Objective To investigate the association between plasma homocysteine(Hcy)level and coronary artery calcification(CAC)and its clinical predictive efficacy.Methods A total of 172 patients who underwent coronary CT angiography North China University of Science and Technology Affiliated Hospital from April 2019 to May 2021 and CAC score(CACS)＞0 were enrolled.According to the CACS value,the subjects were divided into mild calcification group(n=136)and severe calcification group(n=36),and the clinical characteristics of two groups were compared and analyzed.Multivariate Logistic regression model was used to screen the independent influencing factors of CAC severity,and a prediction model was constructed based on the Hcy detection value.The clinical diagnostic value was evaluated by the receiver operating characteristic(ROC)curve.Results There were significant differences in Hcy,white blood cell count,triglyceride and magnesium ion levels between two groups(P＜0.05).Multivariate Logistic regression analysis showed that Hcy,white blood cell count and magnesium ion level were independent risk factors for the progression of CAC.Furthermore,a regression model based on Hcy was constructed and ROC curve was fitted to evaluate its predictive efficacy.The results suggested that the predictive model had the best performance when the critical value of Hcy was set at 27.4μmol/L:the sensitivity was 55.6％,the specificity was 97.1％,and the area under the curve was 0.765.Conclusion Hcy serves as an independent risk factor for the severity of CAC and can effectively predict the progression of CAC with high accuracy.

Objective To evaluate the clinical outcomes of robot-assisted percutaneous vertebroplasty(PVP)versus manual PVP in treating osteoporotic vertebral compression fractures(OVCF),and explore the advantages of robotic assistance for clinical decision-making.Methods Patients who underwent single-level PVP for OVCF at the Department of Joint Surgery and Bone Tumor,Beijing Shijitan Hospital,Capital Medical University,between April 2021 and April 2025 were enrolled.The robot group(n=29)and manual PVP group(control,n=88)were followed-up for 1 month.Parameters compared included:total hospital stay,operative time,cement volume,cement leakage rate,nerve injury rate,intraoperative fluoroscopy number,first-attempt success rate of puncture,postoperative versus preoperative anterior vertebral height difference,Visual Analogue Scale(VAS)and Oswestry Disability Index(ODI)scores preoperatively,at 1-day and 1-month postoperatively.Results No statistically significant differences existed in baseline characteristics(gender,age,fracture-to-surgery interval,and fracture distribution)between groups(P>0.05).The number of intraoperative fluoroscopy times and the ODI index on the first day after surgery in the robot group were significantly lower than those in the control group(P<0.05),and the first-attempt success rate of puncture was significantly higher than that in the control group(P<0.05).There were no statistically significant differences in the other parameters between the two groups(P>0.05).Conclusion Both robot-assisted PVP and manual PVP have good clinical efficacy in the treatment of OVCF.Robot-assisted PVP can reduce the number of intraoperative fluoroscopy times and may have more advantages in improving the first-attempt success rate of puncture and early postoperative lumbar function.However,its reliability needs to be further verified through large-sample randomized controlled studies with multivariate analysis.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Objective To investigate whether miR-15b-5p can alleviate airway inflammation in asthma by negatively regulating ubiquitin specific peptidase 9X (USP9X) to down-regulate the expression of phosphatidylinositol 4, 5-diphosphate 3-kinase catalytic subunit α/AKT serine/threonine kinase 1 (PIK3CA/AKT1) pathway. Methods USP9X was predicted to be a direct target of miR-15b-5p by using an online database (miRWalk), and the luciferase reporter gene assay was performed to verify it. Co-immunoprecipitation (CO-IP) was used to verify the direct binding between USP9X and PIK3CA and the role of USP9X and its small molecule inhibitor WP1130 in the deubiquitination of PIK3CA. C57 mice were randomly divided into Control group, OVA group, OVA combined with NC group and miR-15b-5p agomir group, with 10 mice in each group. BEAS-2B cells were induced with interleukin 13 (IL-13) and treated with miR-15b-5p mimic. HE, Masson, PAS, immunohistochemistry, immunofluorescence staining, flow cytometry, Western blot and quantitative real-time PCR(qRT-PCR) were performed. Results It was found that the administration of miR-15b-5p agomir and mimic could reduce peribronchial inflammatory cells and improve airway inflammation, and miR-15b-5p could target negative regulation of USP9X. USP9X could directly bind to PIK3CA and regulate PIK3CA level in a proteasome-dependent manner, and USP9X could deubiquitinate K29-linked PIK3CA protein. Down-regulation of USP9X could increase PIK3CA ubiquitination level. WP1130, a small molecule inhibitor of USP9X, has the same effect as knockdown of USP9X, both of which could increase the ubiquitination level of PIK3CA and reduce the protein level of PIK3CA. Conclusion The miR-15b-5p/USP9X/PIK3CA/AKT1 signaling pathway may provide potential therapeutic targets for asthma.
Animals ; MicroRNAs/metabolism* ; Asthma/pathology* ; Class I Phosphatidylinositol 3-Kinases/genetics* ; Ubiquitin Thiolesterase/metabolism* ; Proto-Oncogene Proteins c-akt/genetics* ; Mice ; Signal Transduction ; Mice, Inbred C57BL ; Humans ; Inflammation/genetics* ; Cell Line ; Female ; Male

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Tongue squamous cell carcinoma (TSCC) is a prevalent malignancy that afflicts the head and neck area and presents a high incidence of metastasis and invasion. Accurate diagnosis and effective treatment are essential for enhancing the quality of life and the survival rates of TSCC patients. The current treatment modalities for TSCC frequently suffer from a lack of specificity and efficacy. Nanoparticles with diagnostic and photothermal therapeutic properties may offer a new approach for the targeted therapy of TSCC. However, inadequate accumulation of photosensitizers at the tumor site diminishes the efficacy of photothermal therapy (PTT). This study modified gold nanodots (AuNDs) with the TSCC-targeting peptide HN-1 to improve the selectivity and therapeutic effects of PTT. The Au-HN-1 nanosystem effectively targeted the TSCC cells and was rapidly delivered to the tumor tissues compared to the AuNDs. The enhanced accumulation of photosensitizing agents at tumor sites achieved significant PTT effects in a mouse model of TSCC. Moreover, owing to its stable long-term fluorescence and high X-ray attenuation coefficient, the Au-HN-1 nanosystem can be used for fluorescence and computed tomography imaging of TSCC, rendering it useful for early tumor detection and accurate delineation of surgical margins. In conclusion, Au-HN-1 represents a promising nanomedicine for imaging-based diagnosis and targeted PTT of TSCC.
Tongue Neoplasms/diagnostic imaging* ; Carcinoma, Squamous Cell/diagnostic imaging* ; Animals ; Gold/chemistry* ; Mice ; Photothermal Therapy/methods* ; Tomography, X-Ray Computed ; Photosensitizing Agents ; Metal Nanoparticles ; Humans ; Cell Line, Tumor

Objective To evaluate the clinical outcomes of robot-assisted percutaneous vertebroplasty(PVP)versus manual PVP in treating osteoporotic vertebral compression fractures(OVCF),and explore the advantages of robotic assistance for clinical decision-making.Methods Patients who underwent single-level PVP for OVCF at the Department of Joint Surgery and Bone Tumor,Beijing Shijitan Hospital,Capital Medical University,between April 2021 and April 2025 were enrolled.The robot group(n=29)and manual PVP group(control,n=88)were followed-up for 1 month.Parameters compared included:total hospital stay,operative time,cement volume,cement leakage rate,nerve injury rate,intraoperative fluoroscopy number,first-attempt success rate of puncture,postoperative versus preoperative anterior vertebral height difference,Visual Analogue Scale(VAS)and Oswestry Disability Index(ODI)scores preoperatively,at 1-day and 1-month postoperatively.Results No statistically significant differences existed in baseline characteristics(gender,age,fracture-to-surgery interval,and fracture distribution)between groups(P>0.05).The number of intraoperative fluoroscopy times and the ODI index on the first day after surgery in the robot group were significantly lower than those in the control group(P<0.05),and the first-attempt success rate of puncture was significantly higher than that in the control group(P<0.05).There were no statistically significant differences in the other parameters between the two groups(P>0.05).Conclusion Both robot-assisted PVP and manual PVP have good clinical efficacy in the treatment of OVCF.Robot-assisted PVP can reduce the number of intraoperative fluoroscopy times and may have more advantages in improving the first-attempt success rate of puncture and early postoperative lumbar function.However,its reliability needs to be further verified through large-sample randomized controlled studies with multivariate analysis.