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The degradation of alpine meadow profoundly alters soil nitrogen (N) cycling. However, the stability of soil N pools and the response mechanisms of δ15N across different degradation stages remain unclear. In an alpine meadow of Maqin County, Qinghai Province, China, we investigated the effects of degradation on soil stable nitrogen isotopes (δ15N) and their driving factors. Four degradation stages were identified: non-degraded grass meadow (ND), Kobresia humilis + Kobresia pygmaea meadow (SD), thickened turf layer of K. pygmaea meadow (MD), and "black-soil beach" with secondary bare land (HD). The results showed that aboveground biomass significantly decreased with increasing degradation intensity, with biomass in the HD stage reduced to 56.5% of that in the ND stage. Degradation significantly reduced soil pH, electrical conductivity, and soil moisture in the 0-30 cm layer, and altered the vertical distribution pattern of soil C/N. Soil total nitrogen (TN) and microbial biomass nitrogen (MBN) declined markedly with increasing degradation, particularly in the surface soil (0-5 cm), with reductions of 57.8% and 70.6%, respectively. Meadow degradation significantly influenced the distribution of δ15N. In the SD and MD stages, δ15N values increased with soil depth, whereas in the HD stage they became homogenized. The difference in δ15N between surface and deep soil layers (Δδ15N) first decreased and then increased with degradation, approaching zero in the HD stage, indicating a highly open N cycle and homogenization of soil N across the profile. Random forest analysis revealed that the dominant drivers of δ15N varied among degradation stages. Ammonium (NH4+-N) dominated in the ND stage, soil pH in the SD and MD stages, and MBN in the HD stage. Surface soil δ15N was significantly negatively correlated with pH, electrical conductivity, soil moisture, C/N, TN, MBN, and NH4+-N, suggesting that degradation influenced N cycling primarily by altering surface soil environmental condition. In summary, alpine meadow degradation significantly affected soil N pools and N transformation efficiency by altering aboveground biomass and soil physicochemical properties. Δδ15N could serve as an effective indicator of the openness of ecosystem N cycling and degradation stage. 高寒草甸退化显著影响土壤氮循环过程,但不同退化阶段土壤氮库稳定性及δ15N的响应机制尚不明确。本研究以青海省玛沁县高寒草甸为对象,探讨了草甸退化对土壤稳定氮同位素(δ15N)的影响及其驱动因素。退化阶段分为未退化的禾草草甸时期(ND)、矮嵩草+小嵩草草甸时期(SD)、小嵩草草甸草毡表层加厚时期(MD)和黑土滩-杂类草次生裸地时期(HD)。结果表明:随着退化程度加剧,地上生物量显著减少,HD时期生物量仅为ND时期的56.5%。草甸退化显著降低了0～30 cm土层土壤pH、电导率和含水量,并改变了土壤C/N的垂直分布模式。土壤全氮(TN)和微生物生物量氮(MBN)随退化程度加重显著降低,在表层土壤(0～5 cm)中表现最明显,降幅分别达57.8%和70.6%。草甸退化显著影响了δ15N的分布,SD和MD时期δ15N值随土层深度增加而升高,而HD时期则趋向均一化。土壤表层与深层δ15N差值(Δδ15N)随草甸退化呈先降低后升高的趋势,在HD时期接近0,表明此时期氮循环高度开放且土壤剖面氮含量均质化。随机森林模型分析表明,δ15N的主导调控因子因退化时期而异:铵态氮(NH4+-N)主导ND时期,pH主导SD和MD时期,MBN主导HD时期。表层土壤δ15N与pH、电导率、含水量、C/N、TN、MBN和NH4+-N呈显著负相关,表明退化通过改变表层土壤环境影响氮循环过程。综上,高寒草甸退化通过改变地上生物量和土壤理化性质进而显著影响土壤氮库和氮转化效率,Δδ15N是指示氮循环开放程度与退化阶段的有效指标。.

To describe the imaging features of osteonecrosis of the femoral head (ONFH) on 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/CT and explore whether PET/CT can raise suspicion for ONFH in patients with lymphoma. A retrospective analysis was conducted on the clinical data, PET/CT, and MRI findings of 17 patients with lymphoma and ONFH. The 18F-FDG uptake of ONFH was recorded, and the maximum standardized uptake value (SUVmax) of ONFH was measured. The staging and extent of ONFH, and other bone involvements, were visually assessed. Lymphoma disease status was evaluated using the Deauville criteria. A total of 31 femoral heads were involved (2 stage 1, 24 stage 2, 4 stage 3, 1 stage 4). The median SUVmax was higher in stage 3-4 lesions (5.27) than in stage 1-2 lesions (1.37) (P = 0.002). Regarding 18F-FDG uptake patterns, all stage 1 lesions showed normal uptake; among stage 2 lesions, 11 showed increased uptake, 5 showed peripheral increased with central decreased uptake, 2 showed decreased uptake, and 6 showed normal uptake; all stage 3-4 lesions demonstrated increased uptake. On CT, the extent of all stage 2-4 lesions matched MRI findings. Nine patients had osteonecrosis in other bones, including the humeral heads (n = 9), bilateral iliac bones (n = 6), and vertebrae/ribs/scapulae (n = 1). In patients with lymphoma, ONFH exhibits variable degrees of 18F-FDG uptake and may be accompanied by involvement of other bones. PET/CT may raise suspicion for ONFH and detect multiple bone involvements during lymphoma assessment.

Leaf development underpins physiological performance and secondary metabolite accumulation, yet its influence on phyllosphere fungal communities in perennial medicinal plants such as ginseng (Panax ginseng C.A. Meyer) remains poorly understood. Understanding how developmental stage affects leaf chemistry and microbial assembly is important for linking plant metabolism with aboveground microbial ecology. We analyzed ginseng leaves across four developmental stages (S1-S4) using physiological measurements, ginsenoside profiling, untargeted metabolomics, ITS amplicon sequencing, fungal association networks, and metabolite-fungus correlations. Leaf physiological traits and ginsenoside content peaked at stage S2, representing a developmental optimum. Metabolomics revealed early enrichment of sugar phosphates, nucleotide metabolites, and membrane lipids, followed by late accumulation of raffinose-family oligosaccharides, phenylpropanoids, flavonoids, oxylipin-related lipids, and brassinosteroid-linked metabolites. Fungal richness and evenness increased from S1 to S4, with communities shifting from Ascomycota-dominated at early stages to Basidiomycota-enriched on senescing leaves. Fungal association networks showed stage-related increases in network size and changes in topological organization. Integrative analyses indicated that stage-specific metabolic changes were closely associated with fungal community succession, with amino acid, carbohydrate, lipid, flavonoid, and terpenoid pathways potentially linked to stage-specific fungal association patterns. Ginseng leaf development was accompanied by coordinated physiological and metabolic reprogramming that was associated with shifts in phyllosphere fungal composition and inferred association networks. These findings highlight leaf developmental stage as an important context for aboveground microbial dynamics and provide a framework for linking plant metabolism with microbial ecology in perennial crops, while emphasizing that causal relationships between specific metabolites and fungal taxa require further experimental validation.

To develop and validate the Q-Bone system, an intelligent quantitative system for anatomically driven assessment of alveolar bone loss and assistance in the diagnosis of periodontitis across multiple clinical centers and imaging devices. This study included 1,273 periodontitis cases from four clinical centers using diverse imaging devices. A multitask deep learning model, Deep Gradient Network (DGNet), was employed for tooth segmentation and anatomical keypoint localization, and was integrated with an anatomically driven, curvature-based quantification algorithm for alveolar bone resorption ratio (ABRR) measurement. Performance was evaluated using internal and multicenter external datasets, including patient-level agreement analysis for Stage, Grade, and Extent. The Q-Bone system demonstrated strong performance: tooth segmentation achieved an S-measure of 0.929, and keypoint localization reached a PRCK@0.5 of 0.994 in internal validation. Tooth-level ABRR showed high agreement with specialist measurements, with an ICC of 0.973 and minimal bias (- 0.238%). In the multicenter clinical validation cohort (n = 174), agreement between Q-Bone and the specialist reference standard was high at the patient level, with Cohen's κ values of 0.9351 for Stage, 0.9367 for Grade, and 0.9770 for Extent. For the ordinal outcomes of Stage and Grade, linear weighted κ values were 0.9508 and 0.9515, respectively. The Q-Bone system enables automated tooth segmentation, anatomical keypoint localization, tooth-level quantification of alveolar bone loss, and patient-level assessment across Stage, Grade, and Extent. It showed high agreement with specialist reference standards across multicenter and cross-device settings, supporting its applicability as a standardized imaging-based assistance tool for periodontal evaluation.

Given the persistent transmission and marked spatial heterogeneity of echinococcosis in endemic settings, a comprehensive spatiotemporal assessment is warranted. This study aimed to characterize the spatiotemporal epidemiology of echinococcosis in the Xinjiang Uygur Autonomous Region from 2005 to 2024, develop a time-series forecasting framework, and inform region-specific prevention and control strategies. Spatiotemporal clustering analysis was conducted to delineate geographic heterogeneity and dynamic transmission patterns at the county level. An interrupted time series framework was employed to estimate changes in the level and slope associated with the implementation of the universal free health examination policy in September 2016. Subsequently, a seasonal autoregressive integrated moving average (SARIMA) model was fitted to characterize temporal autocorrelation structures and seasonal fluctuations and to produce short-term forecasts of incidence trends. From 2005 to 2024, a total of 23,813 echinococcosis cases were reported in Xinjiang, with an average annual incidence of 5.48 per 100,000 population. Incidence increased significantly from January 2005 to August 2016 (&#x3b2;&#x2009;=&#x2009;0.0026 per 100,000 per month, P&#x2009;<&#x2009;0.001), with an immediate increase observed in September 2016 (0.2265 per 100,000, P&#x2009;<&#x2009;0.05), and then declined significantly through December 2024 (&#x3b2; = -0.0069 per 100,000 per month, P&#x2009;<&#x2009;0.001). Spatial clustering was observed in the Ili and Altay regions. Incidence increased and then decreased across sex and age groups, with larger declines among males. Significant reductions were observed in the 15-44 and &#x2265;&#x2009;45 year groups, but not in the 0-14 year group. The optimal first-stage model was SARIMA(1,1,0)(2,0,0)&#x2081;&#x2082;, and the second-stage model was SARIMA(0,1,1)(1,0,2)&#x2081;&#x2082;. The second-stage model produced a relative prediction error of -&#x2009;14.06% and projected 1,040 cases in 2025. Echinococcosis incidence in Xinjiang demonstrated a temporal increase followed by a sustained decline, with pronounced spatial heterogeneity across regions. Despite inherent uncertainty, SARIMA-based projections offer evidence to strengthen early warning systems and guide region-specific control strategies.

A comprehensive policy framework constitutes a crucial institutional foundation for the sustainable development of healthcare systems and quantitative evaluation of public policies offers a scientific basis for policy refinement and optimization. Amid ongoing healthcare reform and profound shifts in the structure of demand for medical resources, systematically assessing the textual quality of national-level medical resource allocation policies, together with examining of their structural characteristics and evolutionary trajectories, carries considerable practical significance. Through a systematic screening process, 16 national-level policy documents on medical resource allocation were identified. Text-mining techniques were applied to extract high-frequency keywords and build a keyword co-occurrence network, after which the PMC-index model was then used to quantitatively assess the overall quality of these policies. Heterogeneity analyses were then conducted across policy quality grades and time periods to reveal structural differences and evolutionary patterns. The average PMC-index across the 16 policies was 6.67, suggesting that China's medical resource allocation policies are generally of relatively high quality. However, the analysis revealed several structural weaknesses, including limited predictive and forward-looking content, insufficient medium- to long-term planning, and an under-supply of higher-level policy instruments. Temporal analysis showed that the PMC-index increased from the Exploration Stage to the Deepening Stage before declining modestly in the Focus Stage. China's medical resource allocation policies are of relatively high overall quality, yet further improvements remain necessary. Future policy efforts should focus on three priorities: optimizing the hierarchical structure of the policy system, strengthening policy predictability and medium- to long-term planning orientation, and refining policy content and implementation mechanisms. Together, these efforts would enhance the systematization, stability, and governance effectiveness of the policy framework.

Cardiovascular-kidney-metabolic (CKM) syndrome, newly introduced by the American Heart Association, aims to promote the integrated management of metabolic dysfunction, chronic kidney disease, and cardiovascular disease (CVD). The C-reactive protein-triglyceride-glucose index (CTI), a novel composite biomarker that captures both systemic inflammation and insulin resistance, has emerged as a promising metric in cardiometabolic research. However, current evidence regarding its clinical utility remains limited. To date, no studies have systematically examined the association between CTI and CVD risk, particularly across CKM syndrome stages 0 to 3. The China Health and Retirement Longitudinal Study (CHARLS), initiated in 2011, is a large-scale, nationally representative, multicenter prospective cohort study. In accordance with predefined inclusion and exclusion criteria, a total of 6,859 participants were included in the final analysis. To assess the association between CTI and CVD risk, Cox proportional hazards models, receiver operating characteristic (ROC) curve analysis, restricted cubic spline modeling, and stratified subgroup analyses were conducted. During the 10-year follow-up period, 1391 incident CVD events were recorded. In the fully adjusted model, a significant positive association was observed between CTI and CVD risk, with each one-standard deviation increases in CTI corresponding to a 7% higher risk of CVD. Receiver operating characteristic (ROC) curve analysis demonstrated that the CTI improved the discriminatory power of the baseline model for predicting CVD. Restricted cubic spline modeling revealed a nonlinear, S-shaped relationship between CTI and CVD risk. Moreover, analyses stratified across most CKM syndrome stages consistently revealed a positive correlation between CTI and CVD risk. Our findings suggest a positive, S-shaped association between CTI and CVD risk in individuals with CKM syndrome stages 0-3. Enhancing the assessment of CTI could provide a more accessible and efficient screening tool for the prevention and management of CVD in this population.

Chronic liver disease (CLD) and its progression to compensated cirrhosis (CC), decompensated cirrhosis (DC), and acute-on-chronic liver failure (ACLF) represent a global health crisis with high mortality. The "gut-liver axis" plays a pivotal role in this progression, yet a systematic characterization of the dynamic microbial evolution across the entire disease spectrum remains elusive. We aimed to systematically characterize the gut microbiota's dynamic evolution across the spectrum of chronic liver disease and to develop machine-learning models for predicting its critical transitions. In this retrospective cohort study, 947 patients with liver disease (CLD, n&#x2009;=&#x2009;464; CC, n&#x2009;=&#x2009;159; DC, n&#x2009;=&#x2009;260; ACLF, n&#x2009;=&#x2009;64) were enrolled. The relative abundances of 10 dominant gut microbiota-including Enterococcus, Lactobacillus, Clostridium leptum, Clostridium butyricum, Eubacterium rectale, Faecalibacterium prausnitzii, Bacteroides, Enterobacterium, Bifidobacterium, and Atopobium cluster-were quantified via qPCR. Random Forest (RF) models were constructed to predict transitions between disease stages. The discriminatory efficacy of the Enterococcus/Eubacterium rectale Ratio (E/Er Ratio) was further evaluated using Receiver Operating Characteristic (ROC) analysis. Four distinct dynamic evolutionary patterns were identified. The pro-inflammatory/anti-inflammatory ratio increased 5.4-fold from CLD to ACLF. Random Forest models accurately predicted all disease transitions. The model for the DC-to-ACLF transition performed best (Area Under the Curve, AUC&#x2009;=&#x2009;0.961), with clinical parameters (PT, TBil) being the strongest predictors. While the addition of microbial features yielded a modest incremental gain in AUC for the late-stage transition, indices such as the Specific-Butyrate-to-Total ratio were identified as key features, providing critical biological insights into the systemic failure of the gut-liver axis. The E/Er Ratio further served as a robust, non-invasive marker for identifying critical disease turning points. Liver disease progression is characterized by a systematic shift in the gut microbiota from an anti-inflammatory, butyrate-rich state to a pro-inflammatory, pathogen-dominant environment. The integrated RF models and the E/Er Ratio provide a powerful, non-invasive framework for the early prediction and risk stratification of chronic liver disease progression, offering potential targets for gut-centered therapeutic interventions.

Frontline therapy for classic Hodgkin Lymphoma (cHL) incorporating brentuximab vedotin (BV) improves outcomes compared with traditional chemotherapy, but up to 20% of patients relapse and need salvage treatment. Prior retrospective studies examining salvage therapies are mostly limited to patients who received chemotherapy-based treatment in frontline without novel agents. We evaluated outcomes in 116 patients with relapsed/refractory (R/R) cHL who received brentuximab and anthracycline-containing frontline treatment. High risk factors at relapse or progression were common, including primary refractory disease (62%), advanced stage (63%), and extranodal disease (46%). At first salvage, 73% of patients received PD-1 blockade (58% in conjunction with chemotherapy), and 81% received PD-1 blockade at any salvage line. Overall, 78% of patients proceeded to ASCT. With a median follow-up of 19 months, the 2-year PFS and OS from the start of salvage in all patients were 61% and 97% respectively. Among patients with ASCT, the 2-year post-transplant PFS (PFSHCT) was 76% for patients who had PD-1 blockade as salvage before ASCT, compared with 59% for those who did not. In univariate analysis, PD-1 blockade use in first salvage was significantly associated with improved PFSHCT, and this association remained statistically significant after adjusting for stage, extranodal involvement, and primary refractory disease (HR 0.31, p&#x2009;=&#x2009;0.04). Primary refractory disease after BV-AVD emerged as an ongoing unmet need with a significantly inferior 2-year PFSHCT compared with relapsed patients (58% vs 86%, p&#x2009;=&#x2009;0.017). Among primary refractory patients who received ASCT, first salvage incorporating a PD-1 blockade showed a trend toward improved PFSHCT compared with non-PD-1 blockade salvage. These results support PD-1 blockade incorporation as preferred first salvage in R/R cHL after BV-containing frontline therapy.

Tumour-associated autoantibodies (TAAbs) are promising biomarkers for cancer detection, but their induction and clinical relevance in lung cancer remain unclear. Serum samples from 695 individuals were analysed for TAAb profiling by protein-array screening and two-stage ELISA validation. Diagnostic models were constructed with identified TAAbs and compared with conventional tumour markers. Potential mechanisms, clinical and prognostic features of TAAb seropositivity were analysed and its presence in prediagnostic sera was evaluated to assess the potential for early detection. Six TAAbs for small cell lung cancer (SCLC) and four for lung adenocarcinoma (LUAD) were identified, demonstrating excellent diagnostic performance (AUC&#x2009;>&#x2009;0.8) and outperforming ProGRP and CEA. TAAb induction correlated with antigen overexpression, somatic mutations and HLA class II amino acid polymorphisms. TAAb panel seropositivity was associated with older age and advanced stage in both subtypes, and predicted poor survival in SCLC but a favourable outcome in advanced LUAD. In prediagnostic sera, the TAAb concentration increased progressively, with detectability up to 2 years before clinical diagnosis. Distinct TAAb panels were identified for SCLC and LUAD, serving as accurate diagnostic markers that enable early detection and as indicators of prognosis in different clinical contexts.

Ambient ozone pollution represents a growing threat to public health. However, evidence regarding its association with ovarian reserve and the mediating mechanisms remains limited and inconsistent. This cross-sectional study included 8,233 women aged 20-45 who attended the Center for Reproductive Medicine at Jiangxi Maternal and Child Health Hospital between 2021 and 2023. Based on data from the Tracking Air Pollution in China project, ozone exposure was determined by assigning 10-km-resolution daily maximum 8-hour average ozone concentration to each participant's residential address. Serum anti-M&#xfc;llerian hormone (AMH) levels were measured to evaluate ovarian reserve, with six distinct exposure periods defined according to the stages of female follicular development. Participants' lipid profiles were characterized by total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol and triglycerides. The ozone-AMH relationship was assessed using multivariable linear regression models, supplemented by stratified, mediation, and sensitivity analyses. Each interquartile range increase in ozone concentration was linked to an 8.14% (95% confidence intervals [CI]: 3.09% to 12.93%) decrease in AMH levels during period 4. Compared with women aged 20-29 years, this ozone-related decline was less pronounced among women over 35 (P for interaction&#x2009;=&#x2009;0.004). Among the four lipid indicators, TC mediated 11.415% of the association between ozone and AMH levels, while LDL-C accounted for 7.38%. Similar findings were observed for period 6, while no significant linear associations were identified across the other periods. Higher ambient ozone exposure is significantly linked to diminished ovarian reserve. This association is particularly evident during the developmental window from primary and secondary follicles to small antral follicle stage, with younger women showing greater susceptibility. To the best of current knowledge, this study provides the first evidence that alterations in lipid profiles may partially mediate this relationship, offering novel insights for protecting female reproductive health and informing environmental health interventions.

The Sea of Okhotsk (OK) is a crucial transition zone for Chum salmon Oncorhynchus keta from Japanese (JP), Korean (KR), and Russian (RS) populations. Population-specific return-abundance patterns diverged in the early 2000s, when OK warmed rapidly. Previous studies focused on coastal early-life factors cannot fully explain shifts in populations returning to the rapidly warming East/Japan Sea. This study analyzed how environmental changes influenced the return-abundance patterns of JP, RS, and KR, focusing on differences before and after 2000. Key drivers shifted over time: KR, the southwestern marginal population, became increasingly dependent on marine environmental conditions; the drivers of JP return abundance shifted from environmental to hatchery-driven factors; and RS return abundance increased due to favorable conditions and greater releases. During the return stage, key environmental variables for all populations shifted from the Soya to the Tatar route, suggesting northward migration in response to warming. OK warming contributed to reduced JP return abundance across early-life and return stages, whereas RS return abundance increased under more favorable conditions. The increase in RS return abundance increase helped maintain KR return abundance post-2000. This study highlights those population-specific responses to a shared warming signal and helps management strategies, improving forecasts of climate-change impacts on Chum salmon.

Lonicera macranthoides is an important medicinal plant in the genus Lonicera, and its flowers possess significant medicinal value. 'Jincuilei' (JCL), a newly bred variety, is characterized by a long flowering period and persistently closed corollas. To investigate the molecular mechanism underlying the non-dehiscent corolla phenotype in JCL, we performed whole-genome sequencing, transcriptomics, and metabolomics analyses of this variety. The results showed that the L. macranthoides genome size is approximately 879.83&#x2009;Mb, assembled into 439 contigs with a contig N50 of 67.38&#x2009;Mb, which were further scaffolded into 9 pseudochromosomes. Comparative genomics analysis revealed that the divergence time between Lonicera japonica (Japanese honeysuckle) and L. macranthoides occurred approximately 15.1 million years ago (Mya). Within L. macranthoides, comparisons identified 525 expanded and 555 contracted gene families relative to L. japonica. Analysis of endogenous hormone levels in floral organs of JCL and wild-type (WT) plants across different developmental stages revealed highly significant differences in jasmonic acid (JA) content at all stages. Further transcriptomic and metabolomic analyses indicated that both the JA biosynthesis and signaling pathways play key roles in regulating corolla dehiscence. These findings provide valuable insights into Caprifoliaceae evolution and the molecular basis of corolla morphogenesis in L. macranthoides.