Objective:To evaluate the feasibility and clinical value of pre-treatment non-enhanced chest CT radiomics features and machine learning algorithm to predict the mutation status and subtype (19Del/21L858R) of epidermal growth factor receptor (EGFR) for patients with non-small cell lung cancer (NSCLC).Methods:This retrospective study enrolled 280 NSCLC patients from first and second affiliated hospital of University of South China who were confirmed by biopsy pathology, gene examination, and have pre-treatment non-enhanced CT scans. There are 136 patients were confirmed EGFR mutation. Primary lung gross tumor volume was contoured by two experienced radiologists and oncologists, and 851 radiomics features were subsequently extracted. Then, spearman correlation analysis and RELIEFF algorithm were used to screen predictive features. The two hospitals were training and validation cohort, respectively. Clinical-radiomics model was constructed using selected radiomics and clinical features, and compared with models built by radiomics features or clinical features respectively. In this study, machine learning models were established using support vector machine (SVM) and a sequential modeling procedure to predict the mutation status and subtype of EGFR. The area under receiver operating curve (AUC-ROC) was employed to evaluate the performances of established models.Results:After feature selection, 21 radiomics features were found to be efffective in predicting EGFR mutation status and subtype and were used to establish radiomics models. Three types models were established, including clinical model, radiomics model, and clinical-radiomics model. The clinical-radiomics model showed the best predictive efficacy, AUCs of predicting EGFR mutation status for training dataset and validation dataset were 0.956 (95% CI: 0.952-1.000) and 0.961 (95% CI: 0.924-0.998), respectively. The AUCs of predicting 19Del/L858R mutation subtype for training dataset and validation dataset were 0.926 (95% CI: 0.893-0.959), 0.938 (95% CI: 0.876-1.000), respectively. Conclusions:The constructed sequential models based on integration of CT radiomics, clinical features and machine learning can accurately predict the mutation status and subtype of EGFR.

Objective:To construct and implement a multidisciplinary pain management model during the perioperative period based on the project-achieving quality control circle, so as to improve the quality of patient pain management during the perioperative period.Methods:Using the convenient sampling, 310 surgical patients from the Department of Gastrointestinal Surgery, Hepatobiliary Surgery, Thoracic Surgery, Urology Surgery and Joint Surgery of Liaocheng People's Hospital from June to July 2020 were taken as the pre-improvement group, and the routine perioperative pain management model was implemented. Starting from August 2020, a project-achieving quality control circle was carried out, following the steps of theme selection, topic clarification, goal setting, formulation of strategies, investigation of the best strategies, implementation of strategies, and confirmation of effectiveness, to implement a multidisciplinary pain management model during the perioperative period. A total of 310 surgical patients admitted to 5 departments from February to March 2021 were included in the improvement group.Results:The implementation rate of multidisciplinary pain management plan, the rate of out-of-bed activity within 24 hours after surgery, the rate of excellent postoperative rehabilitation compliance, and the average sleep score of patients in the improvement group all increased, with statistical differences ( P<0.05). After improvement, the awareness rate of pain knowledge among medical and nursing staff, the accuracy rate of nurses' rest and active pain assessment records, and the score of nurse pain knowledge all increased, and the differences were statistically significant ( P<0.05) . Conclusions:The construction and implementation of a multidisciplinary pain management model during the perioperative period based on the project-achieving quality control circle can effectively improve the quality of pain management for surgical patients, accelerate patient recovery, and improve the pain management of medical and nursing staff.

Objectives:To explore the clinicopathological characteristics and prognostic risk factors in differentiated thyroid cancer (DTC) patients with lung metastasis.Methods:Patients of differentiated thyroid cancer with lung metastasis in Tianjin Medical University Cancer Institute & Hospital were enrolled from Jan 1, 2010 to Dec 31, 2016. The clinicopathological characteristics and risk factors affecting the prognosis were analyzed retrospectively.Results:A total of 65 DTC patients with lung metastasis were collected in this study, including 56 patients with papillary thyroid carcinoma and 9 patients with follicular thyroid carcinoma; 23 patients died and 42 patients survived. Median follow-up time was 99.4 months. There were 18 males, 47 females. Age 14-73 years, median age 51.0 years. High incidence of DTC lung metastasis was 50-59 years for males and 40-49 years for females. Based on AJCC 8th edition TNM staging, there were 37 patients in stage Ⅱ (age <55 years) and 28 patients in stage Ⅳb (age ≥55 years). The number of 131Ⅰ treatments performed ranged from 1 to 13 times, with a mean of 3.9 times. Firty-five patients were with lung metastasis alone, and 10 patients with lung metastasis and distant metastasis in other organs. Eleven patients suffered from hypoparathyroidism after 131Ⅰ treatment. COX multifactorial regression analysis found that age was independent risk factor affecting prognosis, multiple organs distant metastasis and pathologic subtype were relative risk factors affecting prognosis. There was no correlation between gender, number of 131Ⅰ treatments and poor prognosis. Conclusions:DTC has a high survival even with the occurrence of lung metastasis, but the prognosis is poor when combined with multi-organ metastasis. Age and multiple organ distant metastatic are independent risk factors affecting prognosis.

AIM: To establish a ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method to determination the plasma concentration of clozapine and compare the bioequivalence of a generic clozapine tablet with Clozaril

Lamin B1 is one of the essential members of the nuclear lamina protein family. Its main function is to maintain the integrity of nuclear skeleton, as well as to participate in the cell proliferation and aging by affecting the chromosome distribution. gene expression, and DNA damage repair. The abnormal expression of lamin B1 is related to certain diseases, including neurological diseases [e.g. neural tube defects (NDTs), adult-onset autosomal dominant leukodystrophy (ADLD)] and tumors (e.g. pancreatic cancer). It is also a potential tumor marker as well as drug target. Further research on lamin B1 will help people understand the molecular mechanism of the emergence and development of neural system diseases and tumors, and define a new future in drug target.
Cell Nucleus ; Gene Expression ; Humans ; Lamin Type B ; physiology ; Neoplasms ; Nervous System Diseases