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Background Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear. Methods Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset. Results A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours. Conclusion Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

Aim: To characterize the epidemiology of appendiceal mucinous adenocarcinoma. Methods: Prognostic factors were evaluated with univariate and multivariate analyses. The results were used to generate a nomogram. Results: The incidence of appendiceal mucinous adenocarcinoma showed a significant upward trend. Multivariate Cox analysis identified 11 independent prognostic factors. The nomogram was based on independent risk factors that were significant in multivariate Cox analysis, and the concordance-index for overall survival and cancer-specific survival were 0.76 (95% CI: 0.71–0.79) and 0.74 (95% CI: 0.70–0.79), respectively. Conclusion: Advanced age, single relationship status, male sex, black race, the presence of distant and regional lymph node metastases, poor differentiation or lack of differentiation, advanced SEER extent of disease, cancer-directed surgery and chemotherapy were independently associated with prognosis.

The purpose of this study is to analyze the DNA methylation and gene expression profiles of immune-related CpG sites to identify the molecular subtypes and CpG sites related to the prognosis of HCC. In this study, the DNA methylation and gene expression datasets were downloaded from The Cancer Genome Atlas database, together with immune-related genes downloaded from the immunology database and analysis portal database to explore the prognostic molecular subtypes of HCC. By performing consistent clustering analysis on 830 immune-related CpG sites, we identified seven subgroups with significant differences in overall survival. Finally, 16 classifiers of immune-related CpG sites were constructed and used in the testing set to verify the prognosis of DNA methylation subgroups, and the results were consistent with the training set. Using the TIMER database, we analyzed 16 immune-related CpG sites expression with the abundance of six types of immune infiltrating cells and found that most are positively correlated with the level of infiltration of multiple immune cells in HCC. This study screened potential immune-related prognostic methylation sites and established a new prognosis model of HCC based on DNA methylation molecular subtype, which may help in the early diagnosis of HCC and developing more effective personalized treatments.

Background: The combination of epigenetic drugs and immunotherapy should be able to develop an optimal treatment plan for hepatocellular carcinoma (HCC), yet its mechanism is still in the preliminary exploration stage. The purpose of this study is to analyze the DNA methylation and gene expression profiles of immune-related CpG sites to identify the molecular subtypes and CpG sites related to the prognosis of HCC. Methods: In this study, the DNA methylation and gene expression datasets were downloaded from The Cancer Genome Atlas database, together with immune-related genes downloaded from the immunology database and analysis portal database to explore the prognostic molecular subtypes of HCC. Univariate and multivariate survival analysis was used for selecting the significant methylation sites, and the consensus clustering was performed to find the best molecular subtype associated with the survival of HCC. Next, we used the least absolute shrinkage and selection operator (LASSO) algorithm to construct a prognostic-related model and performed internal verification. Finally, we explored the levels of 16 immune-related genes expression correlate with the infiltration levels of immune cells in HCC. Results: By performing consistent clustering analysis on 830 immune-related CpG sites in 231 samples of a training set, we identified seven subgroups with significant differences in overall survival. Finally, 16 classifiers of immune-related CpG sites were constructed and used in the testing set to verify the prognosis of DNA methylation subgroups, and the results were consistent with the training set. Using the TIMER database, we analyzed 16 immune-related CpG sites expression with the abundance of six types of immune infiltrating cells and found that most are positively correlated with the level of infiltration of multiple immune cells in HCC. Conclusions: This study screened potential immune-related prognostic methylation sites and established a new prognosis model of HCC based on DNA methylation molecular subtype, which may help in the early diagnosis of HCC and developing more effective personalized treatments.

Background Chinese herbal injections (CHIs) have been proven beneficial to patients with non-small cell lung cancer (NSCLC) in combination with chemotherapy. The network meta-analysis (NMA) was designed to update and expand on previous work to better evaluate the effectiveness and safety of different Yiqi Fuzheng (YQFZ) CHIs combined with the Vinorelbine plus cisplatin (NP) regimen versus NP alone for NSCLC. Methods We searched multiple electronic databases and identified randomized controlled trials (RCTs) concerning different YQFZ CHIs combined with the NP regimen for treating NSCLC up to March 1st, 2019. The outcomes are the objective response rate, performance status and adverse reactions (ADRs). Two individuals accomplished the quality assessment of this NMA based on the Cochrane risk of bias tool and the methodological section of the CONSORT statement. Random effects models were generated to estimate efficacy and safety outcomes. Odds ratios and corresponding 95% confidence intervals were calculated via Stata 14 software. Furthermore, the rankings for the efficacy and safety of different YQFZ CHIs for each outcome were determined by the surface under the cumulative ranking curve (SUCRA). Results Initially, a total of 4775 citations were retrieved through comprehensive searching, and 88 eligible articles involving 6695 participants and 8 CHIs were ultimately included. The cluster analysis results of the current evidence indicated that the NP regimen combined with Delisheng, Shenfu and Shenmai injections have a higher clinical effectiveness rate and better performance status compared with the NP regimen alone. Additionally, the NP regimen combined with Shenqifuzheng, Shengmai and Shenfu injections may be considered a favorable choice for reliving ADRs among patients with NSCLC. Conclusions The current evidence demonstrated that the combination of Shenfu injection plus NP regimen could produce better outcomes than other YQFZ CHIs groups in terms of efficacy and safety. However, meticulously designed, strictly executed, high-quality trials are still required to further assess and confirm the results due to the inadequacy of the included RCTs.

Because angle-domain common-image gathers (ADCIGs) from reverse time migration (RTM) are capable of obtaining the correct illumination of a subsurface geologic structure, they provide more reliable information for velocity model building, amplitude-variation versus angle analysis, and attribute interpretation. The approaches for generating ADCIGs mainly consist of two types: (1) indirect approaches that convert extended image gathers into ADCIGs and (2) direct approaches that first obtain propagating angles of wavefronts and then map the imaging result to the angle domain. In practice, however, generation of ADCIGs usually incurs high computational cost, poor resolution, and other drawbacks. To generate efficient ADCIGs using RTM methods, we have introduced a novel approach to obtain polarization vectors — directions of particle motion — from the Cauchy wavefield (CWF) and an efficient localized plane-wave decomposition algorithm to implement the angle-domain imaging condition. The CWF is a wavefield constructed from the Cauchy condition of the wave equation at any given time, and it only contains negative frequencies of the original wavefield so that the polarization vector is obtained from the local CWF in the wavenumber domain. With polarization vectors at our disposal, we have further developed an efficient localized plane-wave decomposition algorithm to implement the angle-domain imaging condition. Numerical examples have indicated that the new approach is able to handle complex wave phenomenon and has advantages in illuminating subsurface structure.

Angle-domain common imaging gathers (ADCIGs) are important input data for migration velocity analysis and amplitude variation with angle analysis. Compared with Kirchhoff migration and one-way wave equation migration, reverse time migration (RTM) is the most accurate imaging method in complex areas, such as the subsalt area. We have developed a method to generate ADCIGs from RTM using analytic wavefield propagation and decomposition. To estimate the wave-propagation direction and angle by spatial Fourier transform during the time domain wave extrapolation, we have developed an analytic wavefield extrapolation method. Then, we decomposed the extrapolated source and receiver wavefields into their local angle components (i.e., local plane-wave components) and applied the angle-domain imaging condition to form ADCIGs. Because the angle-domain imaging condition is a convolution imaging condition about the source and receiver propagation angles, it is costly. To increase the efficiency of the angle-domain imaging condition, we have developed a local plane-wave decomposition method using matching pursuit. Numerical examples of synthetic and real data found that this method could generate high-quality ADCIGs. And these examples also found that the computational cost of this approach was related to the complexity of the source and receiver wavefields.

Summary The quality beam-forming is very important for beam prestack depth migration. Traditionally, the beam is formed by local Tau-P transform. In this paper, a new beam forming method using a locally windowed wave field is presented. This method uses the least square inversion with the Radon spectrum constraints, which makes the estimated beam with higher resolution than the traditional local Tau-P transform. The energy in the local Radon transform domain stands for the probability of the direction of a beam, which can be used as a priori information to constraint the inversion procedure to make the result more reliable. As the energy of Radon spectrum is insensitive to the random noise, this constraint may result in strong random noise suppression and robustness. And the constraint is helpful to enhance the resolution of the beam forming. Therefore, the Radon spectrum constrained least square inversion can yield a high resolution beam with better noise suppression. The numerical examples on both the synthetic and field dataset demonstrate the feasibility of this method.

Summary A new approach of local time-frequency decomposition is presented, which has high resolution in both time and frequency domain and can represent a signal more sparsely. Seismic data usually belongs to the class of nonstationary signal, so it’s more logical to process the data in timefrequency domain. It’s all known that windowed Fourier transforms (WFT) and wavelet transforms (WT) are two important classes of local time-frequency decompositions, but they can’t have a set of basis whose energy is highly localized in both time and frequency, because of the Heisenberg uncertainty principle. The method introduced here conquers this shortcoming. It is deduced under the framework of inverse problem theory and model parameter estimation methods, with the help of windowed Fourier transforms. The numerical examples demonstrate its advantages and effectiveness.

Summary The efficiency of common shot migration can be greatly enhanced by coding migration scheme. However, coding migration scheme introduces the crosstalk noise which can degrade the quality of migration images. In this paper, we present a matrix representation for both frequency dependent coding migration and frequency independent coding migration. A new coding scheme called frequency grouping coding scheme is presented by analyzing the matrix representation. This coding migration scheme makes use of the wavefield similarity of the adjacent frequency to suppress the crosstalk introduced by coding migration scheme. Conventionally, the crosstalk suppression is conducted on a single coding correlation matrix or a single frequency coding correlation matrix. However, this method uses the summation of multi coding correlation matrixes to suppress the corsstalk. This coding scheme could either be used as a single-experiment strategy or a multi-experiments strategy. Numerical tests prove the feasibility of this coding scheme.

Kirchhoff integral migration is widely used in 3-D data processing. However, it is assumed that the acquisition geometry is regular. In fact, the acquisition geometry is, in most cases, irregular. Therefore, Kirchhoff integral migration formula will give wrong imaging amplitude. The distorted amplitude may mislead the AVO analysis and confuse the interpretation. In order to reduce the footprint caused by the irregular acquisition, a topologic transformation is introduced implicitly to change the irregular acquisition into a regular one by adjusting the weighting function of Kirchhoff pre-stack migration formula. Numerical Examples demonstrate that the approach is simple and effective for reducing the acquisition footprint.