Inhibition of autophagy has been widely viewed as a promising
strategy
for anticancer therapy. However, few effective and specific autophagy
inhibitors have been reported. Herein, we described the design, synthesis,
and biological characteristics of new analogues of strigolactones
(SLs), an emerging class of plant hormones, against colorectal cancers.
Among them, an enantiopure analogue 6 exerted potent
and selective cytotoxicity against colorectal cancer cells, but not
normal human colon mucosal epithelial cells, which were further confirmed
by the plate colony formation assay. Moreover, it significantly inhibited
tumor growth in an HCT116 xenograft mouse model with low toxicity.
Mechanistically, it is associated with selective induction of cell
apoptosis and cell cycle arrest. Remarkably, 6 acted
as a potent autophagy/mitophagy inhibitor by selectively increasing
the autophagic flux while blocking the autophagosome–lysosome
fusion in HCT116 cells. This study features stereo-defined SLs as
novel autophagy inhibitors with high cancer cell specificity, which
paves a new path for anticolorectal cancer therapy.
Traditionally, individual intensities to perform games are always assumed to be fixed in networks (e.g. to depend on the number of their neighbors). However, to increase their own fitness or payoffs, individuals may adjust their intensities in reaction to external environment changes in real scenarios. With this motivation, we have studied this adjustment by considering the average payoff of individual neighbors to be the network environment in a spatial prisoner’s dilemma game. An individual will unilaterally increase (decrease) its intensity to perform games between itself and its neighbors when its payoff is greater than or equal to (lower than) the average payoff of its neighbors. Compared with the normal situation, we find that individual cooperation is significantly facilitated either on the cooperator fraction or the effective cooperation fraction when the environment-induced intensity adjustment is considered, and the value of intensity adjustment per time has a positive influence on the maintenance of cooperation. Evolution snapshots and a formulated typical schematic are used to explain the results. We find that cooperation behaviors are enhanced because of the existence of defectors with lower intensities who are near the boundaries between cooperator and defector clusters. Finally, the promotion is also validated in random networks. We hope that our results may shed light on a greater understanding of the role of individual adaptive behaviors in reaction to network environments in the maintenance of cooperation in societies.
In the era of electrification and artificial intelligence, direct current motors are widely utilized with numerous innovative adaptive and learning methods. Traditional methods utilize model-based algebraic techniques with system identification, such as recursive least squares, extended least squares, and autoregressive moving averages. The new method known as deterministic artificial intelligence employs physical-based process dynamics to achieve target trajectory tracking. There are two common autonomous trajectory-generation algorithms: sinusoidal function- and Pontryagin-based generation algorithms. The Pontryagin-based optimal trajectory with deterministic artificial intelligence for DC motors is proposed and its performance compared for the first time in this paper. This paper aims to simulate model following and deterministic artificial intelligence methods using the sinusoidal and Pontryagin methods and to compare the differences in their performance when following the challenging step function slew maneuver.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.