The carbon ion proton therapy system,as one of the most advanced methods for treating solid tumors,has been unanimously recognized for its therapeutic effect.Its unique deep dose distribution and high relatively biological effects,which are outstanding advantages that conventional radiotherapy hardly matches,can provide important technical support for effectively increasing patients'5-year survival rate.Its industrial application and promotion are in line with the policy orientation of national scientific and technological innovation,and strategic emerging industries.This article established a preliminary framework for the standard system of operational services of carbon ion proton therapy system through analyzed the products'operation management,service requirements,and quality requirements in the field of operational services of carbon ion proton therapy system.It provided development direction for the formulation and revision of the standards in the field of operational services of carbon ion proton therapy system,and it contributed to promote products'popularization and industrial development.

Objective:To construct a frailty risk prediction model for elderly patients with CHD based on machine learning, to address the limitations of existing tools and provide evidence-based support for clinical practice.Methods:A retrospective study was conducted on elderly CHD patients hospitalized at the Heart Center of the First Affiliated Hospital of Henan University of Chinese Medicine from September 2023 to March 2024. Meta-analysis and expert meetings were used to identify the risk factors for frailty in elderly CHD patients. Three machine learning algorithms, Logistic Regression, Random Forest, and Support Vector Machine, were used to construct predictive models using R 4.3.1 software. The predictive performance of the models was evaluated using sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC).Results:A total of 490 elderly CHD patients were included, with 267 males and 223 females, and an age of (71.02 ± 7.73) years. Among them, 160 patients (32.7%) developed frailty. Of the constructed models, the Random Forest model demonstrated the best predictive performance, with an accuracy of 0.703, recall of 0.629, and F1 score of 0.741, while the AUC was 0.811 (95% CI 0.762-0.850). Conclusions:The Random Forest model exhibited good predictive performance in assessing frailty risk in elderly CHD patients, with high accuracy and reliability. Future external validation studies can further assess its applicability and stability in different populations.

The carbon ion proton therapy system,as one of the most advanced methods for treating solid tumors,has been unanimously recognized for its therapeutic effect.Its unique deep dose distribution and high relatively biological effects,which are outstanding advantages that conventional radiotherapy hardly matches,can provide important technical support for effectively increasing patients'5-year survival rate.Its industrial application and promotion are in line with the policy orientation of national scientific and technological innovation,and strategic emerging industries.This article established a preliminary framework for the standard system of operational services of carbon ion proton therapy system through analyzed the products'operation management,service requirements,and quality requirements in the field of operational services of carbon ion proton therapy system.It provided development direction for the formulation and revision of the standards in the field of operational services of carbon ion proton therapy system,and it contributed to promote products'popularization and industrial development.

Objective:To construct a frailty risk prediction model for elderly patients with CHD based on machine learning, to address the limitations of existing tools and provide evidence-based support for clinical practice.Methods:A retrospective study was conducted on elderly CHD patients hospitalized at the Heart Center of the First Affiliated Hospital of Henan University of Chinese Medicine from September 2023 to March 2024. Meta-analysis and expert meetings were used to identify the risk factors for frailty in elderly CHD patients. Three machine learning algorithms, Logistic Regression, Random Forest, and Support Vector Machine, were used to construct predictive models using R 4.3.1 software. The predictive performance of the models was evaluated using sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC).Results:A total of 490 elderly CHD patients were included, with 267 males and 223 females, and an age of (71.02 ± 7.73) years. Among them, 160 patients (32.7%) developed frailty. Of the constructed models, the Random Forest model demonstrated the best predictive performance, with an accuracy of 0.703, recall of 0.629, and F1 score of 0.741, while the AUC was 0.811 (95% CI 0.762-0.850). Conclusions:The Random Forest model exhibited good predictive performance in assessing frailty risk in elderly CHD patients, with high accuracy and reliability. Future external validation studies can further assess its applicability and stability in different populations.

Objectives:To investigate the efficacy and safety of anlotinib combined with niraparib in treating patients with platinum-resistant ovarian cancer.Methods:Thirty-five patients with pathological confirmed platinum-resistant ovarian cancer who experienced progression after receiving at least two lines of standard treatment were eligible. All of them were treated with anlotinib combined with niraparib between September 2019 and October 2021. The primary endpoint was progression-free survival (PFS). The second endpoints included overall survival, objective response rate (ORR), disease control rate (DCR) and safety. Survival analysis was performed using the Kaplan-Meier method and Log-rank test, and influence factor analysis was performed using Cox proportional risk regression models.Results:The best overall response showed that partial response was observed in 14 patients, stable disease was noted within 13 patients, and progressive disease was found in 8 patients. Therefore, the ORR and DCR of these 35 patients were 40.0% (95% CI:22.9%-57.1%) and 77.1% (95% CI:62.9%-91.4%), respectively. The median follow-up duration was 18.9 months (6.9-32.2). The median PFS was 6.5 months (95% CI:5.35-7.66). Multivariate Cox regression analysis for PFS indicated that age, Eastern Cooperative Oncology Group performance status (ECOG PS) score, International Federation of Gynecology and Obstetrics (FIGO) stage, and BRCA mutation status were independent factors influencing PFS ( P＜0.05). Additionally, the PFS in patients with BRCA mutation who have never received PARP inhibitor treatment was significantly longer than that in patients without BRCA mutation who have been exposed to prior PARPi treatment (15.0 vs 6.0 month, P=0.029). The most common treatment-related adverse reactions were fatigue (85.7%), hematologic toxic (85.7%) and hypertension (74.3%). There were no treatment-related deaths. Conclusion:Anlotinib combined with niraparib shows a promising efficacy and tolerable safety in platinum-resistant ROC patients.

Objectives:To investigate the efficacy and safety of anlotinib combined with niraparib in treating patients with platinum-resistant ovarian cancer.Methods:Thirty-five patients with pathological confirmed platinum-resistant ovarian cancer who experienced progression after receiving at least two lines of standard treatment were eligible. All of them were treated with anlotinib combined with niraparib between September 2019 and October 2021. The primary endpoint was progression-free survival (PFS). The second endpoints included overall survival, objective response rate (ORR), disease control rate (DCR) and safety. Survival analysis was performed using the Kaplan-Meier method and Log-rank test, and influence factor analysis was performed using Cox proportional risk regression models.Results:The best overall response showed that partial response was observed in 14 patients, stable disease was noted within 13 patients, and progressive disease was found in 8 patients. Therefore, the ORR and DCR of these 35 patients were 40.0% (95% CI:22.9%-57.1%) and 77.1% (95% CI:62.9%-91.4%), respectively. The median follow-up duration was 18.9 months (6.9-32.2). The median PFS was 6.5 months (95% CI:5.35-7.66). Multivariate Cox regression analysis for PFS indicated that age, Eastern Cooperative Oncology Group performance status (ECOG PS) score, International Federation of Gynecology and Obstetrics (FIGO) stage, and BRCA mutation status were independent factors influencing PFS ( P＜0.05). Additionally, the PFS in patients with BRCA mutation who have never received PARP inhibitor treatment was significantly longer than that in patients without BRCA mutation who have been exposed to prior PARPi treatment (15.0 vs 6.0 month, P=0.029). The most common treatment-related adverse reactions were fatigue (85.7%), hematologic toxic (85.7%) and hypertension (74.3%). There were no treatment-related deaths. Conclusion:Anlotinib combined with niraparib shows a promising efficacy and tolerable safety in platinum-resistant ROC patients.

Purpose/Significance To propose data governance and fusion technologies for different business application scenarios for the fusion of multi-source and multi-dimensional big data with complex sources and diverse standards.Method/Process Taking the practice of multi-source and multi-dimensional big data fusion in responding to major public health emergencies as an example,the pa-per focuses on the challenges faced by multi-source and multi-dimensional big data fusion,the design of the application architecture,technology integration,the implementation path,the application scenarios,etc.,and analyzes the application effect and the deficiencies that exist.Result/Conclusion Through the design of intelligent multi-source and multi-dimensional big data fusion technology,real-time monitoring,reading,governance,and interactive correlation of high-frequency updates at 100 billion levels are realized,and intel-ligent paths are explored for effectively responding to public emergencies.

Objective To evaluate the application of multi-parameter three-dimension arterial spin labeling (3D-ASL) in observing the brain perfusion of patients with transient ischemic attack (TIA). Methods A total of 42 TIA patients, admitted to our hospital from July 2014 to March 2017, were included in this study. All subjects underwent conventional MRI, diffusion-weighted imaging (DWI), magnetic resonance angiography (MRA) and 3D-ASL scanning. Abnormal signals, and cerebral arterial stenosis or occlusion were observed under MRI, DWI and MRA; cerebral blood flow (CBF) map was drew after analyzing the 3D-ASL imaging, and abnormal reperfusion of ASL-CBF was qualitatively and quantitatively analyzed. The detection rate of abnormal reperfusion in TIA patients by 3D-ASL (PLD=1.5 s, PLD=2.5 s) and MRA were compared. Results Forty-two TIA patients showed no positive findings on conventional MRI and DWI maps, of which 18 patients showed different degrees of cerebral artery stenosis on MRA maps. Twenty-seven patients (PLD=1.5 s, 64.29％) and 21 (PLD=2.5 s, 50％) on ASL-CBF maps showed different sizes and degrees of abnormal hypoperfusion, and significant difference was found in detection rate of hypoperfusion by 3D-ASL (PLD=1.5 s and PLD=2.5 s, χ2=23.333, P=0.000). The detection rates of hypoperfusion by 3D-ASL (PLD=1.5 s and PLD=2.5 s) were 中华神经医学杂志2017年12月第16卷 第12期 Chin J Neuromed, December 2017, Vol.16, No.12 significantly higher than that by MRA (χ2=17.500, P=0.000; χ2=31.500, P=0.000). Conclusions The 3D-ASL can quantitatively analyze the degrees of perfusion of patients with TIA. 3D-ASL can comprehensively reflect the perfusion status in patients with TIA, and short PLD 3D-ASL is more sensitive than long PLD ASL in finding TIA, while long PLD 3D-ASL can reflect the perfusion status more truly.

Objective To use warm needling moxibustion plus Julisanjie Bolus for the treatment of hysteromyoma and explore a new way to treat hysteromyoma. Method A treatment group of 40 hysteromyoma patients received warm needling moxibustion plus Julisanjie Bolus; a conventional treatment group of 40 hysteromyoma patients, Julisanjie Bolus; a control group of 40 hysteromyoma patients, mifepristone. The therapeutic effects were compared between the treatment group and the conventional treatment or control group. Result The cure rate and the total efficacy rate were 12.5% and 97.5%, respectively, in the treatment group, 5.0% and 75.0%, respectively, in the conventional treatment group and 5.0% and 72.5%, respectively, in the control group. Conclusion The therapeutic effect was significantly better in the treatment group than in the conventional treatment and control groups (P<0.05). There were no obvious adverse reactions during the clinical trial of warm needling moxibustion plus Julisanjie Bolus for the treatment of hysteromyoma.

Acupuncture Points ; Acupuncture Therapy ; Adult ; Ankle ; Cognitive Therapy ; Female ; Humans ; Intestine, Large ; physiopathology ; Middle Aged ; Rectal Diseases ; physiopathology ; psychology ; therapy ; Treatment Outcome ; Wrist