OBJECTIVE To investigate the effect of bevacizumab ,an anti-human vascular endothelial growth factor monoclonal antibody,on pulmonary dissemination of colorectal cancer. METHODS A metastatic colorectal cancer mouse model was established. Mice were randomly divided into two groups(n=8). The mice in experimental group were administered ip with bevacizumab at the dosage of 5 mg · kg-1,and those in control group were given isotype IgG at the same dosage. The antibodies were administered on 2 d before initiation of model establishment and 2 d after that,then once every 5 d for 4 weeks,for a total of 7 times. Liver and lung metastases were determined by histopathological examination. The chemokine receptor C-X-C receptor 4(CXCR4)and its ligand C-X-C ligand 12(CXCL12)mRNA expression in the lung were detected by quantitative RT-PCR. Human colon cancer cells HCT116 were treated with bevacizumab(5 mg·L-1)for 24 h. The expression levels of vascular endothelial growth factor receptor 1(VEGFR1)and CXCR4/7 protein as well as CXCR3/4/7 mRNA were examined by Western blotting and quantitative RT-PCR respectively. RESULTS The number of mice(2/8) with liver metastases was reduced,while the number of mice(8/8) with lung metastases increased in experimental group compared with isotype IgG-treated group(6/8 and 2/8 respectively,P<0.05). The mRNA expression level of CXCR4 and CXCL12 in lung tissue was significantly up-regulated in bevacizumab-treated group com?pared with control group(P<0.05). The mRNA and protein expression level of CXCR4 and CXCR7 was dramatically increased in HCT116 cells treated with bevacizumab(P<0.05). CONCLUSION Bevacizumab can potentially promote lung metastases of colorectal cancer,which may be related to up-regulation of CXCR4 and CXCL12 expression.

Objective To explore the relevance between gait speed and muscle strength of lower extremities, or several kinds of physical functional tests. Methods 341 community-dwelling individuals (160 males, 181 females) aged 65-94 years were selected. They were divided into suspected sarcopenia group (n=137) and normal group (n=204) by their gait speed less or more than 0.8 m/s. It was compared between both groups with the basic physical characteristics, strength of iliopsoas, quadriceps, hamstrings and tibialis anterior, and the scores of One Leg Standing Test, Berg Balance Scale, Functional Gait Assessment, Functional Stretch Test and Timed Up and Go Test. Results The subjects were older in the suspected sarcopenia group than in the normal group. The difference of body weight, height were not statistically significant between groups. The strength of the muscles in bilateral lower limbs was not significantly different between both groups (P>0.05), while the gait speed positively correlated with the strength of iliopsoas, quadriceps and hamstrings (r=0.121-0.227, P<0.05), but not with the tibialis anterior (P>0.05). Gait speed positively correlated with the scores of One Leg Standing Test, Berg Balance Scale, Functional Gait Assessment, Functional Stretch Test (P<0.05), and negatively correlated with the score of Timed Up and Go Test (r=-0.502, P<0.001). The scores of all the tests were significantly different between 2 groups (P<0.05), except that of Functional Stretch Test (P=0.28). Conclusion Sarcopenia diagnosis is not only depended on the strength of muscle of lower extremity, but also their functions.

Objective To investigate the effects of ultrasound-guided continuous thoracic paravertebral nerve block combined with general anesthesia on cardiac function and postoperative complications in elderly patients undergoing thoracotomy.Methods A total of 108 elderly patients who underwent thoracotomy in our hospital from January 2017 to December 2018 were randomly divided into the general anesthesia group(receiving general anesthesia)and the combination group (receiving ultrasound-guided continuous thoracic paravertebral nerve block combined with general anesthesia) (n=54,each group).The anesthesia effect was compared between the two groups.Results The excellence rate of anesthesia was higher in the combination group than in the general anesthesia group(90.7％ vs.72.2％,x2 =4.267,P =0.039).Stroke volume variability(SVV),stroke volume(SV),heart rate(HR) and mean artery pressure(MAP)had no significant difference between the two groups at T0(pre-anesthesia)(P＞0.05).At T1 (anesthesia),T2 (intraoperative tissue traction),and T3(postoperative suture),there were significant differences in SVV,SV,HR and MAP between the two groups(P＜0.05).The incidence of postoperative complications was lower in the combination group than in the general anesthesia group(7.4％ vs.22.2％,x2 =4.696,P=0.000).Conclusions Ultrasound-guided continuous thoracic paravertebral nerve block combined with general anesthesia has good anesthetic effects,minor influence on cardiac function and a low incidence of postoperative complications in elderly patients undergoing thoracotomy.

Objective:To construct an prediction model based on magnetic resonance imaging (MRI) machine learning algorithm and radiomics and investigate its application value in predicting lymphovascular invasion (LVI) status of rectal cancer without lymph node metastasis.Methods:The retrospective cohort study was conducted. The clinicopathological data of 204 rectal cancer patients without lymph node metastasis who were admitted to Gansu Provincial Hospital from February 2016 to January 2024 were collected. There were 123 males and 81 females, aged (61±7)years. All 204 patients were randomly divided into the training dataset of 163 cases and the testing dataset of 41 cases by a ratio of 8∶2 using the electronic computer randomization method. The training dataset was used to construct the prediction model, and the testing dataset was used to validate the prediction model. The clinical prediction model, radiomics model and joint prediction model were constructed based on the selected clinical and/or imaging features. Measurement data with normal distribution were represented as Mean± SD. Count data were described as absolute numbers, and the chi-square test or Fisher exact probability were used for comparison between the groups. Comparison of ordinal data was conducted using the nonparameter rank sum test. The inter-class correlation coefficient (ICC) was used to evaluate the consistency of the radiomics features of the two doctors, and ICC >0.80 was good consistency. Univariate analysis was conducted by corres-ponding statistic methods. Multivariate analysis was conducted by Logistic stepwise regression model. The receiver operating characteristic (ROC) curve was drawn, and the area under the curve (AUC), Delong test, decision curve and clinical impact curve were used to evaluate the diagnostic efficiency and clinical utility of the model. Result:(1) Analysis of factors affecting LVI status of patients. Of the 204 rectal cancer patients without lymph node metastasis, there were 71 cases with positive of LVI and 133 cases with negative of LVI. Results of multivariate analysis showed that gender, platelet (PLT) count and carcinoembryonic antigen (CEA) were independent factors affecting LVI status of rectal cancer without lymph node metastasis in training dataset [ odds ratio=2.405, 25.062, 2.528, 95% confidence interval ( CI) as 1.093-5.291, 2.748-228.604, 1.181-5.410, P<0.05]. (2) Construction of clinical prediction model. The clinical prediction model was conducted based on the results of multivariate analysis including gender, PLT count and CEA. Results of ROC curve showed that the AUC, accuracy, sensitivity and specificity of clinical prediction model were 0.721 (95% CI as 0.637-0.805), 0.675, 0.632 and 0.698 for the training dataset, and 0.795 (95% CI as 0.644-0.946), 0.805, 1.000 and 0.429 for the testing dataset. Results of Delong test showed that there was no significant difference in the AUC of clinical prediction model between the training dataset and the testing dataset ( Z=-0.836, P>0.05). (3) Construction of radiomics model. A total of 851 radiomics features were extracted from 204 patients, and seven machine learning algorithms, including logistic regression, support vector machine, Gaussian process, logistic regression-lasso algorithm, linear discriminant analysis, naive Bayes and automatic encoder, were used to construct the prediction model. Eight radiomics features were finally selected from the optimal Gaussian process learning algorithm to construct a radiomics prediction model. Results of ROC curve showed that the AUC, accuracy, sensitivity and specificity of radiomics prediction model were 0.857 (95% CI as 0.800-0.914), 0.748, 0.947 and 0.642 for the training dataset, and 0.725 (95% CI as 0.571-0.878), 0.634, 1.000 and 0.444 for the testing dataset. Results of Delong test showed that there was no significant difference in the AUC of radiomics prediction model between the training dataset and the testing dataset ( Z=1.578, P>0.05). (4) Construction of joint prediction model. The joint prediction model was constructed based on the results of multivariate analysis and the radiomics features. Results of ROC curve showed that the AUC, accuracy, sensitivity and specificity of radiomics prediction model were 0.885 (95% CI as 0.832-0.938), 0.791, 0.912 and 0.726 for the training dataset, and 0.857 (95% CI as 0.731-0.984), 0.854, 0.714 and 0.926 for the testing dataset. Results of Delong test showed that there was no significant difference in the AUC of joint prediction model between the training dataset and the testing dataset ( Z=0.395, P>0.05). (5) Performance comparison of three prediction models. Results of the Hosmer-Lemeshow goodness-of-fit test showed that all of the clinical prediction model, radiomics prodiction model and joint prediction model having good fitting degree ( χ2=1.464, 12.763, 10.828, P>0.05). Results of Delong test showed that there was no signifi-cant difference in the AUC between the clinical prediction model and the joint prediction model or the radiomics model ( Z=1.146, 0.658, P>0.05), and there was a significant difference in the AUC between the joint prediction model and the radiomics model ( Z=2.001, P<0.05). Results of calibra-tion curve showed a good performance in the joint prediction model. Results of decision curve and clinical impact curve showed that the performance of joint prediction model in predicting LVI status of rectal cancer without lymph node metastasis was superior to the clinical prediction model and the radiomics model. Conclusions:The clinical prediction model is constructed based on gender, PLT count and CEA. The radiomics predictive model is constructed based on 8 selected radiomics features. The joint prediction model is constructed based on the clinical prediction model and the radiomics predictive model. All of the three models can predict the LVI status of rectal cancer with-out lymph node metastasis, and the joint prediction model has a superior predictive performance.

Objective:To investigated the prevalence of anxiety and depression symptoms in patients with colorectal polyps in part of Xinjiang area and to explore the associated influencing factors related to psychological status, and to provide evidence and clues to promote the diagnosis and treatment of psychosomatic diseases in digestive system.Methods:From December 2021 to June 2022, at the First Affiliated Hospital of Shihezi University, the Fourth Division Hospital of Xinjiang Production and Construction Corps, the Third Division Hospital of Xinjiang Production and Construction Corps (Kashgar Hospital), the Thirteenth Division Red Star Hospital of Xinjiang Production and Construction Corps, the Tenth Division Beitun Hospital of Xinjiang Production and Construction Corps, the Seventh Division Hospital of Xinjiang Production and Construction Corps, the Fifth Division Hospital of Xinjiang Production and Construction Corps, patients who underwent colonoscopy and colorectal polyps detected were enrolled. The generalized anxiety disorder scale-7 (GAD-7) was used to screen anxiety symptoms, and the patient health questionaire-8 (PHQ-8) was performed to screen depression symptoms, and the general situation questionnaire was used to collect clinical information of patients. The questionnairs were completed via the Questionnaire Star platform or paper questionnaire, and a database was established. The patients were divided into groups according to whether with anxiety and depression symptoms. Multivariable logistic regression models was performed to analyze the factors related to anxiety and depression.Results:A total of 516 questionnaires were distributed and collected, among which 9 questionnaires were incomplete and 507 questionnaires were valid, the effective rate of questionnaires was 98.26%. The detection rates of anxiety and depression symptoms in 507 patients with colorectal polyps were 21.50%(109/507) and 19.33%(98/507), respectively. The results of multivariable logistic analysis revealed that female ( OR=3.87, 95% confidence interval (95% CI) 2.30 to 6.51, P<0.001), maximum diameter of polyp ( OR=1.74, 95% CI 1.14 to 2.67, P=0.011), perception of polyps as cancer ( OR=13.96, 95% CI 1.48 to 132.07, P=0.022), and the occurrence of gastrointestinal symptoms after polyp detection ( OR=5.43, 95% CI 1.74 to 16.92, P=0.004) were independent risk factors of anxiety in patients with colorectal polyps. Female ( OR=2.42, 95% CI 1.47 to 4.00, P=0.001), the number of polyps ( OR=1.07, 95% CI 1.01 to 1.13, P=0.028) and the count of gastrointestinal symptoms ( OR=2.04, 95% CI 1.34 to 3.10, P=0.001) were independent risk factors of depression in patients with colorectal polyps. Conclusion:Gender, polyp size, number of polyps, disease perception, and concomitant gastrointestinal symptoms are associated with anxiety and depression in patients with colorectal polyps.

Objective : To investigate the effect of long non⁃coding RNA (LncRNA) anoctamin 1 antisense RNA⁃1 (ANO1⁃AS1) on the proliferation and apoptosis of esophageal squamous cell carcinoma (ESCC) cells and its possible mechanisms. Methods : Silenced ANO1⁃AS1 lentivirus was transfected in ESCC cells TE⁃1 and EC109. Subsequently, the expression levels of ANO1⁃AS1 and calcium⁃activated chloride channel protein 1 (ANO1) in the cells were detected by qRT⁃PCR. CCK⁃8 and colony formation assays were used to detect the proliferation of TE⁃1 and EC109 cells. ANO1 positively related expressed genes were obtained from the LinkedOmics database and then the gene set was enriched for pathways and possible pathways were validated. The expression levels of proliferating cell nuclear antigen(PCNA), P53 protein, apoptosis⁃related protein ( Bax and Bcl⁃2), ANO1 protein and phosphatidylinositol⁃3⁃kinase/protein kinase B (PI3K/Akt) pathway⁃related protein were assessed by Western blot. Results: After transfection of lentivirus with silent expression function, the expression level of ANO1⁃AS1 was significantly reduced in TE⁃1 and EC109 cells (P < 0. 05); After down⁃regulation of ANO1⁃AS1, compared with the negative control group, the proliferation ability of ESCC cells was reduced (P < 0. 05) and the rate of clone formation decreased (P < 0. 05); Western blot results showed that, compared with negative controls, the expression of PCNA decreased, the expression of oncogene P53 protein increased ( P < 0. 05 ), the expression of proteins ( Bax) increased, Bcl⁃2 decreased and the levels of phosphorylation of the pathway proteins PI3K and Akt decreased (P < 0. 05) . Conclusion Knockdown of ANO1⁃AS1 can decrease proliferation and promote apoptosis in ESCC, which may be achieved by affecting PI3K/Akt pathway activation.