In-Depth Structural Simplification of Celangulin V: Design, Synthesis, and Biological Activity.

Celangulin V is a novel botanical insecticide with significant bioactivity and a unique molecular target, but its complex polyol ester structure hinders its broader application in agriculture. To discover new analogues of celangulin V with a simpler structure and enhanced biological activities, we initiated a research project aimed at simplifying its structure and assessing insecticidal efficacy. In this study, a series of novel 1-tetralone derivatives were designed via a structure-based rational design approach and synthesized by a facile method. The biological activities of the target compounds were determined against Mythimna separata (M. separata), Plutella xylostella, and Rhopalosiphum padi. The results revealed that most of the synthesized compounds exhibited superior activities compared to celangulin V. Remarkably, the insecticidal activity of compound 6.16 demonstrated 102-fold greater stomach toxicity than celangulin V against M. separata. In addition, certain compounds showed significant contact toxicity against M. separata, a finding not reported previously in the structural optimization studies of celangulin V. Molecular docking analysis illustrated that the binding pocket of compound 6.16 with the H subunit of V-ATPase was the same as celangulin V. This study presents novel insights into the structural optimization of botanical pesticides.

Orchestrated metal-coordinated carrier-free celastrol hydrogel intensifies T cell activation and regulates response to immune checkpoint blockade for synergistic chemo-immunotherapy.

The challenges generated by insufficient T cell activation and infiltration have constrained the application of immunotherapy. Making matters worse, the complex tumor microenvironment (TME), resistance to apoptosis collectively poses obstacles for cancer treatment. The carrier-free small molecular self-assembly strategy is a current research hotspot to overcome these challenges. This strategy can transform multiple functional agents into sustain-released hydrogel without the addition of any excipients. Herein, a coordination and hydrogen bond mediated tricomponent hydrogel (Cel hydrogel) composed of glycyrrhizic acid (GA), copper ions (Cu2+) and celastrol (Cel) was initially constructed. The hydrogel can regulate TME by chemo-dynamic therapy (CDT), which increases reactive oxygen species (ROS) in conjunction with GA and Cel, synergistically expediting cellular apoptosis. What's more, copper induced cuproptosis also contributes to the anti-tumor effect. In terms of regulating immunity, ROS generated by Cel hydrogel can polarize tumor-associated macrophages (TAMs) into M1-TAMs, Cel can induce T cell proliferation as well as activate DC mediated antigen presentation, which subsequently induce T cell proliferation, elevate T cell infiltration and enhance the specific killing of tumor cells, along with the upregulation of PD-L1 expression. Upon co-administration with aPD-L1, this synergy mitigated both primary and metastasis tumors, showing promising clinical translational value.

Hepatic encephalopathy post-TIPS: Current status and prospects in predictive assessment.

Transjugular intrahepatic portosystemic shunt (TIPS) is an essential procedure for the treatment of portal hypertension but can result in hepatic encephalopathy (HE), a serious complication that worsens patient outcomes. Investigating predictors of HE after TIPS is essential to improve prognosis. This review analyzes risk factors and compares predictive models, weighing traditional scores such as Child-Pugh, Model for End-Stage Liver Disease (MELD), and albumin-bilirubin (ALBI) against emerging artificial intelligence (AI) techniques. While traditional scores provide initial insights into HE risk, they have limitations in dealing with clinical complexity. Advances in machine learning (ML), particularly when integrated with imaging and clinical data, offer refined assessments. These innovations suggest the potential for AI to significantly improve the prediction of post-TIPS HE. The study provides clinicians with a comprehensive overview of current prediction methods, while advocating for the integration of AI to increase the accuracy of post-TIPS HE assessments. By harnessing the power of AI, clinicians can better manage the risks associated with TIPS and tailor interventions to individual patient needs. Future research should therefore prioritize the development of advanced AI frameworks that can assimilate diverse data streams to support clinical decision-making. The goal is not only to more accurately predict HE, but also to improve overall patient care and quality of life.