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To minimize grain fleet operational costs, we employ a route optimization approach that considers bunker costs. A mixed-integer programming model is created, factoring in the unique features of bulk grain shipping and varying oil prices at bunker ports. The goal is to optimize the fleet’s transportation route, with decision variables encompassing bunker port selection, bunker volume, and ship navigation path. Using a dry bulk cargo company’s grain transport fleet as a case study, the Gurobi solver validates the model’s effectiveness. Results reveal that, excluding the loading port, the grain fleet can select low oil price ports along the route for bunkering. Optimal cost reduction is achieved by choosing multiple bunker ports and increasing bunker quantity. Additionally, the model harmonizes port charges with bunker costs, refining the grain fleet’s transportation route and effectively managing operational expenses.

Reconstructing the topology of gene regulatory network from gene expression data has been extensively studied. With the abundance functional transcriptomic data available, it is now feasible to systematically decipher regulatory interaction dynamics in a logic form such as a Boolean network (BN) framework, which qualitatively indicates how multiple regulators aggregated to affect a common target gene. However, inferring both the network topology and gene interaction dynamics simultaneously is still a challenging problem since gene expression data are typically noisy and data discretization is prone to information loss. We propose a new method for BN inference from time-series transcriptional profiles, called LogicGep. LogicGep formulates the identification of Boolean functions as a symbolic regression problem that learns the Boolean function expression and solve it efficiently through multi-objective optimization using an improved gene expression programming algorithm. To avoid overly emphasizing dynamic characteristics at the expense of topology structure ones, as traditional methods often do, a set of promising Boolean formulas for each target gene is evolved firstly, and a feed-forward neural network trained with continuous expression data is subsequently employed to pick out the final solution. We validated the efficacy of LogicGep using multiple datasets including both synthetic and real-world experimental data. The results elucidate that LogicGep adeptly infers accurate BN models, outperforming other representative BN inference algorithms in both network topology reconstruction and the identification of Boolean functions. Moreover, the execution of LogicGep is hundreds of times faster than other methods, especially in the case of large network inference. [ABSTRACT FROM AUTHOR]

Summary: The multiple model approach provides a powerful tool for identification and control of nonlinear systems. Among different multiple model structures, the piecewise affine (PWA) models have drawn most of the attention in the past two decades. However, there are two major issues for the PWA model‐based identification and control: the curse of dimensionality and the computational complexity. To resolve these two issues, we propose a novel multiple model approach in this paper. Different from PWA models in which all dimensions of the regressor space are engaged in the partitioning, the key idea of the proposed multiple model architecture is to partition only the range of the control input u(k) at time k (the instant of interest in the control problem) into several intervals and identify a local model that is linear in u(k) within each interval. On the basis of Taylor's theorem, a theoretical upper bound for the approximation error of the model structure can also be obtained. With the proposed multiple model architecture, a switching control algorithm is derived to control nonlinear systems on the basis of the weighted one‐step‐ahead predictive control method and constrained optimization techniques. In addition, the upper bound for the tracking error using this switching control strategy is also analyzed rigorously under certain assumptions. Finally, both simulation studies and experimental results demonstrate the effectiveness of the proposed multiple model architecture and switching control algorithm. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

There is an urgent need for novel strategies to accurately and reliably detect pathogenic bacteria to address the global epidemic of antibiotic resistance. This study proposes an innovative approach combining dual aptamer-based target recognition and proximity ligation assay (PLA) triggered DNAzyme recycling cleavage. This method allows for the precise identification and reliable detection of methicillin-resistant Staphylococcus aureus (MRSA). The fluorescence probe labeled with a fluorophore is modified on gold nanoparticles (AuNPs), resulting in the quenching of the fluorescent signal by the AuNPs. The interaction between MRSA and two aptamers leads to forming a Mg 2+ -dependent DNAzyme. The DNAzyme cleaves the fluorescence probe, causing the fluorescent fragment to detach from the surface of the AuNPs, in which the quenched fluorescence signal in the fluorescence probe reappears. The DNAzyme-assisted cleavage and rebinding process generates a processive strolling along the surface track of AuNPs. Consequently, the fluorescence intensity experiences a substantial recovery. A strong linear correlation is observed between the fluorescence intensity and MRSA concentration within 50 cfu/mL to 10 6  cfu/mL. We believe that implementing the novel integrated strategy will broaden the range of bacterial detection methods in the battlefield environment and stimulate the creation of potential new drugs in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The poor prognosis of immunotherapy in patients with colorectal cancer (CRC) necessitates a comprehensive understanding of the immunosuppressive mechanisms within tumor microenvironment (TME). Undoubtedly, the anti-tumor immune cells play an indispensable role in immune tolerance. Therefore, it is imperative to investigate novel immune-related factors that have the capacity to enhance anti-tumor immunity. Here, we employed bioinformatic analysis using R and Cytoscape to identify the hub gene chemokine (C-X-C motif) ligand 8 (CXCL8), which is overexpressed in CRC, in the malignant progression of CRC. However, its specific role of CXCL8 in CRC immunity remains to be elucidated. For this purpose, we evaluated how tumor-derived CXCL8 promotes M2 macrophage infiltration by in vivo and in vitro, which can be triggered by IL-1β within TME. Mechanistically, CXCL8-induced polarization of M2 macrophages depends on the activation of the STAT3 signaling. Finally, immunohistochemistry and multiplexed immunohistochemistry analysis identified that CXCL8 not only enhances PD-L1 + M2 macrophage infiltration but also attenuates the recruitment of PD-1 + CD8 + T cells in murine CRC models. Together, these findings emphasize the critical role for CXCL8 in promoting M2 macrophage polarization and inhibiting CD8 + T cell infiltration, thereby links CXCL8 to the emergency of immunosuppressive microenvironment facilitating tumor evasion. Overall, these findings may provide novel strategy for CRC immunotherapy., (© 2023 The Authors. The FASEB Journal published by Wiley Periodicals LLC on behalf of Federation of American Societies for Experimental Biology.)

Objective To investigate the killing effect and molecular mechanism of aberrant expression of calnexin (CNX) in the colorectal cancer (CRC) on the CD8 + T immune cells. Methods Immunohistochemistry was used to detect CNX protein level in 102 pairs of CRC cancer and adjacent non-cancerous tissues. Western blotting was employed to examine the protein expression of MHC I in the HCT-15 cells overexpressed with CNX or in the SW480 cells whose CNX expressions were knockdown by siRNA. Murine CD8 + T cells isolated from the spleen were cocultured with CT-26 murine CRC cells infected with lentivirus-mediated CNX overexpression. The killing effect of CD8 + T cells on CT-26 cells was determined by cytotoxicity kit. The secretion of interferon γ (IFN-γ) and tumor necrosis factor α (TNF-α) in the culture medium were examined by ELISA. Results The protein level of CNX in colorectal cancer tissues were significantly lower than that in non-cancerous tissues. CNX overexpressed in HCT-15 cells was upregulated and CNX knockdown in SW480 cells downregulated the MHC I expression in these cells. Furthermore, the overexpression of CNX could not only enhance the killing effect of CD8 + T cells on CT-26 cells, but also promote the secretion of IFN-γ and TNF-α from these cells. Conclusion CNX can enhance the killing potential of CD8 + T cells on tumor cells through upregulating the MHC I expression in colorectal cancer cells.

Nonresponse, or acquired resistance to immune checkpoint inhibitors in colorectal cancer (CRC) highlight the importance of finding potential tolerance mechanisms. Low expression of major histocompatibility complex, class I (MHC-I) on the cell surface of the tumor is one of the main mechanisms of tumor escape from T-cell recognition and destruction. In this study, we demonstrated that a high level of calnexin (CANX) in the tumors is positively correlated with the overall survival in colorectal cancer patients. CANX is a chaperone protein involved in the folding and assembly of MHC-I molecules. Using miRNA target prediction databases and luciferase assays, we identified miR-148a-3p as a potential regulator of CANX. Inhibition of miR-148a-3p restores surface levels of MHC-I and significantly enhanced the effects of CD8 + T-cell-mediated immune attack in vitro and in vivo by promoting CANX expression. These results reveal that miR-148a-3p can function as a tumor promotor in CRC by targeting the CANX/MHC-I axis, which provides a rationale for immunotherapy through targeting the miR-148a-3p/CANX/MHC-I pathway in patients with CRC., (© 2021 Federation of American Societies for Experimental Biology.)