Insights into priming effects of dissolved organic matter degradation in urban lakes with different trophic states.

Priming effect (PE) is recognized as an important potential mechanism for dissolved organic matter (DOM) degradation in aquatic ecosystems. However, the priming effects (PEs) of various priming substances on the degradation of DOM pools in urban lakes along diverse trophic states remain unknown. To address this knowledge gap, the PEs and drivers of glucose and plant leachate of lake water with three trophic states were investigated. We reveal differences in the bioavailability of DOM in lake water, glucose, and plant leachate. The PE of the same priming substance was significantly higher in highly-eutrophic lake water than in mesotrophic lake. The priming intensity induced by glucose was significantly higher when compared to plant leachate. Regarding the addition of glucose, humic-like components (C1 and C3) showed slight PE, while the tyrosine-like component C2 showed negative PE. However, the positive PEs were observed on three components after adding plant leachate. The driver of PE by glucose shifted from nutrients to DOM components with increasing trophic levels. The PEs induced by plant leachate were affected by nutrients, chlorophyll-a (Chl-a), water chemistry, and DOM components in lightly/moderately-eutrophic lake water. This study revealed the intensities, directions, and drivers of PEs, providing essential insights into uncovering the DOM biogeochemical process in urban lakes.

H/D Exchange Coupled with 2H-labeled Stable Isotope-Assisted Metabolomics Discover Transformation Products of Contaminants of Emerging Concern.

Stable isotope-assisted metabolomics (SIAM) is a powerful tool for discovering transformation products (TPs) of contaminants. Nevertheless, the high cost or lack of isotope-labeled analytes limits its application. In-house H/D (hydrogen/deuterium) exchange reactions enable direct 2H labeling to target analytes with favorable reaction conditions, providing intuitive and easy-to-handle approaches for environmentally relevant laboratories to obtain cost-effective 2H-labeled contaminants of emerging concern (CECs). We first combined the use of in-house H/D exchange and 2H-SIAM to discover potential TPs of 6PPD (N-1,3-dimethylbutyl-N'-phenyl-p-phenylenediamine), providing a new strategy for finding TPs of CECs. 6PPD-d9 was obtained by in-house H/D exchange with favorable reaction conditions, and the impurities were carefully studied. Incomplete deuteride, for instance, 6PPD-d8 in this study, constitutes a major part of the impurities. Nevertheless, it has few adverse effects on the 2H-SIAM pipeline in discovering TPs of 6PPD. The 2H-SIAM pipeline annotated 9 TPs of 6PPD, and commercial standards further confirmed the annotated 6PPDQ (2-anilino-5-(4-methylpentan-2-ylamino)cyclohexa-2,5-diene-1,4-dione) and PPPD (N-phenyl-p-phenylenediamine). Additionally, a possible new formation mechanism for 6PPDQ was proposed, highlighting the performance of the strategy. In summary, this study highlighted a new strategy for discovering the TPs of CECs and broadening the application of SIAM in environmental studies.

Changes in CO2 concentration and degassing of eutrophic urban lakes associated with algal growth and decline.

Urban lakes are numerous in the world, but their role in carbon storage and emission is not well understood. This study aimed to answer the critical questions: How does algal growing season influence carbon dioxide concentration (cCO2) and exchange flux (FCO2) in eutrophic urban lakes? We investigated trophic state, seasonality of algal productivity, and their association with CO2 dynamics in four urban lakes in Central China. We found that these lightly-to moderately-eutrophic urban lakes showed a shifting pattern of CO2 source-sink dynamics. In the non-algal bloom phase, the moderately-eutrophic lakes outgassed on average of 12.18 ± 24.37 mmol m-2 d-1 CO2; but, during the algal bloom phase, the lakes sequestered an average 1.07 ± 6.22 mmol m-2 d-1 CO2. The lightly-eutrophic lakes exhibited lower CO2 emission in the algal bloom (0.60 ± 10.24 mmol m-2 d-1) compared to the non-algal bloom (3.84 ± 12.38 mmol m-2 d-1). Biological factors such as Chl-a (chlorophyll a) and AOU (apparent oxygen utilization), were found to be important factors to potentially affect the shifting pattern of lake CO2 source-sink dynamics in moderately-eutrophic lakes, explaining 48% and 34% of the CO2 variation in the non-algal and algal bloom phases, respectively. Moreover, CO2 showed positive correlations with AOU, and negative correlations with Chl-a in both phases. In the lightly-eutrophic lakes, biological factors explained a higher proportion of CO2 variations (29%) in the non-algal bloom phase, with AOU accounting for 19%. Our results indicate that algal growth and decline phases largely affect dissolved CO2 level and exchange flux by regulating in-lake respiration and photosynthesis. Based on the findings, we conclude that shallow urban lakes can act as both sources and sinks of CO2, with algal growth seasonality and trophic state playing pivotal roles in controlling their carbon dynamics.

Source and quality of dissolved organic matter in streams are reflective to land use/land cover, climate seasonality and pCO2.

Sources and quality of dissolved organic matter (DOM) in streams may be largely controlled by the landscape and season. In this study, we attempted to answer three critical questions: 1) Do land use/land cover (LULC) types affect DOM characteristics? 2) Is there a seasonal fluctuation in DOM components? 3) How do DOM quality and LULC types influence aqueous carbon dioxide partial pressure (pCO2). To achieve this, we investigated the fluorescence characteristics of DOM and its implication for pCO2 in three streams draining land with different urban intensities under distinctive dry and wet seasons. Four fluorescence components were identified, including two terrestrial humic-like components, one protein-like component and one microbial humic-like component. We found a significant positive relationship of the maximum fluorescence intensity (Fmax) of the four components and fluorescence index (FI370) with urbanization intensity in both the dry and wet seasons. The mean Fmax, biological index (BIX) and FI370 all exhibited an increasing trend from upstream to downstream in the stream with highest proportions of urban and cropland. The fluorescence characteristics were negatively related to proportion of forested land in the both seasons. The terrestrial humic-like DOM was dominating in the studied streams. Moreover, the seasonality altered the DOM composition, with protein-like component emerging only in stream waters during the dry season, while microbial humic-like component exclusively occurred during the wet season. pCO2 values were positively related to terrestrial humic-like and biological protein-like components, and urban land. The dry season had much higher pCO2 than the wet season. Results from the Partial Least Squares Path (PLS-PM) models further indicated that LULC types were important in mediating fluorescence DOM whilst pCO2 was more sensitive to the direct effect from FDOM dynamics. We conclude that DOM source and quality in streams are reflective to LULC and climate seasonality, and are good indicators of pCO2 via source tracer and quality of fluorescence components.

Intense methane diffusive emissions in eutrophic urban lakes, Central China.

Urban lakes are hotspots of methane (CH4) emissions. Yet, actual field measurements of CH4 in these lakes are rather limited and our understanding of CH4 response to urban lake eutrophication is still incomplete. In this study, we measured dissolved CH4 concentrations and quantified CH4 diffusion from four urban lakes in subtropical China during wet and dry seasons. We found that these lakes were constantly CH4-saturated, contributing the greenhouse gas (GHG) to the atmosphere. Nutrient enrichment significantly increased CH4 concentrations and diffusive fluxes. Average CH4 flux rate in the highly-eutrophic lake zones (4.18 ± 7.68 mmol m-2 d-1) was significantly higher than those in the mesotrophic (0.19 ± 0.18 mmol m-2 d-1) and lightly/moderately-eutrophic zones (0.72 ± 2.22 mmol m-2 d-1). Seasonally, CH4 concentrations and fluxes were significantly higher in the wet season than in the dry season in the mesotrophic and the lightly/moderately-eutrophic lake zones, but an inverse pattern existed in the highly-eutrophic lake zones. CH4 concentrations and fluxes increased with elevated levels of nitrogen, phosphorus and dissolved organic carbon (DOC). The accumulation of nutrients provided autochthonous substrate for methanogenesis, indicated by a negative correlation between CH4 and the C:N ratio. Ammonium-nitrogen (NH4+-N) was the best predictor for spatial fluctuation of CH4 concentrations and diffusive fluxes in the mesotrophic and the lightly/moderately-eutrophic lake zones, while total nitrogen (TN) and total phosphorus (TP) levels showed the highest predictability in the highly-eutrophic lake zones. Based on the findings, we conclude that nutrient enrichment in urban lakes can largely increase CH4 diffusion, and that urban sewage inflow is a key concern for eutrophication boosting CH4 production and diffusive emission. Furthermore, our study reveals that small urban lakes may be an important missing source of GHG emissions in the global C accounting, and that the ratio of littoral-to-pelagic zones can be important for predicting lake-scale estimation of CH4 emission.

Riverine nitrate source and transformation as affected by land use and land cover.

A mixed land use/land cover (LULC) catchment increases the complexity of sources and transformations of nitrate in rivers. Spatial paucity of sampling particularly low-resolution sampling in tributaries can result in a bias for identifying nitrate sources and transformations. In this study, high spatial resolution sampling campaigns covering mainstream and tributaries in combination with hydro-chemical parameters and dual isotopes of nitrate were performed to reveal spatio-temporal variations of nitrate sources and transformations in a river draining a mixed LULC catchment. This study suggested that point sources dominated the nitrate in the summer and winter, while non-point sources dominated the nitrate in the spring and autumn. A positive correlation was observed between proportions from sewage and land use index (LUI). However, negative correlations between soil nitrogen/nitrogen fertilizer and LUI were observed. With an increase of urban areas, the increased contribution from domestic sewage resulted in an increase of NO3- concentrations in rivers. Both urban and agricultural inputs should be considered in nitrate pollution management in a mixed LULC catchment. We concluded that the seasonal variations of nitrate sources were mainly affected by flow velocity conditions and agricultural activities, while spatial variations were mainly affected by LULC. In addition, we found a novel underestimation of dominated sources from Bayesian model because of mixing effect of isotope values from the tributaries to mainstream, however, high spatial resolution sampling can make up for this shortcoming. δ15N and δ18O values of nitrate indicated that nitrate originated from nitrification in soils. The nitrate concentrations and correlation between δ15N and 1/[NO3-] suggested little contribution of nitrate removal by denitrification. Thus, the nitrate reduction in the Yuehe River basin needs to be strengthened. The study provides new implications for estimation of nitrate sources and transformations and basis for nitrate reduction in the river with mixed LULC catchment.

Qualitative and quantitative studies on chemical constituents of Ling-gui-zhu-gan decoction: In vitro and in vivo.

Ling-gui-zhu-gan decoction has significant therapeutic effects in the treatment of diseases related to phlegm and fluid retention. In this study, we aimed to qualitatively characterize the chemical constituents of Ling-gui-zhu-gan decoction in vitro and in vivo by HPLC coupled to Fourier transform ion cyclotron resonance MS, and quantitively determine the contents of typical chemical constituents by HPLC method. As a result, a total of 75 chemical constituents were discovered including 37 flavonoids and their glycosides, 20 saponins, 9 sterols, 3 organic acids and their derivatives, 3 lactones, 2 coumarins, and 1 alcohol. Among them, 17 chemical constituents were specifically identified. Subsequently, an HPLC method was established for simultaneous determination of seven chemical constituents. Finally, a total of 40 prototype components were initially detected by HPLC-MS method in the biological samples of rats after their water extract was orally administrated. Among them, 29, 27, 12, and 32 prototype components were detected in plasma, bile, urine, and feces, respectively. Moreover, 34 metabolites, including 16 phase II metabolites, were detected for the first time. In conclusion, this study lays the foundation for the identification of chemical components in vitro and in vivo and the elucidation of the potential pharmacodynamic components of Ling-gui-zhu-gan decoction.

Ultraviolet humic-like component contributes to riverine dissolved organic matter biodegradation.

Biological degradation of dissolved organic matter (DOM) regulates its structure and fate in river ecosystems. Previous views suggested that labile components were dominantly consumed by microbial metabolism. Here we provide new observations that a part of recalcitrant compounds largely contribute to riverine DOM biodegradation. The excitation-emission matrix fluorescent spectroscopy combined with peak picking and parallel factor analysis are used to explore component variability during DOM incubation. Humic-like and tryptophan-like DOM are the primary components of riverine DOM, with proportion contributions of 39%-82% and 16%-61% for % of the maximum fluorescence intensity, respectively. After 56 days of aerobic incubation in the dark, large amounts of tyrosine-like DOM generation are observed. Elevated temperature enhances the decomposition of ultraviolet humic-like substance and further stimulates labile DOM bio-mineralization into carbon dioxide. Meanwhile, averaged proportions of amino acid compositions (peak B and T) markedly increase (p < 0.05) as the humic-like compositions (peak A, M and C) decrease after DOM incubation, suggesting incomplete degradation of refractory DOM from high-molecular to low-molecular weight compounds. The findings support the new notion of the continuous DOM biodegradation in a mode as "steps by steps", contributing to a new understanding of carbon cycling for the UN Sustainable Development Goal.

Riverine dissolved organic matter (DOM) as affected by urbanization gradient.

Rapid urbanization has considerably altered carbon biogeochemical cycle and river hydrology. However, the influences of urban land use and urban-induced nutrient increase on dissolved organic matter (DOM) characteristics are poorly understood. Here we hypothesize that the alterations significantly change sources and levels of DOM in river systems that drain the urban areas. To test the hypothesis, we investigated DOM in headwater rivers with varied urban intensities in the Three Gorges Reservoir Area (TGRA), China, through field sampling conducted in the dry and wet seasons. We found positive relationships of urban land (%Urban) with DOC concentration and chromophoric DOM (CDOM) absorption coefficients a254, a280 and a350, as well as fluorescence index (FI370), indicating the significantly increased levels of DOM and autochthonous sources along an urbanization gradient. A stepwise regression analysis demonstrated that occurrences of DOC and CDOM can be predicted by %Urban, while increasing autochthonous source is predictable by the increase in riverine nitrogen. Moreover, a254, a280 and FI370 values showed distinct seasonal variations, with significantly higher CDOM concentration in the wet season and with much higher autochthonous signal in the dry season with high nitrogen loading. Based on the findings, we conclude that urbanization influences occurrences and sources of DOM, with increasing urbanization making an important and direct contribution to DOM, and an indirect effect of urban induced nutrient enrichment, i.e., enhanced nutrient loadings increase autochthonous DOM production in rivers.

Understanding the Association between Online Social Support Obtainment and Coping during a Public Crisis.

This study aims to examine how the process of online support obtainment may affect cognitive and behavioral coping during a public crisis. A cross-sectional online survey (N = 555) was conducted during the early stage of the COVID-19 pandemic in the U.S. Our findings revealed that informational support, obtained primarily through passive and private online involvement, led to increased risk perceptions of COVID-19; emotional support, obtained mainly via private online involvement, appeared to elicit higher perceived efficacy to cope with the crisis. People's engagement in preventive behaviors was found to be affected by efficacy perceptions, but not by risk perceptions. The results suggested that online social support functioned as a double-edged sword to affect people's coping with a public crisis.

Anthropogenic land use substantially increases riverine CO2 emissions.

Carbon dioxide (CO2) emissions from inland waters to the atmosphere are a pivotal component of the global carbon budget. Anthropogenic land use can influence riverine CO2 emissions, but empirical data exploring cause-effect relationships remain limited. Here, we investigated CO2 partial pressures (pCO2) and degassing in a monsoonal river (Yue River) within the Han River draining to the Yangtze in China. Almost 90% of river samples were supersaturated in CO2 with a mean ± standard deviation of 1474 ± 1614 µatm, leading to emissions of 557 - 971 mmol/m2/day from river water to the atmosphere. Annual CO2 emissions were 1.6 - 2.8 times greater than the longitudinal exports of riverine dissolved inorganic and organic carbon. pCO2 was positively correlated to anthropogenic land use (urban and farmland), and negatively correlated to forest cover. pCO2 also had significant and positive relationships with total dissolved nitrogen and total dissolved phosphorus. Stepwise multiple regression models were developed to predict pCO2. Farmland and urban land released nutrients and organic matter to the river system, driving riverine pCO2 enrichment due to enhanced respiration in these heterotrophic rivers. Overall, we show the crucial role of land use driving riverine pCO2, which should be considered in future large-scale estimates of CO2 emissions from streams. Land use change can thus modify the carbon balance of urban-river systems by enhancing river emissions, and reforestation helps carbon neutral in rivers.

Identification of a prognostic signature of epithelial ovarian cancer based on tumor immune microenvironment exploration.

This study aims to develop an immune-related genes (IRGs) prognostic signature to stratify the epithelial ovarian cancer (EOC) patients. We identified 332 up- and 154 down-regulated EOC-specific IRGs. As a result, candidate IRGs were idendified to construct prognostic models respectivy for overall survial and progression-free survival. The risk score was validated as a risk factor for prognosis and was used to built a combined nomogram. According to the IRG-related prognostic model, EOC patients were divided into high- and low- risk group and were further explored their association with tumor immune microenvironment (TME). CIBERSORT algorithm showed higher macrophages M1 cell, T cells follicular helper cell and plasma cells infiltrating levels in the low-risk group. In addition, the low-risk group was found with higher immunophenoscore and distinct mutation signatures compared with the high-risk group. These findings may shed light on the development of novel immune biomarkers and target therapy of EOC.

Exploration of a novel prognostic risk signatures and immune checkpoint molecules in endometrial carcinoma microenvironment.

In this study, we devoted to investigate immune-related genes and tumor microenvironment (TME) in EC based on The Cancer Genome Atlas (TCGA) database. In total 799 up-regulated and 139 down-regulated immune-related and differentially expressed genes in EC were investigated for functional annotations and prognosis. By a conjoint Cox regression analysis, we built two risk models for OS and DFS, as well as the consistent nomograms. Immune-related pathways were revealed mostly enriched in the low-risk group. By further analyzing TME based on the risk signatures, the higher immune cell infiltration and activation, lower tumor purity and higher tumor mutational burden were found in low-risk group, which presented a better prognosis. Both the expression and immunophenoscore of immune checkpoints PD-1, CTLA4, PD-L1 and PD-L2 increased significantly in low-risk group. These findings may provide new ideas for novel biomarkers and immunotherapy targets in EC.

A Study on the Failure Behavior of Sand Grain Contacts with Hertz Modeling, Image Processing, and Statistical Analysis.

The crushing behavior of particles is encountered in a large number of natural and engineering systems, and it is important for it to be examined in problems related to hydraulic fracturing, where proppant-proppant and proppant-rock interactions are essential to be modeled as well as geotechnical engineering problems, where grains may crush because the transmitted stresses at their contacts exceed their tensile strength. Despite the interest in the study of the crushing behavior of natural particles, most previous experimental works have examined the single-grain or multiple-grain crushing configurations, and less attention has been given in the laboratory investigation of the interactions of two grains in contact up to their failure as well as on the assessment of the methodology adopted to analyze the data. In the present study, a quartz sand of 1.18-2.36 mm in size was examined, performing a total of 244 grain-to-grain crushing tests at two different speeds, 0.01 and 1 mm/min. In order to calculate stresses from the measured forces, Hertz modeling was implemented to calculate an approximate contact area between the particles based on their local radii (i.e., the radius of the grains in the vicinity of their contact). Based on the results, three different modes of failure were distinguished as conservative, fragmentary, and destructive, corresponding to micro-scale, meso-scale, and macro-scale breakage, respectively. From the data, four different classes of curves could be identified. Class-A and class-B corresponded to an initially Hertzian behavior followed by a brittle failure with a distinctive (single) peak point. The occurrence of hardening prior to the failure point distinguished class-B from class-A. Two additional classes (termed as class-C and class-D) were observed having two or multiple peaks, and much larger displacements were necessary to mobilize the failure point. Hertz fitting, Weibull statistics, and clustering were further implemented to estimate the influence of local radius and elastic modulus values. One of the important observations was that the method of analysis adopted to estimate the local radius of the grains, based on manual assessment (i.e., eyeball fitting) or robust Matlab-based image processing, was a key factor influencing the resultant strength distribution and m-modulus, which are grain crushing strength characteristics. The results from the study were further compared with previously reported data on single- and multiple-grain crushing tests.

Establishment of a novel cell cycle-related prognostic signature predicting prognosis in patients with endometrial cancer.

BACKGROUND: Endometrial cancer (EnCa) ranks fourth in menace within women's malignant tumors. Large numbers of studies have proven that functional genes can change the process of tumors by regulating the cell cycle, thereby achieving the goal of targeted therapy. METHODS: The transcriptional data of EnCa samples obtained from the TCGA database was analyzed. A battery of bioinformatics strategies, which included GSEA, Cox and LASSO regression analysis, establishment of a prognostic signature and a nomogram for overall survival (OS) assessment. The GEPIA and CPTAC analysis were applied to validate the dysregulation of hub genes. For mutation analysis, the "maftools" package was used. RESULTS: GSEA identified that cell cycle was the most associated pathway to EnCa. Five cell cycle-related genes including HMGB3, EZH2, NOTCH2, UCK2 and ODF2 were identified as prognosis-related genes to build a prognostic signature. Based on this model, the EnCa patients could be divided into low- and high-risk groups, and patients with high-risk score exhibited poorer OS. Time-dependent ROC and Cox regression analyses revealed that the 5-gene signature could predict EnCa prognosis exactly and independently. GEPIA and CPTAC validation exhibited that these genes were notably dysregulated between EnCa and normal tissues. Lower mutation rates of PTEN, TTN, ARID1A, and etc. were found in samples with high-risk score compared with that with low-risk score. GSEA analysis suggested that the samples of the low- and high-risk groups were concentrated on various pathways, which accounted for the different oncogenic mechanisms in patients in two groups. CONCLUSION: The current research construct a 5-gene signature to evaluate prognosis of EnCa patients, which may innovative clinical application of prognostic assessment.

Nine glycolysis-related gene signature predicting the survival of patients with endometrial adenocarcinoma.

BACKGROUND: Endometrial cancer is the fourth most common cancer in women. The death rate for endometrial cancer has increased. Glycolysis of cellular respiration is a complex reaction and is the first step in most carbohydrate catabolism, which was proved to participate in tumors. METHODS: We analyzed the sample data of over 500 patients from TCGA database. The bioinformatic analysis included GSEA, cox and lasso regression analysis to select prognostic genes, as well as construction of a prognostic model and a nomogram for OS evaluation. The immunohistochemistry staining, survival analysis and expression level validation were also performed. Maftools package was for mutation analysis. GSEA identified Glycolysis was the most related pathway to EC. qRT-PCR verified the expression level of hub gene in clinical samples. RESULTS: According to the prognostic model using the train set, 9 glycolysis-related genes including B3GALT6, PAM, LCT, GMPPB, GLCE, DCN, CAPN5, GYS2 and FBP2 were identified as prognosis-related genes. Based on nine gene signature, the EC patients could be classified into high and low risk subgroups, and patients with high risk score showed shorter survival time. Time-dependent ROC analysis and Cox regression suggested that the risk score predicted EC prognosis accurately and independently. Analysis of test and train sets yielded consistent results A nomogram which incorporated the 9-mRNA signature and clinical features was also built for prognostic prediction. Immunohistochemistry staining and TCGA validation showed that expression levels of these genes do differ between EC and normal tissue samples. GSEA revealed that the samples of the low-risk group were mainly concentrated on Bile Acid Metabolism. Patients in the low-risk group displayed obvious mutation signatures compared with those in the high-risk group. The expression levels of B3GALT6, DCN, FBP2 and GYS2 are lower in tumor samples and higher in normal tissue samples. The expression of CAPN5 and LCT in clinical sample tissues is just the opposite. CONCLUSION: This study found that the Glycolysis pathway is associated with EC and screened for hub genes on the Glycolysis pathway, which may serve as new target for the treatment of EC.

Identification of molecular markers associated with the progression and prognosis of endometrial cancer: a bioinformatic study.

BACKGROUND: Endometrial cancer (EC) is one kind of women cancers. Bioinformatic technology could screen out relative genes which made targeted therapy becoming conventionalized. METHODS: GSE17025 were downloaded from GEO. The genomic data and clinical data were obtained from TCGA. R software and bioconductor packages were used to identify the DEGs. Clusterprofiler was used for functional analysis. STRING was used to assess PPI information and plug-in MCODE to screen hub modules in Cytoscape. The selected genes were coped with functional analysis. CMap could find EC-related drugs that might have potential effect. Univariate and multivariate Cox proportional hazards regression analyses were performed to predict the risk of each patient. Kaplan-Meier curve analysis could compare the survival time. ROC curve analysis was performed to predict value of the genes. Mutation and survival analysis in TCGA database and UALCAN validation were completed. Immunohistochemistry staining from Human Protein Atlas database. GSEA, ROC curve analysis, Oncomine and qRT-PCR were also performed. RESULTS: Functional analysis showed that the upregulated DEGs were strikingly enriched in chemokine activity, and the down-regulated DEGs in glycosaminoglycan binding. PPI network suggested that NCAPG was the most relevant protein. CMap identified 10 small molecules as possible drugs to treat EC. Cox analysis showed that BCHE, MAL and ASPM were correlated with EC prognosis. TCGA dataset analysis showed significantly mutated BHCE positively related to EC prognosis. MAL and ASPM were further validated in UALCAN. All the results demonstrated that the two genes might promote EC progression. The profile of ASPM was confirmed by the results from immunohistochemistry. ROC curve demonstrated that the mRNA levels of two genes exhibited difference between normal and tumor tissues, indicating their diagnostic efficiency. qRT-PCR results supported the above results. Oncomine results showed that DNA copy number variation of MAL was significantly higher in different EC subtypes than in healthy tissues. GSEA suggested that the two genes played crucial roles in cell cycle. CONCLUSION: BCHE, MAL and ASPM are tumor-related genes and can be used as potential biomarkers in EC treatment.

Spatial and temporal comparisons of dissolved organic matter in river systems of the Three Gorges Reservoir region using fluorescence and UV-Visible spectroscopy.

Understanding optical characteristics, composition and source of dissolved organic matter (DOM) in rivers of the Three Gorges Reservoir (TGR) region is important for region and global carbon cycle. However, chemical compositions and source of DOM from the tributary to mainstream in the TGR region are not well studied. Consequently, 126 water samples were collected from rivers in different land use region, and these rivers covered the main tributaries of the Yangtze River in the TGR region. The temporal and spatial variations of DOM structure and source identification in different land use region were investigated using UV-visible absorbance and fluorescence spectroscopy. Overall, there were higher ratio of humic acid to fulvic, aromaticity, molecular weight and proportion of colored humic substances in DOM in the wet season than in the dry season. The weaker biologic/microbial and stronger terrestrial sources in DOM were observed in the wet season than in the dry season. DOM comparison in variable land use demonstrated the higher terrestrial sources and weaker biologic/microbial sources in DOM in the forest-affected rivers irrespective of hydrological seasonality, as well as in the wet season irrespective of land use types. DOM in the farmland-affected rivers showed more protein-like signal. We found that monsoonal precipitation, anthropogenic activities and land use were important drivers for the DOM quality variations. These findings will be beneficial to unravel riverine DOM structure and sources in relation to anthropogenic activities and also improve our understanding of DOM biogeochemical cycle in the rivers.

Multi-omics analysis of tumor mutational burden combined with prognostic assessment in epithelial ovarian cancer based on TCGA database.

Background: Tumor mutation burden (TMB) is considered as a novel biomarker of response to immunotherapy and correlated with survival outcomes in various malignancies. Here, TMB-related genes (TRGs) expression signatures were constructed to investigate the association between TMB and prognosis in epithelial ovarian cancer (EOC), and the potential mechanism in immunoregulation was also explored. Methods: Based on somatic mutation data of 436 EOC samples from The Cancer Genome Atlas database, we examined the relationship between TMB level and overall survival (OS), as well as disease-free survival (DFS). Next, the TRGs signatures were constructed and validated. Differential abundance of immune cell infiltration, expression levels of immunomodulators and functional enrichment in high- and low-risk groups were also analyzed. Results: Higher TMB level revealed better OS and DFS, and correlated with earlier clinical stages in EOCs (P = 2.796e-04). The OS-related prognostic model constructed based on seven TRGs (B3GALT1, LIN7B, ANGPT2, D2HGDH, TAF13, PFDN4 and DNAJC19) significantly stratified EOC patients into high- and low-risk groups (P < 0.001). The AUC values of the seven-gene prognostic signature at 1 year, 3 years, and 5 years were 0.703, 0.758 and 0.777. While the DFS-related prognostic model was constructed based on the 4 TRGs (LPIN3, PXYLP1, IGSF23 and B3GALT1), with AUCs of 0.617, 0.756, and 0.731, respectively. Functional analysis indicated that immune-related pathways were enriched in low-risk groups. When considering the infiltration patterns of immune cells, we found higher proportions of follicular helper T (Tfh) cell and M1 macrophage, while lower infiltration of M0 macrophage in low-risk groups (P < 0.05). Accordingly, TMB levels of low-risk patients were significantly higher both in OS and DFS model (P < 0.01). Conclusions: Our TRGs-based models are reliable predictive tools for OS and DFS. High TMB may confer with an immunogenic microenvironment and predict favorable outcomes in EOCs.

Internet Use, Risk Awareness, and Demographic Characteristics Associated With Engagement in Preventive Behaviors and Testing: Cross-Sectional Survey on COVID-19 in the United States.

BACKGROUND: During the coronavirus disease (COVID-19) pandemic, engagement in preventive behaviors and getting tested for the virus play a crucial role in protecting people from contracting the new coronavirus. OBJECTIVE: This study aims to examine how internet use, risk awareness, and demographic characteristics are associated with engagement in preventative behaviors and testing during the COVID-19 pandemic in the United States. METHODS: A cross-sectional survey was conducted on Amazon Mechanical Turk from April 10, 2020, to April 14, 2020. Participants' internet use (in terms of the extent of receiving information pertaining to COVID-19), risk awareness (whether any immediate family members, close friends or relatives, or people in local communities tested positive for COVID-19), demographics (sex, age, ethnicity, income, education level, marital status, and employment status), as well as their engagement in preventative behaviors and testing were assessed. RESULTS: Our data included 979 valid responses from the United States. Participants who received more COVID-19-related health information online reported more frequent effort to engage in all types of preventive behaviors: wearing a facemask in public (odds ratio [OR] 1.55, 95% CI 1.34-1.79, P<.001), washing hands (OR 1.58, 95% CI 1.35-1.85, P<.001), covering nose and mouth when sneezing and coughing (OR 1.78, 95% CI 1.52-2.10, P<.001), keeping social distance with others (OR 1.41, 95% CI 1.21-1.65, P<.001), staying home (OR 1.40, 95% CI 1.20-1.62, P<.001), avoiding using public transportation (OR 1.57, 95% CI 1.32-1.88, P<.001), and cleaning frequently used surfaces (OR 1.55, 95% CI 1.34-1.79, P<.001). Compared with participants who did not have positive cases in their social circles, those who had immediate family members (OR 1.48, 95% CI 8.28-26.44, P<.001) or close friends and relatives (OR 2.52, 95% CI 1.58-4.03, P<.001) who tested positive were more likely to get tested. Participants' sex, age, ethnicity, marital status, and employment status were also associated with preventive behaviors and testing. CONCLUSIONS: Our findings revealed that the extent of receiving COVID-19-related information online, risk awareness, and demographic characteristics including sex, ethnicity, age, marital status, and employment status are key factors associated with US residents' engagement in various preventive behaviors and testing for COVID-19.