Strength-ductility materials by engineering a coherent interface at incoherent precipitates.

In the quest for excellent light-structural materials that can withstand mechanical extremes for advanced applications, design and control of microstructures beyond current material design strategies have become paramount. Herein, we design a coherent shell at incoherent precipitates in the 2195 aluminum alloy with multi-step metastable phase transitions. A high local strain rate via a neoteric deformation-driven metallurgy method facilitated the diffusion of Li. The original T1 (Al2CuLi) phases were transformed into coherent-shell (Li-rich) irregular-coated incoherent-core (Al2Cu) precipitates. The ultimate tensile strength and elongation reached 620 ± 18 MPa and 22.3 ± 2.2%, exhibiting excellent strength-ductility synergy. Grain boundaries, dislocation, solid solution atoms, and precipitates all contributed to the yield strength of the materials, among which precipitates occupied a dominant position, contributing approximately 56.07%. A new "incoherent-coherent interact" strain-hardening mechanism was also clarified, which was believed to be promoted in other heat-treatable alloy systems, especially with multi-step metastable phase transitions.

Deep learning to predict rapid progression of Alzheimer's disease from pooled clinical trials: A retrospective study.

The rate of progression of Alzheimer's disease (AD) differs dramatically between patients. Identifying the most is critical because when their numbers differ between treated and control groups, it distorts the outcome, making it impossible to tell whether the treatment was beneficial. Much recent effort, then, has gone into identifying RPs. We pooled de-identified placebo-arm data of three randomized controlled trials (RCTs), EXPEDITION, EXPEDITION 2, and EXPEDITION 3, provided by Eli Lilly and Company. After processing, the data included 1603 mild-to-moderate AD patients with 80 weeks of longitudinal observations on neurocognitive health, brain volumes, and amyloid-beta (Aß) levels. RPs were defined by changes in four neurocognitive/functional health measures. We built deep learning models using recurrent neural networks with attention mechanisms to predict RPs by week 80 based on varying observation periods from baseline (e.g., 12, 28 weeks). Feature importance scores for RP prediction were computed and temporal feature trajectories were compared between RPs and non-RPs. Our evaluation and analysis focused on models trained with 28 weeks of observation. The models achieved robust internal validation area under the receiver operating characteristic (AUROCs) ranging from 0.80 (95% CI 0.79-0.82) to 0.82 (0.81-0.83), and the area under the precision-recall curve (AUPRCs) from 0.34 (0.32-0.36) to 0.46 (0.44-0.49). External validation AUROCs ranged from 0.75 (0.70-0.81) to 0.83 (0.82-0.84) and AUPRCs from 0.27 (0.25-0.29) to 0.45 (0.43-0.48). Aß plasma levels, regional brain volumetry, and neurocognitive health emerged as important factors for the model prediction. In addition, the trajectories were stratified between predicted RPs and non-RPs based on factors such as ventricular volumes and neurocognitive domains. Our findings will greatly aid clinical trialists in designing tests for new medications, representing a key step toward identifying effective new AD therapies.

Assessment of Efficacy and Accuracy of Cervical Cytology Screening With Artificial Intelligence Assistive System.

The role of artificial intelligence (AI) in pathology offers many exciting new possibilities for improving patient care. This study contributes to this development by identifying the viability of the AICyte assistive system for cervical screening, and investigating the utility of the system in assisting with workflow and diagnostic capability. In this study, a novel scanner was developed using a Ruiqian WSI-2400, trademarked AICyte assistive system, to create an AI-generated gallery of the most diagnostically relevant images, objects of interest (OOI), and provide categorical assessment, according to Bethesda category, for cervical ThinPrep Pap slides. For validation purposes, 2 pathologists reviewed OOIs from 32,451 cases of ThinPrep Paps independently, and their interpretations were correlated with the original ThinPrep interpretations (OTPI). The analysis was focused on the comparison of reporting rates, correlation between cytological results and histologic follow-up findings, and the assessment of independent AICyte screening utility. Pathologists using the AICyte system had a mean reading time of 55.14 seconds for the first 3000 cases trending down to 12.90 seconds in the last 6000 cases. Overall average reading time was 22.23 seconds per case compared with a manual reading time approximation of 180 seconds. Usage of AICyte compared with OTPI had similar sensitivity (97.89% vs 97.89%) and a statistically significant increase in specificity (16.19% vs 6.77%) for the detection of cervical intraepithelial neoplsia 2 and above lesions. When AICyte was run alone at a 50% negative cutoff value, it was able to read slides with a sensitivity of 99.30% and a specificity of 9.87%. When AICyte was run independently at this cutoff value, no sole case of high-grade squamous intraepithelial lesions/squamous cell carcinoma squamous lesion was missed. AICyte can provide a potential tool to help pathologists in both diagnostic capability and efficiency, which remained reliable compared with the baseline standard. Also unique for AICyte is the development of a negative cutoff value for which AICyte can categorize cases as "not needed for review" to triage cases and lower pathologist workload. This is the largest case number study that pathologists reviewed OOI with an AI-assistive system. The study demonstrates that AI-assistive system can be broadly applied for cervical cancer screening.

Extrinsic-Riveting Friction Stir Lap Welding of Al/Steel Dissimilar Materials.

To obtain high-quality joints of Al/steel dissimilar materials, a new extrinsic-riveting friction stir lap welding (ERFSLW) method was proposed combining the synthesis advantages of mechanical riveting and metallurgical bonding. SiC-reinforced Al matrix composite bars were placed in the prefabricated holes in Al sheets and steel sheets, arranged in a zigzag array. The bars were stirred and mixed with Al sheets under severe plastic deformation (SPD), forming composite rivets to strengthen the mechanical joining. SiC particles were uniformly dispersed in the lower part of the welding nugget zone (WNZ). The smooth transition between the SiC mixed zone and extrinsic-riveting zone (ERZ) ensured the metallurgical bonding. The maximum tensile shear load of the joints reached 7.8 kN and the maximum load of the weld per unit length was 497 N/mm. The fracture occurred at the interface between the rivets and steel sheets rather than the conventional Al/steel joining interface. Moreover, ERFSLW can prolong the service life of joints due to three fracture stages. This method can be further extended to the welding of other dissimilar materials that conform to the model of "soft/hard".

Comprehensive carbon footprint analysis of wastewater treatment: A case study of modified cyclic activated sludge technology for low carbon source urban wastewater treatment.

To reduce pollution and carbon emissions, a quantitative evaluation of the carbon footprint of the wastewater treatment processes is crucial. However, micro carbon element flow analysis is rarely focused considering treatment efficiency of different technology. In this research, a comprehensive carbon footprint analysis is established under the micro carbon element flow analysis and macro carbon footprint analysis based on life cycle assessment (LCA). Three wastewater treatment processes (i.e., anaerobic anoxic oxic, A2O; cyclic activated sludge technology, CAST; modified cyclic activated sludge technology, M-CAST) for low carbon source urban wastewater are selected. The micro key element flow analysis illustrated that carbon source mainly flows to the assimilation function to promote microorganism growth. The carbon footprint analysis illustrated that M-CAST as the optimal wastewater treatment process had the lowest global warming potential (GWP). The key to reduce carbon emissions is to limit electricity consumption in wastewater treatment processes. Under the comprehensive carbon footprint analysis, M-CAST has the lowest environmental impact with low carbon emissions. The sensitivity analysis results revealed that biotreatment section variables considerably reduced the environmental impact on the LCA and the GWP, followed by the sludge disposal section. With this research, the optimization scheme can guide wastewater treatment plants to optimize relevant treatment sections and reduce pollution and carbon emissions.

High glucose levels accelerate atherosclerosis via NLRP3-IL/ MAPK/NF-κB-related inflammation pathways.

BACKGROUND: As a chronic inflammatory disease, diabetes mellitus (DM) contributes to the development of atherosclerosis (AS). However, how the NLRP3 inflammasome participates in diabetes-related AS remains unclear. Therefore, this study aimed to elucidate the mechanism through which NLRP3 uses high glucose (HG) levels to promote AS. METHODS: Serum and coronary artery tissues were collected from coronary artery disease (CAD) patients with and without DM, respectively. The expression of NLRP3 was detected, and the effects of this inflammasome on diabetes-associated AS were evaluated using streptozotocin (STZ)-induced diabetic apoE-/- mice injected with Adenovirus-mediated NLRP3 interference (Ad-NLRP3i). To elucidate the potential mechanism involved, ox-LDL-irritated human aortic smooth muscle cells were divided into the control, high-glucose, Si-NC, and Si-NLRP3 groups to observe the changes induced by downregulating NLRP3 expression. For up-regulating NLRP3, control and plasmid contained NLRP3 were used. TNF-α, IL-1ß, IL-6, IL-18, phosphorylated and total p38, JNK, p65, and IκBα expression levels were detected following the downregulation or upregulation of NLRP3 expression. RESULTS: Patients with comorbid CAD and DM showed higher serum levels and expression of NLRP3 in the coronary artery than those with only CAD. Moreover, mice in the Ad-NLRP3i group showed markedly smaller and more stable atherosclerotic lesions compared to those in other DM groups. These mice had decreased inflammatory cytokine production and improved glucose tolerance, which demonstrated the substantial effects of NLRP3 in the progression of diabetes-associated AS. Furthermore, using the siRNA or plasmid to downregulate or upregulate NLRP3 expression in vitro altered cytokines and the MAPK/NF-κB pathway. CONCLUSIONS: NLRP3 expression was significantly increased under hyperglycemia. Additionally, it accelerated AS by promoting inflammation via the IL/MAPK/NF-κB pathway.

Equity-based carbon neutral plan induces cross-regional coal leakage and industrial relocation.

China as a major coal-consuming economy faces the challenge of balancing economic development and carbon neutrality goal. This paper incorporates both efficiency-based and equity-based carbon neutrality policies into a numerical model to quantitatively assess how coal reduction under various carbon-neutral policies affects energy mix, economic growth, and industrial structures by 2060. Results show the nationwide coal intensity will ultimately plunge by over 95% from 2017 to 2060, mainly attributed to the coal-phasing-out in most industries. National Gross Domestic Product losses reaches 4,951 billion USD in efficiency-based scenarios by 2060, and the economic losses are even more severe in less developed provinces, especially provinces in Northern China. Although the equity-based policy can reduce the economic burden for the Northern China, the equity-based policy is accompanied by a significant regional shift in coal across the country: eastern coal-intense industries will be relocated northward, leading to increases in embodied coal consumption.

Nanofluid Drop Impact on Heated Surfaces.

We experimentally elucidate the impact dynamics of ethylene glycol (EG) droplets laden with both hydrophilic and hydrophobic SiO2 nanoparticles (NPs) onto a flat heated surface in non-boiling, boiling, and Leidenfrost regimes. We use seven nanofluid concentrations (Cp), ranging from 0.89 to 64.3 wt %, and control the surface temperature (Ts) between 100 and 400 °C, while the nanofluid droplet's impact velocity is constant at 0.22 ± 0.02 m/s. Phase diagrams of impact outcomes are established to illustrate the effect of the additive nanoparticles on the droplets' impact dynamics, revealing that nanoparticles modify droplet impact behaviors differently in each regime. In the non-boiling regime, the droplet spreading profile remains unaffected by nanoparticles up to Cp < 11.9 wt % before reaching the maximum spreading diameter (ßmax). For nanofluid drops with higher nanofluid concentration, the increasing viscosity with concentration is likely to be the primary factor that affects the droplets' spreading profile in the non-boiling regime Ts ≲ Tsat ≈ 200 °C, as the saturation temperature. In the boiling regime 200 °C < Ts ≲ 350 °C, a small amount of nanoparticle addition (Cp = 0.89 wt %) promotes atomization regardless of nanoparticle wettability. Finally, manifested in a complete rebound due to an intervening vapor layer, the Leidenfrost temperature (TL) of the nanofluid droplets is affected by both nanofluid concentration and nanoparticles' wettability. The nanofluid droplets' TL increases with higher nanofluid concentration; moreover, this Leidenfrost temperature increment is more significant for EG droplets laden with hydrophobic nanoparticles. Our results quantitatively reveal the significant influence of nanoparticle concentrations and wettability on drop spreading, impact outcome, and Leidenfrost temperature on heat surfaces, potentially benefiting applications in coating, spraying, and cooling.

Mitochondrial myopathy without extraocular muscle involvement: a unique clinicopathologic profile.

OBJECTIVE: Mitochondrial myopathy without extraocular muscles involvement (MiMy) represents a distinct form of mitochondrial disorder predominantly affecting proximal/distal or axial muscles, with its phenotypic, genotypic features, and long-term prognosis poorly understood. METHODS: A cross-sectional study conducted at a national diagnostic center for mitochondrial disease involved 47 MiMy patients, from a cohort of 643 mitochondrial disease cases followed up at Qilu Hospital from January 1, 2000, to January 1, 2021. We compared the clinical, pathological, and genetic features of MiMy to progressive external ophthalmoplegia (PEO) and mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) patients. RESULTS: MiMy patients demonstrated a more pronounced muscle involvement syndrome, with lower 6MWT scores, higher FSS, and lower BMI compared to PEO and MELAS patients. Serum levels of creatinine kinase (CK), lactate, and growth and differentiation factor 15 (GDF15) were substantially elevated in MiMy patients. Nearly a third (31.9%) displayed signs of subclinical peripheral neuropathy, mostly axonal neuropathy. Muscle biopsies revealed that cytochrome c oxidase strong (COX-s) ragged-red fibers (RRFs) were a typical pathological feature in MiMy patients. Genetic analysis predominantly revealed mtDNA point pathogenic variants (59.6%) and less frequently single (12.8%) or multiple (4.2%) mtDNA deletions. During the follow-up, a majority (76.1%) of MiMy patients experienced stabilization or improvement after therapeutic intervention. CONCLUSIONS: This study provides a comprehensive profile of MiMy through a large patient cohort, elucidating its unique clinical, genetic, and pathological features. These findings offer significant insights into the diagnostic and therapeutic management of MiMy, ultimately aiming to ameliorate patient outcomes and enhance the quality of life.

Unveiling the importance of VOCs from pesticides applicated in main crops for elevating ozone concentrations in China.

Volatile organic compounds (VOCs) are considered as important precursors of ozone in the air, while the contribution of VOCs from pesticide application (PVOCs) to ozone production is unknown. Utilizing data from the Ministry of Agriculture and Rural Affairs of the People's Republic of China and ChinaCropPhen1km, this paper developed PVOC emission inventories with a resolution of 1 km for the main crops (rice, maize, and wheat) from 2012 to 2019 in China. The results revealed that pesticide application is an important VOC emission source in China. Specially, the PVOC emissions from the major grain-producing regions in June accounted for approximately 30% of the annual total PVOC emissions in the local regions. The simulation with the Weather Research and Forecasting Community Multiscale Air Quality model (WRF-CMAQ) indicated that the PVOC emissions increased the mean maximum daily 8-hour average (MDA8) ozone concentration across China by 2.5 ppb in June 2019. During the same period, PVOCs in the parts of North China Plain contributed 10% of the ozone formation. Under the comprehensive emission reduction scenario, it is anticipated that by 2025, the joint implementation of measures including reducing pesticide application, improving pesticide utilization efficiency and promoting solvent substitution will decrease PVOC emissions by 60% compared with 2019, thereby mitigating ozone pollution.

Learning-based intelligent trajectory planning for auto navigation of magnetic robots.

Introduction: Electromagnetically controlled small-scale robots show great potential in precise diagnosis, targeted delivery, and minimally invasive surgery. The automatic navigation of such robots could reduce human intervention, as well as the risk and difficulty of surgery. However, it is challenging to build a precise kinematics model for automatic robotic control because the controlling process is affected by various delays and complex environments. Method: Here, we propose a learning-based intelligent trajectory planning strategy for automatic navigation of magnetic robots without kinematics modeling. The Long Short-Term Memory (LSTM) neural network is employed to establish a global mapping relationship between the current sequence in the electromagnetic actuation system and the trajectory coordinates. Result: We manually control the robot to move on a curved path 50 times to form the training database to train the LSTM network. The trained LSTM network is validated to output the current sequence for automatically controlling the magnetic robot to move on the same curved path and the tortuous and branched new paths in simulated vascular tracks. Discussion: The proposed trajectory planning strategy is expected to impact the clinical applications of robots.

Knowledge-guided Deep Temporal Clustering for Alzheimer's Disease Subtypes in Completed Clinical Trials.

Alzheimer's disease (AD) is a multifaceted neurodegenerative disorder with varied patient progression. We aim to test the hypothesis that AD patients can be categorized into subgroups based on differences in progression. We leveraged data from three randomized clinical trials (RCTs) to develop a knowledge-guided, deep temporal clustering (KG-DTC) framework for AD subtyping. This model combined autoencoders for contextual information capture, k-means clustering for representation formation, and clinical outcome classification for clinical knowledge integration. The derived representations, encompassing demographics, APOE genotype, cognitive assessments, brain volumes, and biomarkers, were clustered using the Gaussian Mixture Model to identify AD subtypes. Our novel KG-DTC framework was developed using placebo data from 2,087 AD patients across three solanezumab clinical trials (EXPEDITION, EXPEDITION2, and EXPEDITION3), achieving high performance in outcome prediction and clustering. The KG-DTC model demonstrated superior clustering structures, especially when combined with k-means clustering loss. External validation with independent clinical trial data showed consistent clustering results, with a 0.33 silhouette score for three clusters. The model's stability was confirmed through a leave-one-out approach, with an average adjusted Rand Index around 0.945. Three distinct AD subtypes were identified, each exhibiting unique patterns of cognitive function, neurodegeneration, and amyloid beta levels. Notably, Subtype 3 (S3) showed rapid cognitive decline across multiple clinical measures (e.g., 0.64 in S1 vs. -1.06 in S2 vs. 15.09 in S3 of average ADAS total change score, p<.001). This innovative approach offers promising insights for understanding variability in treatment outcomes and personalizing AD treatment strategies.

Construction of a synthetic microbial community based on multiomics linkage technology and analysis of the mechanism of lignocellulose degradation.

The efficient degradation of lignocellulose is a bottleneck for its integrated utilization. This research performed species analysis and made functional predictions in various ecosystems using multiomics coupling to construct a core synthetic microbial community with efficient lignocellulose degradation function. The synthetic microbial community was employed to degrade corn straw via solid-state fermentation. The degradation mechanisms were resolved using proteomics. The optimum culture conditions included 10% inoculum level (w/v), 4% nitrogen source ratio and a fermentation time of 23 d. Under these conditions, the degradation rates of cellulose, hemicellulose, and lignin were 34.91%, 45.94%, and 23.34%, respectively. Proteomic analysis revealed that lignin 1,4-ß-xylanase, ß-xylosidase and endo-1,4-ß-xylanase were closely related to lignocellulose degradation. The metabolic pathways involved in lignocellulose degradation and the functional roles of eight strains were obtained. The synthesis of a microbial community via multiomics linkage technology can effectively decompose lignocellulose, which is useful for their further utilization.

Enhanced food system efficiency is the key to China's 2060 carbon neutrality target.

Bioenergy with carbon capture and storage, among other negative-emission technologies, is required for China to achieve carbon neutrality-yet it may hinder land-based Sustainable Development Goals. Using modelling and scenario analysis, we investigate how to mitigate the potential adverse impacts on the food system of ambitious bioenergy deployment in China and its trading partners. We find that producing bioenergy domestically while sticking to the food self-sufficiency ratio redlines would lower China's daily per capita calorie intake by 8% and increase domestic food prices by 23% by 2060. Removing China's food self-sufficiency ratio restrictions could halve the domestic food dilemma but risks transferring environmental burdens to other countries, whereas halving food loss and waste, shifting to healthier diets and narrowing crop yield gaps could effectively mitigate these external effects. Our results show that simultaneously achieving carbon neutrality, food security and global sustainability requires a careful combination of these measures.

Application of machine learning to predict hospital visits for respiratory diseases using meteorological and air pollution factors in Linyi, China.

Urbanization and industrial development have resulted in increased air pollution, which is concerning for public health. This study evaluates the effect of meteorological factors and air pollution on hospital visits for respiratory diseases (pneumonia, acute upper respiratory infections, and chronic lower respiratory diseases). The test dataset comprises meteorological parameters, air pollutant concentrations, and outpatient hospital visits for respiratory diseases in Linyi, China, from January 1, 2016 to August 20, 2022. We use support vector regression (SVR) to build models that enable analysis of the effect of meteorological factors and air pollutants on the number of outpatient visits for respiratory diseases. Spearman correlation analysis and SVR model results indicate that NO2, PM2.5, and PM10 are correlated with the occurrence of respiratory diseases, with the strongest correlation relating to pneumonia. An increase in the daily average temperature and daily relative humidity decreases the number of patients with pneumonia and chronic lower respiratory diseases but increases the number of patients with acute upper respiratory infections. The SVR modeling has the potential to predict the number of respiratory-related hospital visits. This work demonstrates that machine learning can be combined with meteorological and air pollution data for disease prediction, providing a useful tool whereby policymakers can take preventive measures.

Butyrate mitigates metabolic dysfunctions via the ERα-AMPK pathway in muscle in OVX mice with diet-induced obesity.

The higher prevalence of metabolic syndrome (MetS) in women after menopause is associated with a decrease in circulating 17ß-oestradiol. To explore novel treatments for MetS in women with oestrogen deficiency, we studied the effect of exogenous butyrate on diet-induced obesity and metabolic dysfunctions using ovariectomized (OVX) mice as a menopause model. Oral administration of sodium butyrate (NaB) reduced the body fat content and blood lipids, increased whole-body energy expenditure, and improved insulin sensitivity. Additionally, NaB induced oestrogen receptor alpha (ERα) expression, activated the phosphorylation of AMPK and PGC1α, and improved mitochondrial aerobic respiration in cultured skeletal muscle cells. In conclusion, oral NaB improves metabolic parameters in OVX mice with diet-induced obesity. Oral supplementation with NaB might provide a novel therapeutic approach to treating MetS in women with menopause. Video Abstract.

A different pattern of clinical, muscle pathology and brain MRI findings in MELAS with mt-ND variants.

OBJECTIVE: To explore the clinical characteristics of mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) caused by mitochondrial DNA-encoded complex I subunit (mt-ND) variants. METHODS: In this retrospective study, the clinical, myopathological and brain MRI features of patients with MELAS caused by mt-ND variants (MELAS-mtND) were collected and compared with those of MELAS patients carrying the m.3243A > G variant (MELAS-A3243G). RESULT: A total of 18 MELAS-mtND patients (female: 7; median age: 24.5 years) represented 15.9% (n = 113) of all patients with MELAS caused by mtDNA variants in our neuromuscular center from January 2012 to June 2022. In this MELAS-mtND cohort, the two most common variants were m.10191 T > C (4/18, 22.2%) and m.13513 G > A (3/18, 16.7%). The most frequent symptoms were seizures (14/18, 77.8%) and muscle weakness (11/18, 61.1%). Compared with 87 MELAS-A3243G patients, MELAS-mtND patients were significantly more likely to have a variant that was absent in blood cells (40% vs. 1.4%). Furthermore, MELAS-mtND patients had a significantly lower MDC score (7.8 ± 2.7 vs. 9.8 ± 1.9); less hearing loss (27.8% vs. 54.0%), diabetes (11.1% vs. 37.9%), and migraine (33.3% vs. 62.1%); less short stature (males ≤ 165 cm; females ≤ 155 cm; 23.1% vs. 60.8%) and higher body mass index (20.4 ± 2.5 vs. 17.8 ± 2.7). MELAS-mtND patients had significantly more normal muscle pathology (31.3% vs. 4.1%) and fewer RRFs/RBFs (62.5% vs. 91.9%), COX-deficient fibers/blue fibers (25.0% vs. 85.1%) and SSVs (50.0% vs. 81.1%). Moreover, brain MRI evaluated at the first stroke-like episode showed significantly more small cortical lesions in MELAS-mtND patients (66.7% vs. 12.2%). INTERPRETATION: Our results suggested that MELAS-mtND patients have distinct clinical, myopathological and brain MRI features compared with MELAS-A3243G patients.

The association of hepcidin, reticulocyte hemoglobin equivalent and anemia-related indicators on anemia in chronic kidney disease.

Hepcidin is an essential regulator of iron homeostasis in chronic kidney disease (CKD) anemia, reticulocyte hemoglobin equivalent (RET-He) can be used to evaluate the availability of iron for erythropoiesis. Previous research has found that hepcidin indirectly regulates RET-He. This study aimed to investigate the association of hepcidin, RET-He and anemia-related indicators on anemia in chronic kidney disease. A total of 230 individuals were recruited, including 40 CKD3-4 patients, 70 CKD5 patients without renal replacement therapy, 50 peritoneal dialysis patients, and 70 hemodialysis patients. The serum levels of hemoglobin (Hb), reticulocyte, RET-He, serum iron, serum creatinine, serum ferritin, total iron binding capacity, hepcidin-25, high sensitivity C-reactive protein, transferrin, erythropoietin, intrinsic factor antibody, soluble transferrin receptor and interleukins-6 (IL-6) were measured. Hepcidin-25 was positively associated with IL-6, and negatively with total iron binding capacity, intrinsic factor antibody, and transferrin. Reticulocyte Hb equivalent was associated positively with Hb, serum ferritin, serum iron, transferrin saturation, and negatively with serum creatinine, reticulocyte, IL-6, STfR. Hepcidin-25 was not associated with RET-He, while IL-6 was independently associated with hepcidin-25 and RET-He, suggesting that hepcidin has no effffect on the iron dynamics of reticulocytes in CKD, may be related to IL-6, indicate a likelihood of a threshold for stimulation of hepcidin-25 expression by IL-6 in order to indirectly regulates RET-He.

Wetland Park Planning and Management Based on the Valuation of Ecosystem Services: A Case Study of the Tieling Lotus Lake National Wetland Park (LLNWP), China.

The valuation of wetland ecosystem services and the construction of environmental landscapes are generally recognized as contributing to the sustainable development of human wellbeing. The valuation of ecosystem services plays an important role in planning for the recovery of degraded wetlands and in urban wetland park management; however, the role of the valuation of ecosystem services is always ignored. To bring more intuitive awareness to the importance of the ecological functions of wetlands and to rationally plan wetland parks, the Lotus Lake National Wetland Park (LLNWP), an urban wetland park in Northeast China, was selected as the study area. We referred to the millennium ecosystem assessment (MA) method and calculated the valuation of this park using the market value, benefit transfer, shadow engineering, carbon tax, and travel cost. ArcGIS was used for remote sensing interpretation. The research results were as follows. LLNWP was classified under seven types of land-use. The functions of the ecosystem services included provisioning, regulating, supporting, and cultural services, and their total value in LLNWP was 11.68×108 CNY. Regarding the per-unit area value of the ecological service functions of different land types, it was found that forest swamp > herbaceous swamp > artificial wetland > permanent river > floodplain wetland. Combined with the characteristics of the functions of its ecosystem's services, LLNWP was divided into ecological and socio-cultural functions. Then, according to the main service functions of the different land types, we propose that the space in LLNWP can be reused, and proposal planning and management suggestions can be made with the aim of preserving the basic functions.