Xanthine oxidase (XO) is an important therapeutic target for the treatment of hyperuricemia and gout. Based on the previously identified potent XO inhibitor 1, seventeen oxadiazoles and their ring-opening analogues were designed and synthesized via the bioisostere replacement strategy. Among them, compounds 2l, 2n, and 3b showed obvious XO inhibitory activity at the concentration of 10 μmol·L^-1, and compound 3b exhibited an IC₅₀ value of 1.45 μmol·L^-1.

A scoping review was performed to systematically search and summarize the clinical research in the treatment of dysmenorrhea with oral Chinese patent medicines. The oral Chinese patent medicines for treating dysmenorrhea in three major drug lists, guidelines, and textbooks were screened, and the relevant clinical trials were retrieved from eight Chinese and English databases. The key information of the included trials was extracted and visually analyzed. A total of 50 Chinese patent medicines were included, among which oral Chinese patent medicines for the dysmenorrhea patients with the syndrome of Qi stagnation and blood stasis accounted for the highest proportion, and the average daily cost varied greatly among Chinese patent medicines. A total of 150 articles were included, involving 22 Chinese patent medicines, among which Guizhi Fuling Capsules/Pills, Sanjie Zhentong Capsules, and Dan'e Fukang Soft Extract were the most frequently studied. These articles mainly reported randomized controlled trial(RCT), which mainly focused on the comparison of the intervention effect between Chinese patent medicines combined with western medicine and western medicine alone, and the sample size was generally 51-100 cases. The high-frequency outcome indicators belonged to nine domains such as effective rate, adverse reactions, and laboratory examinations. This study showed that oral Chinese patent medicines had advantages in the treatment of dysmenorrhea, and the annual number of related clinical trials showed an overall growing trend. However, there were still problems such as insufficient safety information and vague description of traditional Chinese medicine(TCM) syndromes types in the instructions of Chinese patent medicines. The available clinical research had shortcomings such as uneven distribution of Chinese patent medicines, limited research scale, poor methodological rigor, and insufficient standardization of outcome indicators. In the future, it is necessary to deepen the development of high-quality clinical research and improve the contents of the instructions to ensure the effectiveness and safety of the clinical application of oral Chinese patent medicines in the treatment of dysmenorrhea.
Dysmenorrhea/drug therapy* ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Female ; Administration, Oral ; Nonprescription Drugs/administration & dosage*

The interactions between microorganisms and medicinal plants are crucial to the quality improvement of medicinal plants. Medicinal plants attract microorganisms to colonize by secreting specific compounds and provide niche and nutrient support for these microorganisms, with a symbiotic network formed. These microorganisms grow in the rhizosphere, phyllosphere, and endophytic tissues of plants and significantly improve the growth performance and medicinal component accumulation of medicinal plants by promoting nutrient uptake, enhancing disease resistance, and regulating the synthesis of secondary metabolites. Microorganisms are also widely used in the ecological planting of medicinal plants, and the growth conditions of medicinal plants are optimized by simulating the microbial effects in the natural environment. The interactions between microorganisms and medicinal plants not only significantly improve the yield and quality of medicinal plants but also enhance their geoherbalism, which is in line with the concept of green agriculture and eco-friendly development. This study reviewed the research results on the interactions between medicinal plants and microorganisms in recent years and focused on the analysis of the great potential of microorganisms in optimizing the growth environment of medicinal plants, regulating the accumulation of secondary metabolites, inducing systemic resistance, and promoting the ecological planting of medicinal plants. It provides a scientific basis for the research on the interactions between medicinal plants and microorganisms, the research and development of microbial agents, and the application of microorganisms in the ecological planting of medicinal plants and is of great significance for the quality improvement of medicinal plants and the green and sustainable development of TCM resources.
Plants, Medicinal/metabolism* ; Bacteria/genetics* ; Symbiosis

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*

OBJECTIVES: To explore the measures to improve the follow-up rate of preterm infants after discharge, and to evaluate the effectiveness of these measures using quality improvement methodology. METHODS: The follow-up status of preterm infants discharged from March to May 2017 was used as the baseline before quality improvement, and a specific quality improvement goal for the follow-up rate was proposed. The Pareto chart was used to analyze the causes of follow-up failure, and a key driver diagram was constructed based on the links involved in improving follow-up rate. The causes of failure were analyzed to determine the key links and intervention measures for quality improvement, and the follow-up rate was monitored weekly using a control chart until the quality improvement goal was achieved. RESULTS: The follow-up rate of preterm infants after discharge was 57.92% (117/202) at baseline before quality improvement, and the quality improvement goal was set to increase the follow-up rate of preterm infants from baseline to more than 80% within 12 months. The Pareto chart analysis showed that the main causes of follow-up failure were deficiencies in follow-up file management and irregular follow-up times (33.70%, 31/92), insufficient follow-up education and poor communication (25.00%, 23/92), and the inability to meet the diverse needs of parents (18.48%, 17/92). Based on the key links for quality improvement and the main causes of follow-up failure, the following intervention measures were adopted: (1) strengthen follow-up publicity and education; (2) build a follow-up team; and (3) establish a follow-up platform and system. The control chart indicated that with the implementation of the above intervention measures, the weekly follow-up rate increased to 74.09% (306/413) in July 2017 and 83.09% (511/615) in December 2017, finally achieving the quality improvement goal. During the COVID-19 pandemic, the follow-up rate of preterm infants fluctuated between 23.54% (460/1 954) and 70.97% (1 931/2 721), and subsequently, it returned to pre-pandemic levels starting in February 2023. CONCLUSIONS The application of quality improvement methodology can help to formulate intervention measures based on the main causes of follow-up failure, thereby improving the follow-up rate of preterm infants after discharge. This quality improvement method is feasible and practical and thus holds promise for clinical application.
Humans ; Quality Improvement ; Infant, Premature ; Infant, Newborn ; Patient Discharge ; Follow-Up Studies ; Female ; Male

OBJECTIVES: To explore the application of the colloidal gold method and chemiluminescence method in detecting gonadotropin (Gn) in morning urine for assessing pubertal development status in children. METHODS: A total of 132 children diagnosed with central precocious puberty (CPP), early and fast puberty (EFP), and premature thelarche (PT) at Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from November 2021 to December 2022 were included, along with 685 healthy children who underwent routine health examinations at the hospital's pediatric health care department during the same period. All 132 patients underwent a gonadotropin-releasing hormone (GnRH) stimulation test. Both patients and healthy children had their urinary Gn levels measured using the colloidal gold method and chemiluminescence method, including levels of luteinizing hormone (LH) and follicle-stimulating hormone (FSH). The correlation between serum Gn and urinary Gn detected by the two methods, as well as the correlation between Tanner stages of healthy children and urinary Gn, was analyzed. RESULTS: Urine Gn levels detected by both the colloidal gold method and chemiluminescence method showed a positive correlation with serum LH baseline values, LH peak values, baseline LH/FSH ratios, and peak LH/FSH ratios (P<0.05). In healthy children, urinary LH levels detected by the chemiluminescence method gradually increased from Tanner stage Ⅰ to Ⅳ (P<0.05), while urinary FSH levels were lower in Tanner stage I than in stages Ⅱ, Ⅲ, and IV (P<0.05). Urinary LH levels detected by the colloidal gold method were lower in Tanner stage I compared to stages Ⅱ, Ⅲ, and IV, with the highest levels observed in Tanner stage Ⅳ (P<0.05). Additionally, urinary FSH levels in Tanner stage Ⅲ were higher than in stages Ⅰ and Ⅱ (P<0.05). The area under the receiver operating characteristic curve for evaluating Tanner stages I and II in healthy children using urinary LH and FSH levels by the chemiluminescence method and urinary LH levels by the colloidal gold method were 0.730, 0.699, and 0.783, respectively. CONCLUSIONS The colloidal gold method and chemiluminescence method for detecting Gn in morning urine show good correlation with serum Gn levels. As a non-invasive and convenient detection method, the colloidal gold method can serve as a useful tool for screening the onset of pubertal development in children.
Humans ; Child ; Male ; Female ; Gold Colloid ; Luminescent Measurements/methods* ; Gonadotropins/urine* ; Puberty ; Luteinizing Hormone/urine* ; Child, Preschool ; Adolescent ; Follicle Stimulating Hormone/urine*

OBJECTIVES: To investigate the association between insulin resistance and uterine volume in girls with idiopathic central precocious puberty (ICPP). METHODS: A retrospective study was conducted involving 61 girls diagnosed with ICPP who visited the pediatric growth and development clinic of the Third Affiliated Hospital of Zhengzhou University between January 2022 and September 2024, designated as the ICPP group, and 61 normally developing girls as the control group. The differences in insulin resistance index (homeostasis model assessment of insulin resistance, HOMA-IR), uterine volume, and other indicators between the two groups were compared, and the relationship between insulin resistance and uterine volume in these girls was analyzed. RESULTS: The uterine volume and HOMA-IR level in the ICPP group were significantly higher than those in the control group (P<0.05). Correlation analysis revealed that there was a positive correlation between HOMA-IR level and uterine volume in the ICPP group (r_s=0.643, P<0.001). Multiple linear regression analysis indicated that as HOMA-IR increased,uterine volume in the girls tended to increase (P<0.05). CONCLUSIONS There is an association between insulin resistance and uterine volume in girls with ICPP, and as HOMA-IR increases, uterine volume in the girls also increases.
Humans ; Female ; Insulin Resistance ; Puberty, Precocious/metabolism* ; Uterus/pathology* ; Child ; Retrospective Studies ; Organ Size ; Linear Models

OBJECTIVE: To screen novel diagnostic marker or therapeutic target for multiple myeloma (MM). METHODS: Sel1L, SPAG4, KCNN3 and PARM1 were identified by bioinformatics method based on GEO database as high expression genes in MM. Their RNA and protein expression levels in bone marrow mononuclear cells from myeloma cell lines U266, NCI-H929, MM.1s, RPMI8226 and leukemia cell line THP1, as well as 31 MM patients were evaluated by RT-PCR and Western blot, respectively. Meanwhile, 5 samples of bone marrow from healthy donors for allogeneic hematopoietic stem cell transplantation were employed as controls. RESULTS: Compared with leukemia cell line THP1, the expression levels of KCNN3, PARM1 and Sel1L mRNA were significantly increased in myeloma cell lines U266, NCI-H929 and MM.1s, while PARM1 was further increased in myeloma cell lines 8226. Western blot showed that the 4 genes were all expressed in the 4 myeloma cell lines. Compared with healthy controls, the expression levels of Sel1L, SPAG4, KCNN3 and PARM1 mRNA were significantly higher in MM patients (all P < 0.05). Western blot showed that the 4 genes were all expressed in MM patients, and the protein expression level of Sel1L and KCNN3 were significantly different compared with healthy donors (all P < 0.01). CONCLUSION Sel1L, SPAG4, KCNN3 and PARM1 may be potential diagnostic markers and therapeutic targets for MM.
Humans ; Multiple Myeloma/genetics* ; Cell Line, Tumor ; Proteins/metabolism* ; Computational Biology ; RNA, Messenger/genetics*

BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

OBJECTIVE: As an age-related neurodegenerative disease, the prevalence of mild cognitive impairment (MCI) increases with age. Within the framework of traditional Chinese medicine, spleen-kidney deficiency syndrome (SKDS) is recognized as the most frequent MCI subtype. Due to the covert and gradual onset of MCI, in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes. There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS (MCI-SKDS). METHODS: This investigation enrolled 312 elderly individuals diagnosed with MCI, who were randomly distributed into training and test datasets at a 3:1 ratio. Five machine learning methods, including logistic regression (LR), decision tree (DT), naive Bayes (NB), support vector machine (SVM), and gradient boosting (GB), were used to build a diagnostic prediction model for MCI-SKDS. Accuracy, sensitivity, specificity, precision, F1 score, and area under the curve were used to evaluate model performance. Furthermore, the clinical applicability of the model was evaluated through decision curve analysis (DCA). RESULTS: The accuracy, precision, specificity and F1 score of the DT model performed best in the training set (test set), with scores of 0.904 (0.845), 0.875 (0.795), 0.973 (0.875) and 0.973 (0.875). The sensitivity of the training set (test set) of the SVM model performed best among the five models with a score of 0.865 (0.821). The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset. The DCA of all models showed good clinical application value. The study identified ten indicators that were significant predictors of MCI-SKDS. CONCLUSION The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical; the model demonstrates good predictive value and clinical applicability, and the DT model had the best performance. Please cite this article as: Ai YT, Zhou S, Wang M, Zheng TY, Hu H, Wang YC, Li YC, Wang XT, Zhou PJ. Development of a machine learning-based risk prediction model for mild cognitive impairment with spleen-kidney deficiency syndrome in the elderly. J Integr Med. 2025; 23(4): 390-397.
Humans ; Cognitive Dysfunction/diagnosis* ; Aged ; Male ; Female ; Machine Learning ; Spleen ; Aged, 80 and over ; Kidney ; Medicine, Chinese Traditional