Fe3O4 Nanoparticles That Modulate the Polarisation of Tumor-Associated Macrophages Synergize with Photothermal Therapy and Immunotherapy (PD-1/PD-L1 Inhibitors) to Enhance Anti-Tumor Therapy.

Introduction: Traditional surgical resection, radiotherapy, and chemotherapy have been the treatment options for patients with head and neck squamous cell carcinoma (HNSCC) over the past few decades. Nevertheless, the five-year survival rate for patients has remained essentially unchanged, and research into treatments has been relatively stagnant. The combined application of photothermal therapy (PTT) and immunotherapy for treating HNSCC has considerable potential. Methods: Live-dead cell staining and CCK-8 assays proved that Fe3O4 nanoparticles are biocompatible in vitro. In vitro, cellular experiments utilized flow cytometry and immunofluorescence staining to verify the effect of Fe3O4 nanoparticles on the polarisation of tumor-associated macrophages. In vivo, animal experiments were conducted to assess the inhibitory effect of Fe3O4 nanoparticles on tumor proliferation under the photothermal effect in conjunction with BMS-1. Tumour tissue sections were stained to observe the effects of apoptosis and the inhibition of tumor cell proliferation. The histological damage to animal organs was analyzed by hematoxylin and eosin (H&E) staining. Results: The stable photothermal properties of Fe3O4 nanoparticles were validated by in vitro cellular and in vivo animal experiments. Fe3O4 photothermal action not only directly triggered immunogenic cell death (ICD) and enhanced the immunogenicity of the tumor microenvironment but also regulated the expression of tumor-associated macrophages (TAMs), up-regulating CD86 and down-regulating CD206 to inhibit tumor growth. The PD-1/PD-L1 inhibitor promoted tumor suppression, and reduced tumor recurrence and metastasis. In vivo studies demonstrated that the photothermal action exhibited a synergistic effect when combined with immunotherapy, resulting in significant suppression of primary tumors and an extension of survival. Conclusion: In this study, we applied Fe3O4 photothermolysis in a biomedical context, combining photothermolysis with immunotherapy, exploring a novel pathway for treating HNSCC and providing a new strategy for effectively treating HNSCC.

GNBoost-Based Ensemble Machine Learning for Predicting Tribological Properties of Liquid-Crystal Lubricants.

The intricate development of liquid-crystal lubricants necessitates the timely and accurate prediction of their tribological performance in different environments and an assessment of the importance of relevant parameters. In this study, a classification model using Gaussian noise extreme gradient boosting (GNBoost) to predict tribological performance is proposed. Three additives, polysorbate-85, polysorbate-80, and graphene oxide, were selected to fabricate liquid-crystal lubricants. The coefficients of friction of these lubricants were tested in the rotational mode using a universal mechanical tester. A model was designed to predict the coefficient of friction through data augmentation of the initial data. The model parameters were optimized using particle swarm optimization techniques. This study provides an effective example for lubricant performance evaluation and formulation optimization.