Primate Primordial Germ Cells Acquire Transplantation Potential by Carnegie Stage 23.

Primordial germ cells (PGCs) are the earliest embryonic progenitors in the germline. Correct formation of PGCs is critical to reproductive health as an adult. Recent work has shown that primate PGCs can be differentiated from pluripotent stem cells; however, a bioassay that supports their identity as transplantable germ cells has not been reported. Here, we adopted a xenotransplantation assay by transplanting single-cell suspensions of human and nonhuman primate embryonic Macaca mulatta (rhesus macaque) testes containing PGCs into the seminiferous tubules of adult busulfan-treated nude mice. We discovered that both human and nonhuman primate embryonic testis are xenotransplantable, generating colonies while not generating tumors. Taken together, this work provides two critical references (molecular and functional) for defining transplantable primate PGCs. These results provide a blueprint for differentiating pluripotent stem cells to transplantable PGC-like cells in a species that is amenable to transplantation and fertility studies

Swine blood transcriptomics: Application and advancement

Improving swine feed efficiency (FE) by selection for low residual feed intake (RFI) is of practical interest. However, whether selection for low RFI compromises a pig’s immune response is not clear. In addition, current RFI-based selection for improving feed efficiency was expensive and time-consuming. Seeking alternative tools to facilitate selection, such as predictive biomarkers for RFI, is of great interest. The objectives of this thesis are as follows: (1) to investigate whether selection for low RFI compromise a pig’s immune response; (2) to develop candidate biomarkers applicable at early growth stage for predicting RFI at late growth stage; (3) to improve the annotation of the porcine blood transcriptome. In Chapter 2, pigs of two lines divergently selected for RFI were injected with lipopolysaccharide (LPS). Transcriptomes of peripheral blood at baseline and multi-time points post injection were profiled by RNA-seq. LPS injection induced systemic inflammatory response in both RFI lines. However, no significant differences were detected in dynamics of body temperature, blood cell count and cytokine levels during the time course. Only a very small number of differentially expressed genes (DEGs) were detected between the lines over all time points, though ~ 50% of blood genes were differentially expressed post LPS injection compared to baseline for each line. The two lines were largely similar in most biological pathways and processes studied. Minor differences included a slightly lower level of inflammatory response in the low- versus high-RFI animals. Cross-species comparison showed that humans and pigs responded to LPS stimulation similarly at both the gene and pathway levels, though pigs are more tolerant to LPS than humans. In Chapter 3, post-weaning blood transcriptomic differences between the two lines were studied by RNA-seq. DEGs between the lines significantly overlapped gene sets associated with human diseases, such as eating disorders, hyperphagia and mitochondrial disease. Genes functioning in the mitochondrion and proteasome, and signaling had lower and higher expression in the low-RFI group relative to the high-RFI group, respectively. Expression levels of five differentially expressed genes between the two groups were significantly associated with individual animal’s RFI values. These five genes were candidate biomarkers for predicting RFI. Given limitations of current annotation of the porcine reference genome, a high-quality annotated transcriptome of porcine peripheral blood was built in the last study via a hybrid assembly strategy with a large amount of blood RNA-seq data from studies mentioned above and public databases. Taken together, this work provides evidence that selection for low RFI did not significantly compromise pigs’ immune response to systemic inflammation, offers a few candidate biomarkers for predicting RFI to facilitate RFI-based selection, and significantly advances the structural and functional annotation of porcine blood transcriptome

Master of Science

thesisTo minimize resource consumption and maximize performance, computer architecture research has been investigating approaches that may compute inaccurate solutions. Such hardware inaccuracies may induce a wide variety of program behaviors which are not obs

A novel real-time computational framework for detecting catheters and rigid guidewires in cardiac catheterization procedures

Purpose: Catheters and guidewires are used extensively in cardiac catheterization procedures such as heart arrhythmia treatment (ablation), angioplasty and congenital heart disease treatment. Detecting their positions in fluoroscopic X-ray images is important for several clinical applications, for example, motion compensation, co-registration between 2D and 3D imaging modalities and 3D object reconstruction. Methods: For the generalized framework, a multiscale vessel enhancement filter is first used to enhance the visibility of wire-like structures in the X-ray images. After applying adaptive binarization method, the centerlines of wire-like objects were extracted. Finally, the catheters and guidewires were detected as a smooth path which is reconstructed from centerlines of target wire-like objects. In order to classify electrode catheters which are mainly used in electrophysiology procedures, additional steps were proposed. First, a blob detection method, which is embedded in vessel enhancement filter with no additional computational cost, localizes electrode positions on catheters. Then the type of electrode catheters can be recognized by detecting the number of electrodes and also the shape created by a series of electrodes. Furthermore, for detecting guiding catheters or guidewires, a localized machine learning algorithm is added into the framework to distinguish between target wire objects and other wire-like artifacts. The proposed framework were tested on total 10,624 images which are from 102 image sequences acquired from 63 clinical cases. Results: Detection errors for the coronary sinus (CS) catheter, lasso catheter ring and lasso catheter body are 0.56 ± 0.28 mm, 0.64 ± 0.36 mm and 0.66 ± 0.32 mm, respectively, as well as success rates of 91.4%, 86.3% and 84.8% were achieved. Detection errors for guidewires and guiding catheters are 0.62 ± 0.48 mm and success rates are 83.5%. Conclusion: The proposed computational framework do not require any user interaction or prior models and it can detect multiple catheters or guidewires simultaneously and in real-time. The accuracy of the proposed framework is sub-mm and the methods are robust toward low-dose X-ray fluoroscopic images, which are mainly used during procedures to maintain low radiation dose