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Earth system models (ESMs) participating in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) simulate various components of fine particulate matter (PM2.5) as major climate forcers. Yet the model performance for PM2.5 components remains little evaluated due in part to a lack of observational data. Here, we evaluate near-surface concentrations of PM2.5 and its five main components over China as simulated by 14 CMIP6 models, including organic carbon (OC; available in 14 models), black carbon (BC; 14 models), sulfate (14 models), nitrate (4 models), and ammonium (5 models). For this purpose, we collect observational data between 2000 and 2014 from a satellite-based dataset for total PM2.5 and from 2469 measurement records in the literature for PM2.5 components. Seven models output total PM2.5 concentrations, and they all underestimate the observed total PM2.5 over eastern China, with GFDL-ESM4 (- 1.5 %) and MPI-ESM-1-2-HAM (- 1.1 %) exhibiting the smallest biases averaged over the whole country. The other seven models, for which we recalculate total PM2.5 from the available component output, underestimate the total PM2.5 concentrations partly because of the missing model representations of nitrate and ammonium. Concentrations of the five individual components are underestimated in almost all models, except that sulfate is overestimated in MPI-ESM-1-2-HAM by 12.6 % and in MRI-ESM2-0 by 24.5 %. The underestimation is the largest for OC (by - 71.2 % to - 37.8 % across the 14 models) and the smallest for BC (- 47.9 % to - 12.1 %). The multi-model mean (MMM) reproduces the observed spatial pattern for OC (R = 0.51), sulfate (R = 0.57), nitrate (R = 0.70) and ammonium (R = 0.74) fairly well, yet the agreement is poorer for BC (R = 0.39). The varying performances of ESMs on total PM2.5 and its components have important implications for the modeled magnitude and spatial pattern of aerosol radiative forcing. [ABSTRACT FROM AUTHOR]

Paddy fields serve as significant reservoirs of soil organic carbon (SOC) and their potential for terrestrial carbon (C) sequestration is closely associated with changes in SOC pools. However, there has been a dearth of comprehensive studies quantifying changes in SOC pools following extended periods of rice cultivation across a broad geographical scale. Using 104 rice paddy sampling sites that have been in continuous cultivation since the 1980s across China, we studied the changes in topsoil (0–20 cm) labile organic C (LOC I), semi‐labile organic C (LOC II), recalcitrant organic C (ROC), and total SOC. We found a substantial increase in both the content (48%) and density (39%) of total SOC within China's paddy fields between the 1980s to the 2010s. Intriguingly, the rate of increase in content and density of ROC exceeded that of LOC (I and II). Using a structural equation model, we revealed that changes in the content and density of total SOC were mainly driven by corresponding shifts in ROC, which are influenced both directly and indirectly by climatic and soil physicochemical factors; in particular temperature, precipitation, phosphorous (P) and clay content. We also showed that the δ13CLOC were greater than δ13CROC, independent of the rice cropping region, and that there was a significant positive correlation between δ13CSOC and δ13Cstraw. The δ13CLOC and δ13CSOC showed significantly negative correlation with soil total Si, suggesting that soil Si plays a part in the allocation of C into different SOC pools, and its turnover or stabilization. Our study underscores that the global C sequestration of the paddy fields mainly stems from the substantial increase in ROC pool. [ABSTRACT FROM AUTHOR]

The infestation of pine shoot beetles (Tomicus spp.) in the forests of Southwestern China has inflicted serious ecological damages to the environment, causing significant economic losses. Therefore, accurate and practical approaches to detect pest infestation have become an urgent necessity to mitigate these harmful consequences. In this study, we explored the efficiency of thermal infrared (TIR) technology in capturing changes in canopy surface temperature (CST) and monitoring forest health at the scale of individual tree crowns. We combined data collected from TIR imagery and light detection and ranging (LiDAR) using unmanned airborne vehicles (UAVs) to estimate the shoot damage ratio (SDR), which is a representative parameter of the damage degree caused by forest infestation. We compared multiple machine learning methods for data analysis, including random forest (RF), partial least squares regression (PLSR), and support vector machine (SVM), to determine the optimal regression model for assessing SDR at the crown scale. Our findings showed that a combination of LiDAR metrics and CST presents the highest accuracy in estimating SDR using the RF model (R2 = 0.7914, RMSE = 15.5685). Our method enables the accurate remote monitoring of forest health and is expected to provide a novel approach for controlling pest infestation, minimizing the associated damages caused. [ABSTRACT FROM AUTHOR]

Earth system models (ESMs) participating in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) simulate various components of fine particulate matter (PM2.5) as major climate forcers. Yet the model performance for PM2.5 components remains little evaluated due in part to lack of observational data. Here, we evaluate near-surface concentrations of PM2.5 and its five main components over China as simulated by fourteen CMIP6 models, including organic carbon (OC, available in 14 models), black carbon (BC, 14 models), sulfate (14 models), nitrate (4 models), and ammonium (5 models). For this purpose, we collect observational data between 2000 and 2014 from a satellite-based dataset for total PM2.5 and from 2469 measurement records in the literature for PM2.5 components. Seven models output total PM2.5 concentrations, and they all underestimate the observed total PM2.5 over eastern China, with GFDL-ESM4 (–1.5 %) and MPI-ESM-1-2-HAM (–1.1 %) exhibiting the smallest biases averaged over the whole country. The other seven models, for which we recalculate total PM2.5 from the available components output, underestimate the total PM2.5 concentrations, partly because of the missing model representations of nitrate and ammonium. Concentrations of the five individual components are underestimated in almost all models, except that sulfate is overestimated in MPI-ESM-1-2-HAM by 12.6 % and in MRI-ESM2-0 by 24.5 %. The underestimation is the largest for OC (by –71.2 % to –37.8 % across the 14 models) and the smallest for BC (–47.9 % to –12.1 %). The multi-model mean (MMM) reproduces fairly well the observed spatial pattern for OC (R = 0.51), sulfate (R = 0.57), nitrate (R = 0.70) and ammonium (R = 0.75), yet the agreement is poorer for BC (R = 0.39). The varying performances of ESMs on total PM2.5 and its components have important implications for the modeled magnitude and spatial pattern of aerosol radiative forcing. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is a severe inflammatory auto‐immune disorder affecting millions of people across the globe. The current therapeutic options are not adequate to address the complications of RA. Therefore, the present study was conducted to elucidate the protective effect of lariciresinol, a lignan, against Complete Freund's adjuvant (CFA)‐induced arthritis in rats. The results of the study showed that lariciresinol improves paw swelling and arthritic scores in rats as compared to CFA rats. Lariciresinol also showed a significant reduction in rheumatoid factor, C‐reactive protein, tumor necrosis factor‐α, interleukin (IL)‐17, and tissue inhibitor of metalloproteinases‐3 level with a simultaneous increase in IL‐4 level. The burden of oxidative stress was also reduced in CFA rats, as shown by reduced MDA levels and increased SOD and GPx after the administration of lariciresinol. In a Western blot analysis, lariciresinol showed a significant reduction of transforming growth factor‐β and nuclear factor‐κB (NF‐κB) protein levels in CFA rats. To understand the binding characteristic of lariciresinol with NF‐κB, molecular docking analysis was conducted, which showed Larciresinol interacted with the active site of NF‐κB. Our study demonstrated the significant protective effect of lariciresinol against RA via multi‐target action. [ABSTRACT FROM AUTHOR]

Cinnamomum burmannii (Nees & T. Nees) Blume is a cinnamon species used for daily needs and as an herb in traditional medicine. This study was designed to determine the composition, antioxidant, and antimicrobial activity of essential oils (EOs) extracted from different organs of the plant. The gas chromatography (GC) and gas chromatography-mass spectrometry (GC/MS) analysis revealed that the bark was dominated by 1-isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene (11.60%), γ-muurolene (8.79%), eucalyptol (7.66%), α-muurolene (7.37%), α-terpineol (6.65%), δ-selinene (6.42%), while endo-borneol (41.74 and 40.60%), caryophyllene (6.29 and 10.43%), and bornyl acetate (4.18 and 4.08%) were the primary components of branch and leaf oils. Additionally, a notable antioxidant power of the bark, branch and leaf essential oil was observed from the results of 1,1-diphenyl-2-picrylhydrazyl (DPPH) free-radical scavenging activity (0.03-0.05 mg/mL), antiradical power (ARP) (19.61-32.26), 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid (ABTS) radical scavenging activity assay (0.40-0.75 mol/g), and ferric reducing antioxidant power (FRAP) (0.30-0.66 mg Fe2+/g). Branches and leaves had stronger antioxidant activity, and endo-borneol, bornyl acetate, humulene and cedrene were the main contributors to the antioxidant activity. Moreover, the bark showed notable inhibitory activity against Staphylococcus aureus, while the leaf oil had good antibacterial activity against Micrococcus luteus and Pseudomonas putida. These findings suggest that C. burmannii could be considered a potent source of natural nutraceutical uses. [ABSTRACT FROM AUTHOR]

Low- and medium-resolution satellites have been a relatively mature platform for inland eutrophic water classification and chlorophyll a concentration (Chl-a) retrieval algorithms. However, for oligotrophic and mesotrophic waters in small- and medium-sized reservoirs, problems of low satellite resolution, insufficient water sampling, and higher uncertainty in retrieval accuracy exist. In this paper, a hybrid Chl-a estimation method based on spectral characteristics (i.e., remote sensing reflectance (Rrs)) classification was developed for oligotrophic and mesotrophic waters using high-resolution satellite Sentinel-2 (A and B) data. First, 99 samples and quasi-synchronous Sentinel-2 satellite data were collected from four small- and medium-sized reservoirs in central China, and the usability of the Sentinel-2 Rrs data in inland oligotrophic and mesotrophic waters was verified by accurate atmospheric correction. Second, a new optical classification method was constructed based on different water characteristics to classify waters into clear water, phytoplankton-dominated water, and water dominated by phytoplankton and suspended matter together using the thresholds of Rrs490/Rrs560 and Rrs665/Rrs560. The proposed method has a higher classification accuracy compared to other classification methods, and the band-ratio algorithm is simpler and more effective for satellite sensors without NIR bands. Third, given the sensitivity of the empirical method to water variability and the ease of development and implementation, a nonlinear least squares fitted one-dimensional nonlinear function was established based on the selection of the best-fitting spectral indices for different optical water types (OWTs) and compared with other Chl-a estimation algorithms. The validation results showed that the hybrid two-band method had the highest accuracy with squared correlation coefficient, root mean squared difference, mean absolute percentage error, and bias of 0.85, 2.93, 32.42%, and −0.75 mg/m3, respectively, and the results of the residual values further validated the applicability and reliability of the model. Finally, the performance of the classification and estimation algorithms on the four reservoirs was evaluated to obtain images mapping the Chl-a in the reservoirs. In conclusion, this study improves the accuracy of Chl-a estimation for oligotrophic and mesotrophic waters by combining a new classification algorithm with a two-band hybrid model, which is an important contribution to solving the problem of low resolution and high uncertainty in the retrieval of Chl-a in oligotrophic and mesotrophic waters in small- and medium-sized reservoirs and has the potential to be applied to other optically similar oligotrophic and mesotrophic lakes and reservoirs using similar spectrally satellite sensors. [ABSTRACT FROM AUTHOR]

Henan Province is an important ecological barrier in the middle and lower reaches of the Yellow River. It is of great significance to study its ecosystem quality and the driving mechanisms behind this in order to realize ecological conservation and high-quality development in the Yellow River Basin. In this study, from the perspective of physical elements, socioeconomic elements, and policy adjustments, multi-source data on land use, population density, forestry engineering, and other indicators were selected to construct an index system of the driving factors of ecosystem quality in Henan Province. The characteristics of spatio-temporal change and the formation mechanism of ecosystem quality in Henan Province from 2010 to 2020 were analyzed by comprehensively using the gravity center analysis method and a geo-detector tool. The results showed the following: (1) The ecosystem quality of Henan Province in 2020 has increased by 27.7% compared with that in 2010, and the center of gravity of ecosystem quality continued to move to the northwest of Henan Province. The quality of ecosystems in the hilly region of Western Henan, Tongbai, and Nanyang was better than that in the northern Loess Platform Hilly Area and the Yellow River Plain, and it presented a spatial pattern in which the quality of the south was higher than that of the north, while the east and west were equal; (2) From 2010 to 2020, the average GDP and population density in Henan Province were the most important factors affecting the quality of its ecosystem. The effect of land-use diversity on ecosystem quality in the hilly region of Henan Province was stronger than that in the central and eastern plains; and (3) The interactions among the driving factors were mainly nonlinear enhancement and double factor enhancement, in which the interaction between socio-economic elements and natural environmental elements was the dominant interaction mode and could enhance the impact on the quality of the regional ecological environment. The results of this study indicate that attention should be paid to generating targeted industrial economy layout and land use policies in different natural domains. Moreover, forestry protection engineering policies should be further strengthened to improve the resilience of ecosystem quality to human activities. [ABSTRACT FROM AUTHOR]

Nighttime light (NTL) images obtained by the Visible Infrared Imaging Radiometer (VIIRS) mounted on the National Polar-orbiting Partnership (NPP) could objectively represent human activities and instantly identify urban shapes on a temporal and spatial scale. From 2013 to 2020, the built-up areas of eight provincial capital cities were extracted using NPP/VIIRS NTL data to examine the dynamic changes in city expansion and socioeconomic development in the Yellow River Basin during the urbanization process. The spatial characteristics of urban built-up area expansion were generated using the eight-quadrant analysis method and combined with the statistical data of population and (gross domestic product) GDP to analyze the correlations between the light intensity of built-up areas, population and GDP; this enables an understanding of the changes in population and economy in the development of urban built-up area expansion. The findings show that: (1) unbalanced city development existed in the Yellow River Basin's upper, middle, and lower reaches, and the expansion and light intensity of cities in the upper reaches were slower than those in the middle and lower reaches; (2) the spatial differentiation of urban expansion was significant between each of the reaches in the Yellow River Basin, and greatly influenced by natural geographical elements; and (3) positive correlation exists between light intensity, population, and GDP in the built-up areas of the middle and lower reaches, while the correlations in the upper reaches were not stable. In conclusion, light data indirectly reflects urban development and could be used as a substitute variable for socioeconomic development indicators under certain conditions. [ABSTRACT FROM AUTHOR]

Infestations of Tomicus spp. have caused the deaths of millions of Yunnan pine forests in Southwest China; consequently, accurate monitoring methods are required to assess the damage caused by these pest insects at an early stage. Considering the limited sensitivity of optical reflectance on the early stage of beetle stress, the potential of thermal infrared (TIR) can be exploited for monitoring forest health on the basis of the change of canopy surface temperature (CST). However, few studies have investigated the impact of the leaf area index (LAI) on the accuracy of TIR data-based SDR assessments. Therefore, the current study used unmanned airborne vehicle (UAV)-based TIR and light detection and ranging (LiDAR) data to assess the capacity of determining the potential for using TIR data for determining SDR under different LAI conditions. The feasibility of using TIR for monitoring SDRs at the tree level and plot scales were analyzed using the relationship between SDR and canopy temperature. Results revealed that: (1) prediction accuracy of SDR from CST is promising at high LAI values and decreases quickly with LAI, and is higher at the single tree scale (R2 = 0.7890) than at the plot scale (R2 = 0.5532); (2) at either single tree or plot scale, a significant negative correlation can be found between CST and LAI (−0.9121 at tree scale and −0.5902 at plot scale); (3) LAI affects the transmission paths of sunlight and sensor, which mainly disturbs the relationship between CST and SDR. This article evaluated the high possibility of using TIR data to monitor SDRs at both tree and plot levels and assessed the negative impact of a low LAI (<1) on the relationship between temperature and SDR. Accordingly, when measuring forest health using TIR data, additional data sources are required to eliminate the negative impact of low LAIs and to improve the monitoring accuracy. [ABSTRACT FROM AUTHOR]

Objective. Image segmentation technology is applied to separate a single vertebra from the three-dimensional model of the spine, so as to separate a single vertebra image with smaller error, higher degree of automation, and better results. The objectives are to study the biomechanical characteristics of posterior short-segment pedicle screw fixation by three-dimensional finite element method, analyze the mechanical characteristics of posterior pedicle screw rod fixation system under different factors, and demonstrate the feasibility of its application in the treatment of lumbar fracture. Methods. The authors searched the database for articles about the treatment of lumbar spine fracture, screw rod internal fixation system, and its mechanical parameters. The threshold segmentation method based on region segmentation method was used to segment the image, and the three-dimensional finite element model was used to analyze the biomechanical characteristics of different posterior internal fixation for lumbar spine fracture. Results. The posterior pedicle internal fixation system for the treatment of multilevel spinal fractures is a mature surgical technique and has fewer postoperative complications. Transpedicle fixation is effective and reliable. It can effectively restore the coronal and sagittal curvature of the vertebral body and restore the stability of the spine better. But the choice of internal fixation method should be individualized based on fracture type, identification of critical and secondary injury sites, and stability assessment. Only after mastering the biomechanical characteristics of the posterior screw rod system for the treatment of lumbar fracture, selecting the appropriate method, and fixing the appropriate movement unit can the best fixation be achieved. Conclusion. Threshold method is the most direct and simple image segmentation method. The core technology of thresholding is the selection of threshold, which will affect the final segmentation effect. The most common segmentation method is to calculate the segmentation threshold by histogram. The threshold method has less computation and good segmentation effect for the image with large contrast between background and target. Posterior pedicle screw rod system internal fixation has the advantages of less trauma, good reduction, reliable fixation, and less complications. The design, placement angle and depth of various internal fixation systems, and the number of fixed segments all show different mechanical characteristics. As long as we master the above characteristics, choose the appropriate method and fix the appropriate motor unit, and we can get the best fixation; it can be used as an effective treatment for lumbar fracture. [ABSTRACT FROM AUTHOR]

Objective. To explore the application value of magnetic resonance spectroscopy (MRS) and GSI-energy spectrum electronic computed tomography (CT) medical imaging based on the deep convolutional neural network (CNN) in the treatment of lumbar degenerative disease and osteoporosis. Methods. There were 56 cases of suspected lumbar degenerative disease and osteoporosis. A group of 56 subjects were examined using 1.5 TMR spectrum (MRS) and dual-energy X-ray absorptiometry (DXA) to collect the lumbar L3 vertebral body fat ratio (FF) and L1~4 vertebral bone mineral density (BMD) value. We divided the subjects into 2 groups with T value -2.5 as the critical point. Set T value > -2.5 as the negative group and T value ≤ -2.5 as the positive group. Pearson's method is used for FF-MRS and BMD correlation analyses. A group of all patients underwent GSI-energy spectrum CT scan, and X-ray bone mineral density (DXA) test results (bone density per unit area) were used as the gold standard to analyze the diagnosis of osteoporosis by the GSI-energy spectrum CT scan method value. Results. The differences in FF and BMD between the negative group and the positive group were statistically significant (P < 0.01), and there was a highly negative correlation between the average value of FF and BMD. 30 cases were diagnosed as osteoporosis by DXA. The accuracy of GSI-energy spectrum CT medical imaging in diagnosing osteoporosis is 89.30%. The GSI-energy spectrum CT diagnosis of osteoporosis and DXA examination results have good consistency. Conclusion. Based on the deep convolutional neural network (CNN) MRS technology, GSI-energy spectrum CT medical imaging is used in the clinical diagnosis and treatment of lumbar degenerative lesions and osteoporosis. It has a good advantage in assessing bone quality and has good consistency with DXA examination and has better application value high. [ABSTRACT FROM AUTHOR]

We present a new divergence method to estimated methane (CH4) emissions from satellite observed mean mixing ratio of methane (XCH4) by deriving the regional enhancement of XCH4 in the Planetary Boundary Layer (PBL). The applicability is proven by comparing the estimated emissions with its known emission inventory from a 3‐month GEOS‐Chem simulation. When applied to TROPOspheric Monitoring Instrument observations, sources from well‐known oil/gas production areas, livestock farms and wetlands in Texas become clearly visible in the emission maps. The calculated yearly averaged total CH4 emission over the Permian Basin is 3.06 (2.82, 3.78) Tg a−1 for 2019, which is consistent with previous studies and double that of EDGAR v4.3.2 for 2012. Sensitivity tests on PBL heights, on the derived regional background and on wind speeds suggest our divergence method is quite robust. It is also a fast and simple method to estimate the CH4 emissions globally. Plain Language Summary: Methane (CH4) is an important greenhouse gas in the atmosphere and plays a crucial role in the global climate change. It kept increasing over the last decades. About 70% of CH4 comes from human activities like oil/gas productions or livestock farms. The recently launched TROPOspheric Monitoring Instrument provides an opportunity to estimate the emissions of CH4 on a regional scale. This work presents a new method to fastly derive CH4 emissions at a fairly high spatial resolution without a priori knowledge of sources. Key Points: A new divergence method is developed to estimate methane emissions based on satellite observations, requiring no a priori emissionsThe applicability of this method in identifying and quantifying sources is proven by a GEOS‐Chem simulation with known emission inventoryThe estimated emissions over Texas (United States) based on TROPOspheric Monitoring Instrument observations are evaluated and are found to be robust [ABSTRACT FROM AUTHOR]

Seven scenarios were designed to study the national environmental benefits of ULE in coal-fired power plants (CPPs), ULE in industrial coal burning (ICB) and NH3 emission reduction by using the GEOS-Chem model. The results showed that although the CPPs have achieved the ULE transformation target, the PM2.5 concentration across the country has decreased by 4.8% (1.4 μg/m3). Due to the complex non-linear chemical competition mechanism among nitrate and sulfate, the average concentration of nitrate in the country has increased by 1.5% (0.1 μg/m3), which has reduced the environmental benefits of the power plant emission reduction. If the ULE technology is applied to the ICB to further reduce NOx and SO2, although the PM2.5 concentration can be reduced by 10.1% (2.9 μg/m3), the concentration of nitrate will increase by 2.7% (0.2 μg/m3). Based on the CPPs-ULE, NH3 emissions reduced by 30% and 50% can significantly reduce the concentration of ammonium and nitrate, so that the PM2.5 concentration is decreased by 11.5% (3.3 μg/m3) and 16.5% (4.7 μg/m3). Similarly, based on the CPPs-ICB-ULE, NH3 emissions can be reduced by 30% and 50% and the PM2.5 concentration reduced by 15.6% (4.4 μg/m3) and 20.3% (5.8 μg/m3). The CPPs and ICB use the ULE technology to reduce NOx and SO2, thereby reducing the concentration of ammonium and sulfate, causing the PM2.5 concentration to decline, and NH3 reduction is mainly achieved through reducing the concentration of ammonium and nitrate to reduce the concentration of PM2.5. In order to better reduce the concentration of PM2.5, NOx, SO2 and NH3 emission reduction control measures should be comprehensively considered in different regions of China. By comprehensively considering the economic cost and environmental benefits of ULE in ICB and NH3 emission reduction, an optimal haze control scheme can be determined. [ABSTRACT FROM AUTHOR]

The inappropriate apoptosis of macrophages plays an important role in the pathogenesis of sepsis-induced acute lung injury, however, the detailed regulatory mechanisms remain largely unknown. As an endogenous apoptosis pathway, endoplasmic reticulum (ER) stress plays an important role in cell damage in patients with sepsis. Clarifying the ER stress response and its effect on macrophages during the development of sepsis is helpful to explore new strategies for the prevention and treatment of ALI in sepsis. The mouse model and the RAW264.7 inflammation model were stimulated with LPS to establish in vivo and in vitro. We explored the effects of different expression levels of silent information regulator factor 2-related enzyme 1 (SIRT1) on the ER stress response and apoptosis of macrophages in the sepsis-related injury model. Our studies found that the increased expression of SIRT1 can significantly improve sepsis-related lung injury and relieve lung inflammation. SRT1720, a SIRT1 activator, can significantly inhibit the ER stress response of lung tissue and macrophages, inhibit the expression of pro-apoptotic proteins, promote the expression of anti-apoptotic proteins, and reduce macrophages of apoptosis. While the EX527, an inhibitor of SIRT1, had the opposite effect. SIRT1 can significantly improve sepsis-associated lung injury and LPS-induced macrophage apoptosis. This protective effect is closely related to its inhibition of the ER stress response via the PERK/eIF2-α/ATF4/CHOP pathway. • SIRT1 can significantly inhibit excessive inflammation response in sepsis-associated lung injury. • SIRT1 can obviously inhibit the expression of pro-apoptosis-related proteins and promote the expression of anti-apoptotic proteins in sepsis-associated lung injury. • SIRT1 can effectively reduce LPS-induced apoptosis of macrophages via inhibiting the ER stress. [ABSTRACT FROM AUTHOR]

The dysfunctional immune response and multiple organ injury in sepsis is a recurrent theme impacting prognosis and mortality, while the lung is the first organ invaded by sepsis. To systematically elucidate the transcriptomic changes in the main constituent cells of sepsis-injured lung tissue, we applied single-cell RNA sequencing to the lung tissue samples from septic and control mice and created a comprehensive cellular landscape with 25044 cells, including 11317 immune and 13727 non-immune cells. Sepsis alters the composition of all cellular compartments, particularly neutrophils, monocytes, T cells, endothelial, and fibroblasts populations. Our study firstly provides a single-cell view of cellular changes in septic lung injury. Furthermore, by integrating bulk sequencing data and single-cell data with the Scissors-method, we identified the cell subpopulations that are most associated with septic lung injury phenotype. The phenotypic-related cell subpopulations identified by Scissors-method were consistent with the cell subpopulations with significant composition changes. The function analysis of the differentially expressed genes (DEGs) and the cell-cell interaction analysis further reveal the important role of these phenotype-related subpopulations in septic lung injury. Our research provides a rich resource for understanding cellular changes and provides insights into the contributions of specific cell types to the biological processes that take place during sepsis-induced lung injury., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wang, Chen, Ma, Wang, Wang, Xia, Zhang and Yao.)

Background: Spinal cord injury (SCI) is one of the serious neurological diseases with high morbidity which may be treated with hematopoietic stem cell (HSC) transplants. Circular RNAs (circRNAs) play vital roles in SCI. The study aimed to reveal the function and mechanism of circRNA homeodomain interacting protein kinase 3 (HIPK3) in SCI., Methods: SCI model in vitro was established by treating neuronal cells AGE1.HN with oxygen-glucose deprivation (OGD) and CoCl2. The levels of circHIPK3, miR-382-5p and dual specificity phosphatase 1 (DUSP1) were examined using quantitative real-time PCR (qRT-PCR) or western blot assay. Enzyme linked immunosorbent assay (ELISA) was used to detect the levels of inflammatory factors (IL-6 and TNF-α). Cell proliferation and apoptosis were evaluated by 5'-ethynyl-2'-deoxyuridine (EdU) assay and flow cytometry. Caspase-3 Colorimetric Assay Kit was used to detect aaspase-3 activity. The interactions among circHIPK3, miR-382-5p and DUSP1 were confirmed by dual-luciferase reporter and RNA immunoprecipitation assays., Results: CircHIPK3 and DUSP1 were down-regulated, while miR-382-5p was up-regulated in OGD-induced AGE1.HN cells. Overexpression of circHIPK3 suppressed inflammatory response and cell apoptosis and promoted proliferation in OGD-induced AGE1.HN cells by sponging miR-382-5p. CircHIPK3 regulated DUSP1 expression by targeting miR-382-5p. MiR-382-5p inhibition hindered inflammatory response of IL-6 and TNF-α and neuronal apoptosis and promoted apoptosis via targeting DUSP1., Conclusion: CircHIPK3 overexpression alleviated OGD-induced AGE1.HN cell inflammatory response and neuronal apoptosis via regulating miR-382-5p/DUSP1 axis, indicating that circHIPK3 might be a promising therapeutic target for SCI., (Copyright © 2022. Published by Elsevier B.V.)