Objective: Neural mass model (NMM) has been widely used to investigate the neurophysiological mechanisms of anesthestic drugs induced general anesthesia (GA). However, whether the parameters of NMM could track the effects of anesthesia still unknown.
Approach: We proposed using the cortical NMM (CNMM) to infer the potential neurophysiological mechanism of three different anesthetic drugs (i.e., propofol, sevoflurane, and (S)-ketamine) induced GA, and we employed unscented Kalman filter (UKF) to track any change in raw electroencephalography (rEEG) in frontal area during GA. We did this by estimating the parameters of population gain [i.e., excitatory/inhibitory postsynaptic potential (EPSP/IPSP, i.e., parameter A/B in CNMM) and the time constant rate of EPSP/IPSP (i.e., parameter a/b in CNMM). We compared the rEEG and simulated EEG (sEEG) from the perspective of spectrum, phase-amplitude coupling (PAC), and permutation entropy (PE). 
Main results: Under three estimated parameters (i.e., A, B, and a for propofol/sevoflurane or b for (S)-ketamine), the rEEG and sEEG had similar waveforms, time-frequency spectra, and PAC patterns during GA for the three drugs. The PE curves derived from rEEG and sEEG had high correlation coefficients (propofol: 0.97±0.03, sevoflurane: 0.96±0.03, (S)-ketamine: 0.98±0.02) and coefficients of determination (R2) (propofol: 0.86±0.03, sevoflurane: 0.68±0.30, (S)-ketamine: 0.70±0.18). Except for parameter A for sevoflurane, the estimated parameters for each drug in CNMM can differentiate wakefulness and non-wakefulness states. Compared with the simulation of three estimated parameters, the UKF-based CNMM had lower tracking accuracy under the simulation of four estimated parameters (i.e., A, B, a, and b) for three drugs.
Significance: The results demonstrate that a combination of CNMM and UKF could track the neural activities during GA. The EPSP/IPSP and their time constant rate can interpert the anesthetic drug’s effect on the brain, and can be used as a new index for depth of anesthesia monitoring.

The survival rate of lung cancer patients remains low largely due to chemotherapy resistance during treatment, and cancer stem cells (CSCs) may hold the key to targeting this resistance. Cisplatin is a chemotherapy drug commonly used in cancer treatment, yet the mechanisms of intrinsic cisplatin resistance have not yet been determined because lung CSCs are hard to identify. In this paper, we proposed a mechanism relating to the function of ursolic acid (UA), a new drug, in reversing the cisplatin resistance of lung cancer cells regulated by CSCs. Human lung cancer cell line A549 was selected as the model cell and treated to become a cisplatin-resistant lung cancer cell line (A549-CisR), which was less sensitive to cisplatin and showed an enhanced capability of tumor sphere formation. Furthermore, in the A549-CisR cell line expression, levels of pluripotent stem cell transcription factors Oct-4, Sox-2, and c-Myc were increased, and activation of the Jak2/Stat3 signaling pathway was promoted. When UA was applied to the cisplatin-resistant cells, levels of the pluripotent stem cell transcription factors were restrained by the inhibition of the Jak2/Stat3 signaling pathway, which reduced the enrichment of tumor stem cells, and in turn, reversed cisplatin resistance in lung cancer cells. Hence, as a potential antitumor drug, UA may be able to inhibit the enrichment of the lung CSC population by inhibiting the activation of the Jak2-Stat3 pathway and preventing the resistance of lung cancer cells to cisplatin.

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