Data-derived reference profiles with corepresentation of progesterone, estradiol, LH, and FSH dynamics during the bovine estrous cycle

The effect of progesterone concentrations during superovulation of Holstein heifers in a randomized trial

The aim of this study was to evaluate the effect of different progesterone (P4) concentrations during the follicular growth on the intensity of estrous expression, ovarian response to the superovulatory treatment, and embryo production and quality in superovulated heifers. A total of 63 Holstein heifers were randomly assigned into 2 experimental groups: Low P4 (n = 31) and High P4 (n = 32). Animals received a pre-synchronization protocol followed by a protocol of superovulation that included the allocated P4 treatment. Activity was monitored continuously by an automated activity monitor, and estrus characteristics (maximum intensity and duration) were recorded. Embryo collection was performed 7 d post artificial insemination (AI). Embryos were counted and graded from good or excellent (1) to degenerated (4). The outcomes of interest were: number and diameter of follicles at the time of AI, ovulation success (confirmed 7 d post-AI), time to estrus event, maximum intensity and duration of estrus, number and quality of embryos. Data were analyzed according to the type of outcome variable using logistic, linear, or Poisson regression models. A total of 105 embryos (High P4: n = 42; Low P4: n = 63) were graded for quality. Different P4 levels did not affect the maximum intensity (High P4 = 497.8 ± 23.9%; Low P4 = 542.2 ± 23.5%) or the duration (High P4 = 13.5 ± 1.5 h; Low P4 = 14.3 ± 1.4 h) of estrus. Heifers in the High P4 treatment had greater number of follicles at time of AI (High P4 = 16.6 ± 1.6 follicles; Low P4 = 13.9 ± 1.2 follicles), but with smaller diameter (High P4 = 11.3 ± 0.1 mm; Low P4 = 12.0 ± 0.1 mm) compared with Low P4. High P4 heifers tended to have better embryo quality compared with Low P4 heifers (odds ratio = 1.98; 95% CI = 0.90-4.35). High P4 heifers had less embryos than Low P4 heifers, but this was modified by the CIDR (intravaginal implant of P4) removal to estrus interval (interval 0-21 h: mean ratio = 1.15, 95% CI = 0.42-1.87; interval 22-46 h: mean ratio = 0.58, 95% CI = 0.27-0.96). Although estrous expression was not associated with embryo quality, as the duration and the maximum intensity of estrous expression increased, the number of embryos recovered 7 d post-AI increased (duration: mean ratio = 1.04; 95% CI = 1.03-1.05; maximum intensity: mean ratio = 1.50; 95% CI = 1.42-1.58). In conclusion, P4 during the follicular growth, and intensity of estrus, are playing a role in regulating the quality and the number of embryos produced by superovulated heifers. This study was supported by contributions from Resilient Dairy Genome Project and the Natural Sciences and Engineering Research Council.

Traditional Chinese herbal medicine complex supplementation improves reproductive performance, serum biochemical parameters, and anti-oxidative capacity in periparturient dairy cows

This study was conducted to investigate the effects of a traditional Chinese herbal medicine complex (TCHMC) on the productive performance of periparturient dairy cows. Eighteen non-lactating pregnant Holstein dairy cows with similar body conditions with 1 to 2 parity were randomly divided into three groups (n = 6), receiving a basal diet with 0 (CON group), 200 (T-200 group), and 300 (T-300 group) g TCHMC per day from 14 to 9 days prepartum. The results demonstrated that TCHMC treatments decreased the days of gestation, calving to first service, and calving to first visible estrus. Compared with CON at specific time points, TCHMC treatments increased the concentrations of follicle-stimulating hormone (FSH), luteinizing hormone (LH), and estradiol (E₂), whereas progesterone (P₄) and E₂ concentrations decreased. Serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), and creatine kinase (CK) concentrations were downregulated, whereas that of globulin (GLB) and immunoglobulin G (IgG) were upregulated by TCHMC treatments around the time of calving. Compared with CON and T-200 treatments, the T-300 treatment increased the serum concentrations of glutathione peroxidase (GSH-Px), superoxide dismutase (SOD), catalase (CAT) and total antioxidant capacity (T-AOC) and decreased the malondialdehyde (MDA) concentration from 7 d prepartum to 21 d postpartum when. In addition, although TCHMC treatment had no effect on average birth weight, heart rate, respiratory rate, and body temperature of calves, the T-300 treatment increased serum albumin (ALB) and IgG concentrations in calves from 3 to 14 days postpartum. The addition of TCHMC used in the present study could serve as a potential effective strategy to improve the health and productive performance of periparturient dairy cows, and the optimal dose should be set at 300 g per day.

Interactions of circulating estradiol and progesterone on changes in endometrial area and pituitary responsiveness to GnRH†

Changes in circulating progesterone (P4) and estradiol (E2) during proestrus produce dynamic changes in endometrial function and pituitary release of gonadotropins. Independent and combined effects of P4 and E2 on endometrium and pituitary were evaluated. In a preliminary study, an exogenous hormone model of proestrus was created by removal of corpus luteum and follicles ≥5 mm followed by gradual removal of intravaginal P4 implants during 18 h and treatment with increasing doses of estradiol benzoate during 48 h to mimic proestrus using high E2 (n = 9) or low E2 (n = 9). Decreased P4, increased E2, and increased endometrial area (EA) simulated proestrus in high-E2 cows and this was used subsequently. The main experiment used a 2 × 2 factorial design with: high E2 and low P4 (n = 11); high E2 and high P4 (n = 11); low E2 and high P4 (n = 11); low E2 and low P4 (n = 10). At 48 h, gonadotropin-releasing hormone (GnRH)-induced luteinizing hormone (LH) and follicle stimulating hormone (FSH) release was determined. Variables were analyzed using PROCMIXED of Statistical Analysis System. The EA increased dramatically during 48 h only in high-E2 and low-P4 cows. For FSH, high-E2 cows had greater area under the curve (AUC) and FSH peak after GnRH than low E2, with mild negative effects of high P4. For LH, concentration at peak and AUC were 2-fold greater in high E2 compared to low-E2 groups, with low P4 also 2-fold greater than high-P4 groups. Thus, maximal changes in uterus and pituitary during proestrus depend on both low P4 and high E2, but different physiologic responses are regulated differently by E2 and P4. Changes in endometrium depend on low P4 and high E2, whereas GnRH-induced FSH secretion primarily depends on high E2, and GnRH-induced LH secretion is independently increased by high E2 or reduced by high P4.

Variability of serum reproductive hormones in cows presenting various reproductive conditions in semi-arid areas of the North West Province, South Africa

Background and Aim:

Hormones play a significant role in supporting reproductive processes. Predisposition to metabolic disorders may result from biological alterations in the neurohormonal system, thus leading to impaired immune function and poor reproductive performance. The aim of this study was to determine the reproductive hormonal profile in cows with reproductive conditions in semi-arid areas of the North West Province, South Africa, to establish possible correlations between different conditions and the hormonal profile.

Materials and Methods:

Blood samples were collected from cows in different communal areas of Mafikeng. Convenience sampling was used to collect samples for the study. Blood samples were collected cows experiencing dystocia (n=50), retained placenta (n=13), downer cow syndrome (n=34), vaginal prolapse (n=16), and abortions (n=69), following cases reported at the Animal Health Hospital of the North-West University, Mafikeng Campus. Descriptive statistics, such as mean and standard deviations, were used to describe the distribution of hormone levels across reproductive conditions. p-value less than the significance level was set at 5% (p<0.05).

Results:

Data obtained revealed significantly higher estradiol in abortion (1122.99±71.99 pg/ml), downer cow syndrome (781.32±135.7 pg/ml), and dystocia (862.09±123.44 pg/ml). Oxytocin (OT) differed significantly in cows with dystocia (370.50±71.66 pg/ml) and abortion (574.73±60.65 pg/ml). Significantly low progesterone (Pg) was observed in abortion (2.45±1.509 ng/ml) and dystocia (8.59±0.402 ng/ml) while increased prostaglandin alpha was observed in cows with vaginal prolapse and abortion.

Conclusion:

The findings highlight an increase in serum estradiol and OT in aborting cows. Low Pg and estradiol in cows with vaginal prolapses and retained placenta were noted. An association was seen between downer cow syndrome and high concentrations of estradiol and Pg. Prostaglandin alpha may increase in cases of vaginal prolapse and abortion. Hormonal alterations were observed and may contribute to the incidences of different reproductive conditions.

Genetic parameters of endocrine fertility traits based on in-line milk progesterone profiles in Swedish Red and Holstein dairy cows

Evaluating fertility traits based on endocrine progesterone profiles is becoming a promising option to improve dairy cow fertility. Several studies have been conducted on endocrine fertility traits, mainly in the Holstein breed. In this study, focusing also on the Swedish Red (SR) breed, genetic parameters were estimated for classical and endocrine fertility traits, the latter based on in-line milk progesterone records obtained for 14 Swedish herds using DeLaval Herd Navigator (DeLaval International, Tumba, Sweden). A total of 210,403 observations from 3,437 lactations of 1,107 SR and 1,538 Holstein cows were used. Mixed linear animal models were used for estimation of genetic parameters. Least squares means analysis showed that Holstein cows had a 2.5-d-shorter interval from calving to commencement of luteal activity (C-LA) and longer length of first inter-ovulatory interval (IOI) than SR cows. The highest mean interval for C-LA, IOI, and first luteal phase length (LPL) was observed in the fourth parity. The incidence of short (<18 d), normal, (18-24 d), and long (>24 d) IOI was 29.3, 40.7, and 30%, respectively. Genetic analysis indicated moderate heritability (h²) for C-LA (h² = 0.24), luteal activity during the first 60 d in milk (LA60, h² = 0.15), proportion of samples with luteal activity (PLA, h² = 0.13), and calving to first heat (CFH, h² = 0.18), and low heritability estimates for LPL (h² = 0.08) and IOI (h² = 0.03) in the combined data set for both breeds. Similar heritability estimates were obtained for each breed separately except for IOI and LPL in SR cows, for which heritability was estimated to be zero. Swedish Red cows had 0.01 to 0.06 higher heritability estimates for C-LA, LA60, and PLA than did Holstein cows. Calving interval had moderate heritability among the classical traits for Holstein and the combined data set, but h² was zero for SR. Commencement of luteal activity had a strong genetic correlation with LA60 (mean ± SE; -0.88 ± 0.06), PLA (-0.72 ± 0.11), and CFH (0.90 ± 0.04). Similarly, CFH had a strong genetic correlation with IOI (0.98 ± 0.20). Number of inseminations per series showed a weak genetic correlation with all endocrine traits except IOI. Overall, endocrine traits had higher heritability estimates than classical traits in both breeds, and may have a better potential to explain the actual reproductive status of dairy cows than classical traits. This might favor inclusion of some endocrine fertility traits-especially those related to commencement of luteal activity-as selection criteria and breeding goal traits if recording becomes more common in herds. Further studies on genetic and genomic evaluations for endocrine fertility traits may help to provide firm conclusions. A prerequisite is that the data from automatic devices be made available to recording and breeding organizations in the future and included in a central database.

Validation of a novel milk progesterone-based tool to monitor luteolysis in dairy cows: Timing of the alerts and robustness against missing values

Automated monitoring of fertility in dairy cows using milk progesterone is based on the accurate and timely identification of luteolysis. In this way, well-adapted insemination advice can be provided to the farmer to further optimize fertility management. To properly evaluate and compare the performance of new and existing data-processing algorithms, a test data set of progesterone time-series that fully covers the desired variability in progesterone profiles is needed. Further, the data should be measured with a high frequency to allow rapid onset events, such as luteolysis, to be precisely determined. Collecting this type of data would require a lot of time, effort, and budget. In the absence of such data, an alternative was developed using simulated progesterone profiles for multiple cows and lactations, in which the different fertility statuses were represented. To these, relevant variability in terms of cycle characteristics and measurement error was added, resulting in a large cost-efficient data set of well-controlled but highly variable and farm-representative profiles. Besides the progesterone profiles, information on (the timing of) luteolysis was extracted from the modeling approach and used as a reference for the evaluation and comparison of the algorithms. In this study, 2 progesterone monitoring tools were compared: a multiprocess Kalman filter combined with a fixed threshold on the smoothed progesterone values to detect luteolysis, and a progesterone monitoring algorithm using synergistic control, PMASC, which uses a mathematical model based on the luteal dynamics and a statistical control chart to detect luteolysis. The timing of the alerts and the robustness against missing values of both algorithms were investigated using 2 different sampling schemes: one sample per cow every 8 h versus 1 sample per day. The alerts for luteolysis of the PMASC algorithm were on average 20 h earlier compared with the ones of the multiprocess Kalman filter, and their timing was less sensitive to missing values. This was shown by the fact that, when 1 sample per day was used, the Kalman filter gave its alerts on average 24 h later, and the variability in timing of the alerts compared with simulated luteolysis increased with 22%. Accordingly, we postulate that implementation of the PMASC system could improve the consistency of luteolysis detection on farm and lower the analysis costs compared with the current state of the art.

Coupling a reproductive function model to a productive function model to simulate lifetime performance in dairy cows

Reproductive success is a key component of lifetime performance in dairy cows but is difficult to predict due to interactions with productive function. Accordingly, this study introduces a dynamic model to simulate the productive and reproductive performance of a cow during her lifetime. The cow model consists of an existing productive function model (GARUNS) which is coupled to a new reproductive function model (RFM). The GARUNS model simulates the individual productive performance of a dairy cow throughout her lifespan. It provides, with a daily time step, changes in BW and composition, fetal growth, milk yield and composition and food intake. Genetic-scaling parameters are incorporated to scale individual performance and simulate differences within and between breeds. GARUNS responds to the discrete event signals 'conception' and 'death' (of embryo or fetus) generated by RFM. In turn, RFM responds to the GARUNS outputs concerning the cow's energetic status: the daily total processed metabolizable energy per kg BW (TPEW) and the net energy balance (EB). Reproductive function model models the reproductive system as a compartmental system transitioning between nine competence stages: prepubertal (PRPB), anestrous (ANST), anovulatory (ANOV), pre-ovulating (PREO), ovulating (OVUL), post-ovulating (PSTO), luteinizing (LUTZ), luteal (LUTL) and gestating (GEST). The transition from PRPB to ANST represents the start of reproductive activity at puberty. The cyclic path through ANST, PREO, OVUL, PSTO, LUTZ and LUTL forms the regime of ovulatory cycles, whereas ANOV and GEST are transient stages that interrupt this regime. Anovulatory refers explicitly to a stage in which ovulation cannot occur (i.e. interrupted cyclicity), whereas ANST is a pivotal stage within ovulatory cycles. Reproductive function model generates estradiol and progesterone hormonal profiles consistent with reference profiles derived from literature. Cyclicity is impacted by the GARUNS output EB and clearance of estradiol is impacted by TPEW. A farming system model was designed to describe different farm protocols of heat detection, insemination, feeding (amount and energy density), drying-off and culling. Results of model simulation (10 000 simulations of individual cows over 5000 days lifetime period, with randomly drawn genetic-scaling parameters and standard diet) are consistent with literature for reproductive performance. This model allows simulation of deviations in reproductive trajectories along physiological stages of the cow reproductive cycle. It thus provides the basis for evaluation of the relative importance of different factors affecting fertility at individual cow and herd levels across different breeds and management environments.

Milk Production and Fertility in Cattle

Evolutionary biology provides reasons for why the intensive selection for milk production reduces reproductive success rates. There is considerable exploitable genetic variation in reproductive performance in both dairy and beef cattle, and examination of national genetic trends demonstrates that genetic gain for both reproductive performance and milk production is possible in a well-structured breeding program. Reproductive failure is often postulated to be a consequence of the greater negative energy balance associated with the genetic selection for increased milk production. However, experimental results indicate that the majority of the decline in reproductive performance cannot be attributed to early lactation energy balance, per se; reproductive success will, therefore, not be greatly improved by nutritional interventions aimed at reducing the extent of negative energy balance. Modeling can aid in better pinpointing the key physiological components governing reproductive success and, also, the impact of individual improvements on overall fertility, helping to prioritize variables for inclusion in breeding programs.