Objective: To examine the relationship between self-management behaviors and time perspective among patients with comorbid diabetes, so as to provide the evidence for improving self-management behaviors among patients with comorbid diabetes. Methods: The patients with comorbid diabetes who were registered in the chronic disease health management system of Minhang District, Shanghai Municipality in 2021, followed up regularly, and lived in Meilong Town were recruited. Demographic information and family history of diabetes were collected through questionnaire surveys. Time perspective and self-management behaviors were assessed using the Zimbardo Time Perspective Inventory and Diabetes Self-Management Behavior Scale, respectively. The relationship between self-management behaviors and time perspective was analyzed using a multivariable ordinal logistic regression model. Results: A total of 907 patients with comorbid diabetes were enrolled, including 472 males (52.04%) and 435 females (47.96%). There were 652 cases aged 65 years and above, accounting for 71.89%. In terms of the types of time perspective, 280 patients were future-oriented (30.87%), 236 were balanced (26.02%), 162 were sensation-seeking (17.86%), 123 were fatalistic (13.56%), and 106 were negative (11.69%). In terms of the self-management behaviors, 46 patients were good (5.07%), 643 were moderate (70.89%), and 218 were poor (24.04%). Multivariable ordinal logistic regression analysis showed that after adjusting for age, gender, educational level, marital status, occupation status, monthly income, and family history of diabetes, the patients with comorbid diabetes who had a future-oriented time perspective had better self-management behaviors (OR=1.874, 95%CI: 1.204-2.915). Conclusion The self-management behaviors among patients with comorbid diabetes are moderate to poor, and patients with a future-oriented time perspective can better engage in self-management behaviors.

To introduce the general thinking, guidelines, work objectives and elaboration process of the general technical requirements adopted by volume Ⅳ of the Chinese Pharmacopoeia 2025 Edition, and to summarize and figure out the main characteristics on dosage forms, physico-chemical testing, microbial and biological testing, reference standards and guidelines The newly revised general chapters of pharmacopoeia give full play to the normative and guiding role of the Chinese Pharmacopoeia standard, track the frontier dynamics of international drug regulatory science and the elaboration of monographs, expand the application of state-of-the-art technologies, and steadily promote the harmonization and unification with the ICH guidelines； further enhance the overall capacity of TCM quality control, actively implement the 3 R principles on animal experiments, and practice the concept of environmental-friendly； replace and/or reduce the use of toxic and hazardous reagents, strengthen the requirements of drug safety control This paper aims to provide a full-view perspective for the comprehensive, correct understanding and accurate implementation of general technical requirements included in the Chinese Pharmacopoeia 2025 Edition.

Objective: To provide reference for the correct understanding and accurate implementation of the general chapters of physical and chemical analysis in the Chinese Pharmacopoeia 2025 Edition Volume Ⅳ.
Methods: Introduce the main characteristics and content of the additions and revisions of the general chapters of physical and chemical analysis in the Chinese Pharmacopoeia 2025 Edition Volume Ⅳ.
Results: The general chapters of physical and chemical analysis in the Chinese Pharmacopoeia 2025 Edition are more harmonized with the relevant guidelines of the ICH Q series, and the inclusion of advanced and mature instrument analysis technology standards and analysis method standards related to drug safety, efficacy, and quality controllability is further increased.
Conclusion: The general chapters of physical and chemical analysis in the Chinese Pharmacopoeia 2025 Edition have provided a more convenient new bridge for China’s drugs to go international, standardized testing technology support for achieving full process quality control, and better meet the needs of drug research and development, production, quality control, and supervision in China.

Objective: To explore the causal association between dietary components (carbohydrate, fat, protein, and sugar) and 119 genera of known gut microbiota using Mendelian randomization (MR) methods. Methods: Genome-wide association study (GWAS) data for dietary components were collected from the DietGen, while GWAS data for gut microbiota were collected from the MiBioGen. Single nucleotide polymorphism (SNP) loci associated with the four dietary components were used as instrumental variables, and 119 known gut microbiota genera were used as the outcomes. MR analysis was performed using inverse variance weighted (IVW) method. Heterogeneity was evaluated using Cochran's Q test, horizontal pleiotropy and exclude outliers were tested using MR-Egger regression and MR-PRESSO test. Common genetic pleiotropic genes between dietary components and gut microbiota were identified by MAGMA and PLACO analyses. Results: The MR analysis revealed causal associations between carbohydrates and 4 gut microbiota genera, fats and 14 genera, proteins and 14 genera, and sugars and 11 genera (all P<0.05). The MR-Egger regression analysis showed no horizontal pleiotropy among the selected SNPs, and the MR-PRESSO test did not identify any outliers (all P>0.05). The MAGMA and PLACO analyses revealed that 74.42% (32/43) of the causal associations had pleiotropic genes, with 1 to 10 pleiotropic genes identified. Multiple causal association groups shared the same pleiotropic genes. Conclusion There are potential genetic and causal associations between dietary components and gut microbiota.

ObjectiveAutism spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties with communication and social interaction, restricted and repetitive behaviors. Previous studies have indicated that individuals with ASD exhibit early and lifelong attention deficits, which are closely related to the core symptoms of ASD. Basic visual attention processes may provide a critical foundation for their social communication and interaction abilities. Therefore, this study explores the behavior of children with ASD in capturing attention to changes in topological properties. MethodsOur study recruited twenty-seven ASD children diagnosed by professional clinicians according to DSM-5 and twenty-eight typically developing (TD) age-matched controls. In an attention capture task, we recorded the saccadic behaviors of children with ASD and TD in response to topological change (TC) and non-topological change (nTC) stimuli. Saccadic reaction time (SRT), visual search time (VS), and first fixation dwell time (FFDT) were used as indicators of attentional bias. Pearson correlation tests between the clinical assessment scales and attentional bias were conducted. ResultsThis study found that TD children had significantly faster SRT (P<0.05) and VS (P<0.05) for the TC stimuli compared to the nTC stimuli, while the children with ASD did not exhibit significant differences in either measure (P>0.05). Additionally, ASD children demonstrated significantly less attention towards the TC targets (measured by FFDT), in comparison to TD children (P<0.05). Furthermore, ASD children exhibited a significant negative linear correlation between their attentional bias (measured by VS) and their scores on the compulsive subscale (P<0.05). ConclusionThe results suggest that children with ASD have difficulty shifting their attention to objects with topological changes during change detection. This atypical attention may affect the child’s cognitive and behavioral development, thereby impacting their social communication and interaction. In sum, our findings indicate that difficulties in attentional capture by TC may be a key feature of ASD.

Objective To explore and verify the prognostic value of endothelial cells in glioblastoma. Methods Through bioinformatics analysis of the TCGA and CGGA databases, we screened endothelial cell-related markers in GBM single-cell data according to a series of criteria. Moreover, univariate Cox regression analysis was performed to obtain and screen endothelial cell prognosis-related markers and construct endothelial cell-related prognostic risk score. qPCR experiments was used to verify the differences in the expression of prognostic markers in GBM tissues and peritumoral normal brain tissues. Kaplan-Meier method was used to construct the survival curve to identify the prognostic efficacy of the prognostic risk score. Results A total of 2 115 prognostic genes of glioblastoma (GBM) were screened. Among them, 1 494 was upregulated and 621 was downregulated. Seven groups of cells were obtained after GBM single-cell sequencing analysis, including AC-like tumor cells, endothelial cells, monocytes/macrophages, NB-like tumor cells, neurons, OC-like tumor cells, and OPC-like tumor cells. According to the differential genes of endothelial cells and the corresponding screening criteria, four genes (DUSP6, STC1, VWA1, and TM4SF1) were screened for risk-score construction. The expression of the target gene in GBM tissues and normal brain tissues around the tumor was significantly up-regulated detected by qPCR. The risk score=0.171*DUSP6+0.144*STC1+0.041*VWA1−0.004*TM4SF1. Conclusion The glioblastoma endothelial cells’ risk score determined in this study can preferably predict the prognosis of patients.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

ObjectiveTo explore quality difference factors of Perillae Caulis based on the contents of multiple chemical components and comprehensively evaluate the quality. MethodsA total of 32 batches of Perillae Caulis samples were collected from 12 producing areas such as Hebei， Anhui and Guangdong， and their diameter range， epidermis color and producing areas were recorded. Total flavonoids， total phenols， volatile oils， 5 active components and 84 volatile components in 32 batches of samples were quantitatively or semi-quantitatively determined by colorimetry， ultra performance liquid chromatography-photodiode array detector（UPLC-PDA） and gas chromatography-mass spectrometry（GC-MS）. Then the differences between the contents of these components were analyzed by principal component analysis（PCA） and non-parametric test. According to the weights of the index components determined by PCA model， entropy weight-technique for order preference by similarity to ideal solution（TOPSIS） model was constructed to evaluate the quality of Perillae Caulis with different characters and origins. ResultsThere were significant differences in the composition of Perillae Caulis with different diameters， epidermis colors and producing areas， and 9 differential components were screened out， including 6 index constituents（total flavonoids， total phenols， caffeic acid， scutellarin， rosmarinic acid and luteolin） and 3 volatile components（caryophyllene oxide， （-）-humulene epoxide Ⅱ， 14-hydroxycaryophyllene）， of which 6 index constituents were higher in samples with small diameter， purple-brown epidermis and southern origin， while the contents of 3 volatile components were higher in samples with large diameter， dark-brown epidermis and northern origin. A significant difference was shown in the model scores of different diameters， epidermis colors and origins（P<0.05）， and the scores of Perillae Caulis with small diameter and purple-brown epidermis from southern area， especially Guangdong， had a high score. ConclusionThere are significant differences in the composition and content of chemical constituents between different diameters， epidermal colors and production areas of Perillae Caulis， samples showing small diameter， owing purple-brown epidermis， and originating from Guangdong were of higher-quality due to their higher content of 8 key indices.

ObjectiveTo explore quality difference factors of Perillae Caulis based on the contents of multiple chemical components and comprehensively evaluate the quality. MethodsA total of 32 batches of Perillae Caulis samples were collected from 12 producing areas such as Hebei， Anhui and Guangdong， and their diameter range， epidermis color and producing areas were recorded. Total flavonoids， total phenols， volatile oils， 5 active components and 84 volatile components in 32 batches of samples were quantitatively or semi-quantitatively determined by colorimetry， ultra performance liquid chromatography-photodiode array detector（UPLC-PDA） and gas chromatography-mass spectrometry（GC-MS）. Then the differences between the contents of these components were analyzed by principal component analysis（PCA） and non-parametric test. According to the weights of the index components determined by PCA model， entropy weight-technique for order preference by similarity to ideal solution（TOPSIS） model was constructed to evaluate the quality of Perillae Caulis with different characters and origins. ResultsThere were significant differences in the composition of Perillae Caulis with different diameters， epidermis colors and producing areas， and 9 differential components were screened out， including 6 index constituents（total flavonoids， total phenols， caffeic acid， scutellarin， rosmarinic acid and luteolin） and 3 volatile components（caryophyllene oxide， （-）-humulene epoxide Ⅱ， 14-hydroxycaryophyllene）， of which 6 index constituents were higher in samples with small diameter， purple-brown epidermis and southern origin， while the contents of 3 volatile components were higher in samples with large diameter， dark-brown epidermis and northern origin. A significant difference was shown in the model scores of different diameters， epidermis colors and origins（P<0.05）， and the scores of Perillae Caulis with small diameter and purple-brown epidermis from southern area， especially Guangdong， had a high score. ConclusionThere are significant differences in the composition and content of chemical constituents between different diameters， epidermal colors and production areas of Perillae Caulis， samples showing small diameter， owing purple-brown epidermis， and originating from Guangdong were of higher-quality due to their higher content of 8 key indices.