Multi-Omics Analysis Reveals Biaxial Regulatory Mechanisms of Cardiac Adaptation by Specialized Racing Training in Yili Horses.
Abstract: Yili horses undergo coordinated physiological adaptations across systems in response to customized training. This study aimed to clarify the molecular mechanisms of these adaptations by integrating analyses of cardiac function and multi-omics (lipidomics, transcriptomics, miRNomics). We collected whole blood samples from ten Yili horses before and after 12 weeks of specialized racing training to perform these analyses. Results showed training induced adaptive cardiac remodeling, with substantial increases in LVIDd and LVIDs. At the molecular level, this was accompanied by extensive blood lipid reprogramming (383 differential lipids), enriched in energy pathways like fatty acid metabolism. Transcriptomic analysis identified 851 differential genes, also enriched in energy-related pathways (e.g., oxidative phosphorylation). We constructed a miRNA-mRNA network (189 pairs), finding miRNAs such as miR-150 and miR-199b regulate key energy-supply mRNAs. Integrated analyses revealed precise modulation of pathways: (1) eca-miR-150 is associated with and creatine, with potential links to arginine/proline metabolism; (2) miR-8903 is associated with and nicotinamide, with potential associations with vitamin absorption. These pathways are critical for energy metabolism, redox balance, and signal transduction. Overall, this study reveals how training optimizes energy supply and metabolic homeostasis in Yili horses, offering new insights into training adaptation physiology.
Publication Date: 2025-11-17 PubMed ID: 41300398PubMed Central: PMC12649962DOI: 10.3390/biology14111609Google Scholar: Lookup The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
- Journal Article
Summary
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Overview
- This research investigates how specialized racing training induces physiological and molecular changes in the hearts of Yili horses.
- The study used multi-omics technologies—lipidomics, transcriptomics, and miRNomics—combined with cardiac function analysis to uncover molecular mechanisms underlying cardiac adaptation.
Background and Objective
- Yili horses, a breed known for racing, experience coordinated changes in different biological systems when undergoing training.
- The objective was to elucidate the molecular regulatory mechanisms driving these cardiac adaptations by integrating physiological data with multi-omics profiling.
Methodology
- Subjects: Ten Yili horses were studied before and after a 12-week specialized racing training program.
- Sample Collection: Whole blood samples were collected at both time points for molecular analyses.
- Cardiac Function Analysis: Measurements of left ventricular internal diameter during diastole and systole (LVIDd and LVIDs) were taken to assess cardiac remodeling.
- Multi-Omics Approaches:
- Lipidomics: Identification and quantification of lipid molecules in blood.
- Transcriptomics: Profiling gene expression changes in response to training.
- miRNomics: Analysis of microRNA (miRNA) expression and their regulatory roles.
Findings – Cardiac Structural Adaptations
- Training led to significant increases in LVIDd (left ventricular internal diameter at diastole) and LVIDs (during systole), indicative of cardiac remodeling and improved cardiac function.
Findings – Molecular Adaptations
- Lipidomic Changes:
- 383 lipids changed significantly post-training, reflecting broad blood lipid reprogramming.
- These lipids were enriched in energy-related metabolic pathways, particularly fatty acid metabolism, highlighting shifts in energy substrate utilization.
- Transcriptomic Changes:
- 851 genes showed differential expression after training.
- Gene changes were enriched in pathways important for energy production, such as oxidative phosphorylation.
- miRNomics and Regulatory Networks:
- Constructed a miRNA-mRNA interaction network comprising 189 miRNA-mRNA pairs.
- Important miRNAs like miR-150 and miR-199b were found to regulate mRNAs tied to energy supply.
Integrated Network and Pathway Insights
- Integration of lipid, gene, and miRNA data identified finely-tuned pathways modulating cardiac energy metabolism and signaling.
- Specific findings included:
- eca-miR-150: Linked with metabolites such as creatine, implicating arginine and proline metabolism. These pathways support energy buffering and redox balance in cardiac cells.
- miR-8903: Associated with metabolites like nicotinamide, suggesting involvement in vitamin absorption and maintaining metabolic homeostasis.
- These molecular mechanisms allow the heart to optimize energy supply, balance oxidative stress, and adjust intracellular signaling in response to training demands.
Significance and Implications
- This study provides a comprehensive view of how specialized racing training induces multi-systemic and molecular adaptations in Yili horses, particularly in cardiac metabolism and structure.
- The integration of multi-omics data provides novel insights into the regulatory networks optimizing cardiac function for athletic performance.
- Understanding these mechanisms could inform training strategies and enhance performance or health management in horses and potentially other athletic species.
Cite This Article
APA
Wang T, Li M, Ren W, Meng J, Yao X, Chu H, Yao R, Zhai M, Zeng Y.
(2025).
Multi-Omics Analysis Reveals Biaxial Regulatory Mechanisms of Cardiac Adaptation by Specialized Racing Training in Yili Horses.
Biology (Basel), 14(11), 1609.
https://doi.org/10.3390/biology14111609 Publication
Researcher Affiliations
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China.
- Horse Industry Research Institute, Xinjiang Agricultural University, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China.
- Horse Industry Research Institute, Xinjiang Agricultural University, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China.
- Horse Industry Research Institute, Xinjiang Agricultural University, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China.
- Horse Industry Research Institute, Xinjiang Agricultural University, Urumqi 830052, China.
- Xinjiang Yili Kazakh Autonomous Prefecture Animal Husbandry Station, Urumqi 835000, China.
- Xinjiang Yili Kazakh Autonomous Prefecture Animal Husbandry Station, Urumqi 835000, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China.
- Horse Industry Research Institute, Xinjiang Agricultural University, Urumqi 830052, China.
Grant Funding
- 32202667 / National Natural Science Foundation of China Youth Program
- 2022A02013-1 / Major Science and Technology Project of Xinjiang Uygur Autonomous Region
- ZYYD2025JD02 / Central Guidance Project for Local Science and Technology Development
- 2024D01B40 / The Youth Science Fund of the Natural Science Foundation of Xinjiang Uygur Autonomous Region
- XJMFY202401 / Key Laboratory of Horse Breeding and Exercise Physiology of Xinjiang Project
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
References
This article includes 64 references
- Chang X, Zhang Z, Yao X, Meng J, Ren W, Zeng Y. Lipidomics and biochemical profiling of adult Yili horses in a 26 km endurance race: Exploring metabolic adaptations.. Front. Vet. Sci. 2025;12:159739.
- Le Moyec L, Robert C, Triba M.N, Billat V.L, Mata X, Schibler L, Barrey E. Protein catabolism and high lipid metabolism associated with long distance exercise are revealed by plasma NMR metabolomics in endurance horses.. PLoS ONE 2014;9:e90730.
- Luck M.M, Le Moyec L, Barrey E, Triba M.N, Bouchemal N, Savarin P, Robert C. Energetics of endurance exercise in young horses determined by nuclear magnetic resonance metabolomics.. Front. Physiol. 2015;6:198.
- Tonevitsky A.G, Maltseva D.V, Abbasi A, Samatov T.R, Sakharov D.A, Shkurnikov M.U, Lebedev A.E, Galatenko V.V, Grigoriev A.I, Northoff H. Dynamically regulated miRNA-mRNA networks revealed by exercise.. BMC Physiol. 2013;13:9.
- Safdar A, Abadi A, Akhtar M, Hettinga B.P, Tarnopolsky M.A. miRNA in the regulation of skeletal muscle adaptation to acute endurance exercise in C57Bl/6J male mice.. PLoS ONE 2017;4:e5610.
- Russell A.P, Lamon S, Boon H, Wada S, Güller I, Brown E.L, Chibalin A.V, Zierath J.R, Snow R.J, Stepto N. Regulation of miRNAs in human skeletal muscle following acute endurance exercise and short-term endurance training.. J. Physiol. 2013;591:4637–4653.
- Yan Z, Okutsu M, Akhtar Y.N, Lira V.A. Regulation of exercise-induced fiber type transformation, mitochondrial biogenesis, and angiogenesis in skeletal muscle.. J. Appl. Physiol. 2011;110:264–274.
- Liu J, Liang X, Zhou D, Lai L, Xiao L, Liu L, Fu T, Kong Y, Zhou Q, Vega R.B. Coupling of mitochondrial function and skeletal muscle fiber type by a miR-499/Fnip1/AMPK circuit.. EMBO Mol. Med. 2016;8:1212–1228.
- Cappelli K, Capomaccio S, Viglino A, Silvestrelli M, Beccati F, Moscati L, Chiaradia E. Circulating miRNAs as putative biomarkers of exercise adaptation in endurance horses.. Front. Physiol. 2018;9:429.
- McGivney B.A, McGettigan P.A, Browne J.A, Evans A.C, Fonseca R.G, Loftus B.J, Lohan A, MacHugh D.E, Murphy B.A, Katz L.M. Characterization of the equine skeletal muscle transcriptome identifies novel functional responses to exercise training.. BMC Genom. 2010;11:398.
- Ropka-Molik K, Stefaniuk-Szmukier M, Z˙ukowski K, Piórkowska K, Bugno-Poniewierska M. Exercise-induced modification of the skeletal muscle transcriptome in Arabian horses.. Physiol. Genom. 2017;49:318–326.
- Wang T, Yang X, Meng J. Integrating miRNA, mRNA, and Targeted Metabolomics Analyses to Explore the Regulatory Mechanism of Cardiac Remodeling in Yili Horses.. Biology 2025;14:1535.
- Bou T, Ding W, Liu H, Gong W, Jia Z, Dugarjaviin M, Bai D. A genome-wide landscape of mRNAs, miRNAs, lncRNAs, and circRNAs of skeletal muscles during dietary restriction in Mongolian horses.. Comp. Biochem. Physiol. Part D Genom. Proteom. 2023;46:101084.
- Guijas C, Montenegro-Burke J.R, Warth B, Spilker M.E, Siuzdak G. Metabolomics activity screening for identifying metabolites that modulate phenotype.. Nat. Biotechnol. 2018;36:316–320.
- Wang T, Meng J, Yang X, Zeng Y, Yao X, Ren W. Differential Metabolomics and Cardiac Function in Trained vs. Untrained Yili Performance Horses.. Animals 2025;15:2444.
- Cock P.J.A, Fields C.J, Goto N, Heuer M.L, Rice P.M. The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants.. Nucleic Acids Res. 2010;38:1767–1771.
- Kim D, Langmead B, Salzberg S.L. HISAT: A fast spliced aligner with low memory requirements.. Nat. Methods. 2015;12:357–360.
- Robinson J.T, Thorvaldsdóttir H, Winckler W, Guttman M, Lander E.S, Getz G, Mesirov J.P. Integrative Genomics Viewer.. Nat. Biotechnol. 2011;29:24–26.
- Love M.I, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.. Genome Biol. 2014;15:550.
- Varet H, Brillet-Guéguen L, Coppée J.Y, Dillies M.-A. SARTools: A DESeq2- and EdgeR-based R pipeline for comprehensive differential analysis of RNA-Seq data.. PLoS ONE 2016;11:e0157022.
- Yu G, Wang L.G, Han Y, He Q.Y. clusterProfiler: An R package for comparing biological themes among gene clusters.. Omics J. Integr. Biol. 2012;16:284–287.
- Robinson M.D, McCarthy D.J, Smyth G.K. edgeR: A Bioconductor package for differential expression analysis of digital gene expression data.. Bioinformatics 2010;26:139–140.
- Chen Y, Lun A.T, Smyth G.K. From reads to genes to pathways: Differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline.. F1000Research 2016;5:1438.
- Guo X, Ning J, Chen Y, Liu G, Zhao L, Fan Y, Sun S. Recent advances in differential expression analysis for single-cell RNA-seq and spatially resolved transcriptomic studies.. Brief. Funct. Genom. 2024;23:95–109.
- Agarwal V, Bell G.W, Nam J.W, Bartel D.P. Predicting effective microRNA target sites in mammalian mRNAs.. eLife 2015;4:e05005.
- Irani F.-B.A, Cozens C, Holliger P, DeStefano J.J. Selection of 2′-deoxy-2′-fluoroarabinonucleotide (FANA) aptamers that bind HIV-1 reverse transcriptase with picomolar affinity.. Nucleic Acids Res. 2015;43:9587–9599.
- Betel D, Wilson M, Gabow A, Marks D.S, Sander C. The miRNA. org resource: Targets and expression.. Nucleic Acids Res. 2008;36:D149–D153.
- Szyf M. The genome-and system-wide response of DNA methylation to early life adversity and its implication on mental health.. Can. J. Psychiatry. 2013;58:697–704.
- Rehmsmeier M, Steffen P, Hochsmann M, Giegerich R. Fast and effective prediction of microRNA/target duplexes.. RNA 2004;10:1507–1517.
- McCarthy D.J, Chen Y, Smyth G.K. expression analysis of multifactor RNA-Seq experiments with respect to biological variation.. Nucleic Acids Res. 2012;40:4288–4297.
- Langfelder P, Horvath S. WGCNA: An R package for weighted correlation network analysis.. BMC Bioinform. 2008;9:559.
- Shannon P, Markiel A, Ozier O, Baliga N.S, Wang J.T, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: A software environment for integrated models of biomolecular interaction networks.. Genome Res. 2003;13:2498–2504.
- Wang T, Meng J, Peng X, Huang J, Huang Y, Yan X, Li X, Yang X, Chang X, Zeng Y. Metabolomics analysis and mRNA/miRNA profiling reveal potential cardiac regulatory mechanisms in Yili racehorses under different training regimens.. PLoS ONE 2025;20:e0322468.
- Contrepois K, Wu S, Moneghetti K.J, Hornburg D, Ahadi S, Tsai M.S, Metwally A.A, Wei E, Lee-McMullen B, Quijada J.V. Molecular Choreography of Acute Exercise.. Cell 2020;181:1112–1130.
- Nie Y, Sato Y, Garner R.T, Kargl C, Kaung S, Gilpin C, Gavin T.P. Skeletal muscle-derived exosomes regulate endothelial cell functions via reactive oxygen species-activated nuclear factor-κB signaling.. Exp. Physiol. 2019;104:1262–1273.
- Matsuzaka Y, Tanihata J, Ishiyama A, OYA Y, Rüegg U, Takeda S, Hashido K. Characterization and Functional Analysis of Extracellular Vesicles and Muscle-Abundant miRNAs (miR-1, miR-133a, and miR-206) in C2C12 Myocytes and mdx Mice.. PLoS ONE 2017;12:e0167811.
- Sohel H.M. Extracellular/Circulating MicroRNAs: Rele.ase Mechanisms, Functions and Challenges.. Achiev. Life Sci. 2016;10:175–186.
- Kis J, Rózsa L, Husvéth F, Zsolnai A, Anton I. Role of genes related to performance and reproduction of Thoroughbreds in training and breeding—A review.. Acta Vet. Hung. 2021;69:315–323.
- Nissen S.D, Weis R, Krag-Andersen E.K, Hesselkilde E.M, Isaksen J.L, Carstensen H, Linz D, Sanders P, Hopster-Iversen C, Jespersen T. Electrocardiographic characteristics of trained and untrained standardbred racehorses.. J. Vet. Intern. Med. 2022;36:1119–1130.
- Mosteoru S, Gaiţă L, Gaiţă D. Sport as Medicine for Dyslipidemia (and Other Risk Factors). Curr. Atheroscler. Rep. 2023;25:613–617.
- Forbes S.C, Candow D.G, Smith - Ryan A.E, Hirsch K.R, Roberts M.D, VanDusseldorp T.A, Stratton M.T, Kiani M, Little J.P. Supplements and Nutritional Interventions to Augment High-Intensity Interval Training Physiological and Performance Adaptations—A Narrative Review.. Nutrients 2020;12:390.
- Hao X, Zha C, Shao F, Wang L, Tan B. Amino acids regulate energy utilization through the mammalian target of rapamycin complex 1 and adenosine monophosphate-activated protein -kinase pathway in porcine enterocytes.. Anim. Nutr. 2020;6:98–106.
- Moukette B, Kawaguchi S, Sepulveda M, Hayasaka T, Aonuma T, Liangpunsakul S, Yang L, Dharmakumar R, Conway S, Kim I. MiR-150 blunts cardiac dysfunction in mice with cardiomyocyte loss of β1-adrenergic receptor/β-arrestin signaling and controls a unique transcriptome.. Cell Death Discov. 2022;8:504.
- Li X, Sun Y, Huang S, Chen Y, Chen X, Li M, Si X, He X, Zheng H, Zhong L. Inhibition of AZIN2-sv induces neovascularization and improves prognosis after myocardial infarction by blocking ubiquitin-dependent talin1 degradation and activating the Akt pathway.. EBioMedicine 2019;39:69–82.
- Xu L.S, Yang B.G, Zhang X.Y, Wang Z.Y, Li S, Kang W.G. Role and Mechanism of miR-199b-5p in Myocardial Fibrosis and Endoplasmic Reticulum Stress in Rats with Myocardial Infarction.. Lab. Med. Clin. 2025;22:914–919.
- Wang J, Yang X. Functions and Mechanisms of Non-Coding RNAs in Maintaining Cardiac Homeostasis.. Life Sci. 2018;30:1193–1201.
- Sawako S, Divya V, Tomoaki T, Prives C. GLS2 shapes ferroptosis in hepatocellular carcinoma.. Oncotarget 2023;14:14900–14903.
- Yang Y, Yuan H, Yang T, Li Y, Gao C, Jiao T, Cai Y, Zhao S. The expression regulatory network in the lung tissue of Tibetan pigs provides insight into hypoxia-sensitive pathways in high-altitude hypoxia.. Front. Genet. 2021;12:691592.
- Liang X, Chen M, Wang D, Wen J, Chen J. Vitamin A deficiency indicating as low expression of LRAT may be a novel biomarker of primary hypertension.. Clin. Exp. Hypertens. 2021;43:151–163.
- Sabater-Arcis M, Bargiela A, Furling D, Artero R. miR-7 Restores Phenotypes in Myotonic Dystrophy Muscle Cells by Repressing Hyperactivated Autophagy.. Mol. Ther. Nucleic Acids. 2020;19:278–292.
- Tomé M, López-Romero P, Albo C, Artero R. miR-335 orchestrates cell proliferation, migration and differentiation in human mesenchymal stem cells.. Cell Death Differ 2011;18:985–995.
- Fochi S, Giuriato G, De Simone T, Gomez-Lira M, Tamburin S, Del Piccolo L, Schena F, Venturelli M, Romanelli M G. Regulation of microRNAs in Satellite Cell Renewal, Muscle Function, Sarcopenia and the Role of Exercise.. Int. J. Mol. Sci. 2020;21:6732.
- Zhang K, Zheng X, Sun Y, Feng X, Wu X, Liu W, Gao C, Yan Y, Tian W, Wang Y. TOP2A modulates signaling via the AKT/mTOR pathway to promote ovarian cancer cell proliferation.. Cancer Biol. Ther. 2024;25:2325126.
- Wu M V, Bikopoulos G, Hung S, Ceddia R B. Thermogenic capacity is antagonistically regulated in classical brown and white subcutaneous fat depots by high-fat diet and endurance training in rats: Impact on whole-body energy expenditure.. J. Biol. Chem. 2014;289:34129–34140.
- Mercer K E, Maurer A, Pack L M, Ono-Moore K, Spray B J, Campbell C, Chandler C J, Burnett D, Souza E, Casazza G. Exercise training and diet-induced weight loss increase markers of hepatic bile acid (BA) synthesis and reduce serum total BA concentrations in obese women.. Am. J. Physiol. Endocrinol. Metab. 2021;320:E864–E873.
- Chen Y-M, Chiu W-C, Chiu Y-S. Effect of Inonotus obliquus Extract Supplementation on Endurance Exercise and Energy-Consuming Processes through Lipid Transport in Mice.. Nutrients 2022;14:5007.
- Mashnafi S, Plat J, Mensink R P, Joris P J, Kleinloog J P D, Baumgartner S. Effects of an 8-week aerobic exercise program on plasma markers for cholesterol absorption and synthesis in older overweight and obese men.. Lipids Health Dis. 2021;20:112.
- Zhang W, Zhao L, Tao Y, Lv Q, Wang M, Yu P, Li D, Zhu Q, Wang Y, Shang M. Proline metabolic reprogramming modulates cardiac remodeling induced by pressure overload in the heart.. Sci. Adv. 2024;10:eadl3549.
- Dimina L, Tremblay-Franco M, Deveaux A, Tardivel C, Fouillet H, Polakof S, Martin J-C, Mariotti F. Plasma metabolome analysis suggests that L-arginine supplementation affects microbial activity resulting in a decrease in trimethylamine N-oxide—A randomized controlled trial in healthy overweight adults with cardiometabolic risk factors.. Curr. Dev. Nutr. 2023;7:102038.
- Vega R B, Konhilas J P, Kelly D P, Leinwand L A. Molecular mechanisms underlying cardiac adaptation to exercise.. Cell Metab. 2017;25:1012–1026.
- Roffe-Vazquez D N, Huerta-Delgado A S, Castillo E C, Villarreal-Calderón J R, Gonzalez-Gil A M, Enriquez C, Garcia-Rivas G, Elizondo-Montemayor L. Correlation of vitamin D with inflammatory cytokines, atherosclerotic parameters, and lifestyle factors in the setting of heart failure: A 12-month follow-up study.. Int. J. Mol. Sci. 2019;20:5811.
- Sun Y, Ma M, Cao D, Zheng A, Zhang Y, Su Y, Wang J, Xu Y, Zhou M, Tang Y. Inhibition of fap promotes cardiac repair by stabilizing BNP.. Circ. Res. 2023;132:586–600.
- Arnold Z, Dostal C, Szabó P L, Aykac I, Goncalves A I A, Sousa S L, Baydar S, Budde H, Váradi B, Nadasy G L. Tenascin-C drives cardiovascular dysfunction in a mouse model of diabetic cardiomyopathy.. Cardiovasc. Diabetol. 2025;24:235.
- Chen H, Zhang Q, Zhou A, Zhang L, Li X. Identification of plasma lipid metabolism and potential biomarkers in patients with different coronary occlusive acute myocardial infarction.. Front. Cell Dev. Biol. 2025;13:1575431.
Citations
This article has been cited 2 times.- Wang T, Li M, Ren W, Meng J, Yao X, Chu H, Yao R, Zhai M, Zeng Y. Correction: Wang et al. Multi-Omics Analysis Reveals Biaxial Regulatory Mechanisms of Cardiac Adaptation by Specialized Racing Training in Yili Horses. Biology 2025, 14, 1609. Biology (Basel) 2026 Jan 23;15(3).
- Yuan X, Yao X, Zeng Y, Wang J, Ren W, Wang T, Li X, Yang L, Yang X, Meng J. The Effect of Training on the Expression of Protein and Metabolites in the Plasma Exosomes of the Yili Horse. Animals (Basel) 2026 Jan 6;16(2).
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