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.

Roxadustat is the world's first small molecule hypoxia-inducible factor prolyl hydroxylase inhibitor. Its adverse effect of causing hypothyroidism with low thyroid-stimulating hormone (TSH) is relatively rare and manifests subtly in elderly patients with multiple coexisting diseases. This article reports a case of an elderly patient with renal anemia who developed reversible low-TSH hypothyroidism after taking roxadustat for 12 days, with a significant decrease in thyroid hormone levels. After discontinuing roxadustat for 15 days, the thyroid hormone levels gradually returned to normal. Due to the worsening of renal anemia, the patient took roxadustat again, and 9 days later, the thyroid function-related indicators decreased upon re-examination, leading to the initiation of levothyroxine replacement therapy. In conjunction with relevant literature, this article analyzes the adverse reactions that occur during the oral administration of roxadustat in elderly patients with chronic kidney disease, aiming to provide reference for drug treatment of such 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.

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.

Psoriasis is an incurable chronic inflammatory disease that requires new interventions. Here, we found that fibroblasts exacerbate psoriasis progression by promoting macrophage recruitment via CCL2 secretion by single-cell multi-omics analysis. The natural small molecule celastrol was screened to interfere with the secretion of CCL2 by fibroblasts and improve the psoriasis-like symptoms in both murine and cynomolgus monkey models. Mechanistically, celastrol directly bound to the low-density lipoprotein receptor-related protein 1 (LRP1) β-chain and abolished its binding to the transcription factor c-Jun in the nucleus, which in turn inhibited CCL2 production by skin fibroblasts, blocked fibroblast-macrophage crosstalk, and ameliorated psoriasis progression. Notably, fibroblast-specific LRP1 knockout mice exhibited a significant reduction in psoriasis like inflammation. Taken together, from clinical samples and combined with various mouse models, we revealed the pathogenesis of psoriasis from the perspective of fibroblast-macrophage crosstalk, and provided a foundation for LRP1 as a novel potential target for psoriasis treatment.

OBJECTIVES: To analyze the differentially expressed exosomal miRNAs in patients with chronic heart failure (CHF) complicated by hyperuricemia (HUA) and explore their potential as novel diagnostic molecular markers and their target genes. METHODS: This study was conducted among 30 CHF patients with HUA (observation group) and 30 healthy volunteers (control group) enrolled between September, 2020 and September, 2023. Peripheral blood samples were collected from 6 CHF patients with HUA for analyzing exosomal miRNAs by high-throughput sequencing, and the results were validated in the remaining 24 patients using qRT-PCR. GO and KEGG enrichment analyses were performed to predict the the target genes of the identified differential miRNAs. We also validated the differentially expressed miRNAs by animal experiment. RESULTS: A total of 42 differentially expressed exosomal miRNAs were detected in observation group by high-throughput sequencing; among them, miR-27a-5p was significantly upregulated (P=0.000179), and miR-139-3p was significantly downregulated (P=0.000058). In the 24 patients with both CHF and PUA, qRT-PCR validated significant upregulation of miR-27a-5p (P=0.004) and downregulation of miR-139-3p (P=0.005) in serum exosomes. When combined, miR-27a-5p and miR-139-3p had a maximum area under the curve (AUC) of 0.899 (95% CI: 0812-0.987) for predicting CHF complicated by HUA. GO and KEGG enrichment analyses suggested that the differential expressions of miR-27a-5p and miR-139-3p was associated with the activation of the AMPK-mTOR signaling pathway to activate the autophagic response. We obtained the same conclusion from animal experiment. CONCLUSIONS Upregulated exosomal miR-27a-5p combined with downregulated exosomal miR-139-3p expression can serve as a novel molecular marker for diagnosis of CHF complicated by HUA, and their differential expression may promote autophagy in cardiomyocytes by activating the AMPK-mTOR signaling pathway.
Humans ; Hyperuricemia/diagnosis* ; Heart Failure/genetics* ; MicroRNAs/metabolism* ; Exosomes/metabolism* ; Chronic Disease ; Male ; Female ; Middle Aged ; Animals

OBJECTIVE: This study aimed to explore the interplay between the life-course body mass index (BMI) trajectories and insulin resistance (IR) on incident diabetes. METHODS: This longitudinal cohort included 2,336 participants who had BMI repeatedly measured 3-8 times between 1989 and 2009, as well as glucose and insulin measured in 2009. BMI trajectories were identified using a latent class growth mixed model. The interplay between BMI trajectories and IR on diabetes was explored using the four-way effect decomposition method. Logistic regression and mediation models were used to estimate the interaction and mediation effects, respectively. RESULTS: Three distinct BMI trajectory groups were identified: low-stable ( n = 1,625), medium-increasing ( n = 613), and high-increasing ( n = 98). Both interaction and mediation effects of BMI trajectories and IR on incident diabetes were significant ( P < 0.05). The proportion of incident diabetes was higher in the IR-obesity than in the insulin-sensitivity (IS) obesity group (18.9% vs. 5.8%, P < 0.001). After adjusting for covariates, the odds ratios (95% confidence intervals) of the IR, IS-obesity, and IR-obesity groups vs. the normal group were 3.22 (2.05, 5.16), 2.05 (1.00, 3.97), and 7.98 (5.19, 12.62), respectively. IR mediated 10.7% of the total effect of BMI trajectories on incident diabetes ( P < 0.001). CONCLUSION We found strong interactions and weak mediation effects of IR on the relationship between life-course BMI trajectories and incident diabetes. IS-obesity is associated with a lower risk of incident diabetes than IR-obesity.
Humans ; Insulin Resistance ; Body Mass Index ; Male ; Female ; Middle Aged ; China/epidemiology* ; Adult ; Longitudinal Studies ; Incidence ; Diabetes Mellitus/epidemiology* ; Aged ; Obesity/epidemiology* ; Diabetes Mellitus, Type 2/epidemiology* ; East Asian People

Objective To summarize the medication law of TCM in the treatment of chronic bronchitis;To provide reference for clinical medication.Methods Medical records of patients with chronic bronchitis who were hospitalized in the Respiratory Department of the First Affiliated Hospital of Henan University of Chinese Medicine from January 1,2016 to December 31,2021 were extracted based on HIS electronic medical record data.After screening,the TCM prescriptions used by patients with chronic bronchitis were input into Excel 2019 to establish a database.Based on the software Lantern 5.0,the latent structure model was learned,hidden variables and explicit variables were obtained,and the model was interpreted.SPSS Modeler 18.0 was used to establish model points with Apriori algorithm for Chinese materia medica with a frequency greater than 6%,to obtain the association rules between drugs,and to analyze the medication law of TCM in treating chronic bronchitis.Results A total of 3 410 cases were included,involving 423 kinds of Chinese materia medica,with a cumulative frequency of 82 766 times.Among them,109 kinds of Chinese materia medica with a frequency of>6 % had a cumulative frequency of 69 845 times.The top five commonly used medicines were Fritillariae Cirrhosae Bulbus,Poria,Atractyodis Macrocephalae Rhizoma,Asteris Radix et Rhizoma,Citri Reticulatae Pericarpium,mainly with medicines of reducing cough and phlegm,antiasthmatic medicine,tonifying deficiency,clearing heat,relieving superficies,promoting blood circulation and removing blood stasis.The medicinal properties were warming,cold and mild,and the main tastes were bitter,sweet and pungent,and the meridians were mainly lung,spleen,liver and stomach meridians.Through analysis of latent structure,49 hidden variables and 149 hidden classes were obtained.Combined with professional knowledge,10 comprehensive clustering models and 21 core formulas were deduced,such as Sangbaipi Decoction,Xuefu Zhuyu Decoction,Xiaoqinglong Decoction,Erchen Decoction,Shashen Maidong Decoction,Liuwei Dihuang Pills,Yinqiao Powder,Zhisou Powder,Yupingfeng Powder,Xuefu Zhuyu Decoction combined with Daotan Decoction,etc.It was concluded that the chronic bronchitis syndrome included phlegm-heat stagnation lung syndrome,qi stagnation blood stasis syndrome,cold fluid attacking lung syndrome,phlegm-dampness accumulation lung syndrome,lung qi and yin deficiency syndrome,kidney yin deficiency syndrome,wind heat attacking lung syndrome,wind cold attacking lung syndrome,lung qi and spleen deficiency syndrome,phlegm stasis interjunction syndrome.A total of 41 strong association rules were screened in the analysis of association rules,including 5 strong association rules for two and 36 strong association rules for three.The high confidence rules were Saposheikovize Radix + Angelicae Sinensis Radix →Atractyodis Macrocephalae Rhizoma,Saposheikovize Radix + Codonopsis Radix → Atractyodis Macrocephalae Rhizoma,Codonopsis Radix + Citri Reticulatae Pericarpium → Atractyodis Macrocephalae Rhizoma;the higher degree of improvement were Bupleuri Radix + Mori Cortex → Scutellariae Radix,Perillae Fructus + Belamcandae Rhizoma → Fritillariae Cirrhosae Bulbus,Armeniacae Semen Amarum + Pinelliae Rhizoma → Citri Reticulatae Pericarpium,etc.Conclusion In the treatment of chronic bronchitis,TCM is mainly used to reduce phlegm,relieve cough and asthma,and the method of promoting blood circulation and removing blood stasis is commonly used to help eliminate phlegm.In addition,TCM pays attention to the application of methods such as tonifying lung and securing the exterior,invigorating spleen and benefiting qi.