ObjectiveTo explore the interaction and competitive binding of Homo sapiens long intergenic non-protein-coding RNA 1134 （LINC01134） to CCCTC-binding factor CTCF， affecting the transcription of cyclin-dependent kinase inhibitor （p21） and influencing the proliferation of A549 cells， in order to investigate the possible mechanism of Astragali Radix and Hedyotis diffusa （A-H） in inhibiting A549 proliferation by regulating this axis. MethodsRNA-binding protein immunoprecipitation （RIP） assays were conducted to examine the interaction between LINC01134 and CTCF， and chromatin immunoprecipitation （ChIP） assays were used to study the effect of LINC01134 overexpression on the interaction between CTCF and p21. Stable A549 cell lines （oe-NC and oe-LINC01134） were established using lentiviral transfection， and each group was treated with 10% A-H drug-containing serum. Real-time PCR and Western blot analyses were performed to detect the effects of A-H on the expression of LINC01134， CTCF， and p21 in A549 cells. Cell counting kit-8 （CCK-8） and colony formation assays were used to assess the effects of A-H on A549 cell proliferation via LINC01134. Flow cytometry was employed to evaluate the effects of A-H on the A549 cell cycle through LINC01134， and Western blot was used to detect changes in cell cycle proteins. ResultsCompared with the IgG group， the oe-CTCF group showed a significantly increased abundance of LINC01134 aggregates （P0.01）. Compared with the oe-Vector group， p21 abundance in CTCF complexes was significantly reduced in the oe-LINC01134 group （P0.01）. Compared with the 10% blank + oe-LINC01134 group， the 10% A-H + oe-LINC01134 group reversed the expression of LINC01134 and p21 （P0.05）， but had no significant regulatory effect on CTCF. Compared with the 10% blank + oe-LINC01134 group， the 10% A-H + oe-LINC01134 group reversed cell viability at 72 h （P0.05）， inhibited malignant proliferation （P0.05）， and reversed the proportions of cells in the G₀/G₁ and S phases （P0.01）. Furthermore， compared with the 10% blank + oe-LINC01134 group， the 10% A-H + oe-LINC01134 group reversed the expression of Cyclin D₁， CDK4， Cyclin E， CDK2， phosphorylated retinoblastoma protein （p-Rb）， and E2F transcription factor 3 （E2F3） （P0.01）. ConclusionA-H regulates the LINC01134-CTCF-p21 axis to block the G₁/S phase transition of A549 cell cycle， accelerate cellular senescence， and inhibit malignant proliferation.

ObjectiveTo explore the interaction and competitive binding of Homo sapiens long intergenic non-protein-coding RNA 1134 （LINC01134） to CCCTC-binding factor CTCF， affecting the transcription of cyclin-dependent kinase inhibitor （p21） and influencing the proliferation of A549 cells， in order to investigate the possible mechanism of Astragali Radix and Hedyotis diffusa （A-H） in inhibiting A549 proliferation by regulating this axis. MethodsRNA-binding protein immunoprecipitation （RIP） assays were conducted to examine the interaction between LINC01134 and CTCF， and chromatin immunoprecipitation （ChIP） assays were used to study the effect of LINC01134 overexpression on the interaction between CTCF and p21. Stable A549 cell lines （oe-NC and oe-LINC01134） were established using lentiviral transfection， and each group was treated with 10% A-H drug-containing serum. Real-time PCR and Western blot analyses were performed to detect the effects of A-H on the expression of LINC01134， CTCF， and p21 in A549 cells. Cell counting kit-8 （CCK-8） and colony formation assays were used to assess the effects of A-H on A549 cell proliferation via LINC01134. Flow cytometry was employed to evaluate the effects of A-H on the A549 cell cycle through LINC01134， and Western blot was used to detect changes in cell cycle proteins. ResultsCompared with the IgG group， the oe-CTCF group showed a significantly increased abundance of LINC01134 aggregates （P0.01）. Compared with the oe-Vector group， p21 abundance in CTCF complexes was significantly reduced in the oe-LINC01134 group （P0.01）. Compared with the 10% blank + oe-LINC01134 group， the 10% A-H + oe-LINC01134 group reversed the expression of LINC01134 and p21 （P0.05）， but had no significant regulatory effect on CTCF. Compared with the 10% blank + oe-LINC01134 group， the 10% A-H + oe-LINC01134 group reversed cell viability at 72 h （P0.05）， inhibited malignant proliferation （P0.05）， and reversed the proportions of cells in the G₀/G₁ and S phases （P0.01）. Furthermore， compared with the 10% blank + oe-LINC01134 group， the 10% A-H + oe-LINC01134 group reversed the expression of Cyclin D₁， CDK4， Cyclin E， CDK2， phosphorylated retinoblastoma protein （p-Rb）， and E2F transcription factor 3 （E2F3） （P0.01）. ConclusionA-H regulates the LINC01134-CTCF-p21 axis to block the G₁/S phase transition of A549 cell cycle， accelerate cellular senescence， and inhibit malignant proliferation.

The Proctor's reporting guideline for implementation strategies represents a landmark framework in the field of implementation science, aiming to address the issue of inconsistent reporting in implementation research by standardizing the naming, definition, and operationalization of implementation strategies, thereby enhancing the credibility and utility of research findings. This paper provides an in-depth interpretation of the core connotations of this reporting guideline and illustrates its application in developing interview outlines and specifying implementation strategies, using a brief smoking cessation intervention project as a case study. Through this reporting guideline, abstract recommendations for implementation are systematically transformed into clear, multidimensional operational guides, significantly improving the transparency of strategy connotations and the replicability of actual execution. Meanwhile, the case study highlights the flexibility of the guideline, which allows researchers to adapt the content and format of strategies based on local resources and cultural contexts, thus enhancing practical adaptability while maintaining scientific rigor. However, the application of Proctor's reporting guideline still faces challenges, primarily manifested in the potential confusion surrounding the constructs of temporality and dose in practice, as well as the challenges that the inherent flexibility of the guideline may pose to the assessment of fidelity and effectiveness. Despite these limitations, the reporting guideline remains a vital tool for implementation research; future efforts should focus on optimizing its application—through refining operational guidelines, standardizing flexible adaptations, and involving stakeholders—to better guide implementation studies and continuously promote high-quality development in the field.

ObjectiveTo evaluate the therapeutic effect of Huazhuo SanJie Chubi presciption （HSCD） on chronic gouty arthritis （CGA） rats with low-grade inflammation and to explore the underlying mechanism with a focus on macrophage polarization. MethodsThe 41 male 6-week-old SD rats were randomly allocated， using the random number table， to a normal group （n=8） and a model group （n =33）. CGA with low-grade inflammation was induced in the model group by daily gavage of potassium oxonate （250 mg·kg^-1·d^-1） and hypoxanthine （300 mg·kg^-1·d^-1）， combined with intra-articular injection of a monosodium urate （MSU） crystal suspension （50 μL， 25 g·L^-¹） into the left ankle twice weekly. After 4 weeks of modeling， 3 rats were randomly selected from each group for model validation. The remaining successfully modeled rats were randomly divided into a model group， an HSCD group （10.35 g·kg^-1·d^-1， gavage once daily）， an M1 polarization agonist group （L-methionine sulfoximine， 300 mg·kg^-1， subcutaneous injection every other day）， an M1 polarization agonist + HSCD group， an M2 polarization inhibitor group （PD0325901， 10 mg·kg^-1·d^-1， gavage once daily）， and M2 polarization inhibitor + HSCD group. The corresponding drug or drug combination was administered according to group assignment， whereas rats in the normal and model groups received 0.5% carboxymethyl cellulose sodium （CMC-Na） vehicle （10.35 g·kg^-1·d^-1， gavage once daily）. All interventions were continued for four weeks. During the intervention period， except for the normal group， potassium oxonate （250 mg·kg⁻¹） and hypoxanthine （300 mg·kg^-1） were co-administered by gavage every other day to maintain the model. At the end of treatment， serum uric acid （SUA）， ankle joint diameter and joint swelling index were measured. The levels of high-sensitivity C-reactive protein （hs-CRP）， interleukin-1β （IL-1β）， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， chemokine C-C motif ligand 2 （CCL2）， S100 calcium-binding protein A8/A9 （S100A8/A9）， interleukin-10 （IL-10） and arginase-1 （Arg-1） in serum and joint fluid were determined by enzyme-linked immunosorbent assay （ELISA）. High-frequency ultrasound was used to assess MSU deposition in the ankle joint. Hematoxylin-eosin （HE） staining was performed to evaluate synovial histopathological changes. Quantitative Real-time PCR and immunofluorescence were used to detect the mRNA and protein expression of the M1 macrophage polarization markers inducible nitric oxide synthase （iNOS） and the M2 macrophage polarization marker scavenger receptor cysteine-rich type 1 protein M130 （CD163） in synovial tissue. ResultsCompared with the normal group， the model group showed significantly elevated SUA level and joint swelling index， and increased levels of pro-inflammatory cytokines， CCL2， and S100A8/A9 in both serum and joint fluid （P<0.05）， accompanied by MSU deposition and synovial inflammation in the ankle joint. The mRNA and protein expression levels of macrophage polarization M1/M2 markers iNOS and CD163 in synovial tissues were also significantly up-regulated （P<0.05）. Compared with model group， rats in HSCD group had significantly lower SUA levels， attenuated joint swelling， reduced serum levels of pro-inflammatory cytokines， and decreased levels of CCL2 and S100A8/A9 in both serum and joint fluid， accompanied with alleviated MSU deposition and synovial inflammation （P<0.05）. HSCD markedly downregulated the mRNA and protein expression of M1 marker iNOS （P<0.05）， whereas it had no significant effect on the expression of M2 marker CD163. Compared with the M1 polarization agonist group， the M1 polarization agonist + HSCD group showed significantly reduced joint swelling， lower serum levels of pro-inflammatory cytokines， and decreased levels of CCL2 and S100A8/A9 in joint fluid （P<0.05）. In addition， synovial inflammatory cell infiltration and angiogenesis were attenuated， and iNOS mRNA and protein expression levels were significantly reduced （P<0.05）. Compared with the M2 polarization inhibitor group， the M2 polarization inhibitor + HSCD group exhibited reduced joint swelling， decreased levels of CCL2 and S100A8/A9 in joint fluid and ameliorated synovial inflammation （P<0.05）， whereas the levels of anti-inflammatory mediators （IL-10， Arg-1） and CD163 mRNA and protein expression were not significantly increased. ConclusionHSCD alleviates low-grade inflammation in CGA rats， at least in part， by inhibiting macrophage polarization toward the M1 phenotype.

ObjectiveTo systematically evaluate the content differences of 4 components in Leonuri Herba granules， reveal the quality fluctuation patterns of products from the same and different manufacturers， providing scientific basis for the optimization of production process and quality control. MethodsHigh performance liquid chromatography-diode array detector-charged aerosol detector（HPLC-DAD-CAD） was employed to determine the contents of 4 components（syringic acid， leonurine hydrochloride， ferulic acid， and stachydrine hydrochloride） in samples from 19 manufacturers（53 batches， 159 boxes）. Additionally， fingerprint profiles were constructed， and the fingerprint dissimilarity（P_S） and relative standard deviation（RSD） of different samples from the same manufacturer were calculated. A principal component analysis（PCA） model was established with P_S and the RSD values of the 4 components as variables to classify the manufacturers. Finally， samples from 5 manufacturers（M1-M5） covering three consistency groups were selected to calculate three quality consistency parameters， namely intra-batch consistency（P_A）， inter-batch consistency（P_B）， and P_S. Then， PCA was performed with P_A， P_B， and P_S of these 5 manufacturers as variables. ResultsThe average total content of the 4 index components per bag across the 19 manufacturers ranged from 41.10 mg to 97.54 mg. Among them， the content of stachydrine hydrochloride（a pharmacopoeial quality control component） was 32.46-72.70 mg per bag， all meeting the requirements of the 2025 edition of the Pharmacopoeia of the People's Republic of China， with RSD of 1.7%-17.1%. The content ranges of the other 3 components were as follows：syringic acid of 1.43-41.92 mg per bag， leonurine hydrochloride of 0.67-11.85 mg per bag， and ferulic acid of 0.11-3.81 mg per bag. Notably， leonurine hydrochloride exhibited the most significant content fluctuation among samples from the same manufacturer（RSD of 4.8%-59.2%）. PCA results showed that the 19 manufacturers could be classified into 3 categories. Samples from 8 manufacturers（M2， M6， M7， M8， M10， M15， M17， M18） demonstrated relatively high consistency， five manufacturers（M3， M9， M12， M13， M14） showed moderate consistency， six manufacturers（M1， M4， M5， M11， M16， M19） exhibited low consistency. The two methods yielded consistent classification results for the 5 representative manufacturers， verifying the reliability of the proposed method. Among these， manufacturer M2 showed the best quality consistency and the highest total content of indicator components among M1-M5. ConclusionThe HPLC-DAD-CAD multi-detector hyphenation technology established in this study enables the accurate detection of 4 components in Leonuri Herba granules. Significant differences in the total content of these four components are observed among products from 19 manufacturers. The application of 2 consistency evaluation methods combined with PCA can effectively classify their consistency into 3 categories， and the classification results of the 2 methods are highly consistent. This study provides scientific basis for the process optimization and quality standard improvement of Leonuri Herba granules.

ObjectiveTo systematically evaluate the content differences of 4 components in Leonuri Herba granules， reveal the quality fluctuation patterns of products from the same and different manufacturers， providing scientific basis for the optimization of production process and quality control. MethodsHigh performance liquid chromatography-diode array detector-charged aerosol detector（HPLC-DAD-CAD） was employed to determine the contents of 4 components（syringic acid， leonurine hydrochloride， ferulic acid， and stachydrine hydrochloride） in samples from 19 manufacturers（53 batches， 159 boxes）. Additionally， fingerprint profiles were constructed， and the fingerprint dissimilarity（P_S） and relative standard deviation（RSD） of different samples from the same manufacturer were calculated. A principal component analysis（PCA） model was established with P_S and the RSD values of the 4 components as variables to classify the manufacturers. Finally， samples from 5 manufacturers（M1-M5） covering three consistency groups were selected to calculate three quality consistency parameters， namely intra-batch consistency（P_A）， inter-batch consistency（P_B）， and P_S. Then， PCA was performed with P_A， P_B， and P_S of these 5 manufacturers as variables. ResultsThe average total content of the 4 index components per bag across the 19 manufacturers ranged from 41.10 mg to 97.54 mg. Among them， the content of stachydrine hydrochloride（a pharmacopoeial quality control component） was 32.46-72.70 mg per bag， all meeting the requirements of the 2025 edition of the Pharmacopoeia of the People's Republic of China， with RSD of 1.7%-17.1%. The content ranges of the other 3 components were as follows：syringic acid of 1.43-41.92 mg per bag， leonurine hydrochloride of 0.67-11.85 mg per bag， and ferulic acid of 0.11-3.81 mg per bag. Notably， leonurine hydrochloride exhibited the most significant content fluctuation among samples from the same manufacturer（RSD of 4.8%-59.2%）. PCA results showed that the 19 manufacturers could be classified into 3 categories. Samples from 8 manufacturers（M2， M6， M7， M8， M10， M15， M17， M18） demonstrated relatively high consistency， five manufacturers（M3， M9， M12， M13， M14） showed moderate consistency， six manufacturers（M1， M4， M5， M11， M16， M19） exhibited low consistency. The two methods yielded consistent classification results for the 5 representative manufacturers， verifying the reliability of the proposed method. Among these， manufacturer M2 showed the best quality consistency and the highest total content of indicator components among M1-M5. ConclusionThe HPLC-DAD-CAD multi-detector hyphenation technology established in this study enables the accurate detection of 4 components in Leonuri Herba granules. Significant differences in the total content of these four components are observed among products from 19 manufacturers. The application of 2 consistency evaluation methods combined with PCA can effectively classify their consistency into 3 categories， and the classification results of the 2 methods are highly consistent. This study provides scientific basis for the process optimization and quality standard improvement of Leonuri Herba granules.

BackgroundEmotional disorders in adolescents have emerged as a prominent issue in recent years. Current mainstream clinical assessment approaches for such conditions predominantly rely on interviews and rating scales， which are limited by inherent drawbacks such as high subjectivity and recall bias. Accordingly， there exists an urgent clinical need for the development of objective， quantifiable auxiliary diagnostic tools.In previous studies， frontal electroencephalography （EEG） has demonstrated significant value in assessing depressive and anxiety. However， the lack of standardized quantitative metrics and intuitive visual analytical approaches has severely restricted clinical interpretability of EEG data and diminished patient engagement. To address these key limitations， the present study proposes an innovative analytical framework that converts frontal EEG signals into quantifiable visual metrics to enhance clinical comprehension and acceptance. ObjectiveTo explore the value of frontal EEG in assessing anxiety， depression， and sleep quality in adolescents with emotional disorders， with the aim of providing objective auxiliary tools for clinical diagnosis and assessment of adolescents with emotional disorders. MethodsThis cross-sectional study recruited 105 adolescents aged 12-18 years who visited the outpatient department of a specialized mental hospital in Beijing from April 2023 to April 2024. All participants met the diagnostic criteria for mood （affective） disorders or anxiety disorders in the International Classification of Diseases， tenth edition （ICD-10）. Frontal EEG signals were collected within a big data analytics-driven framework and further processed by EEG system to generate six quantitative cerebral function indices， namely brain load， tension and excitement， emotional stress， sleepiness index， cerebral vitality， and cerebral fatigue. In addition， validated standardized scales， including the Self-rating Anxiety Scale （SAS）， the Self-rating Depression Scale （SDS）， and the Pittsburgh Sleep Quality Index （PSQI）， were administered for anxiety， depressive symptoms， and sleep quality， respectively. ResultsIn adolescent patients with emotional disorders， the SAS score exhibited significant positive correlations with brain load （r_s=0.328， P<0.01）， emotional stress （r_s=0.341， P<0.01）， and cerebral fatigue （r_s=0.286， P<0.01）. The SDS score was positively correlated with brain load （r_s=0.275， P<0.01）， emotional stress （r_s=0.241， P<0.05）， and cerebral fatigue （r_s=0.311， P<0.01）， while showing a significant negative correlation with cerebral vitality （r_s=-0.212， P<0.05）. Additionally， the PSQI total score demonstrated positive correlations with brain load （r_s=0.340， P<0.01）， emotional stress （r_s=0.322， P<0.01）， and cerebral fatigue （r_s=0.229， P<0.05）. ConclusionFrontal EEG-derived indices， including brain load， emotional stress， cerebral fatigue and cerebral vitality， may serve as objective markers for reflecting anxiety， depression， and sleep quality in adolescents with emotional disorders. ［Funded by Beijing High level Innovation and Entrepreneurship Talent Support Program （number， 202504841041）； Horizontal Joint Project］

ObjectiveTo investigate the inhibitory effect of gingerol， an active component of ginger， on Staphylococcus aureus （S. aureus） infection， and to preliminarily explore its mechanism related to extracellular vesicles （EVs）. MethodsS.aureus infection models were established in human umbilical vein endothelial cell （HUVECs）， Vero E6 cells， and C57BL/6 mice. Experimental groups included control， infection， and gingerol-treated groups. Bacterial load and VE-cadherin protein expression were detected using immunofluorescence and Western blot. EVs were isolated by size exclusion chromatography and characterized by transmission electron microscopy and nanoparticle tracking analysis. miRNA sequencing was performed on EVs. ResultsGingerol treatment significantly reduced the bacterial load in both in vitro and in vivo infection models and upregulated VE-cadherin expression. miRNA sequencing of EVs revealed that S. aureus infection upregulated the expression of hsa-miR-320c， while gingerol treatment reversed this abnormal expression. Bioinformatic analysis further predicted that the target genes of hsa-miR-320c were significantly enriched in cell junction-related pathways. ConclusionGingerol exhibits clear antibacterial and host-protective effects， by regulating hsa-miR-320c in EVs to maintain endothelial barrier integrity.

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.

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.