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[Objective] To optimizing the pattern of territorial space development and coordinating the pattern of production-living-ecological space is the key task and fundamental way to achieve sustainable development in the future. [Methods] Based on the land use in Yunnan Province and combined with the natural and social development factors, the MOP-PLUS coupling model was used to simulate the changes of production-living-ecological space and its effects under three scenarios of economic priority, ecological priority and collaborative development in 2030. [Results] (1) Under the three scenarios, the economic benefit increased by 40.29%, 32.10% and 34.79%, the ecological benefit decreased by 0.89%, 0 (unchanged) and 0.06%, the average habitat quality decreased by 0.78%, 0.38% and 0.43%, and the average spatial conflict intensity increased by 2.79%, decreased by 1.21% and decreased by 2.32%. (2) Living space increased and ecological space decreased in the three scenarios. Production space only increased slightly in the economic priority scenario. In all cases, living space encroached on production space, and then production space plagued ecological space. The expansion of living space showed a trend of encroaching from the center to the periphery. (3) Habitat quality decreased to some extent under different development scenarios, and spatial conflicts could be balanced by optimizing spatial layout. Compared with other scenarios, the growth of economic benefits in the collaborative development scenario was moderate, the variation range of habitat quality was relatively balanced, and the intensity of spatial conflicts decreased the most, which was in line with the multiple goals of ecological protection, economic development and social progress. [Conclusion] The simulation-effect-optimization feedback regulation mechanism formed in this paper can be combined with different scales and objectives to carry out land use change simulation and effect analysis, and provide a basis for decision-making of territorial space allocation.

Metastasis is the major cause of treatment failure in patients with prostate adenocarcinoma (PRAD). Diverse programmed cell death (PCD) patterns play an important role in tumor metastasis and hold promise as predictive indicators for PRAD metastasis. Using the LASSO Cox regression method, we developed PCD score (PCDS) based on differentially expressed genes (DEGs) associated with PCD. Clinical correlation, external validation, functional enrichment analysis, mutation landscape analysis, tumor immune environment analysis, and immunotherapy analysis were conducted. The role of Prostaglandin D2 Synthase (PTGDS) in PRAD was examined through in vitro experiments, single-cell, and Mendelian randomization (MR) analysis. PCDS is elevated in patients with higher Gleason scores, higher T stage, biochemical recurrence (BCR), and higher prostate-specific antigen (PSA) levels. Individuals with higher PCDS are prone to metastasis, metastasis after BCR, BCR, and castration resistance. Moreover, PRAD patients with low PCDS responded positively to immunotherapy. Random forest analysis and Mendelian randomization analysis identified PTGDS as the top gene associated with PRAD metastasis and in vitro experiments revealed that PTGDS was considerably downregulated in PRAD cells against normal prostate cells. Furthermore, the overexpression of PTGDS was found to suppress the migration, invasion, proliferationof DU145 and LNCaP cells. To sum up, PCDS may be a useful biomarker for forecasting the possibility of metastasis, recurrence, castration resistance, and the efficacy of immunotherapy in PRAD patients. Additionally, PTGDS was identified as a viable therapeutic target for the management of PRAD. [ABSTRACT FROM AUTHOR]

As an efficient and environmental‐friendly strategy, electrocatalytic oxidation can realize biomass lignin valorization by cleaving its aryl ether bonds to produce value‐added chemicals. However, the complex and polymerized structure of lignin presents challenges in terms of reactant adsorption on the catalyst surface, which hinders further refinement. Herein, NiCo‐based metal‐organic frameworks (MOFs) are employed as the electrocatalyst to enhance the adsorption of reactant molecules through π‐π interaction. More importantly, lattice strain is introduced into the MOFs via curved ligand doping, which enables tuning of the d‐band center of metal active sites to align with the reaction intermediates, leading to stronger adsorption and higher electrocatalytic activity toward bond cleavage within lignin model compounds and native lignin. When 2′‐phenoxyacetophenone is utilized as the model compound, high yields of phenol (76.3%) and acetophenone (21.7%) are achieved, and the conversion rate of the reactants reaches 97%. Following pre‐oxidation of extracted poplar lignin, >10 kinds of phenolic compounds are received using the as‐designed MOFs electrocatalyst, providing ≈12.48% of the monomer, including guaiacol, vanillin, eugenol, etc., and p‐hydroxybenzoic acid dominates all the products. This work presents a promising and deliberately designed electrocatalyst for realizing lignin valorization, making significant strides for the sustainability of this biomass resource. [ABSTRACT FROM AUTHOR]

Introduction: Migraine, as a complex neurological disease, brings heavy burden to patients and society. Despite the availability of established therapies, existing medications have limited efficacy. Thus, we aimed to find the drug targets that improve the prognosis of migraine. Method: We used Mendelian Randomization (MR) and Summary-data-based MR (SMR) analyses to study possible drug targets of migraine by summary statistics from FinnGen cohorts (nCase = 44,616, nControl = 367,565), with further replication in UK Biobank (nCase = 26,052, nControl = 487,214). Genetic instruments were obtained from eQTLGen and UKB-PPP to verify the drug targets at the gene expression and protein levels. The additional analyses including Bayesian co-localization, the heterogeneity in dependent instruments(HEIDI), Linkage Disequilibrium Score(LDSC), bidirectional MR, multivariate MR(MVMR), heterogeneity test, horizontal pleiotropy test, and Steiger filtering were implemented to consolidate the findings further. Lastly, drug prediction analysis and phenome-wide association study(PheWAS) were employed to imply the possibility of drug targets for future clinical applications. Result: The MR analysis of eQTL data showed that four drug targets (PROCR, GSTM4, SLC4A1, and TNFRSF10A) were significantly associated with migraine risk in both the FinnGen and UK Biobank cohorts. However, only GSTM4 exhibited consistent effect directions across the two outcomes(Discovery cohort: OR(95%CI) = 0.94(0.93–0.96); p = 2.70e − 10; Replication cohort: OR(95%CI) = 0.93(0.91–0.94); p = 4.21e − 17). Furthermore, GSTM4 passed the SMR at p < 0.05 and HEIDI test at p > 0.05 at both the gene expression and protein levels. The protein-level MR analysis revealed a strong correlation between genetically predicted GSTM4 with a lower incidence of migraine and its subtypes(Overall migraine: OR(95%CI) = 0.91(0.87–0.95); p = 6.98e-05; Migraine with aura(MA): OR(95%CI) = 0.90(0.85–0.96); p = 2.54e-03; Migraine without aura(MO): OR(95%CI) = 0.90(0.83–0.96); p = 2.87e-03), indicating a strong co-localization relationship (PPH4 = 0.86). Further analyses provided additional validation for the possibility of GSTM4 as a migraine treatment target. Conclusion: This study identifies GSTM4 as a potential druggable gene and promising therapeutic target for migraine. [ABSTRACT FROM AUTHOR]

In view of the low accuracy of the theoretical empirical formula of axial force at the double-sided high-speed rotor end of the traditional air circulation machine, the numerical calculation takes a long time,this paper establishes a narrow gap calculation domain geometric model including double-sided high-speed rotor,and checks the accuracy of the model through experiments. On the basis of axial aerodynamic generation,the axial force is compared and calculated by theoretical formula method and CFD numerical calculation method.Based on the numerical simulation results of axial force, the calculation formula of axial force on the back side of the existing wheel is partially corrected, and a new set of axial aerodynamic calculation formula suitable for air flotation ACM is proposed,and the results show that the minimum error at the compressor end is reduced from 59% to 13% of the original formula, the maximum error is reduced from 261% to 75% of the original formula, the minimum error at the turbine end is reduced from 63% to 2% of the original formula,and the maximum error is reduced from 98% to 8% of the original formula. The new calculation method greatly reduces the error value of the axial force and aims to solve the problem that plagues the engineering side of how to accurately calculate the pneumatic axial force. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this study was to investigate whether the combination of abnormal systemic immune-inflammation index (SII) levels and hyperglycemia increased the risk of cognitive function decline and reduced survival rate in the United States. Methods: This cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) database from 2011–2014 and enrolled 1,447 participants aged 60 years or older. Restricted cubic splines (RCS), linear regression and kaplan-meier(KM) curve were employed to explore the combined effects of abnormal SII and hyperglycemia on cognitive function and survival rate, and subgroup analysis was also conducted. Results: The RCS analysis revealed an inverted U-shaped relationship between lgSII levels and cognitive function. Linear regression analysis indicated that neither abnormal SII nor diabetes alone significantly contributed to the decline in cognitive function compared to participants with normal SII levels and blood glucose. However, when abnormal SII coexisted with diabetes (but not prediabetes), it resulted to a significant decline in cognitive function. After adjusting for various confounding factors, these results remained significant in Delayed Word Recall (β:-0.76, P<0.05) and Digit Symbol Substitution tests (β:-5.02, P<0.05). Nevertheless, these results showed marginal significance in Total Word Recall test as well as Animal Fluency test. Among all subgroup analyses performed, participants with both abnormal SII levels and diabetes exhibited the greatest decline in cognitive function compared to those with only diabetes. Furthermore, KM curve demonstrated that the combination of abnormal SII levels and diabetes decreased survival rate among participants. Conclusion: The findings suggest that the impact of diabetes on cognitive function/survival rate is correlated with SII levels, indicating that their combination enhances predictive power. [ABSTRACT FROM AUTHOR]