OBJECTIVE To investigate the improvement effects and mechanism of Achyranthes bidentata total saponins （ABS） extract on vascular endothelial dysfunction in spontaneously hypertensive rat （SHR） based on cytochrome P450 4A （CYP4A）/20-hydroxyeicosatetetraenoic acid （20-HETE）/G protein-coupled receptor 75 （GPR75） axis. METHODS Ten Wistar- Kyoto rats were taken as the normal control group. Forty SHR were first stratified by systolic blood pressure and then， within each stratum， randomly assigned using a random-number table to the model group （MOD group）， captopril positive control group （CAP group， 10 mg/kg）， ABS low- and high-dose extract groups （ABS-L group， ABS-H group， 60 and 120 mg/kg）， with 10 rats in each group. Animals in each group were given the corresponding drug or equal volume of pure water by gavage， once a day， for 28 consecutive days. After the last administration， systolic blood pressure of rats was measured. The levels of vasoactive substances， inflammatory factors and oxidative stress indicators in serum were measured. The pathological changes of rat thoracic aorta were observed. The level of reactive oxygen species （ROS） in aortic tissue was analyzed. The expressions of endothelial nitric oxide synthase （eNOS）， CYP4A， GPR75， nuclear factor-κB p65 （NF-κB p65）， phosphorylated NF-κB p65， p22phox， and reduced nicotinamide adenine dinucleotide phosphate oxidase 4（NOX4） in thoracic aorta tissue were detected. RESULTS After 28 d of treatment， compared with MOD group， the systolic blood pressure of rats in the ABS-L and ABS-H groups decreased significantly. The levels of 20-HETE， angiotensin Ⅱ， interleukin-1β， interleukin-6， tumor necrosis factor-α， intercellular cell adhesion molecule-1 and malondialdehyde in serum were significantly reduced （P＜0.05 or P＜0.01）， while the levels of nitric oxide， superoxide dismutase， glutathione peroxidase and catalase were significantly increased （P＜0.05 or P＜0.01）. Intimal damage of thoracic aorta was reduced， and endothelial cell morphology was improved. The expressions of ROS， CYP4A， GPR75， p22phox， NOX4 and the phosphorylation level of NF-κB p65 protein in thoracic aorta were down-regulated or reduced （P＜0.05 or P＜0.01）， while the expression of eNOS was up-regulated （P＜0.05 or P＜0.01）. CONCLUSIONS ABS extract may alleviate the inflammatory response and oxidative stress in SHR effectively by down-regulating the expression of CYP4A， reducing the production of 20-HETE， inhibiting the activation of GPR75， and subsequently suppressing the activation of downstream NF-κB and NOX4， thereby improving hypertension-related vascular endothelial dysfunction.

ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

ObjectiveTo investigate the modifiable areal unit problem （MAUP） in the spatial pattern of Pseudostellaria heterophylla production regions and reveal the impact of statistical scales on the spatial distribution characteristics of this medicinal plant species. MethodsUsing multi-source data （literature records， field surveys， and statistical data）， we systematically analyzed the spatial patterns across three administrative levels （provincial， prefectural， and county scales）. Spatial autocorrelation （Moran's I） analysis， high-low clustering （Getis-Ord General G）， and hot/cold spot analysis （Getis-Ord Gi*） were employed. ResultsThe literature-based analysis showed that the production regions of P. heterophylla presented random distribution on the provincial scale and significant aggregation on the prefectural scale. The field survey data showed that the production regions displayed random distribution on the provincial scale but significant aggregation on both prefectural and county scales. The statistical data revealed that the production regions lacked spatial autocorrelation on the provincial scale but demonstrated significant aggregation on prefectural and county scales. ConclusionMAUP effects have substantive implications for understanding and decision-making in the arrangement of medicinal plant production regions. The county scale proves to be the most sensitive and explanatory level for analyzing the spatial pattern of P. heterophylla production regions， providing a critical foundation for habitat modeling， suitability evaluation， and ecological cultivation planning of medicinal plants.

Traditional Chinese Medicine (TCM), as a treasure of the Chinese nation, plays a significant role in maintaining public health. In 2019, the Central Committee of the Communist Party of China and the State Council proposed for the first time the establishment of a TCM registration and evaluation evidence system that integrates TCM theory, "personal experience" and clinical trials (referred to as the "Three-in-One" System) to promote the inheritance and innovation of TCM. Subsequently, the National Medical Products Administration issued several guiding principles to advance the improvement and implementation of this system. Owing to the complexity of its implementation, there are still differing understandings within the TCM industry regarding the positioning of the "Three-in-One" Registration and Evaluation Evidence System, as well as the connotation and value orientation of the "personal experience." To address this, Academician WANG Qi, President of the TCM Association, China International Exchange and Promotion Association for Medical and Healthcare and TCM master, led a group of academicians, TCM masters, TCM pharmacology experts and clinical TCM experts to convene a "Seminar on Promoting the Implementation of the ′Three-in-One′ Registration and Evaluation Evidence System for Chinese Medicinals." Through extensive discussions, an expert consensus was formed, clarifying the different roles of the TCM theory, "personal experience" and clinical trials within the system. It was further emphasized that the "personal experience" is the core of this system, and its data should be derived from clinical practice scenarios. In the future, the improvement of this system will require collaborative efforts across multiple fields to promote the high-quality development of the Chinese medicinal industry.

Objective:To investigate the patterns of mutation evolution in patients with acute myeloid leukemia (AML) during treatment and the possible clinical significances.Methods:A retrospective case series study was conducted. A total of 103 AML patients who were hospitalized at the Affiliated Yuebei People's Hospital of Medical College of Shantou University from November 2019 to August 2021 and underwent high-throughput next-generation sequencing (NGS) technology to detect the mutations of 128 AML-related genes in bone marrow samples were selected. Based on the NGS results, the somatic gene mutations in samples of patients collected at initial diagnosis (73 cases), complete remission (CR) (30 cases), non-remission (NR) (23 cases), and recurrence (12 cases) were analyzed, and the targeted drugs involved in the gene mutations detected in NR and recurrence samples were summarized.Results:The median age [ M ( Q1, Q3)] of onset for 103 patients was 58 (48, 66) years, including 64 males (61%) and 39 females (39%); 86 cases (83%) were primary AML, and 17 cases (17%) were secondary AML; at the initial diagnosis, 51 cases (50%) had normal karyotypes, 34 cases (33%) had abnormalities, and 18 cases (17.5%) were unknown. Compared with the CR samples, the mutation frequencies of FLT3 [29% (21/73) vs. 3% (1/30)], NPM1 [27% (20/73) vs. 3% (1/30)], NRAS [22% (16/73) vs. 3% (1/30)], and IDH2 [14% (10/73) vs. 0 (0/30)] were all higher in the initial diagnosis samples, and the differences were statistically significant (all P < 0.05); compared with the initial diagnosis sample, the median number of gene mutations in each CR sample was lower [4 (2, 5) vs. 7 (5, 9)], and the difference was statistically significant ( P < 0.001). However, there was no statistically significant difference in the median number of gene mutations in each patient between the initial diagnosis samples and the NR samples, the initial diagnosis samples and the recurrence samples, and the NR samples and the recurrence samples (all P > 0.05). Analysis of 14 patients with NGS data at initial diagnosis and CR showed that the same gene mutations could be detected at initial diagnosis and CR, such as DNAH23 (3 cases), USH2A (3 cases), etc; partial gene mutations were detected at initial diagnosis but were not detected at CR, including NRAS (5 cases), FLT3 (3 cases), ANKRD26 (3 cases), NPM1 (3 cases), ETV6 (3 cases), etc; ARID1B (1 case) and DNMT3A (1 case) were negative for mutations at initial diagnosis but positive upon reaching CR. Analysis of 14 patients with NGS data at initial diagnosis and NR showed that most gene mutations persisted at initial diagnosis and NR, such as DNMT3A (5 cases), NRAS (5 cases), KRAS (3 cases), RUNX1 (3 cases), etc; the mutant genes detected at initial diagnosis but not detected at NR included USH2A (2 cases), PCLO (2 cases), ATM (2 cases), FAT1 (2 cases), etc; partial gene mutations were not detected at initial diagnosis but were detected at NR, such as FAT1 (2 cases), TCF3 (2 cases), etc. Analysis of 5 patients with NGS data at CR and recurrence showed that some gene mutations were detected at both CR and recurrence, such as BCORL1 (1 case), ARID2 (1 case), SETD2 (1 case), VEGFC (1 case), etc; FLT1 (1 case) and GNAS (1 case) gene mutations were detected at CR but not detected at recurrence; at recurrence, some gene mutations that were not detected at CR were also detected, such as ANKRD26 (1 case), WT1 (1 case), etc. Among the 23 NR samples and 12 recurrence samples, the targets of drugs approved by US Food and Drug Administration or in clinical trials were detected in 14 (61%) and 5 (42%) samples respectively, including IDH1, IDH2, FLT3, KIT, KRAS, NRAS, SF3B1, U2AF1, and SRSF2. Conclusions:The number of gene mutations in AML patients during CR is significantly less than that at initial diagnosis, some gene mutations disappear when CR is achieved through treatment, but the majority of gene mutations persist during the treatment period, including NR and recurrence, suggesting that monitoring through NGS technology can help understand the evolution of gene mutations during AML treatment and discover the potential therapeutic targets.

Objective To evaluate the efficacy and safety of dupilumab combined with 2％cleboride ointment in the treatment of moderate to severe atopic dermatitis,as well as its impact on serological indica-tors.Methods A retrospective analysis was conducted on the clinical data of 67 patients with moderate to se-vere atopic dermatitis(AD)admitted to the Department of Dermatology of Shaoxing University Affiliated Hospital from March 2021 to December 2024.The study subjects were divided into an experimental group(n=35)and a control group(n=32)according to the treatment method.The experimental group was treated with Dupilumab injection and 2％Cleboride ointment,while the control group was treated with ebastine tab-lets and 2％cleboride ointment.Clinical and related serological indicators of patients after 16 weeks of treat-ment were collected,and the itch digital scale score,eczema area and severity(EASI)score,IL-4,IL-13 levels,and incidence of local skin adverse reactions were analyzed before and after treatment in both groups.Results The total effective rate of the experimental group after treatment was 94.29％(33/35),which was higher than the control group[53.13％(17/32)],and the difference was statistically significant(x2=12.862,P＜0.001).There was no statistically significant difference in symptom scores,IL-4,and IL-13 levels between the two groups before treatment(P＞0.05).After treatment,the symptom scores of the experimental group were lower than those of the control group,and the difference was statistically significant(P＜0.05).The lev-els of IL-4 and IL-13 in the experimental group were lower than those in the control group,and the difference was statistically significant(P＜0.05).The incidence of adverse reactions in the experimental group was 2.86％(1/35),significantly lower than the 34.38％(11/32)in the control group,and the difference was sta-tistically significant(x2=9.252,P=0.002).Conclusion The combination of dupilumab injection and 2％cleboride ointment is effective in relieving skin symptoms,regulating cellular immune function,reducing in-flammatory reactions,and minimizing local skin adverse reactions in patients with moderate to severe AD.It is worthy of clinical promotion and use.

Artificial intelligence (AI) has emerged as a transformative technology in accelerating drug discovery and development within natural medicines research. Natural medicines, characterized by their complex chemical compositions and multifaceted pharmacological mechanisms, demonstrate widespread application in treating diverse diseases. However, research and development face significant challenges, including component complexity, extraction difficulties, and efficacy validation. AI technology, particularly through deep learning (DL) and machine learning (ML) approaches, enables efficient analysis of extensive datasets, facilitating drug screening, component analysis, and pharmacological mechanism elucidation. The implementation of AI technology demonstrates considerable potential in virtual screening, compound optimization, and synthetic pathway design, thereby enhancing natural medicines' bioavailability and safety profiles. Nevertheless, current applications encounter limitations regarding data quality, model interpretability, and ethical considerations. As AI technologies continue to evolve, natural medicines research and development will achieve greater efficiency and precision, advancing both personalized medicine and contemporary drug development approaches.
Biological Products/pharmacology* ; Artificial Intelligence ; Humans ; Drug Discovery/methods* ; Machine Learning ; Deep Learning

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.