Search

The stability of the Larsen C Ice Shelf (LIS) has been widely studied due to its surface lowering, calving, and warming. In this study, we combined multisource remote-sensing data, calculated the long-term series of surface elevation above basal channels and basal melt rate, and analyzed the dynamic changes in the LIS before and after calving in 2017. We found that the basal channels were mainly concentrated in the southern LIS, and the basal melt rate was higher in the south. The Weddell Sea warm water mass entered the bottom of the LIS through the sea trough and promoted basal melting. There was an abnormal basal channel where changes in sea ice concentrations caused by wind-driven currents led to abnormal development. We did not observe significant changes in ice thickness, ice velocity and strain rate in the short term before and after the great calving in 2017. However, the basal melt rate was mainly influenced by the sea ice extent in front of the LIS from 2010 to 2020. Changes in the sea ice extent indirectly altered the proportion of High Salinity Shelf Water (HSSW) entering the ice shelf bottom water mass, which in turn promoted (or inhibited) basal melting of the LIS. In other words, we found no evidence for any dynamic changes in the LIS before and after the great calving in 2017. Since the calving area was within the Passive Shelf Ice (PSI), we have also provided additional evidence for the existence of the PSI. In addition, we speculate that the impact of calving on the LIS will not be visible in the short term, so we need to continuously observe the subsequent dynamic changes in the LIS.

Beam-based additive manufacturing has challenges in fabricating pure copper due to high reflectivity. Material extrusion additive manufacturing (MEAM) avoids these issues with low costs, making it suitable to fabricate complex structures in pure copper. In this work, the effects of several printing parameters on the geometry of the samples are studied from single line, thin wall to cube using homemade copper feedstocks with high powder loading rate (65 vol%). The results show that the single line is most affected by layer thickness, while the thin wall has stricter requirements for printing temperature and printing speed. The geometric accuracy of the cube demonstrates large parametric tolerance due to the overlap and support between the lines. Central composite face-centered (CCF) design and central composite design (CCD) are used to analyze and optimize process parameters for densification. The measured porosity at the optimized printing (printing temperature = 177 °C, air gap = −0.05 mm, layer thickness = 0.3 mm) and sintering parameters (sintering temperature = 1045 °C, holding time = 4 h) is in good agreement with the predicted values. Air gap and sintering temperature have the greatest influence on the porosity, and other parameters within a certain range of on-demand adjustments do not have a significant effect. The ultimate tensile strength and elongation of the sintered samples under the optimal parameters are 153.9 ± 6.1 MPa and 31.36 ± 3.24%, respectively. No printing defects are found at the fracture and the elongation is good, showing the effectiveness of the parameter optimization.

Abstract Ceracris kiangsu (Orthoptera: Arcypteridae), is greatly affected by climatic factors and exhibits strong adaptability, posing a serious threat to the ecological environment. Therefore, predicting its potential suitable habitat distribution provides a proactive theoretical basis for pest control. This study using the Biomod2 package of R simulated and predicted the current and future potential distribution, area changes, changes in the center points of suitable habitats, and niche shifts of C. kiangsu under two different greenhouse gas emission scenarios, SSP1-26 and SSP5-85. The results show that: (1) Currently, the high suitability areas for C. kiangsu are mainly distributed in Yunnan, Jiangxi, Hunan provinces in southern China and phongsaly province in northern Laos. In the future, the center of the suitable habitat distribution pattern of C. kiangsu will remain unchanged, primarily expanding outward from medium and high suitability areas. Additionally, significant suitable habitats for C. kiangsu were discovered in Southeast Asian countries without previous pest records. (2) Compared to the present, the overall suitable habitat area for C. kiangsu is expected to expand, particularly under the SSP5-85 climate change scenario. (3) In the SSP1-26 and SSP5-85 climate scenarios, the geometric center of the suitable habitat generally shows a trend of gradually shifting northeast. (4) Under different climate scenarios, the suitable habitat of C. kiangsu has highly overlapping, indicating that the suitable habitat of C. kiangsu in the invaded areas is broader than in its native regions. In conclusion, the research findings represent a breakthrough in identifying the potential distribution areas of C. kiangsu, which is of great practical significance for the monitoring and control of C. kiangsu pest infestation in China and Southeast Asian countries.

Abstract Named Entity Recognition (NER) is fundamental in natural language processing, involving identifying entity spans and types within a sentence. Nested NER contains other entities, which pose a significant challenge, especially pronounced in the domain of medical-named entities due to intricate nesting patterns inherent in medical terminology. Existing studies can not capture interdependencies among different entity categories, resulting in inadequate performance in nested NER tasks. To address this problem, we propose a novel Layer-based architecture with Segmentation-aware Relational Graph Convolutional Network (LSRGCN) for Nested NER in the medical domain. LSRGCN comprises two key modules: a shared segmentation-aware encoder and a multi-layer conditional random field decoder. The former part provides token representation including boundary information from sentence segmentation. The latter part can learn the connections between different entity classes and improve recognition accuracy through secondary decoding. We conduct experiments on four datasets. Experimental results demonstrate the effectiveness of our model. Additionally, extensive studies are conducted to enhance our understanding of the model and its capabilities.

Low carbon medium manganese steel with chromium and molybdenum addition (4MnCM), alongside a control group without these additions (4Mn), was developed. The quenching (860 °C) and tempering (620 °C) heat treatment process was applied to both steel groups. The influence of Cr and Mo on the microstructure evolution and mechanical properties was examined. The findings revealed that, the low−temperature impact energy values (KV2) of 4MnCM at −60 and −84 °C were enhanced by 104 and 107 J, in comparison to 4Mn. The yield and tensile strength saw an increase of 100 MPa. The higher low-temperature toughness of 4MnCM is attributed, on one hand, to the addition of Cr and Mo, which inhibiting deformation twinning through enhances the stacking fault energy (SFE) of reversed austenite. On the other hand, it is due to the absence of coarse ε−martensite (ε−m) along the crack propagation path. Additionally, the phase transformation of reversed austenite occurs at the crack nucleation stage during the impact process of both steels, which helps alleviate stress concentration and increases the energy required for crack formation. The primary reason for the higher strength of 4MnCM lies in the significant enhancement of precipitation strengthening effects through the precipitation of M6C, M23C6 and Nb/TiC co-precipitation with M6C.

This work introduced the effects of higher tempering temperatures on the microstructural evolution of Cu − bearing medium Mn steel. After quenching steel at 860 °C for 1 h, it was tempered at 600, 640, and 670 °C for 2 h. The results indicated that the low − temperature impact toughness initially increased and then decreased, while the yield strength consistently decreased with increasing temperature. At a tempering temperature of 640 °C, the steel exhibited a relatively high content of reversed austenite and demonstrated the best low − temperature toughness and plasticity. The low − temperature toughness and plasticity of the steel significantly diminished, when the temperature exceeded 640 °C. This is because the degree of alloying element enrichment in the reversed austenite is reduced, accompanied by an increase in dislocation density and the formation of twins. These reversed austenites exhibit a diminished ability to hinder crack nucleation and propagation. The yield strength decreased with increasing temperature, primarily due to the coarsening of the Cu particles, which reduces their precipitation strengthening effect. This study advances the development of high − strength tough medium − manganese steels.

The evolution of crevasses on ice shelves plays a pivotal role in maintaining their stability. Investigating the developmental pattern of crevasses on ice shelf surfaces necessitates long-term dynamic monitoring, high-precision automatic extraction algorithms, and quantitative analysis tools. Accordingly, based on characteristics such as the long span of crevasses and their meandering distribution, we proposed Strip_Unet for the identification of crevasses. Within this, the Strip_block module utilizes strip convolution in conjunction with traditional convolution to capture the contextual information from the surrounding area, and the ASPP module is used to enhance the receptive field. Leveraging this model, we successfully identified crevasses within the damaged area of the Amery Ice Shelf from 2003 through 2023, utilizing 15-meter resolution Landsat imagery. Subsequently, we retrieved the depth details of these crevasses by applying ATL06 data, allowing us to quantitatively assess the evolution of crevasses. Our study represents the first investigation into the development of the damage area on the Amery Ice Shelf through long-term time-series analysis. Our findings indicate that crevasses originate from specific areas and follow recurring propagation cycles, exhibiting a consistent annual increase in total length. Additionally, changes in the width of these crevasses coincide with alterations in their depth. Notably, the downstream regions of the damaged area demonstrate higher crevasses density and the fastest movement speed. The proposed automatic identification of crevasses and three-dimensional dynamic monitoring hold significant potential for application throughout the Antarctic region, providing valuable insights into the long-term stability of ice shelves.

Ice surface temperature (IST) plays a fundamental role in the Antarctic ice sheet/shelf study. However, the production of spatially and temporally continuous Antarctic IST products remains a challenge. We proposed an instantaneous IST retrieval framework that can generate the spatially and temporally continuous Antarctic IST using Advanced Microwave Scanning Radiometer 2 data. To generate a temporally continuous IST product, we developed an innovative scheme, which was based on the acquisition time difference between input and output data. We considered the impact of terrain and sensor observation state. The corresponding parameters were used as the auxiliary variables to improve the model accuracy. We trained and validated nine machine learning models using the generated sample set. The Light Gradient Boosting Machine (LightGBM) model presents the best performance, and the root-mean-square error (RMSE) of the LightGBM model is only half of that of the typical linear models. The RMSE of the LightGBM model decreased with the training sample set size and stabilized at 1.67 K. Further validation using multisource data showed that the IST retrieved using the LightGBM model has RMSEs of 1.39–2.32 K (relative to IST from Landsat-8) and 3.7–5.9 K (relative to IST from Baseline Surface Radiation Network data). Compared to the commonly used ERA5 IST data, the retrieved IST in this study has higher accuracy. We retrieved Antarctic IST from 2013 to 2020. Antarctic IST decreased continuously from 2013 to 2015. After 2015, Antarctic IST increased with large fluctuations.

The surface velocity of the Amery Ice Shelf (AIS) is vital to assessing its stability and mass balance. Previous studies have shown that the AIS basin has a stable multi-year average surface velocity. However, spatiotemporal variations in the surface velocity of the AIS and the underlying physical mechanism remain poorly understood. This study combined offset tracking and DInSAR methods to extract the monthly surface velocity of the AIS and obtained the inter-annual surface velocity from the ITS_LIVE product. An uneven spatial distribution in inter-annual variation in the surface velocity was observed between 2000 and 2022, although the magnitude of variation was small at less than 20.5 m/yr. The increase and decrease in surface velocity on the eastern and western-central sides of the AIS, respectively, could be attributed to the change in the thickness of the AIS. There was clear seasonal variation in monthly average surface velocity at the eastern side of the AIS between 2017 and 2021, which could be attributed to variations in the area and thickness of fast-ice and also to variations in ocean temperature. This study suggested that changes in fast-ice and ocean temperature are the main factors driving spatiotemporal variation in the surface velocity of the AIS.

A fault on the DC side of a flexible HVDC system, along with the rise in short-circuit current, develops rapidly. With the gradual expansion of flexible HVDC technology to large capacities and long-distance transmission and offshore transmission scenarios, the problem of short-circuit current calculation considering the characteristics of line distribution parameters needs urgent attention. Therefore, in order to solve the problem of the inaccurate calculation of the short-circuit current on the DC side, the lumped parameter model is used in a flexible DC system for long-distance transmission. This study analyzes the transmission line structure on the basis of the general model of the MMC short-circuit current calculation on the DC side and establishes a mathematical model of a long-distance transmission line considering the characteristics of distributed parameters. Two impedance equivalent models for different length lines are proposed to facilitate the analytical calculation of the short-circuit current. A short-circuit current calculation method for a flexible HVDC system with long-distance transmission lines is proposed. Additionally, the correctness of the proposed method is verified through the comparison of the simulation values and calculation values. The results show that the error of the lumped parameter calculation is about 10%, and the error of the distributed parameter calculation is less than 2%.

Background: Rab3a regulates vesicle secretion and transport. Emerging evidences have shown that extracellular vesicles (EVs) can reach target lesions of injured spinal cords and exert a positive effect on these lesions. However, the molecular mechanism by which Rab3a regulates vesicle secretion to ameliorate spinal cord injury (SCI) is not fully understood. Methods: An SCI rat model was established which was used to examine the pathological changes and Rab3a expression in spinal cord tissue. Rab3a was overexpressed in the model rats to demonstrate its effect on SCI repair. Rab3a was also knocked down in neuronal cells to verify its role in vesicle secretion and neuronal cells. The binding protein of Rab3a was identified by Co-IP and mass spectrometry. Results: Rab3a was significantly downregulated in SCI rats and Rab3a overexpression promoted SCI repair. Rab3a knockdown inhibited the secretion of neuronal cell-derived EVs. Compared to the EVs from the equal number of control neuronal cells, EVs from Rab3a-knockdown neuronal cells promoted M1 macrophage polarization, which in turn, promoted neuronal cell apoptosis. Mechanistically, STXBP1 was identified as a binding protein of Rab3a, and their interaction promoted the secretion of neuronal cell-derived EVs. Furthermore, METTL2b was significantly downregulated in SCI rats, and METTL2b knockdown significantly reduced Rab3a protein expression. Conclusion: These results suggest that Rab3a promotes the secretion of neuronal cell-derived EVs by interacting with its binding protein STXBP1. Neuronal cells-derived EVs inhibited the polarization of M1 macrophages in the spinal cord microenvironment, thereby promoting SCI repair. Our findings provide a theoretical basis for the clinical treatment of SCI.

Abiotic/biotic stresses pose a major threat to agriculture and food security by impacting plant growth, productivity and quality. The discovery of extensive transcription of large RNA transcripts that do not code for proteins, termed long non-coding RNAs (lncRNAs) with sizes larger than 200 nucleotides in length, provides an important new perspective on the centrality of RNA in gene regulation. In plants, lncRNAs are widespread and fulfill multiple biological functions in stress response. In this paper, the research advances on the biological function of lncRNA in plant stress response were summarized, like as Natural Antisense Transcripts (NATs), Competing Endogenous RNAs (ceRNAs) and Chromatin Modification etc. And in plants, lncRNAs act as a key regulatory hub of several phytohormone pathways, integrating abscisic acid (ABA), jasmonate (JA), salicylic acid (SA) and redox signaling in response to many abiotic/biotic stresses. Moreover, conserved sequence motifs and structural motifs enriched within stress-responsive lncRNAs may also be responsible for the stress-responsive functions of lncRNAs, it will provide a new focus and strategy for lncRNA research. Taken together, we highlight the unique role of lncRNAs in integrating plant response to adverse environmental conditions with different aspects of plant growth and development. We envisage that an improved understanding of the mechanisms by which lncRNAs regulate plant stress response may further promote the development of unconventional approaches for breeding stress-resistant crops.

Abstract Background Based on the results of existing observational studies, it can be found that the association between serum vitamin D levels and the risk of Sjogren’s syndrome (SS) in humans is still controversial. Based on this situation, this study aimed to assess the causal relationship between serum vitamin D levels and SS by using the Mendelian randomization (MR) approach. Methods In this study, genome-wide association studies (GWAS) summary statistics on serum vitamin D levels [sample size = 417,580 (UK Biobank)] and SS [sample size = 416,757 (cases = 2495, controls = 414,262) (FinnGen)] were used. The bi-directional MR analysis was then used to assess possible causal relationships. The major analysis method of MR was performed using inverse-variance weighted (IVW), supplemented by MR-Egger and the weighted median approaches. In addition, sensitivity analyses were used to ensure the stability of the results, including Cochran’s Q test, MR-PRESSO, MR-Egger intercept test, and the leave-one-out test. Results The MR suggested that no significant causal effects of serum 25(OH)D levels on SS risks were observed [odds ratio (OR) = 0.9824; 95% confidence interval (CI) = 0.7130 to 1.3538; P = 0.9137]. Similarly, no evidence supported the causal effects of SS on serum vitamin D levels (β: 0.0076, 95% CI: − 0.0031 to 0.0183; P = 0.1640). Conclusion This study found no obvious evidence that serum vitamin D level is causally associated with SS risks or vice versa. We call for larger sample size studies to further unravel the potential causal relationship and the exact mechanism.

Abstract Despite ongoing debate, the amyloid β-protein (Aβ) remains the prime therapeutic target for the treatment of Alzheimer’s disease (AD). However, rational drug design has been hampered by a lack of knowledge about neuroactive Aβ. To help address this deficit, we developed live-cell imaging of iPSC-derived human neurons (iNs) to study the effects of the most disease relevant form of Aβ-oligomeric assemblies (oAβ) extracted from AD brain. Of ten brains studied, extracts from nine caused neuritotoxicity, and in eight cases this was abrogated by Aβ immunodepletion. Here we show that activity in this bioassay agrees relatively well with disruption of hippocampal long-term potentiation, a correlate of learning and memory, and that measurement of neurotoxic oAβ can be obscured by more abundant non-toxic forms of Aβ. These findings indicate that the development of novel Aβ targeting therapeutics may benefit from unbiased activity-based discovery. To test this principle, we directly compared 5 clinical antibodies (aducanumab, bapineuzumab, BAN2401, gantenerumab, and SAR228810) together with an in-house aggregate-preferring antibody (1C22) and established relative EC50s in protecting human neurons from human Aβ. The results yielded objective numerical data on the potency of each antibody in neutralizing human oAβ neuritotoxicity. Their relative efficacies in this morphological assay were paralleled by their functional ability to rescue oAβ-induced inhibition of hippocampal synaptic plasticity. This novel paradigm provides an unbiased, all-human system for selecting candidate antibodies for advancement to human immunotherapy.

Objectives: To systematically summarize and compare the health management projects on the aged population funded by the National Institutes of Health (NIH) in the US and the National Natural Science Foundation of China (NSFC) in China. Methods: All elderly-related projects from 2007 to 2022 were retrieved by searching the project titles, abstracts, and keywords such as “older adults,” “elderly,” “aged,” “health management,” and so on. Python, CiteSpace, and VOSviewer were used to extract, integrate, and visualize the relevant information. Results: A total of 499 NSFC projects and 242 NIH projects were retrieved. For both countries, prestigious universities and institutions received the most funded projects; the projects that got the most funds were longitudinal studies. Both countries attach great importance to investment in the health management of the aged population. However, different focuses existed in health management projects for older adults in the two countries due to distinct national conditions and development levels. Conclusions: The analysis results of this study can provide a reference for other countries with similar challenges of population aging. Effective measures should be taken to promote the transformation and implementation practice of the project achievements. Nurses can benefit from these projects and facilitate the translation of relevant research findings into clinical practice to improve nursing quality for older adults.

Herein, graphite/copper (Gr/Cu) composites were fabricated by mechanical mixing and microwave sintering to investigate the effect of graphite volume fraction on the thermal conductivity (TC) and coefficient of thermal expansion (CTE) of the Gr/Cu composite. The TC and CTE of the composites were measured in the in-plane and through-plane directions. The obtained results revealed that the graphite volume fraction significantly affects the TC and CTE of Gr/Cu composites. A lower volume fraction led to higher thermal properties. The effect of thermal cycling on the thermal properties of metal matrix composites (MMCs) has remained largely unexplored. In this work, the effect of thermal cycling on the thermal properties of MMCs was investigated in a temperature range of −196°C/+200 °C. The thermal cycling resulted in a staged decrease of TC and a gradual increase in CTE. This could be mainly attributed to the CTE mismatch between the Cu matrix and the Gr phase. Observations by scanning electron microscopy (SEM) showed that thermal cycling created the micro-cracks and micro-voids in the composites, as well as the sliding and detachment of the Gr/Cu interface. The distribution of thermal stress and plastic strain during thermal cycling was simulated by the finite element method. The changes in TC and CTE are discussed regarding thermally induced stress.

The basal channel is a morphological feature that widely exists at the bottom of ice shelves, which is mainly formed by the incision of warm water at the base of ice shelves. The study of the basal channel can contribute to further understanding the impact of global warming on polar ice shelves. In this article, the depression caused by the basal channel on the surface of an ice shelf is used to confirm and extract the channel's position. The automatic acquisition of the channel is realized by machine learning. To extract the basal channel more efficiently and minimize the subjectivity caused by visual interpretation, a neural network was applied for the first time, which effectively improved the accuracy of basal channel extraction. We took the manual extraction results of basal channels as the training set input from the model. The improved U-NET network model was used to classify the 79NG ice shelf area, and the extraction accuracy was 73.58%. Then, the trained model was extended to the Peterman ice shelf and Ryder ice shelf located in Greenland. The extraction accuracies were 75.54% and 72.70%, respectively.

Lung cancer remains the most common malignancy in China. This study aims to provide scientific support for the prevention and treatment of lung cancer by analyzing the epidemiological trends of lung cancer in China from 1990 to 2019. Based on the global health exchange database (GHDx), joinpoint and age-period-cohort analyses were performed to explore the trend of lung cancer incidence and mortality rates from 1990 to 2019. According to incidence rates from 1990 to 2019, a model was constructed to predict the incidence rates in the next 5 years. In addition, changes in risk factors associated with lung cancer deaths were compared between 1990 and 2019 and between males and females in 2019. The results are as follows. The age-standardized incidence rates (ASIRs), and age-standardized death rates (ASDRs) of lung cancer among Chinese had overall upward trends from 1990 to 2019. The ASDRs of females and males in China decreased since 2010. Interestingly, from 2016 to 2019, the ASIRs and ASDRs of females rose significantly. The age-period-cohort model showed that the incidence and mortality rates of lung cancer in China increased with age, and the growth rate accelerated after 45 years old. After 2004, the relative risks of lung cancer incidence increased with the passage of the period. Also, after the 1950–1954 birth cohort, the risks of lung cancer incidence and death began to decrease. The autoregressive integrated moving average (ARIMA) model predicted that the incidence rates of lung cancer in China would continue to rise in the next 5 years. The top five risk factors for lung cancer deaths of both genders in 2019 were smoking, ambient particulate matter pollution, secondhand smoke, high fasting plasma glucose, and household air pollution from solid fuels. The above results provided precise clues for the prevention and treatment of lung cancer in China.

Solar radiation drives many geophysical and biological processes in Antarctica, such as sea ice melting, ice sheet mass balance, and photosynthetic processes of phytoplankton in the polar marine environment. Although reanalysis and satellite products can provide important insight into the global scale of solar radiation in a seamless way, the ground-based radiation in the polar region remains poorly understood due to the harsh Antarctic environment. The present study attempted to evaluate the estimation performance of empirical models and machine learning models, and use the optimal model to establish a 35-year daily global solar radiation (DGSR) dataset at the Great Wall Station, Antarctica using meteorological observation data during 1986–2020. In addition, it then compared against the DGSR derived from ERA5, CRA40 reanalysis, and ICDR (AVHRR) satellite products. For the DGSR historical estimation performance, the machine learning method outperforms the empirical formula method overall. Among them, the Mutli2 model (hindcast test R2, RMSE, and MAE are 0.911, 1.917 MJ/m2, and 1.237 MJ/m2, respectively) for the empirical formula model and XGBoost model (hindcast test R2, RMSE, and MAE are 0.938, 1.617 MJ/m2, and 1.030 MJ/m2, respectively) for the machine learning model were found with the highest accuracy. For the austral summer half-year, the estimated DGSR agrees very well with the observed DGSR, with a mean bias of only −0.47 MJ/m2. However, other monthly DGSR products differ significantly from observations, with mean bias of 1.05 MJ/m2, 3.27 MJ/m2, and 6.90 MJ/m2 for ICDR (AVHRR) satellite, ERA5, and CRA40 reanalysis products, respectively. In addition, the DGSR of the Great Wall Station, Antarctica followed a statistically significant increasing trend at a rate of 0.14 MJ/m2/decade over the past 35 years. To our best knowledge, this study presents the first reconstruction of the Antarctica Great Wall Station DGSR spanning 1986–2020, which will contribute to the research of surface radiation balance in Antarctic Peninsula.

This study explores the ice volumes of Urumqi Glacier No. 1 from 2013 to 2112 to examine the changes in the runoff of the glacier. Based on the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), the changes of the glacier were predicted under three hypothetical climate scenarios: SSP1-1.9, SSP2-4.5, and SSP5-8.5 scenarios. The results derived from the Elmer/Ice ice-flow model showed increasing runoff till 2040 in the SSP2-4.5 and SSP5-8.5 scenarios and gradually decreasing runoff in the SSP1-1.9 scenario. The glacier areas and ice volumes of the two branches will keep declining under all the climate scenarios, including fast reductions until 2080 and slow reductions by the end of the ablation period. Moreover, the east branch (EB) will disappear at the end of the 21st century under the SSP2-4.5 and SSP5-8.5 scenarios. With much mass loss of the EB under all the climate scenarios, the runoff will increase in the early 100-year period and decrease until it is being infinitely close to the precipitation, which is similar with that of the west branch (WB). Since 2070, the ice volumes of the WB will contribute more than 50% of the whole glacier volumes under all the climate scenarios. The WB ice volume percentage will reach 100% in 2080 for the disappearance of the EB under the SSP5-8.5 scenario. As the fast retreat of the EB before 2080, the variations of the total runoff will be consistent with that of the EB runoff, and the EB runoff will account for more than 60% of the total runoff before 2070 under all the climate scenarios. Even if the meltwater of Urumqi Glacier No. 1 is stable from the late 21st century (after 2090), it will decline to approximately 15% of that in 2013. It will greatly influence the runoff of Urumqi River, hence human life and biodiversity.

Human immunodeficiency virus-type 1 (HIV-1) CRF01_AE/B recombinants are newly emerging strains that are spreading rapidly in Southern and Eastern China. This study aimed to elucidate the molecular epidemiological characteristics of HIV-1 CRF01_AE/B recombinants in Nanjing and to explore the impact of these novel strains on the immunological status. A total of 1,013 blood samples from newly diagnosed HIV-1-infected patients were collected in Nanjing from 2015 to 2019, among which 958 partial Pol sequences were sequenced successfully. We depicted the molecular epidemiological characteristics of CRF01_AE/B recombinants by the molecular evolutionary analysis, Bayesian system evolution analysis, and transmission network analysis. The generalized additive mixed model was applied to evaluate the CD4+ T-cell count change of CRF01_AE/B recombinants. The Kaplan–Meier analysis was performed to assess the time from combined antiretroviral therapy (cART) initiation to immune reconstruction. We have identified 102 CRF01_AE/B recombinants (102/958, 10.65%) in Nanjing, including CRF67_01B (45/102, 44.12%), CRF68_01B (35/102, 34.31%), and CRF55_01B (22/102, 12.57%). According to the Bayesian phylogenetic inference, CRF55_01B had a rapid decline stage during 2017–2019, while CRF67_01B and CRF68_01B have experienced a fast growth phase during 2014–2015 and then remained stable. We have constructed 83 transmission networks, in which three larger clusters were composed of CRF67_01B and CRF68_01B. CRF01_AE/B recombinants manifested a faster decrease rate of CD4+ T-cell count than CRF_07BC but similar to CRF01_AE. The probability of achieving immune reconstruction in CRF01_AE/B recombinants was lower than CRF07_BC in the subgroup of baseline CD4+ T-cell count at cART initiation

Coordinated transcriptional regulation of stress-responsive genes orchestrated by a complex network of transcription factors (TFs) and the reprogramming of metabolism ensure a plant’s continued growth and survival under adverse environmental conditions (e.g., abiotic stress). DNA-binding with one finger (Dof) proteins, a group of plant-specific TF, were identified as one of several key components of the transcriptional regulatory network involved in abiotic stress responses. In many plant species, Dofs are often activated in response to a wide range of adverse environmental conditions. Dofs play central roles in stress tolerance by regulating the expression of stress-responsive genes via the DOFCORE element or by interacting with other regulatory proteins. Moreover, Dofs act as a key regulatory hub of several phytohormone pathways, integrating abscisic acid, jasmonate, SA and redox signaling in response to many abiotic stresses. Taken together, we highlight a unique role of Dofs in hormone and stress signaling that integrates plant response to adverse environmental conditions with different aspects of plant growth and development.

Multi-objective optimisation of the bio-inspired lightweight structure is developed by response surface methodology (RSM) and non-dominated sorting genetic algorithm II (NSGA-II) for future applications in the aerospace and military fields. Multilayer bio-inspired sandwich structures of Ti6Al4V alloy are designed and fabricated by selective laser melting (SLM). Results show that the bio-inspired sandwich structures can be optimized by RSM and NSGA-II with a relative error rate of experiment and response value less than 10%. The bio-inspired sandwich structures with different core-arranged configurations were destroyed layer by layer under out-of-plane loadings with a primary failure mode of the core breaking. Increasing the layer number of cores can improve the comprehensive mechanical performances of multilayer bio-inspired sandwich structures with cross-arranged configurations but will decrease the energy absorption capacity of those with parallel-arranged configurations. Furthermore, the two-layered bio-inspired sandwich structure under cross-arranged configurations has the most excellent comprehensive performances with the specific energy absorption of 9.16 × 103 J/kg and the energy absorption of 154.80 J, respectively.

Global Positioning System (GPS) signals are delayed when passing through the ionosphere due to an ionospheric refraction effect. The ionospheric-free linear combination of GPS signals can eliminate most of the error caused by the first-order ionospheric term. However, the influence of higher-order ionospheric terms remains, and it should be accounted for when conducting high-precision geodetic applications. In this study, we use data from twenty-one GPS continuous operating stations from different observing networks distributed in Antarctica and analyze the effect of the second-order ionospheric term on GPS positioning during the whole year for 2012. Results show that the effect on these stations is at the level of submillimeters to millimeters, and the effect in summer is several times higher than it is in winter. In addition, this effect is found to be positively correlated to the change of the total electron content over the Antarctic continent. On the other hand, all of the stations show the southward and upward movements derived from the effect. The common and seasonal displacement trends displayed in the Antarctic region should not be ignored in future high-precision research or applications but should be brought to attention, especially when total electron content in the ionosphere is high.

This study focused on the role of Cu in the microstructure characteristics and tensile properties of novel L12-strengthened multicomponent high-entropy alloys (HEAs). A series of as-cast (Al7.5Co21.9Cr10.9Ti5.0Fe21.9Ni32.8)100-xCux (x = 0.5, 2.5, 5.0) high-entropy alloys (HEAs) were prepared. The microstructures and mechanical properties of HEAs were investigated using X-ray diffraction, a scanning electron microscope, a transmission electron microscope, and atom probe tomography. The XRD patterns of HEAs confirmed that all HEAs consisted of the FCC phase and the L12 phase. As Cu content increased, the dendritic was gradually coarsened. The spherical L12 size decreased, and number density increased in the interdendritic regions (ID). The L12 mainly contained Ni, Ti, Al, and Cu. The acicular L12 size increased and was continuously distributed in the dendritic regions (DR) as the Cu content increased gradually. The ultimate strength and elongation decreased from 1,002 MPa, 20.0% to 906 MPa, 13.1%, respectively. The segregation rates of Ti, Cu, and Al increased in the DR and ID. The L12 nano-precipitates in the DR become denser and finer, while the L12 islets in the ID region increase and elongate. Large lattice distortion caused by Cu addition weakens the strength of the L12-FCC phase boundary, leading to the premature fracture of the three HEAs, which were the main reasons for the decreases in strength and ductility as Cu content increased.

Selective laser melting (SLM) has been used to fabricate a Ti-40Al-9V-0.5Y alloy with high crack sensitivity, the effect of SLM process parameters on morphology, sectional characteristics and crack sensitivity of the as-deposited single tracks are investigated. It is found that the balling effect arises on single tracks with the increase of scanning velocity when other parameters are fixed, due to the significant Marangoni convection and liquid capillary instability. With the increase of scanning velocity, width, depth and aspect ratio of molten pools decrease while contact angle increases. With the increase of defocusing distance, width increases while depth and aspect ratio decrease. Layer thickness has little effect on the width, depth and aspect ratio as well as has a positive correlation with contact angle. The effect of process parameters on crack sensitivity of single tracks strongly depends on the laser volume energy density. Cracks can be suppressed by optimizing SLM process parameters to enhance laser volume energy density. Finally, the optimized process window of Ti-40Al-9V-0.5Y single tracks produced by SLM is determined, providing a valuable reference for the formation of bulk samples without cracks. Keywords: Selective laser melting, Titanium aluminide alloy, Process parameter, Crack sensitivity, Single track

To study Arctic valley glacier responses to global climate change, the Elmer/Ice ice-flow model was used to investigate long-term changes in Austre Lovénbreen, a typical polythermal glacier in Svalbard. Evolution and features, including volume, area, ice thickness, runoff and time and mode of glacier disappearance, were projected. Firstly, steady-state simulations were performed to determine the best parameters for the ice-flow model, which were then used to simulate glacial dynamics. Based on the 21st-century Arctic warming trend in the fifth assessment report published by the Intergovernmental Panel on Climate Change, the evolution of the glacier was simulated under three hypothetical climatic scenarios: pessimistic, high-probability and optimistic. The results predicted that the glacier will retreat until disappearance under all three scenarios, and its disappearance time will likely be approximately 111 years (by 2120). Under all scenarios, glacier volume and area reductions will be slow at first, then fast and finally slow again at the end. In particular, glacial runoff will increase markedly until 2070 in the high-probability scenario, and the peak runoff will be double the current value.

Abstract Background Aerobic exercise has been shown to slow tumor progression in rodents and humans, but the mechanisms behind this effect are still unclear. Here we show that aerobic exercise in the form of chronic endurance training suppresses tumor recruitment of FoxP3+ Treg cells thus enhancing antitumor immune efficiency. Methods Adult wild-type and athymic BALB/c female mice were endurance-trained for 8 weeks. Circulating leukocytes as well as muscle and liver mtDNA copy number were compared to aged-matched concurrent sedentary controls to establish systemic effects. 4 T1 murine mammary tumor cells were injected subcutaneously to the 4th mammary pad at the end of the training period. Tumor growth and survival rates were compared, together with antitumor immune response. Results Exercised wild-type had 17% slower growth rate, 24% longer survival, and 2-fold tumor-CD+ 8/FoxP3+ ratio than sedentary controls. Exercised athymic BALB/c females showed no difference in tumor growth or survival rates when compared to sedentary controls. Conclusions Cytotoxic T cells are a significant factor in endurance exercise-induced suppression of tumor growth. Endurance exercise enhances antitumor immune efficacy by increasing intratumoral CD8+/FoxP3+ ratio.

In January 2016, static GPS measurements were carried out in a 30 × 30 km2 area centered around Kunlun station at Dome Argus (Dome A), East Antarctica, to acquire high-precision 3-D geodetic coordinates at 49 sites. By comparing the coordinates with previous GPS measurements in 2008 and 2013 at the same sites, we constructed a detailed and long-term record of the ice-surface velocity field, 2008–2016, around Dome A. During this time span, the estimated ice-surface velocity ranges from 0.8 ± 0.3 to 28.7 ± 1.6 cm a−1, with a mean of 10.4 ± 0.3 cm a−1. From 2013 to 2016, the surface elevation of most Dome A areas exhibits a rising trend, and the maximum increase of snow surface elevation is 84.8 cm. The mean snow surface elevation change rate at Dome A is estimated to be 6.6 ± 0.7 cm a−1. The difference of 1.0 cm a−1 between the snow surface change rate derived from GPS and pole-height change rate from surface mass balance is suspected to be a result of a combination of firn densification and basal melt under Dome A.

Two-year toxicology and carcinogenesis rodent studies conducted at the National Toxicology Program (NTP) are used to identify potential adverse health effects in humans due to chemical exposure, including cancer. Liver tumor, the most frequently diagnosed tumor type of chemically induced neoplastic effects documented in NTP’s carcinogenicity studies, is usually difficult to be detected at early stage due to the inconspicuous symptoms. However, the abnormal growth of liver cells can lead to liver weight increase, so it is hypothesized that liver tumor incidence is associated with early stage liver weight increase. In this study, the association between liver weight increase and liver tumor incidence are quantified by (1) calculating the correlation coefficient of and (2) building quantitative linear relationship between benchmark dose estimates derived from these two types of data collected from NTP studies. Together with 151 chemical/species/sex combinations of liver tumor data showing positive evidence collected from 76 NTP long-term studies, short-term liver weight data reported in the same NTP report were extracted to be paired with the liver tumor data for the analyses. Results show that the estimated correlation coefficients (as high as 0.78) along with the adequately fitted linear models suggest that the association between relative liver weight increase and aggregated liver tumor incidence are relatively strong. Additional analyses focused on some more specific situations (e.g., specific tumor type or specific strain/sex combination) further confirmed the strong association. Given the design of this study, the interpretation of the findings is not that liver weight increase can be used to predict liver tumor incidence, instead, evident increase in liver weight might be used as a reason to prioritize the test article for a two-year toxicology and carcinogenesis study. Keywords: Risk assessment, Liver tumor, Liver weight, Carcinogenicity, Benchmark dose, NTP

Despite the development of treatment options in breast cancer, many patients die of recurrence and metastasis. Owing to enhanced permeability and retention in solid tumor tissue, nanoparticle (NP) delivery systems have been emerged as novel strategy in cancer chemotherapy. As extracellular matrix, glycosaminoglycan hyaluronan (HA) could bind its surface receptor adhesion molecule CD44 which is strongly expressed on breast cancer. We have previously reported a doxorubicin (DOX)-loaded HA-Lys-LA X-NPs (X-NP-DOX) NP delivery system for breast cancer treatment. In this study, we further investigated the antitumor effect of X-NP-DOX NP delivery system using low-dose DOX in both in vitro and in vivo systems. We demonstrated that low-dose X-NP-DOX possessed the ability for inhibiting MCF-7 breast cancer cell growth, invasion, and migration, and inducing apoptosis in vitro. In in vivo experiments, injection of low-dose X-NP-DOX into tumor-bearing mouse resulted in significant reduction of tumor size. Terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling staining further revealed that low-dose X-NP-DOX induced higher percentage of apoptotic cells compared with free DOX or saline. Furthermore, our study demonstrated that low-dose X-NP-DOX inhibited Notch1 and Ras/MAPK pathways, decreased cancer stem cell population, and reduced tumorigenesis compared to free DOX in both in vitro and in vivo settings. Owing to its enhanced efficacy and higher targetability compared to free DOX, low-dose DOX delivered by NP system may be a promising novel strategy for breast cancer treatment.

Alzheimer’s disease (AD) is a destructive and burdensome neurodegenerative disease, one of the most common characteristics of which are neurofibrillary tangles (NFTs) that are composed of abnormal tau protein. Animal studies have suggested that dl-3-n-butylphthalide (dl-NBP) alleviates cognitive impairment in mouse models of APP/PS1 and SAMP8. However, the underlying mechanisms related to this remain unclear. In this study, we examined the effects of dl-NBP on learning and memory in P301S transgenic mice, which carry the human tau gene with the P301S mutation. We found that dl-NBP supplementation effectively improved behavioral deficits and rescued synaptic loss in P301S tau transgenic mice, compared with vehicle-treated P301S mice. Furthermore, we also found that it markedly inhibited the hyperphosphorylated tau at the Ser262 site and decreased the activity of MARK4, which was associated with tau at the Ser262 site. Finally, dl-NBP treatment exerted anti-inflammatory effects and reduced inflammatory responses in P301S mice. In conclusion, our results provide evidence that dl-NBP has a promising potential for the therapy of tauopathies, including AD.

In the traditional heap leaching of rare earth minerals, the top of the rare earth pile is covered with leaching liquid. This creates trouble for vegetation restoration carried out timely on the top of the pile. In order to solve this trouble, a novel pile structure into which leaching liquid is laterally injected is proposed for heap leaching of rare earth. In this study, a laboratory test is carried out to study the formation and distribution of preferential flow paths for the rare earth pile under a horizontal liquid injection condition. Furthermore, numerical simulations based on a dual-permeability model are conducted to investigate the influence of the preferential flow paths on the seepage characteristics in the rare earth pile. The results show that, under the horizontal liquid injection condition, the fine particles of the rare earth move away from the liquid injection end and also toward the lower part of the pile. The migration of the fine particles results in the formation and connection of macropore, thereby generating preferential flow paths in the rare earth pile. The preferential flow paths are mainly distributed in the lower part of the pile near the liquid injection end. This causes the fluid in the lower part of the pile to seep faster significantly than that in the upper part. Within the region where the preferential flow paths develop, the seepage in the early stage of the horizontal liquid injection is dominated by preferential flow. The preferential flow is more significant at the locations farther away from the liquid injection end.

With increasing public concerns on air pollution in China, there is a demand for long-term continuous PM2.5 datasets. However, it was not until the end of 2012 that China established a national PM2.5 observation network. Before that, satellite-retrieved aerosol optical depth (AOD) was frequently used as a primary predictor to estimate surface PM2.5. Nevertheless, satellite-retrieved AOD often encounter incomplete daily coverage due to its sampling frequency and interferences from cloud, which greatly affect the representation of these AOD-based PM2.5. Here, we constructed a virtual ground-based PM2.5 observation network at 1180 meteorological sites across China using the Extreme Gradient Boosting (XGBoost) model with high-density meteorological observations as major predictors. Cross-validation of the XGBoost model showed strong robustness and high accuracy in its estimation of the daily (monthly) PM2.5 across China in 2018, with R2, root-mean-square error (RMSE) and mean absolute error values of 0.79 (0.92), 15.75 μg/m3 (6.75 μg/m3) and 9.89 μg/m3 (4.53 μg/m3), respectively. Meanwhile, we find that surface visibility plays the dominant role in terms of the relative importance of variables in the XGBoost model, accounting for 39.3% of the overall importance.We then use meteorological and PM2.5 data in the year 2017 to assess the predictive capability of the model. Results showed that the XGBoost model is capable to accurately hindcast historical PM2.5 at monthly (R2 = 0.80, RMSE = 14.75 μg/m3), seasonal (R2 = 0.86, RMSE = 12.28 μg/m3), and annual (R2 = 0.81, RMSE = 10.10 μg/m3) mean levels. In general, the newly constructed virtual PM2.5 observation network based on high-density surface meteorological observations using the Extreme Gradient Boosting model shows great potential in reconstructing historical PM2.5 at ~1000 meteorological sites across China. It will be of benefit to filling gaps in AOD-based PM2.5 data, as well as to other environmental studies including epidemiology.

Background: PM2.5 pollution waves (PPWs) are severe air pollution events with extremely high-level concentration of ambient PM2.5. PPWs, such as haze days, were suggested to be associated with increased cardiopulmonary mortality and morbidity. However, the biological mechanism response to ambient PM2.5 during PPWs is still unclear. Methods: A randomized crossover trial was conducted on 29 healthy young adults. Repeated health measurements were performed before, during and after two typical PPWs under filtered and sham indoor air purification, with a washout interval of at least 2 weeks. Health parameters including blood pressure (BP), pulmonary function, fractional exhaled nitric oxide (FeNO) and circulating biomarkers which reflect platelet activation, blood coagulation and systematic oxidative stress were measured. Results: Ambient PM2.5 levels elevated apparently during PPWs. Under sham purification, significant increase in FeNO and soluble P-selectin (sP-selectin) and decreases in pulmonary function were observed from pre-PPWs period to during-PPWs period. The changes in health biomarkers as mentioned above became attenuated and insignificant under filtered condition. For instance, sP-selectin increased by 12.0% (95% CI: 3.8%, 20.8%) during-PPWs periods compared with pre-PPWs periods under sham purification, while non-significant change was observed under filtered condition. Significant associations between time-weighted personal PM2.5 exposure and increased levels of health biomarkers including FeNO, sP-selectin, oxidized low-density lipoprotein (ox-LDL) and 8-isoprostane (8-isoPGF2α) were found. Conclusion: PPWs could affect cardiopulmonary health through systematic oxidative stress, platelet activation and respiratory inflammation in healthy adults, and short-term indoor air purification could alleviate the adverse cardiopulmonary effects.

Abstract Accurate estimation of the spatiotemporal variations of solar radiation is crucial for assessing and utilizing solar energy, one of the fastest‐growing and most important clean and renewable resources. Based on observations from 2,379 meteorological stations along with scare solar radiation observations, the random forest (RF) model is employed to construct a high‐density network of daily global solar radiation (DGSR) and its spatiotemporal variations in China. The RF‐estimated DGSR is in good agreement with site observations across China, with an overall correlation coefficient (R) of 0.95, root‐mean‐square error of 2.34 MJ/m2, and mean bias of −0.04 MJ/m2. The geographical distributions of R values, root‐mean‐square error, and mean bias values indicate that the RF model has high predictive performance in estimating DGSR under different climatic and geographic conditions across China. The RF model further reveals that daily sunshine duration, daily maximum land surface temperature, and day of year play dominant roles in determining DGSR across China. In addition, compared with other models, the RF model exhibits a more accurate estimation performance for DGSR. Using the RF model framework at the national scale allows the establishment of a high‐resolution DGSR network, which can not only be used to effectively evaluate the long‐term change in solar radiation but also serve as a potential resource to rationally and continually utilize solar energy.

Drug induced liver injury (DILI) and cell death can result from oxidative stress in hepatocytes. An initial pattern of centrilobular damage in the APAP model of DILI is amplified by communication from stressed cells and immune system activation. While hepatocyte proliferation counters cell loss, high doses are still lethal to the tissue. To understand the progression of disease from the initial damage to tissue recovery or death, we computationally model the competing biological processes of hepatocyte proliferation, necrosis and injury propagation. We parametrize timescales of proliferation (α), conversion of healthy to stressed cells (β) and further sensitization of stressed cells towards necrotic pathways (γ) and model them on a Cellular Automaton (CA) based grid of lattice sites. 1D simulations show that a small α/β (fast proliferation), combined with a large γ/β (slow death) have the lowest probabilities of tissue survival. At large α/β, tissue fate can be described by a critical γ/β* ratio alone; this value is dependent on the initial amount of damage and proportional to the tissue size N. Additionally, the 1D model predicts a minimum healthy population size below which damage is irreversible. Finally, we compare 1D and 2D phase spaces and discuss outcomes of bistability where either survival or death is possible, and of coexistence where simulated tissue never completely recovers or dies but persists as a mixture of healthy, stressed and necrotic cells. In conclusion, our model sheds light on the evolution of tissue damage or recovery and predicts potential for divergent fates given different rates of proliferation, necrosis, and injury propagation.

In the present study, an austenitic stainless steel (2Cr17Ni13Mo5) was processed by severe cold rolling (SCR) and subsequent annealing. The grain size was severely refined to ∼100 nm after SCR. The yield strength (YS) and ultimate tensile strength (UTS) increased to 1510.5 MPa and 1660.4 MPa, respectively. Nevertheless, the ductility decreased significantly. Full recrystallization was completed after annealing at 800 °C for 1h. However, the ultrafine-grained structure was maintained with the grain size of 780 nm, which is mainly attributed to the pinning effect of χ phase precipitated at the grain boundary during annealing. Good comprehensive mechanical properties with high strength (YS = 977.6 MPa, UTS = 1197.7 MPa) and good ductility (elongation = 17%) were obtained. The high strength is mainly attributed to the ultrafine-grained structure maintaining, while the annihilation of dislocation contributes to the ductility improvement.

Ice motion is an essential element for accurately evaluating glacier mass balance. Interferometric synthetic aperture radar (InSAR) has been widely applied for monitoring ice motion with high precision and wide coverage in the Antarctic. However, the ionospheric effects can significantly impact InSAR-based ice-motion measurements. At low radar frequencies in particular, the ionospheric effects have been regarded as a serious source of noise in L-band SAR data. The split-spectrum method (SSM) is commonly used for correcting the ionospheric effects of the InSAR technique. However, it requires spatial filtering with the relatively large factors used to scale the sub-bands’ interferograms, which often results in an unwrapped phase error. In this paper, a reformulation of the split-spectrum method (RSSM) is introduced to correct the ionospheric effects in the Grove Mountains of East Antarctica, which have slow ice flow and frequent ionosphere changes. The results show that RSSM can effectively correct the ionospheric effects of InSAR-based ice-motion measurements. To evaluate the ability of ionospheric correction using RSSM, the result of ionospheric correction derived from SSM is compared with the results of RSSM. In addition, ionosphere-corrected ice motion is also compared with GPS and MEaSUREs. The results show that the ionosphere-corrected ice velocities are in good agreement with GPS observations and MEaSUREs. The average ice velocity from the InSAR time series is compared to that from MEaSUREs, and the average ionosphere-corrected ice velocity error reduces 43.9% in SSM and 51.1% in RSSM, respectively. The ionosphere-corrected ice velocity error is the most significant, reducing 86.9% in SSM and 90.4% in RSSM from 1 November 2007 to 19 December 2007. The results show that the ability of RSSM to correct ionospheric effects is slightly better than that of SSM. Therefore, we deduce that the RSSM offers a feasible way to correct ionospheric effects in InSAR-based ice-motion measurements in Antarctica.

The verification and correction of CALIPSO aerosol products is key to understanding the atmospheric environment and climate change. However, CALIPSO often cannot detect the full profile of aerosol for the low instrument sensitivity near the surface. Thus, a correction scheme for the aerosol extinction coefficient (AECs) in the planetary boundary layer (PBL) is proposed to improve the quality of the CALIPSO-based aerosol optical depth (AOD) at 532 nm. This scheme assumed that the aerosol is vertically and uniformly distributed below the PBL, and that the AECs in the whole PBL are equal to those at the top of the PBL; then, the CALIPSO AOD was obtained by vertically integrating AECs throughout the whole atmosphere. Additionally, the CALIPSO AOD and corrected CALIPSO AOD were validated against seven ground-based sites across eastern China during 2007–2015. Our results show that the initial CALIPSO AOD obtained by cloud filtering was generally lower than that of the ground-based observations. After accounting for the AECs in the PBL, the adjustment method tended to improve the CALIPSO AOD data quality. The average R (slope) value from all sites was improved by 7% (46%). Further, the relative distance between the ground track of CALIPSO and the ground station exhibited an influence on the validation result of CALIPSO AOD. The retrieval precision of CALIPSO AOD worsened with the increase in water vapor in the atmosphere. Our findings indicate that our scheme significantly improves the accuracy of CALIPSO AOD, which will help to provide alternative AOD products in the presence of severe atmospheric pollution.

This study explores an iterative method for simultaneously estimating the present-day glacial isostatic adjustment (GIA), ice mass change and elastic vertical crustal deformation of the Antarctic ice sheet (AIS) for the period October 2003–October 2009. The estimations are derived by combining mass measurements of the GRACE mission and surface height observations of the ICESat mission under the constraint of GPS vertical crustal deformation rates in the spatial domain. The influence of active subglacial lakes on GIA estimates are mitigated for the first time through additional processing of ICESat data. The inferred GIA shows that the strongest uplift is found in the Amundsen Sea Embayment (ASE) sector and subsidence mostly occurs in Adelie Terre and the East Antarctica inland. The total GIA-related mass change estimates for the entire AIS, West Antarctica Ice Sheet (WAIS), East Antarctica Ice Sheet (EAIS), and Antarctic Peninsula Ice Sheet (APIS) are 43 ± 38, 53 ± 24, −23 ± 29 and 13 ± 6 Gt a−1, respectively. The overall ice mass change of the AIS is −46 ± 43 Gt a−1 (WAIS: −104 ± 25, EAIS: 77 ± 35, APIS: −20 ± 6). The most significant ice mass loss and most significant elastic vertical crustal deformations are concentrated in the ASE and northern Antarctic Peninsula.

AMPA receptors (AMPARs) mediate fast excitatory synaptic transmission and are crucial for synaptic plasticity, learning, and memory. However, the molecular control of AMPAR stability and its neurophysiological significance remain unclear. Here, we report that AMPARs are subject to lysine acetylation at their C termini. Acetylation reduces AMPAR internalization and degradation, leading to increased cell-surface localization and prolonged receptor half-life. Through competition for the same lysine residues, acetylation intensity is inversely related to the levels of AMPAR ubiquitination. We find that sirtuin 2 (SIRT2) acts as an AMPAR deacetylase regulating AMPAR trafficking and proteostasis. SIRT2 knockout mice (Sirt2−/−) show marked upregulation in AMPAR acetylation and protein accumulation. Both Sirt2−/− mice and mice expressing acetylation mimetic GluA1 show aberrant synaptic plasticity, accompanied by impaired learning and memory. These findings establish SIRT2-regulated lysine acetylation as a form of AMPAR post-translational modification that regulates its turnover, as well as synaptic plasticity and cognitive function.

Background/Aims: To assess the prognostic accuracy of absolute serum creatinine (sCr) changes (‘Delta-sCr’) on the long-term outcomes in cirrhotic patients, and evaluate the performance of the ‘Delta-sCr’ approach to stage acute kidney injury (AKI), compared with the Kidney Disease Improving Global Outcomes (KDIGO) criteria. Methods: We conducted a retrospective analysis of 333 hospitalized patients. We classified AKI stages using two methods: 1) KDIGO AKI criteria; 2) ‘Delta-sCr’ system, defined by the difference between the baseline and the peak sCr value during the hospitalization. The end point was the hazard of 1-year death. Results: The prevalence of AKI in cirrhotic patients was 18.01% by the KDIGO criteria, and 25.22% by the ‘Delta-sCr’ system. On multivariable Cox hazard analysis, both of the two methods were independent predictive factors of death (‘Delta-sCr’ system: OR=2.911, p

The conversion between the line-of-sight slant total electron content (STEC) and the vertical total electron content (VTEC) depends on the mapping function (MF) under the widely used thin layer ionospheric model. The thin layer ionospheric height (TLIH) is an essential parameter of the MF, which affects the accuracy of the conversion between the STEC and VTEC. Due to the influence of temporal and spatial variations of the ionosphere, the optimal TLIH is not constant over the globe, particularly in the polar regions. In this paper, a new method for determining the optimal TLIH is proposed, which compares the mapping function values (MFVs) from the MF at different given TLIHs with the “truth” mapping values from the UQRG global ionospheric maps (GIMs) and the differential TEC (dSTEC) method, namely the dSTEC- and GIM-based thin layer ionospheric height (dG-TLIH) techniques. The optimal TLIH is determined using the dG-TLIH method based on GNSS data over the Antarctic and Arctic. Furthermore, we analyze the relationship between the optimal TLIH derived from the dG-TLIH method and the height of maximum density of the F2 layer (hmF2) based on COSMIC data in the polar regions. According to the dG-TLIH method, the optimal TLIH is mainly distributed between 370 and 500 km over the Arctic and between 400 and 500 km over the Antarctic in a solar cycle. In the Arctic, the correlation coefficient between the hmF2 and optimal TLIH is 0.7, and the deviation between them is 162 km. Meanwhile, in the Antarctic, the correlation coefficient is 0.60, with a phase lag of ~3 months, with the hmF2 leading the optimal TLIH, and the deviation between them is 177 km.

Epileptic activity may be more prevalent in early stage Alzheimer's disease (AD) than previously believed. Several studies report spontaneous seizures and interictal discharges in mouse models of AD undergoing age-related Aβ accumulation. The mechanism by which Aβ-induced neuronal excitability can trigger epileptiform activity remains unknown. Here, we systematically examined field excitatory postsynaptic potentials (fEPSP) in stratum radiatum and population spikes (PSs) in the adjacent stratum pyramidale of CA1 in wild-type mouse hippocampal slices. Soluble Aβ oligomers (oAβ) blocked hippocampal LTP and EPSP–spike (E–S) potentiation, and these effects were occluded by prior treatment with the glutamate uptake inhibitor TBOA. In accord, oAβ elevated glutamate levels in the hippocampal slice medium. Recording the PS revealed that oAβ increased PS frequency and reduced LTP, and this LTP deficit was occluded by pretreatment with the GABAA antagonist picrotoxin. Whole-cell recordings showed that oAβ significantly increased spontaneous EPSC frequency. Decreasing neuronal activity by increasing GABA tone or partially blocking NMDAR activity prevented oAβ impairment of hippocampal LTP. Finally, treating slices with two antiepileptic drugs rescued the LTP inhibition induced by oAβ. We conclude that soluble Aβ oligomers at the low nanomolar levels present in AD brain increase neuronal excitability by disrupting glutamatergic/GABAergic balance, thereby impairing synaptic plasticity.

The ionospheric error can significantly affect the synthetic aperture radar (SAR) signals, particularly in the case of L band and lower frequency SAR systems. The ionospheric distortions are mixed with terrain and ground deformation signals, lowering the precision of the interferometric measurements. Moreover, it is often difficult to detect the small-scale ionospheric structure due to its rapid changes and may have more influence on ionospheric phase compensation for InSAR measurements. In this paper, we present a Faraday rotation (FR) inversion method and corresponding procedure to compensate the ionospheric error for SAR interferograms and to detect the variations of small-scale ionospheric disturbances. This method retrieves the absolute total electron content (TEC) based on the FR estimation and corrects the ionospheric error for synthetic aperture radar interferometry (InSAR) measurements by transforming the differential TEC into the ionospheric phase. In two selected study cases, located in high latitude and equatorial regions where ionospheric disturbances occur frequently, we test the method using the Phased Array L-band Synthetic Aperture Radar (PALSAR) full-polarimetric SAR images. Our results show that the proposed procedure can effectively compensate the ionospheric phase. In order to validate the results, we present the results of ionospheric phase compensation based on the split-spectrum method as a comparison to the proposed method. To analyze the ability of our proposed method in detecting small-scale ionospheric disturbances, TEC derived from FR estimation are also compared with those derived from the global ionosphere maps (GIM). Our research provides a robust choice for the correction of ionospheric error in SAR interferograms. It also provides a powerful tool to measure small-scale ionospheric structure.

The elevation changes of ice sheets have been recognized as an essential climate variable. Long-term time series of these changes are an important parameter to understand climate change, and the longest time-series of ice sheet elevation changes can be derived from combining multiple Ku-band satellite altimetry missions. However, unresolved intermission biases obscure the record. Here, we revise the mathematical model commonly used in the literature to simultaneously correct for intermission bias and ascending–descending bias to ensure the self-consistency and cohesion of the elevation time series across missions. This updated approach is applied to combine Envisat and CryoSat-2 radar altimetry in the period of 2002–2019. We tested this approach by validating it against airborne and satellite laser altimetry. Combining the detailed temporal and spatial evolution of elevation changes with firn densification-modeled volume changes due to surface processes, we found that the Amundsen Sea sector accounts for most of the total volume loss of the Antarctic Ice Sheet (AIS), mainly from ice dynamics. However, surface processes dominate the volume changes in the key regions, such as the Totten Glacier sector, Dronning Maud Land, Princess Elizabeth Land, and the Bellingshausen Sea sector. Overall, accelerated volume loss in the West Antarctic continues to outpace the gains observed in the East Antarctic. The total volume change during 2002–2019 for the AIS was −68.7 ± 8.1 km3/y, with an acceleration of −5.5 ± 0.9 km3/y2.

Snow plays a critical role in hydrological monitoring and global climate change, especially in the Arctic region. As a novel remote sensing technique, global navigation satellite system interferometric reflectometry (GNSS-IR) has shown great potential for detecting reflector characteristics. In this study, a field experiment of snow depth sensing with GNSS-IR was conducted in Ny-Alesund, Svalbard, and snow depth variations over the 2014–2018 period were retrieved. First, an improved approach was proposed to estimate snow depth with GNSS observations by introducing wavelet decomposition before spectral analysis, and this approach was validated by in situ snow depths obtained from a meteorological station. The proposed approach can effectively separate the noise power from the signal power without changing the frequency composition of the original signal, particularly when the snow depth changes sharply. Second, snow depth variations were analyzed at three stages including snow accumulation, snow ablation and snow stabilization, which correspond to different snow-surface-reflection characteristics. For these three stages of snow depth variations, the mean absolute errors (MAE) were 4.77, 5.11 and 3.51 cm, respectively, and the root mean square errors (RMSE) were 6.00, 6.34 and 3.78 cm, respectively, which means that GNSS-IR can be affected by different snow surface characteristics. Finally, the impact of rainfall on snow depth estimation was analyzed for the first time. The results show that the MAE and RMSE were 2.19 and 2.08 cm, respectively, when there was no rainfall but 5.63 and 5.46 cm, respectively, when it was rainy, which indicates that rainfall reduces the accuracy of snow depth estimation by GNSS-IR.