Although neurons attract the most attention in neurobiology, our current knowledge of neural circuit can only partially explain the neurological and psychiatric conditions of the brain. Thus, it is also important to consider the influence of brain interstitial system (ISS), which refers to the space among neural cells and capillaries. The ISS is the major compartment of the brain microenvironment that provides the immediate accommodation space for neural cells, and it occupies 15% to 20% of the total brain volume. The brain ISS is a dynamic and complex space connecting the vascular system and neural networks and it plays crucial roles in substance transport and signal transmission among neurons. Investigation of the brain ISS can provide new perspectives for understanding brain architecture and function and for exploring new strategies to treat brain disorders. This review discussed the anatomy of the brain ISS under both physiological and pathological conditions, biophysical modeling of the brain ISS and in vivo measurement and imaging techniques, including recent findings on brain ISS divisions. Moreover, the implications of ISS knowledge for basic neuroscience and clinical applications are addressed.

CGAS-STING pathway, as an essential intracellular immune response pathway, has attracted much attention in tumor immunotherapy. However, low metabolic stability of conventional STING agonists limits their clinical application. Recent study shows that chemotherapeutic drugs cisplatin and camptothecin (CPT) can activate cGAS-STING pathway and induce immune response by DNA damage. Nevertheless, the ability of chemotherapeutic drugs to activate STING is so weak that new strategies are required to improve drug delivery efficiency for enhanced DNA damage, and then efficiently activate cGAS-STING pathway. Herein, we have developed a hybrid platinum prodrug (CPT-Pt (IV)) which can be triggered to release cisplatin and CPT in tumor cells. CPT-Pt (IV) with high hydrophobicity is further self-assembled with a ROS sensitive polymer (P1) and mPEG_2k-DSPE into ROS responsive nanoparticles (NPs). NPs could accumulate in the tumor site to release cisplatin and CPT, resulting in DNA double damage and finally activating cGAS-STING pathway, inducing DC cells maturation and increasing tumor infiltration of CD8⁺ T cells on colorectal cancer mouse model. This study showed that common DNA targeted drugs can activate the cGAS-STING pathway in situ via nano delivery system, and enhance the effect of chemotherapy and immunotherapy, which provide a new strategy for clinical antitumor therapy.

The mobile health (mHealth) industry is an enormous global market; however, the dropout or continuance of mHealth is a major challenge that is affecting its positive outcomes. To date, the results of studies on the impact factors have been inconsistent. Consequently, research on the pooled effects of impact factors on the continuance intention of mHealth is limited. Therefore, this study aims to systematically analyze quantitative studies on the continuance intention of mHealth and explore the pooled effect of each direct and indirect impact factor. Until October 2021, eight literature databases were searched. Fifty-eight peer-reviewed studies on the impact factors and effects on continuance intention of mHealth were included. Out of the 19 direct impact factors of continuance intention, 15 are significant, with attitude (β = 0.450; 95% CI: 0.135, 0.683), satisfaction (β = 0.406; 95% CI: 0.292, 0.509), health empowerment (β = 0.359; 95% CI: 0.204, 0.497), perceived usefulness (β = 0.343; 95% CI: 0.280, 0.403), and perceived quality of health life (β = 0.315, 95% CI: 0.211, 0.412) having the largest pooled effect coefficients on continuance intention. There is high heterogeneity between the studies; thus, we conducted a subgroup analysis to explore the moderating effect of different characteristics on the impact effects. The geographic region, user type, mHealth type, user age, and publication year significantly moderate influential relationships, such as trust and continuance intention. Thus, mHealth developers should develop personalized continuous use promotion strategies based on user characteristics.

The primordial small gaseous molecules, such as: NO, CO, H₂S and formaldehyde (FA) are present in the brains. Whether FA as well as the other molecules participates in brain functions is unclear. Recently, its pathophysiological functions have been investigated. Notably, under physiological conditions, learning activity induces a transient generation of hippocampal FA, which promotes memory formation by enhancing N-methyl-D-aspartate (NMDA)-currents. However, ageing leads to FA accumulation in brain for the dysregulation of FA metabolism; and excessive FA directly impairs memory by inhibiting NMDA-receptor. Especially, in Alzheimer's disease (AD), amyloid-beta (Aβ) accelerates FA accumulation by inactivating alcohol dehydrogenase-5; in turn, FA promotes Aβ oligomerization, fibrillation and tau hyperphosphorylation. Hence, there is a vicious circle encompassing Aβ assembly and FA generation. Even worse, FA induces Aβ deposition in the extracellular space (ECS), which blocks the medicines (dissolved in the interstitial fluid) flowing into the damaged neurons in the deep cortex. However, phototherapy destroys Aβ deposits in the ECS and restores ISF flow. Coenzyme Q10, which scavenges FA, was shown to ameliorate Aβ-induced AD pathological phenotypes, thus suggesting a causative relation between FA toxicity and AD. These findings suggest that the combination of these two methods is a promising strategy for treating AD.

In multi-site studies of Alzheimer’s disease (AD), the difference of data in multi-site datasets leads to the degraded performance of models in the target sites. The traditional domain adaptation method requires sharing data from both source and target domains, which will lead to data privacy issue. To solve it, federated learning is adopted as it can allow models to be trained with multi-site data in a privacy-protected manner. In this paper, we propose a multi-site federated domain adaptation framework via Transformer (FedDAvT), which not only protects data privacy, but also eliminates data heterogeneity. The Transformer network is used as the backbone network to extract the correlation between the multi-template region of interest features, which can capture the brain abundant information. The self-attention maps in the source and target domains are aligned by applying mean squared error for subdomain adaptation. Finally, we evaluate our method on the multi-site databases based on three AD datasets. The experimental results show that the proposed FedDAvT is quite effective, achieving accuracy rates of 88.75%, 69.51%, and 69.88% on the AD vs. NC, MCI vs. NC, and AD vs. MCI two-way classification tasks, respectively.