BACKGROUND:Anthocyanin is one of the most important active components in Lycium ruthenicum Murr,which has antioxidant and immunomodulatory effects.CD146+human adipose-derived pericytes/perivascular cells(CD146+hAD-PCs)are the progenitors of bone marrow mesenchymal stem cells,which can promote the proliferation and differentiation of hematopoietic stem/progenitor cells in vitro.The support effect of anthocyanin in combination with CD146+hAD-PCs on umbilical cord blood hematopoietic stem/progenitor cells remains to be studied. OBJECTIVE:To investigate the supporting effect of anthocyanins in Lycium ruthenicum Murr(ALRM)combined with CD146+hAD-PCs on umbilical cord blood CD34+hematopoietic stem/progenitor cells(UCB CD34+HSPCs)in vitro. METHODS:The CCK-8 assay was used to detect the effect of different concentrations(0,200,400,600,800,1 000 mg/L)of ALRM on the proliferation of CD146+hAD-PCs.Flow cytometry was used to detect the effect of ALRM on the cell cycle of CD146+hAD-PCs.The co-culture experiments were divided into blank group,ALRM group,CD146+hAD-PCs group,and ALRM+CD146+hAD-PCs group to analyze the in vitro supporting effect of ALRM combined with CD146+hAD-PCs on UCB CD34+HSPCs.The number of expanded cells and the number of colony-forming units were compared at 1,2,and 4 weeks of co-culture.The immunophenotype of cells was detected by flow cytometry.The level of cytokines was detected by enzyme-linked immunosorbent assay. RESULTS AND CONCLUSION:(1)The cell viability of CD146+hAD-PCs was highest at an ALRM concentration of 200 mg/L,the proportion of G0/G1 phase cells decreased and the proportion of S and G2/M phase cells increased in CD146+hAD-PCs(P<0.01).(2)The change in number of UCB CD34+HSPCs cells in the ALRM+CD146+hAD-PCs group was higher than that in the ALRM group at 1,2,and 4 weeks of co-culture(all P<0.05),and higher than that in CD146+hAD-PCs group at 2 and 4 weeks of co-culture(all P<0.05).The number of cells in the ALRM group and blank group decreased gradually with the extension of co-culture time.(3)Colony forming capacity and immunophenotype analysis:The number of colony-forming units in the ALRM+CD146+hAD-PCs group was higher than that in the CD146+hAD-PCs group and ALRM group at 1 and 2 weeks of co-culture(P<0.05).The proportion of CD45+and CD34+CD33-cells in the ALRM+CD146+hAD-PCs group was higher than that in the CD146+hAD-PCs group at 1 and 2 weeks of co-culture(all P<0.01).(4)Changes in cytokines:Interleukin-2 level in the ALRM+CD146+hAD-PCs group was higher than that in the ALRM and CD146+hAD-PCs groups(P<0.05).The interleukin-3 content of the ALRM+CD146+hAD-PCs group was higher than that of the CD146+hAD-PCs group at 2 and 4 weeks(P<0.05).The expression level of granulocyte colony-stimulating factor in the ALRM+CD146+hAD-PCs group was higher than that in the CD146+hAD-PCs group at 1 week,and higher than that in the ALRM group and CD146+hAD-PCs group at 2 weeks(P<0.01).Interferon-γ content in the ALRM group and ALRM+CD146+hAD-PCs group was lower than that in the CD146+hAD-PCs group at 1,2,and 4 weeks of co-culture(P<0.01).(5)Due to the absence of stromal cells in the blank group,UCB CD34+HSPCs could not be counted after 1 week of co-culture and were not subjected to immunophenotyping,colony analysis,or cytokine assays.(6)In summary,ALRM can promote the expansion of UCB CD34+HSPCs in vitro by promoting CD146+hAD-PCs proliferation and cell cycle transformation,which is of great value in hematopoietic stem cell transplantation.

Natural product-based drug combinations (NPDCs) present distinctive advantages in treating complex diseases. While high-throughput screening (HTS) and conventional computational methods have partially accelerated synergistic drug combination discovery, their applications remain constrained by experimental data fragmentation, high costs, and extensive combinatorial space. Recent developments in artificial intelligence (AI), encompassing traditional machine learning and deep learning algorithms, have been extensively applied in NPDC identification. Through the integration of multi-source heterogeneous data and autonomous feature extraction, prediction accuracy has markedly improved, offering a robust technical approach for novel NPDC discovery. This review comprehensively examines recent advances in AI-driven NPDC prediction, presents relevant data resources and algorithmic frameworks, and evaluates current limitations and future prospects. AI methodologies are anticipated to substantially expedite NPDC discovery and inform experimental validation.
Artificial Intelligence ; Biological Products/chemistry* ; Humans ; Drug Combinations ; Drug Discovery/methods* ; Machine Learning ; Algorithms

The mechanism of action of traditional Chinese medicine (TCM) remains unclear. Historically, research on TCM has mainly focused on exploring the mechanisms of active components acting on single targets. However, it is insufficient to explain the complex mechanisms by which these active components in TCM treat diseases. In recent years, the emergence of molecular glues (MGs) theory has provided new strategies to address this issue. MGs are small molecules that can promote interactions between proteins at their interface. The characteristic of MGs is to establish connections between diverse protein structures, thereby enabling a chemically-mediated proximity effect that triggers a wide spectrum of biological functions. Natural products are the result of billions of years of evolutionary processes in the natural environment. Thus, the extensive structural diversity of natural products renders them a rich source of MGs, including polyketides, terpenoids, steroids, lignans, organic acids, alkaloids and other classes. Currently, several well-known natural MGs, including the immunosuppressants cyclosporin A (CsA) and tacrolimus (FK506), as well as the anticancer agent taxol, have been incorporated into clinical practice. Meanwhile, the advancement of new technologies is propelling the discovery of novel MGs from natural products. Thus, we primarily summarize a growing variety of MGs from natural origins reported in recent years and categorize them based on the chemical structural types. Moreover, the main sources of TCM are natural products. The discovery of natural MGs promises to provide a new perspective for the elucidation of the molecular mechanism behind the efficiency of TCM. In summary, this review aims to provide insights from the perspective of natural products that could potentially influence TCM and modern drug development.

Advancements in artificial intelligence (AI) and emerging technologies are rapidly expanding the exploration of chemical space, facilitating innovative drug discovery. However, the transformation of novel compounds into safe and effective drugs remains a lengthy, high-risk, and costly process. Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development. Despite this need, no comprehensive tool currently supports systematic evaluation and efficient screening. Here, we present druglikeFilter, a deep learning-based framework designed to assess drug-likeness across four critical dimensions: 1) physicochemical rule evaluated by systematic determination, 2) toxicity alert investigated from multiple perspectives, 3) binding affinity measured by dual-path analysis, and 4) compound synthesizability assessed by retro-route prediction. By enabling automated, multidimensional filtering of compound libraries, druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates, which can be freely accessed at https://idrblab.org/drugfilter/.

Objective To compare H_p(3) calibration with a homemade (A) thermoluminescent dosimeter (TLD) and an imported (B) TLD in a standard X-ray RQR radiation field, to explore the different responses of A and B, and to provide foundation for the calibration of H_p(3). Methods A column mode was selected. H_p(3) calibration was performed using A and B in a standard X-ray RQR radiation field in the Secondary Standard Dosimetry Laboratory, National Institute for Radiological Protection, China Center for Disease Control and Prevention. Angle response, energy response, and linear response were calibrated with RQR4 (60 kV), RQR7 (90 kV), and RQR9 (120 kV), respectively. Results In terms of angle response, the calibration results of A were relatively high, while the calibration results of B were relatively low. In terms of energy response, the calibration results showed a similar pattern to angle response. In terms of linear response, the calibration results of both A and B were satisfactory. Conclusion Both A and B can be used for normal calibration of H_p(3) in a standard X-ray RQR radiation field. However, in actual monitoring, attention should be paid to the energy and angle response values of TLDs.

Objective: To describe the prevalence and the association of sleep quality trajectory, social jetlag and comorbid symptoms of anxiety and depression among college students, in order to provide a theoretical basis for improving the comorbid symptoms of anxiety and depression in college students. Methods: A questionnaire survey was conducted among 1 135 college students from two universities in Shangrao, Jiangxi Province and Hefei, Anhui Province from April to May 2019, and were followed up once every one year for a total of three times, with a valid sample size of 1 034 individuals after matching with the baseline survey. A selfassessment questionnaire was used to investigate the social jetlag of college students, the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire 9 (PHQ-9) were used to evaluate anxiety and depression symptoms, respectively, while the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. College students with GAD-7 score ≥5 and PHQ-9 score ≥5 were defined as having comorbid anxiety and depression symptoms. Latent class growth model (LCGM) was employed to analyze the sleep quality trajectory of college students, and binary Logistic regression was used to analyze the relationship between social jetlag, sleep quality trajectory and comorbid symptoms of anxiety and depression. Results: The detection rate of comorbid symptoms of anxiety and depression among college students was 16.9%, and the detection rate of social jetlag ≥2 h was 13.8%. The sleep quality showed an overall improvement trend, and the two trajectories were good sleep quality (81.6%) and poor sleep quality (18.4%). Binary Logistic regression model showed that poor sleep quality and social jetlag ≥2 h were positively correlated with comorbid symptoms of anxiety and depression (OR=5.94, 1.84, P<0.05). Conclusions Poor sleep quality and social jetlag ≥2 h in college students increase the risk of comorbid symptoms of anxiety and depression. Early screening and intervention of sleep quality and reduction of social jetlag are crucial for enhancing the mental health of college students.

Objective:To understand the current status of anemia, iron deficiency, and iron-deficiency anemia among preschool children in China.Methods:A cross-sectional study was conducted with a multi-stage stratified sampling method to select 150 streets or townships from 10 Chinese provinces, autonomous regions, or municipalities (East: Jiangsu, Zhejiang, Shandong, and Hainan; Central: Henan; West: Chongqing, Shaanxi, Guizhou, and Xinjiang; Northeast: Liaoning). From May 2022 to April 2023, a total of 21 470 children, including community-based children aged 0.5 to<3.0 years receiving child health care and kindergarten-based children aged 3.0 to<7.0 years, were surveyed. They were divided into 3 age groups: infants (0.5 to<1.0 year), toddlers (1.0 to<3.0 years), and preschoolers (3.0 to<7.0 years). Basic information such as sex and date of birth of the children was collected, and peripheral blood samples were obtained for routine blood tests and serum ferritin measurement. The prevalence rates of anemia, iron deficiency, and iron-deficiency anemia were analyzed, and the prevalence rate differences were compared among different ages, sex, urban and rural areas, and regions using the chi-square test.Results:A total of 21 460 valid responses were collected, including 10 780 boys (50.2%). The number of infants, toddlers, and preschoolers were 2 645 (12.3%), 6 244 (29.1%), and 12 571 (58.6%), respectively. The hemoglobin level was (126.7±14.8) g/L, and the serum ferritin level was 32.3 (18.5, 50.1) μg/L. The overall rates of anemia, iron deficiency, and iron-deficiency anemia were 10.4% (2 230/21 460), 28.3% (6 070/21 460), and 3.9% (845/21 460), respectively. The prevalence rate of anemia was higher for boys than for girls (10.9% (1 173/10 780) vs. 9.9% (1 057/10 680), χ2=5.58, P=0.018), with statistically significant differences in the rates for infants, toddlers and preschoolers (18.0% (475/2 645), 10.6% (662/6 244), and 8.7% (1 093/12 571), respectively, χ2=201.81, P<0.01), and the rate was significantly higher for children in rural than that in urban area (11.8% (1 516/12 883) vs. 8.3% (714/8 577), χ2=65.54, P<0.01), with statistically significant differences in the rates by region ( χ2=126.60, P<0.01), with the highest rate of 15.8% (343/2 173) for children in Central region, and the lowest rate of 5.3% (108/2 053) in Northeastern region. The prevalence rates of iron deficiency were 33.8% (895/2 645), 32.2% (2 011/6 244), and 25.2% (3 164/12 571) in infants, toddlers, and preschoolers, respectively, and 30.0% (3 229/10 780) in boys vs. 26.6% (2 841/10 680) in girls, 21.7% (1 913/8 821), 40.0% (870/2 173), 27.1% (2 283/8 413), 48.9% (1 004/2 053) in Eastern, Central, Western, and Northeastern regions, respectively, and each between-group showed a significant statistical difference ( χ2=147.71, 29.73, 773.02, all P<0.01). The prevalence rate of iron-deficiency anemia showed a significant statistical difference between urban and rural areas, 2.9% (251/8 577) vs. 4.6% (594/12 883) ( χ2=38.62, P<0.01), while the difference in iron deficiency prevalence was not significant ( χ2=0.51, P=0.476). Conclusions:There has been a notable improvement in iron deficiency and iron-deficiency anemia among preschool children in China, but the situation remains concerning. Particular attention should be paid to the prevention and control of iron deficiency and iron-deficiency anemia, especially among infants and children in the Central, Western, and Northeastern regions of China.

Objective:To construct a chain mediating model based on two mediating variables of positive psychological capital and general self-efficacy, so as to explore the impact mechanism of social support on posttraumatic growth in thyroid cancer patients.Methods:From March to December 2023, convenience sampling was used to select 270 postoperative patients with thyroid cancer from the Chinese People's Liberation Army General Hospital as participants. The patients were surveyed using the General Information Questionnaire, Post Traumatic Growth Inventory, Social Support Rating Scale, Positive Psychological Questionnaire, and General Self-efficacy Scale. Spearman correlation was used to analyze the correlation between social support, positive psychological capital, general self-efficacy, and posttraumatic growth in thyroid cancer patients. SPSS PROCESS program was used to test for the chain mediating effect.Results:A total of 270 questionnaires were distributed, and 257 questionnaires were collected. After excluding questionnaires with missing items exceeding 10% and regular responses, 246 valid questionnaires were collected, with a valid response rate of 91.11% (246/270). Spearman correlation showed that there was positive correlations between social support, positive psychological capital, general self-efficacy, and posttraumatic growth in patients ( P<0.01). Mediating effect analysis showed that social support directly and positively predicted posttraumatic growth in thyroid cancer [ β=0.403, 95% CI (0.258, 0.547) ], and also affected patients' posttraumatic growth through three indirect pathways, namely social support → positive psychological capital → posttraumatic growth, with an effect value of 0.083 [95% CI (0.002, 0.173) ], accounting for 13.63% of the total effect, and social support → general self-efficacy → posttraumatic growth, with an effect value of 0.099 [95% CI (0.040, 0.166) ], accounting for 16.26% of the total effect, and social support → positive psychological capital → general self-efficacy → posttraumatic growth, with an effect value of 0.025 [95% CI (0.005, 0.051) ], accounting for 4.11% of the total effect. The total indirect effect accounted for 33.83% of the total effect. Conclusions:Social support can not only directly affect the post-traumatic growth of thyroid cancer patients, but also indirectly affect post-traumatic growth through the mediating effect of positive psychological capital and general self-efficacy.

Objective:Considering the large amount and poor quality of clinical data, this study aims to explore the establishment of high-quality research database and its role in real-world research by taking the establishment of lymphoma research database as an example.Methods:The expert opinions in the field of lymphoma were collected, and the relevant guidelines and standards were referenced to establish a standard medical knowledge dataset. The electronic diagnosis and treatment data of lymphoma patients treated in Peking University Cancer Hospital from February 2005 to December 2020 were retrospectively extracted, the deep Learning, natural language processing were adopted to build a dynamic intelligent information integration and processing system of " lymphoma database based on electronic medical record system - biological sample information database - extended genetic information database" .Results:The research database not only meets the research needs of clinical researchers, but also realizes the management of traces in the whole process of application, approval, traceability and analysis of hospital medical record data and biological sample data. The total number of research variables in the database was 668, and the structured variables accounted for 46.0%. On December 25, 2021, there were 68 687 lymphoma patients in the database, the ratio of male to female patients was 8/9, and the proportion of patients with ≥3 visits accounted for 23.0%. In addition, researchers can superimpose searches in the database according to the target conditions, display the targeted medical records according to research hypothesis, and then establish a research cohort, conducting statistical modeling, and mining data information.Conclusions:By integrating management processes and using new natural language artificial intelligence technology to establish a high-level evidence-based database, it is helpful for the interconnection and resource sharing of hospital information systems, so as to achieve the purpose of providing reliable and detailed data for real-world research.