Comparisons of microstructure and elemental composition of eggshells among wild plover populations

Reproduction investment is a prominent trade-off in life-history theory and is subject to strong selection pressure.The avian eggshell,as a crucial barrier between the bird embryo and the surrounding environment,undergoes optimization under different environmental selection regimes to ensure the successful development of embryos,which can be linked to local adaptation.Therefore,understanding the variation in eggshell microstructure and composition in wild bird populations living in contrasting ambient environments is of great significance.In this study,we utilized electron microscope ultrastructure measurement and elemental analyses to measure and compare the microstructure and element composition of eggshells from three wild plover populations(Charadrius alexandrinus and C.dealbatus)residing in heterogeneous habitats across varied climatic zones.These populations include the high-altitude Qinghai Lake population,the temperate coastal Tangshan population,and the tropical coastal Zhanjiang population.Our findings revealed that the palisade layer was thinner in the Qinghai Lake population compared to its lowland populations.This difference might be attributed to hypoxia which facilitates the hatching process by allowing chicks to easily break through their shells.Additionally,the variations in the elemental composition of the eggshells among populations well reflected the distribution of element content in different geographical regions.The Qinghai Lake population displayed low zinc and low manganese levels but high calcium levels,while the Zhanjiang population exhibited high zinc,high iron,high manganese,and high phosphorus levels.Furthermore,these variations in elemental composition could also account for the observed microstructural differences among populations.Collectively,we propose that the dissimilarities in eggshell microstructure and elemental composition among populations could be attributed to adaptations to different environmental conditions.Our findings lay the groundwork for future research to explore the mechanisms behind the variations in eggshell characteristics among wild bird populations,and contribute to a broader understanding of biodiversity mechanisms.

Hepatic retinaldehyde deficiency is involved in diabetes deterioration by enhancing PCK1-and G6PC-mediated gluconeogenesis

Type 2 diabetes(T2D) is often accompanied with an induction of retinaldehyde dehydrogenase 1(RALDH1 or ALDH1A1) expression and a consequent decrease in hepatic retinaldehyde(Rald)levels. However, the role of hepatic Rald deficiency in T2D progression remains unclear. In this study, we demonstrated that reversing T2D-mediated hepatic Rald deficiency by Rald or citral treatments, or liverspecific Raldh1 silencing substantially lowered fasting glycemia levels, inhibited hepatic glucogenesis,and downregulated phosphoenolpyruvate carboxykinase 1(PCK1) and glucose-6-phosphatase(G6PC)expression in diabetic db/db mice. Fasting glycemia and Pck1/G6pc mRNA expression levels were strongly negatively correlated with hepatic Rald levels, indicating the involvement of hepatic Rald depletion in T2D deterioration. A similar result that liver-specific Raldh1 silencing improved glucose metabolism was also observed in high-fat diet-fed mice. In primary human hepatocytes and oleic acidtreated HepG2 cells, Rald or Rald + RALDH1 silencing resulted in decreased glucose production and downregulated PCK1/G6PC mRNA and protein expression. Mechanistically, Rald downregulated direct repeat 1-mediated PCK1 and G6PC expression by antagonizing retinoid X receptor a, as confirmed by luciferase reporter assays and molecular docking. These results highlight the link between hepatic Rald deficiency, glucose dyshomeostasis, and the progression of T2D, whilst also suggesting RALDH1 as a potential therapeutic target for T2D.

Preclinical and early clinical studies of a novel compound SYHA1813 that efficiently crosses the blood-brain barrier and exhibits potent activity against glioblastoma

Glioblastoma(GBM)is the most common and aggressive malignant brain tumor in adults and is poorly controlled.Previous studies have shown that both macrophages and angiogenesis play significant roles in GBM progression,and co-targeting of CSF1R and VEGFR is likely to be an effective strategy for GBM treatment.Therefore,this study developed a novel and selective inhibitor of CSFIR and VEGFR,SYHA1813,possessing potent antitumor activity against GBM.SYHA1813 inhibited VEGFR and CSFIR kinase activities with high potency and selectivity and thus blocked the cell viability of HUVECs and macrophages and exhibited anti-angiogenetic effects both in vitro and in vivo.SYHA1813 also displayed potent in vivo antitumor activity against GBM in immune-competent and immune-deficient mouse models,including temozolomide(TMZ)insensitive tumors.Notably,SYHA1813 could penetrate the blood-brain barrier(BBB)and prolong the survival time of mice bearing intracranial GBM xenografts.Moreover,SYHA1813 treatment resulted in a synergistic antitumor efficacy in combination with the PD-1 antibody.As a clinical proof of concept,SYHA1813 achieved confirmed responses in patients with recurrent GBM in an ongoing first-in-human phase I trial.The data of this study support the rationale for an ongoing phase I clinical study(ChiCTR2100045380).

Comparative evaluation of data mining methods in predicting the water vapor permeability of cement-based materials

Water vapor permeability of building materials is a crucial parameter for analysing and optimizing the hygrothermal performance of building envelopes and built environments.Its measurement is accurate but time-consuming,while data mining methods have the potential to predict water vapor permeability efficiently.In this study,six data mining methods—support vector regression(SVR),decision tree regression(DT),random forest regression(RF),K-nearest neighbor(KNN),multi-layer perceptron(MLP),and adaptive boosting regression(AdaBoost)—were compared to predict the water vapor permeability of cement-based materials.A total of 143 datasets of material properties were collected to build prediction models,and five materials were experimentally determined for model validation.The results show that RF has excellent generalization,stability,and precision.AdaBoost has great generalization and precision,only slightly inferior to the former,and its stability is excellent.DT has good precision and acceptable generalization,but its stability is poor.SVR and KNN have superior stability,but their generalization and precision are inadequate.MLP lacks generalization,and its stability and precision are unacceptable.In short,RF has the best comprehensive performance,demonstrated by a limited prediction deviation of 26.3%from the experimental results,better than AdaBoost(38.0%)and DT(38.3%)and far better than other remaining methods.It is also found that data mining methods provide better predictions when cement-based materials’water vapor permeability is high.

Bi-level Energy Trading Model Incorporating Large-scale Biogas Plant and Demand Response Aggregator

Increasing intermittent renewable energy sources(RESs)intensifies the imbalance between demand and generation,entailing the diversification of the deployment of electrical energy storage systems(ESSs).A large-scale biogas plant(LBP)installed with heating devices and biogas energy storage(BES)usually exhibits a storage-like characteristic of accommodating an increasing penetration level of RES in rural areas,which is addressed in this paper.By utilizing the temperature-sensitive characteristic of anaerobic digestion that enables the LBP to exhibit a storage-like characteristic,this paper proposes a bi-level energy trading model incorporating LBP and demand response aggregator(DRA)simultaneously.In this model,social welfare is maximized at the upper level while the profit of DRA is maximized at the lower level.Compared with cases only with DRA,the results show that the proposed model with the LBP improves the on-site accommodation capacity of photovoltaic(PV)generation up to 6.3%,18.1%,and 18.9%at 30%,40%,and 50%PV penetration levels,respectively,with a better economic performance.This nonlinear bi-level problem is finally recast by a single-level mathematical program with equilibrium constraints(MPEC)using Karush-Kuhn-Tucker(KKT)conditions and solved by the Cplex solver.The effectiveness of the proposed model is validated using a 33-bus test system and a sensitivity analysis is provided for analyzing what parameter influences the accommodation capacity most.

PXR activation impairs hepatic glucose metabolism partly via inhibiting the HNF4α-GLUT2 pathway

Drug-induced hyperglycemia/diabetes is a global issue. Some drugs induce hyperglycemia by activating the pregnane X receptor(PXR), but the mechanism is unclear. Here, we report that PXR activation induces hyperglycemia by impairing hepatic glucose metabolism due to inhibition of the hepatocyte nuclear factor 4-alpha(HNF4 a)-glucose transporter 2(GLUT2) pathway. The PXR agonists atorvastatin and rifampicin significantly downregulated GLUT2 and HNF4 a expression, and impaired glucose uptake and utilization in HepG2 cells. Overexpression of PXR downregulated GLUT2 and HNF4 a expression, while silencing PXR upregulated HNF4 a and GLUT2 expression.Silencing HNF4 a decreased GLUT2 expression, while overexpressing HNF4 a increased GLUT2 expression and glucose uptake. Silencing PXR or overexpressing HNF4 a reversed the atorvastatininduced decrease in GLUT2 expression and glucose uptake. In human primary hepatocytes, atorvastatin downregulated GLUT2 and HNF4 a mRNA expression, which could be attenuated by silencing PXR. Silencing HNF4 a downregulated GLUT2 mRNA expression. These findings were reproduced with mouse primary hepatocytes. Hnf4 a plasmid increased Slc2 a2 promoter activity. Hnf4 a silencing or pregnenolone-16 a-carbonitrile(PCN) suppressed the Slc2 a2 promoter activity by decreasing HNF4 a recruitment to the Slc2 a2 promoter. Liver-specific Hnf4 a deletion and PCN impaired glucose tolerance and hepatic glucose uptake, and decreased the expression of hepatic HNF4 a and GLUT2. In conclusion, PXR activation impaired hepatic glucose metabolism partly by inhibiting the HNF4 aGLUT2 pathway. These results highlight the molecular mechanisms by which PXR activators induce hyperglycemia/diabetes.

Quantification of traffic-induced compaction based on soil and agricultural implement parameters

Vehicle-induced soil compaction occurs when agricultural machinery is working in the fields.The accumulated soil compaction could destroy soil structure and inhibit crop growth.The low degree of visualization of soil compaction has always been an important reason for restricting the development of compaction alleviation technology.Therefore,the main objective of this study was to predict soil compaction based on soil and agricultural implement parameters.The component of soil compaction prediction includes traffic-induced stress transmission evaluation and the quantitative relationship between soil stress and bulk density.The modified FRIDA model was used to elucidate the soil stress propagation,which has been validated by previous studies.The Bailey formula was used to establish the intrinsic relationship between soil stress and bulk density.The soil uniaxial compression test was applied to obtain the parameters of the Bailey formula,and soil samples were prepared with three different levels of water content.After fitting with the Bailey formula,under the condition that the soil moisture contents were 16%,20%,and 24%,the fitting coefficients of soil bulk density were respectively 0.980,0.959,and 0.975,which were close to 1.The results indicated that the Bailey formula could be used to calculate soil bulk density based on the stress conditions of the soil.To verify the practicality of the soil compaction prediction model,a field experiment was carried out in Zhuozhou City,Hebei Province,China.The treatment was set for 1,3,5,7,and 9 times compaction with two different loads of compaction equipment.The results showed that the fit coefficient between the predicted and measured values of soil bulk density was greater than 0.641.The slope of the equation was greater than 0.782,proving that the soil bulk density prediction model based on agricultural implements and soil parameters has a good predictive effect on soil bulk density.The soil compaction evaluation model can provide a theoretical basis to further understand the soil compaction mechanism,allowing rational measures of soil compaction alleviation to be made.

Optimal control of automated left-turn platoon at contraflow left-turn lane intersections

Purpose–This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane(CLL)intersections.Design/methodology/approach–The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness.The proposed model is cast into a mixed-integer linear programming problem and then solved by the branch-and-bound technique.Findings–The proposed model has a promising control effect under different geometric controlled conditions.Moreover,the proposed model performs robustly under various safety time headways,lengths of the CLL and green times of the main signal.Originality/value–This study proposed a centralized optimal control model for automated left-turn platoon at CLL intersections.The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness。

A comparative study on grid resource utilization rate between China Southern Power Grid and National Grid Plc of UK

Grid resource utilization rate plays a key role in power grid operation.Although the proportion of population and the area in China Southern Power Grid(CSG)and National Grid Plc of UK(NG)are nearly,grid resources utilization of CSG is lower than that of NG.In this paper,the utilization of human resources and equipment resources of CSG and NG have been reviewed.It is discovered that there is a large gap between these two companies.The results show that the utilization in CSG is about 20%to 50%of that in NG.And it is estimated that if the equipment resources utilization of CSG increases to the level of NG in 2012,the coal consumption and thus CO2 emissions would be reduced by 17 million tons and 21 million tons,respectively.As China is a developing country and Britain is a mature developed country,it is to some extent reasonable that grid resources utilization of CSG is lower than that of NG.The benefits of improving equipment resources utilization are illustrated in detail,which provided the reference for developing the grid resource utilization in China.