As the fourth most important cancer management strategy except surgery, chemotherapy and radiotherapy, cancer immunotherapy has been confirmed to elicit durable antitumor effects in the clinic by leveraging the patient's own immune system to eradicate the cancer cells. However, the limited population of patients who benefit from the current immunotherapies and the immune related adverse events hinder its development. The immunosuppressive microenvironment is the main cause of the failure, which leads to cancer immune evasion and immunity cycle blockade. Encouragingly, nanotechnology has been engineered to enhance the efficacy and reduce off-target toxicity of their therapeutic cargos by spatiotemporally controlling the biodistribution and release kinetics. Among them, lipid-based nanoparticles are the first nanomedicines to make clinical translation, which are now established platforms for diverse areas. In this perspective, we discuss the available lipid-based nanoparticles in research and market here, then describe their application in cancer immunotherapy, with special emphasis on the T cells-activated and macrophages-targeted delivery system. Through perpetuating each step of cancer immunity cycle, lipid-based nanoparticles can reduce immunosuppression and promote drug delivery to trigger robust antitumor response.
Gastric cancer (GC) is one of the commonest cancers with high morbidity and mortality in the world. How to realize precise diagnosis and therapy of GC owns great clinical requirement. In recent years, artificial intelligence (AI) has been actively explored to apply to early diagnosis and treatment and prognosis of gastric carcinoma. Herein, we review recent advance of AI in early screening, diagnosis, therapy and prognosis of stomach carcinoma. Especially AI combined with breath screening early GC system improved 97.4 % of early GC diagnosis ratio, AI model on stomach cancer diagnosis system of saliva biomarkers obtained an overall accuracy of 97.18 %, specificity of 97.44 %, and sensitivity of 96.88 %. We also discuss concept, issues, approaches and challenges of AI applied in stomach cancer. This review provides a comprehensive view and roadmap for readers working in this field, with the aim of pushing application of AI in theranostics of stomach cancer to increase the early discovery ratio and curative ratio of GC patients.
The biomedical literature is a vast and invaluable resource for biomedical research. Integrating knowledge from the literature with biomedical data can help biological studies and the clinical decision-making process. Efforts have been made to gather information from the biomedical literature and create biomedical knowledge bases, such as KEGG and Reactome. However, manual curation remains the primary method to retrieve accurate biomedical entities and relationships. Manual curation becomes increasingly challenging and costly as the volume of biomedical publications quickly grows. Fortunately, recent advancements in Artificial Intelligence (AI) technologies offer the potential to automate the process of curating, updating, and integrating knowledge from the literature. Herein, we highlight the AI capabilities to aid in mining knowledge and building the knowledge base from the biomedical literature.
Our oral cavity houses various types of microbes including bacteria, protozoa, fungi and viruses, harboring over 700 bacterial species. Oral dysbiosis refers to the imbalance between symbionts and pathobionts in the oral cavity, posing potential threats to host cardiovascular health. Importantly, oral dysbiosis promotes cardiovascular pathophysiology through different mechanisms. Although overgrowth of certain pathogenic bacteria have been indicated in some cardiometabolic diseases, it is still premature to consider oral microbiome as a suitable predictor for non-invasive diagnostic purpose. However, targeting oral microbiome might still provide preventive and therapeutic insights on cardiovascular diseases. Further extensive efforts are needed to deepen our understanding on oral-cardiovascular connection in the context of diagnostic and therapeutic perspectives.