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.

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:Melanoma is highly malignant and heterogeneous.It is essential to develop a specific prognostic model for improving the patients'survival and treatment strategies.Recent studies have shown that ferroptosis results from the overproduction of lipid peroxidation and is an iron-dependent form of programmed cell death.Despite this,ferroptosis-related genes(FRGs)and their clinical significances remain unknown in malignant melanoma.This study aims to assess the role of FRGs in melanoma,with the goal of developing a novel prognostic model that provides new insights into personalized treatment and improvement of therapeutic outcomes for melanoma. Methods:We systematically characterized the genetic alterations and mRNA expression of 73 FRGs in The Cancer Genome Atlas(TCGA)-skin cutaneous melanoma(SKCM)dataset in this study.The results were validated with real-time RT-PCR and Western blotting.Subsequently,a multi-gene feature model was constructed using the TCGA-SKCM cohort.Melanoma patients were classified into a high-risk group and a low-risk group based on the feature model.As a final step,correlations between ferroptosis-related signatures and immune features,immunotherapy efficacy,or drug response were analyzed. Results:By analyzing melanoma samples from TCGA-SKCM dataset,FRGs exhibited a high frequency of genetic mutations and copy number variations(CNVs),significantly impacting gene expression.Additionally,compared with normal skin tissue,30 genes with significantly differential expression were identified in melanoma tissues.A prognostic model related to FRGs,constructed using the LASSO Cox regression method,identified 13 FRGs associated with overall survival prognosis in patients and was validated with external datasets.Finally,functional enrichment and immune response analysis further indicated significant differences in immune cell infiltration,mutation burden,and hypoxia status between the high-risk group and the low-risk group,and the model was effective in predicting responses to immunotherapy and drug sensitivity. Conclusion:This study develops a strong ferroptosis-related prognostic signature model which could put forward new insights into target therapy and immunotherapy for patients with melanoma.

Objective To explore the effects of positive psychological intervention based on PERMA model of wellbeing on stigma,adaptation to ostomy and quality of life in patients with permanent enterostomy.Methods A total of 83 patients with permanent enterostomy were recruited from October 2022 to September 2023 in a tertiary hospital in Liaoning Province.They were randomly divided into an experimental group and a control group.While the control group received routine nursing,the experimental group received nursing intervention based on PERMA.The intervention lasted 8 weeks,and data were collected before and after the intervention.The scores of the Social Impact Scale(SIS),Ostomy Adjustment Inventory-20(OAI-20)and Stoma Quality of Life(Stoma-QOL)in the 2 groups were compared.Results Experimental group and control group were 40 cases each completed the study.After the intervention,the SIS score of the experimental group was(44.70±9.10),which was significantly lower than(62.15±12.43)of the control group,and the difference between 2 groups was statistically significant(t=-7.163,P＜0.001).The OAI-20 score of the experimental group was(52.28±5.80),which was significantly higher than(41.53±9.00)of the control group,and the difference between the 2 groups was statistically significant(t=6.349,P＜0.001).The Stoma-QOL score of the experimental group was(54.08±8.29),which was significantly higher than(42.95±9.19)of the control group,and the difference between the 2 groups was statistically significant(t=5.688,P＜0.001).Conclusion Nursing interventions based on PERMA are beneficial in reducing stigma of patients with permanent enterostomy,improving their ostomy adjustment and postoperative quality of life.

Dryness is an important concept in the theory of traditional Chinese medicine， which is closely related to the transformation of the body， etiology and pathogenesis. As one of the medicinal properties of Chinese materia medica， there are various types of Chinese materia medica with dryness. Atractylodis Rhizoma（AR） is a representative medicine with warm and dry properties， which has the function of drying dampness and strengthening the spleen. Due to its strong dryness， it can cause certain adverse reactions. In clinical practice， stir-fried AR with bran is often used as medicine. The dryness of AR is closely related to its efficacy， but the underlying mechanism of the relationship between dryness and efficacy is still unclear. At present， the research on dryness Chinese materia medica has been increasing year by year， but there are still problems such as insufficient systematic research， insufficient in-depth research and lack of research on the mechanism of dryness effect， which limit the breakthrough of the theory of processing for slowing down dryness， and hinder the precise application of dryness Chinese materia medica in clinical practice. Therefore， this article comprehensively reviewed the differences in dryness characterization indicators of different Chinese materia medica by searching domestic and foreign literature， focusing on the relevant research on dryness of AR. A systematic summary and induction were made from the characterization indicators， research techniques of dryness markers， the influence of processing on dryness of AR， and the application mining of dryness of AR. The results showed that the dryness characteristics of AR mainly included the upregulation of macroscopic indicators such as water intake， urine output and whole blood viscosity， as well as energy metabolism indicators， the downregulation of water metabolism indicators， and pathological changes such as submandibular gland acinar atrophy. Based on the changes of dryness and component content of AR after processing， it is determined that the main dryness components of AR may be volatile components such as β-eudesmol and atractylon. Due to its dryness， AR is mainly used to treat diseases such as spleen deficiency， rheumatism and edema. However， the current understanding of the correlation between dryness and efficacy of AR is still insufficient， and there are still many bottlenecks in understanding and explaining its dryness. In the future， systematic evaluation and characterization should be carried out to find the common mechanism of AR exerting dryness and efficacy， providing reference for the rational clinical use.

Objective:To analyze the clinical characteristics and genetic basis of a male patient with primary infertility caused by Acephalic spermatozoa syndrome.Methods:A patient who had presented at the Henan Provincial People′s Hospital on October 1, 2022 was selected as the study subject. Clinical data and results of laboratory exams and sperm electron microscopy were collected. The patient was subjected to whole exome sequencing (WES), and candidate variants were verified by Sanger sequencing and pathogenicity analysis.Results:WES revealed that the patient has harbored compound heterozygous variants of the PMFBP1 gene, namely c. 853del (p.Ala285Leufs*24) and c. 1276A>T (p.Lys426X), which were both unreported previously. Sanger sequencing suggested that the c. 853del (p.Ala285Leufs*24) variant has derived from his deceased mother, whilst the c. 1276A>T (p.Lys426X) variant has derived from his father. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), both variants were classified as pathogenic (PVS1+ PM2_Supporting+ PP4). Conclusion:The compound heterozygous variants of the PMFBP1 gene probably underlay the Acephalic spermatozoa syndrome in this patient. The discovery of the novel variants has also enriched the mutational spectrum of Acephalic spermatozoa syndrome.

During coronavirus disease 2019 epidemic, the treatment of severe trauma has been impacted. The Consensus on emergency surgery and infection prevention and control for severe trauma patients with 2019 novel corona virus pneumonia was published online on February 12, 2020, providing a strong guidance for the emergency treatment of severe trauma and the self-protection of medical staffs in the early stage of the epidemic. With the Joint Prevention and Control Mechanism of the State Council renaming "novel coronavirus pneumonia" to "novel coronavirus infection" and the infection being managed with measures against class B infectious diseases since January 8, 2023, the consensus published in 2020 is no longer applicable to the emergency treatment of severe trauma in the new stage of epidemic prevention and control. In this context, led by the Chinese Traumatology Association, Chinese Trauma Surgeon Association, Trauma Medicine Branch of Chinese International Exchange and Promotive Association for Medical and Health Care, and Editorial Board of Chinese Journal of Traumatology, the Chinese expert consensus on emergency surgery for severe trauma and infection prevention during coronavirus disease 2019 epidemic ( version 2023) is formulated to ensure the effectiveness and safety in the treatment of severe trauma in the new stage. Based on the policy of the Joint Prevention and Control Mechanism of the State Council and by using evidence-based medical evidence as well as Delphi expert consultation and voting, 16 recommendations are put forward from the four aspects of the related definitions, infection prevention, preoperative assessment and preparation, emergency operation and postoperative management, hoping to provide a reference for severe trauma care in the new stage of the epidemic prevention and control.