Objective To analyze the distribution status of the end digits of standardized blood pressure measurement recordings in the clinic and the effectiveness of standardized blood pressure measurement for community hypertension screening. Methods The first visit blood pressure measurement data from the Community Health Service Center in Jing'an District, Shanghai from June 2023 to May 2024 were collected and analyzed. According to different measurement methods, the data were divided into two groups: standardized blood pressure measurement and conventional blood pressure measurement. SPSS 19.0 software was used for data analysis. The differences in the distribution balance of the end digits of blood pressure values and the detection rate of blood pressure elevation between the two different groups were analyzed. Results The frequency range of the end digits of blood pressure recorded values in the standardized pressure measurement group was 9.42% to 10.83%, and the detection rate of elevated blood pressure was 24.89%. The conventional pressure measurement group had a preference of the end digit ^"0^", and the detection rate of elevated blood pressure was only 2.12%. The results of multiple logistic regression analysis showed that gender, age, season, and different blood pressure measurement modes were all influencing factors for the detection rate of elevated blood pressure. Conclusion The standardized blood pressure measurement mode in the clinic is suitable for community hypertension screening and pressure measurement, with higher data quality than the conventional pressure measurement mode.

Objective To establish a stable and reliable sepsis model of rat after liver transplantation (LT) for clinical translational research and analyze its characteristics. Methods The "two-sleeve method" was used to establish the in situ LT model of SD rats, and the sepsis model was constructed through cecal ligation and puncture (CLP) at 3 d after the operation. SD rats were randomly divided into 3 groups: sham operation group (Sham group), LT group, and LT + CLP group, with 6 rats in each group. The changes in body weight, rectal temperature and survival rate were compared, and the sepsis score was used for evaluation. The levels of blood biochemical indicators [alanine aminotransferase (ALT), aspartate aminotransferase (AST), urea (Urea), creatinine (Cr), creatine kinase (CK), lactate dehydrogenase (LDH)] and inflammatory factors [interleukin (IL)-1β, IL-6, IL-10, tumor necrosis factor (TNF)-α] in each group were detected, and the pathological changes and cell apoptosis in different organs were observed. Results Compared with the Sham group, the body weight of the LT group and LT + CLP group decreased (all P<0.05). The rectal temperature of the LT + CLP group showed a continuous downward trend after the operation, the sepsis score increased sharply after the operation, and the survival rate dropped to 16.7%, and the differences between the Sham group, LT group and LT + CLP group were statistically significant (all P<0.05). The levels of ALT, AST, Urea, Cr, CK, LDH, and serum IL-1β, IL-6, IL-10 and TNF-α in the LT + CLP group were higher than those in the Sham group and LT group rats within 72 hours after the operation(all P<0.05). The pathological examination of the LT + CLP group showed severe tissue structure destruction, necrosis and infiltration of inflammatory cells in multiple organs, and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) staining showed an increased level of cell apoptosis in multiple organs. Conclusions Using liver transplantation combined with CLP, a stable animal model of liver transplantation infection is successfully established, which exhibits a high mortality rate, significant multi-organ damage and intense inflammatory response, providing an ideal animal model for transplantation infection research.

Background The contamination of public baths with Legionella pneumophila contamination has become a growing public health concern in recent years. However, research on its association with bacterial community characteristics in water samples remains limited. The integration of 16S rRNA sequencing and random forest modeling provides a new approach to elucidate the bacterial community characteristics of public bath water and their association with Legionella pneumophila contamination. Objective To investigate the bacterial community structure and diversity of public bath water in Shanghai, explore the association between Legionella pneumophila contamination and bacterial community characteristics, and identify key bacterial genera associated with contamination, thereby providing a scientific basis for formulating hygiene management regulations for public bath water. Methods From February to March 2023, water samples were collected from ten public baths in Shanghai which were selected based on business scale, regional distribution, and functional differences. Water quality parameters were evaluated, and the samples were categorized into Legionella-positive and Legionella-negative groups based on the detection results of Legionella pneumophila. The bacterial community structure, α-diversity, and β-diversity were analyzed using 16S rRNA sequencing. Redundancy analysis (RDA) was employed to examine the relationship between physicochemical factors and bacterial community diversity. A random forest model was employed to identify key bacterial genera distinguishing the two groups, with the importance of genera being evaluated based on the mean decrease accuracy (MDA). Results The oxygen consumption in the Legionella-positive group was significantly lower than that in the Legionella-negative group (mean values: 1.85 mg·L⁻¹ vs. 6.81 mg·L⁻¹, P< 0.05), while no significant differences were observed in other physicochemical indicators. The sequencing results revealed a total of 27 bacterial phyla and 454 bacterial genera, with Proteobacteria (63.00%) being the dominant phylum. The dominant genera included Pelomonas (8.50%), Acidovorax (8.13%), Mycobacterium (7.93%), and Acinetobacter (6.59%). The α-diversity analysis indicated that bacterial community richness (Chao1 and ACE indices) was significantly higher in the Legionella-positive group than in the Legionella-negative group (P<0.01). The β-diversity analysis showed no significant difference in the bacterial community structure between the two groups (P>0.05). The RDA analysis demonstrated that the bacterial community diversity was positively correlated with pH and negatively correlated with oxygen consumption and free residual chlorine. The RDA1 and RDA2 explained 23.92% and 21.30% of the bacterial community diversity, respectively. The random forest model identified 20 key genera significantly influencing the microbial community distribution between the two groups, including unclassified_Bradyrhizobiaceae (MDA=2.42), Meiothermus (MDA=2.37), and Flavihumibacter (MDA=2.26). Conclusion The diversity of bacterial communities in public bath water is influenced by pH, oxygen consumption, and free residual chlorine. Samples contaminated with Legionella pneumophila exhibit greater microbial richness and contain characteristic key bacterial genera that contribute to community differences. Machine learning random forest technology helps identify these distinctive key bacterial genera. The findings provide a basis for carrying out risk early warning strategies in such settings.

Background/Aims: Dysregulated cholesterol metabolism is a hallmark of hepatocellular carcinoma (HCC) that drives tumor initiation and progression. However, clinical targeting of cholesterol metabolism has yielded limited benefits due to stringent feedback in tumor cells. Identifying a central mediator capable of restoring cholesterol homeostasis within the cell’s intrinsically fine-tuned regulatory framework is urgently needed. Methods: We integrated a proteomic dataset from patients with cholesterol-dysregulated HCC into a global cholesterol metabolic regulatory network to identify potential therapeutic targets for disrupted cholesterol homeostasis. The prognostic significance of the candidate targets was further validated in an independent cohort through immunohistochemistry. Functional and mechanistic studies were conducted in vitro using HCC cell lines and in vivo using mouse models. The pharmacological efficacy of the candidate agent was evaluated in both subcutaneous and orthotopic HCC mouse models. Results: ER lipid raft-associated 1 (ERLIN1), a pivotal regulator of cholesterol metabolism reprogramming, was identified as an independent favorable prognostic indicator in HCC. ERLIN1 constrains HCC progression both in vitro and in vivo by stabilizing the INSIG1–SCAP–SREBP2 axis and maintaining the metabolic balance of intracellular cholesterol. Under hypoxia, impaired factor-inhibiting hypoxia-1-dependent hydroxylation of ASB11 at asparagine residues 90 and 92 enhances ASB11-mediated ERLIN1 degradation. Pharmacological targeting of this axis using zoledronic acid (ZoA) attenuated HCC progression by weakening the ASB11–ERLIN1 interaction and restoring cholesterol homeostasis. Conclusions ERLIN1 represents a druggable metabolic vulnerability in cholesterol-dysregulated HCC. Targeting the ASB11–ERLIN1 axis with the clinically approved ZoA reestablishes cholesterol homeostasis and offers a promising therapeutic strategy to overcome the current limitations of cholesterol-targeted HCC therapies.

Based on the traditional Chinese medicine （TCM） theories of body fluid metabolism and turbid phlegm obstructing the orifices， and drawing on recent advances in cerebrospinal fluid-interstitial fluid （CSF-ISF） exchange， glymphatic clearance， and extracellular matrix （ECM） regulation， this article discusses the possible scientific connotation of "invisible phlegm" from the perspectives of pathogenesis， clinical manifestations， and therapeutic implications. Impaired brain fluid exchange may lead to reduced clearance， the retention of metabolic wastes and pathological proteins. Abnormal ECM remodeling may further disrupt molecular diffusion and local microenvironmental homeostasis， resulting in a pathological process characterized by slowed fluid movement， reduced clearance， and abnormal retention. This process bears a certain functional resemblance to the TCM pathogenesis of impaired distribution of body fluids， endogenous formation of turbid phlegm and obstruction of the brain orifices， and may also be associated with manifestations such as a clouded sensation in the head， cognitive abnormalities， and emotional disturbances. On this basis， the potential effects of certain phlegm-dissolving Chinese medicines in improving brain clearance function and extracellular microenvironmental homeostasis warrant further investigation. We therefore propose that， the "invisible phlegm" of TCM in brain tissue may manifest as a pathological retention state characterized by restricted fluid exchange， impaired clearance function， and extracellular microenvironmental imbalance. This perspective may provide a new avenue for investigating TCM treatment of neurological and psychiatric disorders from the perspective of phlegm.

Based on the traditional Chinese medicine （TCM） theories of body fluid metabolism and turbid phlegm obstructing the orifices， and drawing on recent advances in cerebrospinal fluid-interstitial fluid （CSF-ISF） exchange， glymphatic clearance， and extracellular matrix （ECM） regulation， this article discusses the possible scientific connotation of "invisible phlegm" from the perspectives of pathogenesis， clinical manifestations， and therapeutic implications. Impaired brain fluid exchange may lead to reduced clearance， the retention of metabolic wastes and pathological proteins. Abnormal ECM remodeling may further disrupt molecular diffusion and local microenvironmental homeostasis， resulting in a pathological process characterized by slowed fluid movement， reduced clearance， and abnormal retention. This process bears a certain functional resemblance to the TCM pathogenesis of impaired distribution of body fluids， endogenous formation of turbid phlegm and obstruction of the brain orifices， and may also be associated with manifestations such as a clouded sensation in the head， cognitive abnormalities， and emotional disturbances. On this basis， the potential effects of certain phlegm-dissolving Chinese medicines in improving brain clearance function and extracellular microenvironmental homeostasis warrant further investigation. We therefore propose that， the "invisible phlegm" of TCM in brain tissue may manifest as a pathological retention state characterized by restricted fluid exchange， impaired clearance function， and extracellular microenvironmental imbalance. This perspective may provide a new avenue for investigating TCM treatment of neurological and psychiatric disorders from the perspective of phlegm.

ObjectiveTo explore the listed varieties and prescription characteristics of Chinese patent medicines for stroke in China， explore the medication rules of Chinese medicine for stroke， and provide guidance for further clinical research and development of Chinese patent medicines. MethodsExcel 2021 and the Ancient and Modern Medical Record Cloud Platform （V2.3.5） were used to systematically mine and analyze the varieties and prescriptions of Chinese patent medicines for stroke in China. ResultsA total of 244 Chinese patent medicines （two for different dosage forms of the same prescription）， 1 736 approval documents for Chinese patent medicines， 792 manufacturers， and 83 varieties of protected Chinese patent medicines were finally included in the database. The top three dosage forms were capsules （75）， pills （53）， and tablets （42）. There were 28 Chinese patent medicines for stroke in the National Essential Drug Catalogue （2018）， 129 in the National Essential Medical Insurance， Industrial Injury Insurance and Maternity Insurance Drug Catalogue （2023）， and 4 in the National Non-prescription Drug Catalogue. Among the 138 prescriptions screened out， Chinese patent medicines mainly treated stroke patients with the syndrome of Qi deficiency and blood stasis. The top three most frequent medicinal herbs were Chuanxiong Rhizoma （63）， Pheretima （47）， and Salviae Miltiorrhizae Radix et Rhizoma （47）. The medicinal herbs used were mainly warm， pungent， with the meridian tropism to the liver meridian. The correlation analysis showed that the herb pair with the highest support was Astragali Radix-Chuanxiong Rhizoma， and that with the highest confidence was Carthami Flos-Chuanxiong Rhizoma. Five herb combinations were identified based on the cluster analysis. ConclusionThe Chinese patent medicines for stroke mainly treat patients with the syndrome of Qi deficiency and blood stasis. The medicinal herbs used in the prescriptions mainly have the functions of activating blood and resolving stasis， extinguishing wind and stopping convulsions. Drug compatibility usually focuses on activating blood and resolving stasis， as well as expelling phlegm and opening orifices. This review of the varieties and prescription characteristics of Chinese patent medicines for stroke helps optimize clinical decision-making， guide drug research and development， promote medical research and scientific progress， and provide more effective support and guarantee for the treatment of stroke patients.

Animal models combining disease and syndrome are important research tools to explore the nature of traditional Chinese medicine (TCM) syndromes. At present, the construction and evaluation methods of animal models have preliminarily established the foundation for standardized development. Qi-yin deficiency syndrome is a common type of TCM syndrome in cardiovascular diseases. It is an important pathogenic factor causing the onset, pathological damage, and chronic nature of cardiovascular diseases, as well as triggering other illnesses. The establishment of an animal model of cardiovascular disease with the characteristics of Qi-yin deficiency, along with an objective and standardized evaluation system, has become an important part of modern cardiovascular disease research. In recent years, research on the construction and evaluation of animal models of heart Qi-yin deficiency syndrome has increased, but the construction methods and evaluation criteria vary. Compared with other animal models, the literature is limited, lacking statistics and overall analysis. Therefore, based on the scientific connotation of heart Qi-yin deficiency syndrome, this article systematically reviews the evaluation system of its animal model, covering multidimensional methods such as macroscopic characterization assessment, physicochemical indicators and objective evaluation, and syndrome differentiation based on prescriptions. The specific model construction strategies are described, including single-factor induction methods (sleep deprivation, chronic intermittent hypoxia, arterial occlusion, high-salt feeding) and the compound-factor induction methods (sleep deprivation combined with drug method, chronic intermittent hypoxia combined with drug method, exhaustive swimming combined with drug method). Meanwhile, application examples of each model in the research are listed, the existing problems in the current model construction and evaluation are analyzed, and optimization directions are proposed, such as promoting the compound factor induction strategy and improving the objectivity of the evaluation criteria. This article aims to provide theoretical references for constructing an animal model of heart Qi-yin deficiency syndrome that conforms to TCM characteristics, and thereby laying a scientific foundation for the prevention and treatment of cardiovascular diseases with TCM.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Objective To investigate the sputum metabolic profiles of patients with occupational coal workers' pneumoconiosis (CWP) by an untargeted metabolomics method, and to identify relevant differential metabolic pathways and potential biomarkers. Methods A total of 12 male patients with stage Ⅰ CWP were selected as the CWP group, and 16 healthy male individuals were selected as the control group, using a judgmental sampling method. Sputum metabolites of individuals in both groups were detected to perform non-targeted metabolomic analysis using the ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Differential metabolites (DMs) and their pathways were screened using principal component analysis, partial least squares discriminant analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Potential biomarkers were analyzed and identified via the receiver operating characteristic curve (ROC). Results There were apparent metabolic alterations observed in sputum of CWP patients compared with healthy controls. In the positive ion mode, a total of 42 DMs were identified in sputum from CWP patients, including 19 downregulated and 23 upregulated metabolites. In the negative ion mode, a total of 25 DMs were identified in sputum from CWP patients, including 16 downregulated and 9 upregulated metabolites. KEGG enrichment analysis of sputum from CWP patients showed that seven DMs pathways were enriched in ABC transporters, histidine metabolism, phenylalanine metabolism, arachidonic acid metabolism, linoleic acid metabolism, purine metabolism, and oxidative phosphorylation, involving 26 DMs. ROC analysis indicated that 16(R)-hydroxyarachidonic acid, pyrophosphate, and 2-hydroxyphenylacetate of these 26 DMs may serve as potential biomarkers for CWP. Conclusion Sputum metabolomic profiles were altered in CWP patients compared with healthy controls. The potential biomarkers of CWP prevention and treatment are 16(R)-hydroxyarachidonic acid, pyrophosphate, and 2-hydroxyphenylacetate.