ObjectiveTo investigate the effects of excessive activation of the Specific protein 1 （Sp1）-MicroRNA-582-3p （miR-582-3p）-cyclin-dependent kinase inhibitor （p27） axis on the cell cycle and proliferation of A549 lung adenocarcinoma cells at the cellular level， thereby investigating the possible mechanisms by which Astragali Radix and Hedyotis diffusa（A-H） regulate the axis to inhibit A549 cells proliferation. MethodsLentiviral plasmid transfection technology was used to obtain four stable A549 transgenic cell lines： shRNA-Sp1+LV-miR-582-3p mimic， shRNA-Sp1+LV-mNC， shRNA-NC+LV-miR-582-3p mimic， and shRNA-NC+LV-mNC. Real-time PCR was used to detect the effect of Sp1 on miR-582-3p expression in A549 lung adenocarcinoma cells. CCK-8 and colony formation assay were used to detect the effect of Sp1 on cell proliferation through miR-582-3p， while flow cytometry was used to detect the effect of Sp1 on cell cycle via miR-582-3p. Western blot was used to detect the effect of Sp1 on cyclin in A549 cells through miR-582-3p. CCK-8 was employed to detect the effects of different concentrations （5%， 10%， 20%， 40%， 80%） of A-H on A549 cell viability， and the optimal concentration was selected for subsequent mechanism exploration. Stable transgenic strains oe-Sp1 and control oe-Vector were constructed using the above-mentioned transfection techniques. Real-time PCR was then used to investigate the effect of A-H on miR-582-3p expression in A549 cells， while Western blot was employed to detect the effect of A-H on Sp1 and p27 expression in A549 lung adenocarcinoma cells. ResultsCompared with the shRNA-NC+LV-mNC group， the expression of miR-582-3p was significantly inhibited in the shRNA-Sp1+LV-mNC group （P<0.01）. Compared with the shRNA-Sp1+LV-mNC group， the shRNA-Sp1+LV-miR-582-3p mimic group significantly reversed miR-582-3p expression （P<0.01）， indicating that Sp1 has a significant regulatory effect on miR-582-3p. Compared with the shRNA-Sp1+LV-mNC group， the shRNA-Sp1+LV-miR-582-3p mimic group significantly reversed cell proliferation （P<0.01）， suggesting that miR-582-3p can partially reverse the proliferative effect of Sp1 on A549 lung adenocarcinoma. Compared with the shRNA-Sp1+LV-mNC group， the shRNA-Sp1+LV-miR-582-3p mimic group showed a significant decrease in G₀/G₁ proportions， while the G₂/M and S phase proportions increased significantly （P<0.01）， indicating that miR-582-3p can partially reverse the effect of Sp1 on the A549 cell cycle. Compared with the shRNA-Sp1+LV-mNC group， the shRNA-Sp1+LV-miR-582-3p mimic group significantly reversed the expression of various proteins with the decrease of p27 and the increase of Cyclin D₁， CDK4， Cyclin E， CDK2， p-Rb， and E2F3 （P<0.01）， indicating that miR-582-3p can partially reverse the effect of Sp1 on the cell cycle of A549 lung adenocarcinoma. Compared with the blank group， the serum containing A-H significantly inhibited A549 cell viability in a concentration-dependent manner. Therefore， 10% A-H was selected for intervention of subsequent mechanism experiments. Compared with A-H+oe-Vector， A-H+oe-Sp1 significantly reversed the downregulation of Sp1， miR-582-3p， and the upregulation of p27 （P<0.01）. This suggests that Sp1 can partially reverse the effects of A-H on miR-582-3p and p27 levels in A549 lung adenocarcinoma cells. ConclusionOveractivation of the Sp1-miR-582-3p-p27 axis significantly promotes the proliferation of A549 lung adenocarcinoma cells， and the potential mechanism of the inhibitory effect of A-H on the proliferation of A549 cells may be related to its inhibition on the overactivation of the Sp1-miR-582-3p-p27 axis.

BACKGROUND:Our previous study found that Modified Erxian Pill could alleviate inflammation in collagen-induced arthritis rats,but its mechanism needs to be further verified. OBJECTIVE:To analyze the components absorbed in the blood of Modified Erxian Pill,and observe the effect of the drug-containing serum of Modified Erxian Pill on pyroptosis of J774A.1 macrophages. METHODS:(1)Analysis of components absorbed in the blood of Modified Erxian Pill:Ultra-high performance liquid chromatography-high resolution mass spectrometry was used to detect and identify Modified Erxian Pill and its components absorbed in the blood.(2)Effect of the drug-containing serum of Modified Erxian Pill on pyroptosis of J774A.1 macrophages:Molecular docking technology was used to initially verify the sesquiterpenoids and NLRP3 in components absorbed in the blood of Modified Erxian Pill.J774A.1 macrophages were randomly divided into blank control group,lipopolysaccharide+adenosine triphosphate group,and lipopolysaccharide+adenosine triphosphate+Modified Erxian Pill with low(2.5%),medium(5%),and high(10%)dose groups.The release of lactate dehydrogenase in the cell supernatant of each group was detected according to the kit instructions.The levels of interleukin-1β and interleukin-18 in cell supernatant were detected in each group by ELISA.The cell membrane damage was detected by Hoechst/PI staining.The expression levels of NLRP3,Caspase-1,GSDMD,and GSDMD-N protein in the cells of each group were detected by western blot assay. RESULTS AND CONCLUSION:(1)A total of 32 active components of Modified Erxian Pill were identified,and 21 components entered the blood.The main components into blood included a variety of sesquiterpenoids.(2)Molecular docking results showed that 3-O-Acetyl-13-deoxyphomenone,Incensol oxide,Atractylenolide III,Rupestonic acid,and 3,7-Dihydroxy-9,11-eremophiladien-8-one had good binding activity with NLRP3.(3)Compared with the blank control group,lactate dehydrogenase activity and the expression levels of interleukin-1β and interleukin-18 were significantly increased in cell supernatant of lipopolysaccharide+adenosine triphosphate group(P<0.001).Hoechst/PI staining showed that the number of PI-positive cells was significantly increased.After the intervention of lipopolysaccharide+adenosine triphosphate+Modified Erxian Pill group,all of them showed different degrees of reduction.(4)Compared with the blank control group,NLRP3,Caspase-1,GSDMD,and GSDMD-N protein expression levels were significantly increased in the lipopolysaccharide+adenosine triphosphate group(P<0.05).Compared with lipopolysaccharide+adenosine triphosphate group,the protein expressions of NLRP3,Caspase-1,GSDMD,and GSDMD-N were significantly decreased in the lipopolysaccharide+adenosine triphosphate+Modified Erxian Pill group(P<0.05),and had a certain dose dependence.These findings verify that the drug-containing serum of Modified Erxian Pill may inhibit the pyroptosis of J774A.1 macrophages by regulating the NLRP3/Caspase-1/GSDMD pathway.

BACKGROUND:Rheumatoid arthritis is an inflammatory disease.Many studies have shown that wogonin has a good anti-inflammatory effect on rheumatoid arthritis,but its exact efficacy and specific mechanism of action remain to be clarified. OBJECTIVE:To investigate the mechanism of wogonin ameliorating joint inflammation by regulating endoplasmic reticulum stress pathway in rats with collagen-induced arthritis. METHODS:(1)At the animal level:Female Wistar rats were divided into healthy control group,arthritis model group and wogonin treatment group.Rat models of arthritis in the latter two groups were established by subcutaneous injection of bovine type Ⅱ collagen and adjuvant.In the wogonin group,wogonin was given by gavage for 28 consecutive days after modeling.During this period,the rats in each group were weighed,and arthritis score and ankle swelling were measured every 7 days.After the experiment,the pathological changes of the joint were observed,the mRNA and protein levels of endoplasmic reticulum stress pathway GRP78 and CHOP were detected by qRT-PCR,western blot,and immunohistochemistry.(2)At the cellular level,cell counting kit-8 was used to detect the cytotoxic effect of wogonin on fibroblast-like synoviocytes from rats with collagen-induced arthritis.The fibroblast-like synoviocytes induced by thapsigargin were treated with different concentrations of wogonin.The levels of interleukin-1β and tumor necrosis factor-α in the cell supernatant were detected by ELISA,and the intracellular reactive oxygen species in each group were determined by DCFH-DA probe method.The mRNA and protein levels of GRP78,IRE1α,XBP1s and CHOP were detected by qRT-PCR and western blot,respectively. RESULTS AND CONCLUSION:Compared with the healthy control group,arthritis index score and ankle swelling degree in the arthritis model group were increased(P<0.01),synovial hyperplasia,inflammatory cell infiltration,cartilage destruction and bone erosion were observed in pathological sections,and the mRNA and protein expressions of GRP78 and CHOP in the ankle were significantly increased(P<0.01),which were mainly located in synovial tissue and articular surface.Compared with the arthritis model group,the arthritis index score and ankle swelling degree in the wogonin treatment group were decreased(P<0.05),synovial hyperplasia and the number of inflammatory cells were decreased,cartilage destruction and bone erosion were alleviated,the mRNA and protein expression levels of GRP78 and CHOP in the ankle were decreased(P<0.05),particularly in synovial tissue and on the articular surface.There was no significant difference in body mass among the three groups(P>0.05).In the cell experiment,200 μmol/L wogonin significantly reduced the survival rate of fibroblast-like synoviocytes(P<0.01).Compared with the blank control group,the levels of interleukin-1β,tumor necrosis factor-α,content of reactive oxygen species,and mRNA and protein expression of GRP78,IRE1α,XBP1s,and CHOP in the thapsigargin group were significantly increased(P<0.05);compared with the thapsigargin group,50 and 100 μmol/L wogonin significantly reduced the levels of interleukin-1β and tumor necrosis factor-α in the cell supernatant(P<0.05,P<0.01),and 100 μmol/L wogonin significantly reduced the content of reactive oxygen species(P<0.01)and down-regulated the mRNA and protein expression levels of GRP78,IRE1α,XBP1s and CHOP(all P<0.05).These results suggest that wogonin can effectively alleviate joint inflammatory responses in rats with collagen-induced arthritis,and the endoplasmic reticulum stress pathway may be the key target of its intervention.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.