Methods for and Implementation of Pregnancy Diagnosis in Dairy Cows

Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle

This study aimed to compare the accuracy of IFN-τ stimulated gene abundance (ISGs) in peripheral blood mononuclear cells (PBMCs), CL blood perfusion by Doppler ultrasound (Doppler-US), plasma concentration of P4 on Day 21 and pregnancy-associated glycoproteins (PAGs) test on Day 25 after timed-artificial insemination (TAI) for early pregnancy diagnosis in dairy cows and heifers. Holstein cows (n = 140) and heifers (n = 32) were subjected to a hormonal synchronization protocol and TAI on Day 0. On Day 21 post-TAI, blood samples were collected for PBMC isolation and plasma concentration of P4. The CL blood perfusion was evaluated by Doppler-US. Plasma samples collected on Day 25 were assayed for PAGs. The abundance of ISGs (ISG15 and RSAD2) in PBMCs was determined by RT-qPCR. Pregnancy was confirmed on Days 32 and 60 post-TAI by B-mode ultrasonography. Statistical analyses were performed by ANOVA using the MIXED procedure and GLIMMIX in SAS software. The pregnancy biomarkers were used to categorize the females as having undergone late luteolysis (LL); early embryonic mortality (EEM); late embryonic mortality (LEM); or late pregnancy loss (LPL). The abundance of ISGs, CL blood perfusion by Doppler-US, and concentrations of P4 on Day 21, and PAGs test on Day 25 were significant (P < 0.05) predictors of early pregnancy in dairy cows and heifers. Dairy cows had a greater (P = 0.01) occurrence of LL than heifers, but there was no difference (P > 0.1) for EEM, LEM, and LPL in heifers compared to cows. Cows with postpartum reproductive issues had a greater (P = 0.008) rate of LEM and a lesser (P = 0.01) rate of LPL compared to cows without reproductive issues. In summary, the CL blood perfusion by Doppler-US had the highest accuracy and the least number of false negatives, suggesting it is the best predictor of pregnancy on Day 21 post-TAI. The PAGs test was the most reliable indicator of pregnancy status on Day 25 post-TAI in dairy heifers and cows. The application of machine learning, specifically the MARS algorithm, shows promise in enhancing the accuracy of predicting early pregnancies in cows.

Optimizing ReBreed21 II: Fertility and reproductive efficiency in different parities during a shortened breeding season in beef cattle

This study evaluated the efficiency of a rapid reinsemination program allowing timed AI (TAI) every 21d (ReBreed21) in a commercial beef cow-calf operation. Nelore females from different parities (n = 2085) were synchronized for first TAI (D0 = TAI) using an estradiol/progesterone (E2/P4) protocol and assigned to one of three reinsemination programs: Resynch33 (n = 753), traditional resynch program with second TAI at D42 after first TAI; ReBreed21 (n = 687); or ReBreed21+EC (n = 670). The ReBreed females (n = 1357) received intravaginal P4 insert on D12, on D19 P4 was removed, and a dose of equine chorionic gonadotropin (eCG) was administered, then, ReBreed21 females received 0.6 mg of EC (ReBreed21+EC) or nothing (ReBreed21) and on D21, nonpregnancy (NP) was determined using Doppler ultrasound to detect corpus luteum (CL) blood flow (BF) (NP: <25 % BF pixels of total CL area) and NP cows received immediate TAI and GnRH to induce ovulation. Pregnancy diagnosis was performed at D33 after TAI following all TAIs. Cows considered pregnant at D21, based on CL BF, but NP on D33 were designated False-Positives (FP) and false negatives (FN) were number of nonpregnant cows/heifers on d21 based on the CL BF found to subsequently be pregnant on D33 divided by the total number pregnant. Pregnancy/AI (P/AI) did not differ for the first TAI (55.1 %) among the treatments. Heifers had similar P/AI at the second AI in all groups and similar to the first AI. Primiparous had greater P/AI in ReBreed21+EC and Resynch33 at s TAI compared to ReBreed21, 51.7 %, 55.8 %, 34.2 %, respectively. Multiparous had greater P/AI at second TAI in Resynch33 (60.9 %) than ReBreed21 programs (34.7 %). The percentage FP and FN among ReBreed21 programs did not differ, 13.8 and 0.2 %, respectively. Overall accumulative pregnancies on D21 of the breeding season were greater for ReBreed21 and ReBreed21+EC than Resynch33 (69.7 %, 71.6 %, and 55.5 %, respectively). However, on D42 of the breeding season, only heifers had greater pregnancies in ReBreed21 programs than Resynch33 (73.3 %, 74.3.6 %, and 63.2 %, respectively). Average days to pregnancy were less (P = 0.01) for ReBreed21 and ReBreed21+EC than Resynch33. Thus, the ReBreed21 strategy can improve the efficiency of TAI programs in beef cattle. Of interest, ReBreed21 was particularly effective in nulliparous, somewhat effective in primiparous when EC was added to the program, but relatively ineffective in multiparous beef cattle.

Influence of sub-clinical endometritis on early pregnancy predictors and proinflammatory cytokines in circulating immune cells in dairy cows

In Experiment 1, PBMC were isolated from cows considered healthy or with SCE (n=6/group) on Days 0 (estrus) and 7 (diestrus) of a synchronized estrous cycle. In Experiment 2, on D21 (D0 was defined as the day of Fixed Timed Artificial Insemination (FTAI), cows were evaluated by ultrasonography to assess luteal blood perfusion and PBMC were isolated. On D32, cows were classified into: healthy pregnant (n=7), pregnant with SCE (n=4), healthy non-pregnant (n=8), and non-pregnant with SCE (n=10). Gene expression of ISGs (ISG15, OAS1, MX1 and IFI6) and proinflammatory cytokines (IL1-β, TNF-α and IFN-γ) were determined. Expression of ISG15, MX1, IFI6, TNF-α and IFN-γ did not differ between SCE and healthy cows and between Days 0 and 7. Expression of OAS1 and IL1-β were higher (P=0.02) on Day 7 than Day 0, regardlees of the SCE presence. In Exp.2, ISG15 abundance was 2.5-fold greater (P=0.0008), TNF-α was 2.2-fold greater (P=0.05), and IL1-β tended (P=0.06) to be 2.4-fold higher in pregnant than non-pregnant cows. Luteal blood perfusion was greater (P=0.01) in pregnant animals. In conclusion, OAS1 and IL1-β are transcripts upregulated in PBMC at diestrus, regardless of SCE occurrence. Proinflammatory cytokines are not affected by SCE occurrence, but IL1-β and TNF-α are upregulated in pregnant animals on D21 of pregnancy. ISG15 abundance is a good pregnancy predictor, regardless SCE presence.

Development and evaluation of a lateral flow-based portable optical system for determination of the pregnancy status of dairy cows

Our objectives were to develop and evaluate an integrated system consisting of a lateral-flow immunoassay (LFIA) and an electronic portable imaging device for determination of pregnancy status of cows based on plasma concentrations of pregnancy-specific protein B (PSPB). Experiment 1 was conducted to test the performance of the LFIA for PSPB (PSPB-LFIA) whereas experiment 2 was conducted to evaluate the performance of the integrated system including both the LFIA and imaging device. The PSPB-LFIA strips were made of nitrocellulose membrane with polystreptavidin, anti-mouse antibody, Europium-anti-PSPB conjugates, and biotin-PSPB. After adding buffer and plasma in a 96-well plate, strips were dipped to initiate flow and were read in a fluorescence microscope to estimate PSPB concentrations based on the test-to-control line signal (T/C ratio). The T/C ratio of standards was linearly associated with PSPB (R2 = 0.99 in both experiments) concentrations. To test the ability to identify pregnant cows of the PSPB-LFIA only or the integrated system, plasma samples were collected and transrectal ultrasonography (TUS) was conducted 29 to 35 d post AI in lactating Holstein cows (Experiment 1: n = 83; Experiment 2: n = 205). A cow was considered pregnant (Preg) if concentrations of PSPB in plasma obtained by ELISA were ≥2 ng/mL or if an embryo was visible by TUS. In Experiment 1, the accuracy of the PSPB-LFIA compared with ELISA was 92.7% (91.2% Se; 96.1% Sp; 98.1% PPV; 83.3% NPV) and compared with TUS was 90.4% (100% Se; 78.9% Sp; 84.9% PPV; 100% NPV). The agreement between LFIA and ELISA (kappa = 0.84; 95%CI 0.71-0.96) or LFIA and TUS (kappa = 0.80; 95%CI 0.67-0.93) as methods to classify cows as Preg or Non-Preg was high. In Experiment 2, the accuracy of the PSPB-LFIA compared with ELISA was 96.1% (93.8% Se; 100% Sp; 100% PPV; 90.5% NPV) and compared with TUS was 92.2% (99.0% Se; 84.7% Sp; 87.6% PPV; 98.8% NPV). The agreement between LFIA and ELISA (kappa = 0.92; 95%CI 0.86-0.97) or LFIA and TUS (kappa = 0.84; 95%CI 0.77-0.92) as methods to classify cows as Preg or Non-Preg was high. We conclude that a system integrating a fluorescence-based LFIA and an optical reader was effective for classifying cows as pregnant or not pregnant based on estimations of plasma concentrations of PSPB. This novel system serves as a platform for further development of on-farm pregnancy testing tools based on measurement of biomarkers of pregnancy in bodily fluids of cattle.

Potential of Circulating miRNA Biomarkers and Exosomes for Early Pregnancy Diagnoses in Cattle

Circulating microRNAs (miRNAs) were investigated as biomarkers for the diagnosis of early pregnancy in cattle. The levels of prospective miRNA biomarkers and the features of extracellular vesicles (EVs) in the blood were evaluated. In Study 1, plasma samples from cows 21 days after artificial insemination (AI) were examined using RT-qPCR to determine the levels of seven circulating miRNAs. Only the levels of miR-126-3p were significantly lower in the pregnant group than in the non-pregnant group. In Study 2, among individuals not pregnant at the first AI, the miRNA levels were compared between the individuals pregnant at the second AI and those who remained non-pregnant. The miR-25 levels were significantly higher in the pregnant group at the second AI than in the pregnant group at the first AI; miR-19b, miR-27b, and miR-29a levels were also high. In the non-pregnant group, changes were absent in the miRNA levels in the same individual between the first and second AIs. In Study 3, Western blotting and RT-qPCR showed the presence of miRNAs in EVs and their levels were lower than in plasma. Thus, circulating miR-126-3p may serve as a biomarker for the diagnosis of early pregnancy in cattle. In addition, the expression of some miRNAs tended to be higher during pregnancy than during non-pregnancy in the same individual, suggesting their potential as an index to determine pregnancy and non-pregnancy rates using a comparative method.

Pregnancy evaluation with a point-of-care pregnancy test in dairy cattle

Primiparous and multiparous dairy cattle were evaluated for pregnancy using both transrectal ultrasonography and a point-of-care pregnancy test (Alertys OnFarm Test), which measures pregnancy-associated glycoproteins through lateral diffusion, between Days 28-34 of pregnancy results were compared. A total of 637 animals were included in this study. Pregnancy was confirmed via manual palpation between Days 57-64. Data on parity, calving, and time of artificial insemination (AI) were also collected and evaluated. Overall the accuracy of the lateral diffusion test was 93.1% with 98.9% sensitivity, 88.7 % specificity, 86.8 % positive predictive value, and 99.1% negative predictive value. In heifers, the Alertys OnFarm Test had 100% sensitivity and 81.6% specificity. In contrast, the test had a sensitivity and specificity of 98.5 and 89.5%, respectively for multiparous cows. The pregnancy loss between early diagnosis and confirmation increased with parity. Heifers suffered losses as low as 2.6%, whereas animals in the third parity had significantly more losses (17.9%). Season also affected losses with spring pregnancy losses being considerably higher than autumn losses. The veterinary workload was also evaluated. Using the combined method of pregnancy testing, animals were first tested with the lateral diffusion test; then, the test-negative animals were scanned again, and the number of scanned animals was reduced. The results ranged between 3274% on farms. We concluded that veterinary workload could be reduced by using the point-of-care test. However, farm-level differences may have affected the results of the present study.

Interferon-Stimulated Gene Expression in Peripheral Blood Leucocytes as a Convenient Prediction Marker for Embryo Status in Embryo-Transferred Japanese Black Cows during the Peri-Implantation Period

Pregnancy diagnosis during early gestation is important for cattle reproduction. The expression of interferon-stimulated genes (ISGs) in peripheral blood leukocytes (PBLs) was studied in embryo-transferred (ET) Japanese Black cattle. ISGs in PBLs-ISG15, MX1, MX2, and OAS1-were detected in multiple ovulation ET cattle using a real-time quantitative polymerase chain reaction, and receiver operating characteristic (ROC) curve analysis was performed. Gestational status was predicted using the average ISG levels during the normal estrous cycle (AVE) and the Youden index from the ROC curve analysis as cutoff values. The ISG15, MX1, and MX2 levels were significantly higher in pregnant cattle (n = 10) than in non-pregnant cattle (n = 23) on gestation day 21, whereas the levels of all ISGs were similar between non-pregnant and non-pregnant cattle with late embryonic death (n = 7). ISG15, MX1, and MX2 appropriately predicted the gestational status of ET cows. The statistical evaluation of the diagnostic accuracy in ET cows on day 21 of gestation presented higher values of sensitivity, specificity, accuracy, and positive predictive values of ISG15, MX1, and MX2 using the Youden index than using the AVE. Therefore, ISG15, MX1, and MX2 are excellent biomarkers of gestational status during the peri-implantation period in ET cattle.

Key performance indicators used by dairy consultants during the evaluation of reproductive performance during routine visits

Dairy farms need thorough and efficient reproduction control. Consultants specialized in reproduction use key performance indicators (KPI) to monitor the reproductive performance of farms and must be able to decipher between the approach in a first visit and routine visits. A total of 49 consultants specialized in dairy reproduction from 21 countries responded to an online survey conducted to determine the most suitable parameters during routine visits every 2 to 4 weeks. The survey was comprised of 190 questions, 178 of them rated from 0 (irrelevant) to 10 (maximum importance) points. The questions were divided into five sections: (1) consultant and farm model, (2) general data of the farm, (3) cow reproduction, (4) postpartum and metabolic disease, and (5) heifer reproduction. The median, interquartile range, minimum and maximum values, and 95% confidence interval were determined for each question. Afterward, a multivariate analysis, using between-group linkage via Ward's hierarchical clustering was conducted to generate clusters of consultants according to their response pattern. Finally, a chi-square test was conducted to assess the association between years of experience of the consultant and farm size within the clusters generated in each section of the questionnaire. The majority of the consultants considered 34 parameters to be highly important (rated 8-10) to analyze during routine visits. The consultants used several KPI (in variable quantitative range) to evaluate any of the presented sections and considered that all the five sections are critical to control. They are aware of using KPI that reflect heat detection, fertility, and farming efficiency as well as KPI that can provide information on reproductive efficiency in the near future for cows, such as postpartum and metabolic diseases. However, parameters that are relatively old and ineffective, in terms of reproductive performance control, are still highly regarded by the majority of consultants in a routine-visit scenario. Farm size and years of experience of the consultant did not influence the type or number of parameters chosen as KPI during routine visits. The parameters rated with the highest importance (rate 10) that could be considered for an easy, fast, and universal use in routine visits to assess the reproductive status were: First service CR (%), Overall pregnancy rate (%) for cows, and age at first calving (d) for heifers.

Comparative evaluation of two commercial pregnancy-associated glycoproteins tests for early detection of pregnancy in dairy cattle

The aim of this study was to determine and compare the diagnostic accuracy of two pregnancy-associated glycoproteins tests (IDEXX on-farm pregnancy test [OFPT] and IDEXX rapid visual pregnancy test [RVPT]) for early pregnancy diagnosis in dairy cattle. Blood samples were collected from Holstein cows (n = 317) by coccygeal venipuncture 28-31 days after artificial insemination (AI). The OFPT and RVPT were performed on the farm within 2 h after blood collection using whole blood or blood serum. Transrectal ultrasonography (USG) was performed for pregnancy diagnosis on day 32 post-AI as a gold standard. One-hundred fourteen cows were diagnosed as pregnant and 203 were determined to be nonpregnant. Furthermore, embryonic mortality was detected in four of the nonpregnant animals, based on fragmented/dispersed embryonic membranes and the absence of heartbeat. Sixteen and 14 false positive results (13 jointly for both tests) were obtained for the RVPT and OFPT, respectively. Three false negative results were obtained for the RVPT. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy for the OFPT were 100%, 93.1%, 89.1%, 100% and 95.6%, and for RVPT were 97.4%, 92.1%, 87.4%, 98.4% and 94.0%, respectively. The ability of both tests to distinguish between pregnant and open cows was very good (AUC of both tests above 0.9). The OFPT and RVPT almost perfectly agreed with each other. According to McNemar's analysis, false positive results have been caused difference between the two pregnancy tests and USG. In conclusion, both the RVPT and OFPT proved to be reliable and practical methods for pregnancy diagnosis 28-31 days after AI in dairy cows. However, the results of both pregnancy tests were affected by the occurrence of embryonic mortality around the time of their employment.

Short communication: profiling the expression of Let-7d-5p microRNA in circulating blood of pregnant and nonpregnant cows

The objective of this work was to determine if specific circulating microRNA (miRNA) differed due to pregnancy status in heifers. Blood samples were collected from heifers 21 d after receiving an in vitro-produced embryo. Pregnancy status was diagnosed 21 d after embryo transfer, equivalent to day 28 of gestation, with rectal ultrasonography. Blood samples from 10 pregnant and 10 nonpregnant heifers were then evaluated for miRNA expression. There were five different miRNAs quantified using delta-delta Ct and qPCR methodology. These miRNAs had previously been associated with early pregnancy in cattle. The miRNA Let-7d-5p was decreased in nonpregnant as compared to pregnant females (P < 0.05). There were no changes in 16-5p, 16-1-3p, 16-2-3p, and 26a-5p associated with pregnancy (P > 0.05). Results demonstrate an opportunity to identify and study the differential expression of miRNAs from the blood of pregnant cows. The Let-7d-5p miRNA is a potential early pregnancy marker and is critical to better understand the early relationships of the cellular and molecular interactions of the cow and embryo.

Administration of GnRH at day 20 of AI and embryonic losses in synchronized crossbred buffalo

Introduction

Following the application of different artificial insemination and synchronization protocols, the synchronized buffaloes had a higher incidence of early embryonic or fetal death, thus impairing reproductive performance. Therefore, there is a need to devise a synchronizing program that can improve conception, allow early pregnancy diagnosis, reduce early embryonic losses, and provide an early clue for pregnancy diagnosis and establishment. The present study aimed (1) to determine the effect of administration of different GnRH doses at day 20 of artificial insemination (AI) on the reproductive performance of buffaloes and (2) to observe the influence of synchronization protocol, parity, age, milk production, and body condition score (BCS) on early embryonic loss and progesterone (P4) levels in crossbred buffaloes.

Methods

Crossbred buffaloes (n = 101) were synchronized using the GPGMH protocol. At day 20 of AI, the synchronized buffaloes were randomly divided into four groups and administrated GnRH doses (0, 100, 150, and 200 μg). The buffaloes were monitored for ovarian dynamics, P4 level, non-return rate, embryonic/fetal losses, and pregnancy rates. The previously synchronized buffaloes were also classified for synchronization protocol (with or without GnRH), parity (nulli- or multiparous), milk production (high or low), BCS (low, medium, or good) or age (>3 or < 3 years) groups for observing the embryonic loss and P4 level variations.

Results

The results indicated no difference (P > 0.05) in CL size, P4 level, pregnancy rate and embryo/fetal losses across the treatment groups at different observation periods. There was a high (P < 0.05) incidence of early embryonic mortality in aged, multiparous, low BCS and low milk-producing buffaloes treated without GnRH.

Conclusion

The data suggest that GnRH 200 μg at day 20 of AI improves embryo survival and pregnancy maintenance in crossbred buffaloes.

Meta-analysis of the incidence of pregnancy losses in dairy cows at different stages to 90 days of gestation

Pregnancy losses are a biological challenge and economically important in dairy herds. A meta-analysis was conducted to quantify losses in 4 periods from 19 to 90 d of pregnancy corresponding to the physiological development of gestation in dairy cows. A total of 19,723 diagnostic records from 46 studies were included. Pregnancy losses averaged 27%, 13%, 7%, and 2% in the early embryonic (19 to 32 d), late embryonic (30 to 45 d), early fetal (45 to 60 d), and later fetal (60 to 90 d) stages. These results provide a formal synthesis of the incidence of pregnancy losses in dairy cows.

Use of a cow-side oestrus detection test for fertility management in Kenyan smallholder dairy herds

Background: The use of artificial insemination (AI) has great potential to improve smallholder dairy herds in Africa, however poor success and, in some situations, high costs in Kenya, have been discouraging.  Effective AI requires accurate oestrus detection and the measurement of progesterone (P4) can be used to indicate oestrus as well as non-pregnancy.  A cow-side progesterone lateral flow test, P4 Rapid, was evaluated as an aid to detect oestrus and non-pregnancy in Kenyan dairy cows, and assessed for association with AI efficiency. 

Methods: A total of 527 cows were enrolled in the study, from two counties in central and southern Kenya.  Cattle in the test group (n = 308) were presented when suspected to be in oestrus and tested with the P4 Rapid (low P4 = oestrus, medium P4 = inconclusive, high P4 = not in oestrus/pregnant).  Cattle with low P4 were inseminated.  Cattle in the control group (n = 219) were inseminated when oestrus behaviour was detected i.e. standard practice.

Results: Of the total P4 Rapid tests performed (n = 745), 1.5% were inconclusive, with the true accuracy of the test between 87-97%.  Conception rates were not significantly higher in the test group (83.9%) compared to the control group (77.9%). Abortion rates were not significantly different between the control (9.5%) and test groups (8.2%).  In the test group, 6.2% (19/308) cows showed a medium or high P4 level on day 0 and nine of these were subsequently found to have been already pregnant.

Conclusions: The data indicated that the P4 Rapid test can be a useful tool to assist farmer decision-making in the confirmation of correct timing for AI, and importantly may avoid unnecessary inseminations in pregnant animals, thus reducing the risk of AI-induced abortion.

Use and adequacy of non-pregnancy diagnosis in cow. Which future?

In cattle, early detection of gestation is very important from an economic and management point of view in all types of farming. However, due to the poor efficiency of oestrus detection, it is essential to determine non-pregnant cows as early possible, in order to minimize the inter-insemination interval, thus de facto, reducing herd open days. Direct and indirect gestation diagnostic methods have been developed with the aim of improving the reproductive performance of the herd. Today, the most accurate method for making an early diagnosis of gestation from 28-30 days post insemination is B-Mode ultrasound. In recent years, indirect methods have included techniques that allow non-pregnant cows to be identified with a minimum margin of error, the most widely utilized of which is the Color-Doppler. This technique is rapidly becoming established for the diagnosis of non-pregnancy that allows the identification of non-pregnant animals earlier compared the pregnancy diagnosis. Some limitations of this technique in dairy cow have been presented.

Bayesian estimation of sensitivity and specificity of a milk pregnancy-associated glycoprotein ELISA test for pregnancy diagnosis between 23 and 27 days after insemination in Holstein dairy cows

Pregnancy diagnosis using pregnancy-associated glycoprotein (PAG) ELISA technology in blood or milk samples is validated from 28 d after insemination in dairy cows. The objective of this study was to estimate the sensitivity (Se) and specificity (Sp) of a commercial milk PAG-based ELISA in Holstein dairy cows between 23 and 27 d after insemination. Milk samples (n = 268) from 257 Holstein dairy cows 23 to 27 d after AI were submitted for PAG ELISA testing. Pregnancy status was confirmed by either a second milk PAG ELISA test conducted between 28 and 50 d after insemination (n = 200) or transrectal ultrasonography performed between 28 and 59 d after insemination (n = 68). A Bayesian latent class model was used to compare the paired results from the test at 23 to 27 d after AI test to the reference test. The latent class model typically used for comparing 2 or more imperfect tests was extended to include the possibility of pregnancy loss between the 23 to 27 d test and the reference test. Informative priors for the probability of pregnancy loss, and for the Se and Sp of the PAG and ultrasonography reference tests were obtained from the scientific literature. Estimated median Se and Sp of the PAG ELISA test conducted between 23 and 27 d after AI were 0.98 (95% credible interval 0.93 to 1.0) and 0.98 (0.89 to 1.0), respectively, when using a standardized corrected optical density threshold of 0.15. Although the accuracy of the test under investigation was excellent, more data will be needed to confirm the optimal diagnostic cut point for PAG in milk for early pregnancy diagnosis in this time window. The optimal timing of pregnancy diagnosis will depend on herd-specific logistics and the action to be taken to re-inseminate nonpregnant cows.

Validation of the Human Progesterone Assay Kit for Cattle as a Pregnancy Diagnosis Tool

Accurate pregnancy diagnosis is an important criterion and management tool for successful dairying. Early identification of non-pregnant dairy heifers and cows after breeding can improve pregnancy rate and life time production. Determination of progesterone hormone levels is more accurate to diagnose failed pregnancies in dairy animals. This method is not always available in developing countries. Some of the kits available are developed for humans and might be used for cattle because in principle, progesterone is not species-specific and detection methods are the same in both animals and human beings. The study aimed at validating a human progesterone ELISA kit for use in cattle as a pregnancy diagnosis tool. Forty Boran and crossbred cattle (22 pregnant and 18 non-pregnant) were selected for the study. Ten milliliter of blood sample was collected from each animal using jugular venipuncture. Serum I and plasma was harvested within 2 hours after venipuncture and serum II after 12 hours, and all samples were analyzed for progesterone concentration using the ELISA procedure provided with the kit. The result showed that 88.9% (n = 16) of non-pregnant cows had progesterone concentration below 1 ng/ml with mean (±SE) of 0.48 ± 0.75 ng/ml while all pregnant cows had mean (±SE) concentration of 19.3 ± 0.68 ng/ml with individual values ranging from 5.2–38 ng/ml. Progesterone concentration between breeds and sample type did not show statistically significant difference for pregnant and non-pregnant cows. Nonetheless, the results of the experiments are very promising as far as pregnancy diagnosis is concerned in dairy cows from an economic perspective and accuracy; the experiments have to be performed on larger scale to proof repeatability and sensitivity

Economics of Rebreeding Nonpregnant Dairy Cows Diagnosed by Transrectal Ultrasonography on Day 25 after Artificial Insemination

Pregnancy rates of Holstein cows showed a substantial decline in the past years, which caused intensive TAI programs for nonpregnant cows to shorten the period between unsuccessful insemination and the next attempt on the same cow. Although many studies examined the improvement in pregnancy rates following TAI, only a few examined the economic impact of such programs. In this study, we look at the feasibility of reproductive programs that included early pregnancy diagnosis performed by transrectal ultrasonography 25 days after artificial insemination (AI) and TAI of nonpregnant cows. This resulted in the following two TAI programs: a modified OvSynch program with a second PGF2α treatment at 24 h interval (GPPG, n = 100) and a modified OvSynch program with an intravaginal progesterone-release device inserted between days 0−7 (PRID + GPPG, n = 100). Cows included in the TAI programs recorded an improvement in the cumulative pregnancy rate (67% vs. 53%; 69% vs. 53%) compared to those in which this strategy was not applied (p < 0.05). An economic analysis was performed using a decision-support tool to estimate the net present value (NPV; USD/cow/year). The analysis revealed a difference in NPV of 89.6 USD/cow/year between the programs (rebreeding the nonpregnant cows following the TAI program vs. AI at detected estrus). In summary, rebreeding the nonpregnant cows after early negative pregnancy diagnosis (25 days after AI) using this strategy can improve the cumulative pregnancy rate and profitability of dairy farms.

Use of a cow-side oestrus detection test for fertility management in Kenyan smallholder dairy herds

Background: The use of artificial insemination (AI) has great potential to improve smallholder dairy herds in Africa, however high costs and often poor success rates have been discouraging.  Effective AI requires accurate oestrus detection and the measurement of progesterone (P4) can be used to indicate oestrus as well as non-pregnancy.  A cow-side progesterone lateral flow test, P4 Rapid, was evaluated as an aid to detect oestrus and non-pregnancy in Kenyan dairy cows, and assessed for association with AI efficiency.  Methods: A total of 527 cows were enrolled in the study, from two counties in central and southern Kenya.  Cattle in the test group (n = 308) were presented when suspected to be in oestrus and tested with the P4 Rapid (low P4 = oestrus, medium P4 = inconclusive, high P4 = not in oestrus/pregnant).  Cattle with low P4 were inseminated.  Cattle in the control group (n = 219) were inseminated when oestrus behaviour was detected i.e. standard practice. Results: Of the total P4 Rapid tests performed (n = 745), 1.5% were inconclusive, with the true accuracy of the test between 87-97%.  Conception rates were not significantly higher in the test group (83.9%) compared to the control group (77.9%). Abortion rates were not significantly different between the control (9.5%) and test groups (8.2%).  In the test group, 6.2% (19/308) cows showed a medium or high P4 level on day 0 and 9 of these were subsequently found to have been already pregnant. Conclusions: The data indicated that the P4 Rapid test can be a useful tool to assist farmer decision-making in the confirmation of correct timing for AI, and importantly may avoid unnecessary inseminations in pregnant animals, thus reducing the risk of AI-induced abortion.

Randomized controlled trial of reinsemination strategies in dairy cows diagnosed nonpregnant using color flow Doppler ultrasonography on d 21 after insemination

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We compared 4 reinsemination strategies for use after a Doppler nonpregnancy diagnosis.

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Two of these strategies provided better results than the others.

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Benefiting from an early nonpregnancy diagnosis allowed improvements in subsequent reproduction.

The objective of this study was to quantify the reproductive performance of 4 reinsemination strategies in cows diagnosed nonpregnant using corpus luteum color flow Doppler ultrasonography on d 21 after last insemination. A total of 2,140 color flow Doppler ultrasonography exams from 845 Holstein cows from 10 commercial dairy herds were used in this study. Farms were visited every 2 wk by the research team. On d 7 after insemination, cows were enrolled in a randomized controlled trial to be assigned 1 of 4 treatments if they were subsequently diagnosed nonpregnant on d 21. All cows were then examined on d 21 using Doppler ultrasonography to diagnose nonpregnancy. Treatment A (CON) was the control group: nonpregnant cows were programmed to receive a standard Ovsynch protocol starting on d 32. Nonpregnant cows in treatment B (GnRH) were injected i.m. with GnRH on d 21 after insemination and reinseminated immediately. Cows in treatment C (2×GnRH) received an i.m. injection of GnRH on d 11 after insemination. If diagnosed nonpregnant on d 21 after insemination, they were injected i.m. with GnRH on d 21 after insemination and inseminated immediately. Cows in treatment D (Resynch) received an i.m. injection of GnRH on d 14 after insemination. If diagnosed nonpregnant on d 21 after insemination, they were injected i.m. with PGF_2α on d 21 after insemination and injected i.m. with GnRH on d 24. Then, a standard Ovsynch protocol was started on d 32. Statistical analyses were performed using mixed logistic regression models accounting for cow clustering and herd effect. A theoretical simulation was performed for each treatment to quantify the proportion of cows remaining nonpregnant 42 d after initial insemination. Of the 2,140 color flow Doppler ultrasonography exams in the study, 870 (40.6%) had a Doppler score of D0 (n = 444) or D1 (n = 426), which were indicative of nonpregnancy and used for data analysis. Overall, the number of exams assigned to each treatment was as follows: CON = 223 (25.6%), GnRH = 214 (24.6%), 2×GnRH = 220 (25.3%), and Resynch = 213 (24.5%). The final mixed multivariable logistic regression model included treatment, parity, days in milk at enrollment, and herd. Conception risk at first insemination following enrollment was 31.4, 20.6, 31.9, and 48.7% for treatments CON, GnRH, 2×GnRH, and Resynch, respectively. Based on the simulation, if 100 cows were diagnosed nonpregnant at their color flow Doppler ultrasonography exam on d 21 after last insemination, the total number of cows remaining nonpregnant 42 d after the initial insemination would be 69, 72, 58, and 51 for treatments CON, GnRH, 2×GnRH, and Resynch, respectively. Thus, the treatments used in groups 2×GnRH and Resynch for cows diagnosed nonpregnant on d 21 after insemination yielded better results than those used in the other groups.

The Importance of Interferon-Tau in the Diagnosis of Pregnancy

Several decades of improving dairy cattle towards unilateral utilization of dairy cattle led to enormous progress in the field of milk yield; however, it resulted in a number of unfavorable features, such as reproductive disorders, increased calf mortality, and reduced health. Most cases of embryo loss and/or lost pregnancies occur during the first four to five weeks of gestation; accurate detection for pregnancy during this period is likely to contribute to an improvement in gestation rates. A specific protein, interferon-tau (IFNT), stimulates interferon-stimulated genes (ISGs), and their expression increases during gestation within 21 days after insemination. In bovines, the early conceptus undergoes a phase of rapid growth and elongation before implantation, the latter occurring 2–3 weeks after fertilization. IFNT acts mainly in the endometrium of the luminal epithelium. It is a new type I interferon that regulates several genes encoding uterine-derived factors. They are crucial in the processes of preparing the uterus for placenta attachment, modifying the uterine immune system, and regulating early fetal development. Because IFNT is expressed and induces ISGs in the endometrium during pregnancy recognition, it was reasoned that surrogate markers for pregnancy or IFNT might be present in the blood and provide an indicator of pregnancy status in cattle.

Peripheral leucocyte molecular indicators of inflammation and oxidative stress are altered in dairy cows with embryonic loss

Objective of experiment was to determine whether oxidative stress (OS) and inflammation altered embryonic loss in dairy cows. Blood samples were collected at days 0, 16, 32 and 60 after timed (AI) from 200 Holstein cows to determine embryonic loss based on interferon-stimulated gene-15 (ISG15) mRNA expression (day 16) and ultrasound at day 32 and day 60. Leucocyte expressions of mRNA TLR2, TLR4, TNF-α, IL1B, IL10, STAT3 (inflammation), PTGS2, PTGES (prostaglandin synthesis), and PLA2G4A and ALOX5AP (eicosanoid metabolism) at days 0 and 16 were determined. Plasma redox status for antioxidant enzymatic activities of glutathione peroxidase (GPX), superoxide dismutase (SOD), total antioxidant capacity (TAC), and concentrations of malondialdehyde (MDA) were determined at days 0, 16, 32 and 60. All antioxidant-redox responses were beneficially significant in pregnant cows diagnosed pregnant at day16 and sustained pregnancy to day 60 compared to non-pregnant cows at day16 or pregnant at day16 and lost embryos by days 32 or 60. The leucocyte mRNA expressions of TLR2, TLR4, STAT 3, IL1B, PTGS2, PLA2G4A and ALOX5AP were greater and PTGES was lower at day16 in pregnant cows that lost embryos early (P < 0.05). In conclusion peripheral leucocyte molecular indicators of inflammation and plasma indicators of OS were altered in pregnant cows undergoing embryonic losses compared to cows with a sustained pregnancy.

Recent Possibilities for the Diagnosis of Early Pregnancy and Embryonic Mortality in Dairy Cows

Simple Summary

Pregnancy diagnosis plays an essential role in decreasing days open in dairy farms; therefore, it is very important to select an accurate method for diagnosing early pregnancy. Besides traditional pregnancy diagnoses made by rectal palpation of the uterus from 40 to 60 days after AI and measuring the serum or milk progesterone concentration between 18 to 24 days after AI, there are several new possibilities to diagnose early pregnancy in dairy farms. However, it is very important to emphasize that before introducing any new diagnostic test, we need to make sure the accuracy of that particular test to be able to decrease the rate of iatrogenic pregnancy losses caused by prostaglandin or resynchronization treatments. This review focuses on the diagnostic possibilities and limitations of early pregnancy diagnosis in the field.

Abstract

One of the most recent techniques for the on-farm diagnosis of early pregnancy (EP) in cattle is B-mode ultrasonography. Under field conditions, acceptable results may be achieved with ultrasonography from Days 25 to 30 post-AI. The reliability of the test greatly depends on the frequency of the transducer used, the skill of the examiner, the criterion used for a positive pregnancy diagnosis (PD), and the position of the uterus in the pelvic inlet. Non-pregnant animals can be selected accurately by evaluating blood flow in the corpus luteum around Day 20 after AI, meaning we can substantially improve the reproductive efficiency of our herd. Pregnancy protein assays (PSPB, PAG-1, and PSP60 RIA, commercial ELISA or rapid visual ELISA tests) may provide an alternative method to ultrasonography for determining early pregnancy or late embryonic/early fetal mortality (LEM/EFM) in dairy cows. Although the early pregnancy factor is the earliest specific indicator of fertilization, at present, its detection is entirely dependent on the use of the rosette inhibition test; therefore, its use in the field needs further developments. Recently found biomarkers like interferon-tau stimulated genes or microRNAs may help us diagnose early pregnancy in dairy cows; however, these tests need further developments before their general use in the farms becomes possible.

Feasibility and accuracy of using different methods to detect pregnancy by conceptus-stimulated genes in dairy cattle

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Peripheral blood mononuclear cells (PBMC) are the best biomarker for pregnancy prediction on d 20 after timed AI.

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An abundance of ISG15 was observed in pregnant dairy females in PBMC, total blood leukocytes, and cervical cells.

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Abundance of LGALS3BP is not good biomarker for determination of pregnancy status using any cell type.

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Total milk leukocytes are not useful for detection of genes stimulated by early pregnancy.

Development of new methods for early diagnosis of pregnancy can be important to increase the reproductive efficiency and profitability of dairy herds. The bovine conceptus secretes IFN-τ that stimulates the transcription of several genes in circulating immune cells and extrauterine tissues. The aims of this study were to evaluate the mRNA abundance for pregnancy predictability of a classic gene stimulated by IFN-τ (ISG15) and a novel potential pregnancy marker (LGALS3BP) in peripheral blood mononuclear cells (PBMC), total blood leukocytes (TBL) or milk leukocytes (TML), and cervical cells (CC) on d 20 after timed artificial insemination (TAI) in dairy cattle. Eighteen Holstein females (12 cows and 6 heifers) were submitted to an estrous synchronization protocol for TAI (d 0). On d 20 post-TAI, blood samples were collected from coccygeal vessels for isolation of PBMC and in Tempus Blood RNA tubes (Applied Biosystems) for TBL. Samples of CC were collected using a cytological brush, and the TML were isolated from milk samples collected before routine milking. Pregnancy diagnosis was performed on d 30 post-TAI using transrectal ultrasonography, and females were classified as pregnant (n = 8) or nonpregnant (n = 10). Total RNA was extracted and mRNA abundance of target genes (ISG15 and LGALS3BP) was quantified by reverse-transcription quantitative PCR and normalized in relation to reference genes. Data were analyzed by ANOVA using the MIXED procedure of SAS (SAS Institute Inc.). The mRNA abundance of ISG15 was greater in pregnant than in nonpregnant animals for PBMC, TBL, and CC. No difference was detected for TML based on pregnancy status. For LGALS3BP mRNA abundance, no difference was detected between pregnant and nonpregnant animals for PBMC, TBL, and TML, but a tendency for greater abundance in pregnant animals was observed for CC. The fold change for ISG15 in each pregnant cow related to the mean of nonpregnant animals was 2.73 ± 0.31, 3.40 ± 2.17, 1.64 ± 0.29, and 0.005 ± 0.002 for PBMC, CC, TBL, and TML, respectively. The fold change for LGALS3BP in each pregnant cow related to the mean of nonpregnant animals was 0.97 ± 0.38, 1.77 ± 0.39, 0.20 ± 0.08, and 0.70 ± 0.11 for PBMC, CC, TBL, and TML, respectively. The receiver operating characteristic curve analysis indicated that ISG15 abundance predicted pregnancy in PBMC (area under curve, AUC = 0.92) and CC (AUC = 0.77) but not in TBL (AUC = 0.72) or TML (AUC = 0.52). In conclusion, mRNA abundance for ISG15 in PBMC was the best predictor for pregnancy at d 20 post-TAI, whereas TBL and TML were not good predictors of pregnancy on d 20 post-TAI. The mRNA abundance of LGALS3BP was not associated with pregnancy status in any type of cell evaluated.

Characterization of pregnancy-associated glycoproteins and progesterone as a predictor of twins and conceptus loss in high-risk-pregnancy Holstein cows

The objective of this study was to characterize plasma concentrations of pregnancy-associated glycoprotein (PAG) and progesterone (P4) as predictors of twins and pregnancy loss in Holstein cows with high-risk pregnancies. High-risk pregnancy was characterized using transrectal ultrasonography 37 d after artificial insemination (AI) based on the following criteria: small embryo size <15 mm, n = 10), slow heartbeat (<60 beats per minute, n = 11), and extra-amniotic membrane (additional amniotic membrane, n = 3). A cohort of twins (n = 41) diagnosed at d 37 post-AI was also enrolled. Each high-risk and twin pregnancy cow was paired with a cow of the same parity carrying a normal singleton at d 37 post-AI (control, n = 65). Blood samples were collected to measure PAG and P4 at d 37, 44, and 51 post-AI. Statistical analysis was performed using ANOVA, logistic regression, and receiver operator characteristic (ROC) curve with JMP software (SAS Institute Inc., Cary, NC). Pregnancy loss at d 51 post-AI was greater in high-risk pregnancies than in controls and twins (control = 1.5%; high-risk = 87.5%; twins = 12.2%). Concentration of PAG at d 37 post-AI did not differ among groups (control = 5.3 ± 0.7; high-risk = 4.8 ± 1.2; twins = 4.0 ± 0.9 ng/mL). Concentration of P4 at d 37 post-AI was greater in twins than in high-risk pregnancies and control, and lesser in high-risk pregnancies than in controls (control = 7.0 ± 0.3; high-risk = 5.9 ± 0.4; twins = 8.4 ± 0.3 ng/mL). Regression and ROC analysis for PAG at d 37 post-AI did not find a threshold to predict pregnancy loss or twins. Regression and ROC analysis for P4 at d 37 post-AI found that a threshold of 6.5 ng/mL predicted pregnancy loss with an area under the curve (AUC) of 0.64, and a threshold of 7.2 ng/mL predicted twins with AUC of 0.71. In summary, pregnancy loss and twins were predicted with only moderate accuracy by P4 concentration at d 37 post-AI, and the variability in PAG concentrations at d 37 post-AI was not sufficient to generate a threshold to predict pregnancy loss and twins in Holstein lactating cows.

Approaches to Identify Pregnancy Failure in Buffalo Cows

Simple Summary

Embryonic mortality and pregnancy failures still represent a major issue in domestic livestock production, particularly in dairy cattle. Despite the presence of extensive work in this research area, there is still no effective, accurate and practical method able to determine timing and viability of embryo specifically during early gestation. Indeed, technologies and techniques for predicting pregnancy success must continue to be developed. The aim of this work was to find the best strategy to diagnose pregnancy failures in buffalo cows in order to improve farm reproductive management. Among the methods compared in this study (ultrasonography, progesterone, PAGs), pregnancy-associated glycoproteins (PAGs) seem to be the best marker for predicting embryonic mortality between 25 and 40 days of gestation to be utilized as a diagnostic tool to improve reproductive management in buffalo farms.

Abstract

The aim of this work was to find the best strategy to diagnose pregnancy failures in buffalo. A total of 109 animals belonging to a buffalo herd subjected to a synchronization and artificial insemination (AI) program were enrolled in this study. Blood samples were collected at days 0, 14, 25, 28 and 40 after AI for the determination of progesterone (P4) and pregnancy-associated glycoproteins (PAGs) by the radioimmunoassay (RIA) method. Transrectal ultrasonography was performed on day 25, 28 and 40 after AI to monitor pregnancy. The animals included in the data analysis were assigned ex post in pregnant (n = 50) and mortality (n = 12) groups. By ultrasonography, the predictive sign of mortality was the heartbeat. At day 25, the PAGs concentration was significant in predicting embryonic mortality with respect to ultrasonography and P4, at the cut-off of 1.1 ng/mL. At day 28, either PAGs, at a cut-off of 2.2 ng/mL, or ultrasonography, with no detection of heartbeat, were highly predictive of embryonic mortality. PAGs were the best marker (p < 0.05) for predicting embryonic mortality between 25 and 40 days of gestation in buffalo. Its utilization as a diagnostic tool can influence management decisions in order to improve farm reproductive management.

Postpartum Uterine Involution and Embryonic Development Pattern in Chinese Holstein Dairy Cows

Understanding the postpartum uterine involution pattern and embryonic development could facilitate bovine reproduction management, improve reproductive efficiency, and diagnosis of the reproductive disorder, which would contribute to the success of the dairy business. This study aimed to investigate postpartum uterine involution and embryonic developmental patterns or postconceptional marks of embryonic fetal development in Chinese Holstein dairy cows using B-mode ultrasonography. The results revealed a significant decline in the involution period with an increase of parity and age. The uterine involution period was shorter in multiparous cows when compared with cows with lower parities. Consistently, cows over 4 years old recovered faster than younger cows (2 or 3 years). Besides, the elder cows (over 4 years) had a relatively larger size of resumed cervix uteri and horns. Postpartum uterine involution pattern analysis revealed that the reproductive tract recovered very fast during the first 16 days postpartum for all the parity. Results of postconceptional marks of embryo development revealed a slow increase in diameter of the gravid uterine horn and crown-rump length (CRL) before day 60. In contrast, this increase was dramatic and rapid after the 60th day. We also established two models to estimate gestational age based on gravid uterine horn diameter or CRL. A formula was established to determine the gravid uterine horn size during postconceptional on day 30th–day 90th (r = 0.8714, P < 0.01). In addition, a significant positive correlation between CRL and gestational age (r = 0.98151, P < 0.01) was built. In conclusion, these results illustrated that parity and calving age had significant effects on uterine involution in Chinese Holstein cows. Crown-rump length and gravid uterine horn diameter are both efficient for evaluating the embryo growth. These current findings broaden the understanding of basic reproductive pattern in Chinese Holstein cows and could benefit bovine reproductive management primarily in postpartum and early pregnant cows to reduce the calving interval and avoid periparturient metabolic diseases.

Efficacy of a commercial test kit to determine early pregnancy in cows using whole blood and blood serum

The objective of this study was to determine the efficacy of the Fassisi®BoviPreg visual test kit (Fassisi®BoviPreg) in determining early pregnancies in cows by measuring the pregnancy-associated glycoprotein (PAG) in whole blood and blood serum. The study was conducted on 50 cows, the artificial insemination (AI) dates of which were designated as day 0. Pregnancy diagnosis was performed with transrectal ultrasonography (USG), and serum samples were simultaneously collected and used with Fassisi®BoviPreg to determine pregnancies on 30 days after AI. The results of the Fassisi®BoviPreg test on serum and whole blood samples, respectively, on 30 days after AI were as follows: sensitivity, 61.54% and 50.0%; specificity, 79.17% and 75%; accuracy, 70.0% and 62.0%; positive predictive values, 76.2% and 68.4%; negative predictive values, 65.5% and 58.1%; false-positive diagnoses, 23.8% and 31.6%; and false-negative diagnoses, 34.5% and 41.9%. On day 50 after AI, sensitivities were 63.64% and 50.0%, specificities were 100.0% and 100.0%, and accuracies were 75.0% and 65.62% in serum and whole blood, respectively. Higher pregnancy rates were obtained using Fassisi®BoviPreg in cows with ≥ 5 ng/mL P4 (P < 0.001). In conclusion, the results from the Fassisi®BoviPreg tests on cows on 30 and 50 days after AI showed that the use of blood serum is more accurate and suitable than that of whole blood. The results also showed a higher confidence level in specificity 50 days after AI.

Diagnosing the pregnancy status of dairy cows: How useful is milk mid-infrared spectroscopy?

Pregnancy diagnosis is an essential part of successful breeding programs on dairy farms. Milk composition alters with pregnancy, and this is well documented. Fourier-transform mid-infrared (MIR) spectroscopy is a rapid and cost-effective method for providing milk spectra that reflect the detailed composition of milk samples. Therefore, the aim of this study was to assess the ability of MIR spectroscopy to predict the pregnancy status of dairy cows. The MIR spectra and insemination records were available from 8,064 Holstein cows of 19 commercial dairy farms in Australia. Three strategies were studied to classify cows as open or pregnant using partial least squares discriminant analysis models with random cow-independent 10-fold cross-validation and external validation on a cow-independent test set. The first strategy considered 6,754 MIR spectra after insemination used as independent variables in the model. The results showed little ability to detect the pregnancy status as the area under the receiver operating characteristic curve was 0.63 and 0.65 for cross-validation and testing, respectively. The second strategy, involving 1,664 records, aimed to reduce noise in the MIR spectra used as predictors by subtracting a spectrum before insemination (i.e., open spectrum) from the spectrum after insemination. The accuracy was comparable with the first approach, showing no superiority of the method. Given the limited results for these models when using combined data from all stages after insemination, the third strategy explored separate models at 7 stages after insemination comprising 348 to 1,566 records each (i.e., progressively greater gestation) with single MIR spectra after insemination as predictors. The models developed using data recorded after 150 d of pregnancy showed promising prediction accuracy with the average value of area under the receiver operating characteristic curve of 0.78 and 0.76 obtained through cross-validation and testing, respectively. If this can be confirmed on a larger data set and extended to somewhat earlier stages after insemination, the model could be used as a complementary tool to detect fetal abortion.

Early pregnancy diagnoses based on physiological indexes of dairy cattle: a review

With the development of standardization and scaling in the dairy farming industry, timely and accurate pregnancy diagnosis is required to improve the benefits of breeding by shortening the calving interval. However, the current pregnancy diagnostic methods cannot meet the requirements of the industry. Here, we review changes in the physiological indexes and in the function and morphological status of the reproductive organs of dairy cows at the early stages of pregnancy. In addition, the corresponding pregnancy diagnostic methods based on certain indexes are well development, and the pregnancy diagnostic approaches based on remote sensing and automation technology have become inevitable trends in the industry. These applications will reveal physiological regularities in pregnancy and benefit the detailed management of dairy cows during early pregnancy.

The frontiers of biomedical science and its application to animal science in addressing the major challenges facing Australasian dairy farming

Extraordinary advances are occurring in biomedical science that may revolutionise how we approach health and disease. Many have applications in the dairy industry. We have described one particular area of extracellular vesicles that have already proven to be of interest in diagnostics and prognostics for fertility and assessment of ‘transition’ cows (i.e. evaluation of the problems related to the risk of clinical diseases in dairy cows, such as mastitis and milk fever, during transition period). The addition of measurements of circulating RNA and DNA may prove of value in identifying dairy cows with higher risks of clinical diseases and potentially poor fertility. We describe the exciting opportunity provided by the possibility of generating exosomes to order as therapeutic agents to potentially enhance fertility. The even more radical concept of using exosomes to deliver a CRISPR-linked gene editing function is presented. Undoubtedly, the use of biomedical advances to assist the dairy industry is an obvious and practical approach that has significant merit.

Short communication: Accuracy of corpus luteum color flow Doppler ultrasonography to diagnose nonpregnancy in dairy cows on day 21 after insemination

The main objective of this study was to determine the accuracy of corpus luteum color flow Doppler ultrasonography (CLCFDU) to diagnose nonpregnant dairy cows 21 d after insemination. A secondary objective was to determine the accuracy of other indirect tests such as corpus luteum size and progesteronemia. Data from 1,632 Holstein cows (10 commercial herds) were used for the analysis in this prospective cohort study. The herds were visited weekly by a veterinarian and an animal health technician. During farm visits, cows were examined on d 21 after insemination using transrectal B-mode ultrasonography to quantify the presence and size of the corpus luteum. After identification of the corpus luteum, CLCFDU was performed and scored as D0, D1, D2, or D3 when 10% or less, between 11 and 30%, between 31 and 60%, or 61% or more of the corpus luteum surface was colored, respectively. A blood sample from coccygeal vessels was also collected to quantify progesteronemia. Farmers were blinded to these findings and no intervention was performed following examination. On d 32 after insemination, the cows were examined by the regular herd veterinarian using transrectal palpation and B-mode ultrasonography to determine whether the cows were pregnant or not (the reference test). Statistical analyses were conducted using 2 × 2 contingency tables. The apparent prevalence, sensitivity, specificity, positive predictive value, and negative predictive value of CLCFDU for predicting nonpregnancy were 22.0, 36.6, 99.0, 98.1, and 52.0%, respectively, when using D0 only as the diagnostic criterion; they were 47.2, 76.4, 94.8, 93.5, and 73.8%, respectively, for D0+D1 criteria. The same measures for cows with a corpus luteum <15 mm were 8.0, 11.7, 97.5, 86.9, and 43.4%, respectively, and they were 51.9, 67.4, 70.4, 76.6, and 60.0%, respectively, for progesteronemia <1 ng/mL. The measures of accuracy of CLCFDU to identify nonpregnant cows on d 21 after insemination were high, and the apparent prevalence varied depending on the diagnostic criteria used. The measures of accuracy of corpus luteum size (<15 mm) for the same purpose were high; however, apparent prevalence was low. The measures of accuracy of progesteronemia (<1 ng/mL) were low. In conclusion, CLCFDU had excellent accuracy to diagnose nonpregnancy in dairy cows on d 21 after insemination.

A shortened resynchronization treatment for dairy cows after a nonpregnancy diagnosis

We hypothesized that a shortened version of a modified Ovsynch program (OVS: GnRH-1 - 7 d - PGF_2α-1 - 24 h - PGF_2α-2 - 32 h - GnRH-2 - 16 h - AI) that excluded GnRH-1 to resynchronize ovulation in cows bearing a corpus luteum (CL) after a non-pregnancy diagnosis (NPD) or including progesterone supplementation with the OVS treatment for cows without a CL would produce shorter inter-insemination intervals and pregnancy per AI (P/AI) not different from that of cows treated with the OVS treatment. Of the 1697 lactating Holstein cows enrolled in this experiment, complete data were available for only 1584 cows because the remainder was not treated, inseminated per treatment design, left the herd before pregnancy diagnosis, or some other outcome was missing. Cows were enrolled in the study and assigned to either of three treatments at NPD (32 ± 3 d after AI [Day 0]). Cows with a detected CL were assigned randomly to: (1) a modified Ovsynch (OVS; GnRH-1 - 7 d - PGF_2α-1 - 24 h - PGF_2α-2 - 32 h - GnRH-2 - 16 h - AI) or (2) Short Synch (SS; PGF_2α-1 - 24 h - PGF_2α-2 - 32 h - GnRH-2 - 16 h - AI). Cows with no CL were assigned to OVS plus a progesterone insert (CIDR). Blood was collected at NPD to measure progesterone concentration and determine accuracy of treatment assignment (progesterone ≥ 1 ng/mL for a functional CL). Overall progesterone concentration at NPD was less in OVS + CIDR cows (1.5 ± 0.3 ng/mL) than in OVS (5.2 ± 0.2 ng/mL) or SS cows (3.7 ± 0.3 ng/mL). No differences in luteolytic risk (progesterone < 0.5 ng/mL at 72 h after PGF_2α-1) were detected after PGF_2α (>96.7%) and ovulation risk after GnRH-2 was 93.8, 91.7, and 86.2% for SS, OVS, and OVS + CIDR, respectively. Mean and median inter-insemination interval were less in SS (mean = 34.3 ± 0.05 d [median = 35 d] than OVS cows (40.2 ± 0.05 d [42 d]), but that in OVS cows did not differ from OVS + CIDR cows (41.4 ± 0.05 d [42 d]). Technicians were more accurate in visually detecting a functional CL than a non-functional CL (81.2 vs. 61.1%). Sensitivity of detecting a functional CL by technicians averaged 91.2%, but specificity was 39.8%. Pregnancy per AI at 32 ± 3 d after AI was less for SS (16.5% [n = 115]) than OVS (29.3% [n = 133] when a functional CL was inaccurately detected, but did not differ when a functional CL was detected accurately (27.6% [n = 561] vs 30.3% [508]). Pregnancy per AI did not differ between OVS and OVS + CIDR cows regardless of CL status. Short synch is an alternative to the entire modified Ovsynch program to produce similar P/AI when the CL status was detected accurately, and regardless of functional CL status, SS reduced inter-insemination intervals by 7 d.

Early pregnancy diagnosis at 21 days post artificial insemination using corpus luteum vascular perfusion compared to corpus luteum diameter and/or echogenicity in Nelore heifers

The objective was to compare the use of corpus luteum (CL) vascular perfusion to CL diameter and/or echogenicity to diagnose pregnancy at 21 d after timed-AI. Ovaries of Nelore heifers were assessed using ultrasonography in B-mode and color Doppler simultaneously 21 d after timed-AI (n = 113). Objective evaluations were performed using an image processing software to extract the number of colored pixels (ColorPix), diameter (mm) and echogenicity/mm² (EchoPix) of the CL. Subjective evaluations of the CL were performed by five evaluators using scores of estimated vascular perfusion area of color Doppler scan videos and estimated CL size and qualitative echogenicity of B-mode scan videos. The reference pregnancy diagnosis was performed 33 d after timed-AI using an ultrasonic device. Corpus luteum ColorPix, diameter and EchoPix were highly correlated (P < 0.001) with pregnancy. Pregnancy diagnosis accuracy, sensitivity, and negative predictive value were not different for CL ColorPix and diameter and was less with use of EchoPix compared to the other parameters. Size and vascular perfusion scores were correlated to the greatest extent (0.88-0.94) with the respective objective values within evaluator. The results from the ROC curve analysis indicated a smaller area under the curve for qualitative echogenicity compared to CL size and vascular perfusion. Corpus luteum vascular perfusion was the only subjective evaluation that when assessed there were no false negative pregnancy diagnoses. In conclusion, the use of the objective CL diameter resulted in the same efficacy as CL vascular perfusion evaluations for early pregnancy diagnosis in Nelore heifers.

Short communication: Blood samples before and after embryonic attachment accurately determine non-pregnant lactating dairy cows at 24 d post-artificial insemination using a commercially available assay for pregnancy-specific protein B

Early pregnancy diagnosis is critical to reproductive success on dairy farms. Reproductive success depends on cows becoming pregnant before 130 d in milk and then maintaining that pregnancy. The earlier non-pregnant cows are identified, the sooner they can be reinseminated, thus reducing days to pregnancy. Assays for pregnancy-specific protein B (PSPB) and pregnancy-associated glycoproteins can be used to diagnose pregnancy >28 d post-artificial insemination (AI) in lactating cows. The objective of this study was to determine whether percentage change in serum levels of PSPB within cow from d 17 to 24 can be used to identify non-pregnant cows using a commercially available assay. This study was performed on a large commercial dairy. Blood samples were taken at d 17 and 24 post-AI. The d 17 sample served as a baseline based on previous data. Cows with a 10% increase in serum PSPB levels from d 17 to 24 were considered pregnant. Lactating dairy cows (n = 206; 39% primiparous and 61% multiparous) were synchronized using G6G-Ovsynch. The PSPB diagnosis was compared with the herd veterinarian's diagnosis via ultrasound on d 34. The sensitivity for a 10% cutoff as a non-pregnant diagnosis was 100%, and the specificity was 93.58%. The positive predictive value was 93.27%, and the negative predictive value was 100%. Low PSPB levels at d 24 were predictive of early pregnancy loss by 60 d post-AI. To our knowledge no other method can diagnose non-pregnancy with 100% accuracy and predict pregnancy loss earlier than 24 d post-AI. Using comparative PSPB samples at d 17 and 24 post-AI provides an accurate non-pregnancy diagnosis earlier than any other pregnancy diagnosing method.

Symposium review: The choice and collection of new relevant phenotypes for fertility selection

In dairy production, high fertility contributes to herd profitability by achieving greater production and maintaining short calving intervals. Improved management practices and genetic selection have contributed to reversing negative trends in dairy cow fertility, but further progress is still required. Phenotypes included in current genetic evaluations are largely interval and binary traits calculated from insemination and calving date records. Several indicator traits such as calving, health, variation in body condition score, and longevity traits also apply to genetic improvement of fertility. Several fertility traits are included in the selection indices of many countries, but for improved selection, the development of novel phenotypes that more closely describe the physiology of reproduction and limit management bias could be more effective. Progesterone-based phenotypes can be determined from milk samples to describe the heritable interval from calving to corpus luteum activity, as well as additional measures of cow cyclicity. A fundamental component of artificial insemination practices is the observation of estrus. Novel phenotypes collected on estrous activity could be used to select for cows clearly displaying heat, as those cows are more likely to be inseminated at the right time and therefore have greater fertility performance. On-farm technologies, including in-line milk testing and activity monitors, may allow for phenotyping novel traits on large numbers of animals. Additionally, selection for improved fertility using traditional traits could benefit from refined and accurate recording and implementation of parameters such as pregnancy confirmation and reproductive management strategy, to differentiate embryonic or fetal loss, and to ensure selection for reproductive capability without producer intervention. Opportunities exist to achieve genetic improvement of reproductive efficiency in cattle using novel phenotypes, which is required for long-term sustainability of the dairy cattle population and industry.

Technical note: Validation of an automated in-line milk progesterone analysis system to diagnose pregnancy in dairy cattle

The in-line milk analysis system (IMAS) is an automated biosensor technology that samples and quantifies milk progesterone concentrations (P4c) at frequent intervals starting early postpartum until pregnancy. The objective was to validate the use of pregnancy notifications (PregN) generated by an IMAS based on P4c profiles after artificial insemination (AI) to determine pregnancy and nonpregnancy status in dairy cows. Records of 1,821 AI events from 715 Holstein cows that had milk P4c (ng/mL) measured every 2.2 ± 1.9 d (mean ± standard deviation) between 24.5 ± 8.2 and 173.4 ± 49.3 d in milk through a real-time IMAS (Herd Navigator, DeLaval International, Tumba, Sweden) were evaluated. Based on variations in adjusted milk P4c (< vs. ≥ the 5.0 ng/mL threshold), the system determined the sampling frequency, onset and cessation of luteal phases, and pregnancy. If a luteal phase initiated (P4c increased to ≥5.0 ng/mL) after AI and remained uninterrupted, a PregN was generated starting at (mean ± standard deviation) 31.0 ± 4.3 d until 53.4 ± 7.9 d after AI, when sampling stopped, unless a decline in P4c (to <5.0 ng/mL) occurred indicating nonpregnancy and imminent estrus. The assessment of IMAS PregN at 4 weekly intervals was tested, and a confirmed calving occurrence between 262 and 296 d after AI, with no other subsequent AI recorded, was the gold standard for pregnancy. In total, 14.1 (256/1,821), 41.0 (746/1,821), and 50.7% (924/1,821) of AI events were followed by a decline in P4c before 19, 23, and 30 d after AI, respectively. Frequency of the last 3 sampling events preceding P4c decline was greater if P4c decline occurred between 18 and 25 d after AI (1.4 ± 0.5 samples per day) compared with before 17 or beyond 26 d after AI (1.0 ± 0.5 samples per day). At 30 ± 3 (27 to 33) d after AI, PregN occurred in 46.8% (853/1,821) of AI events, of which 15.2% (130/853) had a decline in P4c between 30 and 55 d after AI and 17.1% (146/853) was later confirmed nonpregnant based on the gold standard. A total of 40.7% (742/1,821) of AI events was confirmed pregnant by the gold standard, which was no different than the proportion of PregN at 51 ± 3 (48 to 54) d (40.9%; 744/1,821). At any time point between 27 and 54 d after AI, sensitivity and negative predictive values for PregN were greater than 95.0 and 96.0%, respectively, whereas specificity values were less than 90.0% for PregN before 40 d but greater than 94.0% for PregN beyond 41 d after AI. In conclusion, IMAS is able to diagnose pregnancy based on P4c profiles with high precision and determine early nonpregnancy based on the spontaneous cessation of the luteal phase. However, for accuracy greater than 95.0%, pregnancy declaration based on IMAS notifications alone should occur no earlier than 41 d after AI.

A 100-Year Review: Practical female reproductive management

Basic knowledge of mechanisms controlling reproductive processes in mammals was limited in the early 20th century. Discoveries of physiologic processes and mechanisms made early in the last century laid the foundation to develop technologies and programs used today to manage and control reproduction in dairy cattle. Beyond advances made in understanding of gonadotropic support and control of ovarian and uterine functions in basic reproductive biology, advancements made in artificial insemination (AI) and genetics facilitated rapid genetic progress of economically important traits in dairy cattle. Technologies associated with management have each contributed to the evolution of reproductive management, including (1) hormones to induce estrus and ovulation to facilitate AI programs; (2) pregnancy diagnosis via ultrasonography or by measuring conceptus-derived pregnancy-associated glycoproteins; (3) estrus-detection aids first devised for monitoring only physical activity but that now also quantitate feeding, resting, and rumination times, and ear temperature; (4) sex-sorted semen; (5) computers and computerized record software packages; (6) handheld devices for tracking cow location and retrieving cow records; and (7) genomics for increasing genetic progress of reproductive and other economically important traits. Because of genetic progress in milk yield and component traits, the dairy population in the United States has been stable since the mid 1990s, with approximately 9 to 9.5 million cows. Therefore, many of these technologies and changes in management have been developed in the face of increasing herd size (4-fold since 1990), and changes from pastoral or dry-lot dairies to increased housing of cows in confinement buildings with freestalls and feed-line lockups. Management of groups of "like" cows has become equally important as management of the one. Management teams, including owner-managers, herdsmen, AI representatives, milkers, and numerous consultants dealing with health, feeding, and facilities, became essential to develop working protocols, monitor training and day-to-day chores, and evaluate current trends and revenues. Good management teams inspect and follow through with what is routinely expected of workers. As herd size will undoubtedly increase in the future, practical reproductive management must evolve to adapt to the new technologies that may find more herds being milked robotically and applying technologies not yet conceived or introduced.

Reproductive management in dairy cows - the future

Background

Drivers of change in dairy herd health management include the significant increase in herd/farm size, quota removal (within Europe) and the increase in technologies to aid in dairy cow reproductive management.

Main body

There are a number of key areas for improving fertility management these include: i) handling of substantial volumes of data, ii) genetic selection (including improved phenotypes for use in breeding programmes), iii) nutritional management (including transition cow management), iv) control of infectious disease, v) reproductive management (and automated systems to improve reproductive management), vi) ovulation / oestrous synchronisation, vii) rapid diagnostics of reproductive status, and viii) management of male fertility. This review covers the current status and future outlook of many of these key factors that contribute to dairy cow herd health and reproductive performance.

Conclusions

In addition to improvements in genetic trends for fertility, numerous other future developments are likely in the near future. These include: i) development of new and novel fertility phenotypes that may be measurable in milk; ii) specific fertility genomic markers; iii) earlier and rapid pregnancy detection; iv) increased use of activity monitors; v) improved breeding protocols; vi) automated inline sensors for relevant phenotypes that become more affordable for farmers; and vii) capturing and mining multiple sources of “Big Data” available to dairy farmers. These should facilitate improved performance, health and fertility of dairy cows in the future.

Training Method and Other Factors Affecting Student Accuracy in Bovine Pregnancy Diagnosis

To optimize bovine pregnancy diagnosis (PD) training, factors influencing student performance were investigated. The objective was to determine whether training method, gender, background (farm, urban, or mixed), previous experience in bovine PD, and current career interest influenced the accuracy of bovine PD by trans-rectal palpation (TRP). Fourth-year (of a 6-year program) veterinary students (n=138) received one PD training session in groups using either simulator training on Breed'n Betsy (BB) or training on live cows (C). Students completed a questionnaire on gender, background, and career interest. Students' PD accuracy (pregnancy status and stage) was determined after training when each student palpated six cows with known pregnancy status. Students' accuracy in determining pregnancy status was measured as sensitivity and specificity (the ability to correctly identify the presence and absence of pregnancy respectively). Factors that influenced overall accuracy with a higher student sensitivity of bovine PD by TRP were training method, farming background, an interest in a mixed animal career, and stage of gestation. Gender of students and previous experience in bovine PD did not have an influence. Training on BB simulators was associated with lower student sensitivity for pregnancy detection in cows <6 months pregnant. Student sensitivity for pregnancy detection in cows >6 months pregnant was similar for training on BB simulators and live cows. No evaluated factors were significantly associated with specificity of PD. Teaching efforts focusing on specificity of PD and repeated simulator-based training in conjunction with live cow exposure are recommended.

A Bayesian latent class model to estimate the accuracy of pregnancy diagnosis by transrectal ultrasonography and laboratory detection of pregnancy-associated glycoproteins in dairy cows

Accurate diagnosis of pregnancy is an essential component of an effective reproductive management plan for dairy cattle. Indirect methods of pregnancy detection can be performed soon after breeding and offer an advantage over traditional direct methods in not requiring an experienced veterinarian and having potential for automation. The objective of this study was to estimate the sensitivity and specificity of pregnancy-associated glycoprotein (PAG) detection ELISA and transrectal ultrasound (TRUS) in dairy cows of South Africa using a Bayesian latent class approach. Commercial dairy cattle from the five important dairy regions in South Africa were enrolled in a short-term prospective cohort study. Cattle were examined at 28-35days after artificial insemination (AI) and then followed up 14days later. At both sampling times, TRUS was performed to detect pregnancy and commercially available PAG detection ELISAs were performed on collected serum and milk. A total of 1236 cows were sampled and 1006 had complete test information for use in the Bayesian latent class model. The estimated sensitivity (95% probability interval) and specificity for PAG detection serum ELISA were 99.4% (98.5, 99.9) and 97.4% (94.7, 99.2), respectively. The estimated sensitivity and specificity for PAG detection milk ELISA were 99.2% (98.2, 99.8) and 93.4% (89.7, 96.1), respectively. Sensitivity of veterinarian performed TRUS at 28-35days post-AI varied between 77.8% and 90.5% and specificity varied between 94.7% and 99.8%. In summary, indirect detection of pregnancy using PAG ELISA is an accurate method for use in dairy cattle. The method is descriptively more sensitive than veterinarian-performed TRUS and therefore could be an economically viable addition to a reproductive management plan.

Accuracy of fetal age estimates using transrectal ultrasonography for predicting calving dates in dairy cows in seasonally calving herds in New Zealand

AIM

To describe the accuracy of transrectal ultrasonography for predicting calving dates in dairy cows under typical New Zealand conditions and to assess potential risk factors for differences between predicted and actual calving dates.

METHODS

Data were collected from 116 seasonally calving herds over 2 years in a retrospective single cohort study. Transrectal ultrasonography was undertaken by experienced veterinarians (n=12) to determine if cows were pregnant, and if so to estimate fetal age. Predicted calving date was calculated by adding 282 days to the estimated conception date. Accuracy was assessed using differences between predicted and actual calving dates for each animal. Potential risk factors for animals calving >10 days before or after their predicted calving date were assessed using multinomial logistic regression models.

RESULTS

The study population comprised 83,104 cows over the 2 years of the study; 75,037 (90.3%) cows calved within 10 days of their predicted calving date, 3,683 (4.4%) calved >10 days earlier, and 4,384 (5.3%) >10 days later, than predicted. Risk factors for calving >10 days before or after the predicted calving date included having >1 artificial insemination (AI) before pregnancy diagnosis (p=0.03), where the cow's most recent AI was <21 days before the end of the herd's AI period (p<0.01), and where the diagnosis was made at the second or third herd-visit (p<0.01). The probability of calving being >10 days later than predicted also increased when the fetus was ≥13 weeks old at pregnancy diagnosis (p<0.01).

CONCLUSIONS AND CLINICAL RELEVANCE

In this study, >90% of cows diagnosed pregnant by veterinarians using transrectal ultrasonography calved within 10 days of the predicted calving date. In herds where herd reproductive performance is high, it would be expected that more cows would conceive to their first AI, and potentially fewer cows would have AI close to the end of the herd's AI period, which would increase diagnostic accuracy. Where herd managers rely on accurate predicted calving dates they should be informed about realistic expected accuracy. For greatest accuracy, a complete AI history should be made available to the person performing the pregnancy diagnoses and cows at most risk of having inaccurate predicted calving dates should be identified.