Objective To observe the value of machine learning(ML)models based on CT angiography(CTA)morphology combined with blood inflammation indicators for predicting rupture of intracranial aneurysms(IA).Methods Totally 286 IA patients were enrolled,including 143 cases in ruptured group and 143 case in unruptured group.Among them 200 cases(100 in ruptured subgroup and 100 in unruptured subgroup)were taken as training set,while 86 cases(43 in ruptured subgroup and 43 in unruptured subgroup)were taken as validation set.CTA morphological parameters and blood inflammation indicators were compared between subgroups in training set,and the impact factors of IA ruptured among univariate variables were screened using stepwise logistic regression analysis.Logistic regression(LR),classification and regression tree(CART)and backpropagation neural network(BPNN)models were constructed based on the above impact factors,respectively.Receiver operating characteristic curves were drawn,the area under the curves(AUC)were calculated to evaluate the efficacy of these models for predicting IA rupture.Results Neutrophil,neutrophil-lymphocyte ratio,interleukin-10,tumor necrosis factor-α,transforming growth factor-β,as well as tumor width,height and size ratio(SR)were all impact factors of IA rupture(all P＜0.05),and collinearity diagnosis suggested that no covariate relationship existed among these factors.LR,CART and BPNN models had good efficacy for predicting IA rupture in both training and validation sets with AUC of 0.878-0.993,and BPNN model had the best predictive efficacy(AUC of 0.993,0.976).Conclusion ML models based on CTA morphology combined with blood inflammation indicators could be used to predict IA rupture effectively,among which BPNN model had the best efficacy.

Objective To observe the value of machine learning(ML)models based on CT angiography(CTA)morphology combined with blood inflammation indicators for predicting rupture of intracranial aneurysms(IA).Methods Totally 286 IA patients were enrolled,including 143 cases in ruptured group and 143 case in unruptured group.Among them 200 cases(100 in ruptured subgroup and 100 in unruptured subgroup)were taken as training set,while 86 cases(43 in ruptured subgroup and 43 in unruptured subgroup)were taken as validation set.CTA morphological parameters and blood inflammation indicators were compared between subgroups in training set,and the impact factors of IA ruptured among univariate variables were screened using stepwise logistic regression analysis.Logistic regression(LR),classification and regression tree(CART)and backpropagation neural network(BPNN)models were constructed based on the above impact factors,respectively.Receiver operating characteristic curves were drawn,the area under the curves(AUC)were calculated to evaluate the efficacy of these models for predicting IA rupture.Results Neutrophil,neutrophil-lymphocyte ratio,interleukin-10,tumor necrosis factor-α,transforming growth factor-β,as well as tumor width,height and size ratio(SR)were all impact factors of IA rupture(all P＜0.05),and collinearity diagnosis suggested that no covariate relationship existed among these factors.LR,CART and BPNN models had good efficacy for predicting IA rupture in both training and validation sets with AUC of 0.878-0.993,and BPNN model had the best predictive efficacy(AUC of 0.993,0.976).Conclusion ML models based on CTA morphology combined with blood inflammation indicators could be used to predict IA rupture effectively,among which BPNN model had the best efficacy.

Objective To investigate the effects of prolonged low-dose neutron-γ radiation on peripheral blood lymphocytes of logging workers. Methods The health information of workers in a logging company was collected by on-site blood sample collection and questionnaire survey. Individual doses of γ and neutron radiation were recorded using LiF elements and CR-39, respectively. Lymphocyte count in peripheral blood was measured by blood cytometer. Cell cycle and cyclins were detected by flow cytometry. Results The annual dose of some logging workers exceeded 5 mSv. Lymphocyte counts showed a difference of 15% between the group exposed to the lowest annual dose of 0–1 mSv (mean: 2.45 × 10⁹/L) and the group exposed to the highest annual dose of 5–25 mSv (mean: 2.08 × 10⁹/L). In comparison to pre-shift workers, logging workers exhibited a G1-phase arrest in the lymphocyte cycle, along with increased expression of cyclins p21 and CDK2. Conclusion Prolonged exposure to low-dose neutron-γ radiation leads to reduced lymphocyte counts as well as changes in lymphocyte cycle and cyclin expression.

Objective To investigate the predictive value of artificial intelligence(AI)-assisted high-resolution computed tomo-graphy(HRCT)in degree of invasion of early lung adenocarcinoma with subsolid nodules(SSN).Methods Ninety patients(a total of 90 SSN)with pulmonary SSN on AI-assisted HRCT scans were selected as the study subjects.According to the degree of invasion in pathology,the cases were divided into invasive adenocarcinoma(IAC)group(48 cases)and non-invasive adenocarcinoma(non-IAC)group(42 cases).The differences in general information,pulmonary SSN morphological characteristics,and related parameters were compared between the two groups.The influencing factors were analyzed using a multiple logistic regression model,and a nomo-gram prediction model was constructed.The diagnostic efficacy of the model was evaluated using receiver operating characteristic(ROC)curves,calibration curves,and clinical decision curves.Results Between the two groups,there were statistically significant differences in age,nodular nature,shape,tumor-lung interface,vacuole sign,burr sign,air-bronchial sign,vascular bunching sign and pleural indentation sign.Compared with the non-IAC group,the CT maximum value,energy,variance of CT value,CT average value,maximum surface area,mean long and short diameter,3D long diameter,surface area,volume,mass and entropy of the IAC group significantly increased,while the CT minimum value,compactness and sphericity of the IAC group significantly decreased.The results of multiple logistic regression model showed that burr sign,vascular bunching sign,tumor-lung interface,mass,pleural indentation sign,and CT average value were independent risk factors affecting the development of SSN into early IAC.Finally,a nomogram pre-diction model was constructed based on risk factors,and the results of ROC curves,calibration curves and clinical decision curves showed that the predictive model had good diagnostic efficacy.Conclusion HRCT imaging features assisted by AI have a high pre-dictive value for the degree of invasion in early lung adenocarcinoma with SSN,and focusing on the burr sign,vascular bunching sign,tumor-lung interface,mass,pleural indentation sign,and CT average value can improve clinical treatment and prognosis for patients.

Objective:Sepsis is a life-threatening organ dysfunction caused by the host's imbalanced response to infection.Due to lack of effective treatments,it has always been the difficulty and focus of clinical treatment of sepsis.Studies have shown that pro-brain-derived neurotrophic factor(proBDNF)binds to the high-affinity total neurotrophic factor p75 neurotrophin receptor(p75NTR),which activates downstream signaling cascades and disrupts immunological inflammation and plays an important role in the progression of sepsis.This study aims to explore the expression changes of lymphocyte-derived proBDNF/p75NTR in patients with sepsis and its effect on lymphocyte differentiation. Methods:From the healthy donors(control group,n=40)and sepsis patients(sepsis group,n=40)admitted to the hospital for the first time,peripheral blood samples and blood routine clinical detection indicators were obtained.By using flow cytometry,the proportion of lymphocyte subsets and their expression of proBDNF/p75NTR were examined.The peripheral blood lymphocytes were isolated from the control group and incubated with lipopolysaccharide(LPS).Flow cytometry analysis technology was used to detect the expression of proBDNF/p75NTR on LPS-treated lymphocyte subsets.On this basis,we investigated the effects on lymphocyte differentiation by inhibiting p75NTR. Results:White blood cell count,neutrophil count,and neutrophil percentage of the patients in the sepsis group at admission were significantly higher than those in the control group;on the contrary,lymphocyte count and lymphocyte percentage in the sepsis group were lower than those in the control group(all P＜0.001).The patients in the sepsis group had considerably greater neutrophil/lymphocyte and monocyte/lymphocyte ratios than those in the control group(both P＜0.05).In the peripheral blood of sepsis patients,proBDNF expression was upregulated on CD19+ B cells,whereas p75NTR expression was elevated on B cells,CD4+ T cells,and CD8+ T cells(all P＜0.05).ProBDNF/p75NTR expression was upregulated by LPS stimulation in vitro in peripheral blood cells of the control group(P＜0.05),and this tendency was similar to the expression alterations in peripheral lymphocytes of the sepsis group.Inhibition of p75NTR increased CD4+ T cell and CD19+ B cell percentages,cytokine expression of IL-4 and IL-10,and reduced IL-1β and IL-6 production(all P＜0.05). Conclusion:The immunosuppressive state of sepsis patients is indicated by a reduction in lymphocyte count and an increase in the proportion of inactive neutrophils.ProBDNF/p75NTR expression is upregulated in the peripheral blood lymphocytes of sepsis patients,and p75NTR inhibition may control lymphocyte differentiation involved in sepsis progression.

Objective:To evaluate the value of a novel multiphase three-dimensional deep learning neural network of computer-aided diagnosis (CAD) used in LDCT lung cancer screening.Methods:Eight thousand eight hundred and fifty volunteers with 1 111 nodules were enrolled in the lung cancer screening from November of 2013 to December of 2017, and the baseline LDCT imaging data of volunteers accompanied with clinical information were retrospectively analyzed. All volunteers in this study were designed to receive LDCT test at least once. All the imaging of volunteers were read through the methods of visual detectioin (VD), CAD, and VD Combined CAD. The criteria of the true pulmonary nodule was determinated by the consistent opinion of two specialists in chest imaging（in case of disagreement, the decision should made by the third chief physician). In terms of the numbers, types or Lung-RADS categories of nodules, the detection rate, missed diagnosis rate and false positive rate of pulmonary nodules or lung cancer among three methods were compared, and the rates between groups were compared by χ 2test. Results:Compared with VD or CAD ,the detection rate of nodules in the CAD combined VD was significantly increased (95.7% , 94.2%, vs. 80.1% P<0.05 ), and the rate of missed diagnosis was significantly reduced (5.8%, 4.3% vs. 19.9% ，χ2=101.650, 128.500 ，P<0.05); Compared with VD, the methods of CAD or VD combined CAD significantly increased the the detection rates of Lung-RADS categories (χ2 =25.083,23.449, P=0.000, 0.000) or different types of nodules (χ2=6.955,6.821, P=0.031, 0.033), but there was no statistically significant difference between CAD and VD combined CAD for Lung-RADS categories and different types of nodules (all P>0.05); Compared with VD and VD combined CAD, the positive prediction rate of CAD for lung cancer was significantly reduced, and the rate of missed diagnosis and false positive rate were significantly increased, but there was no significant difference between VD and VD combined CAD in the prediction rate, missed diagnosis rate and false positive rate of lung cancer. Conclusion:The method of CAD combined VD can reduce the detection of false positive nodules and improve the detection rate of true pulmonary nodules,which is the preferred method using in LDCT lung cancer screening for city population.

Objective: To assess dietary and urinary risk factors for urolithiasis by a case-control study. Methods: A retrospective analysis was made on the pathogenic factors of 1 151 patients with urolithiasis admitted to the People′s Hospital of Chenghai District from January 2016 to June 2018, and including external environmental factors and internal personal factors. Results: The proportion of male and female patients was 1.69∶1, and the peak age at onset of disease ranged from 21 to 60 years.Most of patients were diagnosed as upper urinary tract calculi.The following variables were found to have significant effects on the morbidity of urinay calculi: less intake of water, over intake of protein, fat and salt. Conclusion The diet and increase water intake and with low-protein, low-fat and low-salt diet are helpful to prevent urolithiasis.

OBJECTIVE： To investigate current status and quality of domestic pharmacoeconomic literatures， and to provide reference for the standardization of pharmacoeconomic research. METHODS： Retrieved from CNKI， Wanfang， VIP and other database， the pharmacoeconomic literatures published from Jan. 2017 to May 2018 were collected. The qualities of literatures were evaluated with Guidelines for Quality Evaluation of Pharmacoeconomics Evaluation Reports （“PEERs” for short）. RESULTS： Totally 160 domestic pharmacoeconomic research literatures were included. The results of PEERs evaluation showed of which the coincidence rate was 32.5％ （52/160）. The literatureswhich were in full compliance （the report had a certain reference value） accounted for 1.3％ （2/160）， which were in basic compliance （the report had certain reference value after being revised） accounted for 31.3％（50/160），which were in non-conformity （the report did not had reference value） accounted for 67.5％（108/160）. Domestic pharmacoeconomic researches were of high quality in terms of research object， evaluation method and content，research purpose，  research design and design type， etc.； but the researches were of low quality in terms of research angle， incremental cost/incremental output analysis， sensitivity analysis and other aspects， and there was no explanation or unclear elaboration. CONCLUSIONS： The quality of domestic pharmacoeconomic research literatures are uneven， and their research quality needs to be further improved. It is recommended to standardize the evaluation of pharmacoeconomics， making the evaluation of pharmacoeconomics more scientific and objective.

Objective To investigate the correlation between quantitative parameters of dynamic contrast?enhanced MRI (DCE?MRI) after neoadjuvant chemotherapy and pathological grades in esophageal squamous cell carcinoma. Methods Fifty?six patients with esophageal squamous cell carcinoma who were confirmed by esophagoscope and received neoadjuvant chemotherapy before operation between September 2015 and December 2017 in the Affiliated Cancer Hospital of Zhengzhou University were prospectively analyzed, and MRI examination was performed within one week before operation. All patients underwent routine chest MRI and DCE?MRI scanning, and quantitative parameters of DCE?MRI, including volume transfer constant (Ktrans),exchange rate constant (Kep) and extravascular extracellular volume fraction (Ve) were measured. Pathological grading was assessed as highly differentiated, moderately differentiated, poorly differentiated,and undifferentiated. Intraclass correlation coefficient (ICC) was calculated from the results of two radiologists. Kruskal?Wallis H test was used to compare the differences of quantitative parameters between different pathological grade groups of DCE?MRI,and Mann?Whitney U test was utilized to compare the intraclass differences among pathological grades. Spearman rank correlation analysis was performed for evaluating the correlation between DCE?MRI parameters and pathological grade of esophageal squamous cell carcinoma. The receiver operating characteristic (ROC) curves were used to evaluate the diagnosis accuracy of different DCE?MRI parameters in pathological grade of esophageal squamous cell carcinoma after neoadjuvant chemotherapy. Results The 56 patients were divided into four groups according to pathological findings: well differentiated group (n=8), moderately differentiated group (n=39), poorly differentiated group (n=9) and undifferentiated group (n=0). The differences of Ktransmean,Ktrans75%,Kepmax, Kepmean,Kep75% between different pathological grading groups were statistically significant (all P<0.05),and these parameters showed positive correlation significantly with pathological grading (r values were 0.778, 0.632, 0.594, 0.725, 0.489 respectively, all P<0.05). The ROC curve area of Ktransmean, Ktrans75% in the diagnosis of pathological grade for esophageal squamous cell carcinoma was 0.750,0.856,respectively. The diagnostic efficiency of Ktrans75% was the best with the diagnostic threshold of 0.693/min,sensitivity of 87.5%, specificity of 78.5%, respectively. Conclusion The quantitative parameters of DCE?MRI after neoadjuvant chemotherapy in esophageal squamous cell carcinoma have the potential value for predicting pathological grade.

Objective To investigate the CT and MRI finding of extrapleural solitary fibrous tumor (ESFT) to improve the preoperative diagnostic ability of such tumors. Methods The clinical data and CT/MRI finding of 11 ESFT patients confirmed by pathology from January 2007 to June 2018 in Jiaxing Traditional Chinese Medicine Hospital Affiliated to Zhejiang Chinese Medicine University were retrospectively analyzed. CT scan was performed in 9 cases and MRI scan in 4 cases. Results Of the 11 patients with ESFT, 6 cases occurred in the abdominal cavity, 3 cases in the cavitas pelvis and 2 cases in the ocular region. All the tumors were solitary, and the maximum diameter of the lesion was (8.3 ± 4.2) cm. The boundary of the tumor was clear in 7 cases, and the boundary was not clear in 4 cases. The tumor form was circular or fusiform in 6 cases and lobulated in 5 cases (some tumors had notch sign). CT scanning presented isodensity or inhomogeneous low density, including 4 cases of cystic degeneration accompanied by inner grid separation, and 3 cases of patchy calcification. The enhanced scanning mass showed 6 cases of geographic enhancement and 7 cases of earthworm drilling soil. MRI T1WI showed slightly lower signal intensity; T2WI fat-suppression sequences showed slightly higher mixed signal intensity in 2 cases and an iso-to high mixed signal intensity in 2 cases; and DWI showed uneven high signal intensity in 3 cases. The solid part of the enhanced scanning showed'fast enhancement and slow washout'. Conclusions ESFT is usually manifested as isolated mass, and its CT and MRI finding has certain characteristics, especially in the diagnosis and differential diagnosis of the disease, such as geographic enhancement and earthworm drilling soil signs.