The capacity of targeted anticancer agents to exert immunomodulatory effects provides a strong rationale to develop novel agents suitable for combinatorial regimens with immunotherapy to improve clinical outcomes. In this study, we developed a dual-targeting PI3K and HDAC inhibitor BEBT-908 that potently inhibits tumor cell growth and potentiates anti-PD1 therapy in mice by inducing immunogenic ferroptosis in cancer cells. Treatment with BEBT-908 promoted ferroptotic cell death of cancer cells by hyperacetylating p53 and facilitating the expression of ferroptotic signaling. Furthermore, BEBT-908 promoted a proinflammatory tumor microenvironment that activated host antitumor immune responses and potentiated immune checkpoint blockade therapy. Mechanistically, BEBT-908–induced ferroptosis led to upregulation of MHC class I and activation of endogenous IFNγ signaling in cancer cells via the STAT1 signaling pathway. The dual PI3K/HDAC inhibitor BEBT-908 is a promising targeted therapeutic agent against multiple cancer types that promotes immunogenic ferroptosis and enhances the efficacy of immunotherapy. Significance: The dual PI3K/HDAC inhibitor BEBT-908 elicits potent antitumor responses, effectively inducing immunogenic ferroptosis of tumor cells and potentiating cancer immunotherapy.

Acute lung injury (ALI) and its more severe form acute respiratory distress syndrome (ARDS) are life-threatening conditions with high morbility and mortality, underscoring the urgent need for novel treatments. Leaves of the medicinal herb Microcos paniculata have been traditionally used for treating upper airway infections, by virtue of its content of flavonoids such as apigenin C-glycosides (ACGs). C-glycosides have been shown to exert strong anti-inflammatory properties, although their mechanism of action remains unknown. Herein, hypothesizing that ACGs from M. paniculata inhibit progression of ALI, we used the experimental model of lipopolysaccharide (LPS)-induced ALI in BALB/c mice to evaluate the therapeutic potential of purified ACGs. Our results showed that M. paniculata ACGs inhibited lung inflammation in animals undergoing ALI. The protective effects of ACGs were assessed by determination of cytokine levels and in situ analysis of lung inflammation. ACGs reduced the pulmonary edema and microvascular permeability, demonstrating a dose-dependent down-regulation of LPS-induced TNF-α, IL-6 and IL-1β expression in lung tissue and bronchoalveolar lavage fluid, along with reduced apoptosis. Moreover, metabolic profiling of mice serum and subsequent Ingenuity Pathway Analysis suggested that ACGs activated protective protein networks and pathways involving inflammatory regulators and apoptosis-related factors, such as JNK, ERK1/2 and caspase-3/7, suggesting that ACGs-dependent effects were related to MAPKs and mitochondrial apoptosis pathways. These results were further supported by evaluation of protein expression, showing that ACGs blocked LPS-activated phosphorylation of p38, ERK1/2 and JNK on the MAPKs signaling, and significantly upregulated the expression of Bcl-2 whilst down-regulated Bax and cleaved caspase-3. Remarkably, ACGs inhibited the LPS-dependent TLR4 and TRPC6 upregulation observed during ALI. Our study shows for the first time that ACGs inhibit acute inflammation and apoptosis by suppressing activation of TLR4/TRPC6 signaling pathway in a murine model of ALI. Our findings provide new evidence for better understanding the anti-inflammatory effects of ACGs. In this regard, ACGs could be exploited in the development of novel therapeutics for ALI and ARDS.

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Extreme public health interventions play a critical role in mitigating the local and global prevalence and pandemic potential. Here, we use population size for pathogen transmission to measure the intensity of public health interventions, which is a key characteristic variable for nowcasting and forecasting of COVID-19. By formulating a hidden Markov dynamic system and using nonlinear filtering theory, we have developed a stochastic epidemic dynamic model under public health interventions. The model parameters and states are estimated in time from internationally available public data by combining an unscented filter and an interacting multiple model filter. Moreover, we consider the computability of the population size and provide its selection criterion. With applications to COVID-19, we estimate the mean of the effective reproductive number of China and the rest of the globe except China (GEC) to be 2.4626 (95% CI: 2.4142–2.5111) and 3.0979 (95% CI: 3.0968–3.0990), respectively. The prediction results show the effectiveness of the stochastic epidemic dynamic model with nonlinear filtering. The hidden Markov dynamic system with nonlinear filtering can be used to make analysis, nowcasting and forecasting for other contagious diseases in the future since it helps to understand the mechanism of disease transmission and to estimate the population size for pathogen transmission and the number of hidden infections, which is a valid tool for decision-making by policy makers for epidemic control.

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This paper investigates a box set-membership filter for nonlinear dynamic systems and on-line usage. To the best of our knowledge, although ellipsoid set-membership filter has more freedom degree to optimize a bounding estimation, it is computationally intractable to obtain an optimal prediction and update, and the approximation loss is uncertain in different scenarios. In this paper, we equivalently transform the prediction and update of the box set-membership filter to linear programing problems without loss of performance, respectively. Moreover, for a typical nonlinear dynamic system in target tracking, the remainder bound of the nonlinear function can be obtained analytically on-line. However, the ellipsoid bounding problem of the remainder usually needs to be relaxed to solve a semi-definite programming problem. Thus, the computational complexity of the optimal box set-membership filter is much less than that of the ellipsoid set-membership filter based on the semi-definite programming. Finally, a numerical example in target tracking demonstrates the effectiveness of the box set-membership filter. The proposed box set-membership filter can obtain a better trade-off between the filter accuracy and the computational complexity. INDEX TERMS Nonlinear dynamic systems, target tracking, box set-membership filter, linear programing problem.