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Studying the spatial and temporal changes of grassland soil organic carbon (SOC) is helpful in promote the management of regional ecosystem carbon sinks. Grazing is one of the main ways of rational utilization of grassland. Different grazing intensities will affect the change of SOC density. Under different grazing intensity and management measures in Zhangye grassland, this study uses the parameter localized CENTURY model to simulate the temporal and spatial variations of SOC density from 1970 to 2022. The results showed that long-term light grazing reduced the average SOC by 195.114 g·m −2 and 1.91%. Moderate and severe grazing, respectively, for a long time made the total SOC density loss of 5.21% and 17.69%. In a short period, mild and moderate grazing reduced total SOC first and then increased it. Under light grazing, total SOC density appeared higher relative changes in the southeast, and lower in the northwest and central. There was no significant difference in the relative changes of total SOC between steppe and desert grasslands under light grazing. The decrease range of steppe was gradually greater than that in desert grassland. Since different management measures were implemented in some sampling sites in 2017, we divided the study period into two periods, 1970–2016 and 2017–2022. The implementation of degraded grassland improvement, fallow grazing, and rotational grazing would increase the total SOC density and mild SOC density, rotational grazing > degraded grassland improvement > rest grazing. Rotational grazing and the improvement of degraded grassland increased the density of active and inert SOC, while resting grazing decreased the density of SOC.

Inflammation, nutritional status, and depression interact complexly, impacting health outcomes. This study investigates their associations with all-cause and cardiovascular mortality in middle-aged and elderly individuals with osteoporosis. Using NHANES data from 2007 to 2023, the study applied Cox regression models and restricted cubic spline plots to assess the effects of ALI (Advanced Lung Cancer Inflammation Index) and PHQ-9 scores on mortality outcomes in osteoporosis patients. Subgroup, threshold, and mediation analyses were also conducted. The study included 862 cases of all-cause mortality and 211 cardiovascular deaths. Higher ALI was associated with reduced mortality risk, while higher PHQ-9 scores indicated increased mortality risk. Combined analysis showed that osteoporosis patients with high ALI and no depressive symptoms had the lowest mortality risk. Restricted cubic spline and threshold analyses revealed a linear negative correlation between ALI and mortality risk and a nonlinear positive correlation between PHQ-9 scores and mortality risk. Subgroup analysis showed gender, physical activity, and sleep status influenced the interaction between ALI/PHQ-9 and mortality risk. Causal mediation analysis with bootstrapping found that ALI mediated 3.9% of the effect of osteoporosis on all-cause mortality and 5.6% on cardiovascular mortality, while PHQ-9 scores mediated 6.6% of cardiovascular mortality. A significant negative correlation exists between ALI and mortality risk in osteoporosis patients, while PHQ-9 scores correlate positively. Favorable nutrition and inflammation, coupled with the absence of depression, help reduce mortality risks.

This paper examines the strategic decisions of fashion brands to develop and sell non-fungible tokens (NFTs) within the metaverse. We construct two operational models based on whether NFTs are adopted: the traditional fashion model without NFT (Scenario T) and the digital fashion model with NFT (Scenario D). By comparing the equilibrium outcomes of fashion brands in Scenarios T and D, we derive valuable insights into the implementation of digital strategies in the fashion industry. Our analysis reveals three key findings. First and foremost, the proportion of fashion customers to conventional customers, as well as the digital value and cost of NFTs, are direct factors influencing the adoption of digital strategies by fashion brands. Secondly, opportunistic pricing by manufacturers is an indirect factor influencing fashion brands’ strategic choices, and a fixed production price contract can effectively avoid this case. Finally, we find that personalized pricing and a free NFT strategy are effective tools to boost fashion brands’ digital revenues.

Changes in the volume transport of Atlantic water into the Arctic Ocean can affect the heat and mass balance in the central Arctic Ocean. To understand the impacts of Arctic storms on the inflow through Fram Strait, we implemented the NEMO ocean model for the Arctic Ocean, to simulate the decadal variations of the water volume transport through Fram Strait. The simulations suggest that the water inflow tends to be weaker in the decades of the 1960 and 2010s but stronger in the 1980s. The decadal variation is associated with decadal variability of the storm density in the Greenland Sea. When there is an increased storm density near Fram Strait, the southerly wind anomalies dominate the Atlantic water pathway. As a response, there is an increased Atlantic inflow through Fram Strait. Plain Language Summary On decadal scales, Arctic storms near Fram Strait are highly correlated with the water volume transport into the Arctic Ocean through Fram Strait. When there are more storms near Fram Strait, the transport tends to increase. In addition, the heat flux associated with the water volume transport reflects the impacts of both the linear trend in ocean temperature and the decadal variation of water volume transport. Key Points On a decadal scale, the storms in the Greenland Sea can affect the volume transport of Atlantic water inflow through Fram Strait Associated heat flux reflects the impacts of both the linear trend in ocean temperature and the decadal variation of water volume transport

Osteoporosis significantly increases fracture risk and mortality, yet robust tools for predicting long-term mortality in this population are lacking.This study aimed to develop and validate a nomogram for predicting 5-year all-cause mortality among patients with osteoporosis. A retrospective cohort study was conducted using data from 2,165 osteoporosis patients sourced from the NHANES database (2007-2023; training set) and 304 patients from Dandong Central Hospital (2017-2024; validation set). Potential risk factors were analyzed through LASSO regression, followed by multivariate logistic regression, to identify independent predictors.A nomogram was constructed employing significant predictors. Finally, the C-index, ROC curve, calibration curve, and decision curve analysis were utilized to validate the model in both the training and validation sets. In the study population, 192 patients died in the training set and 36 patients died in the experimental set. At the same time, we collected detailed baseline demographic data. Specifically, the age distribution of the training set was 56.07 ± 17.62, and that of the experimental set was 57.11 ± 18.34. Among them, 49.52% of the training set were male, and 50.99% of the experimental set were male. During the study period, we recorded 228 deaths. Seven independent predictors of 5-year all-cause mortality were identified: increased Age (OR=1.090,95%Cl: 1.115-2.313), Male gender (OR=1.606,95%Cl: 1.071-1.109), Smoking (OR=1.945,95%Cl: 1.289-2.933), higher FBG (OR=1.006,95%Cl: 1.002-1.010), higher Uric acid (OR=1.177,95%Cl: 1.039-1.332); Alcohol use (OR=0.583,95%Cl: 0.410-0.827) and higher BMI (OR=0.946,95%Cl: 0.909-0.985) were protective. The resulting nomogram demonstrated strong discriminatory ability in both the training set (AUC = 0.834) and validation set (AUC = 0.862). In the validation set, the precision rate was 0.514, the recall rate was 0.5, and the F1-score was 0.507. Calibration plots and the Hosmer-Lemeshow test indicated good agreement between predicted and observed outcomes (p > 0.05). Decision curve analysis confirmed significant clinical utility across a wide range of risk thresholds. This study developed and validated a novel nomogram incorporating seven common clinical factors, which can predict the 5-year all-cause mortality risk in patients with osteoporosis. Although the tool demonstrated good performance and has the potential to assist in clinical risk stratification and personalized management, there are still some limitations in the study design. Therefore, its clinical applicability should be interpreted with caution until further external validation.

In this work, we report a compact and highly sensitive photoacoustic spectroscopy (PAS) system based on a cone–sphere coupled photoacoustic cell (CSC-PAC) for real-time detection of trace acetylene (C[sub.2]H[sub.2]) dissolved in transformer oil. The sensing module integrates a conical resonator with a spherical cavity, forming a hybrid structure that effectively enhances photoacoustic confinement and energy coupling efficiency. Finite element thermo-viscoelastic simulations were employed to optimize the cavity geometry and resonance conditions for maximum signal generation. Experimental results demonstrate a strong linear correlation between the photoacoustic signal and C[sub.2]H[sub.2] concentration (R[sup.2] > 0.999), with a sensitivity of 2.45 µV·ppm[sup.−1]. Allan deviation confirms a detection limit of 18.6 ppb is achieved at a 400 s averaging time, confirming excellent system stability. The miniaturized light-acoustic spectroscopy sensor, with a total volume of 7.5 mL and a rapid response time of 25.5 s, provides a high-performance and field-deployable platform for on-site monitoring of high-voltage power equipment and other industrial applications.

Osteoporosis is a systemic metabolic bone disorder characterized by a decrease in bone mass and the degradation of bone microarchitecture. Nevertheless, the precise influence of the core marker of metabolic syndrome—insulin resistance—on the prognosis of patients with osteoporosis and osteopenia remains insufficiently understood. This study seeks to clarify the association between a novel insulin resistance metric, METS-IR, and the risks of all-cause and cardiovascular mortality among individuals diagnosed with OP. This study utilizes data from the National Health and Nutrition Examination Survey (NHANES) collected between 2007 and 2023, employing multivariable Cox proportional hazards regression models and restricted cubic splines to investigate the association between the METS-IR index and the risk of all-cause and cardiovascular mortality in patients diagnosed with osteoporosis and osteopenia. Furthermore, subgroup analyses were performed to identify potential effect modifications and high-risk subpopulations. The study cohort included 2175 individuals with osteoporosis and osteopenia, followed for 16 years, during which 468 all-cause deaths and 102 cardiovascular-related deaths were documented. The study identified a nonlinear positive association between the METS-IR index and the risks of all-cause mortality among patients with osteoporosis and osteopenia. However, no significant association was observed between METS-IR and cardiovascular mortality. At a METS-IR threshold of 2.3, the hazard ratio reached 1, indicating a shift in the risk of all-cause mortality from low to high. Furthermore, subgroup analyses demonstrated a stronger association between METS-IR and all-cause mortality risks in individuals with elevated METS-IR levels or comorbid diabetes, while no such significant relationship was found for cardiovascular mortality. This study highlights a nonlinear positive association between the insulin resistance marker METS-IR and all-cause mortality among patients with osteoporosis and osteopenia, whereas no significant association was observed with cardiovascular mortality. These findings enhance the understanding of insulin resistance’s role in osteoporosis and its comorbidities, particularly in relation to all-cause mortality. This underscores the importance of managing insulin resistance to improve overall survival outcomes, while further studies are needed to explore its specific impacts on cardiovascular outcomes.

The association between insulin resistance (IR) and the risk of all-cause mortality and cardiovascular mortality among osteoarthritis (OA) patients remains uncertain. This study aims to clarify the correlation between a novel marker of IR, the triglyceride glucose-body mass index (TyG-BMI), and the risk of all-cause mortality and cardiovascular mortality in OA patients. Data from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2020 were analyzed. Multivariable Cox proportional hazards regression analysis and restricted cubic spline plots were employed to elucidate the association between the TyG-BMI index and the risk of all-cause mortality or cardiovascular mortality in OA patients. Additionally, subgroup analysis was conducted to explore potential interactions and identify populations at elevated risk of mortality. The study cohort comprised 4097 OA patients who were followed up for a period of 20 years, during which 1197 cases of all-cause mortality and 329 cases of mortality attributed to cardiovascular disease were recorded. Our findings revealed a U-shaped nonlinear relationship between the TyG-BMI index and the risk of all-cause mortality or cardiovascular mortality in OA patients, with the lowest mortality risk thresholds identified at 282 and 270, respectively. Moreover, surpassing these thresholds was associated with a 3% increase in the risk of all-cause mortality and a 5% increase in the risk of cardiovascular mortality for every 10-unit increment in TyG-BMI level. Among American OA patients, a U-shaped nonlinear relationship exists between the TyG-BMI index and the risk of all-cause mortality or cardiovascular mortality. These findings underscore the significant role of IR in the progression of OA.

Background Metabolic disorders play a significant role in determining the length of hospital stay following hip fracture surgery in elderly patients. Therefore, it is crucial to conduct an in-depth investigation into the relationship between stress-induced hyperglycemia—one of the manifestations of metabolic disorders—and hospitalization duration in this patient population. Methods This retrospective cohort study analyzed medical records of patients who underwent hip fracture surgery at a tertiary medical institution between January 2017 and November 2024. LASSO regression identified covariates for multivariate logistic regression. Propensity score matching minimized bias. Standardized mean differences assessed group balance. Logistic regression, restricted cubic splines, and dose-response analyses examined associations between blood glucose levels and LOS. Subgroup and threshold analyses evaluated robustness. Results A total of 1,279 patients were included, with 673 (52.6%) having persistent preoperative hyperglycemia. The mean age was 74.7 ± 9.6 years, with 39.7% male and 60.3% female. Persistent hyperglycemia was significantly associated with prolonged LOS. Multivariate logistic regression showed a 12% increase in LOS for each unit increase in preoperative glucose (OR = 1.12, 95% CI: 1.07–1.18). Propensity score matching confirmed this association, with a significant linear trend ( P  < 0.001). Subgroup analyses revealed interactions with gender, hypertension, cerebrovascular disease, and diabetes mellitus. Conclusion Preoperative blood glucose levels are significantly associated with prolonged LOS in elderly hip fracture patients, showing a nonlinear dose-response relationship. Each 1 mmol/L increase in glucose raises LOS risk by 12%, with stronger correlations in females and diabetics. Timely intervention is critical above 6.16 mmol/L.

Microbiome dysbiosis is a hallmark of inflammatory bowel disease (IBD), and its reprogramming represents a promising intervention strategy. Existing treatments are often limited by gastrointestinal instability and non-specific microbial toxicity, leading to suboptimal outcomes and potential aggravation of IBD symptoms. Herein, we construct a calcium phosphotungstate gel (CPW), characterized by tortile nanofibers (length > 5 μm, diameter ~ 20 nm) forming a stable 3D network, which remains structurally intact in gastrointestinal fluid for over 24 h and exhibits commendable resistance to gastric acid and digestive enzymes. Furthermore, CPW disintegrates specifically in response to the inflammatory biomarker calprotectin (CAL), releasing over 54% of tungsten payloads within 12 h (versus < 6% without CAL). The locally released tungsten ions selectively inhibit nitrate respiratory enzymes and induce apoptosis in approximately 50% of nitrate-dependent pathogens within 24 h, enabling precise microbiome modulation. As a versatile carrier, CPW demonstrated exceptional protection for diverse therapeutics (DIO, peptides, nucleic acids) against digestive enzymes, enabling > 70% cargo release specifically at inflamed sites. In DSS-induced colitis mice, DEX-loaded CPW (DEX@CPW) significantly improved colon length (comparable to healthy controls), reduced pro-inflammatory cytokines (IL-1β, IL-6, TNF-α by 2.1–3.3 fold), and restored beneficial microbiota. Crucially, CPW reduced systemic tungsten exposure by 62.7% in kidneys while increasing intestinal tungsten retention by 1.67-fold, demonstrating superior targeting. This dual-function platform—integrating pathogen-selective metallotherapy and inflammation-triggered drug release—represents a promising clinical approach for IBD by simultaneously modulating dysbiosis and ameliorating inflammation. Graphical abstract