RESUMO
Hepatocellular carcinoma (HCC) is a common cause of cancer-related mortality and morbidity globally, and with the prevalence of metabolic-related diseases, the incidence of metabolic dysfunction-associated fatty liver disease (MAFLD) related hepatocellular carcinoma (MAFLD-HCC) continues to rise with the limited efficacy of conventional treatments, which has created a major challenge for HCC surveillance. Immune checkpoint inhibitors (ICIs) and molecularly targeted drugs offer new hope for advanced MAFLD-HCC, but the evidence for the use of both types of therapy in this type of tumour is still insufficient. Theoretically, the combination of immunotherapy, which awakens the body's anti-tumour immunity, and targeted therapies, which directly block key molecular events driving malignant progression in HCC, is expected to produce synergistic effects. In this review, we will discuss the progress of immunotherapy and molecular targeted therapy in MAFLD-HCC and look forward to the opportunities and challenges of the combination therapy.
Assuntos
Carcinoma Hepatocelular , Inibidores de Checkpoint Imunológico , Imunoterapia , Neoplasias Hepáticas , Terapia de Alvo Molecular , Humanos , Carcinoma Hepatocelular/terapia , Carcinoma Hepatocelular/imunologia , Carcinoma Hepatocelular/tratamento farmacológico , Neoplasias Hepáticas/terapia , Neoplasias Hepáticas/imunologia , Neoplasias Hepáticas/tratamento farmacológico , Imunoterapia/métodos , Inibidores de Checkpoint Imunológico/uso terapêutico , Animais , Terapia Combinada , Hepatopatia Gordurosa não Alcoólica/terapia , Hepatopatia Gordurosa não Alcoólica/imunologia , Hepatopatia Gordurosa não Alcoólica/tratamento farmacológicoRESUMO
Objective: This meta-analysis aimed to determine the efficacy of curcumin in preventing liver fibrosis in animal models. Methods: A systematic search was conducted on studies published from establishment to November 2023 in PubMed, Web of Science, Embase, Cochrane Library, and other databases. The methodological quality was assessed using Sycle's RoB tool. An analysis of sensitivity and subgroups were performed when high heterogeneity was observed. A funnel plot was used to assess publication bias. Results: This meta-analysis included 24 studies involving 440 animals with methodological quality scores ranging from 4 to 6. The results demonstrated that curcumin treatment significantly improved Aspartate aminotransferase (AST) [standard mean difference (SMD) = -3.90, 95% confidence interval (CI) (-4.96, -2.83), p < 0.01, I2 = 85.9%], Alanine aminotransferase (ALT)[SMD = - 4.40, 95% CI (-5.40, -3.40), p < 0.01, I2 = 81.2%]. Sensitivity analysis of AST and ALT confirmed the stability and reliability of the results obtained. However, the funnel plot exhibited asymmetry. Subgroup analysis based on species and animal models revealed statistically significant differences among subgroups. Furthermore, curcumin therapy improved fibrosis degree, oxidative stress level, inflammation level, and liver synthesis function in animal models of liver fibrosis. Conclusion: Curcumin intervention not only mitigates liver fibrosis but also enhances liver function, while concurrently modulating inflammatory responses and antioxidant capacity in animal models. This result provided a strong basis for further large-scale animal studies as well as clinical trials in humans in the future. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42024502671.
RESUMO
BANKGROUND: The tumor microenvironment (TME) is an internal environment composed of various cells and an extracellular matrix. Cancer stem cell-derived exosomes (CSC-Exos), as essential messengers involved in various tumor processes, are important carriers for bidirectional communication between the tumor microenvironment and tumor cells and play an important role in the tumor microenvironment. Nevertheless, few bibliometric analyses have been systematically studied in this field. METHODS: Therefore, we aimed to visualize the research hotspots and trends in this field through bibliometrics to comprehend the future evolution of fundamental and clinical research, as well as to offer insightful information and fresh viewpoints. The Scopus database was used to search the research literature related to exosomes and tumor microenvironments after the establishment of this repository. CiteSpace (version 5.8.R3) and VOSviewer (version 1.6.16) were used for visualization and analysis. RESULTS: In this study, a total of 2077 articles and reviews were included, with the number of articles on exosomes and tumor microenvironments significantly increasing yearly. Recent trends showed that the potential value of exosomes as "tumor diagnostics" and "the application prospect of exosomes as therapeutic agents and drug delivery carriers" will receive more attention in the future. CONCLUSIONS: We revealed the current status and hotspots of tumor stem cell-derived exosomes and tumor microenvironments globally through bibliometrics. The prospect of the regulatory role of CSC-Exos in TME, the potential value of diagnosis, and the application of drug delivery vectors will all remain cutting-edge research areas in the field of tumor therapy. Meanwhile, this study provided a functional literature analysis for related researchers.
Assuntos
Exossomos , Neoplasias , Humanos , Comunicação , Células-Tronco Neoplásicas , Microambiente Tumoral , BiologiaRESUMO
Deep learning has risen to the forefront of many fields in recent years, overcoming challenges previously considered intractable with conventional means. Materials discovery and optimization is one such field, but significant challenges remain, including the requirement of large labeled datasets and one-to-many mapping that arises in solving the inverse problem. Here we demonstrate modeling of complex all-dielectric metasurface systems with deep neural networks, using both the metasurface geometry and knowledge of the underlying physics as inputs. Our deep learning network is highly accurate, achieving an average mean square error of only 1.16 × 10-3 and is over five orders of magnitude faster than conventional electromagnetic simulation software. We further develop a novel method to solve the inverse modeling problem, termed fast forward dictionary search (FFDS), which offers tremendous controls to the designer and only requires an accurate forward neural network model. These techniques significantly increase the viability of more complex all-dielectric metasurface designs and provide opportunities for the future of tailored light matter interactions.