Volume 3, Issue 3 - Special Issue on Artificial Intelligence in Medicine

The era of advanced artificial intelligence has arrived with the development of chatbots like ChatGPT (Chat Generative Pre-trained Transformer). As described by Ouyang et al. (2022), ChatGPT demonstrates an impressive ability to generate human-like responses and solve practical problems, surpassing original expectations for its capabilities. The rapid release and adoption of ChatGPT signals a new phase in AI development, powered by large language models that can be fine-tuned through human feedback. However, risks remain regarding how such powerful models may be misused. Further research is needed to ensure safe and ethical deployment of these transformative technologies.

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.

With the evolution of nanomedicine, the past decades witnessed diversified nanomaterials as marvelous anti-tumor tools ushering in a new era of tumor diagnosis and treatment. Among them, two-dimensional layered nanomaterial as an emerging class of nanomaterials has one dimension less than 100 nm, showing a high specific area and the thinnest sheet-like structure (Liu S, Pan X, Liu H. Twodimensional nanomaterials for photothermal therapy. Angew Chem Int Ed 2020;59:5890–900). The discovery of graphene drove the exploration of various new two-dimensional layered nanomaterials for tumor diagnosis and treatment including graphene-based nanomaterials, black phosphorus (BP), transition metal dichalcogenides (TMDs), layered double hydroxides (LDHs), and bismuth oxyhalides (BiOX, X=F, Cl, Br, I) (Ma H, Xue MQ. Recent advances in the photothermal applications of two-dimensional nanomaterial: photothermal therapy and beyond. J Mater Chem 2021;9:17569). On the one hand, they exhibit strong near-infrared (NIR) absorption and the capacity of optimizing corresponding properties by adjusting the crystal structure. On the other hand, they own unique strengths such as fantastic physicochemical properties (graphene-based nanomaterials), high loading capacity (BP), distinct phase-dependent optical properties (TMDs), a specific chemical response to the tumor microenvironment (LDHs), and large X-ray attenuation coefficient (BiOX). Herein, we briefly introduce three typical two-dimensional layered nanomaterials, their prospects and future research priorities in tumor diagnosis and treatment are concluded.

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.

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.

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.

The monkeypox virus, which causes the viral zoonotic disease, is known as the most significant orthopoxvirus infection following the elimination of smallpox. The monkeypox virus, which was previously exclusive to West and Central African nations and caused endemic diseases in monkeys and people, has recently been linked to human infections in non-endemic areas including the United States of America (USA) and more than 30 additional countries. Guidelines for the diagnosis and treatment of monkeypox have also recently been made available by the Ministry of Health and Family Welfare of India and the Indian Government. The monkeypox outbreak continues to be a worldwide health emergency, the highest degree of alert recognised by the World Health Organization. The Centers for Disease Control and Prevention (CDC) advises vaccination for those who have been exposed to the disease as well as those who may be at higher risk of contracting it, such as those who have been identified by public health officials as a contact of someone who has the disease.