevention and Research Institute of Texas (CPRIT RP180734). This work was supported by NIH/NCATS grants UL1 TR000445 and UL1 TR001105. Study data were collected and managed using REDCap electronic data capture tools hosted at The University of Texas School of Biomedical Informatics (SBMI) at Houston.62 REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing (1) an intuitive interface for validated data entry; (2) audit trails for tracking data manipulation and export procedures; (3) automated export procedures for seamless data downloads to common statistical packages; and (4) procedures for importing data from external sources. T.O.F. was supported by the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, through UTHealth-CCTS Grant Number UL1TR003167 and by 5KL2TR003168-02. A.C.P. was supported by NIH K01HL159032, R01HL148191, and U54GM115428. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.

Author information

Authors and Affiliations

Authors

Contributions

T.O.F. and L.M. conceived and planned the experiments, T.O.F. carried out the experiments. A.C.P., G.M., and J.S. provided the samples. Z.Z., K.S.C., and C.S. analyzed and interpreted the data and produced the figures. T.O.F. drafted the manuscript and all authors contributed to the final manuscript.

Corresponding author

Correspondence to Tina O. Findley.

Ethics declarations

Competing interests

The authors declare no competing interests

Informed consent

Parental permission was obtained for patient participation for each respective institutional biorepository.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Findley, T.O., Palei, A.C., Cho, K.S. et al. Sex differences in metabolic adaptation in infants with cyanotic congenital heart disease. Pediatr Res (2024). https://doi.org/10.1038/s41390-024-03291-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41390-024-03291-4

Search

Quick links