ObjectiveTo investigate the effect of quercetin on acute gouty arthritis （GA） in rats by inhibiting the reactive oxygen species （ROS）/NOD-like receptor protein 3 （NLRP3）/interleukin-1β （IL-1β） signaling pathway. MethodsSixty SPF-grade male SD rats were randomized into normal， model， colchicine （0.3 mg·kg^-1）， and low-， medium-， and high-dose （25， 50， 100 mg·kg^-1， respectively） quercetin groups （n=10）. The rats in the dosing groups were administrated with the corresponding drugs （10 mL·kg^-1） by gavage once a day for one week. An equal volume of normal saline was given by gavage to rats in normal and model groups. One hour after drug administration on day 5， an acute GA model was established in other groups except the control group via intra-articular injection of monosodium urate （MSU） suspension into the right posterior ankle joint cavity. The joint swelling and gait were scored at the time points of 6， 12， 24， 48 h after modeling. Histopathological alterations in the ankle joint tissue from each group were assessed by hematoxylin-eosin （HE） staining. Malondialdehyde （MDA）， xanthine oxidase （XOD）， and total superoxide dismutase （T-SOD） assay kits were used to assess the levels of MDA， XOD， and T-SOD in the serum. The levels of tumor interleukin-6 （IL-6）， necrosis factor-α （TNF-α）， and IL-1β in the rat serum， as well as ROS in the ankle joint tissue， were measured by enzyme-linked immunosorbent assay （ELISA）. Western blot was performed to determine the protein levels of NLRP3， thioredoxin-interacting protein （TXNIP）， apoptosis-associated speck-like protein containing a CARD domain （ASC）， precursor cysteinyl aspartate-specific proteinase-1 （pro-Caspase-1）， cleaved Caspase-1 （Caspase-1 p20）， and IL-1β in the ankle joint tissue. Real-time PCR was employed to assess the mRNA levels of TXNIP， NLRP3， ASC， IL-1β， and TNF-α in the ankle joint tissue. ResultsCompared with the normal group， the model group exhibited decreased spontaneous activity， mental fatigue， increased ankle joint swelling and gait scores （P<0.01）， aggravated synovial tissue edema and inflammatory cell infiltration （P<0.01）， elevated levels of XOD， MDA， TNF-α， IL-1β， and IL-6 in the serum and ROS in the joint tissue （P<0.01）， a declined level of T-SOD （P<0.01）， up-regulated protein levels of NLRP3， TXNIP， ASC， pro-Caspase-1， Caspase-1 p20， and IL-1β in the ankle joint tissue （P<0.01）， and up-regulated mRNA levels of NLRP3， TXNIP， ASC， IL-1β， and TNF-α in the ankle joint tissue （P<0.01）. Compared with the model group， the medium- and high-dose quercetin groups showed improved general conditions， decreased gait scores （P<0.05， P<0.01）， reduced joint swelling （P<0.01）， alleviated synovial tissue edema and inflammatory cell infiltration （P<0.05， P<0.01）， lowered levels of XOD， MDA， TNF-α， IL-1β， and IL-6 in the serum and ROS in the joint tissue （P<0.01）， increased levels of T-SOD （P<0.01）， down-regulated protein levels of TXNIP， NLRP3， ASC， pro-Caspase-1， Caspase-1 p20， and IL-1β in the ankle joint tissue （P<0.05， P<0.01）， and down-regulated mRNA levels of TXNIP， NLRP3， ASC， IL-1β， and TNF-α in the ankle joint tissue （P<0.01）. Low-dose quercetin also ameliorated some of the above parameters （P<0.05， P<0.01）. ConclusionQuercetin exerts anti-GA effects by blocking the ROS/NLRP3/IL-1β signaling pathway， downregulating NLRP3 inflammasome activation， and inhibiting the production of pro-inflammatory cytokines including TNF-α， IL-1β， and IL-6.

Objective: To explore the association between takeout fast foods and sugar sweetened beverage consumption with co-occurrence of anxiety and depressive symptoms among first year junior high school students in Yunnan Province, so as to provide theoretical basis for the prevention of anxiety and depressive symptoms co-occurrence among adolescents. Methods: A random cluster sampling involving 8 500 first year junior high school students in 11 counties in Yunnan Province was conducted by a questionnaire survey from October to December 2022. The Depression Anxiety Stress Scale-21 (DASS-21) was applied to assess anxiety and depressive symptoms in first year junior high school students. Chi-square test was used to compare the anxiety-depression co-occurrence symptoms of first year junior high school students with different demographic characteristics. The association between takeout fast foods and sugar sweetened beverage consumption with co-occurrence of anxiety and depressive symptoms of adolescents was analyzed by binary Logistic regression models. Results: The detection rate of co-occurrence of anxiety and depression symptoms among first year junior high school students in Yunnan Province was 26.92%. After controlling for demographic variables and other confounders, takeout fast foods and sugar sweetened beverage consumption( OR=1.50, 95%CI =1.27-1.77) was associated with anxiety-depression co-occurrence symptoms among first year junior high school students in Yunnan Province ( P <0.01). Stratified analysis showed that both Han ( OR=1.37, 95%CI =1.07-1.77) and ethnic minorities ( OR=1.60, 95%CI =1.29-2.00) exhibited statistically significant associations between takeout fast foods and sugar sweetened beverage consumption with co-occurrence of anxiety and depressive symptoms(both P <0.05). Conclusions Takeout fast foods and sugar sweetened beverage consumption increases the risk of co-occurrence of anxiety and depressive symptoms among first year junior high school students in Yunnan Province. It is recommended to strengthen guidance on the consumption of such products among junior high school students to prevent co-occurrence of anxiety and depressive symptoms.

ObjectiveProtein-protein interactions (PPIs) are fundamental to the execution of biological functions within living cells. However, traditional biochemical methods, such as co-immunoprecipitation (Co-IP), often fail to capture transient, weak, or membrane-associated interactions due to the stringent detergent requirements for cell lysis. Proximity labeling (PL) has emerged in recent years as a transformative technology for mapping the proteomes of specific subcellular compartments and identifying dynamic interactomes in situ. Golgi protein 73 (GP73, also known as GOLPH2), a resident type II Golgi transmembrane protein, is a well-recognized clinical biomarker for liver diseases, including hepatocellular carcinoma (HCC). Despite its clinical significance, the comprehensive physiological and pathological functions of GP73 remain partially understood. This study aims to establish an APEX2-mediated proximity labeling system specifically targeting GP73 to map its interactome in a living cellular environment, thereby providing new insights into its molecular roles and regulatory mechanisms. MethodsTo achieve spatial specificity, we first constructed a stable cell line expressing a fusion protein consisting of GP73 and the engineered soybean peroxidase APEX2. The localization of the GP73-APEX2 fusion protein was validated to ensure it correctly targeted the Golgi apparatus. The proximity labeling reaction was initiated by incubating the cells with biotin-phenol (BP) for 30 min, followed by a brief (1 min) treatment with1 mmol/L hydrogen peroxide (H₂O₂). This catalytic reaction converts BP into highly reactive, short-lived biotin-phenoxyl radicals that covalently attach to endogenous proteins within a small labeling radius of the GP73-APEX2 enzyme. Subsequently, the cells were quenched, and biotinylated proteins were enriched using high-affinity streptavidin-coated magnetic beads. The captured “neighbor” proteins were subjected to on-bead digestion and analyzed via liquid chromatography-tandem mass spectrometry (LC-MS/MS) for high-throughput identification. Rigorous bioinformatics analysis, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction network mapping, was performed to interpret the biological significance of the identified candidates. ResultsOur results demonstrate the successful establishment of a robust and sensitive APEX2-based proximity labeling system for GP73. We identified a total of 95 high-confidence interacting proteins that were significantly enriched in the GP73 proximity proteome compared to control groups. Bioinformatics analysis revealed that these interactors were predominantly associated with biological processes such as vesicular transport, protein localization, and, most notably, molecular functions related to “ribosome binding” and “translation regulation”. This suggested an unexpected role for the Golgi-resident GP73 in the cellular translation machinery. To validate these findings, we performed targeted biochemical assays which confirmed a direct interaction between GP73 and the subunits of the eukaryotic translation initiation factor 3 (eIF3) complex, specifically EIF3G and EIF3I. Furthermore, functional validation using the surface sensing of translation (SUnSET) assay—a non-radioactive method to monitor protein synthesis—revealed that the overexpression of GP73 significantly promoted global protein translation levels in the cell, whereas its depletion or inhibition resulted in reduced translation efficiency. ConclusionThis study successfully utilized APEX2-mediated proximity labeling to provide the first systematic map of GP73 interactome in living cells. Our findings uncover a novel, unconventional function of GP73 as a regulator of cellular protein translation, likely mediated through its interaction with the eIF3 complex. This discovery significantly broadens our understanding of the biological roles of GP73 beyond its traditional function in the Golgi apparatus and suggests that it may act as a bridge between Golgi-related trafficking and the protein synthesis machinery. Furthermore, the technical framework established in this study provides a valuable template for investigating other complex organelle-associated protein networks and resolving transient macromolecular interactions in various physiological and pathological contexts.

AIM:To investigate the effect of fibroblast growth factor 21(FGF21)on high glucose-induced oxidative stress in retinal pigment epithelial(RPE)cells and to clarify the underlying molecular mechanisms.METHODS:Single-cell sequencing data from the GEO database were analyzed to determine the expression profile of the FGF21 receptor FGFR1 in RPE cells. Human ARPE-19 cells were cultured and randomly assigned to control, high glucose(30 mmol/L), and high glucose+FGF21 analog treatment groups, with additional siFGFR1 and PI3K inhibitor groups. Cell viability in different treatment groups was assessed using CCK-8 assay, intracellular reactive oxygen species(ROS)levels were quantified using DCFH-DA fluorescent probing combined with immunofluorescence staining and flow cytometry. Transcriptome sequencing was performed on cells from the high glucose group and high glucose+FGF21 group to analyze the enrichment level of the PI3K/Akt signaling pathway. Western blotting was performed to detect phosphorylation levels of PI3K/Akt pathway components.RESULTS:Single-cell sequencing revealed specific expression of FGFR1 in RPE cells of retinal tissues from diabetic model mice. Under In vitro experiments, high glucose(30 mmol/L)exposure reduced ARPE-19 cell viability by 49.7% and increased ROS levels by approximately 2-fold. Whereas treatment with the FGF21 analog(60 ng/mL)restored cell viability and attenuated high glucose-induced ROS accumulation. Mechanistic studies demonstrated that FGFR1 knockdown inhibited the antioxidative stress of FGF21. Further validation of the molecular mechanism revealed that high glucose significantly suppressed the PI3K/Akt pathway activation(the levels of p-Akt and p-PI3K were decreased by 33.9% and 36.6%, respectively), while FGF21 effectively reversed this inhibitory effect and restored the expression of p-Akt and p-PI3K. Treatment with the PI3K inhibitor LY294002 inhibited the cytoprotective effect of FGF21 and significantly increased the ROS-positive cells, these findings confirm that PI3K/Akt signaling is indispensable downstream mechanism for FGF21 to exert its effects.CONCLUSION:FGF21 alleviates high glucose-induced oxidative stress and cellular injury in RPE cells by activating the PI3K/Akt signaling pathway through its receptor FGFR1.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

AIM: To investigate the effects of Conbercept on various optical coherence tomography(OCT)biomarkers in patients with retinal vein occlusion-related macular edema(RVO-ME), and to analyze the correlation of these biomarker changes with visual prognosis.METHODS: Retrospective study. A total of 57 patients(57 eyes)with RVO-ME, including 25 patients(25 eyes)with central retinal vein occlusion(CRVO)and 32 patients(32 eyes)with branch retinal vein occlusion(BRVO), were enrolled in this study. All the patients received intravitreal injection of conbercept once a month, three times in total. The preoperative and postoperative best-corrected visual acuity(BCVA), and changes in OCT biomarkers, including central macular thickness(CMT), the length of disorganization of the retinal inner layers(DRIL), the number of hyperreflective dots(HRD), the area of intraretinal fluid(IRF), the area of subretinal fluid(SRF), and the length of ellipsoid zone(EZ)disruption were compared. Furthermore, the relationship of these changes with BCVA was analyzed.RESULTS:Compared with the baseline, at 3 mo post-treatment, BCVA(LogMAR)was improved, CMT was decreased, the length of DRIL was shortened, the number of HRD was reduced, the area of IRF was decreased, the area of SRF was reduced, and the length of EZ disruption was shortened(all P<0.05). Spearman correlation analysis showed that there was no correlation between the changes in CMT, the length of DRIL, the number of HRD, the area of IRF, the area of SRF and the change in BCVA before and after treatment(P>0.05). However, the change in the length of EZ disruption was positively correlated with the change in BCVA(rs=0.34, P=0.011), and the R2 value of the fitting curve between the change in the length of EZ disruption and the change in BCVA was 0.113(P=0.011). When comparing the pre- and post-treatment changes in BCVA, the length of DRIL, the number of HRD, the area of IRF, the area of SRF, and the length of EZ disruption between patients in the CRVO group and BRVO group, no significant differences were observed(all P>0.05). In contrast, a significant difference was found in the change in CMT between the two groups(P=0.002).CONCLUSION:Conbercept effectively improves multiple OCT biomarkers in patients with RVO-ME. Repair of EZ disruption is a key driver of visual recovery, and its stability may serve as a novel indicator for personalized decision-making in anti-vascular endothelial growth factor therapy.

Objective: To analyze the influencing factors of aggressive behaviors in high school students, rank the importance of relevant variables with visual presentation, so as to provide new references for developing intervention strategies. Methods: In December 2024, a convenience sampling method was used to select 5 330 students from 5 high schools in Wuhan for an online questionnaire survey. The survey included the Buss-Perry Aggression Questionnaire (BPAQ), Interaction Anxiety Scale (IAS), Emotion Regulation Ability Scale, Inventory of Parent and Peer Attachment (IPPA), and a self designed general information questionnaire. Variables were screened using LASSO regression, followed by multivariate Logistic regression analysis. The Random Forest model was then employed to rank and visualize variable importance. Results: Univariate analysis and LASSO regression results indicated that gender, emotion regulation capability, paternal attachment quality, maternal attachment quality, maternal parenting style, paternal parenting style, parenting consistency, monthly household income per capita, school climate, relationship with classmates, interaction anxiety, and academic ranking were all significant variables (all P <0.01). Multivariate Logistic regression analysis identified the following as influencing factors of aggressive behaviors in high school students: emotional management ability ( OR=0.38, 95%CI =0.34-0.43), gender ( OR=0.83, 95%CI =0.75-0.93), mother attachment quality ( OR=0.89, 95%CI = 0.74 -1.07), father attachment quality ( OR=0.76, 95%CI = 0.66- 0.87), interaction anxiousness ( OR=1.58, 95%CI =1.40- 1.78 ), consistency of parenting styles of parents ( OR=1.40, 95%CI =1.21-1.62), school atmosphere ( OR=1.50, 95%CI =1.14-1.98), academic performance ranking (upper middle: OR=0.76, 95%CI =0.61-0.93; middle: OR=0.70, 95%CI =0.57-0.86) were the influencing factors of aggressive behavior in high school students (all P <0.05). The results of Random Forest showed that emotional management ability was the most important factor affecting aggressive behavior in high school students. Conclusion Emotion regulation capability is identified as the core predictor of adolescent aggressive behaviors, which can significantly reduce the incidence of aggressive behaviors through enhanced emotion management.

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*

Asarum forbesii is a perennial herb born in a shaded and humid environment, which is warm in nature. With the efficacy of warming lung, resolving fluid retention, and relieving coughs, it can be used to treat the syndrome of cold fluid accumulating in lung. To investigate the effects of different shading conditions on the composition and efficacy of A. forbesii, this study planted A. forbesii under 20% natural light(NL20), 40% natural light(NL40), 60% natural light(NL60), and 80% natural light(NL80) and utilized ultra performance liquid chromatography(UPLC) and micro broth 2-fold dilution method to detect the volatile chemical compounds and the minimum inhibitory concentration. At the same time, the study investigated the effects of A. forbesii grown under different shading conditions on the signs, pathological changes of lung tissues, serum cytokine levels, activities of mitochondrial respiratory chain complexes Ⅰ-Ⅴ in lung tissues, and relative expression of related genes of mice with syndrome of cold fluid accumulating in lung. The results indicated that with the increase of shading, the content of kakuol, methyl eugenol, and asarinin in A. forbesii and the antibacterial effect showed a tendency of increasing first and then decreasing, and the NL40 group was significantly better than the other groups. Under the conditions of NL20 and NL40, A. forbesii significantly alleviated the pathological damage to lung tissues, restored the homeostasis of the lung, and enhanced the energy metabolism level of mice with syndrome of cold fluid accumulating in lung. In addition, A. forbesii planted under the two conditions reduced the content of interleukin-8(IL-8), interleukin-13(IL-13), tumor necrosis factor-α(TNF-α), and mucin 5AC(MUC5AC), increased the levels of interleukin-10(IL-10) and aquaporin 1(AQP1), lowered the expression of MMP9, VEGF, TGF-β, and MAPK3. In conclusion, the therapeutic effect of A. forbesii on the syndrome of cold fluid accumulating in lung was positively correlated with the degree of shading, and the chemical composition and efficacy of warming lung and resolving fluid retention were optimal under the conditions of NL20-NL40. This study can provide reference for the pharmacological research and cultivation of A. forbesii.
Animals ; Mice ; Lung/pathology* ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Light ; Cytokines/genetics* ; Humans