Mesenchymal stem cells (MSCs) have emerged as a promising approach for drug delivery strategies because of their unique properties. These strategies include stem cell membrane-coated nanoparticles, stem cell-derived extracellular vesicles, immunomodulatory effects, stem cell-laden scaffolds, and scaffold-free stem cell sheets. MSCs offer advantages such as low immunogenicity, homing ability, and tumor tropism, making them ideal for targeted drug delivery systems. Stem cell-derived extracellular vesicles have gained attention for their immune properties and tumor-homing abilities, presenting a potential solution for drug delivery challenges. The relationship between MSC-based drug delivery and the self-renewal and differentiation capabilities of MSCs lies in the potential of engineered MSCs to serve as effective carriers for therapeutic agents while maintaining their intrinsic properties. MSCs exhibit potent immunosuppressive functions in MSC-based drug delivery strategies. Stem cell-derived EVs have low immunogenicity and strong therapeutic potential for tissue repair and regeneration. Scaffold-free stem cell sheets represent a cutting-edge approach in regenerative medicine, offering a versatile platform for tissue engineering and regeneration across different medical specialties. MSCs have shown great potential for clinical applications in regenerative medicine because of their ability to differentiate into various cell types, secrete bioactive factors, and modulate immune responses. Researchers are exploring these innovative approaches to enhance drug delivery efficiency and effectiveness in treating various diseases.

Heparan sulfate proteoglycans are highly glycosylated proteins in which heparan sulfate, a glycosaminoglycan sugar chain, is an acidic sugar chain consisting of a repeating disaccharide structure of glucuronic acid and N-acetylglucosamine is locally sulfated. Syndecan, one of the transmembrane HSPGs, functions as a receptor that transmits signals from the extracellular microenvironment to the inside of the cell. In the vascular system, heparan sulfate proteoglycans, a major component of the glycocalyx, enable the binding of various plasma-derived molecules due to their diversity, epimerization of glycosaminoglycans chains, long chains, and sulfation. Heparan sulfate proteoglycans present in the extracellular matrix serve as a reservoir for bioactive molecules such as chemokines, cytokines, and growth factors. Aberrant expression of heparan sulfate proteoglycans, heparanase, and sulfatase is observed in many pathological conditions. Therefore, it can be applied to therapeutic strategies for a wide range of fields including Alzheimer’s disease, heart failure, cancer, organ transplants, diabetes, chronic inflammation, aging, and autoimmune diseases.

Adeno-associated virus (AAV) is characterized by non-pathogenicity, long-term infection, and broad tropism and is actively developed as a vector virus for gene therapy products. AAV is classified into more than 100 serotypes based on differences in the amino acid sequence of the capsid protein. Endocytosis involves the uptake of viral particles by AAV and accessory receptors during AAV infection. After entry into the cell, they are transported to the nucleus through the nuclear pore complex. AAVs mainly use proteoglycans as receptors to enter cells, but the types of sugar chains in proteoglycans that have binding ability are different. Therefore, it is necessary to properly evaluate the primary structure of receptor proteins, such as amino acid sequences and post-translational modifications, including glycosylation, and the higher-order structure of proteins, such as the folding of the entire capsid structure and the three-dimensional (3D) structure of functional domains, to ensure the efficacy and safety of biopharmaceuticals. To further enhance safety, it is necessary to further improve the efficiency of gene transfer into target cells, reduce the amount of vector administered, and prevent infection of non-target cells.

Computer vision and artificial intelligence have revolutionized the field of pathological image analysis, enabling faster and more accurate diagnostic classification. Deep learning architectures like convolutional neural networks (CNNs), have shown superior performance in tasks such as image classification, segmentation, and object detection in pathology. Computer vision has significantly improved the accuracy of disease diagnosis in healthcare. By leveraging advanced algorithms and machine learning techniques, computer vision systems can analyze medical images with high precision, often matching or even surpassing human expert performance. In pathology, deep learning models have been trained on large datasets of annotated pathology images to perform tasks such as cancer diagnosis, grading, and prognostication. While deep learning approaches show great promise in diagnostic classification, challenges remain, including issues related to model interpretability, reliability, and generalization across diverse patient populations and imaging settings.

The molecular regulation and therapeutic applications of brain-derived neurotrophic factor (BDNF)–tropomyosin-related kinase B (TrkB) signaling in major depressive disorder (MDD) through interaction with vascular endothelial growth factor (VEGF) and N-methyl-D-aspartic acid (NMDA) receptors show promise. While BDNF-TrkB signaling is implicated in antidepressant action, the association between BDNFs and depression has not yielded conclusive results. Some studies show decreased BDNF levels in depression, while others indicate that increased BDNF expression in certain brain regions can induce depression susceptibility. The role of BDNFs varies across different brain regions, necessitating further study of individual mechanisms. This regional variability complicates the development of targeted therapies. The antidepressant-like and neurotrophic actions of BDNFs require VEGF signaling, but there is also a reciprocal interdependence, as VEGF actions are dependent on BDNFs. This complex relationship complicates the development of targeted therapies.

Cancer gene therapy is attracting considerable attention as a new treatment method for overcoming intractable cancers. CAR-T cell therapy has already achieved remarkable results, particularly for hematological tumors. Because CAR-T cells can increase within the body, they have the advantage of requiring only a single administration. In addition, CAR-T cell therapy targeting the CD19 antigen has been established for relapsed or refractory disease in young people with CD19-positive acute B-cell leukemia (B-acute lymphoblastic leukemia, B-ALL) and diffuse large B-cell lymphoma (DLBCL). In addition to CAR-T cell therapy, oncolytic viruses represent a promising approach for cancer treatment, with some already in clinical use and others being researched for their potential benefits. These viruses infect and kill cancer cells, triggering an immune response that helps the body recognize and fight cancer. Oncolytic virus therapy is a form of immunotherapy that uses modified viruses to target and destroy tumor cells while potentially stimulating antitumor immune responses. These viruses have shown promising activity in clinical trials, with some approved for specific cancers like melanoma. Research is ongoing to improve their efficacy, expand their use to other cancer types, and overcome the logistical challenges associated with their delivery. Gene therapy can potentially treat diseases caused by recessive gene disorders like cystic fibrosis, hemophilia, muscular dystrophy, and sickle cell anemia, as well as acquired genetic diseases, such as cancer and viral infections like acquired immunodeficiency syndrome (AIDS).