Genomic basis for RNA alterations in cancer.

Transcript alterations often result from somatic changes in cancer genomes1. Various forms of RNA alterations have been described in cancer, including overexpression2, altered splicing3 and gene fusions4; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)5. Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.

Escalating Carbon Export from High-Elevation Rivers in a Warming Climate.

High-elevation mountains have experienced disproportionately rapid warming, yet the effect of warming on the lateral export of terrestrial carbon to rivers remains poorly explored and understood in these regions. Here, we present a long-term data set of dissolved inorganic carbon (DIC) and a more detailed, short-term data set of DIC, δ13CDIC, and organic carbon from two major rivers of the Qinghai-Tibetan Plateau, the Jinsha River (JSR) and the Yalong River (YLR). In the higher-elevation JSR with ∼51% continuous permafrost coverage, warming (>3 °C) and increasing precipitation coincided with substantially increased DIC concentrations by 35% and fluxes by 110%. In the lower-elevation YLR with ∼14% continuous permafrost, such increases did not occur despite a comparable extent of warming. Riverine concentrations of dissolved and particulate organic carbon increased with discharge (mobilization) in both rivers. In the JSR, DIC concentrations transitioned from dilution (decreasing concentration with discharge) in earlier, colder years to chemostasis (relatively constant concentration) in later, warmer years. This changing pattern, together with lighter δ13CDIC under high discharge, suggests that permafrost thawing boosts DIC production and export via enhancing soil respiration and weathering. These findings reveal the predominant role of warming in altering carbon lateral export by escalating concentrations and fluxes and modifying export patterns.

Severe flood modulates the sources and age of dissolved organic carbon in the Yangtze River Estuary.

Floods in global large rivers modulate the transport of dissolved organic carbon (DOC) and estuarine hydrological characteristics significantly. This study investigated the impact of a severe flood on the sources and age of DOC in the Yangtze River Estuary (YRE) in 2020. Comparing the flood period in 2020 to the non-flood period in 2017, we found that the flood enhanced the transport of young DOC to the East China Sea (ECS), resulting in significantly enriched Δ14C-DOC values. During the flood period, the proportion of modern terrestrial organic carbon (OC) was significantly higher compared to the non-flood period. Conversely, the proportion of pre-aged sediment OC was significantly lower during the flood period. The high turbidity associated with the flood facilitated rapid transformation and mineralization of sedimentary and fresh terrestrial OC, modifying the sources of DOC. The flux of modern terrestrial OC transported to the ECS during the flood period was 1.58 times higher than that of the non-flood period. These findings suggest that floods can modulate the sources and decrease the age of DOC, potentially leading to increased greenhouse gas emissions. Further research is needed to understand the long-term impacts of floods on DOC dynamics in global estuaries.

Deciphering dissolved organic matter characteristics and its fate in a glacier-fed desert river-the Tarim river, China.

The bioavailable diverse dissolved organic matter (DOM) present in glacial meltwater significantly contributes to downstream carbon cycling in mountainous regions. However, the comprehension of molecular-level characteristics of riverine DOM, from tributary to downstream and their fate in glacier-fed desert rivers remains limited. Herein, we employed spectroscopic and high-resolution mass spectrometry techniques to study both optical and molecular-level characteristics of DOM in the Tarim River catchment, northwest China. The results revealed that the DOC values in the downstream were higher than those in the tributaries, yet they remained comparable to those found in other glacier-fed streams worldwide. Five distinct components were identified using EEM-PARAFAC analysis in both tributary and downstream samples. The dominance of three protein-like components in tributary samples, contrasting with a higher presence of humic-like components in downstream samples, which implied that the dilution and alterations of the glacier DOM signature and overprinting with terrestrial-derived DOM. Molecular composition revealed that thousands of compounds with higher molecular weight and increased aromaticity were transformed, generated and introduced from terrestrial inputs during downstream transportation. The twofold rise in polycyclic aromatic and polyphenolic compounds observed downstream compared to tributaries indicated a greater influx of terrestrial organic matter introduced into the downstream during water transportation. The study suggests that the glacier-sourced DOM experienced minimal photodegradations, with limited influence from human activities, while also being shaped by terrestrial inputs during its transit in the alpine-arid region. This unique scenario offers valuable insights into comprehending the fate of DOM originating from glacial meltwater in arid mountainous regions.

Elevated nitrogen loadings facilitate carbon dioxide emissions from urban inland waters.

Carbon dioxide (CO2) production and emissions from inland waters play considerable roles in global atmospheric CO2 sources, while there are still uncertainties regarding notable nutrient inputs and anthropogenic activities. Urban inland waters, with frequently anthropogenic modifications and severely nitrogen loadings, were hotspots for CO2 emissions. Here, we investigated the spatiotemporal patterns of partial pressure of CO2 (pCO2) and CO2 fluxes (FCO2) in typical urban inland waters in Tianjin, China. Our observation indicated that pCO2 values were oversaturated in highly polluted waters, particularly in sewage rivers and urban rivers, exhibiting approximately 9 times higher than the atmosphere equilibrium concentration during sampling campaigns. Obviously, the spatiotemporal distributions of pCO2 and FCO2 emphasized that the water environmental conditions and anthropogenic activities jointly adjusted primary productivity and biological respiration of inland waters. Meanwhile, statistically positive correlations between pCO2/FCO2 and NH4+-N/NO3--N (p < 0.05) suggested that nitrogen biogeochemical processes, especially the nitrification, played a dominant role in CO2 emissions attributing to the water acidification that stimulated CO2 production and emissions. Except for slight CO2 sinks in waters with low organic contents, the total CO2 emissions from the urban surface waters of Tianjin were remarkable (286.8 Gg yr-1). The results emphasized that the reductions of nitrogen loadings, sewage draining waters, and agricultural pollution could alleviate CO2 emissions from urban inland waters.

The Differing Roles of Flavins and Quinones in Extracellular Electron Transfer in Lactiplantibacillus plantarum.

Lactiplantibacillus plantarum is a lactic acid bacterium that is commonly found in the human gut and fermented food products. Despite its overwhelmingly fermentative metabolism, this microbe can perform extracellular electron transfer (EET) when provided with an exogenous quinone, 1,4-dihydroxy-2-naphthoic acid (DHNA), and riboflavin. However, the separate roles of DHNA and riboflavin in EET in L. plantarum have remained unclear. Here, we seek to understand the role of quinones and flavins in EET by monitoring iron and anode reduction in the presence and absence of these small molecules. We found that addition of either DHNA or riboflavin can support robust iron reduction, indicating electron transfer to extracellular iron occurs through both flavin-dependent and DHNA-dependent routes. Using genetic mutants of L. plantarum, we found that flavin-dependent iron reduction requires Ndh2 and EetA, while DHNA-dependent iron reduction largely relies on Ndh2 and PplA. In contrast to iron reduction, DHNA-containing medium supported more robust anode reduction than riboflavin-containing medium, suggesting electron transfer to an anode proceeds most efficiently through the DHNA-dependent pathway. Furthermore, we found that flavin-dependent anode reduction requires EetA, Ndh2, and PplA, while DHNA-dependent anode reduction requires Ndh2 and PplA. Taken together, we identify multiple EET routes utilized by L. plantarum and show that the EET route depends on access to environmental biomolecules and on the electron acceptor. This work expands our molecular-level understanding of EET in Gram-positive microbes and provides additional opportunities to manipulate EET for biotechnology. IMPORTANCE Lactic acid bacteria are named because of their nearly exclusive fermentative metabolism. Thus, the recent observation of EET activity-typically associated with anaerobic respiration-in this class of organisms has forced researchers to rethink the rules governing microbial metabolic strategies. Our identification of multiple routes for EET in L. plantarum that depend on two different redox active small molecules expands our understanding of how microbes metabolically adapt to different environments to gain an energetic edge and how these processes can be manipulated for biotechnological uses. Understanding the role of EET in lactic acid bacteria is of great importance due to the significance of lactic acid bacteria in agriculture, bioremediation, food production, and gut health. Furthermore, the maintenance of multiple EET routes speaks to the importance of this process to function under a variety of environmental conditions.

Machine Learning Predicts the Methane Clumped Isotopologue (12CH2D2) Distributions Constrain Biogeochemical Processes and Estimates the Potential Budget.

Methane (CH4) is a matter of environmental concern; however, global methane isotopologue data remain inadequate. This is due to the challenges posed by high-resolution testing technology and the need for larger sample volumes. Here, worldwide methane clumped isotope databases (n = 465) were compiled. We compared machine-learning (ML) models and used random forest (RF) to predict new Δ12CH2D2 distributions, which cover valuable and hard-to-replicate methane clumped isotope experimental data. Our RF model yields a reliable and continuous database including ruminants, acetoclastic methane, multiple pyrolysis, and controlled experiments. We showed the effectiveness of utilizing a new data set to quantify isotopologue fractionations in biogeochemical methane processes, as well as predicting the steady-state atmospheric methane clumped isotope composition (Δ13CH3D of +2.26 ± 0.71‰ and Δ12CH2D2 of +62.06 ± 4.42‰) with notable biological contributions. Our measured summer and winter water emitted gases (n = 6) demonstrated temperature-driven seasonal microbial community evolution determined by atmospheric clumped isotope temporal variations (Δ 13CH3D ∼ -0.91 ± 0.25 ‰ and Δ12CH2D2 ∼ +3.86 ± 0.84 ‰), which in turn is relevant for future models quantifying the contribution of methane sources and sinks. Predicting clumped isotopologues translates our methane geochemical understanding into quantifiable variables for modeling that can continue to improve predictions and potentially inform global greenhouse gas emissions and mitigation policy.

Anthropogenic Disturbance Stimulates the Export of Dissolved Organic Carbon to Rivers on the Tibetan Plateau.

The impacts of human activities on the riverine carbon (C) cycle have only recently been recognized, and even fewer studies have been reported on anthropogenic impacts on C cycling in rivers draining the vulnerable alpine areas. Here, we examined carbon isotopes (δ13CDOC and Δ14CDOC), fluorescence, and molecular compositions of riverine dissolved organic matters (DOM) in the Bailong River catchment, the eastern edge of the Tibetan Plateau to identify anthropogenic impacts on the C cycle. Human activities show limited impact on dissolved organic carbon (DOC) concentration, but significantly increased the age of DOC (from modern to ∼1600 yr B.P.) and changed the molecular compositions through agriculture and urbanization despite in the catchment with low population density. Agricultural activities indirectly increased the leaching of N-containing aged organic matter from deep soil to rivers. Urbanization released S-containing aged C from fossil products into rivers directly through wastewater. The aged DOC from agricultural activity and wastewater discharge was partly biolabile and/or photolabile. This study highlights that riverine C is sensitive to anthropogenic disturbance. Additionally, the study also emphasizes that human activities reintroduce aged DOC into the modern C cycle, which would accelerate the geological C cycle.

Unraveling the Linkages between Molecular Abundance and Stable Carbon Isotope Ratio in Dissolved Organic Matter Using Machine Learning.

Dissolved organic matter (DOM) is a complex mixture of molecules that constitutes one of the largest reservoirs of organic matter on Earth. While stable carbon isotope values (δ13C) provide valuable insights into DOM transformations from land to ocean, it remains unclear how individual molecules respond to changes in DOM properties such as δ13C. To address this, we employed Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to characterize the molecular composition of DOM in 510 samples from the China Coastal Environments, with 320 samples having δ13C measurements. Utilizing a machine learning model based on 5199 molecular formulas, we predicted δ13C values with a mean absolute error (MAE) of 0.30‰ on the training data set, surpassing traditional linear regression methods (MAE 0.85‰). Our findings suggest that degradation processes, microbial activities, and primary production regulate DOM from rivers to the ocean continuum. Additionally, the machine learning model accurately predicted δ13C values in samples without known δ13C values and in other published data sets, reflecting the δ13C trend along the land to ocean continuum. This study demonstrates the potential of machine learning to capture the complex relationships between DOM composition and bulk parameters, particularly with larger learning data sets and increasing molecular research in the future.

Exploring the Complexities of Dissolved Organic Matter Photochemistry from the Molecular Level by Using Machine Learning Approaches.

Dissolved organic matter (DOM) sustains a substantial part of the organic matter transported seaward, where photochemical reactions significantly affect its transformation and fate. The irradiation experiments can provide valuable information on the photochemical reactivity (photolabile, photoresistant, and photoproduct) of molecules. However, the inconsistency of the fate of irradiated molecules among different experiments curtailed our understanding of the roles the photochemical reactions have played, which cannot be properly addressed by traditional approaches. Here, we conducted irradiation experiments for samples from two large estuaries in China. Molecules that occurred in irradiation experiments were characterized by the Fourier transform ion cyclotron resonance mass spectrometry and assigned probabilistic labels to define their photochemical reactivity. These molecules with probabilistic labels were used to construct a learning database for establishing a suitable machine learning (ML) model. We further applied our well-trained ML model to "un-matched" (i.e., not detected in our irradiation experiments) molecules from five estuaries worldwide, to predict their photochemical reactivity. Results showed that numerous molecules with strong photolability can be captured solely by the ML model. Moreover, comparing DOM photochemical reactivity in five estuaries revealed that the riverine DOM chemistry largely determines their subsequent photochemical transformation. We offer an expandable and renewable approach based on ML to compatibly integrate existing irradiation experiments and shed insight into DOM transformation and degradation processes.

Characteristics of spatial heterodyne spectroscopy for polarization measurement.

In this paper, a spatial static polarization modulation interference spectrum technique is proposed, which combines polarimetric spectral intensity modulation (PSIM) technology and spatial heterodyne spectroscopy (SHS), and can obtain the total Stokes parameters of the target light simultaneously. Moreover, there are no moving parts or electronically controlled modulation parts. In this paper, the mathematical model of the modulation process and demodulation process of spatial static polarization modulation interference spectroscopy is deduced, a computer simulation is carried out, the principle prototype is developed, and a verification experiment is carried out. Simulation and experimental results show that the combination of PSIM and SHS can achieve high-precision static synchronous measurement of high spectral resolution, high time resolution, and continuous band complete polarization information.

Spatiotemporal optical properties of dissolved organic matter in a sluice-controlled coastal plain river with both salinity and trophic gradients.

Due to the combined effect of sluices and sea tide, the sluice-controlled coastal plain river would be characterized by both trophic state and salinity gradients, affecting the spatiotemporal optical properties of dissolved organic matter (DOM). In this study, we investigated the spatiotemporal variation of water quality parameters and optical properties of DOM in the Haihe River, a representative sluice-controlled coastal plain river in Tianjin, China. A significant salinity gradient and four trophic states were observed in the water body of the Haihe River. Two humic- and one protein-like substances were identified from the DOM by the three-dimensional fluorescence spectra combined with the parallel factor (PARAFAC) analysis. Pearson's correlation analysis and redundancy analysis (RDA) showed that the salinity significantly affected the abundance of chromophoric DOM (CDOM) but did not cause significant changes in the fluorescence optical characteristics. In addition, the effect of Trophic state index (TSI) on the CDOM abundance was greater than that on the fluorescence intensity of fluorescent dissolved organic matter (FDOM). In the water body with both salinity and trophic state gradients, TSI posed a greater influence than salinity on the CDOM abundance. Our results fill the research gap in spatiotemporal DOM characteristics and water quality variation in water bodies with both salinity and trophic state gradients. These results are beneficial for clarifying the joint influence of saline intrusion and sluices on the DOM characteristics and water quality in sluice-controlled coastal plain rivers.

Tough and self-healing hydrogels based on transient crosslinking by nanoparticles.

In this investigation, transient crosslinking was constructed to obtain a hydrogel with excellent mechanical and self-healing properties. Firstly, core-shell particles with hydrophilic amino groups were prepared by emulsion polymerization and subsequently dispersed into hydrophobic association polyacrylamide hydrogels. Transient crosslinking was constructed through hydrogen bonding between core-shell particles and polyacrylamide. As a result, the hydrogels exhibited a tensile strength of 1.4 MPa and self-healing efficiency of 98% at 24 h. Furthermore, reconstruction of the transient crosslinking was confirmed from rheological measurements. Therefore, the essential reinforcement principle based on transient crosslinking would open a novel strategy to obtain hydrogels with superior toughness and self-healing properties.

Expression of severe acute respiratory syndrome coronavirus 2 cell entry genes, angiotensin-converting enzyme 2 and transmembrane protease serine 2, in the placenta across gestation and at the maternal-fetal interface in pregnancies complicated by preterm birth or preeclampsia.

BACKGROUND: Although there is some evidence that severe acute respiratory syndrome coronavirus 2 can invade the human placenta, limited data exist on the gestational age-dependent expression profile of the severe acute respiratory syndrome coronavirus 2 cell entry mediators, angiotensin-converting enzyme 2 and transmembrane protease serine 2, at the human maternal-fetal interface. There is also no information as to whether the expression of these mediators is altered in pregnancies complicated by preeclampsia or preterm birth. This is important because the expression of decidual and placental angiotensin-converting enzyme 2 and transmembrane protease serine 2 across gestation may affect the susceptibility of pregnancies to vertical transmission of severe acute respiratory syndrome coronavirus 2. OBJECTIVE: This study aimed to investigate the expression pattern of specific severe acute respiratory syndrome coronavirus 2 cell entry genes, angiotensin-converting enzyme 2 and transmembrane protease serine 2, in the placenta across human pregnancy and in paired samples of decidua and placenta in pregnancies complicated by preterm birth or preeclampsia compared with those in term uncomplicated pregnancies. STUDY DESIGN: In this study, 2 separate cohorts of patients, totaling 87 pregnancies, were included. The first cohort was composed of placentae from first- (7-9 weeks), second- (16-18 weeks), and third-trimester preterm (26-31 weeks) and third-trimester term (38-41 weeks) pregnancies (n=5/group), whereas the second independent cohort included matched decidua and placentae from pregnancies from term uncomplicated pregnancies (37-41 weeks' gestation; n=14) and pregnancies complicated by preterm birth (26-37 weeks' gestation; n=11) or preeclampsia (25-37 weeks' gestation; n=42). Samples were subjected to quantitative polymerase chain reaction and next-generation sequencing or RNA sequencing for next-generation RNA sequencing for angiotensin-converting enzyme 2 and transmembrane protease serine 2 mRNA expression quantification, respectively. RESULTS: In the first cohort, angiotensin-converting enzyme 2 and transmembrane protease serine 2, exhibited a gestational age-dependent expression profile, that is, angiotensin-converting enzyme 2 and transmembrane protease serine 2 mRNA was higher (P<.05) in the first-trimester placenta than in second-trimester, preterm birth, and term placentae (P<.05) and exhibited a negative correlation with gestational age (P<.05). In the second cohort, RNA sequencing demonstrated very low or undetectable expression levels of angiotensin-converting enzyme 2 in preterm birth, preeclampsia, and term decidua and in placentae from late gestation. In contrast, transmembrane protease serine 2 was expressed in both decidual and placental samples but did not change in pregnancies complicated by either preterm birth or preeclampsia. CONCLUSION: The increased expression of these severe acute respiratory syndrome coronavirus 2 cell entry-associated genes in the placenta in the first trimester of pregnancy compared with those in later stages of pregnancy suggests the possibility of differential susceptibility to placental entry to severe acute respiratory syndrome coronavirus 2 across pregnancy. Even though there is some evidence of increased rates of preterm birth associated with severe acute respiratory syndrome coronavirus 2 infection, we found no increase in mRNA expression of angiotensin-converting enzyme 2 or transmembrane protease serine 2 at the maternal-fetal interface.

Correction of invalid data based on spatial dimension information of a temporally and spatially modulated spatial heterodyne interference imaging spectrometer.

Considering the distribution characteristics of interference data of a temporally and spatially modulated spatial heterodyne interference imaging spectrometer, an algorithm based on spatial dimension baseline of interference data for the detection and correction of invalid data is proposed. The intensity ratio of the target interference data far away from the zero optical path difference has been extracted and calculated, and the intensity of the interference data is compensated; the baseline of the compensated interference data is carried out along the spatial dimension direction, and the deviation matrix is calculated, and combined with the 3σ method for the detection and correction of invalid data. A simulation experiment is carried out in the laboratory to obtain the target push-sweep imaging interference data, and the spectrum is the output spectrum of the integrating sphere halogen tungsten lamp. The experimental results show that the invalid data in the interference data (including invalid data near zero optical path difference) can be effectively identified and corrected using the invalid data detection and correction algorithm described in this paper, which has a good effect on the correction of fixed invalid data and flash pixel.

Characterization of Lignin Compounds at the Molecular Level: Mass Spectrometry Analysis and Raw Data Processing.

Lignin is the second most abundant natural biopolymer, which is a potential alternative to conventional fossil fuels. It is also a promising material for the recovery of valuable chemicals such as aromatic compounds as well as an important biomarker for terrestrial organic matter. Lignin is currently produced in large quantities as a by-product of chemical pulping and cellulosic ethanol processes. Consequently, analytical methods are required to assess the content of valuable chemicals contained in these complex lignin wastes. This review is devoted to the application of mass spectrometry, including data analysis strategies, for the elemental and structural elucidation of lignin products. We describe and critically evaluate how these methods have contributed to progress and trends in the utilization of lignin in chemical synthesis, materials, energy, and geochemistry.

Whole-genome sequencing reveals distinct genetic bases for insulinomas and non-functional pancreatic neuroendocrine tumours: leading to a new classification system.

OBJECTIVE: Insulinomas and non-functional pancreatic neuroendocrine tumours (NF-PanNETs) have distinctive clinical presentations but share similar pathological features. Their genetic bases have not been comprehensively compared. Herein, we used whole-genome/whole-exome sequencing (WGS/WES) to identify genetic differences between insulinomas and NF-PanNETs. DESIGN: The mutational profiles and copy-number variation (CNV) patterns of 211 PanNETs, including 84 insulinomas and 127 NF-PanNETs, were obtained from WGS/WES data provided by Peking Union Medical College Hospital and the International Cancer Genome Consortium. Insulinoma RNA sequencing and immunohistochemistry data were assayed. RESULTS: PanNETs were categorised based on CNV patterns: amplification, copy neutral and deletion. Insulinomas had CNV amplifications and copy neutral and lacked CNV deletions. CNV-neutral insulinomas exhibited an elevated rate of YY1 mutations. In contrast, NF-PanNETs had all three CNV patterns, and NF-PanNETs with CNV deletions had a high rate of loss-of-function mutations of tumour suppressor genes. NF-PanNETs with CNV alterations (amplification and deletion) had an elevated risk of relapse, and additional DAXX/ATRX mutations could predict an increased relapse risk in the first 2-year period. CONCLUSION: These WGS/WES data allowed a comprehensive assessment of genetic differences between insulinomas and NF-PanNETs, reclassifying these tumours into novel molecular subtypes. We also proposed a novel relapse risk stratification system using CNV patterns and DAXX/ATRX mutations.

Nitrate contamination of groundwater in the Lower Volta River Basin of Ghana: Sources and related human health risks.

A significant population within the Lower Volta River Basin of Ghana relies solely on untreated groundwater (GW) and surface water (SW) for various purposes. However, negative practices associated with increasing human activities pose threats to particularly GW quality in the basin. Using NO3- as a proxy, this study mainly focused on the status of GW contamination, origins of NO3- and potential human health risks through integrated hydrochemistry, correlation analysis, isotopes (15N, δ18O), Bayesian and USEPA human health risk models. Slightly acidic to alkaline GW and SW environments were observed. Electrical conductivity (EC) values above 1000 µS/cm were recorded in 45% of the GW with a maximum of 19370 µS/cm. NO3- in GW ranged from 0.12 to 733 mg/L with average 59.6 mg/L and positively correlated with K+, Ca2+, Mg2+, Cl-, Na+ and EC. In SW, a maximum of 5.3 mg/L of NO3- was observed. Largely, 75% of the GW exceeded local background NO3- value of 2.1 mg/L, while 35% were above the WHO recommended value of 50 mg/L. Bivariate and correlation relationships elucidated human contributions to sources of NO3-, Cl-, SO42- and K+ to GW in the basin. From NO3-/Cl- ratio, 43% of the GW and 21% of SW were affected by effluents and agrochemicals. Values for δ15N-NO3- and δ18O-NO3- ranged from +4.2‰ to +27.5‰ and +4.5‰ to +19.9‰ for GW, and from +3.8‰ to +14.0‰ and +10.7‰ to +25.2‰ for SW. Manure, septic effluents and mineralized fertilizers are sources of NO3- contamination of water in the basin. The Bayesian model apportioned 80% of GW NO3- contamination to sewage/manure. Hazard index indicated 70%, 50% and 48% medium to high-risk levels for infants, children and adults respectively, with 79% high-risk of SW NO2- contamination to infants. Immediate measures for GW and SW quality protection are recommended.

Control of the Hydraulic Load on Nitrous Oxide Emissions from Cascade Reservoirs.

Nitrous oxide (N2O) emissions show large variability among dam reservoirs, which makes it difficult to estimate N2O contributions to global greenhouse gases (GHGs). Because river damming alters hydraulic residence time and water depth, the hydraulic load (i.e., the ratio of the mean water depth to the residence time) was hypothesized to control N2O emissions from dam reservoirs. To test this hypothesis, we investigated N2O fluxes and related parameters in the cascade reservoirs along the Wujiang River in Southwest China. The N2O fluxes showed obvious temporal and spatial variations, ranging from -7.86 to 337.22 µmol m-2 d-1, with an average of 12.76 µmol m-2 d-1. Nitrification was the main pathway of N2O production in these reservoirs, and seasonal dissolved oxygen (DO) stratification played an important role in regulating the N2O production. The reservoir N2O flux had a significant negative logarithmic relationship with the hydraulic load, suggesting its control of the N2O emission. This was because the hydraulic load was a prerequisite for regulating the nitrification-denitrification and the DO stratification in the dam reservoirs. This empirical relationship will help to estimate the contribution of reservoir N2O emissions to global GHGs.