As a high sensitive biomarker of lung cancer ,IGFBP2 plays an important role in the occur-rence,development and treatment of lung cancer .Studies have showed that it promotes tumor progression by acti-vating the IGF1R and integrin mediated signal transduction pathway .Recent researches have demonstrated that it participates in targeted therapy of lung cancer ,which may become a new target for the treatment of lung cancer . This paper makes a review on the relationship between IGFBP 2 and lung cancer .

Objective:To summarize the clinical manifestations and color Doppler ultrasonography of benign lymphoepithelial disease (BLL) in lacrimal gland, so as to improve the diagnostic accuracy of lacrimal BLL.Methods:Clinical manifestations and color Doppler flow imaging (CDFI) features of lacrimal BLL in 16 patients (2 males and 14 females, with 31 lesions) who visited the Second Hospital of Hebei Medical University from November 2014 to August 2019 were retrospectively analyzed.Results:The performance for lesions in patients with duration less than 3 months was scattered in irregular low echo, lesion blood flow signals within the rich (Adler Ⅱ level), pathologic examination results showed more lymphocytes were seen in the lacrimal matrix, and the myoepithelium of the lacrimal duct grew to form the epithelium-myocutaneous island. The ultrasonic feasures in patients with course of 3-6 months were in multiple categories such as circular low echo, "honeycomb" change, CDFI showed lesions with a lot of blood flow signals (Adler Ⅲ level), the pathological examination results indicated that there were a large number of lymphocytes and epithelial-musculocutaneous islands in the lacrimal matrix, and the lymphocytes were significantly increased compared with patients with the course of disease less than 3 months. The ultrasound results in patients with a course of more than 6 months showed lesions in multiple categories such as circular low echo, and large low echo, greater than 3 mm in diameter, CDFI showed lesions within the same large amounts of blood flow signals (Adler Ⅲ level), the pathological examination results were consistent with the course of 3 to 6 months. One patient had positive tuberculin test and 11 had higher IgG4 than normal.The number of lymphocytes increased with the prolongation of disease course.Conclusions:With the expert knowledge of color Doppler ultrasonographic characteristics of lacrimal gland BLL and with the serum IgG4 level helps to improve the accuracy of ultrasonic diagnosis.

Objective:To analyze the risk factors of acute kidney injury (AKI) in patients with septic shock in intensive care unit (ICU), construct a predictive model, and explore the predictive value of the predictive model.Methods:The clinical data of patients with septic shock who were hospitalized in the ICU of the Affiliated Hospital of Jining Medical College from April 2015 to June 2019 were retrospectively analyzed. According to whether the patients had AKI within 7 days of admission to the ICU, they were divided into AKI group and non-AKI group. 70% of the cases were randomly selected as the training set for building the model, and the remaining 30% of the cases were used as the validation set. XGBoost model was used to integrate relevant parameters to predict the risk of AKI in patients with septic shock. The predictive ability was assessed through receiver operator characteristic curve (ROC curve), and was correlated with acute physiology and chronic health evaluationⅡ(APACHEⅡ), sequential organ failure assessment (SOFA), procalcitonin (PCT) and other comparative verification models to verify the predictive value.Results:A total of 303 patients with septic shock were enrolled, including 153 patients with AKI and 150 patients without AKI. The incidence of AKI was 50.50%. Compared with the non-AKI group, the AKI group had higher APACHEⅡscore, SOFA score and blood lactate (Lac), higher dose of norepinephrine (NE), higher proportion of mechanical ventilation, and tachycardiac. In the XGBoost prediction model of AKI risk in septic shock patients, the top 10 features were serum creatinine (SCr) level at ICU admission, NE use, drinking history, albumin, serum sodium, C-reactive protein (CRP), Lac, body mass index (BMI), platelet count (PLT), and blood urea nitrogen (BUN) levels. Area under the ROC curve (AUC) of the XGBoost model for predicting the risk of AKI in patients with septic shock was 0.816, with a sensitivity of 73.3%, a specificity of 71.7%, and an accuracy of 72.5%. Compared with the APACHEⅡscore, SOFA score and PCT, the performance of the model improved significantly. The calibration curve of the model showed that the goodness of fit of the XGBoost model was higher than the other scores (the calibration curve had the lowest score, with a score of 0.205).Conclusion:Compared with the commonly used clinical scores, the XGBoost model can more accurately predict the risk of AKI in patients with septic shock, which helps to make appropriate diagnosis, treatment and follow-up strategies while predicting the prognosis of patients.