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Abstract The acidification of coastal waters is distinguished from the open ocean because of much stronger synergistic effects between anthropogenic forcing and local biogeochemical processes. However, ocean acidification research is still rather limited in polar coastal oceans. Here, we present a 16 year (2002–2018) observational dataset in the Chukchi Sea during the rapid sea‐ice melting season to determine the long‐term changes in pH and aragonite saturation state (Ωarag). We found that pH and Ωarag significantly declined in the water column with average rates of −0.0095 ± 0.0027 years−1 and −0.0333 ± 0.0098 years−1, respectively, and are 4–6 times faster than those solely due to increasing atmospheric CO2. We attributed the rapid acidification to the increased dissolved inorganic carbon owing to a combination of ice melt‐induced increased atmospheric CO2 invasion and subsurface remineralization induced by a stronger surface biological production as a result of the increased inflow of the nutrient‐rich Pacific water.

Sphingolipids (SPLs) represent a highly diverse and structurally complex lipid class. The discussion of SPL metabolism-related issues is of importance in understanding the neuropathological progression of Alzheimer's disease (AD). AD is characterized by the accumulation of extracellular deposits of the amyloid β-peptide (Aβ) and intraneuronal aggregates of the microtubule-associated protein tau. Critical roles of Aβ oligomer deposited and ganglioside GM1 could be formed as “seed” from insoluble GAβ polymer in initiating the pathogenic process, while tau might also mediate SPLs and their toxicity. The interaction between ceramide and α-Synuclein (α-Syn) accelerates the aggregation of ferroptosis and exacerbates the pathogenesis of AD. For instance, reducing the levels of SPLs can mitigate α-Syn accumulation and inhibit AD progression. Meanwhile, loss of SPLs may inhibit the expression of APOE4 and confer protection against AD, while the loss of APOE4 expression also disrupts SPLs homeostasis. Moreover, the heightened activation of sphingomyelinase promotes the ferroptosis signaling pathway, leading to exacerbated AD symptoms. Ferroptosis plays a vital role in the pathological progression of AD by influencing Aβ, tau, APOE, and α-Syn. Conversely, the development of AD also exacerbates the manifestation of ferroptosis and SPLs. We are compiling the emerging techniques (Derivatization and IM-MS) of sphingolipidomics, to overcome the challenges of AD diagnosis and treatment. In this review, we examined the intricate neuro-mechanistic interactions between SPLs and Aβ, tau, α-Syn, APOE, and ferroptosis, mediating the onset of AD. Furthermore, our findings highlight the potential of targeting SPLs as underexplored avenue for devising innovative therapeutic strategies against AD.

Sonodynamic therapy (SDT) has attracted significant attention in recent years as it is an innovative approach to tumor treatment. It involves the utilization of sound waves or ultrasound (US) to activate acoustic sensitizers, enabling targeted drug release for precise tumor treatment. This review aims to provide a comprehensive overview of SDT, encompassing its underlying principles and therapeutic mechanisms, the applications of nanomaterials, and potential synergies with combination therapies. The review begins by introducing the fundamental principle of SDT and delving into the intricate mechanisms through which it facilitates tumor treatment. A detailed analysis is presented, outlining how SDT effectively destroys tumor cells by modulating drug release mechanisms. Subsequently, this review explores the diverse range of nanomaterials utilized in SDT applications and highlights their specific contributions to enhancing treatment outcomes. Furthermore, the potential to combine SDT with other therapeutic modalities such as photothermal therapy (PTT) and chemotherapy is discussed. These combined approaches aim to synergistically improve therapeutic efficacy while mitigating side effects. In conclusion, SDT emerges as a promising frontier in tumor treatment that offers personalized and effective treatment options with the potential to revolutionize patient care. As research progresses, SDT is poised to play a pivotal role in shaping the future landscape of oncology by providing patients with a broader spectrum of efficacious and tailored treatment options.

Introduction Obesity is a complex and multifactorial disease that has affected many adolescents in recent decades. Clinical practice guidelines recommend exercise as the key treatment option for adolescents with overweight and obesity. However, the effects of virtual reality (VR) exercise on the physical and brain health of adolescents with overweight and obese remain unclear. This study aims to evaluate the effects of physical and VR exercises on physical and brain outcomes and explore the differences in benefits between them. Moreover, we will apply a multiomics analysis to investigate the mechanism underlying the effects of physical and VR exercises on adolescents with overweight and obesity.Methods and analysis This randomised controlled clinical trial will include 220 adolescents with overweight and obesity aged between 11 and 17 years. The participants will be randomised into five groups after screening. Participants in the exercise groups will perform an exercise programme by adding physical or VR table tennis or soccer classes to routine physical education classes in schools three times a week for 8 weeks. Participants in the control group will maintain their usual physical activity. The primary outcome will be the change in body fat mass measured using bioelectrical impedance analysis. The secondary outcomes will include changes in other physical health-related parameters, brain health-related parameters and multiomics variables.Ethics and dissemination This study was approved by the Ethics Committee of Shanghai Sixth People’s Hospital and registered in the Chinese Clinical Trial Registry. Dissemination of the findings will include peer-reviewed publications, conference presentations and media releases.Trial registration number ChiCTR2300068786.

The understanding of long-time-series variations in air-sea CO2 flux in the Bering Sea is critical, as it is the passage area from the North Pacific Ocean water to the Arctic. Here, a data-driven remote sensing retrieval method is constructed based on a large amount of underway partial pressure of CO2 (pCO2) data in the Bering Sea. After several experiments, a Gaussian process regression model with input parameters of sea surface temperature, sea surface height, mixed-layer depth, chlorophyll a concentration, dry air mole fractions of CO2, and bathymetry was selected. After validation with independent data, the root mean square error of pCO2 was< 24 μatm (R2 = 0.94) with satisfactory performance. Then, we reconstructed the sea surface pCO2 in the Bering Sea from 2003 to 2019 and estimated the corresponding air-sea CO2 fluxes. Significant seasonal variations were identified, with higher sea surface pCO2 in winter/spring than in summer/autumn in both the basin and shelf area. Semiquantitative analysis reveals that the Bering Sea is a non-temperature-dominated area with a mean temperature effect on pCO2 of 12.7 μatm and a mean non-temperature effect of −51.8 μatm. From 2003 to 2019, atmospheric pCO2 increased at a rate of 2.1 μatm yr−1, while sea surface pCO2 in the basin increased rapidly (2.8 μatm yr−1); thus, the CO2 emissions from the basin increased. However, the carbon sink in the continental shelf still continuously increased. The whole Bering Sea exhibited an increasing carbon sink with the area integral of air-sea CO2 fluxes increasing from 6 to 19 TgC over 17 years. Meanwhile, the seasonal amplitudes in pCO2 in the shelf area also increased, approaching 14 μatm per decade. The reaction of the continuously added CO2 in continental seawater reduced the ocean CO2 system capacity. This is the first study to present long-time-series satellite data with high resolution in the Bering Sea, which is beneficial for studying the changes in ocean ecosystems and carbon sink capacity.

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.

Against the backdrop of global warming, extreme precipitation events have become more frequent. In complex terrain regions, due to the vulnerability of their ecosystems, extreme precipitation events can lead to significant secondary disasters. Utilizing daily rainfall data from the National Meteorological Information Center of China and statistical analysis, this study explores the spatial and temporal distribution of extreme precipitation in the Central Southwest China (CSC) region. The temporal pattern of extreme precipitation in CSC shows a consistent trend, while the spatial distribution reveals an opposite phase between the northern and southern parts of CSC. Based on this, we propose a new method for constructing extreme precipitation prediction models for complex terrain regions based on physical mechanisms, and take CSC area as a study case. Instead of anonymous feature selection, this method improves the accuracy and stability of the model by studying the impact of sea–air interactions on extreme precipitation and then introducing it into deep learning. It was found that the sea surface temperature (SST) anomaly in the South Indian Ocean affects extreme precipitation in the CSC by influencing uplift, atmospheric instability, and moisture. The SST anomaly also affects the intensity of cross-equatorial airflow, which changes the trajectory of the Pacific–Japan teleconnection wave and impacts extreme precipitation. These findings provide a comprehensive and reliable approach for forecasting extreme precipitation in CSC and are further integrated into the extreme precipitation prediction models.

The spatiotemporal variations in suspended sediment concentration (SSC) in the lower reaches of the Yellow River exhibit significant variability and are influenced by reservoir operations. Understanding the spatiotemporal distribution characteristics of SSC in water holds crucial implications for environmental protection and reservoir operation management. Based on daily-scale SSC monitoring data from four hydrological stations in the lower Yellow River, this study established an SSC remote sensing model applicable to Landsat series satellite data. The independent variable of the model, Rrs(NIR)/(Rrs(G) + Rrs(R) + Rrs(SWIR)), demonstrated sensitivity to water bodies with different SSC values. Distinctive spatiotemporal characteristics in sediment transport were observed across the lower Yellow River. Spatially, the SSC values in the Sanmenxia and Xiaolangdi reservoirs were notably lower than those in other river sections, averaging 1008.42 ± 602.83 mg/L and 1177.89 ± 627.95 mg/L, respectively. Over time, the majority of the river sections (96%) exhibited decreasing trends in SSC during 1984–2022, particularly in the downstream Xiaolangdi reservoir, with average SSC values of 4265.58 ± 1101.77 mg/L in the 1980s and 1840.80 ± 2255.15 mg/L in the 2020s. Seasonal variations in SSC were prominent, with higher summer concentrations, averaging 5536.43 ± 2188.77 mg/L (2020s summer) and 814.11 ± 158.27 mg/L (2020s winter). Reductions in SSC during 1984–2022 primarily occurred in summer, weakening its seasonal variability in the lower Yellow River. Water discharge emerged as a critical factor influencing suspended sediment transport, with SSC increasing in high-water-flow months. Following the construction of the Xiaolangdi reservoir, the relationship between SSC and water discharge at different stations underwent notable alterations. This study enhances our understanding of the spatiotemporal dynamics of suspended sediment transport in the lower Yellow River, providing valuable insights for utilizing long-term Landsat series data in the dynamic monitoring of river sediment transport.

Chlorophyll-a concentration (Chla) is recognized as an essential climate variable and is one of the primary parameters of ocean-color satellite products. Ocean-color missions have accumulated continuous Chla data for over two decades since the launch of SeaWiFS (Sea-viewing Wide Field-of-view Sensor) in 1997. However, the on-orbit life of a single mission is about five to ten years. To build a dataset with a time span long enough to serve climate change related studies, it is necessary to merge the Chla data from multiple sensors. The European Space Agency has developed two sets of merged Chla products, namely GlobColour and OC-CCI (Ocean Colour Climate Change Initiative), which have been widely used. Nonetheless, issues remain in the long-term trend analysis of these two datasets because the inter-mission differences in Chla have not been completely corrected. To obtain more accurate Chla trends in the global and various oceans, we produced a new dataset by merging Chla records from the SeaWiFS, MODIS (Medium-spectral Resolution Imaging Spectrometer), MERIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite), and OLCI (Ocean and Land Colour Instrument) with inter-mission differences corrected in this work. The fitness of the dataset on long-term Chla trend study was validated by using in situ Chla and comparing the trend estimates to the multi-annual variability of different satellite Chla records. The results suggest that our dataset can be used for long-term series analysis and trend detection. We also provide the global trend map in Chla over 23 years (1998–2020) and present a significant positive global trend with 0.67% ± 0.37%/yr.

Abstract The La Niña of 2007/2008 was particularly strong, so was the southward flow of the cold, nutrient-rich Changjiang (Yangtze River) Diluted Water (CDW) when the winter monsoon started to blow in the fall. Here we use shipboard data in 2008 in two transects, one in the southwestern East China Sea and one in the southern Taiwan Strait, to show that as late as April in 2008 the CDW was still clearly identifiable when the winter monsoon had weakened. Waters as cold as 16 °C with a salinity lower than 30 still occupied the southwestern East China Sea. Waters of 17 °C and S

Node localization in two-dimensional (2D) and three-dimensional (3D) space for wireless sensor networks (WSNs) remains a hot research topic. To improve the localization accuracy and applicability, we first propose a quantum annealing bat algorithm (QABA) for node localization in WSNs. QABA incorporates quantum evolution and annealing strategy into the framework of the bat algorithm to improve local and global search capabilities, achieve search balance with the aid of tournament and natural selection, and finally converge to the best optimized value. Additionally, we use trilateral localization and geometric feature principles to design 2D (QABA-2D) and 3D (QABA-3D) node localization algorithms optimized with QABA, respectively. Simulation results show that, compared with other heuristic algorithms, the convergence speed and solution accuracy of QABA are greatly improved, with the highest average error of QABA-2D reduced by 90.35% and the lowest by 17.22%, and the highest average error of QABA-3D reduced by 75.26% and the lowest by 7.79%.

Like other high-latitude seas, the subpolar Bering and Okhotsk Seas in the northernmost Pacific Ocean changed rapidly from 1998 to 2018. The sea surface temperature (SST) increased by 0.62 and 0.41 °C/decade, respectively, much higher than the global rate of 0.108 °C/decade from 2000 until 2015. Despite this rapid warming, the chlorophyll content did not change significantly in the Bering Sea but increased by 0.047 μg/L/decade in the Okhotsk Sea. The Secchi disk depth (SDD) increased by 0.43 and 0.46 m/decade, respectively. Similar to other warm bodies of water, the SST of the subtropical/tropical South China Sea (SCS) also began rising, by 0.089 °C/decade, albeit more slowly than the global average. The chlorophyll content increased at 0.15 μg/L/decade from 1998 to 2006 but decreased by 0.11 μg/L/decade between 2007 and 2018. The SDD increased by 0.29 m/decade between 1998 and 2018. Although the SDD increased in all three seas, the chlorophyll concentration was maximum around 2006–2009, reflecting different phytoplankton responses to seawater warming.

Algal blooms happen widely in eutrophic lakes. The satellite-derived surface algal bloom area and chlorophyll-a (Chl-a) concentration are commonly used as indicators to judge the water quality. However, vertical migration of phytoplankton may seriously affect the assessment accuracy of water quality with the surface status as an indicator. In fact, the water column-integrated algal biomass is better for describing the water quality. To remotely estimate the algal biomass considering the vertical Chl-a profile (uniform or otherwise), this paper proposed a novel process-oriented algorithm applied successfully in Lake Chaohu, China. First, we built a decision tree to identify the pixel-based Chl-a profile types using the floating algae index, surface Chl-a concentration, and wind speed. Then, the nonuniform profile was expressed as a power decay function (Chl-a(z)=n1×zn2) and parameterized using the surface Chl-a concentration. Finally, the algal biomass was derived from MODIS/Aqua satellite data. The estimation results were acceptable and the bias was −19.95%. The monthly mean algal biomass varied significantly and exhibited two peaks in spring and summer. The annual mean algal biomass increased from 2003 to 2010 (Pearson r = 0.82; p

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.

China plays an important role in the international trade of agricultural commodities. Considering the dynamic reactive nitrogen (Nr) losses of agricultural systems in China, a hypothesis was proposed that crop conversion in China would be correlated with the extent of crop trade, influencing Nr losses in agricultural systems. The objective of this study was to verify the hypothesis based on a hybrid approach, which incorporated life cycle analysis (LCA), copula–Markov chain Monte Carlo (MCMC) simulation, and copula sampling. The approach was proven to be of benefit in (a) evaluating Nr losses in crop planting based on a LCA framework, (b) identifying dependencies and co-movements of the correlated variables in planting structures and crop trade using copula–MCMC simulations, and (c) recognizing fluctuations in Nr losses of crop planting in the future using copula-based sampling method. The planting structures and international trade of four types of crops (i.e. wheat, soybeans, maize, and rice) in 20 provinces of China indicated significant correlations, thus supporting the initial hypothesis. With the improvement of self-sufficiency in crop production, especially soybeans, Nr losses from the crop production of China in 2025 and 2030 would decrease by 8.43% and 4.26%, compared with those in 2018 (i.e. 1916.74 kt N).

Abstract Background MEF2C (Myocyte-specific enhancer factor 2C) has been associated with neurodevelopmental disorders. This study aimed at delineating the clinical profiles of MEF2C gene mutations. Methods In total, 112 Chinese patients with intellectual disability (ID) were recruited, including 44 patients presented with Rett syndrome (RTT) or RTT-like syndrome, and 68 patients with non-syndromic ID. Targeted next-generation sequencing (NGS) was performed. Detailed clinical information was collected. Results Five heterozygous MEF2C gene mutations were identified, of which three were novel. The MEF2C mutant rate was 4.5% (5/112) in total, and 6.8% (3/44) in the RTT (−like) cohort. All patients with MEF2C gene mutation presented with cognitive impairment, gross motor delay, speech disorder and autistic features. Four patients had epilepsy, which responded well to antiepileptic drugs. One female was diagnosed with classical RTT, two females with RTT-like syndrome, and two males with non-syndromic ID. Generally, the phenotype of two males with relatively downstream mutations (c.565C > T, p.Arg 189*; c.766C > T, p.Arg 256*) was milder than that of three females with upstream mutations (c.48C > G, p.Asn16Lys; c.334G > T, p.Glu112* and c.403-1G > T). Conclusions Our findings expanded the current understanding of the consequences of MEF2C dysfunctions, especially MEF2C point mutations. MEF2C mutations are associated with a broad clinical spectrum, ranged from classical RTT to non-syndromic ID. Through our study, it can be inferred that there is correlation between the phenotype and MEF2C-genotype, the mutation site. Overall, the MEF2C gene mutational analysis should be performed in ID cohort, especially in patients with features overlapped with RTT.

Abstract Background SCN8A mutations have recently been associated with epilepsy and neurodevelopmental disorders. This study aimed to broaden the phenotypic-spectrum of disease related with SCN8A mutations. Methods To identify the pathogenic gene of a Chinese family, in which six members suffered from epilepsy, whole-exome sequencing was performed. In addition, target next-generation sequencing (NGS) was performed on 178 sporadic patients, who had epilepsy of unknown etiology within 6 months after birth. A detailed clinical history was obtained. Results A heterozygous missense mutation of SCN8A was identified in the Chinese family. Six de novo mutations of SCN8A were detected in 6 sporadic patients with epilepsy. In the family, six members developed seizures within a few years after birth. Five of them had milder clinical performance, that they had normal cognition and developmental milestones, and seizure-free was achieved by mono-therapy. The other one affected member presented with refractory epilepsy and developmental regression. She died from sudden unexpected death in epilepsy (SUDEP) at 17-year-old. Clinical features of six sporadic patients with SCN8A mutations were diverse, ranging from severe epileptic encephalopathy to benign epilepsy with normal cognition. Seizures started at the mean age of 3.9 months (from 2 months to 6 months). Seizure-free was achieved in four of them by mono- or multi-antiepileptic drugs. Five of them demonstrated mild or severe psychomotor retardation, whereas the other one was normal in development and intelligence. Conclusions Our findings extend the spectrum of SCN8A mutations and the clinical features of patients with SCN8A mutations. The majority of SCN8A mutations were de novo, inherited mutations from the heterozygous parents can also occur. The phenotypic spectrum of SCN8A mutation varied largely. Most affected patients manifested as refractory epilepsy and severe intellectual disability, only a small number of patients presented with milder clinical patterns. Additionally, our study confirmed that the same mutation can lead to different phenotypes.

Abstract Background This study aimed to investigate the new genetic etiologies of Rett syndrome (RTT) or Rett‐like phenotypes. Methods Targeted next‐generation sequencing (NGS) was performed on 44 Chinese patients with RTT or Rett‐like phenotypes, in whom genetic analysis of MECP2, CDKL5, and FOXG1 was negative. Results The detection rate was 31.8% (14/44). A de novo pathogenic variant (c.275_276ins AA, p. Cys92*) of KIF1A was identified in a girl with all core features of typical RTT. A patient with atypical RTT was detected having de novo GRIN1 pathogenic variant (c.2337C > A, p. Val793Phe). Additionally, compound heterozygous pathogenic variants of PPT1 gene were detected in a girl, who initially displayed typical RTT features, but progressed into neuronal ceroid lipofuscinoses (NCL) afterwards. Pathogenic variants in KCNQ2, MEF2C, WDR45, TCF4, IQSEC2, and SDHA were also found in our cohort. Conclusions It is the first time that pathogenic variants of GRIN1 and KIF1A were linked to RTT and Rett‐like profiles. Our findings expanded the genetic heterogeneity of Chinese RTT or Rett‐like patients, and also suggest that some patients with genetic metabolic disease such as NCL, might displayed Rett features initially, and clinical follow‐up is essential for the diagnosis.

We have previously reported that Ginsenoside Rb1 may effectively prevent HUVECs from senescence, however, the detailed mechanism has not demonstrated up to now. Recent studies have shown that sirtuin-1 (Sirt1) plays an important role in the development of endothelial senescence. The purpose of this study was to explore whether Sirt1 is involved in the action of Ginsenoside Rb1 regarding protection against H2O2-induced HUVEC Senescence.Senescence induced by hydrogen peroxide (H2O2) in human umbilical vein endothelial cells (HUVECs) was examined by analyzing plasminogen activator inhibitor-1 (PAI-1) expression, cell morphology, and senescence-associated beta-galactosidase (SA-β-gal) activity. The results revealed that 42% of control-treated HUVECs were SA-β-gal positive after treatment by 60 µmol/L H2O2, however, this particular effect of H2O2 was decreased more than 2-fold (19%) in the HUVECs when pretreated with Rb1 (20 µmol/L) for 30 min. Additionally, Rb1 decreased eNOS acetylation, as well as promoted more NO production that was accompanied by an increase in Sirt1 expression. Furthermore, upon knocking down Sirt1, the effect of Rb1 on HUVEC senescence was blunted.The present study indicated that Ginsenoside Rb1 acts through stimulating Sirt1 in order to protect against endothelial senescence and dysfunction. As such, Sirt1 appears to be of particular importance in maintaining endothelial functions and delaying vascular aging.

The 26S proteasome plays a fundamental role in almost all eukaryotic cells, including vascular endothelial cells. However, it remains largely unknown how proteasome functionality is regulated in the vasculature. Endothelial nitric oxide (NO) synthase (eNOS)-derived NO is known to be essential to maintain endothelial homeostasis. The aim of the present study was to establish the connection between endothelial NO and 26S proteasome functionality in vascular endothelial cells. The 26S proteasome reporter protein levels, 26S proteasome activity, and the O-GlcNAcylation of Rpt2, a key subunit of the proteasome regulatory complex, were assayed in 26S proteasome reporter cells, human umbilical vein endothelial cells (HUVEC), and mouse aortic tissues isolated from 26S proteasome reporter and eNOS knockout mice. Like the other selective NO donors, NO derived from activated eNOS (by pharmacological and genetic approach) increased O-GlcNAc modification of Rpt2, reduced proteasome chymotrypsin-like activity, and caused 26S proteasome reporter protein accumulation. Conversely, inactivation of eNOS reversed all the effects. SiRNA knockdown of O-GlcNAc transferase (OGT), the key enzyme that catalyzes protein O-GlcNAcylation, abolished NO-induced effects. Consistently, adenoviral overexpression of O-GlcNAcase (OGA), the enzyme catalyzing the removal of the O-GlcNAc group, mimicked the effects of OGT knockdown. Finally, compared to eNOS wild type aortic tissues, 26S proteasome reporter mice lacking eNOS exhibited elevated 26S proteasome functionality in parallel with decreased Rpt2 O-GlcNAcylation, without changing the levels of Rpt2 protein. In conclusion, the eNOS-derived NO functions as a physiological suppressor of the 26S proteasome in vascular endothelial cells.

Diabetes impairs physiological angiogenesis by molecular mechanisms that are not fully understood. Methylglyoxal (MGO), a metabolite of glycolysis, is increased in patients with diabetes. This study defined the role of MGO in angiogenesis impairment and tested the mechanism in diabetic animals. Endothelial cells and mouse aortas were subjected to Western blot analysis of vascular endothelial growth factor receptor 2 (VEGFR2) protein levels and angiogenesis evaluation by endothelial cell tube formation/migration and aortic ring assays. Incubation with MGO reduced VEGFR2 protein, but not mRNA, levels in a time and dose dependent manner. Genetic knockdown of the receptor for advanced glycation endproducts (RAGE) attenuated the reduction of VEGFR2. Overexpression of Glyoxalase 1, the enzyme that detoxifies MGO, reduced the MGO-protein adducts and prevented VEGFR2 reduction. The VEGFR2 reduction was associated with impaired angiogenesis. Suppression of autophagy either by inhibitors or siRNA, but not of the proteasome and caspase, normalized both the VEGFR2 protein levels and angiogenesis. Conversely, induction of autophagy either by rapamycin or overexpression of LC3 and Beclin-1 reduced VEGFR2 and angiogenesis. MGO increased endothelial LC3B and Beclin-1, markers of autophagy, which were accompanied by an increase of both autophagic flux (LC3 punctae) and co-immunoprecipitation of VEGFR2 with LC3. Pharmacological or genetic suppression of peroxynitrite (ONOO(-)) generation not only blocked the autophagy but also reversed the reduction of VEGFR2 and angiogenesis. Like MGO-treated aortas from normglycemic C57BL/6J mice, aortas from diabetic db/db and Akita mice presented reductions of angiogenesis or VEGFR2. Administration of either autophagy inhibitor ex vivo or superoxide scavenger in vivo abolished the reductions. Taken together, MGO reduces endothelial angiogenesis through RAGE-mediated, ONOO(-)dependent and autophagy-induced VEGFR2 degradation, which may represent a new mechanism for diabetic angiogenesis impairment.

Based on the MODIS MCD19A2 aerosol dataset， the temporal and spatial distribution characteristics of the atmospheric aerosol optical thickness （AOD） and the influence of meteorological factors in the Qaidam Basin from 2001 to 2021 were investigated by using linear trend， Spearman correlation analysis， and Ångström exponential interpolation， and the results show that： （1） On the interannual scale， the AOD in the Qaidam Basin fluctuates upward， with an annual increase of 3.74% and an annual mean value of 0.110±0.002； on the seasonal scale， AOD has obvious seasonal changes， and its value from high to low is spring， summer， autumn and winter， respectively.AOD in spring and summer fluctuates， while AOD in autumn and winter has no obvious change.on the monthly scale， the AOD is in the shape of a single peak， and the peak value is in April.（2） In space， the high value area of AOD is located in the hinterland of Qaidam Basin， showing the distribution characteristics of high in the middle and low around， and the low value area is located in the high altitude areas such as Kunlun Mountain Range and Qilian Mountain Range and the area with high vegetation cover.（3） Meteorological factors have a certain influence on AOD， among which wind speed， temperature， relative humidity， cloudiness and precipitation are positively correlated with AOD， and wind speed and temperature have the greatest influence on AOD.

The oxidative pyrolysis kinetics of coal before and after immersion effect was studied by thermogravimetric experiments. Non-isothermal thermogravimetric analysis data were analyzed at four heating rates of 5, 10, 20 and 30 K/min. Furthermore, temperature-programmed experiments and Fourier-transform infrared (FTIR) spectroscopy were employed to understand the oxidation activity and chemical structure of raw coal and soaked coal. After coal immersion effect, the increase in the content of active functional groups, the increase in the concentration of gaseous products, and the decrease in crossing point temperature during oxidation process all indicate that soaked coal is easier to oxidize and spontaneously combust. Lastly, four model-free methods such as Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), Friedman and Kissinger methods are employed to calculate the activation energy (Eα). Kinetic analysis reveals that Eα value obtained by the former three methods significantly depends on the conversion of coal oxidative pyrolysis process, and the average Eα value of soaked coal obtained by four methods is lower than that of raw coal. For the kinetic analysis of coal oxygen adsorption and combustion stages, it is more reliable to adopt the FWO and KAS methods in turn. This research helps to better understand the mechanism of enhanced oxidation activity of soaked coal and optimizes the calculation method of kinetic parameters in different oxidation stages of coal.

Aiming at the restricted oxygen environment of coal mine, this paper focus on the whole process from physical adsorption to chemical reaction between coal and oxygen, and quantum chemical calculations investigate the potentiating or inhibiting effects of different active groups on the amount of oxygen adsorbed and thermally released from the main coal structure, and experimentally investigate the effect of oxygen concentration (OC) on the transformation relationship between active functional groups and active sites. The results showed the coal side-chain structure has an effect on the heat release characteristics of the aromatic ring in the process of oxygen adsorption, and the heat of adsorption of the aromatic ring with alkyl and aldehyde side-chains reaches 422.706 kJ/mol. The relationship between carbon oxide release and temperature at different OC all conformed to the exponential function model, and the apparent activation energy was positively correlated with the OC. The increase of OC narrows the gap between the production and consumption rates of active sites, which is helpful for the further understanding of the coal spontaneous combustion (CSC).