The oxidative aging model integrated various risk factors in type 2 diabetes mellitus at system level

BackgroundType 2 diabetes mellitus (T2DM) is a chronic endocrine metabolic disease caused by insulin dysregulation. Studies have shown that aging-related oxidative stress (as “oxidative aging”) play a critical role in the onset and progression of T2DM, by leading to an energy metabolism imbalance. However, the precise mechanisms through which oxidative aging lead to T2DM are yet to be fully comprehended. Thus, it is urgent to integrate the underlying mechanisms between oxidative aging and T2DM, where meaningful prediction models based on relative profiles are needed.MethodsFirst, machine learning was used to build the aging model and disease model. Next, an integrated oxidative aging model was employed to identify crucial oxidative aging risk factors. Finally, a series of bioinformatic analyses (including network, enrichment, sensitivity, and pan-cancer analyses) were used to explore potential mechanisms underlying oxidative aging and T2DM.ResultsThe study revealed a close relationship between oxidative aging and T2DM. Our results indicate that nutritional metabolism, inflammation response, mitochondrial function, and protein homeostasis are key factors involved in the interplay between oxidative aging and T2DM, even indicating key indices across different cancer types. Therefore, various risk factors in T2DM were integrated, and the theories of oxi-inflamm-aging and cellular senescence were also confirmed.ConclusionIn sum, our study successfully integrated the underlying mechanisms linking oxidative aging and T2DM through a series of computational methodologies

Evaluation of six satellite-based terrestrial latent heat flux products in the vegetation dominated Haihe river basin of north China

In this study, six satellite-based terrestrial latent heat flux (LE) products were evaluated in the vegetation dominated Haihe River basin of North China. These LE products include Global Land Surface Satellite (GLASS) LE product, FLUXCOM LE product, Penman-Monteith-Leuning V2 (PML_V2) LE product, Global Land Evaporation Amsterdam Model datasets (GLEAM) LE product, Breathing Earth System Simulator (BESS) LE product, and Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD16) LE product. Eddy covariance (EC) data collected from six flux tower sites and water balance method derived evapotranspiration (WBET) were used to evaluate these LE products at site and basin scales. The results indicated that all six LE products were able to capture the seasonal cycle of LE in comparison to EC observations. At site scale, GLASS LE product showed the highest coefficients of determination (R2) (0.58, p 2), followed by FLUXCOM and PML products. At basin scale, the LE estimates from GLASS product provided comparable performance (R2 = 0.79, RMSE = 18.8 mm) against WBET, compared with other LE products. Additionally, there was similar spatiotemporal variability of estimated LE from the six LE products. This study provides a vital basis for choosing LE datasets to assess regional water budget

Analysis of Buckling Characteristics and Parameter Influence of Composite Thin-walled Lenticular Boom Structures

The stretchable composite thin-walled lenticular boom can be used in the unfolding process of a large spacecraft structure, and its buckling characteristic is one of the focuses of structural design. In this paper, firstly, the critical buckling load formula is derived based on Euler’s formula and laminated theory for the axial compression buckling problem of the lenticular boom, and verified by the finite element method. Secondly, the influence law of the lenticular boom section and layer parameters on the critical buckling load is quantitatively analyzed. The results show that the lenticular boom generally undergoes first-order buckling in the outer direction of the symmetrical bonding surface. The critical buckling load is most significantly affected by the radius of the convex arc, followed by the center ordinate of the convex arc, the thickness of the layer, and the angle of the layer. And these parameters are positively related to the critical buckling load. The radius of the concave arc and the length of the straight section have little effect on the critical buckling load. The research methods and conclusions of this paper can provide reference for the engineering design of the lenticular boom structure

The Roles of Protein Tyrosine Phosphatases in Hepatocellular Carcinoma

The protein tyrosine phosphatase (PTP) family is involved in multiple cellular functions and plays an important role in various pathological and physiological processes. In many chronic diseases, for example cancer, PTP is a potential therapeutic target for cancer treatment. In the last two decades, dozens of PTP inhibitors which specifically target individual PTP molecules were developed as therapeutic agents. Hepatocellular carcinoma (HCC) is one of the most common malignant tumors and is the second most lethal cancer worldwide due to a lack of effective therapies. Recent studies have unveiled both oncogenic and tumor suppressive functions of PTP in HCC. Here, we review the current knowledge on the involvement of PTP in HCC and further discuss the possibility of targeting PTP in HCC

Theoretical Evaluation of the Influence of Molecular Packing Mode on the Intramolecular Reorganization Energy of Oligothiophene Molecules

Accurate determination of the relationships among packing mode, molecular structure and charge transfer mobility for oligothiophene analogues has been significantly impeded, due to the lack of crystal structure information. In the current study, molecular dynamics (MD) were used to investigate the packing mode of non-, methyl- and ethyl-substituted poly(3-alkylthiophenes) (P3ATs). Obvious conformational changes were observed when comparing the packed and isolated oligothiophene molecules, indicating the important influence of packing mode on the geometric structures of these materials. Considering the crucial role played by reorganization energy (RE) in the charge transfer process, both quantum mechanics (QM) and quantum mechanics/molecular mechanics (QM/MM) were performed to examine the impact of different conformations on energy. Our simulations revealed that the geometric structures have distinct effects on the RE. Our data suggest that MD could give a reliable packing mode of oligothiophene analogues, and that QM/MM is indispensable for precisely estimating RE

ERTFM: An effective model to fuse chinese gf-1 and modis reflectance data for terrestrial latent heat flux estimation

Coarse spatial resolution sensors play a major role in capturing temporal variation, as satellite images that capture fine spatial scales have a relatively long revisit cycle. The trade-off between the revisit cycle and spatial resolution hinders the access of terrestrial latent heat flux (LE) data with both fine spatial and temporal resolution. In this paper, we firstly investigated the capability of an Extremely Randomized Trees Fusion Model (ERTFM) to reconstruct high spatiotemporal resolution reflectance data from a fusion of the Chinese GaoFen-1 (GF-1) and the Moderate Resolution Imaging Spectroradiometer (MODIS) products. Then, based on the merged reflectance data, we used a Modi-fied-Satellite Priestley–Taylor (MS–PT) algorithm to generate LE products at high spatial and temporal resolutions. Our results illustrated that the ERTFM-based reflectance estimates showed close similar-ity with observed GF-1 images and the predicted NDVI agreed well with observed NDVI at two cor-responding dates (r = 0.76 and 0.86, respectively). In comparison with other four fusion methods, including the widely used spatial and temporal adaptive reflectance fusion model (STARFM) and the enhanced STARFM, ERTFM had the best performance in terms of predicting reflectance (SSIM = 0.91; r = 0.77). Further analysis revealed that LE estimates using ERTFM-based data presented more detailed spatiotemporal characteristics and provided close agreement with site-level LE observations, with an R2 of 0.81 and an RMSE of 19.18 W/m2. Our findings suggest that the ERTFM can be used to improve LE estimation with high frequency and high spatial resolution, meaning that it has great potential to support agricultural monitoring and irrigation management