Abstract ：

Achieving strong interaction with the targeted composition and constructing abundant transport channels is crucial to obtain the pervaporation (PV) membrane with high selectivity and flux. Here, three ionic liquids (ILs) were screened out based on their relative selectivity and capacity targeting for bioethanol dehydration by COSMO-RS. The interaction energies analysis between ILs, EtOH, and H2O suggests that the ILs can form strong hydrogen bonds with water and disrupt the hydrogen bond in the EtOH-H2O azeotropic mixture, which is beneficial for improving the selectivity. Furthermore, driven by the multiple hydrogen bonds, electrostatic interactions, and van der Waals forces, ILs could self-assemble with polyvinyl alcohol (PVA) to fabricate the PV membrane with well-ordered micelle nanostructure, as its structure was revealed by MD simulations. The formation of the ILs-PVA micelle dramatically influenced membrane surface morphology, roughness, and water contact angle, providing an extra transport channel for the membrane. The optimal membrane (at the cmc point) exhibited a superior ethanol dehydration separation factor of 1627, along with a flux of 684 g/m2h at 50 degrees C. It can be expected that this novel self-assembled ILs-PVA micelle nanostructure strategy will find promising applications in other azeotropic mixture separation processes, like ethanol-ethyl acetate, water-butanol, etc.

Keyword ：

Bioethanol dehydration Ionic liquids Pervaporation membrane Micelle

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Abstract ：

Alterations in cellular metabolism are important hallmarks of glioblastoma(GBM). Metabolic reprogramming is a critical feature as it meets the higher nutritional demand of tumor cells, including proliferation, growth, and survival. Many genes, proteins, and metabolites associated with GBM metabolism reprogramming have been found to be aberrantly expressed, which may provide potential targets for cancer treatment. Therefore, it is becoming increasingly important to explore the role of internal and external factors in metabolic regulation in order to identify more precise therapeutic targets and diagnostic markers for GBM. In this review, we define the metabolic characteristics of GBM, investigate metabolic specificities such as targetable vulnerabilities and therapeutic resistance, as well as present current efforts to target GBM metabolism to improve the standard of care.

Keyword ：

Signaling pathway Glioblastoma Therapy Metabolism

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Owing to the increasing number of cybersecurity threats targeting industrial control systems (ICSs), intrusion response systems (IRSs) have become essential. However, the current IRSs exhibit several limitations, such as neglecting physical domain security policies and relying significantly on expert input. While deep reinforcement learning (DRL) methods yield superior outcomes, they suffer from low interpretability and unreliability. This study introduces an interpretable cross-layer intrusion response system (ICL-IRS), which is a decision-tree-based IRS. It offers a robust understanding of cyberattacks and industrial control logic specific to ICSs. ICL-IRS employs a DRL model, tailored to the characteristics of physical process control, to refine policies. It then scrutinizes the optimized intrusion response policy and generates decision trees. Our experimental results reveal a 21% enhancement in the success rate of the proposed ICL-IRS over competing methods. The effectiveness of ICL-IRS was further validated through a case study on a simulated process-control system.

Keyword ：

Cybersecurity intrusion response system (IRS) deep reinforcement learning (DRL) imitation learning industrial control systems (ICSs)

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Long-chain fatty acyl-Coa ligase 4 (ACSL4) is an important enzyme that converts fatty acids to fatty acyl-Coa esters, there is increasing evidence for its role in carcinogenesis. However, the precise role of ACLS4 in hepatocellular carcinoma (HCC) is not clearly understood. In the present study, we provide evidence that ACSL4 expression was specifically elevated in HCC and is associated with poor clinical outcomes. ACSL4 significantly promotes the growth and metastasis of HCC both in vitro and in vivo . RNA sequencing and functional experiments showed that the effect of ACSL4 on HCC development was heavily dependent on PAK2. ACSL4 expression is well correlated with PAK2 in HCC, and ACSL4 even transcriptionally increased PAK2 gene expression mediated by Sp1. In addition, emodin, a naturally occurring anthraquinone derivative, inhibited HCC cell growth and tumor progression by targeting ACSL4. In summary, ACSL4 plays a novel oncogene in HCC development by regulating PAK2 transcription. Targeting ACSL4 could be useful in drug development and therapy for HCC.

Keyword ：

Emodin Sp1 PAK2 Hepatocellular carcinoma ACSL4

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Activatable near-infrared (NIR) fluorogenic probes offer a potent tool for real-time, in situ detection of hepatic biomarkers, significantly advancing the precision in diagnosing inflammatory liver disease (ILD). However, the limited distribution of small molecule fluorogenic probes in the liver and their rapid clearance impair the accuracy of fluorescence imaging and in ILD diagnosis. In this study, an effective utilization of ionizable lipid nanoparticles (iLNPs) is presented as liver-targeted carriers for efficient delivery of fluorogenic probes, aiming to overcome biodistribution barriers and achieve accurate detection of hepatic biomarkers. Based on this strategy, a liver-targeted NIR fluorogenic nanoprobe hCy-H2O2@iLNP is prepared using hCy-H2O2 as a small molecule reporter for visualizing the over-produced hydrogen peroxide (H2O2) in situ of liver. Notably, iLNPs not only significantly enhance probe accumulation in the liver, but also enable sequence activation of fluorescent nanoprobes. This response is achieved through primary liposome-dissociation release and secondary hCy-H2O2 response with pathological H2O2, enabling high-precision detection of oxidative stress in hepatocytes. These distinctive features facilitate accurate early diagnosis of acetaminophen (APAP)-induced inflammatory liver injury as well as lipopolysaccharide (LPS)-induced hepatitis. Therefore, the organ-targeted nanoprobe design strategy showcasts great potential for early and accurate diagnosis of lesions in situ in different organs. This paper describes an innovative utilization of ionizable lipid nanoparticles (iLNPs) as liver-targeted carriers to construction of sequence-activated fluorogenic nanoprobes, enabling high liver accumulation and precision imaging of inflammatory liver disease (ILD) in vivo. A fluorogenic nanoprobe hCy-H2O2@iLNP is prepared for in situ detection of hepatic hydrogen peroxide (H2O2), facilitating accurate diagnosis of acetaminophen and lipopolysaccharide-induced ILD at early stages. image

Keyword ：

ionizable lipid nanoparticles fluorogenic probe sequence-activated liver-targeting inflammatory liver disease

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Abstract ：

The solute carrier (SLC) family, with more than 400 membrane -bound proteins, facilitates the transport of a wide array of substrates such as nutrients, ions, metabolites, and drugs across biological membranes. Amino acid transporters (AATs) are membrane transport proteins that mediate transfer of amino acids into and out of cells or cellular organelles. AATs participate in many important physiological functions including nutrient supply, metabolic transformation, energy homeostasis, redox regulation, and neurological regulation. Several AATs have been found to significantly impact the progression of human malignancies, and dysregulation of AATs results in metabolic reprogramming affecting tumor growth and progression. However, current clinical therapies that directly target AATs have not been developed. The purpose of this review is to highlight the structural and functional diversity of AATs, the molecular mechanisms in human diseases such as tumors, kidney diseases, and emerging therapeutic strategies for targeting AATs.

Keyword ：

targeted therapy cancer therapy SLC transporter amino acid transporter

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Mobile ad hoc networks (MANETs), which correspond to a novel wireless technology, are widely used in Internet of Things (IoT) systems such as drones, wireless sensor networks, and military or disaster relief communication. From the perspective of communication and data collection, the success rate of collaborations between nodes in mobile ad hoc networks and reliability of data collection mainly depend on whether the nodes in the network operate normally, namely, according to the established network rules. However, mobile ad hoc networks are vulnerable to attacks targeting transmission channels and nodes owing to their dynamic evolution, openness, and distributed characteristics. Therefore, during the network operation, it is necessary to classify and detect the behavior and characteristics of each node. However, most existing research only analyzes and considers responses against a single or small number of attacks. To address these issues, this article first systematically analyzed and classified common active attacks in MANETs. Then, a node trust model was proposed based on the characteristics of various attacks; subsequently, a new secure routing protocol, namely, TC-AODV, was proposed. This protocol has minimal effect on the original communication dynamics and can effectively deal with Packet drop, wormhole, Session hijacking, and other main attacks in MANETs. The NS3 simulation results show that the proposed routing protocol attains good transmission performance, can effectively identify various attacks and bypass malicious nodes, and securely complete the communication process. © 2023 The Author(s)

Keyword ：

Internet of things Mobile ad hoc networks Mobile security Data acquisition Internet protocols Data communication systems Sensor nodes Disaster prevention Network security Routing protocols

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Abstract ：

Hybrid lattice structures have significant potential in engineering applications owing to their outstanding mechanical and thermal properties. In this paper, an innovative design strategy for hybrid lattice structures is proposed involving the integration of primitive surfaces with truss lattice configurations. This approach allows for the full exploitation of the mechanical and thermal properties inherent in each component, leading to the development of new hybrid lattice structures. Firstly, the quasi-static compression and fluid-solid coupling heat conduction analysis of the hybrid lattice structure is carried out by numerical simulation. Then the effects of surface wall thickness, and truss diameter on the mechanical and thermal properties of the lattice structure are discussed. Additionally, the mechanical performance of the array hybrid lattice structure is evaluated through quasi-static compression experiments. These experimental results are compared with those from the numerical simulations, validating the accuracy of the simulation model. Finally, a multi-objective optimization model targeting specific elastic modulus and heat dissipation performance (indicated by Nusselt number) is established, in response to the demand of aviation and aerospace industries for lightweight, load-bearing, and heat- dissipating multi-functional integrated lattice design. The non-dominated sorting genetic algorithm is utilized to solve the optimal model, and the distribution of feasible solutions and Pareto front are obtained. The results show that the interpenetrating hybrid lattice structure has a greater improvement in mechanical and thermal properties than the primitive surfaces. This research holds significant implications for the design of multi- performance hybrid lattice structures.

Keyword ：

Thermal property Mechanical property Hybrid lattice structure Triply periodic minimal surfaces Multi-objective optimization

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Abstract ：

Corona Virus Disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARSCoV-2), poses a serious threat to human health and life safety. How to effectively prevent and treat COVID-19 is crucial. In this study, we used the inhibitors of nonstructural protein Nsp14 of SARS-CoV-2 to perform the quantitative structure activity relationship (QSAR) modelling for the first time. Based on different dataset division strategies, we selected partial least square (PLS) and multiple linear regression (MLR) methods to develop easily interpretable and reproducible QSAR models with 2D molecular descriptors. All models complied with the strict QSAR validation principles of OECD and internationally recognized validation metrics. The best model contained two molecular descriptors with the following statistical parameters: R2 = 0.7796, Q2LOO= 0.7373, R2test = 0.8539 and CCCtest = 0.9073. Obviously, the model exhibited good prediction performance and can be used for quickly predicting the inhibitory activity of unknown compounds against Nsp14. Mechanistic interpretation identified the detailed relationship between molecular structure information and inhibitory activity. The best QSAR model was used to predict the inhibitory activity of 263 true external compounds without experimental values against Nsp14, and the prediction reliability was analyzed and discussed. Molecular docking and ADMET analyses were conducted for compounds with higher similarity to the modelling compounds. Finally, two compounds were identified as potential candidate drugs of targeting Nsp14. The current work lays a solid theoretical foundation for the discovery of inhibitors targeting Nsp14, and has an important reference significance for the development of anti-COVID-19 drugs.

Keyword ：

SARS-CoV-2 ADMET QSAR Nsp14 inhibitor Docking COVID-19

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Abstract ：

Rankine-based pumped thermal energy storage (PTES) is a potential electricity storage technology for accelerating the integration of renewables. This paper provides a novel Rankine-based PTES concept based on cascadecharging, dual-expansion, and hybrid thermal storage, which enables large temperature span and the cooperative thermal matching of the heat pump, thermal storage, and heat engine. A system layout and the corresponding theoretical model for energy and exergy analysis are developed. The integration of low-temperature heat is considered, and multiple criteria are defined to evaluate the thermal energy utilization quantitatively. Afterward, a systematic investigation into its performance is conducted. The influence of key parameters is analyzed with a multiobjective optimization to unveil the trade-off relations between different performance indicators. Beyond that, the exergy loss distribution of the presented concept is revealed, and a comparison with the traditional concept is also performed. Results show the concept has promising comprehensive performance. A round-trip efficiency of over 72 % is achieved under a 100 K temperature span with the exergy efficiency of heat engine reaching about 70 %. Moreover, the strong mutual promotion of thermal integration is observed. The concept reported here can offer a meaningful reference for the coordination design of the Rankine-based PTES.

Keyword ：

Pumped thermal electricity storage Thermodynamic evaluation Configuration design Cascade heat pump Hybrid thermal storage

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