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Abnormal viscosity is closely related to the occurrence of many diseases, such as cancer. Therefore, real-time detection of changes in viscosity in living cells is of great importance. Fluorescent molecular rotors play a critical role in detecting changes in cellular viscosity. Developing red emission viscosity probes with large Stokes shifts and high sensitivity and specificity remains an urgent and important topic. Herein, a novel viscosity-sensitive fluorescent probe (TCF-VIS1) with a large stokes shift and red emission was prepared based on the 2-dicyanomethylene-3-cyano-4,5,5-trimethyl-2,5-dihydrofuran (TCF) skeleton. Due to intramolecular rotation, the probe itself does not fluorescence at low viscosity. With the increase in viscosity, the rotation of TCF-VIS1 is limited, and its fluorescence is obviously enhanced. The probe has the advantages of simple preparation, large Stokes shift, good sensitivity and selectivity, and low cytotoxicity, which make it successfully used for viscosity detection in living cells. Moreover, TCF-VIS1 showed its potential for cancer diagnosis at the cell level and in tumor-bearing mice by detecting viscosity. Therefore, the probe is expected to enrich strategies for the detection of viscosity in biological systems and offer a potential tool for cancer diagnosis. [ABSTRACT FROM AUTHOR]

Green navigation presents a challenge to sustainable mobility. Carbon emissions are a key indicator for evaluating the sustainability of a route. Some methods of green navigation consider the fastest and shortest route to be the least carbon-emitting option, solely from the driver's perspective. To address this issue, various studies have incorporated road factors into the sustainability evaluation model and designed static route planning algorithms to minimize carbon emissions. However, there has been no comprehensive analysis of carbon emissions from both the road and the driver perspectives, and the influence of a sustainability evaluation using dynamic traffic states has not been considered. In this paper, we propose a carbon emission evaluation model based on the life cycle assessment (LCA) and a dynamic route planning algorithm that focuses on near-real-time traffic states. First, we develop an evaluation model for carbon emissions from both the road and the driver perspectives using a carbon footprint measurement method. Next, we propose a route planning method with both a static calculation and near-real-time adjustment to minimize carbon emissions. Finally, we select three cases from South China with different characteristics to verify the effectiveness of our model and algorithm. This evaluation model calculates the carbon emissions caused by all parties involved, providing a comprehensive assessment of the total carbon emissions generated by traffic. This approach addresses the problem of traditional route planning, which often fails to account for the influences of variable traffic conditions on the greenest route. We verify the effectiveness of the greenest navigation algorithm and near-real-time green navigation and apply these two aspects to cases where the greenest route is compared with other common navigation results from different dimensions. We compare carbon emissions from vehicles and roads from electric vehicles and gasoline-powered vehicles. If an electric vehicle is equipped with a wind power generator, the proportion of the vehicle's carbon emissions will be very small. For other vehicle types, the carbon emissions will be more than 1000 times the road emissions. [ABSTRACT FROM AUTHOR]

With the enhanced interoperability of information among vehicles, the demand for collaborative sharing among vehicles increases. Based on blockchain, the classical consensus algorithms in collaborative IoV (Internet of Vehicle), such as PoW (Proof of Work), PoS (Proof of Stake), and DPoS (Delegated Proof of Stake), only consider the node features, which is hard to adapt to the immediacy and flexibility of vehicles. On the other hand, classical consensus algorithms often require mass computing, which undoubtedly increases the communication overhead, resulting in the inability to achieve collaborative IoV under asymmetric networks. Therefore, proposing a low failure rate consensus algorithm that takes into account running time and energy consumption becomes a major challenge in IoV applications. This paper proposes an AI-enabled consensus algorithm with vehicle features, combining vehicle-based metrics and neural networks. First, we introduce vehicle-based metrics such as vehicle online time, performance, and behavior. Then, we propose an integral model and a hierarchical classification method, which combine with a BP neural network to obtain the optimal solution for interconnection. Among them, we also use Informer to predict the future online duration of vehicles, which effectively solves the situation that the primary node vehicle drops off in collaborative IoV. Finally, the experimentations show that the vehicle-based metrics eliminate the problem of the primary node vehicle being offline, which realizes the collaborative IoV considering vehicle features. Meanwhile, it reduces the vehicle network system delay and energy consumption. [ABSTRACT FROM AUTHOR]

The acidic tumor microenvironment (TME) is unfriendly to the activity and function of immune cells in the TME. Here, we report inorganic nanozymes (i.e., SnSe NSs) that mimic the catalytic activity of lactate dehydrogenase to degrade lactate to pyruvate, contributing to the metabolic treatment of tumors. As found in this study, SnSe NSs successfully decreased lactate levels in cells and tumors, as well as reduced tumor acidity. This is associated with activation of the immune response of T cells, thus alleviating the immunosuppressive environment of the TME. More importantly, the nanozyme successfully inhibited tumor growth in mutilate mouse tumor models. Thus, SnSe NSs show a promising result in lactate depletion and tumor suppression, which exemplifies its potential strategy in targeting lactate for metabolic therapy. [ABSTRACT FROM AUTHOR]

Drug nanocrystals, one of most common drug delivery systems, enable the delivery of poorly water-soluble drugs with high drug loading and enhanced dissolution. The rapid clearance and uncontrolled drug release of drug nanocrystals limit their delivery efficiency and clinical application. Herein, an amphiphilic co-polymer, poly oligo(ethylene glycol) methacrylate-b-poly(styrene–co-4-formylphenyl methacrylate) (POEGMA-b-P (St-co-FPMA), PPP), characterized by a hydrophilic part with bottlebrush-like oligo(ethylene glycol) methacrylate (OEGMA) side chains, was synthesized as stabilizers to fabricate a high-drug-loading nanocrystal micelle (053-PPP NC micelle) using the chronic myeloid leukemia (CML) drug candidate N-(2-methyl-5-(3-(trifluoromethyl)benzamido)phenyl)-4-(methylamino)pyrimidine-5-carboxamide (CHMFL-ABL-053 or 053) as a model drug. The 053-PPP NC micelle was characterized and subjected to in vitro and in vivo studies. It featured a worm-like shape of small size, high drug loading (~50%), high colloidal stability, and controlled release in vitro. The presence of the 053-PPP NC micelle resulted in a long-circulation property and a much higher AUC. The 053-PPP NC micelle induced higher accumulation in the tumor tissues under multiple continuous administration. For in vivo efficacy, the 053-PPP NC micelle with a longer dosing interval (96 h), beneficial for improving patient adherence, demonstrated superiority to the 053-F127 NC. The proposed stabilizer PPP and the 053-PPP NC micelle with high drug loading enables drug delivery with long circulation and controlled release of drugs. It is also promising for the development of more efficient nanocrystal-based intravenous injection formulations for poorly water-soluble drugs. It might also offer new possibilities for potential clinical application of the CML candidate drug 053. [ABSTRACT FROM AUTHOR]

Vibrio vulnificus (V. vulnificus) infection-associated multiple antibiotic resistance has raised serious public health concerns. Recently, nanosponges (NSs) have been expected to provide innovative platforms for addressing antibacterial and drug-resistant challenges by targeting various pore-forming toxins (PFTs). In the present study, we constructed NSs to explore the effects and possible mechanism of recombinant V. vulnificus hemolysin (rVvhA)-induced injuries. In vitro, NSs significantly reversed rVvhA-induced apoptosis and necrosis, and improved toxin-induced intracellular reactive oxygen species (ROS) production, adenosine triphosphate (ATP) depletion, and apoptosis signaling pathway disruption. To explore the clinical translation potential of NSs, we established VvhA-induced septicemia and wound infection mouse models, respectively, and further found NSs could notably attenuate rVvhA-induced acute toxicity and septicemia-associated inflammation, as well as local tissue damage. In a conclusion, NSs showed excellent protective effects against rVvhA-induced toxicity, thus providing useful insights into addressing the rising threats of severe V. vulnificus infections. [ABSTRACT FROM AUTHOR]

A time-sensitive network (TSN) extends the conventional Ethernet to support time-sensitive data flow. Thus, it enables simultaneous transmission of high reliability (HR) flow, medium reliability (MR) flow, and low reliability (LR) flow on the same network, thereby improving the reliability of data transmission. A TSN is a symmetric network that connects sensors and other facilities. As a backbone network, it can efficiently connect the underlying sensors and other levels of facilities, as well as ensure the quality of service of the network. For modern supervisory control and data acquisition (SCADA) systems, several types of sensors are widely used. The acquisition cycle of sensors for different purposes varies significantly from milliseconds to seconds. Moreover, these data also have different real-time requirements. Based on satisfiability modulo theories (SMT), this study proposes a TSN routing and scheduling method by adding related scheduling constraints. Compared with other methods, the proposed method can realize the routing and scheduling of hybrid flow in a hyper period and consider MR flow and LR flow, which improves the feasibility and certainty of data flow interaction between substations. [ABSTRACT FROM AUTHOR]

We first identified and characterized a novel peroxiredoxin (Prx), designated as CcPrx4, from the cDNA library of the tentacle of the jellyfish Cyanea capillata. The full-length cDNA sequence of CcPrx4 consisted of 884 nucleotides with an open reading frame encoding a mature protein of 247 amino acids. It showed a significant homology to peroxiredoxin 4 (Prx4) with the highly conserved F-motif (93FTFVCPTEI101), hydrophobic region (217VCPAGW222), 140GGLG143 and 239YF240, indicating that it should be a new member of the Prx4 family. The deduced CcPrx4 protein had a calculated molecular mass of 27.2 kDa and an estimated isoelectric point of 6.3. Quantitative real-time PCR analysis showed that CcPrx4 mRNA could be detected in all the jellyfish tissues analyzed. CcPrx4 protein was cloned into the expression vector, pET-24a, and expressed in Escherichia coli Rosetta (DE3) pLysS. Recombinant CcPrx4 protein was purified by HisTrap High Performance chelating column chromatography and analyzed for its biological function. The results showed that the purified recombinant CcPrx4 protein manifested the ability to reduce hydrogen peroxide and protect supercoiled DNA from oxidative damage, suggesting that CcPrx4 protein may play an important role in protecting jellyfish from oxidative damage.

Our previous studies demonstrated that tentacle extract (TE) from the jellyfish, Cyanea capillata, could cause a dose-dependent increase of systolic blood pressure, which seemed to be the result of direct constriction of vascular smooth muscle (VSM). The aim of this study is to investigate whether TE could induce vasoconstriction in vitro and to explore its potential mechanism. Using isolated aorta rings, a direct contractile response of TE was verified, which showed that TE could induce concentration-dependent contractile responses in both endothelium-intact and -denuded aortas. Interestingly, the amplitude of contraction in the endothelium-denuded aorta was much stronger than that in the endothelium-intact one, implying that TE might also bring a weak functional relaxation in addition to vasoconstriction. Further drug intervention experiments indicated that the functional vasodilation might be mediated by nitric oxide, and that TE-induced vasoconstriction could be attributed to calcium influx via voltage-operated calcium channels (VOCCs) from the extracellular space, as well as sarcoplasmic reticulum (SR) Ca²⁺ release via the inositol 1,4,5-trisphosphate receptor (IP₃R), leading to an increase in [Ca²⁺](c), instead of activation of the PLC/DAG/PKC pathway or the sympathetic nerve system.