Preclinical modeling of metabolic syndrome to study the pleiotropic effects of novel antidiabetic therapy independent of obesity
Diabetes Prevention Program Research Group. Long-term effects of lifestyle intervention or metformin on diabetes development and microvascular complications over 15-year follow-up: The diabetes prevention program outcomes study. Lancet Diabetes Endocrinol. 3(11), 866–875. (2015).
Google Scholar
Centers for Disease Control and Prevention. National Diabetes Statistics Report website. Accessed 09 Dec 2023.
Birkeland, K. I. et al. How representative of a general type 2 diabetes population are patients included in cardiovascular outcome trials with SGLT-2 inhibitors? A large European observational study. Diabetes Obes. Metab. 21(4), 968–974. (2019).
Google Scholar
Butler, J. et al. EMPEROR-reduced trial committees and investigators. Empagliflozin and health-related quality of life outcomes in patients with heart failure with reduced ejection fraction: The EMPEROR-reduced trial. Eur. Heart J. 42(13), 1203–1212. (2021).
Google Scholar
Inzucchi, S. E. et al. Are the cardiovascular and kidney benefits of empagliflozin influenced by baseline glucose-lowering therapy?. Diabetes Obes. Metab. 22(4), 631–639. (2020).
Google Scholar
Kosiborod, M. N. et al. Semaglutide in patients with heart failure with preserved ejection fraction and obesity. N. Engl. J. Med. 389(12), 1069–1084. (2023).
Google Scholar
McMurray, J. J. V. et al. The dapagliflozin and prevention of adverse-outcomes in heart failure (DAPA-HF) trial: Baseline characteristics. Eur. J. Heart Fail. 21(11), 1402–1411. (2019).
Google Scholar
Neal, B. et al. Canagliflozin and cardiovascular and renal events in type 2 diabetes. N. Engl. J. Med. 377(7), 644–657. (2017).
Google Scholar
Packer, M. et al. Design of a prospective patient-level pooled analysis of two parallel trials of empagliflozin in patients with established heart failure. Eur. J. Heart Fail. 22(12), 2393–2398. (2020).
Google Scholar
Persson, F. et al. Dapagliflozin is associated with lower risk of cardiovascular events and all-cause mortality in people with type 2 diabetes (CVD-REAL Nordic) when compared with dipeptidyl peptidase-4 inhibitor therapy: A multinational observational study. Diabetes Obes. Metab. 20(2), 344–351. (2018).
Google Scholar
Zinman, B. et al. Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. N. Engl. J. Med. 373(22), 2117–2128. (2015).
Google Scholar
Ndumele, C. E. et al. Cardiovascular-kidney-metabolic health: A presidential advisory from the American heart association. Circulation (2023).
Google Scholar
Grundy, S. M. et al. American heart association; national heart, lung, and blood institute diagnosis and management of the metabolic syndrome: An American heart association/national heart, lung, and blood institute scientific statement. Circulation 112(17), 2735–2752. (2005).
Google Scholar
Newsome, P. N. & Ambery, P. Incretins (GLP-1 receptor agonists and dual/triple agonists) and the liver. J. Hepatol. 79, 1557–1565. (2023).
Google Scholar
Jacob, J. A. Researchers turn to canine clinical trials to advance cancer therapies. JAMA 315(15), 1550–1552. (2016) (PMID: 27027696).
Google Scholar
Seok, J. et al. Genomic responses in mouse models poorly mimic human inflammatory diseases. Proc. Natl. Acad. Sci. U. S. A. 110(9), 3507–3512. (2013).
Google Scholar
Waring, M. J. et al. An analysis of the attrition of drug candidates from four major pharmaceutical companies. Nat. Rev. Drug Discov. 14(7), 475–486. (2015).
Google Scholar
Zushin, P. H., Mukherjee, S. & Wu, J. C. FDA modernization act 2.0: Transitioning beyond animal models with human cells, organoids, and AI/ML-based approaches. J. Clin. Invest. 133(21), e175824. (2023).
Google Scholar
Gilmore, K. M. & Greer, K. A. Why is the dog an ideal model for aging research?. Exp. Gerontol. 71, 14–20. (2015) (Epub 2015 Aug 29 PMID: 26325590).
Google Scholar
Gordon, I., Paoloni, M., Mazcko, C. & Khanna, C. The comparative oncology trials consortium: Using spontaneously occurring cancers in dogs to inform the cancer drug development pathway. PLoS Med. 6(10), e1000161. (2009).
Google Scholar
Kaeberlein, M., Creevy, K. E. & Promislow, D. E. The dog aging project: Translational geroscience in companion animals. Mamm. Genome 27(7–8), 279–288. (2016).
Google Scholar
Kopper, J. J. et al. Harnessing the biology of canine intestinal organoids to heighten understanding of inflammatory bowel disease pathogenesis and accelerate drug discovery: A one health approach. Front. Toxicol. 10(3), 773953. (2021).
Google Scholar
Masters, A. K. et al. Effects of short-term anti-inflammatory glucocorticoid treatment on clinicopathologic, echocardiographic, and hemodynamic variables in systemically healthy dogs. Am. J. Vet. Res. 79(4), 411–423. (2018) (PMID: 29583045).
Google Scholar
Sebbag, L. & Mochel, J. P. An eye on the dog as the scientist’s best friend for translational research in ophthalmology: Focus on the ocular surface. Med. Res. Rev. 40(6), 2566–2604. (2020).
Google Scholar
Xenoulis, P. G. & Steiner, J. M. Lipid metabolism and hyperlipidemia in dogs. Vet. J. 183(1), 12–21. (2010).
Google Scholar
Kleinert, M. et al. Animal models of obesity and diabetes mellitus. Nat. Rev. Endocrinol. 14(3), 140–162. (2018).
Google Scholar
Yin, W. et al. Plasma lipid profiling across species for the identification of optimal animal models of human dyslipidemia. J. Lipid Res. 53(1), 51–65. (2012).
Google Scholar
Mochel, J. P. et al. Sacubitril/valsartan (LCZ696) significantly reduces aldosterone and increases cGMP circulating levels in a canine model of RAAS activation. Eur. J. Pharm. Sci. 1(128), 103–111. (2019).
Google Scholar
Mochel, J. P. & Danhof, M. Chronobiology and pharmacologic modulation of the renin-angiotensin-aldosterone system in dogs: What have we learned?. Rev. Physiol. Biochem. Pharmacol. 169, 43–69. (2015) (PMID: 26428686).
Google Scholar
Mochel, J. P. et al. Pharmacokinetic/pharmacodynamic modeling of renin-angiotensin aldosterone biomarkers following angiotensin-converting enzyme (ACE) inhibition therapy with benazepril in dogs. Pharm. Res. 32(6), 1931–1946. (2015).
Google Scholar
Schneider, B. et al. Model-based reverse translation between veterinary and human medicine: The one health initiative. CPT Pharmacometrics Syst. Pharmacol. 7(2), 65–68. (2018).
Google Scholar
Moinard, A. et al. Effects of high-fat diet at two energetic levels on fecal microbiota, colonic barrier, and metabolic parameters in dogs. Front. Vet. Sci. 25(7), 566282. (2020).
Google Scholar
Xue, J. et al. A protein- and fiber-rich diet with astaxanthin alleviates high-fat diet-induced obesity in beagles. Front. Nutr. 24(9), 1019615. (2022).
Google Scholar
Peña, C. et al. Effects of low-fat high-fiber diet and mitratapide on body weight reduction, blood pressure and metabolic parameters in obese dogs. J. Vet. Med. Sci. 76(9), 1305–1308. (2014).
Google Scholar
Sun, H. et al. Different diet energy levels alter body condition, glucolipid metabolism, fecal microbiota and metabolites in adult beagle dogs. Metabolites 13(4), 554. (2023).
Google Scholar
Tvarijonaviciute, A. et al. Obesity-related metabolic dysfunction in dogs: A comparison with human metabolic syndrome. BMC Vet. Res. 28(8), 147. (2012).
Google Scholar
Vecchiato, C. G. et al. Fecal microbiota and inflammatory and antioxidant status of obese and lean dogs, and the effect of caloric restriction. Front. Microbiol. 12(13), 1050474. (2023).
Google Scholar
Romero-Corral, A. et al. Normal weight obesity: A risk factor for cardiometabolic dysregulation and cardiovascular mortality. Eur. Heart J. 31(6), 737–746. (2010).
Google Scholar
Shi, T. H., Wang, B. & Natarajan, S. The influence of metabolic syndrome in predicting mortality risk among US adults: Importance of metabolic syndrome even in adults with normal weight. Prev. Chronic Dis. 21(17), E36. (2020).
Google Scholar
EMPA-KIDNEY Collaborative Group. Design, recruitment, and baseline characteristics of the EMPA-KIDNEY trial. Nephrol. Dial. Transpl. 37(7), 1317–1329. (2022).
Google Scholar
Oyama, K. et al. Obesity and effects of dapagliflozin on cardiovascular and renal outcomes in patients with type 2 diabetes mellitus in the DECLARE-TIMI 58 trial. Eur. Heart J. 43(31), 2958–2967. (2022) (PMID: 34427295).
Google Scholar
Wheeler, D. C. et al. The dapagliflozin and prevention of adverse outcomes in chronic kidney disease (DAPA-CKD) trial: baseline characteristics. Nephrol. Dial. Transp. 35(10), 1700–1711. (2020).
Google Scholar
Adamson, C. et al. Efficacy of dapagliflozin in heart failure with reduced ejection fraction according to body mass index. Eur. J. Heart Fail. 23(10), 1662–1672. (2021).
Google Scholar
Iennarella-Servantez, C. A. et al. Diet-induced clinical responsiveness of translational dog model for human western diet (WD)-related disease research. J. Anim. Sci. 99(3), 58–59. (2021).
Google Scholar
German, A. J. et al. A simple, reliable tool for owners to assess the body condition of their dog or cat. J. Nutr. 136(7 Suppl), 2031S-2033S. (2006) (PMID: 16772488).
Google Scholar
National Health and Nutrition Examination Survey. (NHANES 2015–2016: Males and Females over 20 years). https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/docs/temp-wweia-usual-intake-data-tables/.
National Research Council. Nutrient Requirements of Dogs and Cats (The National Academies Press, Washington, 2006).
Acierno, M. J. et al. ACVIM consensus statement: Guidelines for the identification, evaluation, and management of systemic hypertension in dogs and cats. J. Vet. Intern. Med. 32(6), 1803–1822. (2018).
Google Scholar
Larner, C. D. High performance lipoprotein profiling for cardiovascular risk assessment. PhD thesis, Texas A&M University (2012).
Minamoto, T. et al. Altered lipoprotein profiles in cats with hepatic lipidosis. J. Feline Med. Surg. 21(4), 363–372. (2019).
Google Scholar
Schneider, B. K. et al. Breakthrough: A first-in-class virtual simulator for dose optimization of ACE inhibitors in translational cardiovascular medicine. Sci. Rep. 13(1), 3300. (2023).
Google Scholar
Sotillo, S. et al. Dose-response of benazepril on biomarkers of the classical and alternative pathways of the renin-angiotensin-aldosterone system in dogs. Sci. Rep. 13(1), 2684. (2023).
Google Scholar
Ward, J. L., Chou, Y. Y., Yuan, L., Dorman, K. S. & Mochel, J. P. Retrospective evaluation of a dose-dependent effect of angiotensin-converting enzyme inhibitors on long-term outcome in dogs with cardiac disease. J. Vet. Intern. Med. 35(5), 2102–2111. (2021).
Google Scholar
Ward, J. L. et al. Circulating renin-angiotensin-aldosterone system activity in cats with systemic hypertension or cardiomyopathy. J. Vet. Intern. Med. 36(3), 897–909. (2022).
Google Scholar
Domenig, O. et al. Neprilysin is a mediator of alternative renin-angiotensin-system activation in the Murine and human kidney. Sci. Rep. 21(6), 33678. (2016).
Google Scholar
Guo, Z. et al. Measurement of equilibrium angiotensin II in the diagnosis of primary aldosteronism. Clin. Chem. 66(3), 483–492. (2020) (PMID: 32068832).
Google Scholar
Zoufaly, A. et al. Human recombinant soluble ACE2 in severe COVID-19. Lancet Respir. Med. 8(11), 1154–1158. (2020).
Google Scholar
González-Arostegui, L. G., Muñoz-Prieto, A., Tvarijonaviciute, A., Cerón, J. J. & Rubio, C. P. Measurement of redox biomarkers in the whole blood and red blood cell lysates of dogs. Antioxidants (Basel) 11(2), 424. (2022).
Google Scholar
Campos, C., Guzmán, R., López-Fernández, E. & Casado, A. Evaluation of the copper(II) reduction assay using bathocuproinedisulfonic acid disodium salt for the total antioxidant capacity assessment: The CUPRAC-BCS assay. Anal. Biochem. 392(1), 37–44. (2009) (Epub 2009 May 21 PMID: 19464250).
Google Scholar
Rubio, C. P. et al. Validation of three automated assays for total antioxidant capacity determination in canine serum samples. J. Vet. Diagn. Invest. 28(6), 693–698. (2016).
Google Scholar
Benzie, I. F. & Strain, J. J. The ferric reducing ability of plasma (FRAP) as a measure of “antioxidant power”: The FRAP assay. Anal. Biochem. 239(1), 70–76. (1996) (PMID: 8660627).
Google Scholar
Arnao, M. B., Cano, A., Hernández-Ruiz, J., García-Cánovas, F. & Acosta, M. Inhibition by L-ascorbic acid and other antioxidants of the 2.2’-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) oxidation catalyzed by peroxidase: A new approach for determining total antioxidant status of foods. Anal. Biochem. 236(2), 255–261. (1996).
Google Scholar
Da Costa, C. M., Dos Santos, R. C. C. & Lima, E. S. A simple automated procedure for thiol measurement in human serum samples. J. Bras. Patol. Med. Lab. 42, 345–350. (2006).
Google Scholar
Tvarijonaviciute, A., Tecles, F., Caldin, M., Tasca, S. & Cerón, J. Validation of spectrophotometric assays for serum paraoxonase type-1 measurement in dogs. Am. J. Vet. Res. 73(1), 34–41. (2012) (PMID: 22204286).
Google Scholar
Kapun, A. P., Salobir, J., Levart, A., Kotnik, T. & Svete, A. N. Oxidative stress markers in canine atopic dermatitis. Res. Vet. Sci. 92(3), 469–470. (2012).
Google Scholar
Verk, B., Nemec Svete, A., Salobir, J., Rezar, V. & Domanjko, P. A. Markers of oxidative stress in dogs with heart failure. J. Vet. Diagn. Invest. 29(5), 636–644. (2017).
Google Scholar
Erel, O. A new automated colorimetric method for measuring total oxidant status. Clin. Biochem. 38(12), 1103–1111. (2005) (Epub 2005 Oct 7 PMID: 16214125).
Google Scholar
Tatzber, F., Griebenow, S., Wonisch, W. & Winkler, R. Dual method for the determination of peroxidase activity and total peroxides-iodide leads to a significant increase of peroxidase activity in human sera. Anal. Biochem. 316(2), 147–153. (2003) (PMID: 12711334).
Google Scholar
Alberti, A., Bolognini, L., Macciantelli, D. & Caratelli, M. The radical cation of N, N-diethyl-para-phenylendiamine: A possible indicator of oxidative stress in biological samples. Res. Chem. Intermed. 26, 253–267. (2000).
Google Scholar
Rubio, C. P. et al. Stability of biomarkers of oxidative stress in canine serum. Res. Vet. Sci. 121, 85–93. (2018).
Google Scholar
Witko-Sarsat, V. et al. Advanced oxidation protein products as a novel marker of oxidative stress in uremia. Kidney Int. 49(5), 1304–1313. (1996) (PMID: 8731095).
Google Scholar
Matyash, V., Liebisch, G., Kurzchalia, T. V., Shevchenko, A. & Schwudke, D. Lipid extraction by methyl-tert-butyl ether for high-throughput lipidomics. J. Lipid Res. 49(5), 1137–1146. (2008).
Google Scholar
Sumner, L. W. et al. Proposed minimum reporting standards for chemical analysis chemical analysis working group (CAWG) metabolomics standards initiative (MSI). Metabolomics 3(3), 211–221. (2007).
Google Scholar
Adutwum, L. A., de la Mata, A. P., Bean, H. D., Hill, J. E. & Harynuk, J. J. Estimation of start and stop numbers for cluster resolution feature selection algorithm: An empirical approach using null distribution analysis of Fisher ratios. Anal. Bioanal. Chem. 409(28), 6699–6708. (2017).
Google Scholar
Sinkov, N. A. & Harynuk, J. J. Cluster resolution: A metric for automated, objective and optimized feature selection in chemometric modeling. Talanta 83(4), 1079–1087. (2011).
Google Scholar
Lyu, Y. et al. Differences in metabolic profiles of healthy dogs fed a high-fat vs. a high-starch diet. Front. Vet. Sci. 9, 801863. (2022).
Google Scholar
Cavaghan, M. K., Ehrmann, D. A. & Polonsky, K. S. Interactions between insulin resistance and insulin secretion in the development of glucose intolerance. J. Clin. Invest. 106(3), 329–333. (2000).
Google Scholar
Rix, I., Nexøe-Larsen, C., Bergmann, N. C., Lund, A. & Knop, F. K. Glucagon Physiology. In: Feingold, K. R., Anawalt, B., Blackman, M. R., Boyce, A., Chrousos, G., Corpas, E., de Herder, W. W., Dhatariya, K., Dungan, K., Hofland, J., Kalra, S., Kaltsas, G., Kapoor, N., Koch, C., Kopp, P., Korbonits, M., Kovacs, C. S., Kuohung, W., Laferrère, B., Levy, M., McGee, E. A., McLachlan, R., New, M., Purnell, J., Sahay, R., Shah, A. S., Singer, F., Sperling, M. A., Stratakis, C. A., Trence, D. L. & Wilson, D. P., (eds). South Dartmouth (MA): MDText.com, Inc. (2000).
Burger, M. & Schaller, D. J. Metabolic Acidosis. 2023 Jul 17. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing. PMID: 29489167 (2023).
Wieërs, M. L. A. J., Beynon-Cobb, B., Visser, W. J. & Attaye, I. Dietary acid load in health and disease. Pflugers Arch. 476(4), 427–443. (2024).
Google Scholar
Sharma, S., Hashmi, M. F. & Aggarwal, S. Hyperchloremic Acidosis. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing (2023).
Bamgbola, O. F. Review of the pathophysiologic and clinical aspects of hypokalemia in children and young adults: An Update. Curr. Treat Options Pediatr. 8(3), 96–114. (2022).
Google Scholar
Batlle, D. et al. Proximal renal tubular acidosis and hypophosphatemia induced by arginine. Adv. Exp. Med. Biol. 151, 239–249. (1982) (PMID: 6817609).
Google Scholar
Vasquez-Rios, G., Westrich, D. J. Jr., Philip, I., Edwards, J. C. & Shieh, S. Distal renal tubular acidosis and severe hypokalemia: A case report and review of the literature. J. Med. Case Rep. 13(1), 103. (2019).
Google Scholar
Lambert, D. C., Kane, J., Slaton, A. & Abramowitz, M. K. Associations of metabolic syndrome and abdominal obesity with anion gap metabolic acidosis among US adults. Kidney360 3(11), 1842–1851. (2022).
Google Scholar
Stoian, M. & Stoica, V. The role of distubances of phosphate metabolism in metabolic syndrome. Maedica (Bucur) 9(3), 255–260 (2014).
Google Scholar
Sun, K. et al. Serum potassium level is associated with metabolic syndrome: A population-based study. Clin. Nutr. 33(3), 521–527. (2014).
Google Scholar
Kalaitzidis, R., Tsimihodimos, V., Bairaktari, E., Siamopoulos, K. C. & Elisaf, M. Disturbances of phosphate metabolism: Another feature of metabolic syndrome. Am. J. Kidney Dis. 45(5), 851–858. (2005) (PMID: 15861350).
Google Scholar
Shimodaira, M., Okaniwa, S. & Nakayama, T. Reduced serum phosphorus levels were associated with metabolic syndrome in men but not in women: A cross-sectional study among the Japanese population. Ann. Nutr. Metab. 71(3–4), 150–156. (2017).
Google Scholar
Tropf, M., Nelson, O. L., Lee, P. M. & Weng, H. Y. Cardiac and metabolic variables in obese dogs. J. Vet. Intern. Med. 31(4), 1000–1007. (2017).
Google Scholar
Hussain, A. et al. Association of NT-ProBNP, blood pressure, and cardiovascular events: The ARIC study. J. Am. Coll. Cardiol. 77(5), 559–571. (2021).
Google Scholar
Jang, I. S., Yoon, W. K. & Choi, E. W. N-terminal pro-B-type natriuretic peptide levels in normotensive and hypertensive dogs with myxomatous mitral valve disease stage B. Ir. Vet. J. 76(1), 3. (2023).
Google Scholar
Bayes-Genis, A. et al. Practical algorithms for early diagnosis of heart failure and heart stress using NT-proBNP: A clinical consensus statement from the heart failure association of the ESC. Eur. J. Heart Fail. (2023).
Google Scholar
Singletary, G. E., Morris, N. A., Lynne O’Sullivan, M., Gordon, S. G. & Oyama, M. A. Prospective evaluation of NT-proBNP assay to detect occult dilated cardiomyopathy and predict survival in Doberman Pinschers. J. Vet. Intern. Med. 26(6), 1330–1336. (2012).
Google Scholar
Wilshaw, J. et al. Accuracy of history, physical examination, cardiac biomarkers, and biochemical variables in identifying dogs with stage B2 degenerative mitral valve disease. J. Vet. Intern. Med. 35(2), 755–770. (2021).
Google Scholar
Akinkuolie, A. O., Paynter, N. P., Padmanabhan, L. & Mora, S. High-density lipoprotein particle subclass heterogeneity and incident coronary heart disease. Circ. Cardiovasc. Qual. Outcomes 7(1), 55–63. (2014).
Google Scholar
Superko, H. R. et al. High-density lipoprotein subclasses and their relationship to cardiovascular disease. J. Clin. Lipidol. 6(6), 496–523. (2012).
Google Scholar
Duan, R. et al. Estimation of the LDL subclasses in ischemic stroke as a risk factor in a Chinese population. BMC Neurol. 20(1), 414. (2020).
Google Scholar
Lahm Cardoso, J. M. et al. Blood pressure, serum glucose, cholesterol, and triglycerides in dogs with different body scores. Vet. Med. Int. 2016, 8675283. (2016).
Google Scholar
Aleksandrova, K., Koelman, L. & Rodrigues, C. E. Dietary patterns and biomarkers of oxidative stress and inflammation: A systematic review of observational and intervention studies. Redox Biol. 42, 101869. (2021).
Google Scholar
Boden, G. et al. Excessive caloric intake acutely causes oxidative stress, GLUT4 carbonylation, and insulin resistance in healthy men. Sci. Transl. Med. 7(304), 304re7. (2015).
Google Scholar
Matsuzawa-Nagata, N. et al. Increased oxidative stress precedes the onset of high-fat diet-induced insulin resistance and obesity. Metabolism 57(8), 1071–1077. (2008) (PMID: 18640384).
Google Scholar
Chiofalo, B. et al. Effects of dietary protein and fat concentrations on hormonal and oxidative blood stress biomarkers in guide dogs during training. J. Vet. Behav. 37, 86–92. (2020).
Google Scholar
Qu, W. et al. Profound perturbation in the metabolome of a canine obesity and metabolic disorder model. Front. Endocrinol. (Lausanne) 19(13), 849060. (2022).
Google Scholar
Amjad, S. et al. Role of NAD+ in regulating cellular and metabolic signaling pathways. Mol. Metab. 49, 101195. (2021).
Google Scholar
Surjana, D., Halliday, G. M. & Damian, D. L. Role of nicotinamide in DNA damage, mutagenesis, and DNA repair. J. Nucleic Acids. 25(2010), 157591. (2010).
Google Scholar
Frühbeck, G., Méndez-Giménez, L., Fernández-Formoso, J. A., Fernández, S. & Rodríguez, A. Regulation of adipocyte lipolysis. Nutr. Res. Rev. 27(1), 63–93. (2014) (Epub 2014 May 28 PMID: 24872083).
Google Scholar
Bánhegyi, G. & Loewus, F. A. Ascorbic acid catabolism: Breakdown pathways in animals and plants. In Vitamin C, Function and Biochemistry in Animals and Plants (eds Asard, H. et al.) 35 (Taylor & Francis, New York, 2004).
Google Scholar
Hishikawa, D., Hashidate, T., Shimizu, T. & Shindou, H. Diversity and function of membrane glycerophospholipids generated by the remodeling pathway in mammalian cells. J. Lipid Res. 55(5), 799–807. (2014).
Google Scholar
Sivaprakasam, S., Prasad, P. D. & Singh, N. Benefits of short-chain fatty acids and their receptors in inflammation and carcinogenesis. Pharmacol. Ther. 164, 144–151. (2016).
Google Scholar
Hooper, L. et al. Reduction in saturated fat intake for cardiovascular disease. Cochrane Database Syst. Rev. 5(5), CD011737. (2020).
Google Scholar
Siri-Tarino, P. W., Sun, Q., Hu, F. B. & Krauss, R. M. Saturated fat, carbohydrate, and cardiovascular disease. Am. J. Clin. Nutr. 91(3), 502–509. (2010).
Google Scholar
Bolsoni-Lopes, A. et al. Palmitoleic acid (n-7) increases white adipocytes GLUT4 content and glucose uptake in association with AMPK activation. Lipids Health Dis. 20(13), 199. (2014).
Google Scholar
Cruz, M. M. et al. Palmitoleic acid (16:1n7) increases oxygen consumption, fatty acid oxidation and ATP content in white adipocytes. Lipids Health Dis. 17(1), 55. (2018).
Google Scholar
Alves, S. P., Marcelino, C., Portugal, P. V. & Bessa, R. J. Short communication: The nature of heptadecenoic acid in ruminant fats. J. Dairy Sci. 89(1), 170–173. (2006) (PMID: 16357280).
Google Scholar
Amigo, J. M., Skov, T., Bro, R., Coello, J. & Maspoch, S. Solving GC-MS problems with PARAFAC2. TrAC Trends Anal. Chem. 27, 714–725. (2008).
Google Scholar
Giebelhaus, R. T., Sorochan Armstrong, M. D., de la Mata, A. P. & Harynuk, J. J. Untargeted region of interest selection for gas chromatography–mass spectrometry data using a pseudo F-ratio moving window. J. Chromatogr. A 1682, 463499. (2022).
Google Scholar
Giebelhaus, R. T., Erland, L. A. E. & Murch, S. J. HormonomicsDB: A novel workflow for the untargeted analysis of plant growth regulators and hormones. F1000Research 11, 119 (2022).
Google Scholar
Monnerie, S. et al. Metabolomic and lipidomic signatures of metabolic syndrome and its physiological components in adults: A systematic review. Sci. Rep. 10(1), 669. (2020).
Google Scholar
Kadowaki, T. et al. Interconnection between cardiovascular, renal and metabolic disorders: A narrative review with a focus on Japan. Diabetes Obes. Metab. 24(12), 2283–2296. (2022).
Google Scholar
National Heart, Lung, and Blood Institute (NHLBI). What is metabolic syndrome? Last 18 May 2022.
R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
Rubio, C. P., Martinez-Subiela, S., Hernández-Ruiz, J., Tvarijonaviciute, A. & Ceron, J. J. Analytical validation of an automated assay for ferric-reducing ability of plasma in dog serum. J. Vet. Diagn. Invest. 29(4), 574–578. (2017).
Google Scholar
Johnson, M. C. Hyperlipidemia disorders in dogs. Compend. Contin. Educat. Pract. Vet. 27, 361–364 (2005).
Littman, M. P. Spontaneous systemic hypertension in 24 cats. J. Vet. Intern. Med. 8(2), 79–86. (1994). PMID: 8046680.
Jocelyn, P. C. Spectrophotometric assay of thiols. Methods Enzymol. 143, 44–67. (1987). PMID: 3657559.
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