Integrating Angiogenic, Inflamatory and Molecular Biomarkers for Early Prediction of Preeclampsia : A Comprehensive Systematic Review
Keywords:
Preeclampsia, biomarkers, sFlt-1/PlGF ratio, early prediction, multi-marker models, angiogenesisAbstract
Background: Preeclampsia (PE) is a leading cause of maternal and perinatal morbidity and mortality worldwide. Early prediction remains challenging due to its multifactorial pathophysiology. This systematic review evaluates the predictive performance of angiogenic, inflammatory, and molecular biomarkers for early PE prediction.
Methods: We screened 80 studies (that examined biomarkers in pregnant women, reported predictive accuracy, and included comparison groups. Data extraction focused on single and multi-marker performance, prediction timing, and clinical applicability.
Results: Angiogenic markers were most studied. Low PlGF and elevated sFlt-1 consistently predicted PE, with the sFlt-1/PlGF ratio showing pooled sensitivity 80%, specificity 92% (AUC 0.90–0.95). For short-term rule-out, sFlt-1/PlGF ≤38 had 99.3% negative predictive value for PE within one week. First-trimester multi-omics models (e.g., leptin/ceramide ratio, cell-free RNA panels) achieved AUC 0.85–0.94, detecting risk up to 18 weeks before onset. Inflammatory markers (CA-125, IL-6, TNF-α) and molecular markers (microRNAs, MMP-7, PAPP-A) showed moderate individual performance but improved in combination. Early-onset PE was more accurately predicted than late-onset disease. Machine learning and multi-marker integration consistently outperformed single biomarkers.
Discussion: The sFlt-1/PlGF ratio is the most clinically validated biomarker for short-term rule-out in symptomatic women. First-trimester multi-marker screening enables aspirin prophylaxis in high-risk women. However, standardization, cost-effectiveness, and population-specific validation remain challenges.
Conclusion: Integrating angiogenic, inflammatory, and molecular biomarkers significantly improves early PE prediction compared to single markers. The sFlt-1/PlGF ratio is ready for clinical use for short-term prediction. Future research should validate multi-omics panels in diverse populations and integrate placental pathology.
References
S. Agrawal, A. Cerdeira, C. Redman, M. Vatish (2018) Meta-Analysis and Systematic Review to Assess the Role of Soluble FMS-Like Tyrosine Kinase-1 and Placenta Growth Factor Ratio in Prediction of Preeclampsia: The SaPPPhirE Study. HYPERTENSION. https://doi.org/10.1161/HYPERTENSIONAHA.117.10182
C. Chirilă, C. Mǎrginean, P. Chirilă, M. Gliga (2023) The Current Role of the sFlt-1/PlGF Ratio and the Uterine–Umbilical–Cerebral Doppler Ultrasound in Predicting and Monitoring Hypertensive Disorders of Pregnancy: An Update with a Review of the Literature. Children. https://doi.org/10.3390/children10091430
P. Chaemsaithong, M. Gil, N. Chaiyasit, et al (2023) Accuracy of placental growth factor alone or in combination with soluble fms-like tyrosine kinase-1 or maternal factors in detecting preeclampsia in asymptomatic women in the second and third trimesters: a systematic review and meta-analysis. American Journal of Obstetrics and Gynecology. https://doi.org/10.1016/j.ajog.2023.03.032
R. Allen, E. Rogozińska, Kirsty Cleverly, et al (2014) Abnormal blood biomarkers in early pregnancy are associated with preeclampsia: a meta-analysis. European Journal of Obstetrics, Gynecology, and Reproductive Biology. https://doi.org/10.1016/j.ejogrb.2014.09.027
K. Ferguson, J. Meeker, T. McElrath, et al (2017) Repeated measures of inflammation and oxidative stress biomarkers in preeclamptic and normotensive pregnancies. American Journal of Obstetrics and Gynecology. https://doi.org/10.1016/j.ajog.2016.12.174
D. Carty, J. Brennand, J. McCulloch, et al (2010) FIRST TRIMESTER E-SELECTIN LEVELS PREDICT PRE-ECLAMPSIA: PP.12.468. Journal of Hypertension. https://doi.org/10.1097/01.hjh.0000378793.32863.b2
Qianyang Huang, Shiying Hao, Jin You, et al (2021) Early-pregnancy prediction of risk for pre-eclampsia using maternal blood leptin/ceramide ratio: discovery and confirmation. BMJ Open. https://doi.org/10.1136/bmjopen-2021-050963
Taishun Li, Mingyang Xu, Yuan Wang, et al (2024) Prediction model of preeclampsia using machine learning based methods: a population based cohort study in China. Frontiers in Endocrinology. https://doi.org/10.3389/fendo.2024.1345573
N. Castillo Marco, T. Cordero, M. Igual, et al (2025) O-089 Maternal plasma cell-free RNA as a liquid biopsy for first-trimester screening of early and late-onset preeclampsia. Human Reproduction. https://doi.org/10.1093/humrep/deaf097.089
I. Marić, K. Contrepois, M. Moufarrej, et al (2022) Early prediction and longitudinal modeling of preeclampsia from multiomics. Patterns. https://doi.org/10.1016/j.patter.2022.100655
A. Tarca, R. Romero, N. BENSHALOM-TIROSH, et al (2019) The prediction of early preeclampsia: Results from a longitudinal proteomics study. PLoS ONE. https://doi.org/10.1371/journal.pone.0217273
O. Erez, R. Romero, E. Maymon, et al (2017) The prediction of late-onset preeclampsia: Results from a longitudinal proteomics study. PLoS ONE. https://doi.org/10.1371/journal.pone.0181468
Lucie Roubalova, V. Kroutilova, Maria Fernanda Lopez-G Tinajero, et al (2024) Added Value in Low-Risk Pregnancies of Longitudinal Changes in Uterine Doppler and Circulating Angiogenic Factors during the Third Trimester in Predicting Term Preeclampsia. Fetal Diagnosis and Therapy. https://doi.org/10.1159/000541731
V. Bucher, A. R. Mitchell, Pia Gudmundsson, et al (2024) Prediction of adverse maternal and perinatal outcomes associated with pre-eclampsia and hypertensive disorders of pregnancy: a systematic review and meta-analysis. EClinicalMedicine. https://doi.org/10.1016/j.eclinm.2024.102861
J. Allotey, Kym I. E. Snell, M. Smuk, et al (2020) Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: an individual participant data meta-analysis. Health Technology Assessment. https://doi.org/10.3310/hta24720
A. Staff, Ó. Burke, S. Benton, et al (2013) Maternal circulating PlGF concentrations and placenta-related pregnancy complications: First results from the CoLab AngF Study. Pregnancy Hypertension. https://doi.org/10.1016/j.preghy.2013.04.007
Pensée Wu, C. B. van den Berg, Z. Alfirevic, et al (2015) Early Pregnancy Biomarkers in Pre-Eclampsia: A Systematic Review and Meta-Analysis. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms160923035
Jessica J Miller, V. Higgins, N. Melamed, et al (2023) Clinical Validation of the sFlt-1:PlGF Ratio as a Biomarker for Preeclampsia Diagnosis in a High-Risk Obstetrics Unit. The Journal of Applied Laboratory Medicine. https://doi.org/10.1093/jalm/jfad003
F. Schneuer, Natasha Nassar, Amina Khambalia, et al (2012) First trimester screening of maternal placental protein 13 for predicting preeclampsia and small for gestational age: in-house study and systematic review. Placenta. https://doi.org/10.1016/j.placenta.2012.05.012
J. Kusanovic, R. Romero, T. Chaiworapongsa, et al (2009) A prospective cohort study of the value of maternal plasma concentrations of angiogenic and anti-angiogenic factors in early pregnancy and midtrimester in the identification of patients destined to develop preeclampsia. Journal of Maternal-Fetal & Neonatal Medicine. https://doi.org/10.3109/14767050902994754
Shiting Qin, Ningxia Sun, Longqiang Xu, et al (2021) The Value of Circulating microRNAs for Diagnosis and Prediction of Preeclampsia: a Meta-analysis and Systematic Review. Reproductive Sciences. https://doi.org/10.1007/s43032-021-00799-6
A. Tarca, R. Romero, O. Erez, et al (2020) Maternal whole blood mRNA signatures identify women at risk of early preeclampsia: a longitudinal study. Journal of Maternal-Fetal & Neonatal Medicine. https://doi.org/10.1080/14767058.2019.1685964
R. Gonen, R. Shahar, Y. Grimpel, et al (2009) Placental Protein 13 as an Early Marker for Preeclampsia: A Prospective Longitudinal Study. Obstetric Anesthesia Digest. https://doi.org/10.1097/01.AOA.0000362086.72838.61
I. J. Andresen, M. Zucknick, M. L. Degnes, et al (2024) Prediction of late-onset preeclampsia using plasma proteomics: a longitudinal multi-cohort study. Scientific Reports. https://doi.org/10.1038/s41598-024-81277-2
K. Evers, A. Atkinson, Christian Barro, et al (2018) Neurofilament as Neuronal Injury Blood Marker in Preeclampsia. HYPERTENSION. https://doi.org/10.1161/HYPERTENSIONAHA.117.10314
M. Ozat, Mine Kanat-Pektas, O. Yenicesu, et al (2011) Serum concentrations of CA-125 in normal and preeclamptic pregnancies. Archives of Gynecology and Obstetrics. https://doi.org/10.1007/s00404-010-1736-2
I. Hromadníková, K. Kotlabova, K. Ivankova, L. Krofta (2017) First trimester screening of circulating C19MC microRNAs and the evaluation of their potential to predict the onset of preeclampsia and IUGR. PLoS ONE. https://doi.org/10.1371/journal.pone.0171756
I. Vasilache, A. Cărăuleanu, D. Socolov, et al (2022) Predictive performance of first trimester serum galectin-13/PP-13 in preeclampsia screening: A systematic review and meta-analysis. Experimental and Therapeutic Medicine. https://doi.org/10.3892/etm.2022.11297
Alexandre Fillion, A. Boutin, C. Gasse, et al (2022) First-trimester placental soluble fms-like tyrosine kinase 1 (sFlt-1) for the prediction of preeclampsia. American Journal of Obstetrics and Gynecology. https://doi.org/10.1016/j.ajog.2021.11.584
Iasmina M. Craici, S. Wagner, K. Bailey, et al (2013) Podocyturia Predates Proteinuria and Clinical Features of Preeclampsia: Longitudinal Prospective Study. HYPERTENSION. https://doi.org/10.1161/HYPERTENSIONAHA.113.01115
Robin Shoemaker, Marko Poglitsch, Hong Huang, et al (2025) Abstract 064: Application of Angiotensin-Based Biomarkers Quantified by Mass Spectrometry to Predict Preeclampsia. HYPERTENSION. https://doi.org/10.1161/hyp.82.suppl_1.064
Aimal Mangsang Sangma, A. Ruram, W. Shullai, Polina Boruah (2025) Role of soluble fms-like tyrosine kinase-1/placental growth factor ratio as an early predictor of preeclampsia in pregnant women. Journal of Laboratory Physicians. https://doi.org/10.25259/jlp_127_2025
Jian-bo Zhang, Wei-Chi She, J. Yue, et al (2020) Early Prediction of Preeclampsia by Using Serum Human Leukocyte Antigen G: A Retrospective Case-Control Study Followed by a Prospective Unselected Cohort Study. Social Science Research Network. https://doi.org/10.2139/ssrn.3741242
S. Daskalopoulou, Kim Phan, I. Schiller, et al (2023) S-11-1: ARTERIAL STIFFNESS AND HEMODYNAMIC PARAMETERS FOR THE EARLY PREDICTION OF PREECLAMPSIA: A PROSPECTIVE COHORT STUDY. Journal of Hypertension. https://doi.org/10.1097/01.hjh.0000913012.20678.63
E. Reyna-Villasmil, Jorly Mejía-Montilla, Joel Santos-Bolívar, et al (2017) Angiopoyetina-2 plasmática en el segundo trimestre, como predictor del desarrollo de preeclampsia. Revista Peruana de Ginecología y Obstetricia. https://doi.org/10.31403/RPGO.V63I1959
Qianyang Huang, Shiying Hao, Jin You, et al (2021) Case finding of early pregnancies at risk of preeclampsia using maternal blood leptin/ceramide ratio: multi-omics discovery and validation from a longitudinal study. https://doi.org/10.22541/AU.161111178.89108280/V1
K. De Clippel, M. Wijman, P. Struijk, et al (2006) OC102: Longitudinal observation of the human yolk sac, yolk sac and fetoplacental hemodynamics: preliminary results. Ultrasound in Obstetrics and Gynecology. https://doi.org/10.1002/uog.2962
O. Erez, F. Gotsch, Eunjung Jung, et al (2022) Perturbations in the kinetics of the thrombin generation assay identify women at risk for preeclampsia in the first trimester and provide a rationale for a preventive approach. American Journal of Obstetrics and Gynecology. https://doi.org/10.1016/j.ajog.2022.11.1276
Aiqi Yin, Yixuan Chen, Huafan Zhang, et al (2025) Increased first-trimester CA125 levels associated with the development of preeclampsia. Journal of Translational Medicine. https://doi.org/10.1186/s12967-025-07565-1
W. F. Gharib, Khaled Ahmed Atwa, Naglaa E. Salem, et al (2025) Assessment of Maternal Serum Netrin-1 as a New Biomarker of Preeclampsia. The Egyptian Journal of Fertility and Sterility. https://doi.org/10.21608/egyfs.2025.469371
Y. Giguère, M. Charland, E. Bujold, et al (2010) Combining biochemical and ultrasonographic markers in predicting preeclampsia: a systematic review. Clinical Chemistry. https://doi.org/10.1373/clinchem.2009.134080
C. Kleinrouweler, M. Wiegerinck, C. Ris-Stalpers, et al (2012) Accuracy of circulating placental growth factor, vascular endothelial growth factor, soluble fms‐like tyrosine kinase 1 and soluble endoglin in the prediction of pre‐eclampsia: a systematic review and meta‐analysis. BJOG: an International Journal of Obstetrics and Gynaecology. https://doi.org/10.1111/j.1471-0528.2012.03311.x
Marianna Danielli, R. Thomas, C. Gillies, et al (2022) Blood biomarkers to predict the onset of pre-eclampsia: A systematic review and meta-analysis. Heliyon. https://doi.org/10.1016/j.heliyon.2022.e11226
Y. Veisani, E. Jenabi, A. Delpisheh, S. Khazaei (2019) Angiogenic factors and the risk of preeclampsia: A systematic review and meta-analysis. International Journal of Reproductive BioMedicine. https://doi.org/10.18502/ijrm.v17i1.3815
Y. Giguère, M. Charland, E. Bujold, et al (2011) [Combining biochemical and ultrasonographic markers in predicting preeclampsia: a systematic review]. Annales de Biologie Clinique. https://doi.org/10.1684/abc.2011.0572
R. Romero, J. Nien, J. Espinoza, et al (2008) A longitudinal study of angiogenic (placental growth factor) and anti-angiogenic (soluble endoglin and soluble vascular endothelial growth factor receptor-1) factors in normal pregnancy and patients destined to develop preeclampsia and deliver a small for gestational age neonate. Journal of Maternal-Fetal & Neonatal Medicine. https://doi.org/10.1080/14767050701830480
A. Tarca, Andreea B. Taran, R. Romero, et al (2021) Prediction of preeclampsia throughout gestation with maternal characteristics and biophysical and biochemical markers: a longitudinal study. American Journal of Obstetrics and Gynecology. https://doi.org/10.1016/J.AJOG.2021.01.020
G. Lambert-Messerlian, E. Eklund, E. Chien, et al (2014) Use of first or second trimester serum markers, or both, to predict preeclampsia. Pregnancy Hypertension. https://doi.org/10.1016/j.preghy.2014.07.001
K. Hymavathi, Bhaavya Paturi, Duvvuru Akshitha, K. Sravya (2021) Preeclampsia prediction –First trimester screening markers. Indian Journal of Obstetrics and Gynecology Research. https://doi.org/10.18231/J.IJOGR.2021.046
J. Forest, J. Masse, E. Bujold, et al (2012) OS090. Performance of candidate clinical and biochemical markers in screening early in pregnancy to detect women at high risk to develop preeclampsia. Pregnancy Hypertension. https://doi.org/10.1016/j.preghy.2012.04.091
T. Metz, A. Allshouse, A. Euser, K. Heyborne (2014) Preeclampsia in high risk women is characterized by risk group-specific abnormalities in serum biomarkers. American Journal of Obstetrics and Gynecology. https://doi.org/10.1016/j.ajog.2014.04.027
Sean-Tee Lim, Wentao Li, J. Kemper, et al (2020) Biomarkers and the Prediction of Adverse Outcomes in Preeclampsia: A Systematic Review and Meta-analysis. Obstetrics and Gynecology. https://doi.org/10.1097/AOG.0000000000004149
R. Levine, C. Lam, Cong Qian, et al (2007) Soluble endoglin and other circulating antiangiogenic factors in preeclampsia. Obstetrical & Gynecological Survey. https://doi.org/10.1097/01.OGX.0000253489.32189.4D
O. Erez, R. Romero, J. Espinoza, et al (2008) The change in concentrations of angiogenic and anti-angiogenic factors in maternal plasma between the first and second trimesters in risk assessment for the subsequent development of preeclampsia and small-for-gestational age. Journal of Maternal-Fetal & Neonatal Medicine. https://doi.org/10.1080/14767050802034545
A. Cohen, J. Wenger, T. James-Todd, et al (2013) The association of circulating angiogenic factors and HbA1c with the risk of preeclampsia in women with preexisting diabetes. Hypertension in Pregnancy. https://doi.org/10.3109/10641955.2013.837175
Ruqaiya Shahid, M. F. Bari, Mehwish Hussain (2021) Serum biomarkers for the prediction and diagnosis of preeclampsia: A meta-analysis. Journal of Taibah University Medical Sciences. https://doi.org/10.1016/j.jtumed.2021.07.003
K. Nicolaides, D. Wright (2019) Re: Prediction of pre‐eclampsia: review of reviews. Ultrasound in Obstetrics and Gynecology. https://doi.org/10.1002/uog.20852
U. Perni, C. Sison, V. Sharma, et al (2012) Angiogenic Factors in Superimposed Preeclampsia: A Longitudinal Study of Women With Chronic Hypertension During Pregnancy. HYPERTENSION. https://doi.org/10.1161/HYPERTENSIONAHA.111.181735
J. Lai, A. Syngelaki, K. Nicolaides, et al (2022) Using ultrasound and angiogenic markers from a 19-23 week assessment to inform the subsequent diagnosis of preeclampsia. American Journal of Obstetrics and Gynecology. https://doi.org/10.1016/j.ajog.2022.03.007
T. McElrath, K. Lim, E. Paré, et al (2012) Longitudinal evaluation of predictive value for preeclampsia of circulating angiogenic factors through pregnancy. American Journal of Obstetrics and Gynecology. https://doi.org/10.1016/j.ajog.2012.08.010
Yangxue Yin, Min Liu, Hong-biao Yu, et al (2020) Circulating microRNAs as biomarkers for diagnosis and prediction of preeclampsia: A systematic review and meta-analysis. European Journal of Obstetrics, Gynecology, and Reproductive Biology. https://doi.org/10.1016/j.ejogrb.2020.08.016
M. Garcés, Elizabeth Sanchez, L. F. Cardona, et al (2015) Maternal Serum Meteorin Levels and the Risk of Preeclampsia. PLoS ONE. https://doi.org/10.1371/journal.pone.0131013
D. Rizos, M. Eleftheriades, Gregory Karampas, et al (2013) Placental growth factor and soluble fms-like tyrosine kinase-1 are useful markers for the prediction of preeclampsia but not for small for gestational age neonates: a longitudinal study. European Journal of Obstetrics, Gynecology, and Reproductive Biology. https://doi.org/10.1016/j.ejogrb.2013.08.040
K. Bramham, Paul Townsend Seed, L. Lightstone, et al (2016) Diagnostic and predictive biomarkers for pre-eclampsia in patients with established hypertension and chronic kidney disease. Kidney International. https://doi.org/10.1016/j.kint.2015.10.012
R. Kerley, Cathal M. McCarthy (2018) Biomarkers of glomerular dysfunction in pre-eclampsia - A systematic review. Pregnancy Hypertension. https://doi.org/10.1016/j.preghy.2018.03.002
A. Sahay, Vidya Patil, D. Sundrani, et al (2014) A longitudinal study of circulating angiogenic and antiangiogenic factors and AT1-AA levels in preeclampsia. Hypertension Research. https://doi.org/10.1038/hr.2014.71
M. L. Degnes, A. Westerberg, I. J. Andresen, et al (2024) Protein biomarker signatures of preeclampsia - a longitudinal 5000-multiplex proteomics study. Scientific Reports. https://doi.org/10.1038/s41598-024-73796-9
M. P. Lubis, H. Hariman, S. Lumbanraja, A. Bachtiar (2019) The Role of Placental Growth Factor, Soluble Endoglin, and Uterine Artery Diastolic Notch to Predict the Early Onset of Preeclampsia. Open Access Macedonian Journal of Medical Sciences. https://doi.org/10.3889/oamjms.2019.154
B. Sibai, M. Koch, S. Freire, et al (2008) Serum inhibin A and angiogenic factor levels in pregnancies with previous preeclampsia and/or chronic hypertension: are they useful markers for prediction of subsequent preeclampsia? American Journal of Obstetrics and Gynecology. https://doi.org/10.1016/j.ajog.2008.06.071
I. Tzanaki, A. Makrigiannakis, Charoula Lymperopoulou, et al (2025) Pregnancy-associated plasma protein A (PAPP-A) as a first trimester serum biomarker for preeclampsia screening: a systematic review and meta-analysis. Journal of Maternal-Fetal & Neonatal Medicine. https://doi.org/10.1080/14767058.2024.2448502
A. Doherty, J. Carvalho, S. Drewlo, et al (2014) Altered hemodynamics and hyperuricemia accompany an elevated sFlt-1/PlGF ratio before the onset of early severe preeclampsia. Journal of Obstetrics and Gynaecology Canada. https://doi.org/10.1016/S1701-2163(15)30511-9
K. Marrufo-Gallegos, J. R. Villafán-Bernal, S. Espino-Y-Sosa, et al (2023) Influential Serum Kinases (Non-sFlt-1) and Phosphatases in Preeclampsia—Systematic Review and Metanalysis. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms241612842
S. Ghazvini, Saji Uthaman, Lilly Synan, et al (2023) Predicting the onset of preeclampsia by longitudinal monitoring of metabolic changes throughout pregnancy with Raman spectroscopy. Bioengineering & Translational Medicine. https://doi.org/10.1002/btm2.10595
E. Litwinska, M. Litwińska, P. Oszukowski, et al (2015) Biochemical markers in screening for preeclampsia and intrauterine growth restriction. Ginekologia Polska. https://doi.org/10.17772/GP/57863
Jorge Montenegro-Martínez, Ana Camacho-Carrasco, David Núñez-Jurado, et al (2024) Longitudinal changes of angiogenic factors as a potential predictive tool in women with suspected preeclampsia. Pregnancy Hypertension. https://doi.org/10.1016/j.preghy.2024.01.130
R. Romero, Eunjung Jung, T. Chaiworapongsa, et al (2022) Toward a new taxonomy of obstetrical disease: improved performance of maternal blood biomarkers for the great obstetrical syndromes when classified according to placental pathology. American Journal of Obstetrics and Gynecology. https://doi.org/10.1016/j.ajog.2022.04.015
E. Timokhina, I. Ignatko, Yu. A Samoylova, et al (2025) New indicators of known markers in early prediction of the increase in the severity of preeclampsia. V F Snegirev Archives of Obstetrics and Gynecology. https://doi.org/10.17816/aog676879
V. Giardini, R. Rovelli, P. Algeri, et al (2020) Placental growth factor as a predictive marker of preeclampsia – PREBIO study – PREeclampsia BIOchemical study. Journal of Maternal-Fetal & Neonatal Medicine. https://doi.org/10.1080/14767058.2020.1792878
Yifan Wu, Yang Liu, Yiling Ding (2021) Predictive Performance of Placental Protein 13 for Screening Preeclampsia in the First Trimester: A Systematic Review and Meta-Analysis. Frontiers in Medicine. https://doi.org/10.3389/fmed.2021.756383
Jing Zhu, Jun Zhang, M. Ng, et al (2019) Angiogenic factors during pregnancy in Asian women with elevated blood pressure in early pregnancy and the risk of preeclampsia: a longitudinal cohort study. BMJ Open. https://doi.org/10.1136/bmjopen-2019-032237
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