Synthesis and Characterization of Transition Metal Based Metal Oxide and Metallic Nanocrystals for Ac Magnetic Devices and Catalysis

The d-block elements are very important in magnetics, electronics, catalysis, and biological systems. The synthesis and characterization of nearly monodisperse d-block element based nanocrystals with a precise control over the size, composition, and shape are important to utilize the nanocrystals in such applications. The goals of my thesis are to synthesize d-block transition metal based nanocrystals and understand their magnetic and catalytic properties. I present the size- and composition-dependent AC magnetic permeability of superparamagnetic iron oxide nanocrystals for radio frequency applications. The nanocrystals are synthesized through high-temperature solvothermal decomposition, and their stoichiometry is determined by Mossbauer spectroscopy. Size-dependent magnetic permeability is observed in maghemite nanocrystals, while as-synthesized, magnetite-rich, iron oxide nanocrystals do not show size dependence due to the inhomogeneous crystal structure of the as-synthesized nanocrystals. The saturation magnetization of iron oxide nanocrystals is increased by doping of non-magnetic Zn2+ into A site of ferrite, resulting the enhancement of the real part of the magnetic permeability of Zn0.25Fe2.75O4 nanocrystals by twofold compared to that of similarly sized ferrite nanocrystals. The integration of 12.3 nm Zn0.25Fe2.75O4 nanocrystals into a microfabricated toroidal inductor and a solenoid inductor yield higher quality factors than air core inductors with the same geometries. The ligand exchange with dendrimers reduces the blocking temperature of Mn0.08Zn0.33Fe2.59O4 nanocrystal, indicating the decrease of dipolar coupling between nanocrystals. The study on MnxFe3-xO4 and CoxFe3-xO4 nanocrystals shows a clear difference in DC and AC magnetic behaviors of soft and hard magnetic nanocrystals. The inductor with zinc ferrite nanocrystal core is embedded into a power converter and its temperature dependent energy efficiency is measured. The energy efficiency of a power converter with the nanocrystal core inductor rises as the temperature increases while that of the power converters with an air core inductor or commercial core inductor decreases. Finally, I describe the hydrodeoxygenation reaction of 5-hydroxymethylfurfural into 2,5-dimethylfuran by metallic nanocrystals such as Pt, PtMn, PtFe, PtCo, and PtNi. Both conversion ratio and selectivity for 2,5-dimethylfuran show clear composition dependent catalytic properties and, in particular, 3.7 nm Pt3Co2 nanocrystals achieve 98 % of selectivity for 2,5-dimethylfuran

The genome-scale metabolic network analysis of Zymomonas mobilis ZM4 explains physiological features and suggests ethanol and succinic acid production strategies

<p>Abstract</p> <p>Background</p> <p><it>Zymomonas mobilis </it>ZM4 is a Gram-negative bacterium that can efficiently produce ethanol from various carbon substrates, including glucose, fructose, and sucrose, <it>via </it>the Entner-Doudoroff pathway. However, systems metabolic engineering is required to further enhance its metabolic performance for industrial application. As an important step towards this goal, the genome-scale metabolic model of <it>Z. mobilis </it>is required to systematically analyze <it>in silico </it>the metabolic characteristics of this bacterium under a wide range of genotypic and environmental conditions.</p> <p>Results</p> <p>The genome-scale metabolic model of <it>Z. mobilis </it>ZM4, ZmoMBEL601, was reconstructed based on its annotated genes, literature, physiological and biochemical databases. The metabolic model comprises 579 metabolites and 601 metabolic reactions (571 biochemical conversion and 30 transport reactions), built upon extensive search of existing knowledge. Physiological features of <it>Z. mobilis </it>were then examined using constraints-based flux analysis in detail as follows. First, the physiological changes of <it>Z. mobilis </it>as it shifts from anaerobic to aerobic environments (i.e. aerobic shift) were investigated. Then the intensities of flux-sum, which is the cluster of either all ingoing or outgoing fluxes through a metabolite, and the maximum <it>in silico </it>yields of ethanol for <it>Z. mobilis </it>and <it>Escherichia coli </it>were compared and analyzed. Furthermore, the substrate utilization range of <it>Z. mobilis </it>was expanded to include pentose sugar metabolism by introducing metabolic pathways to allow <it>Z. mobilis </it>to utilize pentose sugars. Finally, double gene knock-out simulations were performed to design a strategy for efficiently producing succinic acid as another example of application of the genome-scale metabolic model of <it>Z. mobilis</it>.</p> <p>Conclusion</p> <p>The genome-scale metabolic model reconstructed in this study was able to successfully represent the metabolic characteristics of <it>Z. mobilis </it>under various conditions as validated by experiments and literature information. This reconstructed metabolic model will allow better understanding of <it>Z. mobilis </it>metabolism and consequently designing metabolic engineering strategies for various biotechnological applications.</p

Prediction of novel synthetic pathways for the production of desired chemicals

<p>Abstract</p> <p>Background</p> <p>There have been several methods developed for the prediction of synthetic metabolic pathways leading to the production of desired chemicals. In these approaches, novel pathways were predicted based on chemical structure changes, enzymatic information, and/or reaction mechanisms, but the approaches generating a huge number of predicted results are difficult to be applied to real experiments. Also, some of these methods focus on specific pathways, and thus are limited to expansion to the whole metabolism.</p> <p>Results</p> <p>In the present study, we propose a system framework employing a retrosynthesis model with a prioritization scoring algorithm. This new strategy allows deducing the novel promising pathways for the synthesis of a desired chemical together with information on enzymes involved based on structural changes and reaction mechanisms present in the system database. The prioritization scoring algorithm employing Tanimoto coefficient and group contribution method allows examination of structurally qualified pathways to recognize which pathway is more appropriate. In addition, new concepts of binding site covalence, estimation of pathway distance and organism specificity were taken into account to identify the best synthetic pathway. Parameters of these factors can be evolutionarily optimized when a newly proven synthetic pathway is registered. As the proofs of concept, the novel synthetic pathways for the production of isobutanol, 3-hydroxypropionate, and butyryl-CoA were predicted. The prediction shows a high reliability, in which experimentally verified synthetic pathways were listed within the top 0.089% of the identified pathway candidates.</p> <p>Conclusions</p> <p>It is expected that the system framework developed in this study would be useful for the <it>in silico </it>design of novel metabolic pathways to be employed for the efficient production of chemicals, fuels and materials.</p

Photocatalytic Hydrogen Evolution from Sub-Stoichiometric Colloidal WO3-xNanowires

We report direct photocatalytic hydrogen evolution from substoichiometric highly reduced tungsten oxide (WOx) nanowires (NWs) using sacrificial alcohol. WOx NWs are synthesized via nonaqueous colloidal synthesis with a diameter of about 4 nm and an average length of about 250 nm. As-synthesized WOx NWs exhibit a broad absorption across the visible to infrared regions attributed to the presence of oxygen vacancies. The optical band gap is increased in these WOx NWs compared to stoichiometric bulk tungsten oxide (WO3) powders as a result of the Burstein\u2013Moss shift. As a consequence of this increase, we demonstrate direct photocatalytic hydrogen production from WOx NWs through alcohol photoreforming. The stable H2 evolution on platinized WOx NWs is observed under conditions in which platinized bulk WO3 and bulk WO2.9 powders either do not show activity or show very low rates, suggesting that increased surface area and specific exposed facets are key for the improved performance of WOx NWs. This work demonstrates that control of size and composition can lead to unexpected and beneficial changes in the photocatalytic properties of semiconductor materials

Analysis of clinical and genomic profiles of therapy-related myeloid neoplasm in Korea

Background Therapy-related myeloid neoplasm (T-MN) rarely occurs among cancer survivors, and wascharacterized by poor prognosis. T-MN has germline predisposition in a considerable proportion. Here, clinical characteristics and germline/somatic variant profiles in T-MN patients were investigated, and the findings were compared with those of previous studies. Methods A review of medical records, cytogenetic study, targeted sequencing by next-generation sequencing, and survival analysis were performed on 53 patients with T-MN at a single institution in Korea. Results The patients were relatively younger compared to T-MN patients in other studies. Our T-MN patients showed ahigh frequency of complex karyotypes, −5/del(5q), and −7/del(7q), which was similar to the Japanese study group but higher than the Australian study group. The most common primary disease was non-Hodgkin lymphoma, followed by breast cancer. The detailed distributions of primary diseases were different across study groups. Seven patients (13.2%) harbored deleterious presumed/potential germline variants in cancer predisposition genes (CPG) such as BRIP1, CEBPA, DDX41, FANCM, NBN, NF1, and RUNX1. In the somatic variant profile, TP53 was the most frequently mutated gene, which was consistent with the previous studies about T-MN. However, the somatic variant frequency in our study group was lower than in other studies. Adverse factors for overall survival were male sex, older age, history of previous radiotherapy, previous longer cytotoxic therapy, and −5/del(5q). Conclusion The findings of our study corroborate important information about T-MN patients. As well as a considerable predisposition to CPG, the clinical characteristics and somatic variant profile showed distinctive patterns. Germline variant testing should be recommended for T-MN patients. If the T-MN patients harbor pathogenic germline variants, the family members for stem cell donation should be screened for carrier status through germline variant testing to avoid donor-derived myeloid neoplasm. For the prediction of the prognosis in T-MN patients, sex, age, past treatment history, and cytogenetic findings can be considered.This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korean government (MSIT) (NRF-2017R1A2A1A17069780 and NRF-2020R1A3B3079653) and a Grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) funded by the Ministry of Health & Welfare, Republic of Korea (Grant No. HR14C0003)

Transcriptional signatures of the BCL2 family for individualized acute myeloid leukaemia treatment

Abstract Background Although anti-apoptotic proteins of the B-cell lymphoma-2 (BCL2) family have been utilized as therapeutic targets in acute myeloid leukaemia (AML), their complicated regulatory networks make individualized therapy difficult. This study aimed to discover the transcriptional signatures of BCL2 family genes that reflect regulatory dynamics, which can guide individualized therapeutic strategies. Methods From three AML RNA-seq cohorts (BeatAML, LeuceGene, and TCGA; n = 451, 437, and 179, respectively), we constructed the BCL2 family signatures (BFSigs) by applying an innovative gene-set selection method reflecting biological knowledge followed by non-negative matrix factorization (NMF). To demonstrate the significance of the BFSigs, we conducted modelling to predict response to BCL2 family inhibitors, clustering, and functional enrichment analysis. Cross-platform validity of BFSigs was also confirmed using NanoString technology in a separate cohort of 47 patients. Results We established BFSigs labeled as the BCL2, MCL1/BCL2, and BFL1/MCL1 signatures that identify key anti-apoptotic proteins. Unsupervised clustering based on BFSig information consistently classified AML patients into three robust subtypes across different AML cohorts, implying the existence of biological entities revealed by the BFSig approach. Interestingly, each subtype has distinct enrichment patterns of major cancer pathways, including MAPK and mTORC1, which propose subtype-specific combination treatment with apoptosis modulating drugs. The BFSig-based classifier also predicted response to venetoclax with remarkable performance (area under the ROC curve, AUROC = 0.874), which was well-validated in an independent cohort (AUROC = 0.950). Lastly, we successfully confirmed the validity of BFSigs using NanoString technology. Conclusions This study proposes BFSigs as a biomarker for the effective selection of apoptosis targeting treatments and cancer pathways to co-target in AML

ITDetect: a method to detect internal tandem duplication of FMS-like tyrosine kinase (FLT3) from next-generation sequencing data with high sensitivity and clinical application

Abstract Internal tandem duplication (ITD) of the FMS-like tyrosine kinase (FLT3) gene is associated with poor clinical outcomes in patients with acute myeloid leukemia. Although recent methods for detecting FLT3-ITD from next-generation sequencing (NGS) data have replaced traditional ITD detection approaches such as conventional PCR or fragment analysis, their use in the clinical field is still limited and requires further information. Here, we introduce ITDetect, an efficient FLT3-ITD detection approach that uses NGS data. Our proposed method allows for more precise detection and provides more detailed information than existing in silico methods. Further, it enables FLT3-ITD detection from exome sequencing or targeted panel sequencing data, thereby improving its clinical application. We validated the performance of ITDetect using NGS-based and experimental ITD detection methods and successfully demonstrated that ITDetect provides the highest concordance with the experimental methods. The program and data underlying this study are available in a public repository

NPM1 as a potential therapeutic target for atypical teratoid/rhabdoid tumors

Background Atypical teratoid/rhabdoid tumors (AT/RTs) are highly malignant brain tumors with inactivation of the SMARCB1 gene, which play a critical role in genomic transcriptional control. In this study, we analyzed the genomic and transcriptomic profiles of human AT/RTs to discover new druggable targets. Methods Multiplanar sequencing analyses, including whole exome sequencing (WES), single nucleotide polymorphism (SNP) arrays, array comparative genomic hybridization (aCGH), and whole transcriptome sequencing (RNA-Seq), were performed on 4 AT/RT tissues. Validation of a druggable target was conducted using AT/RT cell lines. Results WES revealed that the AT/RT genome is extremely stable except for the inactivation of SMARCB1. However, we identified 897 significantly upregulated genes and 523 significantly downregulated genes identified using RNA-Seq, indicating that the transcriptional profiles of the AT/RT tissues changed substantially. Gene set enrichment assays revealed genes related to the canonical pathways of cancers, and nucleophosmin (NPM1) was the most significantly upregulated gene in the AT/RT samples. An NPM1 inhibitor (NSC348884) effectively suppressed the viability of 7 AT/RT cell lines. Network analyses showed that genes associated with NPM1 are mainly involved in cell cycle regulation. Upon treatment with an NPM1 inhibitor, cell cycle arrest at G1 phase was observed in AT/RT cells. Conclusions We propose that NPM1 is a novel therapeutic target for AT/RTs.This research was supported by the Bio & Medical Technology Development Program (NRF-2018M3A9H3021707) and the Basic Science Research Program (NRF-2019R1A2C2005144) through the National Research Foundation of Korea (NRF) funded by the Ministry of Science & ICT of Republic of Korea and a grant from the Samsung SDS. The funders collaboratively provided grants to complete the sequencing, data analysis, in vitro experiments, and publication