Volume 3, Issue 1 - Special Issue on Nanomedicine

The complexity of the tumor microenvironment (TME) severely hinders the therapeutic effects of various cancer treatment modalities. The TME differs from normal tissues owing to the presence of hypoxia, low pH, and immune-suppressive characteristics. Modulation of the TME to reverse tumor growth equilibrium is considered an effective way to treat tumors. Recently, polymeric nanomedicines have been widely used in cancer therapy, because their synthesis can be controlled and they are highly modifiable, and have demonstrated great potential to remodel the TME. In this review, we outline the application of various stimuli responsive polymeric nanomedicines to modulate the TME, aiming to provide insights for the design of the next generation of polymeric nanomedicines and promote the development of polymeric nanomedicines for cancer therapy.

Microbubbles have been the earliest and most widely used ultrasound contrast agents by virtue of their unique features: such as non-toxicity, intravenous injectability, ability to cross the pulmonary capillary bed, and significant enhancement of echo signals for the duration of the examination, resulting in essential preclinical and clinical applications. The use of microbubbles functionalized with targeting ligands to bind to specific targets in the bloodstream has further enabled ultrasound molecular imaging. Nevertheless, it is very challenging to utilize targeted microbubbles for molecular imaging of extravascular targets due to their size. A series of acoustic nanomaterials have been developed for breaking free from this constraint. Especially, biogenic gas vesicles, gas-filled protein nanostructures from microorganisms, were engineered as the first biomolecular ultrasound contrast agents, opening the door for more direct visualization of cellular and molecular function by ultrasound imaging. The ordered protein shell structure and unique gas filling mechanism of biogenic gas vesicles endow them with excellent stability and attractive acoustic responses. What’s more, their genetic encodability enables them to act as acoustic reporter genes. This article reviews the upgrading progresses of ultrasound contrast agents from microbubbles to biogenic gas vesicles, and the opportunities and challenges for the commercial and clinical translation of the nascent field of biomolecular ultrasound.

Ferritin is an endogenous protein which is self-assembled by 24 subunits into a highly uniform nanocage structure. Due to the drug-encapsulating ability in the hollow inner cavity and abundant modification sites on the outer surface, ferritin nanocage has been demonstrated great potential to become a multi-functional nanomedicine platform. Its good biocompatibility, low toxicity and immunogenicity, intrinsic tumor-targeting ability, high stability, low cost and massive production, together make ferritin nanocage stand out from other nanocarriers. In this review, we summarized ferritin-based nanomedicine in field of disease diagnosis, treatment and prevention. The different types of drugs to be loaded in ferritin, as well as drug-loading methods were classified. The strategies for site-specific and non-specific functional modification of ferritin were investigated, then the application of ferritin for disease imaging, drug delivery and vaccine development were discussed. Finally, the challenges restricting the clinical translation of ferritin-based nanomedicines were analyzed.

Single-nucleotide variants account for about half of known pathogenic genetic variants in human. Genome editing strategies by reversing pathogenic point mutations with minimum side effects have great therapeutic potential and are now being actively pursued. The emerge of precise and efficient genome editing strategies such as base editing and prime editing provide powerful tools for nucleotide conversion without inducing double-stranded DNA breaks (DSBs), which have shown great potential for curing genetic disorders. A diverse toolkit of base editors has been developed to improve the editing efficiency and accuracy in different context of application. Here, we summarized the evolving of base editors (BEs), their limitations and future perspective of base editing-based therapeutic strategies.

The central circadian clock in the brain controls the time-of-the-day variations in acute meal responses, with a low glycemic response but a high satiety/thermogenic response to meals consumed at waking compared to other time points. Consistently, studies show that consuming a significant proportion of calories, particularly carbohydrates, in breakfast is beneficial for the chronic management of obesity and its associated metabolic syndrome, compared to consuming identical meals at dinner. Conversely, breakfast skipping or/and late dinner can have unfavorable metabolic outcomes. It remains controversial how meal frequency affects metabolic health. In contrast, irregular meals, especially irregular breakfasts, show consistent adverse metabolic consequences. Time-restricted feeding (TRF), with all calories consumed within less than 12-h per day, can improve metabolism and extend lifespan. A major component of TRF in humans is caloric restriction, which contributes significantly to the beneficial effects of TRF in humans. By comparison, TRF effects in rodents can be independent of caloric restriction and show day/night phase specificity. TRF could alleviate metabolic abnormalities due to circadian disruption, but its effects appear independent of the circadian clock in rodents. Understanding neuroendocrine mechanisms underlying clock-mediated metabolic regulation will shed light on the metabolic effects of temporal meal patterns.

Diabetes is one of the fastest-growing non-communicable diseases, becoming an important public health concern worldwide as well as in China. Currently, China has the largest population living with diabetes. Artificial intelligence (AI) is a fast-growing field and its applications to diabetes could enable the delivery of better management services for people with diabetes. This perspective summarized the latest findings of digital technologies and AI use in the following areas of diabetes care, mainly including screening and risk predictions of diabetes and diabetic complications, precise monitoring and intervention combined with new technologies, and mobile health application in self-management support for people with diabetes. Challenges to promote further use of AI in diabetes care included data standardization and integration, performance of AI-based medical devices, motivation of patients, and sensitivity to privacy. In summary, although the AI applications in clinical practice is still at an early stage, we are moving toward a new paradigm for diabetes care with the rapid development and emerging application of AI.