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Against the background of climate warming, marine heatwaves (MHWs) and terrestrial drought events have become increasingly frequent in recent decades. However, the combined effects of MHWs and terrestrial drought on CO2 uptake in marginal seas are still unclear. The East China Sea (ECS) experienced an intense and long-lasting MHW accompanied by an extreme terrestrial drought in the Changjiang basin in the summer of 2022. In this study, we employed multi-source satellite remote sensing products to reveal the patterns, magnitude, and potential drivers of CO2 flux changes in the ECS resulting from the compounding MHW and terrestrial drought extremes. The CO2 uptake of the ECS reduced by 17.0% (1.06 Tg C) in the latter half of 2022 and the Changjiang River plume region shifted from a CO2 sink to a source (releasing 0.11 Tg C) in July-September. In the majority of the ECS, the positive sea surface temperature (SST) anomaly during the MHW diminished the solubility of CO2 in seawater, thereby reducing CO2 uptake. Moreover, the reduction in nutrient input associated with terrestrial drought, which is unfavorable to phytoplankton growth, further reduced the capacity of CO2 uptake. Meanwhile, the CO2 sink doubled for the offshore waters of the ECS continental shelf in July-September 2022, indicating the complexity and heterogeneity of the impacts of extreme climatic events in marginal seas. This study is of great significance in improving the estimation results of CO2 fluxes in marginal seas and understanding sea–air CO2 exchanges against the background of global climate change. [ABSTRACT FROM AUTHOR]

Seawater pH is a direct proxy of ocean acidification, and monitoring the global pH distribution and long-term series changes is critical to understanding the changes and responses of the marine ecology and environment under climate change. Owing to the lack of sufficient global-scale pH data and the complex relationship between seawater pH and related environmental variables, generating time-series products of satellite-derived global sea surface pH poses a great challenge. In this study, we solved the problem of the lack of sufficient data for pH algorithm development by using the massive underway sea surface carbon dioxide partial pressure (pCO2) dataset to structure a large data volume of near in situ pH based on carbonate calculation between underway pCO2 and calculated total alkalinity from sea surface salinity and relevant parameters. The remote sensing inversion model of pH was then constructed through this massive pH training dataset and machine learning methods. After several tests of machine learning methods and groups of input parameters, we chose the random forest model with longitude, latitude, sea surface temperature (SST), chlorophyll a (Chla), and Mixed layer depth (MLD) as model inputs with the best performance of correlation coefficient (R2 = 0.96) and root mean squared error (RMSE = 0.008) in the training set and R2 = 0.83 (RMSE = 0.017) in the testing set. The sensitivity analysis of the error variation induced by the uncertainty of SST and Chla (SST ≤ ±0.5 °C and Chla ≤ ±20%; RMSESST ≤ 0.011 and RMSEChla ≤ 0.009) indicated that our sea surface pH model had good robustness. Monthly average global sea surface pH products from 2004 to 2019 with a spatial resolution of 0.25° × 0.25° were produced based on the satellite-derived SST and Chla products and modeled MLD dataset. The pH model and products were validated using another independent station-measured pH dataset from the Global Ocean Data Analysis Project (GLODAP), showing good performance. With the time-series pH products, refined interannual variability and seasonal variability were presented, and trends of pH decline were found globally. Our study provides a new method of directly using remote sensing to invert pH instead of indirect calculation based on the construction of massive underway calculated pH data, which would be made useful by comparing it with satellite-derived pCO2 products to understand the carbonate system change and the ocean ecological environments responding to the global change. [ABSTRACT FROM AUTHOR]

This study introduces a cellulose nanofiber surfactant system, in which the surface is hydrophobically modified with different alkyl chain structures for the effective envelopment of solid lipid microparticles (SLMs). To endow bacterial cellulose nanofibers (BCNFs) with excellent ability to assemble at the lipid–water interface, alkyl chains with designated molecular structures, such as decane, didecane, and eicosane, are covalently grafted onto the BCNF surface. Interfacial tension and interfacial rheology measurements indicate that dialkyl chain‐grafted BCNFs (diC10BCNF) exhibit strong interfibrillar association at the interface. The formation of a dense and tough fibrillary membrane contributes significantly to the enveloping of the SLMs, regardless of the lipid type. Because the diC10BCNF‐enveloped SLMs exhibit a core molecular crystalline phase at the microscale, they can immobilize an oil‐soluble antioxidant while maintaining its long‐term storage stability. These findings show that the cellulose‐surfactant‐based SLM technology is applicable to the stabilization and formulation of readily denatured active ingredients. [ABSTRACT FROM AUTHOR]

Nutritional intervention is effective in reducing the risk of neural tube defects (NTDs). To determine the effects of nutritional supplementation on human metabolism, a metabonomic study was carried out on 96 women of reproductive age. Subjects with nutritional intervention were given fortified wheat flour (containing folic acid, vitamin B, vitamin B, ferric sodium edetate and zinc oxide) for 8 months. Serum metabolic fingerprinting was detected via ultraperformance liquid chromatography in tandem with time-of-flight mass spectrometry (UPLC-TOF MS), and data acquired was processed by multivariate statistical analysis. The result revealed a significant difference between the control and intervention group. Twenty potential biomarkers, including fructose 6-phosphate, sphingosine 1-phosphate, docosahexaenoic acid and hexadecanoic acid, were located and identified by the accurate mass measurement of TOF MS. These compounds are believed to be functionally related to anti-oxidative competence in vivo. In conclusion, metabonomics study is a valuable approach in exploring the effect mechanism of nutritional intervention on NTD prevention. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: It was reported that Hcy was related to the development of kidney disease, but it remains unknown whether Hcy is an independent biomarker for diabetic nephropathy. Analytical method for simultaneous determination of aminothiols among the Hcy metabolic cycle is desirable to discover other potential biomarkers. A high-performance liquid chromatography–electrospray tandem mass spectrometric (HPLC–ESI-MS/MS) method was established for simultaneous quantitation of Cysteine (Cys), total homocysteine (tHcy), S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), cystathionine (Cysta), methionine (Met), glutathione (GSH) and cysteinylglycine (Cys-gly) in plasma with N-(2-mercaptopropionyl)-glycine (MPG) as internal standard. The method had simple pretreatment without derivatization and the chromatograms show better separation of the eight aminothiols and the analytic time was 20min. The results demonstrated that it provided an excellent linearity for all analytes over their respective concentration ranges and illustrated excellent precision and plasma recovery as well. Then, the method was applied in the case–control study of patients with diabetes mellitus (DM) and diabetic nephropathy (DN). In conclusion, it is an effective method to quantitate the concentrations of aminothiols in the human plasma. SAH and SAM were suggested as better potential biomarkers of DM and DN. [Copyright &y& Elsevier]