2,666 research outputs found

    Serum Helicobacter pylori NapA antibody as a potential biomarker for gastric cancer

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    Helicobacter pylori (H. pylori) infection is strongly associated with gastric cancer. However, only a minority of infected individuals ever develop gastric cancer. This risk stratification may be in part due to differences among strains. The relationship between neutrophil-activating protein (NapA) and gastric cancer is unclear. The purpose of this study is to evaluate the significance of NapA as a biomarker in gastric cancer. We used enzyme linked immunosorbent assay (ELISA) to determine the status of H. pylori infection. Indirect ELISA method was used for detection of NapA antibody titer in the serum of H. pyloriinfected individuals. Unconditional logistic regressions were adopted to analyze the variables and determine the association of NapA and gastric cancer. The results of study indicated serum H. pylori NapA antibody level were associated with a reduced risk for development of gastric cancer. It may be used in conjugation with other indicators for gastric cancer detection

    TPQCI: A topology potential-based method to quantify functional influence of copy number variations

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    Copy number variation (CNV) is a major type of chromosomal structural variation that play important roles in many diseases including cancers. Due to genome instability, a large number of CNV events can be detected in diseases such as cancer. Therefore, it is important to identify the functionally important CNVs in diseases, which currently still poses a challenge in genomics. One of the critical steps to solve the problem is to define the influence of CNV. In this paper, we provide a topology potential based method, TPQCI, to quantify this kind of influence by integrating statistics, gene regulatory associations, and biological function information. We used this metric to detect functionally enriched genes on genomic segments with CNV in breast cancer and multiple myeloma and discovered biological functions influenced by CNV. Our results demonstrate that, by using our proposed TPQCI metric, we can detect disease-specific genes that are influenced by CNVs. Source codes of TPQCI are provided in Github (https://github.com/usos/TPQCI)

    A pan-kidney cancer study identifies subtype specific perturbations on pathways with potential drivers in renal cell carcinoma

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    Background: Renal cell carcinoma (RCC) is a complex disease and is comprised of several histological subtypes, the most frequent of which are clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (PRCC) and chromophobe renal cell carcinoma (ChRCC). While lots of studies have been performed to investigate the molecular characterizations of different subtypes of RCC, our knowledge regarding the underlying mechanisms are still incomplete. As molecular alterations are eventually reflected on the pathway level to execute certain biological functions, characterizing the pathway perturbations is crucial for understanding tumorigenesis and development of RCC. Methods: In this study, we investigated the pathway perturbations of various RCC subtype against normal tissue based on differential expressed genes within a certain pathway. We explored the potential upstream regulators of subtype-specific pathways with Ingenuity Pathway Analysis (IPA). We also evaluated the relationships between subtype-specific pathways and clinical outcome with survival analysis. Results: In this study, we carried out a pathway-based analysis to explore the mechanisms of various RCC subtypes with TCGA RNA-seq data. Both commonly altered pathways and subtype-specific pathways were detected. To identify the distinctive characteristics of each subtype, we focused on subtype-specific perturbed pathways. Specifically, we observed that some of the altered pathways were regulated by several recurrent upstream regulators which presenting different expression patterns among distinct RCC subtypes. We also noticed that a large number of perturbed pathways were controlled by the subtype-specific upstream regulators. Moreover, we also evaluated the relationships between perturbed pathways and clinical outcome. Prognostic pathways were identified and their roles in tumor development and progression were inferred. Conclusions: In summary, we evaluated the relationships among pathway perturbations, upstream regulators and clinical outcome for differential subtypes in RCC. We hypothesized that the alterations of common upstream regulators as well as subtype-specific upstream regulators work together to affect the downstream pathway perturbations and drive cancer initialization and prognosis. Our findings not only increase our understanding of the mechanisms of various RCC subtypes, but also provide targets for personalized therapeutic intervention

    Large-Scale Covariability Between Aerosol and Precipitation Over the 7-SEAS Region: Observations and Simulations

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    One of the seven scientific areas of interests of the 7-SEAS field campaign is to evaluate the impact of aerosol on cloud and precipitation (http://7-seas.gsfc.nasa.gov). However, large-scale covariability between aerosol, cloud and precipitation is complicated not only by ambient environment and a variety of aerosol effects, but also by effects from rain washout and climate factors. This study characterizes large-scale aerosol-cloud-precipitation covariability through synergy of long-term multi ]sensor satellite observations with model simulations over the 7-SEAS region [10S-30N, 95E-130E]. Results show that climate factors such as ENSO significantly modulate aerosol and precipitation over the region simultaneously. After removal of climate factor effects, aerosol and precipitation are significantly anti-correlated over the southern part of the region, where high aerosols loading is associated with overall reduced total precipitation with intensified rain rates and decreased rain frequency, decreased tropospheric latent heating, suppressed cloud top height and increased outgoing longwave radiation, enhanced clear-sky shortwave TOA flux but reduced all-sky shortwave TOA flux in deep convective regimes; but such covariability becomes less notable over the northern counterpart of the region where low ]level stratus are found. Using CO as a proxy of biomass burning aerosols to minimize the washout effect, large-scale covariability between CO and precipitation was also investigated and similar large-scale covariability observed. Model simulations with NCAR CAM5 were found to show similar effects to observations in the spatio-temporal patterns. Results from both observations and simulations are valuable for improving our understanding of this region's meteorological system and the roles of aerosol within it. Key words: aerosol; precipitation; large-scale covariability; aerosol effects; washout; climate factors; 7- SEAS; CO; CAM

    TPSC: a module detection method based on topology potential and spectral clustering in weighted networks and its application in gene co-expression module discovery

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    Background: Gene co-expression networks are widely studied in the biomedical field, with algorithms such as WGCNA and lmQCM having been developed to detect co-expressed modules. However, these algorithms have limitations such as insufficient granularity and unbalanced module size, which prevent full acquisition of knowledge from data mining. In addition, it is difficult to incorporate prior knowledge in current co-expression module detection algorithms. Results: In this paper, we propose a novel module detection algorithm based on topology potential and spectral clustering algorithm to detect co-expressed modules in gene co-expression networks. By testing on TCGA data, our novel method can provide more complete coverage of genes, more balanced module size and finer granularity than current methods in detecting modules with significant overall survival difference. In addition, the proposed algorithm can identify modules by incorporating prior knowledge. Conclusion: In summary, we developed a method to obtain as much as possible information from networks with increased input coverage and the ability to detect more size-balanced and granular modules. In addition, our method can integrate data from different sources. Our proposed method performs better than current methods with complete coverage of input genes and finer granularity. Moreover, this method is designed not only for gene co-expression networks but can also be applied to any general fully connected weighted network

    Quantitative Optical Coherence Tomography Angiography of Choroidal Neovascularization in Age-Related Macular Degeneration

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    Purpose To detect and quantify choroidal neovascularization (CNV) in patients with age-related macular degeneration (AMD) using optical coherence tomography (OCT) angiography. Design Observational, cross-sectional study. Participants A total of 5 normal subjects and 5 subjects with neovascular AMD were included. Methods A total of 5 eyes with neovascular AMD and 5 normal age-matched controls were scanned by a high-speed (100 000 A-scans/seconds) 1050-nm wavelength swept-source OCT. The macular angiography scan covered a 3×3-mm area and comprised 200×200×8 A-scans acquired in 3.5 seconds. Flow was detected using the split-spectrum amplitude-decorrelation angiography (SSADA) algorithm. Motion artifacts were removed by 3-dimensional (3D) orthogonal registration and merging of 4 scans. The 3D angiography was segmented into 3 layers: inner retina (to show retinal vasculature), outer retina (to identify CNV), and choroid. En face maximum projection was used to obtain 2-dimensional angiograms from the 3 layers. The CNV area and flow index were computed from the en face OCT angiogram of the outer retinal layer. Flow (decorrelation) and structural data were combined in composite color angiograms for both en face and cross-sectional views. Main Outcome Measures The CNV angiogram, CNV area, and CNV flow index. Results En face OCT angiograms of CNV showed sizes and locations that were confirmed by fluorescein angiography (FA). Optical coherence tomography angiography provided more distinct vascular network patterns that were less obscured by subretinal hemorrhage. The en face angiograms also showed areas of reduced choroidal flow adjacent to the CNV in all cases and significantly reduced retinal flow in 1 case. Cross-sectional angiograms were used to visualize CNV location relative to the retinal pigment epithelium and Bruch's layer and classify type I and type II CNV. A feeder vessel could be identified in 1 case. Higher flow indexes were associated with larger CNV and type II CNV. Conclusions Optical coherence tomography angiography provides depth-resolved information and detailed images of CNV in neovascular AMD. Quantitative information regarding CNV flow and area can be obtained. Further studies are needed to assess the role of quantitative OCT angiography in the evaluation and treatment of neovascular AMD.National Institutes of Health (U.S.) (Grant 1R01 EY023285-01)National Institutes of Health (U.S.) (Grant R01 EY013516)Rosenbaum's P30EY010572National Institutes of Health (U.S.) (Clinical and Translational Science Award Grant UL1TR000128)Research to Prevent Blindness, Inc. (United States) (Grant R01-EY11289-26)United States. Air Force Office of Scientific Research (FA9550-10-1-0551)German Research Foundation (DFG-HO-1791/11-1)German Research Foundation (DFG-GSC80-SAOT

    Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer

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    Background: Existing studies have demonstrated that the integrative analysis of histopathological images and genomic data can be used to better understand the onset and progression of many diseases, as well as identify new diagnostic and prognostic biomarkers. However, since the development of pathological phenotypes are influenced by a variety of complex biological processes, complete understanding of the underlying gene regulatory mechanisms for the cell and tissue morphology is still a challenge. In this study, we explored the relationship between the chromatin accessibility changes and the epithelial tissue proportion in histopathological images of estrogen receptor (ER) positive breast cancer. Methods: An established whole slide image processing pipeline based on deep learning was used to perform global segmentation of epithelial and stromal tissues. We then used canonical correlation analysis to detect the epithelial tissue proportion-associated regulatory regions. By integrating ATAC-seq data with matched RNA-seq data, we found the potential target genes that associated with these regulatory regions. Then we used these genes to perform the following pathway and survival analysis. Results: Using canonical correlation analysis, we detected 436 potential regulatory regions that exhibited significant correlation between quantitative chromatin accessibility changes and the epithelial tissue proportion in tumors from 54 patients (FDR < 0.05). We then found that these 436 regulatory regions were associated with 74 potential target genes. After functional enrichment analysis, we observed that these potential target genes were enriched in cancer-associated pathways. We further demonstrated that using the gene expression signals and the epithelial tissue proportion extracted from this integration framework could stratify patient prognoses more accurately, outperforming predictions based on only omics or image features. Conclusion: This integrative analysis is a useful strategy for identifying potential regulatory regions in the human genome that are associated with tumor tissue quantification. This study will enable efficient prioritization of genomic regulatory regions identified by ATAC-seq data for further studies to validate their causal regulatory function. Ultimately, identifying epithelial tissue proportion-associated regulatory regions will further our understanding of the underlying molecular mechanisms of disease and inform the development of potential therapeutic targets

    Replicating Elite Dominance in Intangible Cultural Heritage Safeguarding: The Role of Local Government–Scholar Networks in China

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    Since “intangible cultural heritage” (ICH) became the new focal point in the global heritage discourse, governments and scholars in many countries have begun to promote this new form of “immaterial” culture. The People’s Republic of China has been one of the most active state parties implementing the new scheme and adapting it to domestic discourses and practices. Policies formulated at the national level have become increasingly malleable to the interests of local government-scholar networks. By conducting a comparative case study of two provinces, this article aims to identify the role of local elite networks in the domestic implementation of the 2003 Convention for the Safeguarding of Intangible Cultural Heritage, focusing on the incentives of scholars and officials to participate in ICH policy networks. It finds that the implementation of the Convention has not removed the power asymmetry between elite and popular actors but, instead, has fostered an elite-driven policy approach shaped by symbiotic, mutually legitimizing government–scholar networks

    Peatland Heterogeneity Impacts on Regional Carbon Flux and Its Radiative Effect Within a Boreal Landscape

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    Peatlands, with high spatial variability in ecotypes and microforms, constitute a significant part of the boreal landscape and play an important role in the global carbon (C) cycle. However, the effects of this peatland heterogeneity within the boreal landscape are rarely quantified. Here, we use field-based measurements, high-resolution land cover classification, and biogeochemical and atmospheric models to estimate the atmosphere-ecosystem C fluxes and the corresponding radiative effect (RE) for a boreal landscape (Kaamanen) in northern Finland. Our result shows that the Kaamanen catchment currently functioned as a sink of carbon dioxide (CO2) and a source of methane (CH4). Peatlands (26% of the area) contributed 22% of the total CO2 uptake and 89% of CH4 emissions; forests (61%) accounted for 78% of CO2 uptake and offset 6% of CH4 emissions; water bodies (13%) offset 7% of CO2 uptake and contributed 11% of CH4 emissions. The heterogeneity of peatlands accounted for 11%, 88%, and 75% of the area-weighted variability (deviation from the area-weighted mean among different land cover types (LCTs) within the catchment) in CO2 flux, CH4 flux, and the combined RE of CO2 and CH4 exchanges over the 25-year time horizon, respectively. Aggregating peatland LCTs or misclassifying them as nonpeatland LCTs can significantly (p < 0.05) bias the regional CH4 exchange and RE estimates, while differentiating between drier noninundated and wetter inundated peatlands can effectively reduce the bias. Current land cover products lack such details in peatland heterogeneity, which would be needed to better constrain boreal C budgets and global C-climate feedbacks. Plain Language Summary Peatlands form part of the boreal landscapes exhibiting diverse types and microforms that have different characteristics of topography, hydrology, vegetation, and soil. Our understanding is still limited concerning how boreal peatlands, especially their inherent heterogeneities, affect the regional biosphere-atmosphere exchange of carbon and related climate effects, and what level of detail is needed to characterize them in land cover maps. By combining remote sensing information, field measurements, and biogeochemical modeling, we showed that, among different land cover types, peatlands played a dominant role in the variability of methane (CH4) flux (88%) and the combined radiative climate effect due to carbon dioxide and CH4 exchanges (75% over the 25-year time horizon). Possible aggregation and misclassification of peatland types could induce significant biases in the regional CH4 balances and radiative effect estimates, but the distinction of noninundated drier and inundated wetter peatland types could reduce these biases effectively.Peer reviewe