OBJECTIVE To evaluate the efficacy and safety of total glucosides of paeonia （TGP） in the treatment of systemic lupus erythematosus （SLE）. METHODS Randomized controlled trial （RCT） about TGP combined with western medicine versus western medicine alone for SLE treatment were retrieved from PubMed， Embase， Cochrane Library， Web of Science， CNKI， VIP， Wanfang Data， and CBM. The search period spanned from the inception of each database to June 1， 2025. After literature screening， data extraction， and quality assessment of the included studies， Meta-analysis was performed using RevMan 5.4 software. RESULTS Fifteen RCTs， involving 1 318 patients， were included. Meta-analysis results showed that compared with western medicine alone， TGP combined with western medicine significantly improved clinical efficacy [OR＝4.96， 95%CI（3.41， 7.23）， P＜0.000 01]， complement 3 [MD＝0.18， 95%CI （0.13， 0.23）， P＜0.000 01] and complement 4[MD＝0.08， 般021） 95%CI （0.04， 0.11）， P＜0.000 01]， and reduced the levels of immunoglobulin G （IgG） [MD＝－3.10， 95%CI （－3.59，－2.62）， P＜0.000 01]， IgA [MD＝－0.68， 95%CI （－0.78， －0.58）， P＜0.000 01]， IgM [MD＝－0.43， 95%CI （－0.53，－0.34）， P＜0.000 01]， systemic lupus erythematosus disease activity index （SLEDAI） [MD＝－1.59， 95%CI （－2.20， －0.99）， P＜0.000 01]， recurrence rate [OR＝0.23， 95%CI （0.13， 0.42）， P＜0.000 01] and the incidence of adverse drug reactions [OR＝ 0.54， 95%CI （0.36， 0.82）， P＝0.004]. CONCLUSIONS TGP therapy can improve clinical efficacy of SLE patients， promote the restoration of immunoglobulins and complements， reduce SLEDAI and recurrence rate and has good safety.

ObjectiveTo observe the clinical efficacy and safety of Tangning Tongluo tablets in the treatment of nonproliferative diabetic retinopathy （DR）. MethodsFourteen research centers participated in this study， which spanned a time interval from September 2021 to May 2023. A total of 240 patients with nonproliferative DR were included and randomly assigned into an observation group （120 cases） and a control group （120 cases）. The observation group was treated with Tangning Tongluo tablets， and the control group with calcium dobesilate capsules. Both groups were treated for 24 consecutive weeks. The vision， DR progression rate， retinal microhemangioma， hemorrhage area， exudation area， glycosylated hemoglobin （HbA1c） level， and TCM syndrome score were assessed before and after treatment， and the safety was observed. ResultsThe vision changed in both groups after treatment （P<0.05）， and the observation group showed higher best corrected visual acuity （BCVA） than the control group （P<0.05）. The DR progression was slow with similar rates in the two groups. The fundus hemorrhage area and exudation area did not change significantly after treatment in both groups， while the observation group outperformed the control group in reducing the fundus hemorrhage area and exudation area. There was no significant difference in the number of microhemangiomas between the two groups before treatment. After treatment， the number of microhemangiomas decreased in both the observation group （Z=-1.437， P<0.05） and the control group （Z=-2.238， P<0.05）， and it showed no significant difference between the two groups. As the treatment time prolonged， the number of microhemangiomas gradually decreased in both groups. There was no significant difference in the HbA1c level between the two groups before treatment. After treatment， the decline in the HbA1c level showed no significant difference between the two groups. The TCM syndrome score did not have a statistically significant difference between the two groups before treatment. After treatment， neither the TCM syndrome score nor the response rate had significant difference between the two groups. With the extension of the treatment time， both groups showed amelioration of TCM syndrome compared with the baseline. ConclusionTangning Tongluo tablets are safe and effective in the treatment of nonproliferative DR， being capable of improving vision and reducing hemorrhage and exudation in the fundus.

ObjectiveEarly blight is a common destructive disease in the growth process of Solanaceae crops, which can lead to crop failure and serious losses. Traditional crop disease detection methods are difficult to detect disease characteristics in a timely manner during the incubation period of disease, and thus take scientific and effective prevention and control measures. This study obtained hyperspectral images of early blight of peppers at different infection stages through continuous monitoring with a hyperspectral imager. The earliest identifiable time during the incubation period of early blight in peppers (the earliest identifiable time during the incubation period in this experiment was 24 h after inoculation) was determined using the spectral angle cosine-correlation coefficient and Chebyshev distance. MethodsTaking the symptoms of the latent period of early blight in peppers as the research object, 13 characteristic wavelengths were selected using a genetic algorithm. An identification model of crop disease latent period symptoms based on spectral features was established through optimized combinations of characteristic wavelengths combined with a logistic regression model. Simultaneously, a recognition model of the latent period of early blight in peppers based on image texture features was established using local binary patterns. ResultsThe experiment was tested with 120 samples. The accuracy of the identification model of crop disease latent period symptoms based on spectral features reached over 93% in both the training set and the test set. The accuracy of the identification model of crop disease latent period symptoms based on texture features reached 98.96% and 100% in the training set and test set, respectively. ConclusionBoth spectral features and texture features can be used to detect and identify crop disease latent period symptoms. Texture features more significantly revealed the characteristics of the latent period of the disease compared to spectral features, effectively improving the detection performance of the model. The research results in this article can provide theoretical references for monitoring and identifying other crop disease latent period symptoms.

Objective: To understand the dynamic temporal evolution pathways of Internet addiction among university students and to identify the core driving nodes, so as to provide theoretical evidences for the precise implementation of targeted interventions. Methods: Using a convenient cluster sampling method, a total of 1 066 full time freshmen and sophomores were recruited from three universities in Guizhou, Jiangxi, and Guangdong Provinces for a follow up survey (T1:January-March 2024; T2:January-March 2025). The Revised Chen Internet Addiction Scale (CIAS-R) was employed to assess the status of Internet addiction among university students, and cross sectional as well as cross lagged panel network models were constructed to analyze Internet addiction and its multidimensional influencing factors. Results: The T1 network comprised 19 nodes and 114 non zero edges, while the T2 network comprised 19 nodes and 126 non zero edges. Cross sectional network analysis revealed the strongest association between "insufficient sleep" and "daytime fatigue"; the core nodes were "first thought upon waking for going online" and "feeling low after disconnection" (characteristics of psychological dependence) at T1, while the core nodes shifted to "impaired health" and "excitement when online" (characteristics of functional impairment and addictive psychodynamic features) at T2. Cross lagged network analysis further indicated that "reduced leisure" directly predicted "sleep compression", and a bidirectional relationship was observed between "needing more time to achieve satisfaction" and "academic decline". Conclusions Internet addiction among university students exhibits dynamic evolutionary characteristics. Stage specific targeted interventions focusing on core driving nodes are needed, integrating behavioral regulation and academic support to break the vicious cycle and enhancing the ability to cope with real life demands.

ObjectiveEarly detection of crop diseases is crucial for effective agricultural management and yield protection. While visible light imaging has been widely applied for disease detection due to its accessibility and non-destructive nature, most existing methods primarily focus on identifying diseases during the symptomatic phase, when visual symptoms are already prominent. However, detecting plant diseases during the incubation period—when symptoms are still subtle or invisible—remains a major challenge due to the lack of distinctive visual cues and limited research methodologies. This study aims to address this gap by proposing a novel three-channel recognition model to accurately identify early blight symptoms during the incubation stage in Solanaceae crops, particularly in chili and tomato, using only visible light images. MethodsWe established a controlled experimental setup in which healthy leaves and leaves inoculated with early blight pathogens were photographed continuously over time. A total of 1 258 visible light images were collected, capturing various stages of disease progression. From these images, lesion regions were manually annotated. To quantitatively characterize early and subtle color changes within the lesion areas, we extracted color moments—first-order (mean), second-order (standard deviation), and third-order (skewness)—from multiple color spaces, including Lab and HSV. By analyzing the temporal variation of these color moments across disease progression stages, we identified the first-order moment of the saturation (S) channel in the HSV color space as the most sensitive indicator of lesion development on inoculated leaves. Using this insight, we defined four disease categories: healthy, incubation stage, early stage, and late stage. Subsequently, a three-channel classification model was constructed by integrating features from three color channels that provided complementary information. Three-channel models were constructed based on R-G-B, L-a-b, and H-S-V color spaces, respectively, to evaluate performance across different crops and to determine which color representation provides the most discriminative power for identifying disease symptoms during the incubation period. ResultsThe proposed models demonstrated strong classification performance. The three-channel model built using the Lab color space achieved a 94.44% accuracy in recognizing the incubation stage of early blight in pepper, effectively distinguishing subtle pre-symptomatic features from healthy tissue. The model based on the HSV color space achieved 100% accuracy in detecting incubation-stage symptoms in tomato, underscoring the discriminative power of S-channel variations in this context. These results confirm the model’s capability to identify early blight before visible lesions become pronounced, which is essential for timely disease intervention. ConclusionThis study presents a new technical pathway for early-stage disease detection using visible light images by focusing on subtle color feature changes during the incubation period. The proposed three-channel recognition model effectively identifies early blight in both chili and tomato, offering a non-destructive, low-cost, and easily deployable solution for early warning and precision agriculture. Furthermore, this framework can be generalized to other crops and diseases where early detection plays a critical role in minimizing yield losses and ensuring sustainable production. The method lays a solid foundation for future research in pre-symptomatic plant disease recognition and provides valuable tools for intelligent crop monitoring and precision management systems.

OBJECTIVE: To compare the biomechanical properties of personalized Y-shaped plates with horizontal plates, vertical plates, and traditional Y-shaped plates in the treatment of distal humeral intra-articular fractures through finite element analysis, and to evaluate their potential for clinical application. METHODS: The study selected a 38-year-old male volunteer and obtained a three-dimensional model of the humerus by scanning his upper limbs using a 64-slice spiral CT. Four types of fracture-internal fixation models were constructed using Mimics 19.0, Geomagic Wrap 2017, Creo 6.0, and other software: horizontal plates, vertical plates, traditional Y-shaped plate, and personalized Y-shaped plate. The models were then meshed using Hypermesh 14.0 software, and material properties and boundary conditions were defined in Abaqus 6.14 software. AnyBody 7.3 software was used to simulate elbow flexion and extension movements, calculate muscle strength, joint forces, and load torques, and compare the peak stress and maximum displacement of the four fixation methods at different motion angles (10°, 30°, 50°, 70°, 90°, 110°, 130°, 150°) during elbow flexion and extension. RESULTS: Under dynamic loading during elbow flexion and extension, the personalized Y-shaped plate exhibits significant biomechanical advantages. During elbow flexion, the peak internal fixation stress of the personalized Y-shaped plate was (28.8±0.9) MPa, which was significantly lower than that of the horizontal plates, vertical plates, and traditional Y-shaped plate ( P<0.05). During elbow extension, the peak internal fixation stress of the personalized Y-shaped plate was (18.1±1.6) MPa, which was lower than those of the other three models, with significant differences when compared with horizontal plates and vertical plates ( P<0.05). Regarding the peak humeral stress, the personalized Y-shaped plate model showed mean values of (10.9±0.8) and (13.1±1.4) MPa during elbow flexion and extension, respectively, which were significantly lower than those of the other three models ( P<0.05). Displacement analysis showed that the maximum displacement of the humerus with the personalized Y-shaped plate during elbow flexion was (2.03±0.08) mm, slightly higher than that of the horizontal plates, but significantly lower than that of the vertical plates, showing significant differences ( P<0.05). During elbow extension, the maximum displacement of the humerus with the personalized Y-shaped plate was (1.93±0.13) mm, which was lower than that of the other three models, with significant differences when compared with vertical plates and traditional Y-shaped plates ( P<0.05). Stress contour analysis showed that the stress of the personalized Y-shaped plate was primarily concentrated at the bifurcation of the Y-shaped structure. Displacement contour analysis showed that the personalized Y-shaped plate effectively controlled the displacement of the distal humerus during both flexion and extension, demonstrating excellent stability. CONCLUSION The personalized Y-shaped plate demonstrates excellent biomechanical performance in the treatment of distal humeral intra-articular fractures, with lower stress and displacement, providing more stable fixation effects.
Humans ; Male ; Adult ; Healthy Volunteers ; Finite Element Analysis ; Tomography, Spiral Computed ; Models, Anatomic ; Biomechanical Phenomena ; Humeral Fractures, Distal/surgery* ; Fracture Fixation, Internal/instrumentation* ; Bone Plates ; Computer Simulation ; Precision Medicine/methods* ; Elbow Joint/surgery* ; Elbow/surgery* ; Humerus/surgery* ; Torque ; Stress, Mechanical ; Intra-Articular Fractures/surgery* ; Prosthesis Design/methods* ; Imaging, Three-Dimensional ; Range of Motion, Articular

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

A comprehensive phytochemical investigation of the leaves and twigs of Physalis angulata. var. villosa resulted in the isolation of 23 withanolide derivatives, including one novel 13,20-γ-lactone withanolide derivative (1) and three new withanolide derivatives (2-4). Architecturally, physalinin A (1) represents the first identified type B withanolide featuring a 13,20-γ-lactone moiety. The molecular structures of all isolates were elucidated using an integrated approach combining nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS), infrared (IR) spectroscopy, and quantum chemical calculations to confirm structural assignments. The antiproliferative activities of all isolated withanolides were evaluated against four human cancer cell lines (HEL, HCT-116, Colo320DM, and MDA-MB-231). Among them, eight derivatives (2, 5-8, 14, 15, and 23) exhibited significant inhibitory effects, with half-maximal inhibitory concentration (IC₅₀) values of 0.18 ± 0.03 to 17.02 ± 0.21 μmol·L^-1. Structure-activity relationship (SAR) analysis suggested that the presence of an epoxide ring enhances anticancer activity, potentially through increased reactivity or specific interactions with molecular targets involved in cancer progression. These findings underscore the pharmacological potential of withanolides as promising lead compounds for the development of novel anticancer therapeutics.
Withanolides/isolation & purification* ; Physalis/chemistry* ; Humans ; Molecular Structure ; Cell Line, Tumor ; Antineoplastic Agents, Phytogenic/isolation & purification* ; Cell Proliferation/drug effects* ; Plant Leaves/chemistry* ; Plant Extracts/pharmacology*

General anesthesia is widely used in clinical practice,whereas the exact mechanism behind the general anesthetic-induced reversible loss of consciousness remains unclear.Recent studies have revealed a close relationship between the dopaminergic system and general anesthetic-induced loss of consciousness.This system,encompassing dopamine neurons,dopamine receptors,and related neural pathways,regulates functions such as movement,memory,arousal,and cognition.The dopaminergic neurons in the ventral periaqueductal gray and ventral tegmental area,along with D1 receptors,have been shown to facilitate emergence from anesthesia.However,the role of D2 receptors remains controversial.This review summarizes recent advancements in the role of the dopaminergic system in general anesthesia and the underlying mechanism,with the aim of clarifying the mechanism of general anesthesia and providing a theoretical basis for preventing delayed emergence from anesthesia.
Humans ; Anesthesia, General ; Brain/metabolism* ; Dopaminergic Neurons/physiology* ; Dopamine/physiology* ; Animals

Ocular accommodation refers to the process by which the ciliary muscle creates a clear image of the object in the retina by changing the refractive power of the lens. When the accommodation ability of the eye is insufficient, the imaging focus falls on the region behind the retina and hyperopic defocus is easily formed, resulting in axial growth and leading to the development of myopia, and it is found that most myopic patients usually have some accommodation dysfunction. Myopia has become a public health problem in China, and the prevalence of adolescents has increased dramatically. How to prevent and stop the occurrence and development of myopia is a major challenge. Previous studies have found that ocular accommodation dysfunction is associated with the occurrence and development of myopia, and the measurement of parameters related to accommodation function has certain guiding significance for the prevention and control of myopia. The purpose of this paper is to review the correlation between myopia and ocular accommodation function, with a view to providing new ideas for the prevention, control and treatment of myopia.