A CRISPR-Based Toolbox for Studying T Cell Signal Transduction

CRISPR/Cas9 system is a powerful technology to perform genome editing in a variety of cell types. To facilitate the application of Cas9 in mapping T cell signaling pathways, we generated a toolbox for large-scale genetic screens in human Jurkat T cells. The toolbox has three different Jurkat cell lines expressing distinct Cas9 variants, including wild-type Cas9, dCas9-KRAB, and sunCas9. We demonstrated that the toolbox allows us to rapidly disrupt endogenous gene expression at the DNA level and to efficiently repress or activate gene expression at the transcriptional level. The toolbox, in combination with multiple currently existing genome-wide sgRNA libraries, will be useful to systematically investigate T cell signal transduction using both loss-of-function and gain-of-function genetic screens

Essays on Monetary Policy

In a standard New Keynesian model, the central bank moves the real rate when it changes the nominal interest rate since the price level responds sluggishly to change in nominal rates due to nominal rigidity. Monetary policy is non-neutral, for it moves the real rate, thus alters agents’ intertemporal consumption decisions. The standard model is a simplified world without information frictions or regional heterogeneity. In a world with information frictions, monetary policy actions communicate to the public about the central bank’s private information. Monetary policy can generate additional effects by shaping agents’ beliefs about the true state of the economy or the future monetary policy path. In a world with regional heterogeneity, monetary policy can have interesting interactions with local characteristics. This dissertation investigates regime-dependent, state-dependent, and heterogeneous regional effects of monetary policy.Chapter 1 introduces a new regime dependence of monetary policy due to information frictions: the effects of monetary policy shocks depend on the type of the fundamental macro shock in the economy. Specifically, output responses to monetary policy shocks are amplified relative to their counterparts in perfect information models when the fundamental macro shock is a productivity level shock or a demand shock. In contrast, output responses are dampened when the fundamental macro shock is a productivity growth rate shock. Households observe the overall fundamental in the economy but cannot distinguish its persistent part from its temporary part. The central bank sets the interest rate tracking a function of the persistent fundamental plus a monetary policy shock, so the interest rate is a noisy signal about the persistent fundamental with the monetary policy shock as the noise. Exogenous monetary policy shocks lead households to update their perceptions about the persistent fundamental differently facing varying types of fundamental macro shocks, thus generating heterogeneous effects on output.Chapter 2 introduces the position effect: the effects of a monetary policy shock depend on its relative position in the monetary policy sequence. I use both event study and local projections methods to investigate how the effects of monetary policy depend on the relative position of monetary policy shocks in monetary policy sequences. The effects of monetary policy are less potent in the first half of monetary policy sequences, which I phrase as the position effect. Possible explanations include different implicit forward guidance, different information effects, and Fed's different interest rate smoothing behavior at different positions in the monetary policy sequence. I provide supporting evidence for the interest rate smoothing behavior: less interest rate smoothing in the first half of a monetary policy sequence shortens the shock duration, thus weakening the effect.Chapter 3, joint work with Ninghui Li, investigates the regional heterogeneity of monetary policy on local house prices. House prices in growing urban areas are more sensitive to monetary policy. We first define urban growth and urban decline using CBSA level population data and then test local house prices to monetary policy shocks using local projections. The housing supply elasticity does not drive our results, although it plays a role in house price dynamics. We find evidence supporting that the effect of monetary policy interacts with the long-run expectations driven by local population growth

A CRISPR-Based Toolbox for Studying T Cell Signal Transduction.

CRISPR/Cas9 system is a powerful technology to perform genome editing in a variety of cell types. To facilitate the application of Cas9 in mapping T cell signaling pathways, we generated a toolbox for large-scale genetic screens in human Jurkat T cells. The toolbox has three different Jurkat cell lines expressing distinct Cas9 variants, including wild-type Cas9, dCas9-KRAB, and sunCas9. We demonstrated that the toolbox allows us to rapidly disrupt endogenous gene expression at the DNA level and to efficiently repress or activate gene expression at the transcriptional level. The toolbox, in combination with multiple currently existing genome-wide sgRNA libraries, will be useful to systematically investigate T cell signal transduction using both loss-of-function and gain-of-function genetic screens

A CRISPR-Based Toolbox for Studying T Cell Signal Transduction.

CRISPR/Cas9 system is a powerful technology to perform genome editing in a variety of cell types. To facilitate the application of Cas9 in mapping T cell signaling pathways, we generated a toolbox for large-scale genetic screens in human Jurkat T cells. The toolbox has three different Jurkat cell lines expressing distinct Cas9 variants, including wild-type Cas9, dCas9-KRAB, and sunCas9. We demonstrated that the toolbox allows us to rapidly disrupt endogenous gene expression at the DNA level and to efficiently repress or activate gene expression at the transcriptional level. The toolbox, in combination with multiple currently existing genome-wide sgRNA libraries, will be useful to systematically investigate T cell signal transduction using both loss-of-function and gain-of-function genetic screens

Laser shape variation influence on melt pool dynamics and solidification microstructure in laser powder bed fusion

The shape variation of the laser beam is evidently observed in the laser powder bed fusion (LPBF) process because of changes in laser incidence angle and misalignment between the build plate and the laser focus plane. This issue is particularly relevant in large-scale LPBF systems where the laser beam needs to scan a large build area. However, most LPBF modeling studies assume vertical laser radiation. The heat transfer, melt pool, and solidification evolution due to the laser shape variation have not been well addressed and quantified. In the present study, the temperature distribution, melt pool geometry and flow dynamics are captured via numerical modelling, and the grain morphology is characterized under various laser incidence angles. The results show that the melt pool depth becomes shallower, and the width is near the beam size as the laser beam becomes more elongated. The beam shape variation can affect the liquid flow pattern with increasing incidence angle, resulting in a larger vortex at the front of the melt pool and a smaller vortex at the rear of the melt pool. The thermal gradient increases and the solidification rate decreases as the laser incident angle becomes larger. The present study enhances the understanding of multi-physics in the LPBF process

Quantum Dots-Loaded Self-Healing Gels for Versatile Fluorescent Assembly

From the perspective of applied science, methods that allow the simple construction of versatile quantum dots (QDs)-loaded gels are highly desirable. In this work, we report the self-healing assembly methods for various fluorescent QDs-loaded gels. Firstly, we employed horizontal frontal polymerization (FP) to fabricate self-healing gels within several minutes using a rapid and energy-saving means of preparation. The as-prepared gels showed pH sensitivity, satisfactory mechanical properties and excellent self-healing properties and the healing efficiency reached 90%. The integration of the QDs with the gels allowed the generation of fluorescent composites, which were successfully applied to an LED device. In addition, by using the self-healing QDs-loaded gels as building blocks, the self-healing assembly method was used to construct complex structures with different fluorescence, which could then be used for sensing and encoding. This work offers a new perspective on constructing various fluorescent assemblies by self-healing assembly, and it might stimulate the future application of self-healing gels in a self-healing assembly fashion

An Attention Cascade Global–Local Network for Remote Sensing Scene Classification

Remote sensing image scene classification is an important task of remote sensing image interpretation, which has recently been well addressed by the convolutional neural network owing to its powerful learning ability. However, due to the multiple types of geographical information and redundant background information of the remote sensing images, most of the CNN-based methods, especially those based on a single CNN model and those ignoring the combination of global and local features, exhibit limited performance on accurate classification. To compensate for such insufficiency, we propose a new dual-model deep feature fusion method based on an attention cascade global–local network (ACGLNet). Specifically, we use two popular CNNs as the feature extractors to extract complementary multiscale features from the input image. Considering the characteristics of the global and local features, the proposed ACGLNet filters the redundant background information from the low-level features through the spatial attention mechanism, followed by which the locally attended features are fused with the high-level features. Then, bilinear fusion is employed to produce the fused representation of the dual model, which is finally fed to the classifier. Through extensive experiments on four public remote sensing scene datasets, including UCM, AID, PatternNet, and OPTIMAL-31, we demonstrate the feasibility of the proposed method and its superiority over the state-of-the-art scene classification methods

Exploration of a hypoxia-immune-related microenvironment gene signature and prediction model for hepatitis C-induced early-stage fibrosis

Abstract Background Liver fibrosis contributes to significant morbidity and mortality in Western nations, primarily attributed to chronic hepatitis C virus (HCV) infection. Hypoxia and immune status have been reported to be significantly correlated with the progression of liver fibrosis. The current research aimed to investigate the gene signature related to the hypoxia-immune-related microenvironment and identify potential targets for liver fibrosis. Method Sequencing data obtained from GEO were employed to assess the hypoxia and immune status of the discovery set utilizing UMAP and ESTIMATE methods. The prognostic genes were screened utilizing the LASSO model. The infiltration level of 22 types of immune cells was quantified utilizing CIBERSORT, and a prognosis-predictive model was established based on the selected genes. The model was also verified using qRT-PCR with surgical resection samples and liver failure samples RNA-sequencing data. Results Elevated hypoxia and immune status were linked to an unfavorable prognosis in HCV-induced early-stage liver fibrosis. Increased plasma and resting NK cell infiltration were identified as a risk factor for liver fibrosis progression. Additionally, CYP1A2, CBS, GSTZ1, FOXA1, WDR72 and UHMK1 were determined as hypoxia-immune-related protective genes. The combined model effectively predicted patient prognosis. Furthermore, the preliminary validation of clinical samples supported most of the conclusions drawn from this study. Conclusion The prognosis-predictive model developed using six hypoxia-immune-related genes effectively predicts the prognosis and progression of liver fibrosis. The current study opens new avenues for the future prediction and treatment of liver fibrosis