Unveiling the role of TAGLN2 in glioblastoma: From proneural-mesenchymal transition to Temozolomide resistance.

Glioblastoma (GBM) presents a daunting challenge due to its resistance to temozolomide (TMZ), a hurdle exacerbated by the proneural-to-mesenchymal transition (PMT) from a proneural (PN) to a mesenchymal (MES) phenotype. TAGLN2 is prominently expressed in GBM, particularly in the MES subtype compared to low-grade glioma (LGG) and the PN subtype. Our research reveals TAGLN2's involvement in PMT and TMZ resistance through a series of in vitro and in vivo experiments. TAGLN2 knockdown can restrain proliferation and invasion, trigger DNA damage and apoptosis, and heighten TMZ sensitivity in GBM cells. Conversely, elevating TAGLN2 levels amplifies resistance to TMZ in cellular and intracranial xenograft mouse models. We demonstrate the interaction relationship between TAGLN2 and ERK1/2 through co-immunoprecipitation (Co-IP) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) spectrometry analysis. Knockdown of TAGLN2 results in a decrease in the expression of p-ERK1/2, whereas overexpression of TAGLN2 leads to an increase in p-ERK1/2 expression within the nucleus. Subsequently, the regulatory role of TAGLN2 in the expression and control of MGMT has been demonstrated. Finally, the regulation of TAGLN2 by NF-κB has been validated through chromatin immunoprecipitation and ChIP-PCR assays. In conclusion, our results confirm that TAGLN2 exerts its biological functions by interacting with the ERK/MGMT axis and being regulated by NF-κB, thereby facilitating the acquisition of promoting PMT and increased resistance to TMZ therapy in glioblastoma. These results provide valuable insights for the advancement of targeted therapeutic approaches to overcome TMZ resistance in clinical treatments.

Interfacial engineering of POM-stabilized Ni quantum dots on porous titanium mesh for high-rate and stable alkaline hydrogen production.

The development of low-cost, high-efficiency, and stable electrocatalysts for the alkaline hydrogen evolution reaction (HER) is a key challenge because the alkaline HER kinetics is slowed by an additional water dissociation step. Herein, we report an interfacial engineering strategy for polyoxometalate (POM)-stabilized nickel (Ni) quantum dots decorated on the surface of porous titanium mesh (POMs-Ni@PTM) for high-rate and stable alkaline hydrogen production. Benefiting from the strong interfacial interactions among POMs, Ni atoms, and PTM substrates, as well as unique POM-Ni quantum dot structures, the optimized POMs-Ni@PTM electrocatalyst exhibits a remarkable alkaline HER performance with an overpotential (η10) of 30.1 mV to reach a current density of 10 mA cm-2, which is much better than those of bare Ni decorated porous titanium mesh (Ni@PTM) (η10 = 171.1 mV) and POM decorated porous titanium mesh (POMs@PTM) electrocatalysts (η10 = 493.6 mV), comparable to that of the commercial 20 wt% platinum/carbon (20% Pt/C) electrocatalyst (η10 = 20 mV). Moreover, the optimized POMs-Ni@PTM electrocatalyst demonstrates excellent stability under continuous alkaline water-splitting at a current density of ∼100 mA cm-2 for 100 h, demonstrating great potential for its practical application.

Functional MRI of inhibitory control processing in problematic mobile video gamers.

With the development of mobile technology, mobile video games provide people with a more convenient way of entertainment, but problematic playing could also bring some negative consequences. Prior studies have indicated that Internet gaming addicts were accompanied by impaired inhibitory control. However, as a relatively new form of problematic game usage based on mobile devices, little is known about the neurobiological underpinnings of inhibitory control in problematic mobile video game (PMVG) users. Adopting an event-related fMRI Stroop task, the present study aimed to examine the different neural correlates of inhibitory control between PMVG and healthy control (HC) subjects. Compared with HC group, PMVG group showed greater brain activities in the right dorsolateral prefrontal cortex (DLPFC) during the Stroop process. Moreover, correlation analysis showed that brain activities extracted from the voxel in the DLPFC cluster had a significantly negative correlation with reward sensitivity. Our current findings may suggest the compensating effect in key brain regions of inhibitory control in problematic mobile video gamers relative to healthy controls.

Recent advances in high- ß N experiments and magnetohydrodynamic instabilities with hybrid scenarios in the HL-2A Tokamak.

Over the past several years, high- ß N experiments have been carried out on HL-2A. The high- ß N is realized using double transport barriers (DTBs) with hybrid scenarios. A stationary high- ß N ( > 2 ) scenario was obtained by pure neutral-beam injection (NBI) heating. Transient high performance was also achieved, corresponding to ß N ≥ 3 , n e / n e G ∼ 0.6 , H 98 ∼ 1.5 , f b s ∼ 30 % , q 95 ∼ 4.0 , and G ∼ 0.4 . The high- ß N scenario was successfully modeled using integrated simulation codes, that is, the one modeling framework for integrated tasks (OMFIT). In high- ß N plasmas, magnetohydrodynamic (MHD) instabilities are abundant, including low-frequency global MHD oscillation with n = 1, high-frequency coherent mode (HCM) at the edge, and neoclassical tearing mode (NTM) and Alfvénic modes in the core. In some high- ß N discharges, it is observed that the NTMs with m / n = 3 / 2 limit the growth of the plasma energy and decrease ß N . The low-n global MHD oscillation is consistent with the coupling of destabilized internal (m/n = 1/1) and external (m/n = 3/1 or 4/1) modes, and plays a crucial role in triggering the onset of ELMs. Achieving high- ß N on HL-2A suggests that core-edge interplay is key to the plasma confinement enhancement mechanism. Experiments to enhance ß N will contribute to future plasma operation, such as international thermonuclear experimental reactor .

Reconstruction of 3D greyscale image for reservoir rock from a single image based on pattern dictionary.

Most methods that model 3D porous media from 2D images are based on binary images. In this paper, we propose a method for reconstructing 3D greyscale isotropic porous media images from a single image. Our proposed method incorporates a fast-sampling procedure to control the continuity and variability between adjoining reconstruction layers, a new similarity calculation method to obtain the most similar patterns from a pattern dictionary, and a central area simulation procedure to solve the block effect problem. The reconstruction results from application of our proposed method to a real reservoir 3D model obtained via computed tomography (CT) and a comparison with the original CT structure demonstrate that our proposed method can reproduce properties such as autocorrelation function, linear function, shape distribution, average shape factor, average pore radius size, average throat radius size, average pore volume, permeability and grey histogram. Further, the comparison results indicate that the statistical characteristics of the reconstructions match the training image and the CT model perfectly.

Multiscale modeling algorithm for core images.

Computed tomography (CT) images of large core samples acquired by imaging equipment are insufficiently clear and ineffectively describe the tiny pore structure; conversely, images of small core samples are insufficiently globally representative. To alleviate these challenges, the idea of a super-resolution reconstruction algorithm is combined with that of a three-dimensional core reconstruction algorithm, and a multiscale core CT image fusion reconstruction algorithm is proposed. To obtain sufficient image quality with high resolution, a large-scale core image is used to provide global feature information as well as information regarding the basic morphological structure of a large-scale pore and particle. Then the texture pattern and the tiny pore distribution information of a small-scale core image is used to refine the coarse large-scale core image. A blind image quality assessment is utilized to estimate the degradation model of core images at different scales. A multilevel pattern mapping dictionary containing local binary patterns is designed to speed up the pattern matching procedure, and an adaptive weighted reconstruction algorithm is designed to reduce the blockiness. With our method, images of the same core at different scales were successfully fused. The proposed algorithm is extensively tested on microstructures of different rock samples; all cases of the reconstructed results and those of the actual sample were found to be in good agreement with each other. The final reconstructed image contains both large-scale and small-scale information that can provide a better understanding of the core samples and inform the accurate calculation of parameters.

Pattern density function for reconstruction of three-dimensional porous media from a single two-dimensional image.

Three-dimensional (3D) structures are useful for studying the spatial structures and physical properties of porous media. A 3D structure can be reconstructed from a single two-dimensional (2D) training image (TI) by using mathematical modeling methods. Among many reconstruction algorithms, an optimal-based algorithm was developed and has strong stability. However, this type of algorithm generally uses an autocorrelation function (which is unable to accurately describe the morphological features of porous media) as its objective function. This has negatively affected further research on porous media. To accurately reconstruct 3D porous media, a pattern density function is proposed in this paper, which is based on a random variable employed to characterize image patterns. In addition, the paper proposes an original optimal-based algorithm called the pattern density function simulation; this algorithm uses a pattern density function as its objective function, and adopts a multiple-grid system. Meanwhile, to address the key point of algorithm reconstruction speed, we propose the use of neighborhood statistics, the adjacent grid and reversed phase method, and a simplified temperature-controlled mechanism. The pattern density function is a high-order statistical function; thus, when all grids in the reconstruction results converge in the objective functions, the morphological features and statistical properties of the reconstruction results will be consistent with those of the TI. The experiments include 2D reconstruction using one artificial structure, and 3D reconstruction using battery materials and cores. Hierarchical simulated annealing and single normal equation simulation are employed as the comparison algorithms. The autocorrelation function, linear path function, and pore network model are used as the quantitative measures. Comprehensive tests show that 3D porous media can be reconstructed accurately from a single 2D training image by using the method proposed in this paper.

Stable-phase method for hierarchical annealing in the reconstruction of porous media images.

In this paper, we introduce a stable-phase approach for hierarchical annealing which addresses the very large computational costs associated with simulated annealing for the reconstruction of large-scale binary porous media images. Our presented method, which uses the two-point correlation function as the morphological descriptor, involves the reconstruction of three-phase and two-phase structures. We consider reconstructing the three-phase structures based on standard annealing and the two-phase structures based on standard and hierarchical annealings. From the result of the two-dimensional (2D) reconstruction, we find that the 2D generation does not fully capture the morphological information of the original image, even though the two-point correlation function of the reconstruction is in excellent agreement with that of the reference image. For the reconstructed three-dimensional (3D) microstructure, we calculate its permeability and compare it to that of the reference 3D microstructure. The result indicates that the reconstructed structure has a lower degree of connectedness than that of the actual sandstone. We also compare the computation time of our presented method to that of the standard annealing, which shows that our presented method of orders of magnitude improves the convergence rate. That is because only a small part of the pixels in the overall hierarchy need to be considered for sampling by the annealer.