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BackgroundCystatin C (CysC) levels in amyotrophic lateral sclerosis (ALS) have been found changes, however, the associations between serum CysC levels and the progression and survival of ALS remain largely unknown.MethodsA total of 1,086 ALS patients and 1,026 sex-age matched healthy controls (HCs) were enrolled in this study. Serum CysC, other renal function, and metabolic parameters were measured. Correlation analysis and binary logistic regression were used to explore the factors related to serum CysC. Kaplan–Meier curve and Cox regression model were used for survival analysis.ResultsCysC levels were significantly higher in ALS patients compared to HCs (0.94 vs. 0.85 mg/L, p

Quantifying the spatiotemporal patterns of the coordination between ecosystem service supply and demand is vital for regional sustainable development. To reveal the dynamic pattern of the coordination of ecosystem service (ES) supply and demand in the Lhasa River Basin, we quantified the supply of the following four ESs using the InVEST model from 2000 to 2018: carbon sequestration (CS), water conservation (WC), habitat quality (HQ), and soil conservation (SC). Using socio-economic data, including land development degree, GDP, and population density, the ES demand was quantified. The ES supply–demand ratio (ESDR) and coupling coordination degree (CCD) model were used to evaluate the coupling relationship and coordination of ES supply and demand. The spatial autocorrelation analysis was used to determine the spatial correlation and changes in the ES supply–demand coupling coordination degree. The results indicate that the distribution of ESDR exhibited significant spatial heterogeneity. The area with ES supply far greater than demand was always in the upstream area of the Lhasa River, while the ES demand of Chengguan District far exceeded supply. Grasslands and forests were the main contributors to ESDRs, providing positive ESDRs for three services, SC, HQ, and WC, with a total proportion above 80%. From 2000 to 2018, the mismatch between ES supply and demand was gradually spreading upstream, while the upstream areas had a relatively high CCD. The spatial correlations of the CCD in the Lhasa River basin all showed statistically significant differences (p < 0.01). The high–high aggregation areas were concentrated in the northeast of the Lhasa River basin, while the low–low aggregation areas were centered around Chengguan District. This study provides reference values for optimizing the land use spatial patterns in ecologically vulnerable areas with the goal of sustainable development.

Abstract Aims Surveys and research on the applications of the hepatic venous pressure gradient (HVPG) are important for understanding the current status and future development of this technology in China. This article aimed to investigate the status of hepatic venous pressure gradient measurement in China in 2022. Methods We investigated the overall status of HVPG technology in China—including hospital distribution, hospital level, annual number of cases, catheters used, average cost, indications, and current challenges by using online questionnaire. By counting the number and percentages of cases of these results, we hope to clarify the current status of HVPG measurements in China. Results According to the survey, 85 hospitals in China used HVPG technology in 2022 distributed across 29 provinces. A total of 4989 HVPG measurements were performed in all of the surveyed hospitals in 2022, of which 2813 cases (56.4%) were measured alone. The average cost of HVPG measurement was 5646.8 ± 2327.9 CNY. Of the clinical teams who performed the measurements (sometimes multiple per hospital), 94.3% (82/87) used the balloon method, and the majority of the teams (72.4%, 63/87) used embolectomy catheters. Conclusions This survey clarified the clinical application status of HVPG in China and confirmed that some medical institutions in China have established a foundation for this technology. It is still necessary to continue promoting and popularizing this technology in the future.

Abstract Forest carbon sequestration capacity in China remains uncertain due to underrepresented tree demographic dynamics and overlooked of harvest impacts. In this study, we employ a process-based biogeochemical model to make projections by using national forest inventories, covering approximately 415,000 permanent plots, revealing an expansion in biomass carbon stock by 13.6 ± 1.5 Pg C from 2020 to 2100, with additional sink through augmentation of wood product pool (0.6-2.0 Pg C) and spatiotemporal optimization of forest management (2.3 ± 0.03 Pg C). We find that statistical model might cause large bias in long-term projection due to underrepresentation or neglect of wood harvest and forest demographic changes. Remarkably, disregarding the repercussions of harvesting on forest age can result in a premature shift in the timing of the carbon sink peak by 1–3 decades. Our findings emphasize the pressing necessity for the swift implementation of optimal forest management strategies for carbon sequestration enhancement.

1. Forest ecosystem is a basic component of terrestrial ecosystem that mitigates the impact of climate change through absorbing significant amount of carbon dioxide. Forest is crucial in maintaining ecological equilibrium, reducing greenhouse gas emission, and preserving biodiversity. Thus, standardised and precise methodologies for measuring forest carbon sequestration and assessing its potential are of paramount importance in evaluating the impacts of climate change.2. We presented the “forestat”, an approach for assessing forest carbon sequestration and its potential based on annual growth of biomass, considering site class and forest age conditions, wrapped in an R package, which is applicable to all forest types. By using a comprehensive system of forest stand models, “forestat” contributes to a refined comprehension of relationships between forest biomass and carbon sequestration and offers an evaluation of the carbon sequestration potential in forest ecosystem, unifying the methods of carbon measurement and its potential estimation in both natural and plantation forests.3. Based on the two applications, this study (a) introduces and demonstrates the methods in R package “forestat”; (b) uses the 6th, 7th, 8th, and 9th National Forest Inventory data to investigate carbon sequestration and potential productivity of degraded forests in China; and (c) conducts suitability analysis for tree species in the Yellow River Basin.4. “forestat” provides a unified, efficient, and standardized analytical tool for forest carbon sequestration and its potential. This study also highlights the primary forest functionalities.

Background and purposeSpontaneous aneurysmal subarachnoid hemorrhage (aSAH) is a common acute cerebrovascular disease characterized by severe illness, high mortality, and potential cognitive and motor impairments. We carried out a retrospective study at Fujian Provincial Hospital to establish and validate a model for forecasting functional outcomes at 6 months in aSAH patients who underwent interventional embolization.Methods386 aSAH patients who underwent interventional embolization between May 2012 and April 2022 were included in the study. We established a logistic regression model based on independent risk factors associated with 6-month adverse outcomes (modified Rankin Scale Score ≥ 3, mRS). We evaluated the model’s performance based on its discrimination, calibration, clinical applicability, and generalization ability. Finally, the study-derived prediction model was also compared with other aSAH prognostic scales and the model’s itself constituent variables to assess their respective predictive efficacy.ResultsThe predictors considered in our study were age, the World Federation of Neurosurgical Societies (WFNS) grade of IV-V, mFisher score of 3–4, secondary cerebral infarction, and first leukocyte counts on admission. Our model demonstrated excellent discrimination in both the modeling and validation cohorts, with an area under the curve of 0.914 (p

Background: This study aimed to investigate whether dexmedetomidine provides survival benefit in critically ill patients with sepsis-induced coagulopathy (SIC).Methods: Patients with sepsis-induced coagulopathy admitted to the ICU were identified from the Medical Information Marketplace for Intensive Care (MIMIC)-IV database. They were divided into two groups: patients who started dexmedetomidine within 48 h of ICU admission and lasted for more than 4 h and patients who did not receive dexmedetomidine as a control group. The primary outcome was 28-day hospital mortality, the secondary outcome was in-hospital mortality, and the extended outcomes included duration of mechanical ventilation and vasopressor use, ICU stay, and hospital stay. Propensity score matching (PSM) analysis was used to match patients who received dexmedetomidine with those who did not, and multivariable Cox models and logistics models were used to account for baseline differences and unmeasured confounders. An external validation was performed with the Critical care database comprising patients with infection at Zigong Fourth People’s Hospital.Results: After PSM, 592 patients who received dexmedetomidine were matched with 592 patients who did not receive dexmedetomidine. In the primary and secondary endpoints, dexmedetomidine was associated with a lower risk of 28-day hospital mortality (19.3% vs. 14.2%, hazard ratio (HR) 0.71; P = 0.020) and in-hospital mortality (22.3% vs. 16.4%, odds ratio (OR) 0.68; P = 0.017) in patients with SIC. Regarding the extended outcome, dexmedetomidine was also associated with a longer length of hospital stay (median 12.54 days vs. 14.87 days, P = 0.002) and longer ICU stay (median 5.10 days vs. 6.22 days, P = 0.009). In addition, the duration of mechanical ventilation was significantly increased in the dexmedetomidine group (median 41.62 h vs. 48.00 h, p = 0.022), while the duration of vasopressor use was not significantly different (median 36.67 h vs. 39.25 h, p = 0.194). Within 48 h of ICU stay, receiving a dose of dexmedetomidine greater than 0.474 μg/kg/h and continuous dexmedetomidine administration for 24–48 h may be associated with 28-day hospitalization outcomes in patients with SIC. External cohort validation also found that the use of dexmedetomidine after admission to the ICU can reduce 28-day mortality in patients with SIC.Conclusion: Dexmedetomidine administration is associated with reduced 28-day hospital mortality and in-hospital mortality in critically ill patients with SIC, and these findings deserve further verification in randomized controlled trials.

Background: Numerous studies have demonstrated a positive association between the level of tissue inhibitor of metalloproteinase 3 (TIMP3) and chronic kidney disease (CKD). Nevertheless, whether those associations reflect causal links still to be determined. This study intended to research the causal relationship of TIMP3 with CKD and markers of kidney function, such as creatinine‐based estimated glomerular filtration rate (eGFRcrea), cystatin C‐based estimated glomerular filtration rate (eGFRcys), eGFRcrea in diabetics (eGFRcrea (DM)) and eGFRcrea in non diabetics (eGFRcrea (No DM)).Methods: In this study, we investigated the causal relationships between TIMP3 and CKD and kidney function markers using a two-sample Mendelian randomization (MR) technique. We used summary level datasets for TIMP3 and CKD from genome-wide association studies that we were able to access through the study by Suhre K and Pattaro C.Results: We found that TIMP3 had a significant positive causal effect on the risk of CKD (Inverse variance weighted (IVW):odds ratio (OR):0.962, 95% confidence interval (CI): (0.936-0.988),P:0.005). However TIMP3 levels had no significant effect on risk of eGFRcys (PIVW: 0.114),eGFRcrea (PIVW:0.333). After grouping patients based on their diabetes status, we found that genetically higher levels of TIMP3 had a significant impact on eGFRcrea in participants without diabetes (OR:1.003,95%CI (1.001-1.006),P IVW:0.007), but not in participants with diabetes (PIVW = 0.057). Heterogeneity and pleiotropy analyses were carried out to verify the accuracy of the MR findings. Their findings were all not statistically significant.Conclusion: Our study suggests that TIMP3 may be causally associated with CKD and eGFRcrea (No DM)in people of European ancestry. Strategies aimed to increase TIMP3 levels may provide new ways to delay the deterioration of renal function.

Ocean satellite data are often impeded by intrinsic limitations in resolution and accuracy. However, conventional data reconstruction approaches encounter substantial challenges when facing the nonlinear oceanic system and high-resolution fusion of variables. This research presents a Discrete Satellite Gridding Neural Network (DSGNN), a new machine learning method that processes satellite data within a discrete grid framework. By transforming the positional information of grid elements into a standardized vector format, the DSGNN significantly elevates the accuracy and resolution of data fusion through a neural network model. This method’s innovative aspect lies in its discretization and fusion technique, which not only enhances the spatial resolution of oceanic data but also, through the integration of multi-element datasets, better reflects the true physical state of the ocean. A comprehensive analysis of the reconstructed datasets indicates the DSGNN’s consistency and reliability across different seasons and oceanic regions, especially in its adept handling of complex nonlinear interactions and small-scale oceanic features. The DSGNN method has demonstrated exceptional competence in reconstructing global ocean datasets, maintaining small error variance, and achieving high congruence with in situ observations, which is almost equivalent to 1/12° hybrid coordinate ocean model (HYCOM) data. This study offers a novel and potent strategy for the high-resolution reconstruction and fusion of ocean satellite datasets.

Biodiversity experiments have shown that soil organic carbon (SOC) is not only a function of plant diversity, but is also closely related to the nitrogen (N) -fixing plants. However, the effect of N-fixing trees on SOC chemical stability is still little known, especially with the compounding effects of tree species diversity. An experimental field manipulation was established in subtropical plantations of southern China to explore the impacts of tree species richness (i.e., one, two, four and six tree species) and with/without N-fixing trees on SOC chemical stability, as indicated by the ratio of easily oxidized organic carbon to SOC (EOC/SOC). Plant-derived C components in terms of hydrolysable plant lipids and lignin phenols were isolated from soils for evaluating their relative contributions to SOC chemical stability. The results showed that N-fixing tree species rather than tree species richness had a significant effect on EOC/SOC. Hydrolysable plant lipids and lignin phenols were negatively correlated with EOC/SOC, while hydrolysable plant lipids contributed more to EOC/SOC than lignin phenols, especially in the occurrence of N-fixing trees. The presence of N-fixing tree species led to an increase in soil N availability and a decrease in fungal abundance, promoting the selective retention of certain key components of hydrolysable plant lipids, thus enhancing SOC chemical stability. These findings underpin the crucial role of N-fixing trees in shaping SOC chemical stability, and therefore, preferential selection of N-fixing tree species in mixed plantations is an appropriate silvicultural strategy to improve SOC chemical stability in subtropical plantations.

Litter decomposition is key to ecosystem carbon (C) and nutrient cycling, but this process is anticipated to weaken due to projected more extensive and prolonged drought. Yet how litter quality and decomposer community complexity regulate decomposition in response to drought is less understood. Here, in a five-year manipulative drought experiment in a Masson pine forest, leaf litter from four subtropical tree species (Quercus griffithii Hook.f. & Thomson ex Miq., Acacia mangium Willd., Pinus massoniana Lamb., Castanopsis hystrix Miq.) representing different qualities was decomposed for 350 ​d in litterbags of three different mesh sizes (i.e., 0.05, 1, and 5 ​mm), respectively, under natural conditions and a 50% throughfall rain exclusion treatment. Litterbags of increasing mesh sizes discriminate decomposer communities (i.e., microorganisms, microorganisms and mesofauna, microorganisms and meso- and macrofauna) that access the litter and represent an increasing complexity. The amount of litter C and nitrogen (N) loss, and changes in their ratio (C/Nloss), as well as small and medium-sized decomposers including microorganisms, nematodes, and arthropods, were investigated. We found that drought did not affect C and N loss but decreased C/Nloss (i.e., decomposer N use efficiency) of leaf litter irrespective of litter quality and decomposer complexity. However, changes in the C/Nloss and the drought effect on C loss were both dependent on litter quality, while drought and decomposer complexity interactively affected litter C and N loss. Increasing decomposer community complexity enhanced litter decomposition and allowing additional access of meso- and macro-fauna to litterbags mitigated the negative drought effect on the microbial-driven decomposition. Furthermore, both the increased diversity and altered trophic structure of nematode due to drought contributed to the mitigation effects via cascading interactions. Our results show that litter quality and soil decomposer community complexity co-drive the effect of drought on litter decomposition. This experimental finding provides a new insight into the mechanisms controlling forest floor C and nutrient cycling under future global change scenarios.

The precise interpolation of oceanic temperature and salinity is crucial for comprehending the dynamics of marine systems and the implications of global climate change. Prior neural network-based interpolation methods face constraints related to their capacity to delineate the intricate spatio-temporal patterns that are intrinsic to ocean data. This research presents an innovative approach, known as the Discretized Spatial Encoding Neural Network (DSE-NN), comprising an encoder–decoder model designed on the basis of deep supervision, network visualization, and hyperparameter optimization. Through the discretization of input latitude and longitude data into specialized vectors, the DSE-NN adeptly captures temporal trends and augments the precision of reconstruction, concurrently addressing the complexity and fragmentation characteristic of oceanic data sets. Employing the North Atlantic as a case study, this investigation shows that the DSE-NN presents enhanced interpolation accuracy in comparison with a traditional neural network. The outcomes demonstrate its quicker convergence and lower loss function values, as well as the ability of the model to reflect the spatial and temporal distribution characteristics and physical laws of temperature and salinity. This research emphasizes the potential of the DSE-NN in providing a robust tool for three-dimensional ocean temperature and salinity reconstruction.