Deciphering association signals from genome-wide association studies

Over 90% of disease-associated variants detected from Genome-wide Association Studies (GWAS) are in non-coding regions of the genome, making the interpretation of GWAS signals a daunting challenge. Recent advances in genome-wide experimental assays like high-throughput chromosome conformation capture (Hi-C) have greatly improved our understanding of chromatin folding principles and revealed the structural basis of gene regulation and genome function. One essential task in the analysis of chromatin interactome data is the identification of long-range chromatin interactions. However, existing computational tools are all designed for analyzing individual cell types or samples, ignoring unbalanced sequencing depths and heterogeneity among multiple samples. In my first dissertation project, I present MUNIn, a novel statistical framework for identifying long-range chromatin interactions from multiple samples. MUNIn achieves lower false positive rates for sample-specific interactions and enhanced statistical power for shared interactions. Following MUNIn, I will briefly illustrate how I used chromatin conformation data with functional genomics data to identify potential functional genes underlying GWAS signals for cognitive impairment among children born extremely preterm. In my second dissertation project, I propose SnapHiC-G, a new computational approach based on a global background model to identify cell-type-specific long-range enhancer-promoter interactions from single-cell HiC (scHi-C) data. SnapHiC-G outperforms existing methods designed for both single-cell and bulk Hi-C data with higher sensitivity in identifying long-range enhancer-promoter interactions. SnapHiC-G is a powerful tool for characterizing cell-type-specific enhancer-promoter interactions in single cells from complex tissue samples and facilitating the interpretation of non-coding GWAS variants. In my third project, I explore the effect of using a more comprehensive LD reference panel for LD score calculation and LD score regression (LDSC) estimates to control for false positives in GWAS results. Results showed that more polygenic signals could be captured by including more variants in the regression, and low-frequency variants exhibited less inflation compared with common variants. Assessing the impact of using a more comprehensive LD reference panel in LD score computation as well as LDSC estimates has important practical implications, and it will guide the choices of the most appropriate LD scores to use and sets of variants to be included in the analysis.Doctor of Philosoph

On the shock wave boundary layer interaction in slightly-rarefied gas

The shock wave and boundary layer interaction (SWBLI) plays an important role in the design of hypersonic vehicles. However, discrepancies between the numerical results of high-temperature gas dynamics and experiment data have not been fully addressed. It is believed that the rarefaction effects are important in SWBLI, but the systematic analysis of the temperature-jump boundary conditions and the role of translational/rotational/vibrational heat conductivities are lacking. In this paper, we derive the three-temperature Navier-Stokes-Fourier (NSF) equations from the gas kinetic theory, with special attention paid to the components of heat conductivity. With proper temperature-jump boundary conditions, we simulate the SWBLI in the double cone experiment. Our numerical results show that, when the three heat conductivities are properly recovered, the NSF equations can capture the position and peak value of the surface heat flux, in both low- and high-enthalpy inflow conditions. Moreover, the separation bubble induced by the separated shock and the reattachment point induced by impact between transmitted shock and boundary layer are found to agree with the experimental measurement

Research on Crash Safety Design of Electric Vehicle Power Battery

By expounding the collision conditions of electric vehicles, analyzing the characteristics of battery collision under different collision conditions, and studying the traditional collision safety design of electric vehicle power batteries, a new safety design method based on battery damage tolerance is proposed, which aims to provide help for improving the safety protection of electric vehicle power batteries in collision and improve the safety of power batteries in collision, Meet people's requirements for vehicle safety

Antidiabetic effect of Tibetan medicine Tang-Kang-Fu-San in db/db mice via activation of PI3K/Akt and AMPK pathways

This study was to investigate the anti-diabetic effects and molecular mechanisms of Tang-Kang-Fu-San (TKFS), a traditional Tibetan medicine, in treating type 2 diabetes mellitus of spontaneous diabetic db/db mice. Firstly HPLC fingerprint analysis was performed to gain the features of the chemical compositions of TKFS. Next different doses of TKFS (0.5 g/kg, 1.0 g/kg, and 2.0 g/kg) were administrated via oral gavage to db/db mice and their controls for 4 weeks. TKFS significantly lowered hyperglycemia and ameliorated insulin resistance (IR) in db/db mice, indicated by results from multiple tests, including fasting blood glucose test, intraperitoneal insulin and glucose tolerance tests, fasting serum insulin levels and homeostasis model assessment of IR analysis as well as histology of pancreas islets. TKFS also decreased concentrations of serum triglyceride, total and low-density lipoprotein cholesterol, even though it did not change the mouse body weights. Results from western blot and immunohistochemistry analysis indicated that TKFS reversed the down-regulation of p-Akt and p-AMPK, and increased the translocation of Glucose transporter type 4 in skeletal muscles of db/db mice. In all, TKFS had promising benefits in maintaining the glucose homeostasis and reducing IR. The underlying molecular mechanisms are related to promote Akt and AMPK activation and Glucose transporter type 4 translocation in skeletal muscles. Our work showed that multicomponent Tibetan medicine TKFS acted synergistically on multiple molecular targets and signaling pathways to treat type 2 diabetes mellitus

Existence and Asymptotic Behavior of Traveling Wave Fronts for a Time-Delayed Degenerate Diffusion Equation

This paper is concerned with traveling wave fronts for a degenerate diffusion equation with time delay. We first establish the necessary and sufficient conditions to the existence of monotone increasing and decreasing traveling wave fronts, respectively. Moreover, special attention is paid to the asymptotic behavior of traveling wave fronts connecting two uniform steady states. Some previous results are extended

MELA: Multilingual Evaluation of Linguistic Acceptability

Recent benchmarks for Large Language Models (LLMs) have mostly focused on application-driven tasks such as complex reasoning and code generation, and this has led to a scarcity in purely linguistic evaluation of LLMs. Against this background, we introduce Multilingual Evaluation of Linguistic Acceptability -- MELA, the first multilingual benchmark on linguistic acceptability with 48K samples covering 10 languages from a diverse set of language families. We establish baselines of commonly used LLMs along with supervised models, and conduct cross-lingual transfer and multi-task learning experiments with XLM-R. In pursuit of multilingual interpretability, we analyze the weights of fine-tuned XLM-R to explore the possibility of identifying transfer difficulty between languages. Our results show that ChatGPT benefits much from in-context examples but still lags behind fine-tuned XLM-R, while the performance of GPT-4 is on par with fine-tuned XLM-R even in zero-shot setting. Cross-lingual and multi-task learning experiments show that unlike semantic tasks, in-language training data is crucial in acceptability judgements. Results in layerwise probing indicate that the upper layers of XLM-R become a task-specific but language-agnostic region for multilingual acceptability judgment. We also introduce the concept of conflicting weight, which could be a potential indicator for the difficulty of cross-lingual transfer between languages. Our data will be available at https://github.com/sjtu-compling/MELA.Comment: Work in progres