Analyzing large-scale evolving graphs are crucial for understanding the dynamic and evolutionary nature of social networks. Most existing works focus on discovering repeated and consistent temporal patterns, however, such patterns cannot fully explain the complexity observed in dynamic networks. For example, in recommendation scenarios, users sometimes purchase products on a whim during a window shopping.Thus, in this paper, we design and implement a novel framework called BurstGraph which can capture both recurrent and consistent patterns, and especially unexpected bursty network changes. The performance of the proposed algorithm is demonstrated on both a simulated dataset and a world-leading E-Commerce company dataset, showing that they are able to discriminate recurrent events from extremely bursty events in terms of action propensity.
Ferroptosis, as a promising therapeutic strategy for cancers, has aroused great interest. Quantifying the quick dynamic changes in key parameters during the early course of ferroptosis can provide insights for understanding the underlying mechanisms of ferroptosis and help the development of therapies targeting ferroptosis. However, in situ and quantitatively monitoring the quick responses of living cancer cells to ferroptosis at the single-cell level remains technically challenging. In this work, we selected HuH7 cells (hepatocellular carcinoma (HCC) cells) as a cell model and Erastin as a typical ferroptosis inducer. We utilized scanning electrochemical microscopy (SECM) to quantitatively and in situ monitor the early course of ferroptosis in HuH7 cells by characterizing the three key parameters of cell ferroptosis (i.e., cell membrane permeability, respiratory activity, and the redox state). The SECM results show that the membrane permeability of ferroptotic HuH7 cells continuously increased from 0 to 8.1 × 10 −5 m s −1 , the cellular oxygen consumption was continuously reduced by half, and H 2 O 2 released from the cells exhibited periodic bursts during the early course of ferroptosis, indicating the gradually destroyed cell membrane structure and intensified oxidative stress. Our work realizes, for the first time, the in situ and quantitative monitoring of the cell membrane permeability, respiratory activity, and H 2 O 2 level of the early ferroptosis process of a single living cancer cell with SECM, which can contribute to the understanding of the physiological process and underlying mechanisms of ferroptosis.
In vitro cardiac tissue model holds great potential as
a powerful
platform for drug screening. Respiratory activity, contraction frequency,
and extracellular H2O2 levels are the three
key parameters for determining the physiological functions of cardiac
tissues, which are technically challenging to be monitored in an in
situ and quantitative manner. Herein, we constructed an in vitro cardiac
tissue model on polyacrylamide gels and applied a pulsatile electrical
field to promote the maturation of the cardiac tissue. Then, we built
a scanning electrochemical microscopy (SECM) platform with programmable
pulse potentials to in situ characterize the dynamic changes in the
respiratory activity, contraction frequency, and extracellular H2O2 level of cardiac tissues under both normal physiological
and drug (isoproterenol and propranolol) treatment conditions using
oxygen, ferrocenecarboxylic acid (FcCOOH), and H2O2 as the corresponding redox mediators. The SECM results showed
that isoproterenol treatment induced enhanced oxygen consumption,
accelerated contractile frequency, and increased released H2O2 level, while propranolol treatment induced dynamically
decreased oxygen consumption and contractile frequency and no obvious
change in H2O2 levels, suggesting the effects
of activation and inhibition of β-adrenoceptor on the metabolic
and electrophysiological activities of cardiac tissues. Our work realizes
the in situ and quantitative monitoring of respiratory activity, contraction
frequency, and secreted H2O2 level of living
cardiac tissues using SECM for the first time. The programmable SECM
methodology can also be used to real-time and quantitatively monitor
electrochemical and electrophysiological parameters of cardiac tissues
for future drug screening studies.
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