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.

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.

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

Objective To study the role of protective antigen(PA)and N-terminal segment of lethal factor (LFn)in the entrance of EGFP(enhanced green fluorescent protein)into HeLa cells. Methods The DNA fragments encoding LFn and EGFP were amplified,respectively,and cloned into the plasmid pET-21 a(+)one after another to construct a recombinant plasmid pET-LFn-EGFP. The plasmid was txansformed into BL21 cells to express LFn-EGFP protein under the induction of IPTG. The protein was purified by Ni chelating chromatography. After incubation with LFn-EGFP in the presence of PA or not, the HeLa cells were analyzed by flow cytometry or laser confocal microscopy. Results The fusion protein LFn-EGFP was purified by over 90% homogeneity and retained the ability of LF to bind with PA when incubated with J774A.1 macrophage cells,and could get into HeLa cells. Conclusion The LFn-EGFP could enter the HeLa cells in a PA independent pathway. But PA could help more LFn-EGFP molecules enter into HeLa cells.

Objective To explore the special technique and the brain protection method of cardiopulmonary bypass(CPB) in large artery operation involving in aortic arch. Methods The procedures of cardiopulmonary bypass and the clinical outcome of 52 patients, who received large artery operation involving in aortic arch, were analysed retrospectively. Results The conventional hypothermal cardiopulmonary bypass was performed as basic method in all patients, deep hypothermal circulatory arrest were used in 13 patients, deep hypothermal circulatory arrest plus retrograde cerebral perfusion in 12 cases, selective antegrade cerebral perfusion in 7 cases, and separate perfusion of upper and low body in 20 cases. The total mortality was 17 3%(9/52), and there were 3 patients with the various severitits of cerebral complications. The mean cardiopulmonary bypass time was (180 6?51 8)min and the mean aortic block time was(62 4?61 9)min. Conclusion During the large artery operations involving in aortic arch, in order to prolong the period of deep hypothermal circulatory arrest, improve the effects of brain and spinal protection and minimize operative complications, different perfusion techniques should be employed according to different artery lesions and operative approaches.