Melatonin has been used to promote in vitro embryo development in different species. This study determined the effects of melatonin on in vitro porcine embryo development; in particular, cleavage rate, blastocyst rate, and blastocyst cell number. Starting 5 hr after insemination, porcine zygotes were cultured in porcine zygote medium 3 (PZM-3) culture medium supplemented with melatonin at increasing concentrations (10(-12) M, 10(-9) M, 10(-6) M, 10(-3) M). Melatonin at a concentration of 10(-9) M had a positive effect on cleavage rates, while the highest concentration of melatonin (10(-3) M) significantly decreased cleavage rates. Although blastocyst rates were not increased by 10(-9) M melatonin, blastocyst cell numbers were significantly higher for embryos subjected to 10(-9) M melatonin. The expression levels of the pro-apoptotic gene BAX and anti-apoptotic gene BCL2L1 in blastocysts were not affected by the presence of melatonin in the culture medium. To further study the protective properties of 10(-9) M melatonin against stressful conditions, hydrogen peroxide (0.01 mm) and heat (40 degrees C) were used during embryo culture. The addition of melatonin to embryos subjected to 40 degrees C for 3 hr increased cleavage rates, but had no protective effect for embryos subjected to 0.01 mm H(2)O(2), probably because the physiological levels of melatonin could not counteract the pharmacological levels of H(2)O(2). Our data indicate that 10(-9) M melatonin has a positive effect on porcine embryo cleavage rates and blastocyst total cell numbers and it might have a protective effect against heat stress.
Spermatozoa deliver more than the paternal genome into the oocyte; they also carry remnant messenger RNA from spermatogenesis. The RNA profiles of spermatozoa from high-fertility and a low-fertility Holstein bulls were analysed using Affymetrix bovine genechips. A total of 415 transcripts out of approximately 24,000 were differentially detected in spermatozoa collected from both bulls (fold change > or =2.0; P<0.01). These transcripts were associated with different cellular functions and biological processes. Spermatozoa from high-fertility bulls contained higher concentrations of transcripts for membrane and extracellular space protein locations, while spermatozoa from the low-fertility bulls were deficient of transcripts for transcriptional and translational factors. Quantitative real-time PCR was used on three low-fertility and four high-fertility bulls to validate the microarray data. Two highly represented transcripts in the microarray analysis (protamine 1 and casein beta 2) were validated, as well as a third transcript (thrombospondin receptor CD36 molecule) that showed a lower concentration in low-fertility bulls. This study presents the global analysis of spermatozoa originating from bulls with opposite fertility. These results provide some specific transcripts in spermatozoa that could be associated with bull fertility.
Conclusion: Deep learning with multiple harmonized data sources can yield effective models for OPC primary and nodal segmentation using CT alone. The utility of these models will depend on the clinical use case and will be explored on further investigation, though current model performance metrics, particularly for nodal segmentation, are likely adequate for prospective testing in clinical and research applications.
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