Four-week whey protein supplementation modulates biochemical and angiogenic parameters in rat cardiovascular tissues
Abstract
Whey protein (WP) is widely used for its anabolic effects and potential cardiovascular benefits; however, its long-term effects on cardiac and vascular tissues remain unclear. This study assessed the biochemical, molecular, and morphological effects of a four-week WP supplementation (6 g/kg/day) in male Wistar rats. For this purpose, twenty-four male Wistar rats were divided into control, sham, and WP groups. The WP group received 6 g/kg of WP in 1 ml tap water daily for one month; the sham group received only water, and the control group received no treatment. Immunohistochemistry was performed for Vascular Endothelial Growth Factor (VEGF), Fibroblast Growth Factor-1 (FGF-1), and Interleukin-6 (IL-6). Serum levels of total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and glucose levels were assessed biochemically. WP significantly decreased serum total cholesterol, LDL-C, and glucose levels, while increasing serum HDL-C and triglyceride levels. Immunohistochemistry revealed elevated expression of VEGF and FGF-1 in the aortic tunica media and reduced aortic tunica intima thickness, without other histopathological alterations in cardiac or aortic tissues. WP supplementation elevated lipid levels and reduced glucose levels, without causing morphological damage. The increased expression of VEGF and FGF-1, along with significant changes in biochemical parameters, such as decreased total cholesterol, LDL-C, and glucose levels, and increased HDL-C and triglycerides, suggests that WP may influence molecular markers associated with vascular and metabolic processes. These findings underscore the necessity for further research to better understand the long-term cardiovascular implications of WP supplementation.
Keywords
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References
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Details
| Primary Language | English |
|---|---|
| Subjects | Veterinary Histology and Embryology |
| Journal Section | Research Article |
| Authors | |
| Project Number | None |
| Submission Date | August 26, 2025 |
| Acceptance Date | December 23, 2025 |
| Early Pub Date | March 2, 2026 |
| Publication Date | March 2, 2026 |
| DOI | https://doi.org/10.33988/auvfd.1772261 |
| IZ | https://izlik.org/JA87RX23UK |
| Published in Issue | Year 2026 Issue: Advanced Online Publication |
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‘Ankara Üniversitesi Veteriner Fakültesi Dergisi’ aims to disseminate high-quality, peer-reviewed scientific research that contributes to the advancement of knowledge in the fields of veterinary medicine and animal science. The journal seeks to serve as an international platform for the publication of original research articles, short communications, case reports, and invited review articles, promoting scientific excellence and interdisciplinary collaboration. Ankara Univ Vet Fak Derg publishes review articles by invitation only.
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1. Adams DC, Rohlf FJ, Slice DE (2004): Geometric morphometrics: ten years of progress following the revolution. Ital J Zool, 71, 5-16. DOI: 10.33988/auvfd. 1748170.
2. AOAC (2000): Association of Official Analytical Chemists, Official Methods of Analysis, 17th ed. AOAC International Maryland USA.
3. Bishop CD (1995): Antiviral activity of the essential oil of Melaleuca alternifolia (Maiden and Betche) Cheel (tea tree) against tobacco mosaic virus. J Essential Oil Res, 7, 641- 644. DOI: 10.33988/auvfd. 1748170.
4. Hui YH (1996): Oleoresins and essential oils. 145-153. In: Hui YH (Ed.). Bailey’s industrial oil and fat products. Wiley-Interscience Publication. New York, USA.
5. Lamont LA, Bulmer BJ, Sisson DD, et al (2002): Doppler echocardiographic effects of medetomidine on dynamic left ventricular outflow tract obstruction in cats. J Am Vet Med Assoc, 221, 1276-1281. DOI: 10.33988/auvfd. 1748170.
6. Sandstedt K, Ursing J, Walder M (1983): Thermotolerant Campylobacter with no or weak catalase activity isolated from dogs. Curr Microbiol, 8, 209-213. DOI: 10.33988/auvfd. 1748170.
7. Sandstedt K, Ursing J (1991): Description of the Campylobacter upsaliensis previously known as CNW group. Syst Appl Microbiol, 14, 39-45. DOI: 10.33988/auvfd. 1748170.
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Lamont LA, Bulmer BJ, Sisson DD, et al (2002): Doppler echocardiographic effects of medetomidine on dynamic left ventricular outflow tract obstruction in cats. J Am Vet Med Assoc, 221, 1276-1281. DOI: 10.33988/auvfd. 1748170.
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Describe how AI was used for specific aspects of the study (eg, to generate or refine study hypotheses, assist in the generation of a list of adjustment variables, create graphs to show visual relationships).
For studies using LLMs, provide the name of the platform or program, tool, version, and manufacturer; specify dates and prompt(s) used and their sequence and any revisions to prompts in response to initial outputs.
For studies reporting ML and algorithm development, include details about data sets used for development, training, and validation. Clearly state if algorithms were trained and tested only on previously collected or existing data sets or if the study includes prospective deployment. Include the ML model and describe the variables and outcome(s) and selection of the fine-tuning parameters. Describe any assumptions involved (eg, log linearity, proportionality) and how these assumptions were tested.
Indicate the metric used to evaluate the performance of the algorithms, including bias, discrimination, calibration, reclassification, and others as appropriate.
Indicate the methods used to address missing data.
Indicate institutional review board/ethics review, approval, waiver, or exemption.
Describe methods or analyses included to address and manage AI-related methodologic bias and inaccuracy of AI-generated content.
Indicate, when appropriate, if sensitivity analyses were performed to explore the performance of the AI model in vulnerable or underrepresented subgroups.
Provide a data sharing statement, including if code will be shared.
Results Section
When reporting comparisons, provide performance assessments (eg, against standard of care), include effect sizes and measures of uncertainty (eg, 95% CIs) and other measurements such as likelihood ratios, and include information about performance errors, inaccurate or missing data, and sufficient detail for others to reproduce the findings.
Report the results of analyses to address methodologic bias and population representation.
If examples of generated text or content are included in tables or figures, be sure to indicate the source and licensing information, as noted above.
Discussion Section
Discuss the potential for AI-related bias and what was done to identify and mitigate such bias.
Discuss the potential for inaccuracy of AI-generated content and what was done to identify and manage this.
Discuss generalizability of findings across populations and results of analyses performed to explore the performance of the AI model in vulnerable or underrepresented subgroups.
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