Effect of follicular wave synchronization using a progesterone-releasing intravaginal device-based protocol on in vitro embryo production in Bos taurus cows subjected to 14-day intervals ovum pick-up.

Follicular wave synchronization (FWS) before ovum pick-up (OPU) is one of the strategies used to improve the efficiency of in vitro embryo production (IVP). This study aimed to evaluate the effect of FWS on the total follicular number, cumulus-oocyte complex (COC) recovery, and in vitro embryo development in Angus cows (n = 33) subjected to OPU with 14-day intersession intervals. Additionally, it was also evaluated the presence of carryover effects given the short intersession interval used. The experiment was run as a 2-treatment (FWS vs. Control) x 2-period (1 vs. 2) crossover design. Animals in the FWS group received an intravaginal progesterone implant (1gr), estradiol benzoate (2 mg), and D-cloprostenol (150 µg) on day 0 and the OPU was performed on day 5. Control group animals did not receive any hormone treatment. The FWS increased the number of 6-10 mm follicles (P = 0.05), but it decreased the COC recovery rate (P < 0.01). The FWS did not affect the total or frozen embryo numbers (P = 0.49 and P = 0.17; respectively), but it increased the total blastocyst cell number (P < 0.01). A carryover effect was found on the total and < 6 mm follicles number (P = 0.10 and P < 0.01; respectively), and on the regular, atretic, viable, and total number of COC (P = 0.01, P = 0.08, P = 0.02 and P < 0.01; respectively). We concluded that the FWS increased the quality of embryos after OPU with 14-day intersession intervals in Angus cows and that this kind of OPU/IVP scheme enabled the existence of a carryover effect, especially on the follicle number and COC morphology.

Association of bovine viral diarrhea virus, bovine herpesvirus 1, and Neospora caninum with late embryonic losses in highly supplemented grazing dairy cows.

The objectives of this study were: 1- to evaluate the association of Bovine Viral Diarrhea Virus (BVDV), Bovine Herpes Virus 1 (BoHV-1), and Neospora caninum (N. caninum) with the risk for Late Embryonic Loss (LEL) in grazing dairy cows, 2- to evaluate blood progesterone concentration at the time of LEL occurrence, and 3- to describe a novel ultrasound-guided technique for conceptus sampling. We run a prospective cohort study involving 92 cows (46 LEL and 46 NLEL). An LEL cow was that having an embryo with no heartbeat, detached membranes, or floating structures, including embryo remnants detected at pregnancy check by ultrasonography (US) 28-42 days post-AI, whereas an NLEL cow was that with embryo heartbeats detectable by US at pregnancy check 28-42 d post-IA. We took two blood samples from every cow at pregnancy check by US (the day of LEL detection) and 28 d later to perform serological diagnosis of BVDV, BoHV-1, and N. caninum; and to measure blood progesterone concentration at pregnancy check (28-42 d post-AI). We also sampled the conceptus from all the LEL cows. We performed PCR to detect BVDV, BoHV-1, and N. caninum in sampled conceptuses from LEL cows. Finally, we evaluated the associations of risk factors (serological titers, seroconversion, and progesterone) with LEL odds with logistic models. The risk for LEL was associated with serological titers to BVDV (P = 0.03) and tended to be associated with seroconversion to BVDV, given that 19.6% (9/46) in LEL and 6.5% (3/46) in NLEL cows seroconverted to BVDV (P = 0.09). In addition, BVDV was detected in conceptuses from LEL cows that seroconverted to BVDV but not in LEL cows that did not seroconvert. Conversely, the risk for LEL was not associated with the titers or seroconversion to BoHV-1 and N. caninum. BoHV-1 and N. caninum were not identified in any of the conceptuses. Finally, blood progesterone concentration was similar in LEL and NLEL cows, and it was not associated with the risk for LEL (P = 0.54). In conclusion, BVDV infection is a risk factor for LEL in dairy cows.

Late embryonic losses in supplemented grazing lactating dairy cows: Risk factors and reproductive performance.

The main objective of this study was to evaluate the risk factors for late embryonic loss (LEL) in supplemented grazing dairy cows. Additional objectives were to assess the incidence of LEL and its association with the reproductive performance of cows. A data set containing productive, reproductive, and health records of 13,551 lactations was used. A retrospective case-control study involving 631 cows with LEL (cases) and 2,524 controls (4 controls per case within each study year) was run. A case of LEL was defined when the embryo had no heartbeat or there was evidence of detached membranes or floating structures including embryo remnants by ultrasonography (US) at 28 to 42 d post-artificial insemination (AI), whereas a non-case was defined as a cow diagnosed with positive pregnancy by US 28 to 42 d post-AI and reconfirmed as pregnant 90 ± 7 d post-AI. Four controls per case were randomly selected from the non-cases with a temporal matching criterion (±3 d around the date of the fecundating AI of the case). Multivariable logistic models were offered with the following predictors: year of LEL (2011 through 2015), season of LEL (summer vs. fall vs. winter vs. spring), parity (1 vs. 2 vs. ≥3), uterine disease (UD), non-uterine disease (NUD), body condition score at parturition, body condition score at 28 to 42 d post-AI (BCS-LEL), days in milk (DIM), and daily milk yield (MY). Statistical significance was set at P < 0.05 and a tendency was set at P ≤ 0.10. We found that 4.7, 22, and 23% of cows had LEL, UD, and NUD, respectively. Cases tended to have higher daily MY than controls (32.5 vs. 31.8 kg); also, cases had much longer calving to pregnancy interval (226 vs. 118 d), lower hazard of pregnancy [hazard ratio = 0.39, 95% confidence interval (CI) = 0.35-0.43], and higher odds for non-pregnancy [odds ratio (OR) = 2.89, 95% CI = 2.37-3.54] than controls. We found that the odds for LEL increased with parity number (OR = 2.48, 95% CI = 1.99-3.08 for parity ≥3) and with BCS-LEL <2.50 (OR = 1.81, 95% CI = 1.33-2.47). Conversely, the odds for LEL decreased with BCS-LEL >3.00 (OR = 0.70, 95% CI = 0.53-0.91). The odds for LEL increased with UD (OR = 1.23, 95% CI = 1.01-1.49), NUD (OR = 1.24, 95% CI = 1.01-1.54), DIM (OR = 1.03, 95% CI = 1.00-1.05), and daily MY (OR = 1.14, 95% CI = 1.04-1.25) in univariable models only. Finally, the odds for LEL were not associated with year, season, DIM, and body condition score at parturition. In conclusion, LEL is associated with extended calving to pregnancy interval, and among its risk factors are parity number and BCS-LEL.

Associations of subclinical hypocalcemia with fertility in a herd of grazing dairy cows.

The main objective was to assess the associations of subclinical hypocalcemia (SCH), diagnosed at parturition (SCH-0) and 7 d in milk (SCH-7), with fertility in a herd of grazing dairy cows. Additional objectives were to characterize Ca concentration on 0 and 7 d in milk (DIM), assessing the risk factors for SCH-0 and SCH-7 and also the relationship with health status (metritis, endometritis, subclinical ketosis, and culling). A prospective observational study was carried out in a dairy farm in Argentina. Holstein cows (n = 126) were body condition scored (BCS, 1-5) on -21 ± 3, 0, 7 ± 3, and 28 ± 7 DIM and blood was collected on 0 and 7 ± 3 DIM to determine Ca and ß-hydroxybutyrate concentrations. Calcium concentrations <2.0 and <2.14 mmol/L were used to define SCH-0 and SCH-7, respectively. The associations of SCH with (1) the odds for pregnancy to first service (P1AI) and pregnancy by 100 DIM (P100) were evaluated by logistic models, (2) the services per pregnancy was evaluated by a Poisson regression model, and (3) the hazards of insemination and pregnancy were evaluated with proportional hazards regression models whereas median days from calving to first insemination and to pregnancy were estimated by Kaplan-Meier method. Additionally, Ca concentration was assessed by linear regression models, and the associations of SCH-0 and SCH-7 with the odds for metritis, endometritis, subclinical ketosis, and culling were evaluated by logistic models. Calcium concentrations were similar at 0 and 7 DIM (2.40 vs. 2.41 mmol/L, respectively); they were higher in cows calving in fall than in summer (2.58 vs. 2.24 mmol/L), and they also were higher in primiparous than in multiparous cows (2.53 vs. 2.28 mmol/L, respectively). The proportion of cows having SCH-0 and SCH-7 was 27.3 and 39.3%, respectively. Fall-calving cows had lower odds for SCH-0 [odds ratio (OR) = 0.31, 95% confidence interval (CI) = 0.12-0.86] than summer-calving cows, multiparous cows had higher odds for SCH-0 (OR = 3.96, 95% CI = 1.09-14.39) than primiparous cows, and cows with prepartum BCS ≥3.00 had higher odds for SCH-0 (OR = 4.03, 95% CI = 1.17-13.89) than in cows with BCS <3.00. Conversely, parity and prepartum BCS were not important predictors for SCH-7. Surprisingly, SCH-0 was not a risk factor for SCH-7. Cows with SCH-0 had lower odds for P1AI (OR = 0.26, 95% CI = 0.07-0.99) than normocalcemic cows, given that P1AI was 14 versus 38%, respectively. The hazard of first service was not associated with SCH-0 (hazard ratio = 1.03, 95% CI = 0.63-1.70) but cows with SCH-0 had lower hazard of pregnancy (hazard ratio = 0.39, 95% CI = 0.16-0.98) and took 32 d longer to get pregnant (105 vs. 73) than normocalcemic cows. Conversely, SCH-7 was not associated with fertility. Finally, SCH-0 and SCH-7 were associated with the odds for subclinical ketosis and metritis, respectively. In conclusion, SCH-0 but not SCH-7 is associated with reduced fertility in a herd of grazing dairy cows, but both were associated with health status.

Effect of peer instruction on the likelihood for choosing the correct response to a physiology question.

The aims of the present study were to measure the effects of individual answer (correct vs. incorrect), individual answer of group members (no vs. some vs. all correct), self-confidence about the responses (low vs. mid vs. high), sex (female vs. male students), and group size (2-4 students) on the odds for change and for correctness after peer instruction in a veterinary physiology course (n = 101 students). Data were assessed by multivariable logistic regression analysis. The likelihood for change after peer instruction increased when the confidence on an individual answer was low (P < 0.01), when the answer was incorrect (P < 0.01), and when group members had different responses (P < 0.01). The likelihood for correctness after peer instruction increased when the confidence in group answers was high (P < 0.01), when the individual answer was correct (P < 0.01), and when at least one of the group members had the correct response (P < 0.01). After peer discussion, more changes were from incorrect to correct responses than vice versa (72% vs. 28%, P < 0.01). Changes to correct answers occurred after discussion with peers having both the correct individual response (76% of times) and also the incorrect individual answer (24% of times). In conclusion, the benefits of peer instruction are due to students having correct answers generally prevail in discussions. Also, students who all have incorrect answers can get the correct answer through debate and discussion.

How does a hopping kangaroo breathe?

We developed a model to demonstrate how a hopping kangaroo breathes. Interestingly, a kangaroo uses less energy to breathe while hopping than while standing still. This occurs, in part, because rather than using muscle power to move air into and out of the lungs, air is pulled into (inspiration) and pushed out of (expiration) the lungs as the abdominal organs "flop" within the kangaroo's body. Specifically, as the kangaroo hops upward, the abdominal organs lag behind, and the insertion of the diaphragm is pulled toward its origin, flattening the dome and increasing the vertical dimension of the thoracic cavity (the thoracic cavity and lungs enlarge). Increasing the volume of the thoracic cavity reduces alveolar pressure below atmospheric pressure (barometric pressure), and air moves into the alveoli by bulk flow. In contrast, the impact of the organs against the diaphragm at each landing causes expiration. Specifically, upon landing, the abdominal organs flop into the diaphragm, causing it to return to its dome shape and decreasing the vertical dimension of the thoracic cavity. This compresses the alveolar gas volume and elevates alveolar pressure above barometric pressure, so air is expelled. To demonstrate this phenomenon, the plunger of a syringe model of the respiratory system was inserted through a compression spring. Holding the syringe and pressing the plunger firmly against a hard surface expels air from the lungs (the balloon within the syringe deflates) and compresses the spring. This models the kangaroo landing after a hop forward. Subsequently, the compression spring provides the energy for the "kangaroo" to "hop" forward upon the release of the syringe, and air enters the lungs (the balloon within the syringe inflates). The model accurately reflects how a hopping kangaroo breathes. A model was chosen to demonstrate this phenomenon because models engage and inspire students as well as significantly enhance student understanding.

Hooke's law: applications of a recurring principle.

Students generally approach topics in physiology as a series of unrelated phenomena that share few underlying principles. However, if students recognized that the same underlying principles can be used to explain many physiological phenomena, they may gain a more unified understanding of physiological systems. To address this concern, we developed a simple, inexpensive, and easy to build model to demonstrate the underlying principles regarding Starling's Law of the Heart as well as lung and arterial elastic recoil. A model was chosen because models significantly enhance student understanding. Working with models also encourages research-oriented learning and helps our students understand complex ideas. Students are drawn into discussion by the power of learning that is associated with manipulating and thinking about objects. Recognizing that the same underlying principles can be used to explain many physiological phenomena may help students gain a more complete understanding of physiological systems.

A model of locomotor-respiratory coupling in quadrupeds.

Locomotion and respiration are not independent phenomena in running mammals because locomotion and respiration both rely on cyclic movements of the ribs, sternum, and associated musculature. Thus, constraints are imposed on locomotor and respiratory function by virtue of their linkage. Specifically, locomotion imposes mechanical constraints on breathing that require the respiratory cycle to be synchronized with gait. Thus, many mammals, including humans, synchronize respiration with the movement of the limbs during locomotion. For example, quadrupeds synchronize locomotor and respiratory cycles at a 1:1 ratio (stride/breath) over a wide range of speeds. Interestingly, quadrupeds maintain an almost constant stride frequency (and therefore respiratory frequency) at different speeds. To increase speed, quadrupeds lengthen their stride. Accordingly, to increase minute ventilation, quadrupeds must increase tidal volume since respiratory rate is coupled with stride frequency. We developed a simple, inexpensive, and easy to build model to demonstrate this concept. A model was chosen because models significantly enhance student understanding. Students are drawn into discussion by the power of learning that is associated with manipulating and thinking about objects. Building and using this model strengthen the concept that locomotor-respiratory coupling provides a basis for the appropriate matching of lung ventilation to running speed and metabolic power.

Student interaction characteristics during collaborative group testing.

We used collaborative testing in a veterinary physiology course (65 students) to answer the following questions: 1) do students with individual correct responses or students with individual incorrect responses change their answers during group testing? and 2) do high-performing students make the decisions, that is, are low-performing students carried by high-performing peers? To address these questions, students first completed the exam in the traditional format as individuals. After completing the exam as individuals, students completed the same exam in groups of two. Finally, the same questions were discussed by the instructor and students (instructor feedback). We found that students with individual incorrect responses changed their answers during group testing more often than students with individual correct responses (odds ratio: 7.58, P < 0.01). Furthermore, student feedback was more beneficial when group members had different individual answers than when they had same individual answers (P < 0.05). In addition, when group members had different individual answers, more answers were changed to correct responses than to incorrect responses (77% vs. 23%, P < 0.01). It was more important to have the correct answer than to be the high-performing student, because the student with the correct response (being either the high- or low-performing student) generally prevailed ( approximately 80% of the time, P = 0.5). Finally, the positive effects of group testing (77% of total effects, P < 0.05) were due to students who changed their individual answer to the correct response after discussion with peers with the correct response and also with the incorrect individual response.

Collaborative group testing benefits high- and low-performing students.

We used collaborative group testing in a veterinary physiology course (65 students) to test the hypothesis that all students (e.g., high-performing and low-performing students of each group) benefit from collaborative group testing. In this format, students answered questions in the traditional format as individuals. Immediately after completing the exam as individuals, students answered the same questions in groups of two, and, finally, the same questions were discussed by the instructor and students. We measured two learning outcomes for every student: individual and group test scores. Based on individual test scores, students were categorized as "high performing" (students with higher individual scores) or "low performing" (students with lower individual scores). Finally, student evaluations of the format were collected. Collaborative group testing enhanced student performance. Specifically, group scores were higher than individual scores (P < 0.001). Importantly, the size of the collaborative testing effect was large for the population and for the low-performing students; however, the collaborative testing effect was small for the high-performing students. Finally, student evaluations of this testing format were very positive. In conclusion, collaborative group testing was beneficial for all students; however, collaborative testing was significantly more beneficial for low-performing students.

Peer instruction enhanced student performance on qualitative problem-solving questions.

We tested the hypothesis that peer instruction enhances student performance on qualitative problem-solving questions. To test this hypothesis, qualitative problems were included in a peer instruction format during our Physiology course. Each class of 90 min was divided into four to six short segments of 15 to 20 min each. Each short segment was followed by a qualitative problem-solving scenario that could be answered with a multiple-choice quiz. All students were allowed 1 min to think and to record their answers. Subsequently, students were allowed 1 min to discuss their answers with classmates. Students were then allowed to change their first answer if desired, and both answers were recorded. Finally, the instructor and students discussed the answer. Peer instruction significantly improved student performance on qualitative problem-solving questions (59.3 +/- 0.5% vs. 80.3 +/- 0.4%). Furthermore, after peer instruction, only 6.5% of the students changed their correct response to an incorrect response; however, 56.8% of students changed their incorrect response to a correct response. Therefore, students with incorrect responses changed their answers more often than students with correct responses. In conclusion, pausing four to six times during a 90-min class to allow peer instruction enhanced student performance on qualitative problem-solving questions.