PET/MR imaging of hypoxic atherosclerotic plaque using 64Cu-ATSM

ABSTRACT OF THE DISSERTATION PET/MR Imaging of Hypoxic Atherosclerotic Plaque Using 64Cu-ATSM by Xingyu Nie Doctor of Philosophy in Biomedical Engineering Washington University in St. Louis, 2017 Professor Pamela K. Woodard, Chair Professor Suzanne Lapi, Co-Chair It is important to accurately identify the factors involved in the progression of atherosclerosis because advanced atherosclerotic lesions are prone to rupture, leading to disability or death. Hypoxic areas have been known to be present in human atherosclerotic lesions, and lesion progression is associated with the formation of lipid-loaded macrophages and increased local inflammation which are potential major factors in the formation of vulnerable plaque. This dissertation work represents a comprehensive investigation of non-invasive identification of hypoxic atherosclerotic plaque in animal models and human subjects using the PET hypoxia imaging agent 64Cu-ATSM. We first demonstrated the feasibility of 64Cu-ATSM for the identification of hypoxic atherosclerotic plaque and evaluated the relative effects of diet and genetics on hypoxia progression in atherosclerotic plaque in a genetically-altered mouse model. We then fully validated the feasibility of using 64Cu-ATSM to image the extent of hypoxia in a rabbit model with atherosclerotic-like plaque using a simultaneous PET-MR system. We also proceeded with a pilot clinical trial to determine whether 64Cu-ATSM MR/PET scanning is capable of detecting hypoxic carotid atherosclerosis in human subjects. In order to improve the 64Cu-ATSM PET image quality, we investigated the Siemens HD (high-definition) PET software and 4 partial volume correction methods to correct for partial volume effects. In addition, we incorporated the attenuation effect of the carotid surface coil into the MR attenuation correction _-map to correct for photon attention. In the long term, this imaging strategy has the potential to help identify patients at risk for cardiovascular events, guide therapy, and add to the understanding of plaque biology in human patients

Diverse Applications of Nanomedicine

The design and use of materials in the nanoscale size range for addressing medical and health-related issues continues to receive increasing interest. Research in nanomedicine spans a multitude of areas, including drug delivery, vaccine development, antibacterial, diagnosis and imaging tools, wearable devices, implants, high-throughput screening platforms, etc. using biological, nonbiological, biomimetic, or hybrid materials. Many of these developments are starting to be translated into viable clinical products. Here, we provide an overview of recent developments in nanomedicine and highlight the current challenges and upcoming opportunities for the field and translation to the clinic. \ua9 2017 American Chemical Society

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Unified Graph and Low-Rank Tensor Learning for Multi-View Clustering

Multi-view clustering aims to take advantage of multiple views information to improve the performance of clustering. Many existing methods compute the affinity matrix by low-rank representation (LRR) and pairwise investigate the relationship between views. However, LRR suffers from the high computational cost in self-representation optimization. Besides, compared with pairwise views, tensor form of all views' representation is more suitable for capturing the high-order correlations among all views. Towards these two issues, in this paper, we propose the unified graph and low-rank tensor learning (UGLTL) for multi-view clustering. Specifically, on the one hand, we learn the view-specific affinity matrix based on projected graph learning. On the other hand, we reorganize the affinity matrices into tensor form and learn its intrinsic tensor based on low-rank tensor approximation. Finally, we unify these two terms together and jointly learn the optimal projection matrices, affinity matrices and intrinsic low-rank tensor. We also propose an efficient algorithm to iteratively optimize the proposed model. To evaluate the performance of the proposed method, we conduct extensive experiments on multiple benchmarks across different scenarios and sizes. Compared with the state-of-the-art approaches, our method achieves much better performance

Nitrogen Self-Doping Carbon Derived from Functionalized Poly(Vinylidene Fluoride) (PVDF) for Supercapacitor and Adsorption Application

A new synthetic strategy has been developed for the facile fabrication of a N-doped porous carbon (NC-800) material via a facile carbonization of functionalized poly(vinylidene fluoride) (PVDF). The prepared NC-800 exhibits good specific capacitance of 205 F/g at 1 A/g and cycle stability (95.2% retention after 5000 cycles at 1 A/g). The adsorption capacity of NC-800 on methylene blue and methyl orange was 780 mg/g and 800 mg/g, respectively. The facile and economical method and good performance (supercapacitor and adsorption) suggest that the NC-800 is a promising material for energy storage and adsorption

Greenhouse Gas Emissions in the Process of Landfill Disposal in China

Quantitative accounting of greenhouse gas (GHG) emissions has become an important global focus. GHG emissions from the waste sector have high potential in GHG emissions reduction. We analyzed the GHG emissions inventory in the waste sector of the European Union, Germany, the United Kingdom, the United States of America, and Canada from 1990 to 2019. Landfill disposal was the main category of GHGs from the waste sector, with a contribution rate between 69% and 95%. Landfill disposal also played a prominent role in emission reduction, with a contribution rate higher than 86%. GHG emissions from landfill sites in China were calculated using the inventory analysis method recommended by the IPCC and combined with actual situations. The results showed that the highest GHG emissions from landfill disposal in China occurred in 2020, with an estimated 165 million tons of carbon dioxide (CO2) equivalent. In 2019, the per capita GHG emissions from landfill sites in China was 117 kg CO2 equivalent/person, which was higher than Germany (87 kg CO2 equivalent/person) but lower than the European Union (189 kg CO2 equivalent/person)

Study on the Technology of Monodisperse Droplets by a High-Throughput and Instant-Mixing Droplet Microfluidic System

In this study, we report a novel high-throughput and instant-mixing droplet microfluidic system that can prepare uniformly mixed monodisperse droplets at a flow rate of mL/min designed for rapid mixing between multiple solutions and the preparation of micro-/nanoparticles. The system is composed of a magneton micromixer and a T-junction microfluidic device. The magneton micromixer rapidly mixes multiple solutions uniformly through the rotation of the magneton, and the mixed solution is sheared into monodisperse droplets by the silicone oil in the T-junction microfluidic device. The optimal conditions of the preparation of monodisperse droplets for the system have been found and factors affecting droplet size are analyzed for correlation; for example, the structure of the T-junction microfluidic device, the rotation speed of the magneton, etc. At the same time, through the uniformity of the color of the mixed solution, the mixing performance of the system is quantitatively evaluated. Compared with mainstream micromixers on the market, the system has the best mixing performance. Finally, we used the system to simulate the internal gelation broth preparation of zirconium broth and uranium broth. The results show that the system is expected to realize the preparation of ceramic microspheres at room temperature without cooling by the internal gelation process