Pathway-Based Multi-Omics Data Integration for Breast Cancer Diagnosis and Prognosis.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Development of a temperature control system for spectroscopic measurements with rare-earth doped crystals

This thesis describes the development of a temperature control system for optical spectroscopy experiments with rare-earth doped samples. Low temperature emission spectra were afterwards recorded for a series for Eu3+ singly doped and Ce3+, Eu3+ codoped Y2SiO5 samples. The analysis and assignment of the different energy transitions is presented. The experimental setups used in this thesis involve the optics part, the electronic part and the cooling down system. For the optical measurements, two kinds of pumping laser were used: Dye laser (580 nm) and UV laser (370 nm). A suitable optics system was designed for the collection of fluorescence signals. Electronic circuits were on the other hand built to connect two thermal sensors within the cryostat used for the optical measurements. Two reference temperature sensors were set up so that they could be readout simultaneously by using a switch connected with a temperature monitor. A good control of the cooling down process and the final temperature reached by the samples under investigation is fundamental for spectroscopic investigations performed at cryogenic temperatures as the ones described here

A Survey of Document-Level Information Extraction

Document-level information extraction (IE) is a crucial task in natural language processing (NLP). This paper conducts a systematic review of recent document-level IE literature. In addition, we conduct a thorough error analysis with current state-of-the-art algorithms and identify their limitations as well as the remaining challenges for the task of document-level IE. According to our findings, labeling noises, entity coreference resolution, and lack of reasoning, severely affect the performance of document-level IE. The objective of this survey paper is to provide more insights and help NLP researchers to further enhance document-level IE performance

Photoinduced Thiol-X Polymerizations With Tunable Kinetics and Material Properties

Conventional thermosetting photopolymers have been broadly implemented across industrial settings such as dental composites, UV coatings, and adhesives, with an emerging focus on additive manufacturing. To date, materials for most of these applications are based on (meth)acrylate or similar chain growth free-radical photopolymerizations. However, (meth)acrylate chemistry is generally limited due to the chain growth polymerization mechanism. Introducing alternative step-growth reactions, especially those based on click chemistry, as a means for polymerization is highly desirable as it broadens the range of mechanical, thermal, and optical performance as well as enabling recyclability. Thiol-X click chemistries refer to a series of reactions reacting a thiol with a variety of other functional groups such as alkenes, alkynes, isocyanates, or epoxies. Herein, this thesis is focused on the fundamental understanding andimplementation of photoinduced thiol-X step-growth based polymer networks that achieve rapid kinetics and tunable material properties. Three reactions examined in this thesis include the anion- mediated thiol-Michael reaction, the radical initiated thiol-ene reaction, and the anionic thiol- isocyanate reaction (along with its reverse reaction). In the first part of this thesis, the kinetics and mechanism of the thiol-Michael reaction were evaluated in both bulk and solvent conditions. Individual kinetic parameters for propagation and chain transfer steps were determined for commonly used thiol and vinyl monomers. The calculated kinetic parameters were successfully used to predict the reactivity and selectivity of the monomers in ternary and the network forming reaction systems. Secondly, a series of dental restorativematerials was designed incorporating the thiol-Michael photopolymerization. The beneficial features inherent to anion-mediated thiol-Michael polymerizations such as rapid photo-curing, low stress generation, ester content tunability, and improved mechanical performance in a moist environment were explored. Compared with conventional methacrylate free-radical polymerizations, the thiol-Michael formulations show a dramatic reduction in shrinkage stress. One formulation of the ester-free thiol-Michael resins was observed to have superior and stable mechanical performance even after extensive water exposure. As such, the photopolymerized thiol-Michael resins were promising candidates for implementation in composite dental restorative materials. Finally, to address challenges arising from global plastic waste disposal issues, a series of recyclable thermosetting materials was developed by incorporating dynamic thiourethane bonds into the network. The thiourethane networks were fabricated from a commercially available thiol and isocyanate. The resultant polymer network was readily depolymerized to liquid oligomers in the presence of excess of thiol and a base catalyst, followed by re-repolymerization to form pristine materials without any loss of performance or change in mechanical properties. Furthermore, by combining thiol-isocyanate/thiol-ene sequential reactions, a series of chemically recyclable photopolymers was designed and implemented in formulations for additive manufacturing. Overall, the ease with which these thiourethane networks are polymerized, recycled, and reformulated gives new directions and hope in the design of sustainable, recyclable thermosetting polymers.</p

Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

Comparison of logistic regression, SVM and random forest performance in the plasma training data set. Table S2. Pathway significance and relative log fold changes in our metabolomics data and TCGA breast cancer RNA-Seq data. Table S3. Detected metabolites and their differential test results among the two models. a All-stage diagnosis model. b Early-stage diagnosis model. Table S4. Single-variate logistic analysis of metabolites or pathways selected as features in the metabolite-based or pathway-based early-stage diagnosis model. Table S5. Comparison of pathway features in the full-size (101 input pathways) and half-size (51 input pathways) pathway-based early-stage diagnosis models. (DOCX 34 kb