Involvement of aberrant chromosome architecture and locus-specific vulnerability to DNA methylation epimutations in bovine large offspring syndrome

Large/abnormal offspring syndrome (LOS/AOS) and Beckwith-Wiedemann syndrome (BWS) are similar congenital overgrowth syndromes which occur naturally in ruminants and humans, respectively. The incidence of these syndromes increases when offspring are conceived with the use of assisted reproductive technologies (ART; i.e. in vitro oocyte maturation, in vitro fertilization, and embryo culture). Molecular defects reported in both syndromes include global gene misregulation, DNA methylome epimutations, and disruption of genomic imprinting (parental-allele-specific gene expression). Although we have reported that bovine LOS occurs spontaneously (SLOS) based on phenotypic similarities to ART-LOS, to date no study has been conducted to determine if SLOS has the same methylome epimutations as ART-LOS. One goal of my dissertation research is to characterize DNA methylation profiles in bovine SLOS and ART-LOS to determine whether there are conserved genomic loci with DNA methylation defects between these overgrowth conditions. In addition, while it is known that LOS is characterized by global alterations in DNA methylation, it is largely unknown how altered DNA methylation drives the development of LOS, as the methylation errors (i.e., differentially methylated regions; DMRs) observed in the syndrome only explain [less than] 4 percent of the gene misregulation in short range (the flanking 20,000 DNA bases from the DMR). Therefore, another goal of my dissertation research is to determine whether long-range regulatory mechanisms of gene expression, such as chromosome architecture, is altered in LOS as a result of aberrant DNA methylation. In this dissertation, Chapter 1 is the literature review and will introduce epigenetic regulation of gene expression including chromosome architecture and clinical features and molecular findings of LOS and BWS. Chapter 2 and 3 are the research chapters. In Chapter 2, I characterize allele-specific chromosome architecture of IGF2R imprinted domain in fibroblast cells derived from control bovine fetuses and identified disrupted chromosome architecture in LOS. I also observed genomic location-based clustering tendency of misregulated genes in LOS. This study has been published in the Journal iScience (https://doi.org/10.1016/j.isci.2022.104269) (Li et al., 2022). In Chapter 3, I determined that bovine SLOS has DNA methylation defects with some similarities and differences when compared to ART-LOS. I also identified vulnerable genomic loci for DNA methylation defects in LOS, which could serve as molecular markers for the diagnosis of the syndrome during early pregnancy. This study has been published in the journal Epigenetics (https://doi.org/10.1080/15592294.2022.2067938). Chapter 4 is the general discussion in which my research findings are incorporated into the general knowledge of the field and implications and directions of future studies are discussed. In Appendix 1, I briefly introduce our ongoing Hi-C (global chromosome architecture), methylome and transcriptome project in which samples from LOS and BWS will be analyzed together to further shed light into the etiology of these syndromes, knowledge that will equally help Agriculture and Biomedicine. I anticipate submitting this manuscript for peer review and publication in July of 2022, thus becoming the third primary literature manuscript from my dissertation research. Appendix 2 is a review paper in which I am main contributor author published in Veterinary Clinics of North America: Food Animal Practice in 2019 (PMID: 31103180, https://doi.org/10.1016/j.cvfa.2019.02.007). This review summarized clinical and molecular findings in LOS and for the first time reported the existence of SLOS. Lastly, Appendix 3 summarizes my contributions of five other publications in which I collaborated with groups in the Division, at Mizzou, and other Academic institutions in the USA during my tenure as a PhD student.Includes bibliographical references

Exploring Privacy-traces of Users from Online Community: A Case Study of Diabetes Topic Discussions

Online health communities (OHCs) have already become essential medium for people to obtain medical knowledge, share experiences and emotions. OHC users are able to post user-generated content (UGC) to interact with each other. However, the large amount of UGC may lead to personal information even privacy disclosed online. Although such disclosure may help users to trade some social support, which is the basis of sustaining a successful OHC, the users should be aware of the risks of leaving such traces online. This study selects a popular online Q & A community “Zhihu” in China as the research target. By collecting all questions and corresponding answers from 4 diabetes sub-communities, we would like to identify online privacy-traces of users from UGC. According to the theory of Communication Privacy Management, we build an explanatory model to understand user behaviors of concealing or revealing private information from the aspects of user characteristics, peer attention, and social support effects

Stroke Extraction of Chinese Character Based on Deep Structure Deformable Image Registration

Stroke extraction of Chinese characters plays an important role in the field of character recognition and generation. The most existing character stroke extraction methods focus on image morphological features. These methods usually lead to errors of cross strokes extraction and stroke matching due to rarely using stroke semantics and prior information. In this paper, we propose a deep learning-based character stroke extraction method that takes semantic features and prior information of strokes into consideration. This method consists of three parts: image registration-based stroke registration that establishes the rough registration of the reference strokes and the target as prior information; image semantic segmentation-based stroke segmentation that preliminarily separates target strokes into seven categories; and high-precision extraction of single strokes. In the stroke registration, we propose a structure deformable image registration network to achieve structure-deformable transformation while maintaining the stable morphology of single strokes for character images with complex structures. In order to verify the effectiveness of the method, we construct two datasets respectively for calligraphy characters and regular handwriting characters. The experimental results show that our method strongly outperforms the baselines. Code is available at https://github.com/MengLi-l1/StrokeExtraction.Comment: 10 pages, 8 figures, published to AAAI-23 (oral

The iNOS/Src/FAK axis is critical in Toll-like receptor-mediated cell motility in macrophages

AbstractThe Toll-like receptors (TLRs) play a pivotal role in innate immunity for the detection of highly conserved, pathogen-expressed molecules. Previously, we demonstrated that lipopolysaccharide (LPS, TLR4 ligand)-increased macrophage motility required the participation of Src and FAK, which was inducible nitric oxide synthase (iNOS)-dependent. To investigate whether this iNOS/Src/FAK pathway is a general mechanism for macrophages to mobilize in response to engagement of TLRs other than TLR4, peptidoglycan (PGN, TLR2 ligand), polyinosinic–polycytidylic acid (polyI:C, TLR3 ligand) and CpG-oligodeoxynucleotides (CpG, TLR9 ligand) were used to treat macrophages in this study. Like LPS stimulation, simultaneous increase of cell motility and Src (but not Fgr, Hck, and Lyn) was detected in RAW264.7, peritoneal macrophages, and bone marrow-derived macrophages exposed to PGN, polyI:C and CpG. Attenuation of Src suppressed PGN-, polyI:C-, and CpG-elicited movement and the level of FAK Pi-Tyr861, which could be reversed by the reintroduction of siRNA-resistant Src. Besides, knockdown of FAK reduced the mobility of macrophages stimulated with anyone of these TLR ligands. Remarkably, PGN-, polyI:C-, and CpG-induced Src expression, FAK Pi-Tyr861, and cell mobility were inhibited in macrophages devoid of iNOS, indicating the importance of iNOS. These findings corroborate that iNOS/Src/FAK axis occupies a central role in macrophage locomotion in response to engagement of TLRs

Altered microrna expression profiles in bovine fetuses with an assisted reproduction-induced congenital overgrowth syndrome

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Assisted reproductive technologies (ART) refer to a series of fertility treatments used to conceive offspring. ART is used worldwide in humans for treatment of infertility and in ruminants to improve genetic merit. The use of ART can induce congenital overgrowth conditions in humans and ruminants, namely Beckwith-Wiedemann syndrome (BWS) and large offspring syndrome (LOS), respectively. Shared phenotypes and epigenotypes have been found between BWS and LOS. A previous study in our laboratory found global misregulation of transcripts in bovine fetuses with LOS. microRNAs (miRNAs) have been shown to play important roles in post-transcriptional regulation of gene expression. There is one study that reports misregulation of one miRNA in BWS and no studies have been done to identify misregulation of miRNAs in LOS. The goal of this study is to investigate miRNA expression profiles, determine whether there are miRNAs misregulated in bovine LOS fetuses, and functionally analyze the misregulated miRNAs. In this thesis, chapter 1, the literature review, will introduce BWS including its molecular basis, clinical features, diagnosis, and treatments. Chapter 1 will also introduce LOS including studies on embryo culture in various species, gene expression studies, and previous studies from our laboratory. In addition, chapter 1 will introduce miRNAs including its biogenesis and function. Chapter 2, which is the research chapter, will show the data of misregulated miRNA profiles in bovine LOS fetuses. Chapter 2 will become a manuscript and will be sent for peer-review soon. After chapter 2, the reader will find a general discussion in which my research findings will be incorporated into the general knowledge of the field

Point Cloud Information Extraction for Streetlights with Vehicle-borne LiDAR

The acquisition of detailed information for the streetlights in a large scene remains a tough task since the streetlights are of great number and types. In this paper, a method is proposed to extract and classify the streetlights, with the aid of prior sample sets on the basis of skeleton-line-buffer discriminant algorithm. First, a model and a priori sample set for streetlights are established according to the expression characteristics of streetlights in vehicle-borne LiDAR point cloud. Secondly, with the theory and method of mathematical morphology, the rod-shaped objects are extracted in vehicle LiDAR point cloud scene, and the candidate streetlights are chosen under the constraint of streetlight model and semantic rules. Then, the candidate samples are selected from the sample sets according to the parameter information and the statistical information obtained from the selected streetlights. Finally, based on the matching algorithm of least squares theory, we select and match the priori samples of streetlights and the candidate streetlights. Based on the double buffer of streetlight skeleton information, we discriminate and analyze the candidate streetlights to achieve the extraction and identification of street lights. Finally, the priori samples of streetlights and the point cloud of the candidate streetlights are matched and screened with the matching algorithm of least square theory; and based on the double buffer of streetlight skeleton information, the candidate streetlights are discriminated and analyzed to achieve the extraction and identification of streetlights. Our experiment shows that the algorithm is efficient and robust for the extraction of detailed information of streetlights. For the streetlights with less occlusion and relatively complete data, the extraction accuracy is 0.952, and for those with serous occlusion, low point cloud density and poor data integrity, the extraction accuracy is 0.780. And the above results validate the robustness of the proposed algorithm for the extraction of intermediate streetlights from large scenes. The detailed information extracted by the algorithm can be used to serve the fine and dynamic management of streetlights in large scenes

Diversity of formyltetrahydrofolate synthetase genes in the rumens of roe deer (Capreolus pygargus) and sika deer (Cervus nippon) fed different diets

Reductive acetogenesis by homoacetogens represents an alternative pathway to methanogenesis to remove metabolic hydrogen during rumen fermentation. In this study, we investigated the occurrence of homoacetogen in the rumens of pasture-fed roe deer (Capreolus pygargus) and sika deer (Cervus nippon) fed either oak leaf (tannin-rich, 100 mg/kg dried matter), corn stover, or corn silage-based diets, by using formyltetrahydrofolate synthetase (FTHFS) gene sequences as a marker. The diversity and richness of FTHFS sequences was lowest in animals fed oak leaf, indicating that tannin-containing plants may affect rumen homoacetogen diversity. FTHFS amino acid sequences in the rumen of roe deer significantly differed from those of sika deer. The phylogenetic analyses showed that 44.8% of sequences in pasture-fed roe deer, and 72.1%, 81.1%, and 37.5% of sequences in sika deer fed oak leaf, corn stover, and corn silage based diets, respectively, may represent novel bacteria that have not yet been cultured. These results demonstrate that the rumens of roe deer and sika deer harbor potentially novel homoacetogens and that diet may influence homoacetogen community structure.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Research on the Electrodeposition of Graphene Quantum Dots under Supercritical Conditions to Enhance Nickel-Based Composite Coatings

A graphene quantum dots (GQDs)-reinforced nickel-based composite coating was electrodeposited on the surface of a copper plate with a supercritical carbon dioxide fluid (SC-CO2)-assisted DC power supply. The effect of the current density on surface morphology, microstructure, average grain size, hardness, and corrosion resistance of the resulting coatings was investigated in detail. It was found that the GQDs composite coating showed a more compact surface, a smaller grain size, higher microhardness, and stronger corrosion resistance than the pure Ni coating produced in SC-CO2 and a texture coefficient indicative of a (111) preferred orientation. When the current density was 8 A/dm2, the surface morphology of the GQDs composite coating showed a high density, and the grain size was about 23 nm. In addition, the micro-hardness and corrosion resistance of the GQDs composite coating was greatly improved compared with those of the pure nickel coating; at the same time, its wear rate, friction coefficient, and self-corrosion current density were decreased by 73.2%, 17.5%, and 9.2%, respectively

Point Sampling with General Noise Spectrum

Point samples with different spectral noise properties (often defined using color names such as white, blue, green, and red) are important for many science and engineering disciplines including computer graphics. While existing techniques can easily produce white and blue noise samples, relatively little is known for generating other noise patterns. In particular, no single algorithm is available to generate different noise patterns according to user-defined spectra. In this paper, we describe an algorithm for generating point samples that match a user-defined Fourier spectrum function. Such a spectrum function can be either obtained from a known sampling method, or completely constructed by the user. Our key idea is to convert the Fourier spectrum function into a differential distribution function that describes the samples ’ local spatial statistics; we then use a gradient descent solver to iteratively compute a sample set that matches the target differential distribution function. Our algorithm can be easily modified to achieve adaptive sampling, and we provide a GPU-based implementation. Finally, we present a variety of different sample patterns obtained using our algorithm, and demonstrate suitable applications