Engineering topics
Li, Wen
Publications and source records attributed to Li, Wen.
Inhibition of USP7 activity selectively eliminates senescent cells in part via restoration of p53 activity
The accumulation of senescent cells (SnCs) is a causal factor of various age-related diseases as well as some of the side effects of chemotherapy. Pharmacological elimination of SnCs (senolysis) has the potential to be developed into novel therapeutic strategies to treat these diseases and pathological conditions. Here we show that ubiquitin-specific peptidase 7 (USP7) is a novel target for senolysis because inhibition of USP7 with an inhibitor or genetic depletion of USP7 by RNA interference induces apoptosis selectively in SnCs. The senolytic activity of USP7 inhibitors is likely attributable in part to the promotion of the human homolog of mouse double minute 2 (MDM2) ubiquitination and degradation by the ubiquitin–proteasome system. This degradation increases the levels of p53, which in turn induces the pro-apoptotic proteins PUMA, NOXA, and FAS and inhibits the interaction of BCL-XL and BAK to selectively induce apoptosis in SnCs. Further, we show that treatment with a USP7 inhibitor can effectively eliminate SnCs and suppress the senescence-associated secretory phenotype (SASP) induced by doxorubicin in mice. These findings suggest that small molecule USP7 inhibitors are novel senolytics that can be exploited to reduce chemotherapy-induced toxicities and treat age-related diseases.
Developing a camera-based 3D momentum imaging system capable of 1 Mhits/s
A camera-based three-dimensional (3D) imaging system with a superb time-of-flight (TOF) resolution and multi-hit capability was recently developed for electron/ion imaging [Lee et al. J. Chem. Phys. 141, 221101 (2014)]. In this work, we report further improvement of the event rate of the system by adopting an event-driven camera, Tpx3Cam, for detecting the 2D positions of electrons, while a high-speed digitizer provides highly accurate (~30 ps) TOF information for each event at a rate approaching 1 Mhits/sec.
Artificial Neural Networks for Determining Magnetospheric Conditions
This chapter presents a neural-network-based technique that allows for the reconstruction of the global, time-varying distribution of some physical quantity Q, that has been sparsely sampled at various locations within the magnetosphere, and at different times. We begin with a general introduction to the problem of prediction and specification, and why it is important and difficult to achieve with existing methods. We then provide a basic introduction to neural networks, and describe our technique using the specific example of reconstructing the electron plasma density in the Earth's inner magnetosphere on the equatorial plane. We then show more advanced uses of the technique, including 3D reconstruction of the plasma density, specification of chorus and hiss waves, and energetic particle fluxes. We summarize and conclude with a general discussion of how machine learning techniques might be used to advance the state-of-the-art in space weather prediction, and insight discovery.
An Engergetic Electron Flux Dropout Due to Magnetopause Shadowing on 1 June 2013
We examine the mechanisms responsible for the dropout of energetic electron flux during 31 May to 1 June 2013 using Van Allen Probe (Radiation Belt Storm Probes (RBSP)) electron flux data and simulations with the Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model. During the storm main phase, L-shells at RBSP locations are greater than ~8, which are connected to open drift shells. Consequently, diminished electron fluxes were observed over a wide range of energies. The combination of drift shell splitting, magnetopause shadowing, and drift loss all results in butterfly electron pitch angle distributions (PADs) at the nightside. During storm sudden commencement, RBSP observations display electron butterfly PADs over a wide range of energies. However, it is difficult to determine whether there are butterfly PADs during the storm main phase since the maximum observable equatorial pitch angle from RBSP is not larger than ~40° during this period. To investigate the causes of the dropout, the CIMI model is used as a global 4-D kinetic inner magnetosphere model. The CIMI model reproduces the dropout with very similar timing and flux levels and PADs along the RBSP trajectory for 593 keV. Furthermore, the CIMI simulation shows butterfly PADs for 593 keV during the storm main phase. Based on comparison of observations and simulations, we suggest that the dropout during this event mainly results from magnetopause shadowing.