Structural variations: detection and annotation in cancer genomes

Structural variations (SVs) are genomic variants that typically impact more than 50 nucleotides in length and significantly contribute to cancer development and evolution. However, it is challenging to accurately infer and classify SVs in full range and type using short-read next-generation sequencing (NGS) technologies, which will also limit downstream annotation efforts to understanding their oncogenic impact. This PhD thesis addresses the challenges of SV detection and annotation in cancer genomics. Firstly, Chapter 1 summarises current methods and limitations for inferring somatic SVs. A comprehensive evaluation study is conducted in Chapter 2 to assess the extent to which various common factors impact SV detection accuracy, and hence should be considered in whole-genome sequencing (WGS) study designs. Shiny-SoSV, a web-based interactive performance calculator is developed in Chapter 3 for estimation and comparison of somatic SV detection sensitivity and precision based on any combinations of user-definable parameters. In Chapter 4, a “real-life” application of somatic SV detection and annotation is conducted for a large-scale prostate cancer genomics study, providing insights into the role of SV in cancer development. Finally, in Chapter 5, two validation approaches, using visual inspection and long-read sequencing data, are evaluated and compared to provide guidance on a “best practise” for SV validation. Overall, this PhD work highlights, and offers solutions to overcome challenges associated with SV detection and annotation, and illustrates the power of incorporating SVs in cancer genomic studies

Evolutionary nonnegative matrix factorization for data compression

This paper aims at improving non-negative matrix factor- ization (NMF) to facilitate data compression. An evolutionary updat- ing strategy is proposed to solve the NMF problem iteratively based on three sets of updating rules including multiplicative, firefly and sur- vival of the fittest rules. For data compression application, the quality of the factorized matrices can be evaluated by measurements such as spar- sity, orthogonality and factorization error to assess compression quality in terms of storage space consumption, redundancy in data matrix and data approximation accuracy. Thus, the fitness score function that drives the evolving procedure is designed as a composite score that takes into account all these measurements. A hybrid initialization scheme is per- formed to improve the rate of convergence, allowing multiple initial can- didates generated by different types of NMF initialization approaches. Effectiveness of the proposed method is demonstrated using Yale and ORL image datasets

Salt Content Distribution and Paleoclimatic Significance of the Lop Nur “Ear” Feature: Results from Analysis of EO-1 Hyperion Imagery

Lop Nur, a playa lake located on the eastern margin of Tarim Basin in northwestern China, is famous for the “Ear” feature of its salt crust, which appears in remote-sensing images. In this study, partial least squares (PLS) regression was used to estimated Lop Nur playa salt-crust properties, including total salt, Ca2+, Mg2+, Na+, Si2+, and Fe2+ using laboratory hyperspectral data. PLS results for laboratory-measured spectra were compared with those for resampled laboratory spectra with the same spectral resolution as Hyperion using the coefficient of determination (R2) and the ratio of standard deviation of sample chemical concentration to root mean squared error (RPD). Based on R2 and RPD, the results suggest that PLS can predict Ca2+ using Hyperion reflectance spectra. The Ca2+ distribution was compared to the “Ear area” shown in a Landsat Thematic Mapper (TM) 5 image. The mean value of reflectance from visible bands for a 14 km transversal profile to the “Ear area” rings was extracted with the TM 5 image. The reflectance was used to build a correlation with Ca2+ content estimated with PLS using Hyperion. Results show that the correlation between Ca2+ content and reflectance is in accordance with the evolution of the salt lake. Ca2+ content variation was consistent with salt deposition. Some areas show a negative correlation between Ca2+ content and reflectance, indicating that there could have been a small-scale temporary runoff event under an arid environmental background. Further work is needed to determine whether these areas of small-scale runoff are due to natural (climate events) or human factors (upstream channel changes

USP38 Exacerbates Atrial Inflammation, Fibrosis, and Susceptibility to Atrial Fibrillation After Myocardial Infarction in Mice

BACKGROUND: Inflammation plays an important role in the pathogenesis of atrial fibrillation (AF) after myocardial infarction (MI). The role of USP38, a member of the ubiquitin-specific protease family, on MI-induced atrial inflammation, fibrosis, and associated AF is unclear. METHODS: In this study, we surgically constructed a mouse MI model using USP38 cardiac conditional knockout (USP38-CKO) and cardiac-specific overexpression (USP38-TG) mice and applied biochemical, histological, electrophysiological characterization and molecular biology to investigate the effects of USP38 on atrial inflammation, fibrosis, and AF and its mechanisms. RESULTS: Our results revealed that USP38-CKO attenuates atrial inflammation, thereby ameliorating fibrosis, and abnormal electrophysiologic properties, and reducing susceptibility to AF on day 7 after MI. USP38-TG showed the opposite effect. Mechanistically, The TAK1/NF-κB signaling pathway in the atria was significantly activated after MI, and phosphorylated TAK1, P65, and IκBα protein expression was significantly upregulated. USP38-CKO inhibited the activation of the TAK1/NF-κB signaling pathway, whereas USP38-TG overactivated the TAK1/NF-κB signaling pathway after MI. USP38 is dependent on the TAK1/NF-κB signaling pathway and regulates atrial inflammation, fibrosis, and arrhythmias after MI to some extent. CONCLUSIONS: USP38 plays an important role in atrial inflammation, fibrosis, and AF susceptibility after MI, providing a promising target for the treatment of AF after MI

3D printing high interfacial bonding polyether ether ketone components via pyrolysis reactions

Recently, 3D-printed polyether-ether-ketone (PEEK) components have been shown to offer many applications in state-of-the-art electronics, 5G wireless communications, medical implantations, and aerospace components. Nevertheless, a critical barrier that limits the application of 3D printed PEEK components is their weak interfacial bonding strength. Herein, we propose a novel method to improve this unsatisfied situation via the interface plasticizing effect of benzene derivatives obtained from the thermal pyrolysis of trisilanolphenyl polyhedral oligomeric silsequioxane (POSS). Based on this method, the bonding strength of the filaments and interlayers of 3D-printed POSS/PEEK components can reach 82.9 MPa and 59.8 MPa, respectively. Moreover, the enhancing mechanism of the pyrolysis products derived from the POSS is characterized using pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), Fourier transform infrared spectroscopy (FTIR), and X-ray computed tomography (X-CT). Our proposed strategy broadens the novel design space for developing additional 3D-printed materials with satisfactory interfacial bonding strength

Magnetically-dressed CrSBr exciton-polaritons in ultrastrong coupling regime

The strong coupling between photons and matter excitations such as excitons, phonons, and magnons is of central importance in the study of light-matter interactions. Bridging the flying and stationary quantum states, the strong light-matter coupling enables the coherent transmission, storage, and processing of quantum information, which is essential for building photonic quantum networks. Over the past few decades, exciton-polaritons have attracted substantial research interest due to their half-light-half-matter bosonic nature. Coupling exciton-polaritons with magnetic orders grants access to rich many-body phenomena, but has been limited by the availability of material systems that exhibit simultaneous exciton resonances and magnetic ordering. Here we report magnetically-dressed microcavity exciton-polaritons in the van der Waals antiferromagnetic (AFM) semiconductor CrSBr coupled to a Tamm plasmon microcavity. Angle-resolved spectroscopy reveals an exceptionally high exciton-polariton coupling strength attaining 169 meV, demonstrating ultrastrong coupling that persists up to room temperature. Temperature-dependent exciton-polariton spectroscopy senses the magnetic order change from AFM to paramagnetism in CrSBr, confirming its magnetic nature. By applying an out-of-plane magnetic field, an effective tuning of the polariton energy is further achieved while maintaining the ultrastrong exciton-photon coupling strength, which is attributed to the spin canting process that modulates the interlayer exciton interaction. Our work proposes a hybrid quantum platform enabled by robust opto-electronic-magnetic coupling, promising for quantum interconnects and transducers.Comment: 8 pages, 4 figure

High-Speed Serial Optical Link Test Bench Using FPGA with Embedded Transceivers

We develop a custom Bit Error Rate test bench based on Altera’s Stratix II GX transceiver signal integrity development kit, demonstrate it on point-to-point serial optical link with data rate up to 5 Gbps, and compare it with commercial stand alone tester. The 8B/10B protocol is implemented and its effects studied. A variable optical attenuator is inserted in the fibre loop to induce transmission degradation and to measure receiver sensitivity. We report comparable receiver sensitivity results using the FPGA based tester and commercial tester. The results of the FPGA also shows that there are more one-tozero bit flips than zero-to-one bit flips at lower error rate. In 8B/10B coded transmission, there are more word errors than bit flips, and the total error rate is less than two times that of non-coded transmission. Total error rate measured complies with simulation results, according to the protocol setup

Evolutionary nonnegative matrix factorization with adaptive control of cluster quality

Nonnegative matrix factorization (NMF) approximates a given data matrix using linear combinations of a small number of nonnegative basis vectors, weighted by nonnegative encoding coefficients. This enables the exploration of the cluster structure of the data through the examination of the values of the encoding coefficients and therefore, NMF is often used as a popular tool for clustering analysis. However, its encoding coefficients do not always reveal a satisfactory cluster structure. To improve its effectiveness, a novel evolutionary strategy is proposed here to drive the iterative updating scheme of NMF and generate encoding coefficients of higher quality that are capable of offering more accurate and sharper cluster structures. The proposed hybridization procedure that relies on multiple initializations reinforces the robustness of the solution. Additionally, three evolving rules are designed to simultaneously boost the cluster quality and the reconstruction error during the iterative updates. Any clustering performance measure, such as either an internal one relying on the data itself or an external based on the availability of ground truth information, can be employed to drive the evolving procedure. The effectiveness of the proposed method is demonstrated via careful experimental designs and thorough comparative analyses using multiple benchmark datasets

An integrated transcriptomic and metabolic phenotype analysis to uncover the metabolic characteristics of a genetically engineered Candida utilis strain expressing δ-zein gene

IntroductionCandida utilis (C. utilis) has been extensively utilized as human food or animal feed additives. With its ability to support heterologous gene expression, C. utilis proves to be a valuable platform for the synthesis of proteins and metabolites that possess both high nutritional and economic value. However, there remains a dearth of research focused on the characteristics of C. utilis through genomic, transcriptomic and metabolic approaches.MethodsWith the aim of unraveling the molecular mechanism and genetic basis governing the biological process of C. utilis, we embarked on a de novo sequencing endeavor to acquire comprehensive sequence data. In addition, an integrated transcriptomic and metabolic phenotype analysis was performed to compare the wild-type C. utilis (WT) with a genetically engineered strain of C. utilis that harbors the heterologous δ-zein gene (RCT).Resultsδ-zein is a protein rich in methionine found in the endosperm of maize. The integrated analysis of transcriptomic and metabolic phenotypes uncovered significant metabolic diversity between the WT and RCT C. utilis. A total of 252 differentially expressed genes were identified, primarily associated with ribosome function, peroxisome activity, arginine and proline metabolism, carbon metabolism, and fatty acid degradation. In the experimental setup using PM1, PM2, and PM4 plates, a total of 284 growth conditions were tested. A comparison between the WT and RCT C. utilis demonstrated significant increases in the utilization of certain carbon source substrates by RCT. Gelatin and glycogen were found to be significantly utilized to a greater extent by RCT compared to WT. Additionally, in terms of sulfur source substrates, RCT exhibited significantly increased utilization of O-Phospho-L-Tyrosine and L-Methionine Sulfone when compared to WT.DiscussionThe introduction of δ-zein gene into C. utilis may lead to significant changes in the metabolic substrates and metabolic pathways, but does not weaken the activity of the strain. Our study provides new insights into the transcriptomic and metabolic characteristics of the genetically engineered C. utilis strain harboring δ-zein gene, which has the potential to advance the utilization of C. utilis as an efficient protein feed in agricultural applications