Establishing an oxidative stress mitochondria-related prognostic model in hepatocellular carcinoma based on multi-omics characteristics and machine learning computational framework.

Hepatocellular carcinoma (HCC) has high incidence and mortality rates worldwide. Damaged mitochondria are characterized by the overproduction of reactive oxygen species (ROS), which can promote cancer development. The prognostic value of the interplay between mitochondrial function and oxidative stress in HCC requires further investigation. Gene expression data of HCC samples were collected from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC). We screened prognostic oxidative stress mitochondria-related (OSMT) genes at the bulk transcriptome level. Based on multiple machine learning algorithms, we constructed a consensus oxidative stress mitochondria-related signature (OSMTS), which contained 26 genes. In addition, we identified six of these genes as having a suitable prognostic value for OSMTS to reduce the difficulty of clinical application. Univariate and multivariate analyses verified the OSMTS as an independent prognostic factor for overall survival (OS) in HCC patients. The OSMTS-related nomogram demonstrated to be a powerful tool for the clinical diagnosis of HCC. We observed differences in biological function and immune cell infiltration in the tumor microenvironment between the high- and low-risk groups. The highest expression of the OSMTS was detected in hepatocytes at the single-cell transcriptome level. Hepatocytes in the high- and low-risk groups differed significantly in terms of biological function and intercellular communication. Moreover, at the spatial transcriptome level, high expression of OSMTS was mainly in regions enriched in hepatocytes and B cells. Potential drugs targeting specific risk subgroups were identified. Our study revealed that the OSMTS can serve as a promising tool for prognosis prediction and precise intervention in HCC patients.

CCAIB: Congestion Control Based on Adaptive Integral Backstepping for Wireless Multi-Router Network.

Wireless information collecting and processing terminals, such as cell phones, sensors and smart wearable devices, are expected to be deployed on a large scale in the future to promote the continuous advancement of the global information revolution. Since most of these terminals connect to each other using long-distance and high-speed networks by multiple routers and eventual access the internet, the application of mobile internet is gradually increasing and data traffic on the mobile internet is growing exponentially, from which arises congestion in wireless networks on multiple routers. This research solves the congestion problem for wireless networks with multiple bottleneck routers. First, the wireless network model is expanded to multi-router networks, which considers the interrelationships between connecting routers. Afterwards, a new Active Queue Management (AQM) method called Congestion Control Based on Adaptive Integral Backstepping (CCAIB) is designed to handle congestion in wireless networks. In CCAIB, an adaptive control method is used to estimate the packet loss ratios of wireless links and a controller is designed based on the estimation results through a backstepping procedure. It can be shown from the simulation results that the performance of CCAIB is better than the H∞ algorithm in queue length stability. Besides, the window size of CCAIB is 100 times that of the H∞ algorithm, and the proportion of packets marked as discarded when using CCAIB is about 0.1% of the H∞ algorithm. Moreover, CCAIB has satisfactory adaptability to network parameters such as wireless link capacity, propagation delay, wireless packet loss ratios, desired queue length and router location.

Long noncoding RNA RP11-909N17.2 presages a poor prognosis of non-small cell lung cancer.

BACKGROUND: Long non-coding RNAs (lncRNAs) were detected extraordinarily expressed in various tumors and could combine with microRNAs (miRNAs) to play important role in tumor cells. This study is to explore the role of lncRNA RP11-909N17.2 in NSCLC and discuss in what way it functions in NSCLC. METHODS: 120 NSCLC patients were enlisted in this study. Expression levels of lncRNA RP11-909N17.2 and miR-767-3p were detected and the correlation between lncRNA RP11-909N17.2 expression and the clinical data characteristics was analyzed. Prognosis potential of lncRNA RP11-909N17.2 was inferred with Kaplan-Meier and multivariate Cox regression assays. Biological functions of NSCLC cells were accessed by cell counting Kit-8, transwell migration and invasion assay. Mechanism of RP11-909N17.2 action on NSCLC cells was investigated by luciferase activity assay with wide-type or mutation. RESULTS: LncRNA RP11-909N17.2 has an ascendant expression while miR-767-3p has descended one in NSCLC tissue specimens and cells. Over-expression of lncRNA RP11-909N17.2 can shorten the overall survival period of NSCLC patients when compared with low expression. Knockdown of lncRNA RP11-909N17.2 suppressed biology function of NSCLC cell including proliferation, migration, and invasion. CONCLUSION: LncRNA RP11-909N17.2 can be developed into a prognostic index for NSCLC. LncRNA RP11-909N17.2 plays a promoting role in NSCLC cells possibly by binding miR-767-3p as a sponge.

Overexpression of miR-25 is associated with progression and poor prognosis of cholangiocarcinoma.

Cholangiocarcinoma (CCA) is a rare but highly aggressive type of malignancy. MicroRNA (miR)-25 has been demonstrated to be involved in the genesis of numerous cancer types. The aim of the present study was to investigate the prognostic value and functional role of miR-25 in CCA. The expression of miR-25 was determined by reverse transcription-quantitative (RT-q)PCR. The association between miR-25 expression and clinicopathological features was analyzed using the χ2 test. Kaplan-Meier survival analysis and Cox linear regression were performed to explore the prognostic value of miR-25. The effects of miR-25 on the biological behavior of CCA cells were determined using loss-and gain-of-function experiments in CCA cell lines. Upregulated miR-25 expression was observed in CCA tissues and cell lines compared with that in the respective controls (all P<0.05). Patients with high expression of miR-25 in CCA tissues had a comparatively higher tumor-nodes-metastasis stage (P=0.026), a higher rate of lymph node metastasis (P=0.032) and a shorter overall survival rate (log-rank P=0.022). miR-25 was determined to be an independent prognostic factor for CCA patients (P=0.036). In vitro, transfection with miR-25 inhibitor suppressed cell viability, migration and invasion, while miR-25 mimics had the opposite effect. These results indicated that miR-25 functions as an oncogene and is involved in tumor progression in CCA. miR-25 may serve as a prognostic biomarker and a potential therapeutic target for CCA treatment.