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Hepatocellular carcinoma is the predominant histologic variant of hepatic malignancy and has become a major challenge to global health. The increasing incidence and mortality of hepatocellular carcinoma has created an urgent need for effective prevention, diagnosis, and treatment strategies. This is despite the impressive results of multiple treatments in the clinic. However, the unique tumor immunosuppressive microenvironment of hepatocellular carcinoma increases the difficulty of treatment and immune tolerance. In recent years, the application of nanoparticles in the treatment of hepatocellular carcinoma has brought new hope for tumor patients. Nano agents target tumor-associated fibroblasts, regulatory T cells, myeloid suppressor cells, tumor-associated macrophages, tumor-associated neutrophils, and immature dendritic cells, reversed the immunosuppressive microenvironment of hepatocellular carcinoma. In addition, he purpose of this review is to summarize the advantages of nanotechnology in guiding surgical excision, local ablation, TACE, standard chemotherapy, and immunotherapy, application of nano-vaccines has also continuously enriched the treatment of liver cancer. This study aims to investigate the potential applications of nanotechnology in the management of hepatocellular carcinoma, with the ultimate goal of enhancing therapeutic outcomes and improving the prognosis for patients affected by this malignancy. [ABSTRACT FROM AUTHOR]

Introduction: Patients with Primary Sjögren's syndrome (pSS) are at a higher risk of thyroid disorders than the general population. This retrospective analysis of 202 patients with pSS was conducted to uncover risk factors associated with thyroid involvement and to create a predictive model for this condition. Methods: We analyzed 202 patients with pSS from Guang'anmen Hospital, China Academy of Chinese Medical Sciences, with 105 cases of thyroid involvement and 97 without. The Least Absolute Shrinkage and Selection Operator method was used to identify key variables for our risk model. These variables were then subjected to multivariate logistic regression to develop the model. The accuracy of the model was assessed through the C-index, receiver operating characteristic curves, calibration plots, and decision curve analysis, with internal validation via bootstrapping. Results: High-sensitivity C-reactive protein (HCRP), pulmonary disease, pharyngeal dryness, forgetfulness, night sweats, hyperuricemia, nasal dryness, anxiety, Ro52, and aspartate aminotransferase (AST) were incorporated into the nomogram. The model showed robust discrimination and calibration abilities. Decision curve analysis indicated the clinical utility of our nomogram in intervening on the probability thresholds of thyroid disease. Conclusion: By integrating HCRP, pulmonary disease, pharyngeal dryness, forgetfulness, night sweats, hyperuricemia, nasal dryness, anxiety, Ro52, and AST, our thyroid risk nomogram can predict the risk of thyroid involvement in patients with pSS, aiding in more informed treatment strategies. [ABSTRACT FROM AUTHOR]