Due to the moist environment in the mouth, there are many challenges that arise, such as difficult biofilm removal, short drug retention time, and low tissue repair efficiency, while treating dental caries, periodontal disease, and other oral diseases. As a biomimetic biomaterial, polydopamine (PDA) possesses multifunctional properties, including mussel-inspired adhesion and stimuli-responsive drug release. PDA adhesion properties originate from its surface catechol and amino functional groups, which maintain strong wettability in aqueous environments. With smart responsiveness encompassing photothermal, pH, and enzymatic stimuli, PDA enables controlled drug release under specific conditions. Additionally, PDA exhibits antibacterial, anti-inflammatory, and osteoblast-promoting functions, thus demonstrating significant application potential in the treatment of oral diseases. In hard tissue therapies, specifically for dental caries, PDA promotes enamel remineralization by inducing hydroxyapatite crystal growth and enhances dentin collagen mineralization through Ca2+ chelation while inhibiting cariogenic bacteria. In mandibular defect repair, functionalized PDA coatings on bone implants facilitate mesenchymal stem cell adhesion and differentiation, activate osteogenic signaling pathways, and synergistically promote vascularization to improve bone-implant integration. For soft tissue treatments, specifically for periodontitis, PDA alleviates alveolar bone resorption via antibacterial and anti-inflammatory effects coupled with osteoclast inhibition. In denture stomatitis management, PDA’s strong wet adhesion prolongs drug retention, while its photothermal effect and reactive oxygen generation provide both broad-spectrum antibacterial activity and wound healing promotion. This review summarizes PDA’s synthesis mechanisms and biological functions, with an emphasis on its therapeutic applications in oral diseases, providing innovative strategies for oral healthcare.

ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

Objective To explore the factors affecting the quality of psychological assistance hotline connections in Shaanxi Province, and to provide a basis for optimizing services. Methods A total of 149 calls with suicidal tendencies were included from January to March 2022, and data were collected by 31 trained assessors through standardized questionnaires (general information, suicide risk, emotional intensity, and wiring characteristics). Results The results showed that 56.38% of the callers were female, with age groups concentrated between ≤ 18 years old (29.53%) and 19-34 years old (43.62%). The call duration was mainly between 31 and 45 minutes (50.34%). Operators conducted a suicide risk assessment on the callers, with 38.9% having a comprehensive assessment, 38.9% having an incomplete assessment, and 22.1% having no assessment. The main mental disorders of the callers were depression (48.32%), anxiety (15.44%), and bipolar disorder (14.77%), with 25.50% having comorbidities of ≥ 2 disorders. Emotional scores were as follows: depression (4.11 ± 0.76), sadness (3.97 ± 1.03), and despair (3.78 ± 1.05). There were significant differences in depression, anger, despair, and sadness among the callers with different levels of danger (t=4.79, 3.35, 15.79, 4.24, all P<0.05). Women had higher levels of fear than men (t=3.10, P<0.01). The longer the call duration, the higher the level of despair (t=5.66, P<0.01). Multiple regression analysis showed that incomplete suicide risk assessment by operators (B=-2.36), general procedures for operators' connections (B=5.44), and technical factors (B=2.01) significantly affected the quality of psychological assistance hotlines (all P<0.05). Conclusion Callers with suicidal tendencies generally have serious mental and psychological problems and prominent negative emotions. Strengthening the suicide risk assessment ability of operators and standardizing processes and service attitudes are key to improving the quality of psychological assistance hotlines.

ObjectiveTo investigate the effects of modified Xiaoyaosan （JJXYS） on behavioral abnormalities and hippocampal mitochondrial quality control （MQC） in the rat model of post-myocardial infarction depression （PMD） and preliminarily explore its potential mechanism. MethodsA rat model of PMD was established by left anterior descending coronary artery ligation combined with chronic unpredictable mild stress （CUMS）. Rats were randomized into a control group， a model group， a fluoxetine （FLX， 10 mg·kg^-1） group， and low-， medium-， and high-dose JJXYS （JJXYS-L/M/H， 1.12， 2.24， 4.48 g·kg^-1， respectively） groups. Depressive-like behaviors were evaluated by body weight monitoring， sucrose preference test， open field test， and forced swimming test. Hematoxylin-eosin staining and Nissl staining were used to observe hippocampal histomorphology and neuronal changes. Enzyme-linked immunosorbent assay was conducted to determine the serum levels of 5-hydroxytryptamine （5-HT）， dopamine （DA）， interleukin-1 beta （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-alpha （TNF-α）. The mRNA levels of MQC-related genes including peroxisome proliferator-activated receptor-gamma coactivator-1 alpha （PGC-1α）， nuclear respiratory factor 1 （Nrf1）， and transcription factor A， mitochondrial （TFAM） in the hippocampal tissue were measured by real-time PCR. The expression of proteins related to the dynamin-related protein 1 （Drp1）/PTEN-induced putative kinase 1 （PINK1）/Parkin signaling pathway was determined by Western blot. ResultsCompared with the control group， the model group showed restricted body weight gain， aggravated depressive-like behaviors， declined serum 5-HT and DA levels， evident hippocampal neuronal damage and reduced Nissl bodies， as well as downregulated expression of MQC-related genes and proteins （P<0.05）. Compared with the model group， both FLX and JJXYS alleviated the above changes to varying degrees. Moreover， the JJXYS-M and JJXYS-H groups showed more pronounced effects， improving behavioral performance， restoring 5-HT and DA levels， alleviating hippocampal pathological injury， and upregulating the expression of PGC-1α/Nrf1/TFAM mRNA and Drp1/PINK1/Parkin signaling pathway-related proteins （P<0.05）. ConclusionJJXYS can significantly alleviate depressive-like behaviors and neurotransmitter imbalance in the rat model of PMD by regulating hippocampal MQC and upregulating the Drp1/PINK1/Parkin-related pathway. This study provides experimental evidence for the intervention of PMD with JJXYS.

Brain’s neural activities encompass both periodic rhythmic oscillations and aperiodic neural fluctuations. Rhythmic oscillations manifest as spectral peaks of neural signals, directly reflecting the synchronized activities of neural populations and closely tied to cognitive and behavioral states. In contrast, aperiodic fluctuations exhibit a power-law decaying spectral trend, revealing the multiscale dynamics of brain neural activity. In recent years, researchers have made notable progress in studying brain aperiodic dynamics. These studies demonstrate that aperiodic activity holds significant physiological relevance, correlating with various physiological states such as external stimuli, drug induction, sleep states, and aging. Aperiodic activity serves as a reflection of the brain’s sensory capacity, consciousness level, and cognitive ability. In clinical research, the aperiodic exponent has emerged as a significant potential biomarker, capable of reflecting the progression and trends of brain diseases while being intricately intertwined with the excitation-inhibition balance of neural system. The physiological mechanisms underlying aperiodic dynamics span multiple neural scales, with activities at the levels of individual neurons, neuronal ensembles, and neural networks collectively influencing the frequency, oscillatory patterns, and spatiotemporal characteristics of aperiodic signals. Aperiodic dynamics currently boasts broad application prospects. It not only provides a novel perspective for investigating brain neural dynamics but also holds immense potential as a neural marker in neuromodulation or brain-computer interface technologies. This paper summarizes methods for extracting characteristic parameters of aperiodic activity, analyzes its physiological relevance and potential as a biomarker in brain diseases, summarizes its physiological mechanisms, and based on these findings, elaborates on the research prospects of aperiodic dynamics.

Objective: Hundreds of countries have implemented lockdown policies to slow the spread of coronavirus disease-2019 (COVID-19), but the impact of these measures on maternal mental health is not well understood. Methods: This study integrated a stress-process model to examine the pathways from lockdown-related stressors to prenatal psychological outcomes, with COVID-19 coping strategies (COP) and self-efficacy in managing negative affect (NEG) as mediators and lockdown duration, hours on pandemic-related information, and number of pregnancies as moderators. Pregnant women in Shanghai completed the Regulatory Emotional Self-Efficacy Scale, COVID-19 Coping Scale, Depression, Anxiety, and Stress Scale-21. Structural equation modeling (SEM) was used to test and modify the hypothetical model, and moderated mediation and slope analyses were undertaken. Results: In the final SEM demonstrating satisfactory fit, three stressors—decreased household income, insufficient daily supplies, and acquired infections—showed positive direct relationships with NEG and COP. Acquired infections, NEG, and COP were identified as direct predictors of mental health outcomes. The relationship between these three stressors and mental health was mediated by NEG and COP. Additionally, the number of pregnancies moderated the mediating effect of COP; this effect was more pronounced among first-time pregnant women than those with multiple pregnancies. Conclusion This study provides insights into how lockdown measures impact psychological outcomes in pregnant women quarantined at home. Interventions aimed at increasing coping strategies may be more effective for primiparous women during future public health emergencies.

Objective: Hundreds of countries have implemented lockdown policies to slow the spread of coronavirus disease-2019 (COVID-19), but the impact of these measures on maternal mental health is not well understood. Methods: This study integrated a stress-process model to examine the pathways from lockdown-related stressors to prenatal psychological outcomes, with COVID-19 coping strategies (COP) and self-efficacy in managing negative affect (NEG) as mediators and lockdown duration, hours on pandemic-related information, and number of pregnancies as moderators. Pregnant women in Shanghai completed the Regulatory Emotional Self-Efficacy Scale, COVID-19 Coping Scale, Depression, Anxiety, and Stress Scale-21. Structural equation modeling (SEM) was used to test and modify the hypothetical model, and moderated mediation and slope analyses were undertaken. Results: In the final SEM demonstrating satisfactory fit, three stressors—decreased household income, insufficient daily supplies, and acquired infections—showed positive direct relationships with NEG and COP. Acquired infections, NEG, and COP were identified as direct predictors of mental health outcomes. The relationship between these three stressors and mental health was mediated by NEG and COP. Additionally, the number of pregnancies moderated the mediating effect of COP; this effect was more pronounced among first-time pregnant women than those with multiple pregnancies. Conclusion This study provides insights into how lockdown measures impact psychological outcomes in pregnant women quarantined at home. Interventions aimed at increasing coping strategies may be more effective for primiparous women during future public health emergencies.

Objective: Hundreds of countries have implemented lockdown policies to slow the spread of coronavirus disease-2019 (COVID-19), but the impact of these measures on maternal mental health is not well understood. Methods: This study integrated a stress-process model to examine the pathways from lockdown-related stressors to prenatal psychological outcomes, with COVID-19 coping strategies (COP) and self-efficacy in managing negative affect (NEG) as mediators and lockdown duration, hours on pandemic-related information, and number of pregnancies as moderators. Pregnant women in Shanghai completed the Regulatory Emotional Self-Efficacy Scale, COVID-19 Coping Scale, Depression, Anxiety, and Stress Scale-21. Structural equation modeling (SEM) was used to test and modify the hypothetical model, and moderated mediation and slope analyses were undertaken. Results: In the final SEM demonstrating satisfactory fit, three stressors—decreased household income, insufficient daily supplies, and acquired infections—showed positive direct relationships with NEG and COP. Acquired infections, NEG, and COP were identified as direct predictors of mental health outcomes. The relationship between these three stressors and mental health was mediated by NEG and COP. Additionally, the number of pregnancies moderated the mediating effect of COP; this effect was more pronounced among first-time pregnant women than those with multiple pregnancies. Conclusion This study provides insights into how lockdown measures impact psychological outcomes in pregnant women quarantined at home. Interventions aimed at increasing coping strategies may be more effective for primiparous women during future public health emergencies.

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence