BackgroundSevere mental disorders represent a major public health concern due to the high disability rates and substantial disease burden， which has garnered significant national attention and prompted their inclusion in public health project management systems. However， credible evidence regarding the current status of disease management and factors influencing disease stabilization among patients with severe mental disorders in Luzhou City， Sichuan Province， remains limited. ObjectiveTo investigate the current management status of patients with severe mental disorders in Luzhou City， Sichuan Province， and to analyze influencing factors of disease stabilization among patients under standardized care， so as to provide evidence-based insights for developing targeted management strategies to optimize clinical interventions for this patient population. MethodsIn March 2023， data were extracted from the Sichuan Mental Health Service Comprehensive Management Platform for patients with severe mental disorders in Luzhou City who received management between December 2017 and December 2022. Information on mental health service utilization and clinical status changes was collected. Trend analysis was conducted to evaluate temporal changes in key management indicators for severe mental disorders in Luzhou City. Logistic regression analysis was employed to identify factors influencing the disease stabilization or fluctuation of these patients. ResultsThis study enrolled a total of 20 232 patients. In Luzhou City， the stabilization rate and standardized management rate of severe mental disorders were 94.89% and 79.36% in 2017， respectively， which increased to 95.33% and 96.92% by 2022. The regular medication adherence rate rose from 34.42% in 2018 to 86.81% in 2022. In 2022， the regular medication adherence rate was 71.80% for schizophrenia， 55.26% for paranoid psychosis， and 51.43% for schizoaffective disorder. Multivariate analysis identified the following protective factors for disease stabilization： age of 18~39 years （OR=0.613， 95% CI： 0.409~0.918）， age of 40~65 years （OR=0.615， 95% CI： 0.407~0.931）， urban residence （OR=0.587， 95% CI： 0.478~0.720）， and regular medication adherence （OR=0.826， 95% CI： 0.702~0.973）. Risk factors for disease fluctuation included poor （OR=1.712， 95% CI： 1.436~2.040）， non-inclusion in care-support programs （OR=1.928， 95% CI： 1.694~2.193）， non-participation in community rehabilitation （OR=2.255， 95% CI： 1.930~2.634）， and intermittent medication adherence （OR=3.893， 95% CI： 2.548~5.946）. ConclusionThe stability rate， standardized management rate， and regular medication adherence rate of patients with severe mental disorders in Luzhou City have shown a year-by-year increase. Age， household registration status， economic condition， medication compliance， and community-based rehabilitation were identified as influencing factors for disease fluctuation in these patients. ［Funded by Luzhou Science and Technology Plan Project （number， 2022-ZRK-186）］

The traditional Chinese medicine （TCM） myocardial infarction （MI） unit is a standardized， regulated， and continuous integrated care unit guided by TCM theory and built upon existing chest pain centers or emergency care units. This unit emphasizes multidisciplinary collaboration and forms a restructured clinical entity without altering current departmental settings， offering comprehensive diagnostic and therapeutic services with full participation of TCM in the treatment of MI. Its core medical model is patient-centered and disease-focused， providing horizontally integrated TCM-based care across multiple specialties and vertically constructing a full-cycle treatment unit for MI， delivering prevention， treatment， and rehabilitation during the acute， stable， and recovery phases. Additionally， the unit establishes a TCM-featured education and prevention mechanism for MI to guide patients in proactive health management， reduce the incidence of myocardial infarction， and improve quality of life.

ObjectiveTo investigate the mechanism by which Huanglian Jiedutang （HLJDT） inhibits pyroptosis and neuroinflammation in Alzheimer's disease （AD） mice via the NOD-like receptor protein 3 （NLRP3）/cysteinyl aspartate-specific protease-1 （Caspase）-1/gasdermin D （GSDMD） pathway. MethodsThirty APP/PS1 double transgenic mice were randomly and evenly divided into the model group （model group）， the positive control group （Donepezil group， 0.65 mg·kg^-1）， and the HLJDT treatment group （HLJDT group， 5.2 g·kg^-1）. Ten C57BL/6 mice were assigned to the blank control group （control group）. The Morris water maze and novel object recognition tests were used to evaluate learning and memory abilities. Nissl staining was employed to observe the morphology， quantity， and distribution of neurons in the hippocampal region. Golgi staining was used to examine the morphology and density of neuronal dendritic spines in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was performed to detect the mRNA expression of neuroinflammation-related factors and genes in the NLRP3/Caspase-1/GSDMD pyroptosis pathway in the hippocampus. Western blot was used to detect the expression of postsynaptic density protein 95 （PSD95）， amyloid precursor protein （APP）， inflammatory factors including nuclear factor-κB （NF-κB）， phosphorylated NF-κB （p-NF-κB）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， as well as pyroptosis pathway-related proteins including NLRP3， Caspase-1， GSDMD， and GSDMD-N. ResultsCompared with the control group， the model group exhibited significantly decreased learning and memory abilities （P<0.01）， reduced numbers of neurons in the hippocampal CA3 region and dendritic spines in the hippocampal CA1 region （P<0.01）， and significantly increased hippocampal mRNA expression levels of NLRP3， Caspase-1， GSDMD， NF-κB， TNF-α， IL-1β， and IL-18 （P<0.01）. Protein levels of PSD95 were markedly decreased， while the expression levels of NLRP3， Caspase-1， GSDMD， p-NF-κB/NF-κB， TNF-α， IL-1β， and APP were significantly elevated （P<0.01）. Compared with the model group， both the Donepezil and HLJDT groups showed significantly improved learning and memory abilities （P<0.05， P<0.01）， increased numbers of hippocampal neurons in the hippocampal CA3 region and dendritic spines in the hippocampal CA1 region （P<0.01）， and significantly decreased hippocampal mRNA expression levels of NLRP3， Caspase-1， GSDMD， NF-κB， TNF-α， IL-1β， and IL-18 （P<0.05， P<0.01）. Protein levels of NLRP3， Caspase-1， GSDMD， p-NF-κB/NF-κB， TNF-α， IL-1β， and APP were significantly downregulated， while PSD95 expression was significantly upregulated （P<0.05， P<0.01）. There was no statistically significant difference in GSDMD-N levels in the Donepezil group， while GSDMD-N expression was significantly decreased in the HLJDT group （P<0.05）. ConclusionThis study confirms that HLJDT can improve learning and memory abilities in APP/PS1 double transgenic mice， and attenuate neuronal loss and synaptic damage， possibly through inhibition of pyroptosis via the NLRP3/Caspase-1/GSDMD pathway.

ObjectiveTo investigate the mechanism by which Huanglian Jiedutang （HLJDT） inhibits pyroptosis and neuroinflammation in Alzheimer's disease （AD） mice via the NOD-like receptor protein 3 （NLRP3）/cysteinyl aspartate-specific protease-1 （Caspase）-1/gasdermin D （GSDMD） pathway. MethodsThirty APP/PS1 double transgenic mice were randomly and evenly divided into the model group （model group）， the positive control group （Donepezil group， 0.65 mg·kg^-1）， and the HLJDT treatment group （HLJDT group， 5.2 g·kg^-1）. Ten C57BL/6 mice were assigned to the blank control group （control group）. The Morris water maze and novel object recognition tests were used to evaluate learning and memory abilities. Nissl staining was employed to observe the morphology， quantity， and distribution of neurons in the hippocampal region. Golgi staining was used to examine the morphology and density of neuronal dendritic spines in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was performed to detect the mRNA expression of neuroinflammation-related factors and genes in the NLRP3/Caspase-1/GSDMD pyroptosis pathway in the hippocampus. Western blot was used to detect the expression of postsynaptic density protein 95 （PSD95）， amyloid precursor protein （APP）， inflammatory factors including nuclear factor-κB （NF-κB）， phosphorylated NF-κB （p-NF-κB）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， as well as pyroptosis pathway-related proteins including NLRP3， Caspase-1， GSDMD， and GSDMD-N. ResultsCompared with the control group， the model group exhibited significantly decreased learning and memory abilities （P<0.01）， reduced numbers of neurons in the hippocampal CA3 region and dendritic spines in the hippocampal CA1 region （P<0.01）， and significantly increased hippocampal mRNA expression levels of NLRP3， Caspase-1， GSDMD， NF-κB， TNF-α， IL-1β， and IL-18 （P<0.01）. Protein levels of PSD95 were markedly decreased， while the expression levels of NLRP3， Caspase-1， GSDMD， p-NF-κB/NF-κB， TNF-α， IL-1β， and APP were significantly elevated （P<0.01）. Compared with the model group， both the Donepezil and HLJDT groups showed significantly improved learning and memory abilities （P<0.05， P<0.01）， increased numbers of hippocampal neurons in the hippocampal CA3 region and dendritic spines in the hippocampal CA1 region （P<0.01）， and significantly decreased hippocampal mRNA expression levels of NLRP3， Caspase-1， GSDMD， NF-κB， TNF-α， IL-1β， and IL-18 （P<0.05， P<0.01）. Protein levels of NLRP3， Caspase-1， GSDMD， p-NF-κB/NF-κB， TNF-α， IL-1β， and APP were significantly downregulated， while PSD95 expression was significantly upregulated （P<0.05， P<0.01）. There was no statistically significant difference in GSDMD-N levels in the Donepezil group， while GSDMD-N expression was significantly decreased in the HLJDT group （P<0.05）. ConclusionThis study confirms that HLJDT can improve learning and memory abilities in APP/PS1 double transgenic mice， and attenuate neuronal loss and synaptic damage， possibly through inhibition of pyroptosis via the NLRP3/Caspase-1/GSDMD pathway.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. Methods The study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including random forest (RF), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results (1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%.Conclusion Electronic nose combined with machine learning not only has the potential capabilities to differentiate the benign and malignant pulmonary nodules, but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.

ObjectiveTo observe the clinical efficacy of Shentong Zhuyutang combined with Dilongtang in the treatment of lumbar disc herniation （LDH） with Qi stagnation and blood stasis syndrome， and its effect on nucleus pulposus reabsorption and immune-inflammatory factors， exploring its therapeutic mechanism from the perspective of reabsorption. MethodsA total of 120 patients with LDH from the Fourth Clinical Medical College of Guangzhou University of Chinese Medicine， treated between June 2020 and January 2023， were randomly divided into the control group （52 cases， with 8 dropouts） and the observation group （49 cases， with 11 dropouts） according to a random number table. The control group received routine treatment， while the observation group was treated with Shentong Zhuyutang combined with Dilongtang in addition to routine treatment. Visual Analogue Scale （VAS）， Oswestry Disability Index （ODI）， Japanese Orthopaedic Association （JOA） score， and traditional Chinese medicine （TCM） syndrome score were measured before treatment and after 3 courses of treatment. Venous blood samples were collected for the determination of serological indexes. MR examination was performed during the 6-month follow-up to calculate the absorption rate. ResultsAfter treatment， both groups showed significant reductions in VAS， ODI， TCM syndrome score， serum tumor necrosis factor （TNF）-α， matrix metalloproteinase （MMP）-9， and vascular endothelial growth factor （VEGF） levels， and a significant increase in JOA score compared with pre-treatment values （P<0.05）. Compared with the control group， the observation group showed significantly lower VAS， ODI， TCM syndrome score， serum TNF-α， MMP-9， and VEGF levels， and a significantly higher JOA score （P<0.05）. The proportion of nucleus pulposus reabsorption in the observation group was 57.14% （28/49）， significantly higher than 21.15% （11/52） in the control group （χ²=6.161， P<0.05）. ConclusionShentong Zhuyutang combined with Dilongtang can effectively relieve pain， improve lumbar function， and alleviate TCM clinical symptoms in LDH patients with Qi stagnation and blood stasis syndrome. Imaging findings suggest that the treatment promotes the reabsorption of nucleus pulposus protrusion， while laboratory testing shows reduced serum levels of TNF-α， MMP-9， and VEGF， which contribute to the rehabilitation of patients.

The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.