Curcumin derivative C212 inhibits Hsp90 and eliminates both growing and quiescent leukemia cells in deep dormancy.

BACKGROUND: Relapsed leukemia following initial therapeutic response and remission is difficult to treat and causes high patient mortality. Leukemia relapse is due to residual quiescent leukemia cells that escape conventional therapies and later reemerge. Eliminating not only growing but quiescent leukemia cells is critical to effectively treating leukemia and preventing its recurrence. Such dual targeting therapeutic agents, however, are lacking in the clinic. To start tackling this problem, encouraged by the promising anticancer effects of a set of curcumin derivatives in our earlier studies, we examined in this work the effects of a 4-arylmethyl curcumin derivative (C212) in eliminating both growing and quiescent leukemia cells. METHODS: We analyzed the effects of C212 on the growth and viability of growing and quiescent leukemia cells using MTS, apoptosis, cell cycle and cell tracking assays. The effects of C212 on the quiescence depth of leukemia cells were measured using EdU incorporation assay upon growth stimulation. The mechanisms of C212-induced apoptosis and deep dormancy, particularly associated with its inhibition of Hsp90 activity, were studied using molecular docking, protein aggregation assay, and Western blot of client proteins. RESULTS: C212, on the one hand, inhibits growing leukemia cells at a higher efficacy than curcumin by inducing apoptosis and G2/M accumulation; it, on the other hand, eliminates quiescent leukemia cells that are resistant to conventional treatments. Furthermore, C212 drives leukemia cells into and kills them at deep quiescence. Lastly, we show that C212 induces apoptosis and drives cells into deep dormancy at least partially by binding to and inhibiting Hsp90, leading to client protein degradation and protein aggregation. CONCLUSION: C212 effectively eliminates both growing and quiescent leukemia cells by inhibiting Hsp90. The property of C212 to kill quiescent leukemia cells in deep dormancy avoids the risk associated with awaking therapy-resistant subpopulation of quiescent leukemia cells during treatments, which may lead to the development of novel therapies against leukemia relapse. Video abstract.

The Analysis of the Urban Sprawl Measurement System of the Yangtze River Economic Belt, Based on Deep Learning and Neural Network Algorithm.

In the context of rapid urbanization, the spread of cities in the Yangtze River Economic Belt is intensifying, which has an impact on the green and sustainable development of these cities. It is necessary to establish an accurate urban sprawl measurement system. First, the regulation theory of urban sprawl is explained. According to the actual development situation of cities in the Yangtze River Economic Belt, smart growth theory is selected as the basic regulation method of urban sprawl. Second, the back propagation neural network (BPNN) algorithm under deep supervised learning is applied to construct a smart evaluation model of land use growth. Finally, based on the actual development of cities in the Yangtze River Economic Belt, the quantitative growth measurement method is selected to construct a measurement system of urban sprawl in the Yangtze River Economic Belt, and the empirical analysis is carried out. The training results show that the proposed BPNN smart growth evaluation model, based on deep supervised learning, has good evaluation accuracy, and the error is within the preset range. The analysis of the quantitative growth-based measurement system in the increase of urban construction land shows that the increase in urban construction land area of the Yangtze River Economic Belt from 2014 to 2019 was 78.67 km2. Meanwhile, the increases in urban construction land area in different years are different. The empirical results show that the population composition of the Yangtze River Economic Belt and the urban construction area between 2005 and 2019 show a trend of increasing annually; at the same time, urban sprawl development shows a staged characteristic. It is of great significance to apply deep learning fusion neural network algorithm in the construction of the urban sprawl measurement system, which provides a quantitative basis for the in-depth analysis and discussion of urban sprawl.

[A Digital System for Bioimpedance and Electrical Impedance Tomography Measurement System].

A digital system for bioimpedance and electrical impedance tomography (EIT) measurement controlled by an ATmega16 microcontroller was constructed in our laboratory. There are eight digital electrodes using AD5933 to measure the impedance of the targets, and the data is transmitted to the computer wirelessly through nRF24L01. The structure of the system, circuit design, system testing, vitro measurements of animals' tissues and electrical impedance tomography are introduced specifically in this paper. The experimental results showed that the system relative error was 0.42%, and the signal noise ratio was 76.3 dB. The system not only can be used to measure the impedance by any two electrodes within the frequency of 1-100 kHz in a sweep scanning, but also can reconstruct the images of EIT. The animal experiments showed that the data was valid and plots were fitting with Cole-Cole theory. The testing verified the feasibility and effectiveness of the system. The images reconstructed of a salt-water tank are satisfactory and match with the actual distribution of the tank. The system improves the effectiveness of the front-end measuring signal and the stability of the system greatly.