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Article

The Impacts of Protein Supplementation and Semen Exposure on Uterine Cytokines in Beef Heifers

by
Kyle J. McLean
*,
Kiernan J. Brandt
,
Taylor B. Ault-Seay
,
Rebecca R. Payton
,
Liesel G. Schneider
,
J. Lannett Edwards
,
Phillip R. Myer
and
Justin D. Rhinehart
Department of Animal Science, University of Tennessee Institute of Agriculture, Knoxville, TN 37996, USA
*
Author to whom correspondence should be addressed.
Agriculture 2025, 15(15), 1642; https://doi.org/10.3390/agriculture15151642
Submission received: 18 June 2025 / Revised: 21 July 2025 / Accepted: 22 July 2025 / Published: 30 July 2025
(This article belongs to the Section Farm Animal Production)
Browse Figures
Versions Notes

Abstract

Reproductive efficiency is largely impacted during heifer development, which generally requires nutrient supplementation for proper maturation. Nutritional status can also influence inflammation within the reproductive tract. Therefore, we hypothesized that cytokine concentrations in uterine luminal fluid (ULF) will be impacted by protein supplementation following exposure to semen via artificial insemination (AI). Commercial heifers (n = 60) were utilized to determine the effects of protein supplementation and AI on cytokine concentrations in ULF. Heifers were randomly assigned to one of three crude protein (CP) treatments (11%, 15%, and 19% overall CP) via supplementation: (1) CON (10% CP), (2) P20 (20% CP), and (3) P40 (40% CP). All heifers underwent estrus synchronization and ULF was collected 14 d after insemination. Cytokine profiles were constructed in MetaboAnalyst 5.0, and R Studio was used for individual cytokine analyses. Control heifers had increased (p = 0.05) MIP-1β concentrations (148.7 ± 123.9 pg) over P20 heifers (42.3 ± 123.9 pg), and P40 heifers (75.5 ± 123.9 pg) had intermediate concentrations. Semen exposure (1877 ± 550 pg) showed a trend (p = 0.06) to increase concentrations of IP-10 compared with heifers who were not inseminated (1556 ± 550 pg). In conclusion, although protein supplementation and semen exposure had minimal effects on overall cytokine profiles, MIP-1β, IP-10, and MIP-1α were identified as potential key regulators of uterine inflammation during early gestation.

1. Introduction

With the rapidly growing human population, the beef industry must incorporate sustainable practices to provide enough nutrient-dense food even as land availability decreases [1,2]. Reproductive efficiency, and thus overall beef production, is impacted during the development of new breeding females. Heifer development is largely influenced by nutrition [3,4], and if inadequate, reproductive efficiency will decrease [5]. Nutrient supplementation is generally required for the proper maturation of beef heifers. Heifers provided supplemental crude protein (CP) during development experience elevated growth and fertility rates compared to those without CP supplementation [6]. However, overfeeding protein can delay the onset of puberty and reduce pregnancy rates [7,8,9]. Recent studies have reported amino acid (AA) concentrations within uterine luminal fluid (ULF) throughout the estrous cycle [10] and early gestation [11,12,13]. Concentrations of AA have been shown to increase during early gestation [11,12] and are reduced in sub-fertile cattle [14]. These data further implicate AA and CP concentrations on the successful establishment of pregnancy. Nutritional status can also influence immunological status [15]. To prevent embryonic rejection, an immuno-tolerant uterine environment via cytokine signaling must be created to facilitate attachment [16]. Cytokines impact a variety of reproductive and pregnancy-related processes like the estrous cycle [17], ovulation [18], embryonic development [19], and implantation [20]. Therefore, identifying how nutrition, specifically protein, can influence inflammation within ULF could lead to alterations in management strategies to improve reproductive outcomes. Therefore, we hypothesized that cytokine and chemokine concentrations within the reproductive tract will be impacted by protein supplementation following insemination, which may alter the establishment of pregnancy and embryonic development.

2. Materials and Methods

Commercial Angus heifers (n = 60), owned by the University of Tennessee and located at the Middle Tennessee Research and Education Center (Spring Hill, TN, USA), were utilized to determine the effects of protein supplementation on cytokine concentrations in ULF following estrus synchronization and artificial insemination (AI). All animal procedures and diets have previously been described in detail [21]. Briefly, all heifers had ad libitum access to native grass hay, trace mineral supplements, and water. Heifers were housed in three-acre pens with 5 heifers each, resulting in four pens per treatment. Heifers were blocked by body weight into four weight classes (n = 15 heifers per class) and randomly assigned to one of three supplemental treatments: (1) control (CON), 10% CP supplement, consisting of 100% corn; (2) 20% CP supplement (P20) consisting of 25% corn and 75% dried distiller’s grains (DDGs); (3) 40% CP supplement (P40) consisting of 25% DDGs and 75% soybean meal. This resulted in diets of approximately 11%, 15%, and 19% overall CP for CON, P20, and P40 heifers, respectively. All heifers underwent a 7-Day CO-Synch + Control Internal Drug Release (CIDR) estrus synchronization protocol [22]. Heifers received an initial 100 µg intramuscular (i.m.) injection of gonadotrophin releasing hormone (GnRH; gonadorelin diacetate tetrahydrate, Cystorelin®, Boehrenger Ingleheim, Duluth, GA, USA) and CIDR device (1.38 g progesterone; Zoetis Animal Health, Flor-ham Park, NJ, USA) was inserted into the vagina for 7 days. Upon CIDR removal, heifers received an i.m. injection of 500 µg prostaglandin-F2α (PGF2α; Cloprostenol sodium; Synchsure™, Boehrenger Ingleheim, Duluth, GA, USA). Fixed-time AI was performed by a single technician beginning approximately 54 h after CIDR removal, concurrent with an i.m. injection of GnRH. At the time of breeding, one animal from each pen was randomly selected to not be inseminated to serve as a synchronized but unexposed control for cytokine analyses. Uterine luminal flush was collected 14 d after insemination by placing 20 mL of sterile saline into the vagina via insertion of a Foley catheter in the fornix vagina, mixed with vaginal fluid by rectal massage, removed through the catheter, and stored at −80 °C until cytokine quantification could be completed. Cytokine concentrations of Interleukin (IL)-1α (sensitivity 0.36 pg/mL), IL-1β (sensitivity 4.93 pg/mL), IL-10 (sensitivity 1.05 pg/mL), IL-17a (sensitivity 0.67 pg/mL), IL-36ra (sensitivity 1.23 pg/mL), IL-8 (sensitivity 22.6 pg/mL), IL-4 (sensitivity 16.57 pg/mL), IL-6 (sensitivity 11.23 pg/mL), Interferon γ-induced Protein-10 (IP-10; sensitivity 0.91 pg/mL), Tumor Necrosis Factor-α (TNF-α; sensitivity 22.62 pg/mL), Interferon γ (IFN-γ; sensitivity 0.08 pg/mL), Monocyte Chemoattractant Protein-1 (MCP-1; sensitivity 2.74 pg/mL), Macrophage Inflammatory Protein (MIP)-1α (sensitivity 98.54 pg/mL), MIP-1β (sensitivity 2.32 pg/mL), and Vascular Endothelial Growth Factor a (VEGFa; sensitivity 1.18 pg/mL) were quantified within ULF using the MILLIPLEX® MAP Bovine Cytokine/Chemokine Magnetic Bead Panel (MilliporeSigma, Burlington, MA, USA) according to manufacturer protocol, and analyzed on the Luminex 200 system (Luminex, Austin, TX, USA) at the University of Tennessee Institute of Agriculture Genomics Hub. The accuracy of this kit is stated to be between 91 and 103% with no cross-reactivity between the antibodies. The inter-assay coefficient of variation averaged 22.5% across all cytokines.
Cytokine profile analyses were completed with cytokine concentrations using MetaboAnalyst 5.0 [23] to identify differences in cytokine profiles within protein supplementation treatments and semen exposure. The chemometrics analysis using Partial Least Squares-Discriminant Analysis (PLS-DA) with permutation testing was utilized to evaluate cytokine profiles amongst all nutritional treatment, and orthogonal PLS-DA with permutation testing was utilized to evaluate cytokine profiles for pairwise comparisons between protein treatments and semen exposure. Permutation tests were conducted within MetaboAnalyst 5.0 with permutation numbers set at 100 for all analyses conducted. Following cytokine profile analyses, individual Analyses of Variance (ANOVAs) were conducted to elucidate differences in individual cytokines. A randomized complete block design was implemented for individual statistical analyses in R Studio version 4.5.1 with pen as the experimental unit and heifers as the sampling unit. One-way ANOVAs were performed via the aov function, with protein supplementation treatments and semen exposure treated as fixed effects. Normality was assessed by the Shapiro–Wilk statistic > 0.8 and the Kolmogorov–Smirnov test > 0.2. Cytokine concentrations that were not normally distributed were log transformed to achieve normality and were reported as back transformed means and standard errors. Standard errors are reported as pooled standard errors for a specific fixed effect comparison. Due to the transient nature of cytokines in any physiological state but particularly in healthy animals, any values outside of the standard curve range were dropped from the dataset and treated as missing values. Outliers were determined to be any value observed to be greater or less than ±2 times the standard error and were removed from the dataset. Fisher’s Least Squares Difference (LSD) was utilized for mean separation. Means were reported different when p < 0.05 and tendencies at p < 0.10.

3. Results

There were no differences (p = 0.63) in cytokine profiles, via PLS-DA, amongst all three nutritional supplements. There were also no differences (p > 0.56) in cytokine profiles from orthogonal PLS-DA, from the pairwise comparisons of protein supplementation, CON vs. P20 (p = 0.56; Figure 1A), CON vs. P40 (p = 0.73; Figure 1B), and P20 vs. P40 (p = 0.99; Figure 1C). Interestingly, the ellipses which represent the 95% confidence intervals of each profile were visually larger for heifers on the CON supplement compared with the P20 or P40 in both the three-way and pairwise comparisons. There was no difference (p = 0.64) in cytokine profiles in ULF between heifers that underwent a synchronization protocol and were exposed to semen via AI compared with heifers that underwent a synchronization protocol but were not exposed to semen (Figure 1D).
Individual ANOVAs identified three cytokines, MIP-1β, IP-10, and MIP-1α, which were impacted by protein supplementation, semen exposure, or the interaction of protein supplementation × semen exposure. Concentrations of IL-1α, IL-1β, IL-10, IL-17a, IL-36ra, IL-8, IL-4, IL-6, TNF-α, IFN-γ, MCP-1, and VEGFa were not influenced (p > 0.10) by protein supplementation, semen exposure, or the interaction of protein supplementation × semen exposure. Heifers provided the CON supplement had increased (p = 0.05) concentrations of MIP-1β (148.7 ± 123.9 pg) compared with heifers fed the P20 supplement (42.3 ± 123.9 pg), and heifers fed the P40 supplement (75.5 ± 123.9 pg) had intermediate concentrations (Figure 2A). Exposure to semen (1877 ± 550 pg) tended (p = 0.06) to increase concentrations of IP-10 compared with heifers who were not inseminated (1556 ± 550 pg; Figure 2B).
Concentrations of MIP-1α tended (p = 0.07) to be influenced by an interaction of protein supplementation × semen exposure (Figure 3). Heifer who received the CON and P20 supplements (70.9 ± 127.2 pg and 63.5 ± 127.2 pg, respectively) and were not inseminated were similar to heifers who were fed the P20 and P40 supplements (112.9 ± 127.2 pg and 120.3 ± 127.2 pg, respectively) but were inseminated. Heifers on the CON diet and inseminated (220.7 ± 127.2 pg) and heifers fed the P40 supplement and not inseminated (232.7 ± 127.2 pg) were similar to each other but tended to be greater than the other groups (Figure 3).

4. Discussion

These data are part of a larger study in which both cytokines and AA were analyzed during the development and through the breeding of these heifers [21,24]. Interestingly, the AA and cytokines were different throughout development but with limited impacts of supplemental protein [21,24]. The current dataset follows a similar trend with limited impacts of protein supplementation on cytokines following synchronization and AI. This is potentially due to the minor overall dietary differences that were created by these treatments (overall CP ranged from 11% to 19%) or the capacity of the rumen to supply CP when adequate levels of feed are provided. However, the two cytokines, MIP-1α and MIP-1β, were influenced by the interaction of protein supplementation and semen exposure or protein supplementation level alone. Recent research has reported a fluctuation in systemic and reproductive tract cytokines throughout the estrous cycle [17,24,25,26,27], including MIP-1α and MIP-1β. These cytokines, MIP-1α and MIP-1β, were also found to increase in the uterus during heifer development [24] and during estrus [26]. Macrophage Inflammatory Protein-1α exhibited an interactive effect of protein supplementation level and semen exposure. This may be indicative of a return to estrus in the not-exposed P40 heifers or a failure to conceive in the exposed group CON heifers. However, this effect requires more research to be completely elucidated. Macrophage Inflammatory Protein-1β is highly homologous, 60% [28], to MIP-1α. Interestingly, MIP-1β was only impacted by protein supplementation in the current study. In previous work, MIP-1β was shown to have a relationship with progesterone concentrations [24]. This may explain the lack of an interactive effect in the current dataset since all of the heifers underwent estrus synchronization 14 d prior to sampling. Protein supplementation was reported to not impact MIP-1β during heifer development [24]. Thus, the current dataset may indicate that protein supplementation following synchronization can alter the inflammatory status of the reproductive tract. However, more research needs to be conducted to further understand the impacts of protein, inflammation via MIP-1β, and successful pregnancy.
Interferon gamma-induced protein-10 is released from T lymphocytes, neutrophils, monocytes, splenocytes, endothelial cells, and fibroblasts [29,30] to stimulate an inflammatory response as a chemoattractant. This classical function could explain the results in the current dataset as the inseminated heifers work to clear spermatozoa out of the uterus. This idea is supported by data in abortion-prone mice which had decreased concentrations of IP-10 [31]. Murine models have reported an important role of both IFNγ and IP-10 [32] and inflammation, in general, early in gestation [31]. However, most inflammatory cytokines, except IP-10, in the current dataset were not influenced by insemination. This may be a species-specific difference between cattle and mice or an artifact of the small sample size in the current dataset. Since cytokine concentrations can fluctuate quickly, the lack of differences may be explained by the timing of sample collection, especially since other data reporting correlations between IP-10 and IFNγ, MIP-1β, and TNF-α during early gestation [27]. More research to elucidate the exact function of inflammation and IP-10 during early pregnancy is required to understand the importance of this in bovine gestation.
Recent work within various reproductive fluids of cattle has shown limited impacts of global or supplemental nutrition, growth rate, or even early gestation on cytokine profiles [24,26,27,33]. However, there were distinct cytokine profiles based on type of mating, AI vs. natural service [26] further emphasizing the complexity of the interaction between nutrition, immunology, and reproductive function. This trend continued in the current dataset with no differences observed in cytokine profiles between protein supplementation and exposure to semen. Interestingly, our lab and others have identified multiple cytokines, IL-1β, IL-8, MIP-1β, TNFα, VEGFa, and IFNγ, that are consistently differentially present within reproductive fluids [17,24,25,26,27,33]. Inflammation early in gestation has been reported to be important during the establishment of pregnancy and embryonic development in mice [31,34], humans [34,35], sheep [36], and most likely cattle [17,24,25,26]. Nonetheless, more research needs to be conducted to understand the importance and timing of inflammation during early embryonic development and the establishment of gestation.
The results of the current study do not come without limitations. The transient nature of cytokine concentrations makes large-scale conclusions difficult, particularly with only a single observation. Additionally, while the animals were synchronized, not all individuals respond in the same time frame. Thus, animal-to-animal variation could be the source of the larger standard errors observed. This work was designed to be exploratory in nature and is the first step in elucidating if cytokines can be utilized as biomarkers for pregnancy and the functions cytokines complete during early gestation. The current dataset provides three targets for future work to be conducted.

5. Conclusions

In conclusion, although protein supplementation and exposure to semen had minimal effects on overall cytokine profiles, MIP-1β, IP-10, and MIP-1α were identified as potential key regulators of uterine inflammation during early gestation. This dataset does have limitations due to the exploratory nature of the experimental design, which is a result of the unbalanced treatment groups. However, this work could be extraordinarily impactful to reproductive efficiency in beef cattle and could be utilized as a starting point for more directed studies on the three cytokines, MIP-1β, IP-10, and MIP-1α, and their role in early gestation and the establishment of pregnancy.

Author Contributions

K.J.M. contributed to experimental design, data acquisition, analyses, interpretation of data, and manuscript preparation. K.J.B. contributed to data acquisition, sample analyses, data interpretation, and manuscript preparation. T.B.A.-S. contributed to data acquisition, sample analyses, data interpretation, and manuscript preparation. R.R.P., L.G.S., J.L.E., P.R.M. and J.D.R. contributed to data interpretation and manuscript edits. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the University of Tennessee Institute of Agriculture, the University of Tennessee Department of Animal Science, and the United States Department of Agriculture, National Institute of Food and Agriculture, Capacity Grant No. 1019048.

Institutional Review Board Statement

The study was conducted in accordance with procedures approved by the University of Tennessee Institutional Animal Care and Use Committee (2649-1018 approved on October 2018).

Data Availability Statement

Data is available upon request from the corresponding author.

Acknowledgments

The authors would like to thank Kevin Thompson and the Middle Tennessee Research and Education Center for help in collecting samples and providing care of the animals used in the study, and Neal Schrick for his advice on experimental design and uterine flush techniques. Additionally, the authors would like to thank the state of Tennessee through UT AgResearch, the Department of Animal Science, and the USDA National Institute of Food and Agriculture, Hatch Project No. 1019048 for providing funding and support for this research.

Conflicts of Interest

The authors declare that they have no competing interests.

Abbreviations

The following abbreviations are used in this manuscript:
AAAmino Acid
AIArtificial Insemination
ANOVAAnalysis of Variance
CIDRControl Internal Drug Release
CONControl Supplement of 10% Crude Protein
CPCrude Protein
DDGsDried Distillers Grains
GnRHGonadotrophin Releasing Hormone
IFNγInterferon gamma
ILInterleukin
i.m.Intramuscular
IP-10Interferon γ-induced Protein-10
LSDLeast Squares Difference
MCP-1Monocyte Chemoattractant Protein-1
MIPMacrophage Inflammatory Protein
P20Treatment Supplement of 20% Crude Protein
P40Treatment Supplement of 40% Crude Protein
PGF2αProstaglandin-F2α
PLS-DAPartial Least Squares-Discriminant Analysis
TNF-αTumor Necrosis Factor alpha
ULFUterine Luminal Fluid
VEGFaVascular Endothelial Growth Factor a

References

  1. Elliot, I. Meat Output Must Double by 2050. Feedstuffs. Available online: http://feedstuffsfoodlink.com/story-meat-output-must-double-by-2050-71-66920 (accessed on 15 January 2013).
  2. Reynolds, L.P.; Wulster-Radcliffe, M.C.; Aaron, D.K.; Davis, T.A. Importance of animals in agricultural sustainability and food security. J. Nutr. 2015, 145, 1377–1379. [Google Scholar] [CrossRef]
  3. Freetly, H.C.; Kuehn, L.A.; Cundiff, L.V. Growth curves of crossbred cows sired by Hereford, Angus, Belgian Blue, Brahman, Boran, and Tuli bulls, and the fraction of mature body weight and height at puberty. J. Anim. Sci. 2011, 89, 2373–2379. [Google Scholar] [CrossRef]
  4. Perry, G.A. Factors affecting puberty in replacement beef heifers. Theriogenology 2016, 86, 373–378. [Google Scholar] [CrossRef]
  5. Short, R.E.; Bellows, R.A.; Staigmiller, R.; Berardinelli, J.; Custer, E. Physiological mechanisms controlling anestrus and infertility in postpartum beef cattle. J. Anim. Sci. 1990, 68, 799–816. [Google Scholar] [CrossRef]
  6. Short, R.E.; Bellows, R.A. Relationships among weight gains, age at puberty and reproductive performance in heifers. J. Anim. Sci. 1971, 32, 127–131. [Google Scholar] [CrossRef]
  7. Ferrell, C.L. Effects of postweaning rate of gain on onset of puberty and productive performance of heifers of different breeds. J. Anim. Sci. 1982, 55, 1272–1283. [Google Scholar] [CrossRef]
  8. Lalman, D.L.; Petersen, M.K.; Ansotegui, R.P.; Tess, M.W.; Clark, C.K.; Wiley, J.S. The effects of ruminally undegradable protein, propionic acid, and monensin on puberty and pregnancy in beef heifers. J. Anim. Sci. 1993, 71, 2843–2852. [Google Scholar] [CrossRef]
  9. Kane, K.K.; Hawkins, D.E.; Pulsipher, G.D.; Denniston, D.J.; Krehbiel, C.R.; Thomas, M.G.; Petersen, M.K.; Hallford, D.M.; Remmenga, M.D.; Roberts, A.J.; et al. Effect of increasing levels of undegradable intake protein on metabolic and endocrine factors in estrous cycling beef heifers. J. Anim. Sci. 2004, 82, 283–291. [Google Scholar] [CrossRef]
  10. Hugentobler, S.A.; Diskin, M.G.; Leese, H.J.; Humpherson, P.G.; Watson, T.; Sreenan, J.M.; Morris, D.G. Amino acids in oviduct and uterine fluid and blood plasma during the estrous cycle in the bovine. Mol. Reprod. Dev. 2007, 74, 445–454. [Google Scholar] [CrossRef]
  11. Groebner, A.E.; Rubio-Aliaga, I.; Schulke, K.; Reichenbach, H.D.; Daniel, H.; Wolf, E.; Meyer, H.H.; Ulbrich, S.E. Increase of essential amino acids in the bovine uterine lumen during preimplantation development. Reproduction 2011, 141, 685–695. [Google Scholar] [CrossRef]
  12. Forde, N.; Simintiras, C.A.; Sturmey, R.; Mamo, S.; Kelly, A.K.; Spencer, T.E.; Bazer, F.W.; Lonergan, P. Amino acids in the uterine luminal fluid reflects the temporal changes in transporter expression in the endometrium and conceptus during early pregnancy in cattle. PLoS ONE 2014, 9, e100010. [Google Scholar] [CrossRef]
  13. Crouse, M.S.; Greseth, N.P.; McLean, K.J.; Crosswhite, M.R.; Pereira, N.N.; Ward, A.K.; Reynolds, L.P.; Dahlen, C.R.; Neville, B.W.; Borowicz, P.P.; et al. Maternal nutrition and stage of early pregnancy in beef heifers: Impacts on hexose and AA concentrations in maternal and fetal fluids. J. Anim. Sci. 2019, 97, 1296–1316. [Google Scholar] [CrossRef]
  14. Meier, S.; Mitchell, M.D.; Walker, C.G.; Roche, J.R.; Verkerk, G.A. Amino acid concentrations in uterine fluid during early pregnancy differ in fertile subfertile dairy cow strains. J. Dairy Sci. 2014, 97, 1364–1376. [Google Scholar] [CrossRef]
  15. Chandra, R.K. Nutrition and the immune system: An introduction. Am. J. Clin. Nutr. 1997, 66, 460S–463S. [Google Scholar] [CrossRef]
  16. Schjenken, J.E.; Tolosa, J.M.; Paul, J.W.; Clifton, V.L.; Smith, R.J. Mechanisms of maternal immune tolerance during pregnancy. In Recent Advances in Research on the Human Placenta; IntechOpen: London, UK, 2012; Volume 11, pp. 211–242. [Google Scholar]
  17. Krakowski, L.; Zdzisinska, B. Selected cytokines and acute phase proteins in heifers during the ovarian cycle course and in different pregnancy periods. J. Bull. Vet. Inst. Pulawy 2007, 51, 31. [Google Scholar]
  18. Espey, L.L.; Bellinger, A.S.; Healy, J.A. Chapter 9—Ovulation: An Inflammatory Cascade of Gene Expression. In The Ovary, 2nd ed.; Leung, P.C.K., Adashi, E.Y., Eds.; Academic Press: San Diego, CA, USA, 2004; pp. 145–165. [Google Scholar]
  19. Zolti, M.; Ben-Rafael, Z.; Meirom, R.; Shemesh, M.; Bider, D.; Mashiach, S.; Apte, R.N. Cytokine involvement in oocytes and early embryos. Fertil. Steril. 1991, 56, 265–272. [Google Scholar] [CrossRef]
  20. Simón, C.; Moreno, C.; Remohı, J.; Pellicer, A. Cytokines and embryo implantation. J. Reprod. Immunol. 1998, 39, 117–131. [Google Scholar] [CrossRef]
  21. Brandt, K.J.; Ault-Seay, T.B.; Payton, R.R.; Schneider, L.G.; Edwards, J.L.; Myer, P.R.; Rhinehart, J.D.; McLean, K.J. The impacts of supplemental protein during development on amino acid concentrations in the uterus and pregnancy outcomes of Angus heifers. Animals 2023, 13, 1995. [Google Scholar] [CrossRef]
  22. Geary, T.; Pas, J.W.; Thrift, F.; Dolezal, S. Effects of a timed insemination following synchronization of ovulation using the Ovsynch or CO-Synch protocol in beef cows. Prof. Anim. Sci. 1998, 14, 217–220. [Google Scholar] [CrossRef]
  23. Pang, Z.; Chong, J.; Zhou, G.; de Lima Morais, D.A.; Chang, L.; Barrette, M.; Gauthier, C.; Jacques, P.É.; Li, S.; Xia, J. MetaboAnalyst 5.0: Narrowing the gap between raw spectra and functional insights. Nucleic Acids Res. 2021, 49, W388–W396. [Google Scholar] [CrossRef]
  24. Ault-Seay, T.B.; Harrison, T.D.; Brandt, K.J.; Payton, R.R.; Schneider, L.G.; Myer, P.R.; Rhinehart, J.D.; Rispoli, L.A.; McLean, K.J. The effects of protein level on cytokines and chemokines in the uterine environment of beef heifers during development. J. Anim. Sci. 2021, 99, skab105. [Google Scholar] [CrossRef]
  25. Oliveira, L.J.; Mansourri-Attia, N.; Fahey, A.G.; Browne, J.; Forde, N.; Roche, J.F.; Lonergan, P.; Fair, T. Characterization of the Th Profile of the Bovine Endometrium during the Oestrous Cycle and Early Pregnancy. PLoS ONE 2013, 8, e75571. [Google Scholar] [CrossRef]
  26. McLean, K.J.; Ault-Seay, T.B.; Myer, P.R. Changes in vaginal cytokines concentrations during artificial insemination and natural service in beef heifers. BMC Res. Notes 2024, 17, 1–6. [Google Scholar] [CrossRef]
  27. Dalton, C.M. The Effects of Pregnancy Status on Vaginal Cytokine Profiles in Lactating Cows. Master’s Thesis, University of Tennessee, Knoxville, TN, USA, 2023. [Google Scholar]
  28. Sherry, B.; Tekamp-Olson, P.; Gallegos, C.; Bauer, D.; Davatelis, G.; Wolpe, S.D.; Masiarz, F.; Coit, D.; Cerami, A. Resolution of the two components of macrophage inflammatory protein 1, and cloning and characterization of one of those components, macrophage inflammatory protein 1 β. J. Exp. Med. 1988, 168, 2251–2259. [Google Scholar] [CrossRef] [PubMed]
  29. Antonelli, A.; Ferrari, S.M.; Giuggioli, D.; Ferrannini, E.; Ferri, C.; Fallahi, P. Chemokine (C–X–C motif) ligand (CXCL)10 in autoimmune diseases. Autoimmun. Rev. 2014, 13, 272–280. [Google Scholar] [CrossRef]
  30. Li, J.; Ge, M.; Lu, S.; Shi, J.; Li, X.; Wang, M.; Huang, J.; Shao, Y.; Huang, Z.; Zhang, J.; et al. Pro-inflammatory effects of the Th1 chemokine CXCL10 in acquired aplastic anaemia. Cytokine 2017, 94, 45–51. [Google Scholar] [CrossRef]
  31. Jiang, Y.; Huang, F.; Chai, X.; Yuan, W.; Ding, H.; Wu, X. The role of IP-10 and its receptor CXCR3 in early pregnancy. Mol. Immunol. 2021, 140, 59–69. [Google Scholar] [CrossRef]
  32. Taft, R.A. Virtues and limitations of the preimplantation mouse embryo as a model system. Theriogenology 2008, 69, 10–16. [Google Scholar] [CrossRef]
  33. Harrison, T.D.; Chaney, E.M.; Brandt, K.J.; Ault-Seay, T.B.; Payton, R.R.; Schneider, L.G.; Strickland, L.G.; Schrick, F.N.; McLean, K.J. The effects of nutritional level and body condition score on cytokines in seminal plasma of beef bulls. Front. Anim. Sci. 2023, 3, 1078960. [Google Scholar] [CrossRef]
  34. Raghupathy, R. Th 1-type immunity is incompatible with successful pregnancy. Immunol. Today 1997, 18, 478–482. [Google Scholar] [CrossRef]
  35. Wegmann, T.G.; Lin, H.; Guilbert, L.; Mosmann, T.R. Bidirectional cytokine interactions in the maternal-fetal relationship: Is successful pregnancy a TH2 phenomenon? Immunol. Today 1993, 14, 353–356. [Google Scholar] [CrossRef]
  36. Asselin, E.; Johnson, G.A.; Spencer, T.E.; Bazer, F.W. Monocyte chemotactic protein-1 and -2 messenger ribonucleic acids in the ovine uterus: Regulation by pregnancy, progesterone, and interferon-tau. Biol. Reprod. 2001, 64, 992–1000. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. The effects of protein supplementation or exposure to semen on cytokine profiles following synchronization and AI in ULF of beef heifers. (A) Orthogonal PLS-DA analysis of the pairwise comparison of protein supplements CON (red) and P20 (green) in ULF on cytokine profiles (p = 0.56), (B) orthogonal PLS-DA analysis of the pairwise comparison of protein supplements CON (red) and P40 (green) in ULF on cytokine profiles (p = 0.73), (C) orthogonal PLS-DA analysis of the pairwise comparison of protein supplements P20 (red) and P40 (green) in ULF on cytokine profiles (p = 0.99), and (D) orthogonal PLS-DA analysis of the pairwise comparison of exposure (E; red) and not inseminated (NE; green) in ULF on cytokine profiles (p = 0.64).
Figure 1. The effects of protein supplementation or exposure to semen on cytokine profiles following synchronization and AI in ULF of beef heifers. (A) Orthogonal PLS-DA analysis of the pairwise comparison of protein supplements CON (red) and P20 (green) in ULF on cytokine profiles (p = 0.56), (B) orthogonal PLS-DA analysis of the pairwise comparison of protein supplements CON (red) and P40 (green) in ULF on cytokine profiles (p = 0.73), (C) orthogonal PLS-DA analysis of the pairwise comparison of protein supplements P20 (red) and P40 (green) in ULF on cytokine profiles (p = 0.99), and (D) orthogonal PLS-DA analysis of the pairwise comparison of exposure (E; red) and not inseminated (NE; green) in ULF on cytokine profiles (p = 0.64).
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Figure 2. The effects of protein supplementation or exposure to semen on cytokine profiles following synchronization and AI in ULF of beef heifers. (A) The effects of protein supplementation on MIP-1β. The pooled standard error for all groups was 123.9 pg. Means without a common letter were different by p < 0.05. (B) The effects of insemination on IP-10 (inseminated n = 47 vs. not inseminated n = 12). The pooled standard error for all groups was 550 pg.
Figure 2. The effects of protein supplementation or exposure to semen on cytokine profiles following synchronization and AI in ULF of beef heifers. (A) The effects of protein supplementation on MIP-1β. The pooled standard error for all groups was 123.9 pg. Means without a common letter were different by p < 0.05. (B) The effects of insemination on IP-10 (inseminated n = 47 vs. not inseminated n = 12). The pooled standard error for all groups was 550 pg.
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Figure 3. The effects of protein supplementation and exposure to semen (inseminated n = 47 vs. not inseminated n = 12) on MIP-1α following synchronization and AI in ULF of beef heifers. The pooled standard error for all groups was 127.2 pg.
Figure 3. The effects of protein supplementation and exposure to semen (inseminated n = 47 vs. not inseminated n = 12) on MIP-1α following synchronization and AI in ULF of beef heifers. The pooled standard error for all groups was 127.2 pg.
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MDPI and ACS Style

McLean, K.J.; Brandt, K.J.; Ault-Seay, T.B.; Payton, R.R.; Schneider, L.G.; Edwards, J.L.; Myer, P.R.; Rhinehart, J.D. The Impacts of Protein Supplementation and Semen Exposure on Uterine Cytokines in Beef Heifers. Agriculture 2025, 15, 1642. https://doi.org/10.3390/agriculture15151642

AMA Style

McLean KJ, Brandt KJ, Ault-Seay TB, Payton RR, Schneider LG, Edwards JL, Myer PR, Rhinehart JD. The Impacts of Protein Supplementation and Semen Exposure on Uterine Cytokines in Beef Heifers. Agriculture. 2025; 15(15):1642. https://doi.org/10.3390/agriculture15151642

Chicago/Turabian Style

McLean, Kyle J., Kiernan J. Brandt, Taylor B. Ault-Seay, Rebecca R. Payton, Liesel G. Schneider, J. Lannett Edwards, Phillip R. Myer, and Justin D. Rhinehart. 2025. "The Impacts of Protein Supplementation and Semen Exposure on Uterine Cytokines in Beef Heifers" Agriculture 15, no. 15: 1642. https://doi.org/10.3390/agriculture15151642

APA Style

McLean, K. J., Brandt, K. J., Ault-Seay, T. B., Payton, R. R., Schneider, L. G., Edwards, J. L., Myer, P. R., & Rhinehart, J. D. (2025). The Impacts of Protein Supplementation and Semen Exposure on Uterine Cytokines in Beef Heifers. Agriculture, 15(15), 1642. https://doi.org/10.3390/agriculture15151642

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