Qingyong Wang

BACKGROUND: Vascular cognitive impairment (VCI) is a prevalent and heterogeneous condition, both clinically and pathophysiologically, that still lacks approved treatment. Peripheral electrical nerve stimulation (PENS) shows promise for VCI management, yet its underlying neurobiological mechanisms are not well understood. METHODS: VCI was induced in rats via permanent bilateral common carotid artery occlusion. Cognitive function was assessed using the Morris water maze, Y-maze, and novel object recognition. Synaptic plasticity was evaluated through long-term potentiation recordings and Golgi staining. The nucleus tractus solitarius (NTS)–medial septum–hippocampus circuit was dissected using fiber photometry recording, immunofluorescence multiplex labeling, in vivo multichannel recordings, anterograde/retrograde tracing, and chemogenetic manipulation. RESULTS: We found that PENS at Zusanli (ST36) acupoint significantly elevated hippocampal acetylcholine levels, enhanced synaptic plasticity, and rescued spatial and nonspatial memory deficits in VCI rats. Chemogenetic activation of cholinergic neurons in the NTS enhanced the cognitive function of VCI rats, whereas chemogenetic inhibition of these neurons counteracted the cognitive benefits of PENS. The NTS sends cholinergic projections to the hippocampal cornu ammonis 1 region through the medial septum. Specific inhibition of NTS ^ChAT -medial septum ^ChAT -cornu ammonis 1 circuit reversed the enhancement of spatial memory observed in VCI rats treated with PENS, while leaving the nonspatial memory unaffected. CONCLUSIONS: Our findings identify the NTS–medial septum–cornu ammonis 1 cholinergic circuit as a critical mechanism mediating PENS-induced reversal of spatial memory deficits in VCI, revealing a novel and spatially selective therapeutic target for VCI.

To evaluate the importance of AI technologies in modernizing traditional Chinese medicine (TCM) therapy, this article presents the systematic review of the relevant literature and explains the beneficial effects of AI technology on the TCM treatment outcomes from the experience of famous and veteran Chinese medicines, including acupuncture, Tui Na massage, and Qigong practitioners. This study also focuses on the urgent necessity to apply AI technologies to develop therapeutic models on the theme “treating the disease before it happens.” Furthermore, the study also discusses the major bottlenecks and future prospects for the development of intelligent TCM treatment strategies.

As an emerging comprehensive discipline, artificial intelligence (AI) has been widely applied in various fields, including traditional Chinese medicine (TCM), a treasure of the Chinese nation. Realizing the organic combination of AI and TCM can promote the inheritance and development of TCM. The paper summarizes the development and application of AI in auxiliary TCM diagnosis, analyzes the bottleneck of artificial intelligence in the field of auxiliary TCM diagnosis at present, and proposes a possible future direction of its development.

In order to evaluate the importance of deep learning techniques in stroke diseases, this paper systematically reviews the relevant literature. Deep learning techniques have a significant impact on the diagnosis, treatment, and prediction of stroke. In addition, this study also discusses the current bottlenecks and the future development prospects of deep learning technology.

With the continuous development of artificial intelligence technology, “brain‐computer interfaces” are gradually entering the field of medical rehabilitation. As a result, brain‐computer interfaces (BCIs) have been included in many countries’ strategic plans for innovating this field, and subsequently, major funding and talent have been invested in this technology. In neurological rehabilitation for stroke patients, the use of BCIs opens up a new chapter in “top‐down” rehabilitation. In our study, we first reviewed the latest BCI technologies, then presented recent research advances and landmark findings in BCI‐based neurorehabilitation for stroke patients. Neurorehabilitation was focused on the areas of motor, sensory, speech, cognitive, and environmental interactions. Finally, we summarized the shortcomings of BCI use in the field of stroke neurorehabilitation and the prospects for BCI technology development for rehabilitation.

The rapid progress of the combination of medicine and engineering provides better chances for the clinical treatment and healthcare engineering. Traumatic brain injury (TBI) and its related symptoms have become a major global health problem. At present, these techniques has been widely used in the rehabilitation of TBI. In this review article, we summarizes the progress of the combination of medicine and industry in the rehabilitation of traumatic brain injury in recent years, mainly from the following aspects: artificial intelligence (AI), brain‐computer interfaces (BCI), noninvasive brain stimulation (NIBS), and wearable‐assisted devices. We believe the summary of this article can improve insight into the combination of medicine and industry in the rehabilitation of traumatic brain injury.