Traditional Chinese medicine (TCM) has been practiced for thousands of years and at the present time is widely accepted as an alternative treatment for cancer. In this review, we sought to summarize the molecular and cellular mechanisms underlying the chemopreventive and therapeutic activity of TCM, especially that of the Chinese herbal medicine‐derived phytochemicals curcumin, resveratrol, and berberine. Numerous genes have been reported to be involved when using TCM treatments and so we have selectively highlighted the role of a number of oncogene and tumor suppressor genes in TCM therapy. In addition, the impact of TCM treatment on DNA methylation, histone modification, and the regulation of noncoding RNAs is discussed. Furthermore, we have highlighted studies of TCM therapy that modulate the tumor microenvironment and eliminate cancer stem cells. The information compiled in this review will serve as a solid foundation to formulate hypotheses for future studies on TCM‐based cancer therapy.
Memristive logic device is a promising unit for beyond von Neumann computing systems and 2D materials are widely used because of their controllable interfacial properties. Most of these 2D memristive devices, however, are made from semiconducting chalcogenides which fail to gate the off‐state current. To this end, a crossbar device using 2D HfSe2 is fabricated, and then the top layers are oxidized into “high‐k” dielectric HfSexOy via oxygen plasma treatment, so that the cell resistance can be remarkably increased. This two‐terminal Ti/HfSexOy/HfSe2/Au device exhibits excellent forming‐free resistive switching performance with high switching speed (<50 ns), low operation voltage (<3 V), large switching window (103), and good data retention. Most importantly, the operation current and the power consumption reach 100 pA and 0.1 fJ to 0.1 pJ, much lower than other HfO based memristors. A functionally complete low‐power Boolean logic is experimentally demonstrated using the memristive device, allowing it in the application of energy‐efficient in‐memory computing.
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