Objective To investigate the cognition level and behavior compliance of blood pressure measurement in community residents and analyze the related influencing factors, and to provide evidence for community health management and blood pressure control. Methods A questionnaire survey was conducted to investigate 4470 community patients. Questionnaires included basic personal information，blood pressure measurement cognition, and blood pressure measurement behavior related issues. SPSS 19.0 was used to analyze the basic information, blood pressure measurement cognition, and pressure measurement behavior of the survey subjects. Logistic regression was performed to analyze relevant factors affecting blood pressure measurement cognition and behavior compliance. Results The overall cognitive compliance rate for blood pressure measurement among the visiting community patients was 31.52%. Age, education level, and chronic disease had a statistically significant impact on the cognitive knowledge (P<0.05). The overall behavior compliance rate of blood pressure measurement among the community patients was 23.69%. The cognition, age and education had a statistically significant impact on the overall behavior compliance rate of blood pressure measurement (P<0.05). Conclusion The cognitive level and standardized behavior of blood pressure measurement of community patients need to be improved. More attention should be paid to the elderly, low education level residents and community residents without chronic diseases, to promote community residents to form correct and standardized behavior of blood pressure measurement through health education.

Yin-yang, visceral manifestation, and ti-yong theories are the core theories of traditional Chinese medicine (TCM) and play a crucial role in its formation and development. With the continuous evolution of Chinese philosophy, TCM philosophy and theories have undergone significant influence, resulting in differing interpretations of the visceral manifestation of liver and mingmen across various historical periods by different medical practitioners. This paper focuses on the different understandings of the position of liver and mingmen, combining relevant philosophical images and TCM anatomical illustrations to deeply explore ancient medical theorists′ concepts regarding the four spatial directions of left, right, up, and down. The research reveals that ancient medical theorists′ conceptualization of spatial theory transitioned from an initial circular motion to a vertical movement, with the focus shifting from the upper part to the lower part. The primary reasons for these differences and changes could be explained by the varying emphasis on the ti-yong theory and differing focal points within the yin-yang theory. This study systematically examines the evolution of visceral manifestation theories related to liver and mingmen, highlights the shifts in physicians′ perspectives on spatial theory, and analyzes the influence of the ti-yong theory and yin-yang theory on these changes. The findings aim to provide a theoretical guide for advancing research and clinical application of spatial theory in TCM, thereby fostering the integration of TCM philosophy with medical theory.

ObjectiveGliomas in the motor functional area can damage the corticospinal tract (CST), leading to motor dysfunction. Currently, there is a lack of unified methods for evaluating the extent of CST damage, especially in patients with high surgical risk where the minimum distance from the lesion to the CST is less than 10 mm. This study aims to further clarify the classification method and clinical significance of CST morphological changes in these patients. MethodsThis retrospective study analyzed 109 high-risk functional area glioma patients who underwent neurosurgical treatment with preoperative diffusion tensor imaging (DTI) imaging and intraoperative neurostimulation guidance between 2014 and 2024. All patients had a lesion-to-tract distance (LTD) of less than 10 mm between the CST and the lesion. Preoperative DTI evaluation of CST involvement-induced morphological changes were reviewed. Patients were divided into 3 groups: 17 cases (15.6%) with symmetric CST morphology compared to the healthy side (CST symmetry), 48 cases (44.0%) with significant CST morphology changes compared to the healthy side (CST deformation), and 44 cases (40.4%) with CST overlap with the tumor (CST overlap). Then we classified patients according to preoperative assessment of tumor-induced morphological changes, and analyze postoperative motor function for each category. ResultsPostoperative pathology showed a significantly higher proportion of high-grade gliomas (HGG) in the CST overlap group compared to the other two groups (P=0.001). Logistic regression analysis showed that CST overlap was a predictor of HGG (P=0.000). The rate of total tumor resection in the CST deformation group and overlap group was lower than in the CST symmetric group (P=0.008). There was a total of 41 postoperative hemiplegic patients, with 4 cases (23.5%) in the CST symmetric group, 11 cases (22.9%) in the CST deformation group, and 26 cases (59.1%) in the CST overlap group. CST overlap with the tumor predicted postoperative hemiplegia (P=0.016). Two-way ANOVA analysis of the affected/healthy side and CST morphology groups showed significant main effects of CST grouping and healthy-affected side (P=0.017 and P=0.010), with no significant interaction (P=0.31). The fractional anisotropy (FA) value in the CST overlap group and the affected side was lower. A decrease in the FA value on the affected side predicted postoperative hemiplegia (sensitivity 69.2%, specificity 71.9%). ConclusionWe have established a method to predict postoperative hemiplegia in high-risk motor functional area glioma patients based on preoperative CST morphological changes. CST overlap leads to a decrease in CST FA values. This method can be used for precise patient management and aid in accurate preoperative surgical planning.

Objective: To analyze the space time characteristics of poor vision among primary and secondary school students in Chengdu, in order to provide the reference for formulating myopia prevention and control policies for students. Methods: The data relating to poor vision among primary and secondary school students in Chengdu from 2021 to 2023 were sourced from the Sichuan Students Physical Health Big Data Center. The districts and counties of Chengdu were divided into three circles, including the main urban area, suburban districts and counties, and suburban districts and counties. The Chi square test was used for inter group comparison, and the Cochran-Armitage test was used to analyze the trend of changes. Global and local Moran s I were used to analyze spatial clustering. Results: The detection rates of poor vision among primary and secondary school students in Chengdu from 2021 to 2023 were 62.47%, 61.61% and 60.78%, respectively, showing a decreasing trend ( Z=-32.01, P <0.01). For each year, the higher detection rate of poor vision among students was detected in the higher level of education, and differences were statistically significant ( χ 2=161 549.47, 173 471.87, 233 459.09, P <0.01). The rate of poor vision among primary and secondary school students gradually decreased from the central districts and counties of Chengdu to the surrounding districts and counties for each year, and the differences were statistically significant ( χ 2=299.20, 776.22, 633.16, P <0.01). The spatial autocorrelation analysis showed that the first circle of Chengdu City was mainly characterized by high-high agglomeration ( P <0.01), with the rate of poor vision among primary school students in Wuhou District in 2023 exhibiting a low-high anomaly. The third circle was mainly characterized by low-low aggregation ( P <0.01), while the spatial clusterings of the second circle was not significant ( P >0.05). Conclusions The myopia prevention and control work in Chengdu has achieved preliminary results. It should continue to consolidate existing achievements and implement targeted myopia prevention and control measures based on regional characteristics.

OBJECTIVE To determine the contents of 15 components in Aurantii Fructus Immaturus from different origins （Citrus aurantium， C. junos， C. aurantium Linn.， C. sinensis Osb.， C. sinensis）， screen differential components， and provide references for the quality evaluation of Aurantii Fructus Immaturus. METHODS HPLC method was adopted to determine the contents of synephrine， N-methyltyramine， 5，7-dihydroxychromone-7-neohesperidoside， neoponcirin， narirutin， naringin， hesperidin， neohesperidin， naringenin， hesperetin， sinensetin， nobiletin， tangeretin， 5-demethylnobiletin， and auraptene in 46 batches of Aurantii Fructus Immaturus from different origins. The determination was performed on Waters Symmetry C18 column with mobile phase consisted of acetonitrile-0.1% formic acid （gradient elution） at the flow rate of 1.0 mL/min； column temperature was set at 40 ℃ ， detection wavelength was 284 nm， and sample injection volume was 5 μL. The differences between different origins of Aurantii Fructus Immaturus were analyzed by cluster analysis， principal component analysis （PCA） and orthogonal partial least squares-discriminant analysis （OPLS-DA）， and differential components were screened. RESULTS The linear relationships of the aforementioned 15 components were all good within the tested mass concentration ranges （all r＞0.999 0）. The RSDs for precision， stability （24 h）， and repeatability tests were all less than 2.00%. The average recovery rate ranged from 91.1% to 103.9% （all RSDs＜3.10%）. Cluster analysis， PCA， and OPLS-DA revealed that C. sinensis Osb. and C. sinensis were clustered into one category， while C. aurantium，C. junos and C. aurantium Linn. were clustered into another category. The variable importance projection values for neohesperidin， auraptene， naringin， neoponcirin， tangeretin， hesperidin， sinensetin， and 5，7-dihydroxychromone-7-neohesperidoside were all greater than 1. CONCLUSIONS In this study， the contents of 15 components in Aurantii Fructus Immaturus from different origins are determined， and 8 differential components， including neohesperidin， auraptene， naringin， and neoponcirin， are screened out.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

OBJECTIVE To construct three-class （insufficient， normal， excessive） and two-class （insufficient， normal） models for predicting plasma concentration of valproic acid （VPA）， and compare the performance of these two models， with the aim of providing a reference for formulating clinical medication strategies. METHODS The clinical data of 480 patients who received VPA treatment and underwent blood concentration test at the Xi’an International Medical Center Hospital were collected from November 2022 to September 2024 （a total of 695 sets of data）. In this study， predictive models were constructed for target variables of three-class and two-class models. Feature ranking and selection were carried out using XGBoost scores. Twelve different machine learning algorithms were used for training and validation， and the performance of the models was evaluated using three indexes: accuracy， F1 score， and the area under the working characteristic curve of the subject （AUC）. RESULTS XGBoost feature importance scores revealed that in the three-class model， the importance ranking of kidney disease and electrolyte disorders was higher. However， in the two-class model， the importance ranking of these features significantly decreased， suggesting a close association with the excessive blood concentration of VPA. In the three-class model， Random Forest method performed best， with F1 score of 0.704 0 and AUC of 0.519 3 on the test set； while in the two-class model， CatBoost method performed optimally， with F1 score of 0.785 7 and AUC of 0.819 5 on the test set. CONCLUSIONS The constructed three-class model has the ability to predict excessive VPA blood concentration， but its prediction and model generalization abilities are poor； the constructed two-class model can only perform classification prediction for insufficient and normal blood concentration cases， but its model performance is stronger.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

The chemical constituents of the petroleum ether extract derived from the 90% ethanol extract of Elephantopus scaber were investigated. By silica gel column chromatography, C_(18), MCI column chromatography and semi-preparative high performance liquid chromatography, ten compounds were isolated. Their structures were identified as 3β-hydroxy-6β,7β-epoxytaraxeran-14-ene(1), 3β-hydroxyolean-12-en-28-oic acid(2), D-friedoolean-14-ene-3β,7α-diol(3), 3β-hydroxy-11α-methoxyolean-12-ene(4), 3β-hydroxyolean-11,13(18)-diene(5), 11α-hydroxy-β-amyrin(6), betulinic acid(7), 3β-hydroxy-30-norlupan-20-one(8), 6-acetonylchelerythrine(9), and 4',5'-dehydrodiodictyonema A(10) by analysis of the 1D NMR, 2D NMR, MS, and IR spectral data. Among them, compound 1 was a new triterpene and other compounds except compounds 2 and 7 were isolated from this plant for the first time.
Triterpenes/isolation & purification* ; Drugs, Chinese Herbal/isolation & purification* ; Molecular Structure ; Asteraceae/chemistry* ; Chromatography, High Pressure Liquid ; Magnetic Resonance Spectroscopy