Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

Nanoparticle delivery systems have good application prospects in the field of precision therapy, but the preparation process of nanomaterial has problems such as short in vivo circulation time, easy recognition, and clearance by the immune system in the body. In recent years, biomimetic nanoparticle delivery systems mediated by natural cell membranes have become a research hotspot to address these issues. The natural membrane biomimetic nanoparticle delivery system cleverly integrates the advantages of natural biofilm "autologous" and "artificial" functional carriers by using endogenous cell membranes to modify the surface of nanocarriers, endowing them with characteristics such as tumor targeting, low immunogenicity, and long blood circulation. Currently, biomimetic nanoparticle delivery systems have been used in the treatment of malignant tumors, cardiovascular diseases, bacterial infections, and other diseases. This paper analyzes the development status and current research hotspots of natural cell membrane camouflaged biomimetic nanoparticle delivery systems mainly reviews the latest research progress of red blood cell membrane camouflaged biomimetic nanoparticle delivery systems in the field of disease treatment in recent years. It focuses on exploring the advantages, future development prospects, and limitations of biomimetic nanoparticle delivery systems based on red blood cell membrane camouflage in improving drug delivery, to provide a reference for the in-depth research and development of this system.

ObjectiveTo develop a predictive model and application for spontaneous passage of common bile duct stones using automated machine learning algorithms given the complexity of treatment decision-making for patients with common bile duct stones， and to reduce unnecessary endoscopic retrograde cholangiopancreatography （ERCP） procedures. MethodsA retrospective analysis was performed for the data of 835 patients who were scheduled for ERCP after a confirmed diagnosis of common bile duct stones based on imaging techniques in Changshu First People’s Hospital （dataset 1） and Changshu Traditional Chinese Medicine Hospital （dataset 2）. The dataset 1 was used for the training and internal validation of the machine learning model and the development of an application， and the dataset 2 was used for external testing. A total of 22 potential predictive variables were included for the establishment and internal validation of the LASSO regression model and various automated machine learning models. The area under the receiver operating characteristic curve （AUC）， sensitivity， specificity， and accuracy were used to assess the performance of models and identify the best model. Feature importance plots， force plots， and SHAP plots were used to interpret the model. The Python Dash library and the best model were used to develop a web application， and external testing was conducted using the dataset 2. The Kolmogorov-Smirnov test was used to examine whether the data were normally distributed， and the Mann-Whitney U test was used for comparison between two groups， while the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. ResultsAmong the 835 patients included in the study， 152 （18.20%） experienced spontaneous stone passage. The LASSO model achieved an AUC of 0.875 in the training set （n=588） and 0.864 in the validation set （n=171）， and the top five predictive factors in terms of importance were solitary common bile duct stones， non-dilated common bile duct， diameter of common bile duct stones， a reduction in serum alkaline phosphatase （ALP）， and a reduction in gamma-glutamyl transpeptidase （GGT）. A total of 55 models were established using automated machine learning， among which the gradient boosting machine （GBM） model had the best performance， with an AUC of 0.891 （95% confidence interval： 0.859‍ ‍—‍ ‍0.927）， outperforming the extreme randomized tree mode， the deep learning model， the generalized linear model， and the distributed random forest model. The GBM model had an accuracy of 0.855， a sensitivity of 0.846， and a specificity of 0.857 in the test set （n=76）. The variable importance analysis showed that five factors had important influence on the prediction of spontaneous stone passage， i.e.， were solitary common bile duct stones， non-dilated common bile duct， a stone diameter of <8 mm， a reduction in serum ALP， and a reduction in GGT. The SHAP analysis of the GBM model showed a significant increase in the probability of spontaneous stone passage in patients with solitary common bile duct stones， non-dilated common bile duct， a stone diameter of <8 mm， and a reduction in serum ALP or GGT. ConclusionThe GBM model and application developed using automated machine learning algorithms exhibit excellent predictive performance and user-friendliness in predicting spontaneous stone passage in patients with common bile duct stones. This application can help avoid unnecessary ERCP procedures， thereby reducing surgical risks and healthcare costs.

ObjectiveTo identify the main chemical constituents of Anmeidan （AMD） and to explore the mechanism of AMD in regulating the extracellular signal-regulated kinase 1/2 （ERK1/2）/mitogen-activated protein kinase （MAPK）-interacting serine/threonine-protein kinase （MNK）/eukaryotic translation initiation factor 4E （eIF4E） signaling pathway to improve circadian rhythm disturbances in insomnia rats. MethodsThe main chemical constituents of AMD were identified using ultra-high-performance liquid chromatography-linear ion trap-electrostatic orbital trap mass spectrometry （UPLC-LTQ/Orbitrap/MS） in combination with reference standards. Sixty male Sprague-Dawley （SD） rats were randomly divided into control， model， melatonin， and AMD low-， medium-， and high-dose groups， with 10 rats in each group. Except for the control group， all rats were administered p-chlorophenylalanine via intraperitoneal injection to establish an insomnia model. The activity-rest rhythm of rats was assessed using the open field test and circadian rhythm test. Hematoxylin-eosin （HE） staining and Nissl staining were used to observe structural changes in hypothalamic neurons. Immunofluorescence， real-time quantitative polymerase chain reaction （Real-time PCR）， and Western blot analysis were employed to detect mRNA and protein expression levels of ERK1/2， MNK， and eIF4E in the hypothalamus. ResultsA total of 50 chemical components， including flavonoids， phenylpropanoids， triterpenoid saponins， alkaloids， and lignans， were identified in AMD. Compared with the control group， the model group exhibited significantly increased total distance traveled， average speed， central area residence time， and cumulative rearing time （P<0.01）， as well as prolonged cumulative activity time and total activity time in both light and dark phases （P<0.01）. Hypothalamic neurons in the model group were sparsely arranged， reduced in number， and exhibited nuclear disappearance or nucleolar rupture， with a significantly increased apoptosis index （P<0.01）. The cytoplasm appeared turbid， Nissl body staining was lighter， and the Nissl body apoptosis index was significantly increased （P<0.01）. The mRNA expression levels of ERK1/2， MNK， and eIF4E were significantly decreased （P<0.01）， along with a significant reduction in protein expression levels of ERK1/2， phosphorylated ERK1/2 （p-ERK1/2）， MNK， phosphorylated MNK （p-MNK）， eIF4E， and phosphorylated eIF4E （p-eIF4E） （P<0.01）. Compared with the model group， the total distance， average speed， central area residence time and body upright cumulative time of the AMD high-dose group were significantly reduced （P<0.01）. The total distance， average speed and body upright cumulative time of the AMD medium-dose group were significantly reduced （P<0.01）. The cumulative time of light activity and total time of activity in each dose group of AMD were significantly shortened （P<0.01）. The cumulative time of dark activity in the high-dose group of AMD was prolonged （P<0.01）. The neurons in the middle and high dose groups of AMD were closely arranged， the number of neurons increased， and the apoptosis index of hypothalamic cells decreased significantly （P<0.05， P<0.01）. The cytoplasm of the low， middle and high dose groups of AMD was clear， the color of Nissl body became darker， and the apoptosis index of Nissl body decreased significantly （P<0.01）. The expression of ERK1/2， MNK and eIF4E mRNA and protein in the hypothalamus of the middle and high dose groups of AMD increased significantly （P<0.05， P<0.01）. ConclusionAMD primarily contains 50 chemical constituents， including flavonoids， phenylpropanoids， and triterpenoid saponins. It exhibits a "synergistic enhancement" effect through multiple components and multiple pathways to improve insomnia. AMD ameliorates circadian rhythm disturbances in p-chlorophenylalanine-induced insomnia rats by upregulating ERK1/2/MNK/eIF4E signaling pathway-related proteins.

Traditional Chinese Medicine (TCM), as a treasure of the Chinese nation, plays a significant role in maintaining public health. In 2019, the Central Committee of the Communist Party of China and the State Council proposed for the first time the establishment of a TCM registration and evaluation evidence system that integrates TCM theory, "personal experience" and clinical trials (referred to as the "Three-in-One" System) to promote the inheritance and innovation of TCM. Subsequently, the National Medical Products Administration issued several guiding principles to advance the improvement and implementation of this system. Owing to the complexity of its implementation, there are still differing understandings within the TCM industry regarding the positioning of the "Three-in-One" Registration and Evaluation Evidence System, as well as the connotation and value orientation of the "personal experience." To address this, Academician WANG Qi, President of the TCM Association, China International Exchange and Promotion Association for Medical and Healthcare and TCM master, led a group of academicians, TCM masters, TCM pharmacology experts and clinical TCM experts to convene a "Seminar on Promoting the Implementation of the ′Three-in-One′ Registration and Evaluation Evidence System for Chinese Medicinals." Through extensive discussions, an expert consensus was formed, clarifying the different roles of the TCM theory, "personal experience" and clinical trials within the system. It was further emphasized that the "personal experience" is the core of this system, and its data should be derived from clinical practice scenarios. In the future, the improvement of this system will require collaborative efforts across multiple fields to promote the high-quality development of the Chinese medicinal industry.

Neurofibromatosis type 1 (NF1) presents with a diverse range of symptoms that can affect the skin, bones, eyes, central nervous system, and other organs. This article reports the diagnosis and treatment process of a patient with NF1 complicated by bilateral severe-to-profound sensorineural hearing loss. Genetic testing revealed a heterozygous variant of NF1 NM_ 000267.3: c.4054_ 4058del(p.Ser1352LeufsTer20, supporting the diagnosis of NF1. After thorough evaluation, a right cochlear implantation was performed, yielding satisfactory postoperative results. This case suggests that NF1 patients may exhibit phenotypic heterogeneity and atypicality, providing a reference for clinicians in the diagnosis and treatment of such patients.

OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors， thereby providing reference for hospital pharmacy management. METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected. High-use days were defined as the 75th percentile of outpatient budesonide usage， and a corresponding dataset was established. The prediction task was formulated as a classification problem， and three ensemble learning models were developed： Random Forest， Extreme Gradient Boosting （XGBoost）， and Histogram-based Gradient Boosting Classifier. Model performance was evaluated using accuracy， precision， recall， F1-score， and log-loss. Model interpretability was analyzed using Shapley Additive Explanations （SHAP）. RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance （accuracy＝0.75， F1-score＝0.48）， followed by XGBoost （accuracy＝0.74， F1-score＝0.43） and Random Forest （accuracy＝0.72， F1-score＝0.22）. SHAP results suggested that the prediction results of the last two models have the highest correction. CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide， with the Histogram- based Gradient Boosting Classifier demonstrating the best predictive performance. Low temperature， high humidity， and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.

Objective: To investigate the knowledge, attitudes and practice related to salt reduction among residents in Xicheng District, Beijing Municipality, and to analyze the influencing factors of salt reduction practice, so as to provide the evidence for formulating salt reduction strategies. Methods: In July 2023, permanent residents aged 18-79 years in Xicheng District were selected using the multistage stratified random sampling method and probability proportionate to size sampling method. Data on demographic information, history of chronic diseases, salt intake, as well as knowledge, attitudes, and practices regarding salt reduction were collected through questionnaire surveys. The residents' salt intake excess rate, salt reduction awareness rate, salt reduction attitudes support rate, and salt reduction practice rate were analyzed. The influencing factors of salt reduction practice were analyzed by a multivariable logistic regression model. Results: Totally 6 360 questionnaires were allocated, and 6 211 valid questionnaires were recovered, with an effective recovery rate of 97.66%. Among the respondents, 3 022 (48.66%) were males and 3 189 (51.34%) were females, with a mean age of (46.80±15.10) years. Excessive salt intake was identified in 2 111 individuals, with an excess rate of 33.99%. Knowledge awareness of salt reduction was observed in 4 187 participants, with an awareness rate of 67.41%. Supportive attitudes were reported by 5 636 participants, with a support rate of 90.74%. And salt reduction practices were adopted by 3 152 participants, with a practice rate of 50.75%. The multivariable logistic regression analysis revealed that female (OR=1.397, 95%CI: 1.257-1.553), aged 40-79 years (40-<60 years, OR=1.290, 95%CI: 1.141-1.459; 60-79 years, OR=1.301, 95%CI: 1.114-1.519, having chronic diseases (OR=1.826, 95%CI: 1.582-2.108), awareness of salt reduction (OR=1.695, 95%CI: 1.511-1.901), and a supportive attitude towards salt reduction (OR=6.235, 95%CI: 4.900-7.933) were promoting factors for residents' salt reduction practice. Conclusions Residents in Xicheng District demonstrated high awareness and supportive attitudes regarding salt reduction, yet the actual practice rate was relatively low. Factors influencing salt reduction practice included gender, age, chronic disease, salt reduction knowledge and attitude.

BACKGROUND: There are few multi-city studies on the association between temperature and mortality in basin climates. This study was based on the Sichuan Basin in southwest China to assess the association of basin temperature with non-accidental mortality in the population and with the temperature-related mortality burden. METHODS: Daily mortality data, meteorological and air pollution data were collected for four cities in the Sichuan Basin of southwest China. We used a two-stage time-series analysis to quantify the association between temperature and non-accidental mortality in each city, and a multivariate meta-analysis was performed to obtain the overall cumulative risk. The attributable fractions (AFs) were calculated to access the mortality burden attributable to non-optimal temperature. Additionally, we performed a stratified analyses by gender, age group, education level, and marital status. RESULTS: A total of 751,930 non-accidental deaths were collected in our study. Overall, 10.16% of non-accidental deaths could be attributed to non-optimal temperatures. A majority of temperature-related non-accidental deaths were caused by low temperature, accounting for 9.10% (95% eCI: 5.50%, 12.19%), and heat effects accounted for only 1.06% (95% eCI: 0.76%, 1.33%). The mortality burden attributable to non-optimal temperatures was higher among those under 65 years old, females, those with a low education level, and those with an alternative marriage status. CONCLUSIONS Our study suggested that a significant association between non-optimal temperature and non-accidental mortality. Those under 65 years old, females, and those with a low educational level or alternative marriage status had the highest attributable burden.
Female ; Humans ; China/epidemiology* ; Cities ; Cold Temperature ; Hot Temperature ; Mortality ; Temperature ; Time Factors ; Middle Aged ; Male

italic>Salvia miltiorrhiza, a commonly used traditional Chinese medicine, has been widely recognized for its blood-activating and stasis-removing properties in the clinical treatment of cardiovascular and cerebrovascular diseases. The synthesis and regulatory mechanism of tanshinones, the key active constituents of Salvia miltiorrhiza, have been a hot topic of research. The paper summarized the research findings on the regulation of tanshinone biosynthesis by transcription factors such as AP2/ERF, bHLH, MYB, bZIP, and WRKY in recent years. The review identifies the existing issues in the transcriptional regulation studies of Salvia miltiorrhiza and discusses the research direction of transcription factors in the regulation of tanshinone biosynthesis, providing a theoretical basis for the further discovery and utilization of functional genes involved in the regulation of tanshinone bioactive constituents.