ObjectiveTo identify potential influencing factors of urate crystal deposition at ankle/foot in patients with hyperuricemia （HUA）， and to analyze the predictive value of inflammatory indicators for urate crystal deposition in patients with different traditional Chinese medicine （TCM） syndromes， so as to provide potential reference for clinical risk assessment and individualized TCM intervention. MethodsA retrospective study was carried out with the enrollment of 231 HUA patients from The Third Affiliated People's Hospital of Fujian University of Traditional Chinese Medicine between January 2021 and December 2024. The enrolled patients were further divided into a crystal deposition-positive group （143 cases） and a crystal deposition-negative group （88 cases） according to the results of dual-energy computed tomography （CT）. Sociodemographic data， living habits， serum uric acid levels， and inflammatory indicators of the enrolled patients were collcted， and TCM syndrome differentiation was performed. Furthermore， univariate analysis was used to compare inter-group differences in clinical characteristics. MMultivariate Logistic regression was applied to identify the influencing factors of urate crystal deposition. In addition， the receiver operating characteristic （ROC） curves were plotted to evaluate the predictive efficacy of inflammatory indicators for crystal deposition across different TCM syndromes. ResultsThere were statistically significant inter-group differences in the proportion of males， age， body mass index， proportion of mental labor， rate of low water intake， and rate of high-sugar beverage consumption （P<0.05），whereas no significant difference in low exercise intensity was found between the two groups. Furthermore， compared with the negative group， the positive group had higher serum uric acid level， neutrophil-to-lymphocyte ratio （NLR）， and platelet-to-lymphocyte ratio （PLR）， but lower systemic immune-inflammation index （SIRI） （P<0.05）. Regarding the distribution of TCM syndromes， the positive group was dominated by the dampness-heat accumulation syndrome （55/143，38.46%）， while the negative group was mainly characterized by the phlegm-turbidity obstruction syndrome （44/88，50.00%）. Multivariate Logistic regression analysis revealed that high-sugar beverage consumption， elevated NLR， and elevated PLR were risk factors for urate crystal deposition ［odd ratio （OR） = 8.002， 5.377， 1.034， respectively； 95% CI 1.572-40.732， 2.179-13.270， 1.013-1.054，all P<0.05］， while SIRI was a protective factor （OR = 0.869， 95% CI 0.778-0.971， P<0.05）. In the positive group， patients with the dampness-heat accumulation syndrome exhibited the highest NLR， while the lowest PLR and SIRI， showing statistically significant differences with those of other syndromes （all P<0.05）. In addition， ROC curve analysis indicated that for the dampness-heat accumulation syndrome， the combined "NLR + PLR" model had an area under the curve （AUC） of 0.901 （95% CI 0.850-0.951， P<0.01）， with a sensitivity of 89.1% and a specificity of 79.5%； for the blood stasis-heat obstruction syndrome， the combined "NLR + PLR" model had an AUC of 0.880 （95% CI 0.825-0.934， P<0.01）， with a sensitivity of 100.0% and a specificity of 67.3%； for the liver-kidney Yin-deficiency syndrome， the single PLR model had an AUC of 0.842 （95% CI 0.731-0.952， P<0.01）， with a sensitivity of 83.3% and a specificity of 84.0%. ConclusionUrate crystal deposition in HUA patients exhibits intimate associations with high-sugar beverage consumption as well as elevated NLR and PLR levels. Meanwhile， TCM syndrome differentiation has potential correlation with inflammatory characteristics. The inflammatory indicator-based prediction model constructed based on TCM syndromes exhibits good predictive value.

The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry* ; Animals ; Mice ; Berberis/chemistry* ; RAW 264.7 Cells ; Macrophages/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; Nitric Oxide/metabolism* ; Molecular Structure ; Anti-Inflammatory Agents/isolation & purification*

This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

BACKGROUND AND OBJECTIVE: Patients with glioma experience a high symptom burden and have diverse palliative care needs. However, the assessment scales used in palliative care remain non-standardized and highly heterogeneous. To evaluate the application patterns of the current scales used in palliative care for glioma, we aim to identify gaps and assess the need for disease-specific scales in glioma palliative care. METHODS: We conducted a systematic search of five databases including PubMed, Web of Science, Medline, EMBASE, and CINAHL for quantitative studies that reported scale-based assessments in glioma palliative care. We extracted data on scale characteristics, domains, frequency, and psychometric properties. Quality assessments were performed using the Cochrane ROB 2.0 and ROBINS-I tools. RESULTS: Of the 3,405 records initially identified, 72 studies were included. These studies contained 75 distinct scales that were used 193 times. Mood (21.7%), quality of life (24.4%), and supportive care needs (5.2%) assessments were the most frequently assessed items, exceeding half of all scale applications. Among the various assessment dimensions, the Distress Thermometer (DT) was the most frequently used tool for assessing mood, while the Short Form-36 Health Survey Questionnaire (SF-36) was the most frequently used tool for assessing quality of life. The Mini Mental Status Examination (MMSE) was the most common tool for cognitive assessment. Performance status (5.2%) and social support (6.8%) were underrepresented. Only three brain tumor-specific scales were identified. Caregiver-focused scales were limited and predominantly burden-oriented. CONCLUSIONS: There are significant heterogeneity, domain imbalances, and validation gaps in the current use of assessment scales for patients with glioma receiving palliative care. The scale selected for use should be comprehensive and user-friendly.
Humans ; Glioma/psychology* ; Palliative Care/methods* ; Quality of Life ; Psychometrics ; Brain Neoplasms/psychology*

Combined with elastic network model (ENM), the perturbation response scanning (PRS) has emerged as a robust technique for pinpointing allosteric interactions within proteins. Here, we proposed the PRS analysis of drug-target networks (DTNs), which could provide a promising avenue in network medicine. We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework, for drug repurposing of multiple sclerosis (MS). First, the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes. Then, based on topological analysis and functional annotation, the neurotransmission module was identified as the "therapeutic module" of MS. Further, perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis, giving a list of repurposable drugs for MS. Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of serotonin 2B receptor (HTR2B). Finally, we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex. These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS. As a useful systematic method, our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

The development of traditional Chinese medicine (TCM) diagnosis and treatment has undergone multiple paradigms, evolving from sporadic experiential practices to systematic approaches in syndrome differentiation and treatment and further integration of disease and syndrome frameworks. TCM is a vital component of the medical system, valued alongside Western medicine. Treatment based on syndrome differentiation embodies both personalized treatment and holistic approaches; however, the inconsistency and lack of stability in syndrome differentiation limit clinical efficacy. The existing integration of diseases and syndromes primarily relies on patchwork and embedded systems, where the full advantages of synergy between Chinese and Western medicine are not fully realized. Recently, driven by the development of diagnosis and treatment concepts and advances in analytical technology, Western medicine has been rapidly transforming from a traditional biological model to a precision medicine model. TCM faces a similar need to progress beyond traditional syndrome differentiation and disease-syndrome integration toward a more precise diagnosis and treatment paradigm. Unlike the micro-level precision trend of Western medicine, precision diagnosis and treatment in TCM is primarily reflected in data-driven applications that incorporate information at various levels, including precise syndrome differentiation, medication, disease management, and efficacy evaluation. The current priority is to accelerate the development of TCM precision diagnosis and treatment technology platforms and advance discipline construction in this area.

ObjectiveTo use bioinformatics technology to screen the molecular patterns and diagnostic biomarkers of ferroptosis closely related to psoriasis， observe the therapeutic effect of Kaixuan Jiedu core prescription on psoriasis and explore its potential mechanism through animal experiments. MethodsPsoriasis microarray data from GEO were analyzed to identify differentially expressed genes （DEGs）. Intersection with a ferroptosis gene set yielded psoriasis ferroptosis-related genes （FRGs）， which underwent correlation， consensus clustering， enrichment， and immune infiltration analyses. Core diagnostic FRGs （Hub-FRGs） were identified using random forest （RF）， support vector machine （SVM）， LASSO regression， Nomogram， and ROC analyses. In vivo， imiquimod （5% cream） induced psoriasis in mice （except controls）. Drug treatment groups received respective doses， while control and model groups received saline via daily gavage for 7 days. Back skin changes were recorded and PASI scored. Hematoxylin-eosin （HE） staining assessed histopathology. The levels of ferrous ion （Fe²⁺）， malondialdehyde （MDA）， 4-hydroxynonenal （4-HNE） and free fatty acid （FFA） in skin tissue were detected. The level of reactive oxygen species （ROS） in skin tissue was detected by immunofluorescence. Immunohistochemistry was used to detect the expression of ChaC glutathione-specific γ-glutamyl transferase 1 （CHAC1）， arachidonic acid 12-lipoxygenase β （ALOX12B）， trimotif protein 21 （TRIM21）， proliferation marker （Ki67） and nuclear transcription factor-κB （NF-κB） protein. ResultsAnalysis of GSE30999 identified 2 100 DEGs and 24 FRGs. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment revealed 1 000 biological functions and 75 pathways. After cluster analysis， combined with three machine learning algorithms， Nomogram and ROC curve analysis， the core Hub-FRGs （CHAC1， ALOX12 B， TRIM21） were obtained. Immunoinfiltration showed inactive memory CD4⁺T cells and activated dendritic cells abundance significantly correlated with Hub-FRGs. In vivo， model group vs. control showed significantly increased PASI/Baker scores （P<0.05）， epidermal hyperkeratosis， inflammatory infiltration， and elevated levels of Fe²⁺， MDA， 4-HNE， FFA， ROS， CHAC1， ALOX12B， TRIM21， Ki67， and NF-κB （P<0.05）. Drug groups vs. model group exhibited significantly reduced scores （P<0.05）， alleviated skin lesions， and decreased levels of Fe²⁺， MDA， 4-HNE， FFA， ROS， Hub-FRGs， Ki67， and NF-κB （P<0.05）. ConclusionKaixuan Jiedu core prescription can significantly improve the skin pathological injury of psoriasis mice， showing good therapeutic and repair effects， and its mechanism may be related to regulating the expression of ferroptosis genes CHAC1， ALOX12B and TRIM21， which are closely related to the pathogenesis of psoriasis.

ObjectiveTo use bioinformatics technology to screen the molecular patterns and diagnostic biomarkers of ferroptosis closely related to psoriasis， observe the therapeutic effect of Kaixuan Jiedu core prescription on psoriasis and explore its potential mechanism through animal experiments. MethodsPsoriasis microarray data from GEO were analyzed to identify differentially expressed genes （DEGs）. Intersection with a ferroptosis gene set yielded psoriasis ferroptosis-related genes （FRGs）， which underwent correlation， consensus clustering， enrichment， and immune infiltration analyses. Core diagnostic FRGs （Hub-FRGs） were identified using random forest （RF）， support vector machine （SVM）， LASSO regression， Nomogram， and ROC analyses. In vivo， imiquimod （5% cream） induced psoriasis in mice （except controls）. Drug treatment groups received respective doses， while control and model groups received saline via daily gavage for 7 days. Back skin changes were recorded and PASI scored. Hematoxylin-eosin （HE） staining assessed histopathology. The levels of ferrous ion （Fe²⁺）， malondialdehyde （MDA）， 4-hydroxynonenal （4-HNE） and free fatty acid （FFA） in skin tissue were detected. The level of reactive oxygen species （ROS） in skin tissue was detected by immunofluorescence. Immunohistochemistry was used to detect the expression of ChaC glutathione-specific γ-glutamyl transferase 1 （CHAC1）， arachidonic acid 12-lipoxygenase β （ALOX12B）， trimotif protein 21 （TRIM21）， proliferation marker （Ki67） and nuclear transcription factor-κB （NF-κB） protein. ResultsAnalysis of GSE30999 identified 2 100 DEGs and 24 FRGs. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment revealed 1 000 biological functions and 75 pathways. After cluster analysis， combined with three machine learning algorithms， Nomogram and ROC curve analysis， the core Hub-FRGs （CHAC1， ALOX12 B， TRIM21） were obtained. Immunoinfiltration showed inactive memory CD4⁺T cells and activated dendritic cells abundance significantly correlated with Hub-FRGs. In vivo， model group vs. control showed significantly increased PASI/Baker scores （P<0.05）， epidermal hyperkeratosis， inflammatory infiltration， and elevated levels of Fe²⁺， MDA， 4-HNE， FFA， ROS， CHAC1， ALOX12B， TRIM21， Ki67， and NF-κB （P<0.05）. Drug groups vs. model group exhibited significantly reduced scores （P<0.05）， alleviated skin lesions， and decreased levels of Fe²⁺， MDA， 4-HNE， FFA， ROS， Hub-FRGs， Ki67， and NF-κB （P<0.05）. ConclusionKaixuan Jiedu core prescription can significantly improve the skin pathological injury of psoriasis mice， showing good therapeutic and repair effects， and its mechanism may be related to regulating the expression of ferroptosis genes CHAC1， ALOX12B and TRIM21， which are closely related to the pathogenesis of psoriasis.

Objective: To explore the association between the Internet usage characteristics and suicidal ideation among vocational high school students, so as to provide a theoretical basis for precise intervention of suicide among vocational high school students. Methods: A total of 1 781 students were recruited from three vocational high schools in Wuhan and Xianning in March 2023 by using the cluster random sampling method. The Columbia-Suicide Severity Rating Scale and Revised Chen Internet Addiction Scale were used to measure suicidal ideation and Internet addiction, respectively. LASSO regression model was used to select influential factors related to suicidal ideation, and the gradient boosting decision tree algorithm XGBoost was used to develop prediction models and evaluate predictive performance. By calculating the SHAP values, the contribution of each influential factor was quantified. Results: The prevalence of suicidal ideation among vocational high school students was 42.22% and prevalence of Internet addiction was 26.39%. LASSO regression results indicated that age, gender, experience of being left behind, parental relationship, holding a class cadre position, using the Internet for learning, Internet use during dawn, morning and late night, Internet addiction, and depressive symptoms were all the influential factors of suicidal ideation among vocational high school students ( β= -0.05 , 0.29, 0.09, 0.27, 0.10, -0.01, 0.09, 0.05, 0.24, 0.28, 0.78, all P <0.05). The AUC of the prediction model was 0.75. The results based on SHAP values indicated that all influential factors identified through multivariate analysis contributed positively to the model predictions ( SHAP >0). Among these, depressive symptoms and parental relationship had the greatest impact on suicidal ideation ( SHAP =0.77, 0.26), and the joint effect of features with higher contribution could improve the prediction probability. Conclusions Depressive symptoms, parental relationships, Internet addiction, and time of Internet use are most important risk factors of suicidal behaviors for vocational high school students. Thus, effective interventions should be conducted to reduce their suicidal ideation.