Background: With the rapid development of digital biomarkers in Parkinson disease (PD) research, it has become increasingly important to explore the current research trends and key areas of focus. Objective: This study aimed to comprehensively evaluate the current status, hot spots, and future trends of global PD biomarker research, and provide a systematic review of deep learning models for freezing of gait (FOG) digital biomarkers. Methods: This study used bibliometric analysis based on the Web of Science Core Collection database to conduct a comprehensive analysis of the multidimensional landscape of Parkinson digital biomarkers. After identifying research hot spots, the study also followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines for a scoping review of deep learning models for FOG from 5 databases: Web of Science, PubMed, IEEE Xplore, Embase, and Google Scholar. Results: A total of 750 studies were included in the bibliometric analysis, and 40 studies were included in the scoping review. The analysis revealed a growing number of related publications, with 3700 researchers contributing. Neurology had the highest average annual participation rate (12.46/19, 66%). The United States contributed the most research (192/1171, 16.4%), with 210 participating institutions, which was the highest among all countries. In the study of deep learning models for FOG, the average accuracy of the models was 0.92, sensitivity was 0.88, specificity was 0.90, and area under the curve was 0.91. In addition, 31 (78%) studies indicated that the best models were primarily convolutional neural networks or convolutional neural networks–based architectures. Conclusions: Research on digital biomarkers for PD is currently at a stable stage of development, with widespread global interest from countries, institutions, and researchers. However, challenges remain, including insufficient interdisciplinary and interinstitutional collaboration, as well as a lack of corporate funding for related projects. Current research trends primarily focus on motor-related studies, particularly FOG monitoring. However, deep learning models for FOG still lack external validation and standardized performance reporting. Future research will likely progress toward deeper applications of artificial intelligence, enhanced interinstitutional collaboration, comprehensive analysis of different data types, and the exploration of digital biomarkers for a broader range of Parkinson symptoms. Trial Registration: Open Science Foundation (OSF Registries) OSF.IO/RG8Y3; https://doi.org/10.17605/OSF.IO/RG8Y3

Thrombin plays a pivotal role in the pathogenesis of atherosclerosis. Baicalin, an active flavonoid compound, was shown to attenuate the development of atherosclerosis, but the mechanism remains elusive. In the present study, the role and mechanism of baicalin in thrombin-induced cell injury was investigated in human umbilical vein endothelial cells (HUVECs). Our results showed that baicalin significantly reduced thrombin-induced apoptosis of HUVECs. Additional experiments showed that baicalin inhibited thrombin-induced NF-κB activation and PAR-1 expression. In addition, baicalin decreased thrombin-induced PAR-1 expression by inhibiting ERK pathway. These results indicated that baicalin has protective effects on thrombin-induced cell injury in HUVECs possibly through inhibition of PAR-1 expression and its downstream NF-κB activation, which was mediated by ERK1/2 activation.

Atherosclerosis (AS) is a chronic inflammatory disease of the arterial intima. As AS represents the most common type of vascular disease, it affects millions of individuals and is a source of high morbidity and mortality rates worldwide. Overwhelming evidence indicates that AS‐related inflammation is mediated by proinflammatory cytokines, chemokines, adhesion molecules and inflammatory signaling pathways, with each of these factors being shown to play critical roles during the entire progression of AS. While a number of drugs have been approved for use in the treatment of AS, their benefits are modest, which underscores the urgency for the development of new drug therapies. In part, these deficits in effective drugs can be attributable to the lack of a clear understanding of the molecular mechanisms of AS. In this study, we investigate the capacity for thrombin to trigger inflammation and induce cell proliferation in vascular smooth muscle cells (VSMCs). We then assessed the effects of baicalin and its potential mechanisms on VSMC inflammation as induced by thrombin. Baicalin, which is a natural bioactive compound of S. baicalensis Georgi (SBG), exerted a protective effect against thrombin‐induced VSMC inflammation as resulting from the upregulation of PAR‐1. This protection as exerted by baicalin appears to reside in its capacity to produce an inhibitory effect on the thrombin‐induced activation of the ERK1/2 pathway. These findings suggest that baicalin may be a promising candidate for the treatment of atherosclerosis.

Background: COVID-19 pandemic has altered the work mode in long-term care facilities (LTCFs), but little is known about the mental health status of caregivers of older adults.Methods: A total of 672 formal caregivers of older adults in LTCFs and 1,140 formal patient caregivers in hospitals (comparison group) responded to an online survey conducted from March 25, 2022 to April 6, 2022. Five psychological scales, including Insomnia Severity Index (ISI), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), The 5-item World Health Organization Wellbeing Index (WHO-5) and Perceived Stress Scale-14 item (PSS-14), were applied to assess participants’ mental health status. Factors, including sex, profession, marital status, economic conditions, length of working experience, frequent night shift beyond 1 day per week and having organic diseases, were included in logistic regression analysis to identify associated factors with mental health outcomes of formal caregivers of older adults in LTCFs.Results: Caregivers of older adults in LTCFs developed similar severe psychological symptoms with patient caregivers in hospital setting. For caregivers of older adults in LTCFs, unmarried status was a potent risk factor for insomnia, anxiety, impaired wellbeing and health risk stress, with odds ratios ranging from 1.91 to 3.64. Frequent night shift beyond 1 day per week was associated with higher risks of insomnia, depression and impaired wellbeing. Likewise, having organic disease or inferior economic condition, and being nurses appeared to be independent predictors for multiple mental health-related outcomes.Conclusion: During COVID-19 post-epidemic era, caregivers of older adults in LTCFs had a higher prevalence of psychological symptoms, especially those with particular risk factors. Special attention should be paid to promote their mental health.