Parkinson's disease （PD） is a complex neurodegenerative disease involving multiple systems and neurotransmitters. Due to the high clinical heterogeneity of PD，it is urgent to establish a comprehensive and long-term traditional Chinese medicine （TCM） management model. In this paper，the conceptual framework of full-cycle management of PD is preliminarily constructed：based on the evolution of the pathophysiological mechanisms of protein deposition and neurotransmitter disorder in PD，the three-stage syndrome characteristics of the prodromal stage （predominant healthy Qi with subtle pathogenic factors），the early clinical stage （declining healthy Qi with growing pathogenic factors） and the middle and late stages （overwhelming pathogenic factors with deficient healthy Qi） are longitudinally described. Through the syndrome differentiation of visceral manifestations，the etiology and pathogenesis of PD motor and non-motor symptoms were comprehensively analyzed，while the matching treatment methods and prescriptions were inferred，and the modular scheme of the combining main symptoms，accompanying symptoms and secondary symptoms was proposed. The conceptual gap of TCM regarding motor complications （'variable syndrome'） and PD-related hyperpyrexia syndrome （'critical syndrome'） was explained. This framework reflects the characteristics of combination of disease and syndrome and overall constant motion，and provides new theories and research ideas for individualized and whole-process management of PD in TCM.

Parkinson's disease （PD） is a complex neurodegenerative disease involving multiple systems and neurotransmitters. Due to the high clinical heterogeneity of PD，it is urgent to establish a comprehensive and long-term traditional Chinese medicine （TCM） management model. In this paper，the conceptual framework of full-cycle management of PD is preliminarily constructed：based on the evolution of the pathophysiological mechanisms of protein deposition and neurotransmitter disorder in PD，the three-stage syndrome characteristics of the prodromal stage （predominant healthy Qi with subtle pathogenic factors），the early clinical stage （declining healthy Qi with growing pathogenic factors） and the middle and late stages （overwhelming pathogenic factors with deficient healthy Qi） are longitudinally described. Through the syndrome differentiation of visceral manifestations，the etiology and pathogenesis of PD motor and non-motor symptoms were comprehensively analyzed，while the matching treatment methods and prescriptions were inferred，and the modular scheme of the combining main symptoms，accompanying symptoms and secondary symptoms was proposed. The conceptual gap of TCM regarding motor complications （'variable syndrome'） and PD-related hyperpyrexia syndrome （'critical syndrome'） was explained. This framework reflects the characteristics of combination of disease and syndrome and overall constant motion，and provides new theories and research ideas for individualized and whole-process management of PD in TCM.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

ObjectiveTo analyze the lipid characteristics and related risk factors of children with Wilson disease （WD）. MethodsThe clinical data of 315 children with WD and 248 healthy children who underwent physical examination were retrospectively collected. The differences in lipid levels between the two groups were compared. The WD group was divided into the normal lipid group （85 cases） and the dyslipidemia group （230 cases） according to lipid levels. General data and biochemical indicators were compared between the two groups， and multivariate Logistic regression analysis was used to analyze the independent risk factors for dyslipidemia in children with WD. ResultsThe incidence of dyslipidemia in children with WD was 73.0% （230/315）， comprising 77 cases （33.5%） of hypertriglyceridemia， 11 cases （4.8%） of hypercholesterolemia， 104 cases （45.2%） of combined hyperlipidemia， 9 cases （3.9%） of hyperlipoprotein（a）emia， and 29 cases （12.6%） of hypoalphalipoproteinemia. There were statistically significant differences in age distribution among different types of dyslipidemia （P<0.05）， whereas no significant differences were observed in gender distribution （P>0.05）. Compared with the normal lipid group， the dyslipidemia group showed significantly higher levels of homocysteine， superoxide dismutase （SOD）， platelet count （PLT）， fibrinogen， alanine aminotransferase， aspartate aminotransferase， γ-glutamyl transferase， uric acid， cystatin C （Cys-C）， type IV collagen （C-IV）， and laminin （all P<0.05）. Multivariate Logistic regression analysis showed that C-IV （OR=5.037， 95% CI： 2.562-9.900）， PLT （OR=2.297， 95% CI： 1.580-3.339）， Cys-C （OR=2.008， 95% CI： 1.395-2.890）， and SOD （OR=1.996， 95% CI： 1.342-2.970） were all independent risk factors for dyslipidemia in children with WD. ConclusionChildren with WD have a high incidence of dyslipidemia， which is dominated by combined hyperlipidemia and hypertriglyceridemia. C-IV， PLT， Cys-C， and SOD are independent risk factors for dyslipidemia in children with WD.

ObjectiveTo investigate the effects of Hei Xiaoyaosan on neuroinflammation in APP/PS1 mice and decipher the mechanism based on the C-X3-C chemokine ligand 1 （CX3CL1）-CX3CL1 receptor 1 （CX3CR1） signaling axis. MethodsSixty 16-week-old male APP/PS1 mice were selected and acclimatized for one week， and they were then randomly allocated into a model group， a CX3CL1 group （bilateral hippocampal injection of CX3CL1 at 0.5 g·L^-1）， and high-， medium-， and low-dose （22.10， 11.05， and 5.53 g·kg^-1， respectively） Hei Xiaoyaosan groups， with 12 mice in each group. Twelve age-matched male C57BL/6J mice served as the blank group （bilateral hippocampal injection of an equal volume of PBS）. The high-， medium-， and low-dose Hei Xiaoyaosan groups received corresponding drugs via gavage， while the blank group received an equal volume of normal saline， with an intervention period of 90 days. Morris water maze was used to assess learning and memory abilities. Nissl staining was performed to observe the pathological changes in neurons of the hippocampal CA1 region. Immunohistochemistry was adopted to detect amyloid-β_1-42 （Aβ_1-42） deposition in the hippocampal CA1 region. The immunofluorescence assay was employed to detect the expression of M1 and M2 microglial markers， including cluster of differentiation 86 （CD86）/ionized calcium-binding adapter molecule 1 （Iba-1） and arginase-1 （Arg1）/Iba1. Enzyme-linked immunosorbent assay （ELISA） was employed to measure the levels of interleukin-8 （IL-8） and interleukin-13 （IL-13） in the hippocampal tissue. Western blot was employed to determine the protein levels of CX3CL1， CX3CR1， CREB-binding protein （CBP）， cyclic AMP response element-binding protein （CREB）， phosphorylated （p）-CREB， and brain-derived neurotrophic factor （BDNF） in the hippocampal tissue. ResultsCompared with the blank group， the model group exhibited prolonged escape latency on day 5 and a reduced swimming distance in the target quadrant （P<0.01）， disarrangement of hippocampal neurons， with a reduced number of cells and uneven Nissl body staining， increased CD86/Iba1 expression， decreased Arg1/Iba1 expression （P<0.01）， enhanced Aβ expression （P<0.01）， an elevated IL-8 level and a declined IL-13 level （P<0.01）， and downregulated protein levels of CX3CL1， CX3CR1， CBP， p-CREB， and BDNF （P<0.01）. Compared with the model group， all treatment groups showed shortened escape latency on day 5 and an increased swimming distance in the target quadrant （P<0.05， P<0.01）， regular arrangement of neurons with an increased number and increased Nissl bodies， reduced CD86/Iba1 expression， increased Arg1/Iba1 and decreased Aβ expression （P<0.01）， and a declined IL-8 level and an elevated IL-13 level （P<0.05， P<0.01）. In the CX3CL1 group and the high- and medium-dose Hei Xiaoyaosan groups， the relative expression levels of CX3CL1， CX3CR1， CBP， and p-CREB were upregulated （P<0.01）. In the low-dose Hei Xiaoyaosan group， the relative expression levels of CX3CL1， CX3CR1， CBP， p-CREB/CREB， and BDNF were upregulated （P<0.05， P<0.01）. ConclusionHei Xiaoyaosan can improve learning and cognitive abilities in APP/PS1 mice. Specifically， it may regulate the CX3CL1/CX3CR1 signaling axis to activate the CREB/BDNF signaling pathway for the subsequent release of BDNF， modulation of microglial polarization， reduction of inflammatory cytokine levels， and attenuation of Aβ deposition.

ObjectiveTo investigate the potential mechanisms and pathways through which Gandouling （GDL） exerts its effects in the treatment of liver fibrosis in Wilson disease. MethodsSixty male SD rats were randomly divided into six groups： the normal group， the model group， the GDL low-， medium-， and high-dose groups （0.24， 0.48， 0.96 g·kg^-1）， and the penicillamine group （90 mg·kg^-1）， with 10 rats in each group. A copper-loaded Wilson disease rat model was established by gavage administration of 300 mg·kg^-1 copper sulfate pentahydrate to all groups except the normal group. Hematoxylin-eosin （HE） staining and Masson staining were used to observe the pathomorphological changes in the liver. Enzyme-linked immunosorbent assay （ELISA） was employed to measure the levels of hyaluronic acid （HA）， laminin （LN）， procollagen type-Ⅲ peptide （PC-Ⅲ）， and collagen type-Ⅳ （C-Ⅳ）. Transmission electron microscopy was used to examine the ultrastructure of liver tissues. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the expression levels of liver tissues and serum exosomal long noncoding RNA H19 （LncRNA H19）， phosphatidylinositol 3-kinase （PI3K）， protein kinase B （Akt）， and mammalian target of rapamycin （mTOR）. Western blot analysis was performed to assess the expression levels of PI3K， Akt， mTOR， and their phosphorylated forms， as well as autophagy-related proteins Beclin1 and microtubule-associated protein 1 light chain 3B （LC3-Ⅱ/LC3-Ⅰ） in liver tissues. Beclin1 and LC3-Ⅱ fluorescence signal intensity was observed by immunofluorescence. ResultsCompared with the normal group， the model group exhibited inflammatory cell infiltration in hepatocytes， unclear nuclear boundaries with cell cleavage and necrosis， and collagen fiber deposition around confluent areas. The levels of HA， LN， PC-Ⅲ， and C-Ⅳ were significantly elevated （P<0.01）. Transmission electron microscopy revealed an increased number of autophagic vesicles， with autophagic lysosomes exhibiting a single-layer membrane structure following degradation of most envelopes. Expression levels of Beclin1 and LC3-Ⅱ/LC3-Ⅰ were significantly increased （P<0.01）， and fluorescence signals of Beclin1 and LC3-Ⅱ were markedly enhanced. The protein expression levels of PI3K， Akt， mTOR， p-PI3K， p-Akt， and p-mTOR were reduced （P<0.01）， while LncRNA H19 expression was increased （P<0.01）， and mRNA expression levels of PI3K， Akt， and mTOR were decreased （P<0.01）. After treatment with GDL， the degree of liver fibrosis was significantly improved， with decreased levels of HA， LN， PC-Ⅲ， and C-Ⅳ. The number of autophagic vesicles was significantly reduced， and expression levels of Beclin1 and LC3-Ⅱ/LC3-Ⅰ proteins were lower （P<0.01）. The fluorescence signals of Beclin1 and LC3-Ⅱ weakened dose-dependently. The protein levels of PI3K， Akt， mTOR， p-PI3K， p-Akt， and p-mTOR were elevated （P<0.01）， while the expression level of LncRNA H19 was reduced （P<0.01）. Furthermore， the mRNA expression levels of PI3K， Akt， and mTOR increased （P<0.05， P<0.01）. ConclusionGDL may alleviate liver fibrosis and reduce liver injury by regulating the PI3K/Akt/mTOR autophagy signaling pathway via LncRNA H19.

OBJECTIVES: To evaluate the inhibitory effect of Macrothele raveni crude venom against proliferation of different cancer cells and identify the active components in the venom. METHODS: Different cancer cell lines were treated with different concentrations of Macrothele raveni venom for 48 h, and cell proliferation and the half-maximal inhibitory concentrations (IC₅₀) of the venom were assessed with CCK-8 assay. The apoptosis rate of breast cancer MCF7 cells following the treatment was analyzed with flow cytometry, and the changes in cellular caspase-8 and caspase-9 expressions were detected. The crude venom was separated into protein, peptide, and small-molecule compound fractions using gel filtration chromatography and high-performance liquid chromatography (HPLC). The protein and peptide components were identified using proteomics analysis, and small-molecule compounds were structurally characterized using nuclear magnetic resonance (NMR), mass spectrometry (MS), and HPLC. RESULTS The crude venom exhibited strong concentration-dependent inhibitory effects on proliferation of MCF7 cells and nasopharyngeal carcinoma SUNE1 and HONE1 cells (IC₅₀ of 2.14±0.29, 1.57±0.14, and 2.85±0.15 µg/mL, respectively), with less potent inhibitory effects in gastric cancer HGC27 cells and colorectal cancer SW620 cells (IC₅₀ of 3.02±0.27 and 3.02±0.28 µg/mL, respectively). The crude venom significantly promoted MCF7 cell apoptosis likely via the caspase 8 signaling pathway. The protein fraction from the crude venom showed a weak inhibitory effect in MCF7 cells, whereas the peptide fraction exhibited a much stronger inhibitory effect (IC₅₀ of 6.41±0.31 µg/mL). The peptides in the peptide fraction, with relative molecular mass around 10 000, were homologous to those found in Macrothele gigas venom. The small-molecule fraction consisted mainly of nucleotide metabolites without obvious inhibitory effects in MCF7 cells, but its combination with the peptide fraction showed significantly enhanced inhibitory activity. Conclusion The inhibitory effects of Macrothele raveni venom, which vary significantly across different cancer cell lines, are attributed primarily to its peptide components, which may act synergistically with the nucleotide metabolites.
Humans ; Cell Proliferation/drug effects* ; Apoptosis/drug effects* ; Animals ; Cell Line, Tumor ; MCF-7 Cells ; Caspase 8/metabolism* ; Peptides/pharmacology* ; Caspase 9/metabolism*

OBJECTIVES: To explore the value of ferroptose-related genes in the diagnosis and prediction of ulcerative colitis (UC). METHODS: We used UC dataset from the GEO database to screen for differentially expressed genes (DEGs) in UC. The DEGs related to ferroptositis were screened from the FerrDb database and their functions were analyzed. The hub genes were identified by constructing the protein-protein interaction network (PPI), the differences in immune infiltration levels between UC and the control group were evaluated using CIBERSORT, and the diagnostic values of the hub genes for UC were verified by using the training set. In a mouse model of UC, we examined the expression levels of the hub genes in the colon tissues of the mice using real-time fluorescence quantitative PCR (qPCR). RESULTS: We identified a total of 76 DEGs related to ferroptosis. Functional enrichment analysis showed that these genes were significantly enriched in ferroptosis and hypoxia pathways. The PPI network identified 10 hub genes, and 9 of them were highly expressed in UC. Analysis of immune cell infiltration showed that 27 cell types were significantly increased in UC (P<0.05), and the immune checkpoints-related genes had the strongest correlation with the hub gene PPARG (P<0.05). Verification analysis using the training set showed that P4HB, PPARG and STAT3 had the best predictive value for UC (P<0.05). In the UC mouse model, the expression of PPARG was significantly decreased and the expressions of P4HB and STAT3 were significantly increased in the colon tissues of the mice as compared with the normal mice. CONCLUSIONS Ferroptose-related genes have significant value for diagnosis and prediction of UC.
Colitis, Ulcerative/genetics* ; Animals ; Mice ; Ferroptosis/genetics* ; Humans ; Protein Interaction Maps ; Disease Models, Animal ; Gene Expression Profiling ; STAT3 Transcription Factor/genetics*