Objective To explore the clinical characteristic,level of plasma renin angiotensin (PRA),plas-ma angiotensin Ⅱ(Ang Ⅱ)and plasma aldosterone(Aldo)in the sleep apnea hypopnea syndrome (SAHS)patients, and to investigate the association between SAHS and hypertension.Methods The patients were selected for the study who were monitored with polysomnography.They were divided into SAHS group and non-SAHS group according to apea-hypopnea index(AHI),and there were 180 patients in the SAHS group,175 patients in the non-SAHS group. The systolic blood pressure(SBP),diastolic blood pressure(DBP)and the level of PRA,plasma Ang II and plasma Aldo were compared by variance analysis.Results The gender composition was different between the two groups,and had statistically significant difference(χ2 =16.30,P <0.01).The data of age,body mass index,neck circumference, waistline,DBP,SBP in SAHS group were significantly higher than those in non-SAHS group,and the differences were statistically significant(t =6.84,8.19,9.84,6.63,7.08,5.45,all P <0.01 ).The prevalence of hypertension in SAHS group was 46.58%,which was higher than 18.20% in non-SAHS group,and the difference had statistically significant(χ2 =46.71,P <0.01).The AHI had positive correlation with SBP,DBP,and they had statistically signifi-cant differences (rs =0.162,0.228,all P <0.01).The levels of PRA and plasma Ang Ⅱ were lower in SAHS group than those in non-SAHS group,while the level of plasma Aldo was higher in SAHS group than that in non-SAHS group,and had statistically significant differences(F =15.41,14.21,17.67,all P <0.01).In the SAHS group,the levels of PRA and plasma Ang Ⅱ were lower in hypertension group than those in non-hypertension group,while the level of plasma Aldo was higher in hypertension group than that in non-hypertension group,and had statistically signif-icant differences (F =15.41,14.21,17.67,all P <0.01).Also,the levels of PRA and plasma Ang Ⅱ were lower in SAHS group with hypertension than those in non-SAHS group with hypertension,while the level of plasma Aldo was higher in SAHS group with hypertension than that in non-SAHS group with hypertension,and the differences were sta-tistically significant(F =15.41,14.21,17.67,all P <0.01).Conclusion The occurrence of SAHS is correlated with the gender composition,age,body mass index,neck circumference,waistline,DBP and SBP.In SAHS complica-tions in each system,the highest incidence is hypertension.And the AHI has positive correlation with SBP,DBP,and the difference is significant.In the SAHS group,if the AHI is higher,the risk of hypertension is greater.In the SAHS patients with hypertension,the level of plasma Aldo is significantly elevated,while the levels of PRA and plasma AngⅡ are decreased significantly.

Although links between cancer and inflammation were firstly proposed in the nineteenth century, the molecular mechanism has not yet been clearly understood. Epidemiological studies have identified chronic infections and inflammation as major risk factors for various types of cancer. NF-κB transcription factors and the signaling pathways are central coordinators in innate and adaptive immune responses. STAT3 regulates the expression of a variety of genes in response to cellular stimuli, and thus plays a key role in cell growth and apoptosis. Recently, roles of NF-κB and STAT3 in colon, gastric and liver cancers have been extensively investigated. The activation and interaction between STAT3 and NF-κB play vital roles in control of the communication between cancer cells and inflammatory cells. NF-κB and STAT3 are two major factors controlling the ability of pre-neoplastic and malignant cells to resist apoptosis-based tumor-surveillance and regulating tumor angiogenesis and invasiveness. Understanding the molecular mechanisms of NF-κB and STAT3 cooperation in cancer will offer opportunities for the design of new chemo-preventive and chemotherapeutic approaches.
Cell Transformation, Neoplastic ; Humans ; Inflammation ; metabolism ; NF-kappa B ; chemistry ; metabolism ; Neoplasms ; metabolism ; pathology ; Protein Structure, Tertiary ; STAT3 Transcription Factor ; chemistry ; metabolism ; Signal Transduction

The immune checkpoint blockade (ICB) targeting on PD-1/PD-L1 has shown remarkable promise in treating cancers. However, the low response rate and frequently observed severe side effects limit its broad benefits. It is partially due to less understanding of the biological regulation of PD-L1. Here, we systematically and comprehensively summarized the regulation of PD-L1 from nuclear chromatin reorganization to extracellular presentation. In PD-L1 and PD-L2 highly expressed cancer cells, a new TAD (topologically associating domain) (chr9: 5,400,000-5,600,000) around CD274 and CD273 was discovered, which includes a reported super-enhancer to drive synchronous transcription of PD-L1 and PD-L2. The re-shaped TAD allows transcription factors such as STAT3 and IRF1 recruit to PD-L1 locus in order to guide the expression of PD-L1. After transcription, the PD-L1 is tightly regulated by miRNAs and RNA-binding proteins via the long 3'UTR. At translational level, PD-L1 protein and its membrane presentation are tightly regulated by post-translational modification such as glycosylation and ubiquitination. In addition, PD-L1 can be secreted via exosome to systematically inhibit immune response. Therefore, fully dissecting the regulation of PD-L1/PD-L2 and thoroughly detecting PD-L1/PD-L2 as well as their regulatory networks will bring more insights in ICB and ICB-based combinational therapy.

Aiming at the problems of missing important features, inconspicuous details and unclear textures in the fusion of multimodal medical images, this paper proposes a method of computed tomography (CT) image and magnetic resonance imaging (MRI) image fusion using generative adversarial network (GAN) and convolutional neural network (CNN) under image enhancement. The generator aimed at high-frequency feature images and used double discriminators to target the fusion images after inverse transform; Then high-frequency feature images were fused by trained GAN model, and low-frequency feature images were fused by CNN pre-training model based on transfer learning. Experimental results showed that, compared with the current advanced fusion algorithm, the proposed method had more abundant texture details and clearer contour edge information in subjective representation. In the evaluation of objective indicators, Q ^AB/F, information entropy (IE), spatial frequency (SF), structural similarity (SSIM), mutual information (MI) and visual information fidelity for fusion (VIFF) were 2.0%, 6.3%, 7.0%, 5.5%, 9.0% and 3.3% higher than the best test results, respectively. The fused image can be effectively applied to medical diagnosis to further improve the diagnostic efficiency.
Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Tomography, X-Ray Computed ; Magnetic Resonance Imaging/methods* ; Algorithms