Objective To observe the effect of ethanol extract and ethyl acetate extract of Capparis Spinosa on the thickness of dermis,synthesis of collagen type Ⅰ,type Ⅲ,and expression of transforming growth factor-β1 in mouse models of scleroderma.Methods Mouse models of scleroderma were established through local injection of bleomycin on the back once a day for 4 weeks.After confirmation of model establishment,72 mouse models were equally and randomly divided into three groups.Two groups received topical treatment with ethanol extract of Capparis Spinosa and ethyl acetate extract of Capparis Spinosa,respectively,no treatment was given to the rest of the control group.After 2-,4-,6-week treatment,8 mice were sacrificed and tissue samples were obtained from the back,and subiected to the measurement of dermal thickness by HE staining,as well as to the analysis of expression of collagen type Ⅰ,collagen type Ⅲ and transforming growth factor-β1 by immunohistochemical staining.Results On week 2,4,6,the thickness of dermis was 23.22,24.94,19.97 μm respectively in mice treated with ethanol extract of Capparis Spinosa,27.66.26.15,22.13 μm respectively in those treated with ethyl acetate extract of Capparis Spinosa.Compared with the mouse models without treatment,the thickness of dermis significantly decreased(F=12.99,P＜0.01),the expression of collagen type Ⅰ(F=7.47,P＜0.01)and transforming growth factor-β1(F=11.76,P＜0.01)were also inhibited in those receiving treatment.However,the expression of collagen type Ⅲ was not affected obviously by the treatment.Conclusion The ethanol extract and ethyl acetate extract of Capparis Spinosa have the effect against skin fibrosis.

BACKGROUND:Conventional rehabilitation evaluation call not provide more objective data for analysis,so all innovative method to monitor rehabilitation of the cervical spine is introduced.OBJECTIVE:The monitoring rehabilitation system of the cervical spine develops independently under Visual Basic 6.0 environment.It can gather both video and photos at dynamic and static states.According to the suitable feature points of the video,the system could calculate characteristic parameters,such as moving angles,distances,speed,acceleration,and integral curves.Thus,the system could create patients'database.RESULTS:The system could calculate different kinds of patients'characteristic parameters through data recording.Through the objective comparison of characteristic parameters,the turning flexibility of head and controlling capability for head turning could be reflected.CONCLUSl0N:The design is an innovation in the monitoring rehabilitation systems of the cervical spine.It makes up the shortcomings of conventional rehabilitation evaluation and objectively reflects the rehabilitation status of patients.

Cardiac Catheterization ; Ductus Arteriosus, Patent ; therapy ; Heart Septal Defects, Atrial ; therapy ; Humans ; Printing, Three-Dimensional ; Vena Cava, Inferior

Objective To understand the current situation and existing problems in the training of healthcare-asso-ciated infection(HAI)management,and provide scientific basis for strengthening the management of HAI preven-tion and control system.Methods A questionnaire survey was adopted to investigate situation of training on HAI in 15 provincial-level HAI training agencies in China during the past 30 years,and basic condition of training on HAI management in recent 5 years.Results Among 15 provincial-level training agencies,66.67%(n=10)were respon-sible by HAI management quality control centers,80.00% have already conducted training in each city,53.33%carried out training for 10 to 20 times,33.34% performed training for ≤2 times per year.Of 33 728 trainees in 2011-2015,41.30% were 41-50 years old,61.82% were nursing staff,50.56% had bachelor degree,43.96%were with the intermediate professional title.Most trainers were HAI prevention and control experts in their respec-tive province,accounting for 68.07%,the curriculums were mainly designed on professional course,and only 26.78% were involved in management.Conclusion Professional structure of HAI management personnel is not reasonable,faculty is imbalance,knowledge update is lacking,and HAI training and education system need to be improved further.

Objective:To evaluate the kinetic metrics changes of FDG in key organs after chemo-immunotherapy in patients with locally advanced non-small cell lung cancer (NSCLC) identified by total-body PET/CT dynamic imaging, and explore its potential biological significance.Methods:From August 2020 to March 2021, 16 patients (13 males, 3 females; age: 43-67 years) with locally advanced NSCLC who underwent total-body 18F-FDG PET/CT dynamic imaging in Sun Yat-sen University Cancer Center were retrospectively analyzed. ROIs of key organs were drawn at baseline and after chemo-immunotherapy to obtain the time-activity curves (TACs). The kinetic metrics, including K1, k2, k3 and metabolic rate of FDG (MR FDG), were fitted by the two-tissue compartment model. Paired t test or Wilcoxon signed rank test was used to compare the differences of FDG kinetic parameters in each organ before and after treatment. Results:Compared with baseline, SUV max of colon (3.23±1.29 vs 4.81±2.73), MR FDG ((2.77±1.96) vs 3.56(1.07, 9.89) μmol·100 g -1·min -1) of lungs, SUV max (2.16±0.27 vs 2.33±0.41), k3 ((0.008±0.002) vs (0.012±0.004) min -1) and MR FDG ((2.65±0.81) vs (3.76±1.59) μmol·100 g -1·min -1) of spleen, and SUV max (2.59±0.45 vs 4.49±2.73), k2 ((0.76±0.37) vs (1.27±0.66) min -1), k3 ((0.032±0.007) vs (0.066±0.029) min -1) and MR FDG ((5.14±1.44) vs (8.39±2.67) μmol·100 g -1·min -1) of bone marrow were increased after chemo-immunotherapy with significant differences ( t values: from -5.40 to 3.47, z=-2.02, all P<0.05). There were no significant differences of SUV max, k values and MR FDG in other organs ( t values: from -2.00 to 2.35, z values: from -1.45 to -0.05, all P>0.05). Conclusions:After chemo-immunotherapy, the activation of immune system may be manifested as the increase of FDG kinetic rate constants in spleen and bone marrow. The lung and colon may be target organs for immune-related adverse effects.

Objective:To evaluate the value of chemoradiotherapy and surgery in cervical esophageal cancer (CEC).Methods:Data of 459 patients with CEC from 2004 to 2017 were collected and retrospectively analyzed from the surveillance, epidemiology, and end results (SEER) database of National Cancer Institute (US). All patients were divided into the chemoradiotherapy group ( n=379) and surgery group ( n=80) according to the treatment methods. Survival analysis was performed by Kaplan-Meier method and survival curve was drawn. Multivariate survival analysis was conducted by Cox proportional hazards regression model. The death rate of different causes between two groups was calculated by cumulative incidence function (CIF). The differences of death rate between two groups were evaluated by Fine-Gray competing risk model. By analyzing the clinical characteristics and survival of CEC patients, the overall survival (OS) was compared between the surgery and chemoradiotherapy groups. Results:The 2- and 5-year survival rates in the chemoradiotherapy group were 43.1% and 22.4%, while those of the surgical group were 46.8% and 26.0%, respectively. No significant difference was observed in the OS between the chemoradiotherapy and surgery groups ( P=0.750). Cox multivariate analysis showed that treatment (surgery group vs. chemoradiotherapy group) was not an independent prognostic factor for OS. Based on the results of competing risk analysis, the risk of esophageal cancer-specific death in the chemoradiotherapy group was higher than that in the surgery group, and the difference was statistically significant between two groups ( P<0.001). The risk of other cause-specific death in the chemoradiotherapy group was lower than that in the surgery group ( P<0.001). The proportion of patients who died of oral, oropharyngeal, hypopharyngeal and laryngeal diseases in the surgery group was significantly higher than that in the chemoradiotherapy group(all P<0.001). Conclusions:No significant difference is observed in the OS of CEC patients treated with chemoradiotherapy or surgery. In the surgery group, the risk of esophageal cancer-specific death is lower, whereas the risk of other cause-specific death is higher compared with those in the chemoradiotherapy group.

Objective:To explore the effect of pretreatment body mass index (BMI) on the prognosis of patients with unresectable locally advanced non-small cell lung cancer (NSCLC) after chemoradiotherapy.Methods:The clinical data of 711 patients with locally advanced NSCLC treated with radiotherapy, sequential chemoradiotherapy or concurrent chemoradiotherapy from January 2013 to December 2017 in Cancer Hospital of Chinese Academy of Medical Science and Peking Union Medical College were retrospectively analyzed. Radiotherapy was performed with intensity-modulated radiotherapy (IMRT) or volumetric-modulated arc therapy (VMAT), and the chemotherapy regimens were paclitaxel+carboplatin, pemetrexed+cisplatin or etoposide+cisplatin. The effects of pretreatment BMI and other clinical factors on overall survival (OS) of patients were analyzed. Survival analysis was performed by using Kaplan-Meier method; univariate and multivariate analyses were performed by using Cox proportional hazards model.Results:According to the World Health Organization (WHO) recommended BMI grouping method for Asian, the median OS time of low BMI group (<18.5 kg/m 2, 23 cases), normal BMI group (18.5-23.9 kg/m 2, 293 cases) and high BMI group (≥24.0 kg/m 2, 395 cases) was 17 months (95% CI 11-29 months), 29 months (95% CI 22-36 months) and 30 months (95% CI 27-34 months), respectively. OS in the low BMI group was poorer than that in the normal BMI group and high BMI group ( χ2 = 11.20, P = 0.004). Maximally selected rank statistics was used to determine the optimal cut-off value of BMI for prediction of survival as 21.31 kg/m 2, according to which patients were divided into low BMI group (BMI<21.31 kg/m 2, 130 cases) and high BMI group (BMI≥21.31 kg/m 2, 581 cases), the median OS time of the two groups was 20 months (95% CI 17-27 months) and 32 months (95% CI 28-35 months), respectively. OS in the low BMI group was poorer than that in the high BMI group ( χ2 = 12.30, P < 0.001). Multivariate analysis showed that age ≥ 65 years old, male, Karnofsky score < 80 points, low BMI, smoking, histological type of squamous cell carcinoma and radiotherapy alone were independent risk factors for OS (all P < 0.05). Conclusions:For patients with unresectable locally advanced NSCLC who received chemoradiotherapy, those with low pretreatment BMI have poor prognosis.

BACKGROUND: The detection of pulmonary nodules is a key step to achieving the early diagnosis and therapy of lung cancer. Deep learning based Artificial intelligence (AI) presents as the state of the art in the area of nodule detection, however, a validation with clinical data is necessary for further application. Therefore, the aim of this study is to evaluate the performance of AI in the detection of malignant and non-calcified nodules in chest CT. METHODS: Two hundred chest computed tomography (CT) data were randomly selected from a self-built nodule database from Tianjin Medical University General Hospital. Both the pathology confirmed lung cancers and the nodules in the process of follow-up were included. All CTs were processed by AI and the results were compared with that of radiologists retrieved from the original medical reports. The ground truths were further determined by two experienced radiologists. The size and characteristics of the nodules were evaluated as well. The sensitivity and false positive rate were used to evaluate the effectiveness of AI and radiologists in detecting nodules. The McNemar test was used to determine whether there was a significant difference. RESULTS: A total of 889 non-calcified nodules were determined by experts on chest CT, including 133 lung cancers. Of them, 442 nodules were less than 5 mm. The cancer detection rates of AI and radiologists are 100%. The sensitivity of AI on nodule detection was significantly higher than that of radiologists (99.1% vs 43%, P<0.001). The false-positive rate of AI was 4.9 per CT and decreased to 1.5 when nodules less than 5 mm were excluded. CONCLUSIONS AI achieves the detection of all malignancies and improve the sensitivity of pulmonary nodules detection beyond radiologists, with a low false positive rate after excluding small nodules.
Artificial Intelligence ; Deep Learning ; Humans ; Lung Neoplasms ; diagnosis ; diagnostic imaging ; Multiple Pulmonary Nodules ; diagnosis ; diagnostic imaging ; Tomography, X-Ray Computed

BACKGROUND: Subsolid pulmonary nodules are common computed tomography (CT) findings of primary lung adenocarcinoma. It is of clinical value to determine the clinical treatment strategies based on CT features. The aim of this study is to find the valuable CT characteristics on differential diagnosis and the degree of invasion prediction by a retrospectively analysis of three groups subsolid nodules, including benign, and invasive adenocarcinoma. METHODS: The CT findings of 106 cases of resected sub-solid nodules were retrospectively analyzed. The nodules were firstly divided into benign and malignant groups and the malignant group was further divided into non/micro-invasive group (atypical adenomatous hyperplasia/adenocarcinoma in situ/minimally invasive adenocarcinoma) and invasive adenocarcinoma group. The nodule size, proportion of solid components, tumor-lung interface, shape, margin, pleural traction, air bronchus sign, vascular abnormalities inside the nodule were evaluated. The univariate analysis (χ2 test, non-parametric test Mann-Whitney U test) was performed to screen statistically significant variables and then enrolled in further multivariate Logistic regression analysis. RESULTS: Multivariate logistic regression analysis showed that a clear tumor-lung interface, air bronchus sign, and pulmonary vascular abnormalities were important indicators of malignant nodules with hazard ratios of 38.1 (95%CI: 5.0-287.7; P<0.01), 7.9 (95%CI: 1.3-49.3; P=0.03), 7.2 (95%CI: 1.4-37.0; P=0.02), respectively. The proportion of solid components was the only significant indicator for identifying invasive adenocarcinoma from AAH/AIS/MIA , with a risk ratio of 1.04 (95%CI: 1.01-1.06, P=0.01). CONCLUSIONS SSNs with clear tumor-lung interface, air bronchus sign, and pulmonary vascular abnormality inside nodule are more likely to be malignant. A higher percentage of solid components indicates a higher likelihood to be an invasive lesion in malignant SPNs.
Adenocarcinoma ; diagnostic imaging ; pathology ; Adenocarcinoma of Lung ; Adult ; Aged ; Diagnosis, Differential ; Female ; Humans ; Lung Neoplasms ; diagnostic imaging ; pathology ; Male ; Middle Aged ; Multivariate Analysis ; Neoplasm Invasiveness ; Retrospective Studies ; Tomography, X-Ray Computed