Pregnancy Loss In Dairy Cows Research Articles

Recent advances in early pregnancy loss diagnosis in dairy cows: New approaches.

Early pregnancy loss is a primary cause of low reproductive rates in dairy cows, posing severe economic losses to dairy farming. The accurate diagnosis of dairy cows with early pregnancy loss allows for oestrus synchronization, shortening day open, and increasing the overall conception rate of the herd. Several techniques are available for detecting early pregnancy loss in dairy cows, including rectal ultrasound, circulating blood progesterone, and pregnancy-associated glycoproteins (PAGs). Yet, there is a need to improve on existing techniques and develop novel strategies to identify cows with early pregnancy loss accurately. This manuscript reviews the applications of rectal ultrasound, circulating blood progesterone concentration, and PAGs in the diagnosis of pregnancy loss in dairy cows. The manuscript also discusses the recent progress of new technologies, including colour Doppler ultrasound (CDUS), interferon tau-induced genes (ISGs), and exosomal miRNA in diagnosing pregnancy loss in dairy cows. This study will provide an option for producers to re-breed cows with pregnancy loss, thereby reducing the calving interval and economic costs. Meanwhile, this manuscript might also act as a reference for exploring more economical and precise diagnostic technologies for early pregnancy loss in dairy cows.

Profiles of interferon-stimulated genes in multiple tissues and circulating pregnancy-associated glycoproteins and their association with pregnancy loss in dairy cows†.

Pregnancy loss (PL) in lactating dairy cows disrupts reproductive and productive efficiency. We evaluated the expression of interferon-stimulated genes (ISG) in blood leukocytes, vaginal and cervical epithelial cells, luteolysis-related genes, progesterone, and pregnancy-associated glycoprotein (PAG) profiles in lactating dairy cows (n = 86) to gain insight about PL. Expression of ISG on d17, d19, and d21 was greater in cows that maintained the pregnancy (P33) compared to nonpregnant with no PL (NP). Greater ISG differences between groups were observed in the cervix (96.7-fold) than vagina (31.0-fold), and least in blood leukocytes (5.6-fold). Based on individual profiles of ISG and PAG, PL was determined to occur either before (~13%) or after (~25%) d22. For cows with PL before d22, ISG expression was similar on d17 but by d21 was lower and OXTR was greater than P33 cows and similar to NP; timing of luteolysis was similar compared to NP cows suggesting embryonic failure to promote luteal maintenance and to attach to the endometrium (no increase in PAG). For cows with PL after d22, ISG expression was similar to P33 cows on d17, d19, and d21 and luteolysis, when it occurred, was later than NP cows; delayed increase in PAG suggested later or inadequate embryonic attachment. In conclusion, PL before d22 occurred due to embryonic demise/failure to signal for luteal maintenance, as reflected in reduced ISG expression by d21. Alternatively, embryos with PL between d22 and 33 adequately signaled for luteal maintenance (ISG) but had delayed/inadequate embryonic attachment and/or inappropriate luteolysis causing PL.

Associations of inflammatory and reproductive tract disorders postpartum with pregnancy and early pregnancy loss in dairy cows

Our objective was to describe associations of postpartum health with pregnancy and pregnancy loss (P-LOSS) from d 19 to 40 after first postpartum artificial insemination (AI) in lactating Holstein cows. In 2 commercial dairy herds in Ontario, Canada, 468 Holstein cows were enrolled 21 ± 3 d before expected parturition when body condition score (BCS) and lameness were assessed. Serum total Ca, haptoglobin (Hp), and nonesterified fatty acids (NEFA) were measured at 2 and 6 ± 2 d in milk (DIM). Blood β-hydroxybutyrate (BHB) measurement and metritis detection were done at 4, 8, 11, and 15 ± 2 DIM. Cows were examined for endometritis (ENDO; ≥11.5% polymorphonuclear cells in endometrial cytology) and purulent vaginal discharge (PVD) at 35 ± 3 DIM. Lameness was assessed again at 21 and 49 ± 3 DIM and BCS at 63 ± 3 DIM. First postpartum AI occurred primarily (86%) based on detection of estrus by activity monitors, on average (± standard deviation) at 65 ± 9 DIM, and the remaining cows received timed AI at 86 ± 18 DIM. Serum progesterone (P4) was measured on d 8 and 12 after AI, and pregnancy at first AI (P/AI) was estimated by the expression of ISG15 in peripheral blood leukocytes at d 19 after AI and by pregnancy-associated glycoprotein in serum at d 29, 33, and 40 after AI. Each metabolite (Ca, Hp, NEFA, and BHB) was categorized above or below a cut-point identified with receiver operating characteristic curve analysis associated with P/AI confirmed by ultrasound at d 33 from a larger data set. Data were analyzed using multivariable mixed logistic regression models, accounting for parity, health variables, covariates (season at calving and at AI, milk yield at first Dairy Herd Improvement Association test [categorized into terciles], AI method, and DIM), and herd. The proportions of cows classified pregnant at d 19, 29, 33, and 40 after AI were 64%, 54%, 50%, and 45%, respectively. At d 19 after AI, P/AI was less likely in cows diagnosed with ENDO (52% vs. 69%) or PVD (54% vs. 67%). At d 29, P/AI was less likely in cows with Hp ≥1.54 g/L at 2 DIM (38% vs. 55%) or PVD (35% vs. 56%). Both metritis and ENDO were associated with decreased P/AI at d 40 after AI. Cows diagnosed with metritis had greater risk of P-LOSS from d 19 to 29 (43% vs. 22%) or from d 33 to 40 (37% vs. 7%) than cows without metritis. From d 29 to 33, the risk of P-LOSS was greater in cows with NEFA ≥0.73 mM at 2 DIM (13% vs. 5%) or BCS ≤2.75 at 63 DIM (14% vs. 5%). The concentration of P4 on d 8 after AI was positively associated with P/AI at d 29, 33, and 40, and negatively associated with P-LOSS from d 19 to 29. Postpartum health disorders, particularly reproductive tract disease, can have detrimental effects on early pregnancy establishment and on pregnancy maintenance from d 19 to 40 after AI.

Metabolomic evolution of the postpartum dairy cow uterus.

High rates of early pregnancy loss are a critical issue in dairy herds, particularly in seasonal, grazing systems. Components of the uterine luminal fluid (ULF), on which the early embryo depends for sustenance and growth, partly determine early pregnancy losses. Here, changes in ULF from early to mid-postpartum in crossbred dairy cows were explored, linking them with divergent embryo development. For this, the uteri of 87 cows at Day 7 of pregnancy at first and third estrus postpartum were flushed to collect ULF. Eighteen metabolites (chiefly organic acids and sugars) significantly varied in abundance across postpartum, indicating a molecular signature of physiological recovery consistent of the upregulation of pyrimidine metabolism and glycerophospholipid metabolism, and downregulation of pentose phosphate and taurine metabolism pathways. Joint pathway analysis of metabolomics data and a previously generated proteomics data set on the same ULF samples suggests key links between postpartum recovery and subsequent successful embryo development. These include upregulation of VEGFA and downregulation of metabolism, NRF2, T-cell receptor, which appear to improve the ULF's capacity of sustaining normal embryo development, and a putative osmo-protectant role of beta-alanine. These relationships should be further investigated to develop tools to detect and reduce early pregnancy loss in dairy cows.

Genetic parameters of pregnancy loss in dairy cows estimated from pregnancy-associated glycoproteins in milk

This study examined the feasibility of using pregnancy-associated glycoproteins (PAG) in milk within breeding for pregnancy maintenance and assessed the genetic variation in pregnancy loss traits. A total of 374,206 PAG samples from 41,889 Swedish Red (SR) and 82,187 Swedish Holstein (SH) cows were collected at monthly test-day milkings in 1,119 Swedish herds. Pregnancy status was defined based on PAG levels and confirmed by data on artificial insemination (AI), calving, and culling from d 1 postinsemination to calving. Pregnancy loss traits were defined as embryonic loss (diagnosed 28 d to 41 d after AI), fetal loss (42 d after AI until calving), and total pregnancy loss. Least squares means (± standard error, %) and genetic parameters were estimated using mixed linear models. Heritability was estimated to be 0.02, 0.02, and 0.03 for embryonic loss, fetal loss, and total pregnancy loss, respectively. Cows with pregnancy loss had lower PAG concentrations than cows which successfully maintained pregnancy and calved. PAG recording was limited to monthly test-day milking, resulting in low estimated embryonic loss (17.5 ± 0.4 and 18.7 ± 0.4 in SR and SH, respectively) and higher fetal loss (32.8 ± 0.5 and 35.1 ± 0.5 in SR and SH, respectively). Pregnancy loss might have occurred earlier but remained undetected until the next test-day milking, when it was recorded as fetal loss rather than embryonic loss. Estimated genetic correlation between embryonic and fetal pregnancy loss traits and classical fertility traits were in general high. Identification of novel genetic traits from PAG data can be highly specific, as PAG are only secreted by the placenta. Thus, PAG could be useful indicators in selection to genetically improve pregnancy maintenance and reduce reproductive losses in milk production. Further studies are needed to clarify how these results could be applied in breeding programs concurrent with selection for classical fertility traits.

Transformer neural network to predict and interpret pregnancy loss from activity data in Holstein dairy cows

Predicting/detecting pregnancy loss of dairy cows offers the opportunity to shorten the time interval between artificial inseminations. Although several methods of pregnancy detection are being practiced, models with accurate, timely and interpretable detection of pregnancy are still lacking. This study proposed a transformer neural network to predict the probability of pregnancy loss based on continuous activity data, which were collected from activity-monitoring tags attached to 185 Holstein cows from a commercial dairy farm in Cayuga County, NY, USA. Our best model achieved an average accuracy of 0.87, F1 score of 0.87, recall of 0.87 and specificity of 0.90 using 14-day time-series activity windows (90% overlap) using 5-fold cross-validation, outperforming commonly used classic statistical learning and deep learning models for time-series data. The results indicated that our predictive model gave high probabilities of correctly detecting pregnancy loss prior to the increased activities and veterinary confirmation by transrectal ultrasound. In addition, our model interpretation aligned with the changes in the temporal activity levels, revealing that drastic fluctuations in time-series activity data contributed heavily to the final prediction. To the best of our knowledge, this is the first work on developing transformer models for the prediction of pregnancy loss in dairy cows. In addition to facilitating the development of future precision management on modern farms, our work potentiates an increase in the reproductive efficiency and profitability of dairy farms.

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.

Short communication: Effect of subclinical mastitis on reproductive performance of Holstein dairy cows in the Northwest of Spain

Aim of study: To investigate the effect of subclinical mastitis (SCM) before and after first artificial insemination (AI), characterized by a somatic cell count (SCC) higher than 200×103 cell/mL, on reproductive performance including first service conception rate (FSCR) and pregnancy loss (PL) in Holstein dairy cows. Area of study: The central area of Lugo, Galicia, Spain. Material and methods: This retrospective study was conducted on herd database of a population of 80 commercial Holstein dairy cow farms. A total number of 2053 lactations were included in this study. A binary logistic regression was carried out to analyse all data. Main results: The results of this study indicated that cows that registered a SCC lower than 200×103 cell/mL within 30 days after first AI were more likely to conceive pregnancy than cows with a higher SCC (31.2% and 25.1% FSCR, respectively; OR=1.285, 95% CI=1.000-1.653). Additionally, an increased SCC neither 30 days before nor 30 days after first AI had a negative effect on prevalence of PL in dairy cows. Research highlights: These findings revealed that SCM within 30 days after first AI negatively affected FSCR, whilst 30 days before first AI did not affect it. Therefore, it could be suggested that preventing subclinical mastitis after first AI, during a critical period of 30 days, is important to maximize the reproductive performance of dairy cows.

Effect of Timed Artificial Insemination Protocols on the Pregnancy Rate Per Insemination and Pregnancy Loss in Dairy Cows and Korean Native Cattle under Heat Stress

Effect of Timed Artificial Insemination Protocols on the Pregnancy Rate Per Insemination and Pregnancy Loss in Dairy Cows and Korean Native Cattle under Heat Stress

Serological screening for Coxiella burnetii in the context of early pregnancy loss in dairy cows.

Q fever is one of the commonest infectious diseases worldwide. A Coxiella burnetii prevalence of 97.6% has been found by ELISA and PCR tests of the bulk tank milk in dairy cattle farms of Hungary. The herd- and individual-level seroprevalence rates of C. burnetii in the examined dairy cows and farms have dramatically increased over the past ten years. Three high-producing industrial dairy farms were studied which had previously been found ELISA and PCR positive for C. burnetii by bulk tank milk testing. Coxiella burnetii was detected in 52% of the 321 cows tested by ELISA. Pregnancy loss was detected in 18% of the cows between days 29-35 and days 60-70 of gestation. The study found a higher seropositivity rate (80.5%) in the cows that had lost their pregnancy and a seropositivity of 94.4% in the first-bred cows that had lost their pregnancy at an early stage. The ELISA-positive pregnant and aborted cows were further investigated by the complement fixation test (CFT). In dairy herds an average of 66.6% individual seropositivity was detected by the CFT (Phase II) in previously ELISA-positive animals that had lost their pregnancy and 64.5% in the pregnant animals. A higher (Phase I) seropositivity rate (50.0%) was found in the cows with pregnancy loss than in the pregnant animals (38.5%). The high prevalence of C. burnetii in dairy farms is a major risk factor related to pregnancy loss.

202 Factors influencing pregnancy loss in lactating dairy cows

Abstract Pregnancy loss in high producing dairy cows is significant and negatively affects profitability of dairy farms. It is not clear the extent of pregnancy loss prior to a subsequent estrus or first pregnancy diagnosis. It is clear that percent of cows losing pregnancies are greatest following 1st pregnancy diagnoses then decrease in a time-related fashion throughout gestation. Non-disease related factors that are associated with pregnancy losses in dairy cows include parity, timing of AI relative to ovulation, circulating concentrations of progesterone during growth of the ovulatory follicle(s), double ovulations, unilateral twins, service sire, extent of change in body condition during early lactation, and serum levels of pregnancy associated glycoproteins at 24 or 28 d post-AI. Metabolic changes related to high milk production resulted in a greater chance for double ovulations. A growing body of literature indicates that cows with unilateral double ovulations and unilateral twins have a greater chance for pregnancy loss during the 1st 90 d of pregnancy compared to cows with single ovulations or bilateral twins. It also appears there is a preferential timing of loss in cows with double vs. single ovulations. Levels of circulating concentrations of progesterone during follicular wave development affect follicular development of cows. In a study that controlled progesterone during follicular development, low levels of progesterone caused a greater percentage of cows to have double ovulations and increased chances for pregnancy loss after 35 d post-AI. Lastly, it appears that cows that lose body condition during the 1st 30 DIM have a greater chance of pregnancy loss between 35 and 69 d post-AI compared with cows that maintained or gained body condition during that period. These data lead towards a greater understanding of the potential causes of pregnancy loss in dairy cows and can be instrumental in the development of reproductive technologies to reduce these losses.

Physiological profile of undifferentiated bovine blastocyst-derived trophoblasts.

ABSTRACTTrophectoderm of blastocysts mediate early events in fetal-maternal communication, enabling implantation and establishment of a functional placenta. Inadequate or impaired developmental events linked to trophoblasts directly impact early embryo survival and successful implantation during a crucial period that corresponds with high incidence of pregnancy losses in dairy cows. As yet, the molecular basis of bovine trophectoderm development and signaling towards initiation of implantation remains poorly understood. In this study, we developed methods for culturing undifferentiated bovine blastocyst-derived trophoblasts and used both transcriptomics and proteomics in early colonies to categorize and elucidate their functional characteristics. A total of 9270 transcripts and 1418 proteins were identified and analyzed based on absolute abundance. We profiled an extensive list of growth factors, cytokines and other relevant factors that can effectively influence paracrine communication in the uterine microenvironment. Functional categorization and analysis revealed novel information on structural organization, extracellular matrix composition, cell junction and adhesion components, transcription networks, and metabolic preferences. Our data showcase the fundamental physiology of bovine trophectoderm and indicate hallmarks of the self-renewing undifferentiated state akin to trophoblast stem cells described in other species. Functional features uncovered are essential for understanding early events in bovine pregnancy towards initiation of implantation.

Evidence that mastitis can cause pregnancy loss in dairy cows: A systematic review of observational studies

The objective of this study was to conduct a systematic review to identify and assess evidence and knowledge gaps in published observational studies that have investigated the relationship between mastitis and pregnancy loss (PL) in dairy cows. PubMed and ScienceDirect were used to search pertinent peer-reviewed research reports of interest. Screening of research reports was conducted at 3 levels: titles, abstracts, and full-text articles. The search identified 651 records for initial screening. The final screening process identified 8 qualified articles for review after removing 10 duplicate records, 582 titles, 31 abstracts, and 20 full-text articles. Two studies produced strong epidemiologic evidence indicating that (1) exposure to clinical mastitis during early gestation (first 45 d of gestation) is associated with subsequent PL during the following 90 d; and (2) subclinical mastitis 1 to 30 d before artificial insemination (AI) is associated with subsequent PL at 35 to 41 d of gestation. An additional study showed that exposure to clinical mastitis during early lactation in combination with low body condition can increase the risk of PL in dairy cows; however, the interaction effect between clinical mastitis and low body condition on PL was considered weak. Four other studies produced inconclusive evidence indicating that mastitis is a predisposing factor for PL in dairy cows, as the exposure risk period for mastitis overlapped with the follow-up period for diagnosis of PL in dairy cows. Finally, one study failed to identify a relationship between mastitis and PL in dairy cows. Further research is needed to (1) support the hypothesis that mastitis in combination with low body condition score (or other exposure factors) can increase the risk of PL, (2) compare the effect of clinical versus subclinical mastitis on PL, (3) compare the effect of mastitis before breeding and during gestation on PL, and (4) compare the effect of mastitis on PL in dairy cows during different lactations.

72 EFFECT OF PROGESTERONE SUPPLEMENTATION ON DAY 4 AFTER TIMED ARTIFICIAL INSEMINATION ON PREGNANCY RATE OF LACTATING DAIRY COWS

Progesterone plays an important role in the maintenance of pregnancy. It is hypothesised that insufficient progesterone early in pregnancy may result in embryonic loss, and that supplemental progesterone would decrease pregnancy loss in dairy cows. The aim of this study was to compare the effect of progesterone supplementation after timed AI on pregnancy rate of dairy cows. The experiment was conducted in a single commercial herd, in Sao Paulo State (Brazil), during a period of 1 year (January–December 2016). The cows were assigned at a nonpregnancy diagnosis 32 ± 3 days after AI to 1 to 6 resynchronization treatments. They were submitted to the same fixed time AI protocol: Day 0, 0.1 mg of gonadorelin, 2 mg of oestradiol benzoate, and an intravaginal device of 1.9 g of progesterone; Day 7, 25 mg of dinoprost tromethamine; Day 8, 25 mg of dinoprost tromethamine, 1 mg of oestradiol cipionate, and device withdrawal; Day 10, AI. At Day 14, the cows were alternately arranged in 2 groups. Group 1 received a 900-mg progesterone supplementation IM injection, and Group 2 did not receive progesterone supplementation. Then, 32 ± 3 days after insemination, pregnancy diagnosis was performed by transrectal ultrasonography, and the data were tabulated. Full statistical analysis will be done at the end of the study, when more than 500 cows will be allocated to the 2 groups. From January until April 2016, 230 lactating dairy cows were submitted to the experiment. Both groups had similar average days in lactation (166), average number of lactations (1.95), and average number of inseminations (4.3). Group 1 had a pregnancy rate of 25% (29/116), and group 2 had a pregnancy rate of 15.8% (18/114) (P = 0.01, one-way ANOVA). Based on these preliminary data, pregnancy rates of lactating dairy cows may be improved with progesterone supplementation on Day 4 after insemination. These results need to be confirmed on larger numbers of cows.

Observed and expected combined effects of clinical mastitis and low body condition on pregnancy loss in dairy cows

The objective was to compare the observed and expected combined effects of clinical mastitis before timed artificial insemination (TAI) and low body condition at 70 d postpartum (dpp) on pregnancy loss in dairy cows. Cows were examined for pregnancy by ultrasonographic examination 28–32 d after TAI; the presence of an embryo with a heartbeat was the criterion used to determine pregnancy. Cows diagnosed pregnant were re-examined by transrectal palpation of the uterus and its contents 28 d later to confirm pregnancy status and to identify pregnancy loss. Eighty-eight (17%) of 512 cows were diagnosed with pregnancy loss. Cows affected with clinical mastitis before insemination and a body condition score (BCS) ≤ 2.75 at 70 dpp were 2.03 times more likely to experience pregnancy loss, compared to cows without clinical mastitis and with a BCS > 2.75 (RR = 2.03; 95% CI = 1.15, 3.60; P = 0.01). This observed combined effect for pregnancy loss (RR = 2.03) was higher than the expected combined effect based on adding (RR = 1.39) or multiplying (RR = 1.42) absolute independent excesses due to clinical mastitis or low body condition.

Pregnancy loss in dairy cows: the contributing factors, the effects on reproductive performance and the economic impact

This study investigated the effects of the herd, cow parity, the insemination protocol and season on the incidence of pregnancy loss (PL) in dairy herds. Furthermore, we determined the downstream effects of PL on reproductive performance and its economic impact. The overall incidence rate of PL was 6.9% in 1,001 pregnant cows and its incidence peaked (p < 0.01) during the second trimester of gestation. GLIMMIX analysis revealed that cow parity was the important risk factor for the PL. The odds ratio showed that the likelihood of PL in cows with parities of 1 or 2 was decreased by 0.6 or 0.5 fold compared to the cows with a parity of 3 or higher. Following PL, the mean rate of endometritis was 23.2% and endometritis was more common (p < 0.05) when PL occurred during the third trimester than during the first and second trimesters. The mean culling rate was 46.4% and this did not differ with the period of PL. The overall mean intervals from PL to the first service and conception were 63.4 and 101.8 days, respectively. The mean interval from PL to first service was longer (p < 0.01) for cows with PL during the third trimester than for the cows with PL during the first and second trimesters. The economic loss resulting from each PL was estimated at approximately $2,333, and this was largely due to an extended calving interval and increased culling. These results suggest that cow parity affects the incidence of PL, which extends calving interval and causes severe economic loss of dairy herds.

The usefulness of the computerized medical records of one practice for research into pregnancy loss in dairy cows

The use of routinely collected data for epidemiological research has been advocated to reduce the cost of field research. The disadvantage of such an approach is the lack of control over the collection and quality of the data. This study was undertaken to describe the quality of practice-generated computerized medical records and to assess their usefulness as a source of data for research. In particular, this study evaluated the quality of the medical records generated by one software program for research into pregnancy loss in dairy cows. The records of approximately 4000 cows in 70 herds in one private dairy practice were analyzed. Various methods were used to assess data quality. The task of preparing the medical records for analysis was complex. However, the programs written for this study could be adapted for use elsewhere allowing the generation of similar data-sets from other practices. The quality of the data available from these medical records was acceptable. More information is needed to set standards for quality in data-sets such as this. The observed tendency of cows with complete data to have worse reproductive performance has divergent implications for practising veterinarians. More work is needed to refine this association.

Assessment of the Quality of Practice-Generated Computerized Medical Records as a Data Source For Research Into Pregnancy Loss in Dairy Cows

This paper discusses the suitability of medical records as a source of data for research into the problem of pregnancy loss in dairy cows. The process of converting the computerized veterinary practice records into analyzable data is described. Various measures of data quality are discussed including the percent of missing, incorrect and outlier values in the final data set. Finally, descriptive statistics are calculated to demonstrate the similarity between the population of dairy cows described by the medical records and the target population of commercial dairy cows. This paper demonstrates that the positive aspects of practice-generated computerized medical records (volume of data, similarity to the target population) compensate for the disadvantages of poor case definition and missing data. The analysis of these data to investigate pregnancy loss in dairy cattle is currently under way and will be reported elsewhere.