Explore the vast range of titles available.

BackgroundSchizophrenia (SCZ) is a severe psychiatric disorder that involves inflammatory processes. The aim of this study was to explore the field of inflammation-related research in SCZ from a bibliometric perspective.MethodsRegular and review articles on SCZ- and inflammation-related research were obtained from the Web of Science Core Collection (WOSCC) database from its inception to February 19, 2022. R package “bibliometrix” was used to summarize the main findings, count the occurrences of the top keywords, visualize the collaboration network between countries, and generate a three-field plot. VOSviewer software was applied to conduct both co-authorship and co-occurrence analyses. CiteSpace was used to identify the top references and keywords with the strongest citation burst.ResultsA total of 3,596 publications on SCZ and inflammation were included. Publications were mainly from the USA, China, and Germany. The highest number of publications was found in a list of relevant journals. Apart from “schizophrenia” and “inflammatory”, the terms “bipolar disorder,” “brain,” and “meta-analysis” were also the most frequently used keywords.ConclusionsThis bibliometric study mapped out a fundamental knowledge structure consisting of countries, institutions, authors, journals, and articles in the research field of SCZ and inflammation over the past 30 years. The results provide a comprehensive perspective about the wider landscape of this research area.

In recent years, multimodal agent AI (MAA) has emerged as a pivotal area of research, holding promise for transforming human-machine interaction. Agent AI systems, capable of perceiving and responding to inputs from multiple modalities (e.g., language, vision, audio), have demonstrated remarkable progress in understanding complex environments and executing intricate tasks. This survey comprehensively reviews the state-of-the-art developments in MAA and examines its fundamental concepts, key techniques, and applications across diverse domains. We first introduce the basics of agent AI and its multimodal interaction capabilities. We then delve into the core technologies that enable agents to perform task planning, decision-making, and multi-sensory fusion. Furthermore, we focus on exploring various applications of MAA in robotics, healthcare, gaming, and beyond. Additionally, we mainly focus on analyzing the challenges and limitations of current systems and propose promising research directions for future improvements, including human-AI collaboration, online learning method improvement. By reviewing existing work and highlighting open questions, this survey aims to provide a comprehensive roadmap for researchers and practitioners in the field of MAA.

Depression and cognitive decline are common and frequently co-occur among older adults with hypertension, but their symptom-level relationships are poorly understood. This study explored interrelationship between depressive symptoms and cognitive function as well as their associations with quality of life (QoL) in a national hypertension sample from China. Depression, cognitive function, and global QoL were assessed utilizing Chinese versions of the 10-item Center for Epidemiological Studies Short Depression Scale (CESD-10), Mini-Mental State Examination, and World Health Organization Quality of Life-brief version (WHOQOL-BREF), respectively. We identified central symptoms and bridge symptoms based on centrality strength and bridge strength indexes, while symptoms having links to QoL were analyzed via flow network analysis. The study included 4,683 older adults. The prevalence of depression (CESD-10 total score ≥10) and cognitive impairment (MMSE total score <24) were 28.5% (95% CI = 27.2-29.8%) and 19.9% (95% CI = 18.8-21.1%), respectively. \"Feeling blue/depressed\" (CESD3) and \"language\" (Lan) were emerged as the most influential symptoms within the network model. \"Naming\" and \"Language\" were identified as most important bridge symptoms. Finally, \"sleep disturbances\" (CESD10) and \"hopelessness\" (CESD5) exhibited the strongest negative association with QoL. Targeting central and bridge symptoms (e.g., depressed emotions, language, and naming ability) may provide pathways for addressing both depression and cognitive decline among older adults with hypertension. Moreover, improving sleep quality and alleviating hopelessness could help increase QoL in this population.

Psychiatric syndromes are common following recovery from Coronavirus Disease 2019 (COVID-19) infection. This study investigated the prevalence and the network structure of depression, insomnia, and suicidality among mental health professionals (MHPs) who recovered from COVID-19. Depression and insomnia were assessed with the Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index questionnaire (ISI7) respectively. Suicidality items comprising suicidal ideation, suicidal plan and suicidal attempt were evaluated with binary response (no/yes) items. Network analyses with Ising model were conducted to identify the central symptoms of the network and their links to suicidality. A total of 9858 COVID-19 survivors were enrolled in a survey of MHPs. The prevalence of depression and insomnia were 47.10% (95% confidence interval (CI) = 46.09–48.06%) and 36.2% (95%CI = 35.35–37.21%), respectively, while the overall prevalence of suicidality was 7.8% (95%CI = 7.31–8.37%). The key central nodes included “Distress caused by the sleep difficulties” (ISI7) (EI = 1.34), “Interference with daytime functioning” (ISI5) (EI = 1.08), and “Sleep dissatisfaction” (ISI4) (EI = 0.74). “Fatigue” (PHQ4) (Bridge EI = 1.98), “Distress caused by sleep difficulties” (ISI7) (Bridge EI = 1.71), and “Motor Disturbances” (PHQ8) (Bridge EI = 1.67) were important bridge symptoms. The flow network indicated that the edge between the nodes of “Suicidality” (SU) and “Guilt” (PHQ6) showed the strongest connection (Edge Weight= 1.17, followed by “Suicidality” (SU) - “Sad mood” (PHQ2) (Edge Weight = 0.68)). The network analysis results suggest that insomnia symptoms play a critical role in the activation of the insomnia-depression-suicidality network model of COVID-19 survivors, while suicidality is more susceptible to the influence of depressive symptoms. These findings may have implications for developing prevention and intervention strategies for mental health conditions following recovery from COVID-19.

Cognitive impairment is a major health concern in older adults with hypertension, and both depression and abnormal sleep duration are recognized as potential contributing factors. This study aimed to explore the nonlinear association of depression and sleep duration with cognitive impairment among older adults with hypertension. This cross-sectional study was based on the 2017-2018 wave of Chinese Longitudinal Healthy Longevity Survey. Depression and cognitive function were measured using the 10-item Center for Epidemiological Studies Short Depression Scale and Mini Mental State Examination, respectively. Univariate, binary logistic regression, and restricted cubic spline regression analyses were used to examine the associations between depression, sleep duration and cognitive impairment. A total of 3,989 older adults with hypertension were included. The prevalence of depression and cognitive impairment were 28.1% (95%CI = 26.7-29.5%) and 10.1% (95%CI = 9.2-11.1%), respectively. After adjusting for confounding factors, a significant linear association (nonlinear  = 0.814) between depression and cognitive impairment risk was found, while a U-shaped nonlinear association was identified between sleep duration and cognitive impairment risk (  = 0.040). Both shorter (<6.6 h) and longer (>7.7 h) sleep duration per day were associated with higher cognitive impairment risk, with an inflection point at 7.3 h. The effect of sleep duration on cognitive impairment risk was more significant for participants with a higher (≥ 6 years) education level. This study highlights the importance of managing depression and optimizing sleep duration in addressing the risk of cognitive decline in older adults with hypertension.

Background: Associations between the microbiome–gut–brain axis and dementia have attracted considerable attention in research literature. This study examined the microbiome–gut–brain axis and dementia-related research from a bibliometric perspective. Methods: A search for original research and review articles on the microbiome–gut–brain axis and dementia was conducted in the Web of Science Core Collection (WOSCC) database. The R package “bibliometrix” was used to collect information on countries, institutions, authors, journals, and keywords. VOSviewer software was used to visualize the co-occurrence network of keywords. Results: Overall, 494 articles met the study inclusion criteria, with an average of 29.64 citations per article. Corresponding authors of published articles were mainly from China, the United States and Italy. Zhejiang University in China and Kyung Hee University in Korea were the most active institutions, while the Journal of Alzheimer’s Disease and Nutrients published the most articles in this field. Expected main search terms, “Parkinson disease” and “chain fatty-acids” were high-frequency keywords that indicate current and future research directions in this field. Conclusions: This bibliometric study helped researchers to identify the key topics and trends in the microbiome–gut–brain axis and dementia-related research. High-frequency keywords identified in this study reflect current trends and possible future directions in this field related to methodologies, mechanisms and populations of interest.

Background: Macau is a densely populated international tourist city. Compared to most tensely populated countries/territories, the prevalence and mortality of COVID-19 in Macau are lower. The experiences in Macau could be helpful for other areas to combat the COVID-19 pandemic. This article introduced the endeavours and achievements of Macau in combatting the COVID-19 pandemic. Method: Both qualitative and quantitative analysis methods were used to explore the work, measures, and achievements of Macau in dealing with the COVID-19 pandemic. Results: The results revealed that Macau has provided undifferentiated mask purchase reservation services, COVID-19 vaccination services to all residents and non-residents in Macau along with delivering multilingual services, in Chinese, English and Portuguese, to different groups of the population. To facilitate the travels of people, business and trades between Macau and mainland China, the Macau government launched the Macau Health Code System, which uses the health status declaration, residence history declaration, contact history declaration of the declarant to match various relevant backend databases within the health authority and provide a risk-related colour code operations. The Macau Health Code System connects to the Chinese mainland's own propriety health code system seamlessly, whilst effectively protecting the privacy of the residents. Macau has also developed the COVID-19 Vaccination Appointment system, the Nucleic Acid Test Appointment system, the Port and Entry/Exit Quarantine system, the medical and other supporting systems. Conclusion: The efforts in Macau have achieved remarkable results in COVID-19 prevention and control, effectively safeguarding the lives and health of the people and manifesting the core principle of \"serving the public\". The measures used are sustainable and can serve as an important reference for other countries/regions.Background: Macau is a densely populated international tourist city. Compared to most tensely populated countries/territories, the prevalence and mortality of COVID-19 in Macau are lower. The experiences in Macau could be helpful for other areas to combat the COVID-19 pandemic. This article introduced the endeavours and achievements of Macau in combatting the COVID-19 pandemic. Method: Both qualitative and quantitative analysis methods were used to explore the work, measures, and achievements of Macau in dealing with the COVID-19 pandemic. Results: The results revealed that Macau has provided undifferentiated mask purchase reservation services, COVID-19 vaccination services to all residents and non-residents in Macau along with delivering multilingual services, in Chinese, English and Portuguese, to different groups of the population. To facilitate the travels of people, business and trades between Macau and mainland China, the Macau government launched the Macau Health Code System, which uses the health status declaration, residence history declaration, contact history declaration of the declarant to match various relevant backend databases within the health authority and provide a risk-related colour code operations. The Macau Health Code System connects to the Chinese mainland's own propriety health code system seamlessly, whilst effectively protecting the privacy of the residents. Macau has also developed the COVID-19 Vaccination Appointment system, the Nucleic Acid Test Appointment system, the Port and Entry/Exit Quarantine system, the medical and other supporting systems. Conclusion: The efforts in Macau have achieved remarkable results in COVID-19 prevention and control, effectively safeguarding the lives and health of the people and manifesting the core principle of \"serving the public\". The measures used are sustainable and can serve as an important reference for other countries/regions.

Late-life depression (LLD) is a significant global public health challenge among older adults. Exploring central/influential symptoms with longitudinal study designs can enhance the efficacy of detection, early prevention, and interventions for LLD. This study aimed to identify key symptoms of LLD using a panel graphical vector autoregression (panel-GVAR) model based on longitudinal national survey data. Data from the China Health and Retirement Longitudinal Study (CHARLS) between 2013 and 2020, encompassing four waves, were utilized to construct a longitudinal depressive symptom network. Depressive symptoms were assessed using the 10-item Center for Epidemiological Studies Depression Scale (CESD-10). In expected influence (in-EI) and out expected influence (out-EI) were identified to characterize the interaction of symptoms within the temporal network, while expected influence (EI) was used to examine the interaction of symptoms in both the contemporaneous network and the between-subjects network. A total of 1393 older adults were assessed. A persistently significant increase in the prevalence of depression was observed over time. In the temporal network, \"restless sleep\" (CESD7) and \"could not get going\" (CESD10) were the most influential symptom and most influenced symptom, respectively. In both the contemporaneous network and the between-subjects network, \"felt depressed\" (CESD3) emerged as the most central symptom within the community of depressive symptoms. Given the challenges associated with treating LLD and its adverse effects on daily life for older adults, timely interventions targeting identified key symptoms may help prevent and mitigate depression in this population.

Background: The 2019 novel coronavirus disease (COVID-19) outbreak had a detrimental impact on the mental health of older adults. This study evaluated the central symptoms and their associations in the network of depressive symptoms and compared the network structure differences between male and female older adults in Hong Kong. Methods: Altogether, 3,946 older adults participated in this study. We evaluated the centrality indicators for network robustness using stability and accuracy tests, and examined the potential differences between the structure and connectivity of depression networks in male and female older adults. Results: The overall prevalence of depressive symptoms was 43.7% (95% CI=40.6-46.7%) in males, and 54.8% (95% CI=53.1-56.5%) in females (P<0.05). Sad Mood, Guilt, Motor problems and Lack of Energy were influential symptoms in the network model. Gender differences were found in the network global strength, especially in the following edges: Sad Mood--Guilt, Concentration--Guilt, Anhedonia--Motor, Lack of Energy--Suicide, Appetite--Suicide and Concentration--Suicide. Conclusions: Central symptoms in the depressive symptom network among male and female older adults may be prioritized in the treatment and prevention of depression during the pandemic.Background: The 2019 novel coronavirus disease (COVID-19) outbreak had a detrimental impact on the mental health of older adults. This study evaluated the central symptoms and their associations in the network of depressive symptoms and compared the network structure differences between male and female older adults in Hong Kong. Methods: Altogether, 3,946 older adults participated in this study. We evaluated the centrality indicators for network robustness using stability and accuracy tests, and examined the potential differences between the structure and connectivity of depression networks in male and female older adults. Results: The overall prevalence of depressive symptoms was 43.7% (95% CI=40.6-46.7%) in males, and 54.8% (95% CI=53.1-56.5%) in females (P<0.05). Sad Mood, Guilt, Motor problems and Lack of Energy were influential symptoms in the network model. Gender differences were found in the network global strength, especially in the following edges: Sad Mood--Guilt, Concentration--Guilt, Anhedonia--Motor, Lack of Energy--Suicide, Appetite--Suicide and Concentration--Suicide. Conclusions: Central symptoms in the depressive symptom network among male and female older adults may be prioritized in the treatment and prevention of depression during the pandemic.