Molecular phenotypes of bovine blastocyst derived from in vitro-matured oocyte supplemented with PAPP-A

Insulin-like growth factor-1 (IGF-1) regulates cellular lipid content, whereas pregnancy-associated plasma protein-A (PAPP-A) increases IGF-1 bioavailability. Using in vitro-matured cumulus-oocyte complexes, we aimed to evaluate the impact of PAPP-A on the blastocyst lipid content, embryo cryotolerance and embryonic transcriptional profile. We determined that PAPP-A did not affect the lipid content of oocytes, blastocysts, or blastocyst yield (P > 0.05). However, PAPP-A modulated the embryo transcriptional profiles by downregulating PPARGC1A and AKR1B1, which are related to lipid metabolism; CASP9, a pro-apoptotic gene; and IFN-τ, a marker of embryo quality (P < 0.05). Furthermore, the use of PAPP-A improved blastocyst re-expansion in the first 3 h of culture after vitrification (P < 0.05). Although PAPP-A did not affect the blastocyst lipid content or embryo production, we suggest that embryonic transcriptional modulation could contribute to maintain the balance in embryo lipid metabolism. Furthermore, PAPP-A's approach seems to control key intracellular pathways that improve post-cryopreservation development of blastocysts.

Artificial Intelligence-Based Grading Quality of Bovine Blastocyst Digital Images: Direct Capture with Juxtaposed Lenses of Smartphone Camera and Stereomicroscope Ocular Lens

In this study, we developed an online graphical and intuitive interface connected to a server aiming to facilitate professional access worldwide to those facing problems with bovine blastocysts classification. The interface Blasto3Q, where 3Q refers to the three qualities of the blastocyst grading, contains a description of 24 variables that were extracted from the image of the blastocyst and analyzed by three Artificial Neural Networks (ANNs) that classify the same loaded image. The same embryo (i.e., the biological specimen) was submitted to digital image capture by the control group (inverted microscope with 40× magnification) and the experimental group (stereomicroscope with maximum of magnification plus 4× zoom from the cell phone camera). The images obtained from the control and experimental groups were uploaded on Blasto3Q. Each image from both sources was evaluated for segmentation and submitted (only if it could be properly or partially segmented) for automatic quality grade classification by the three ANNs of the Blasto3Q program. Adjustments on the software program through the use of scaling algorithm software were performed to ensure the proper search and segmentation of the embryo in the raw images when they were captured by the smartphone, since this source produced small embryo images compared with those from the inverted microscope. With this new program, 77.8% of the images from smartphones were successfully segmented and from those, 85.7% were evaluated by the Blasto3Q in agreement with the control group.