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The emergence of high-entropy materials has inspired the exploration of novel materials in diverse technologies. In electrochemical energy storage, high-entropy design has shown advantageous impacts on battery materials such as suppressing undesired short-range order, frustrating energy landscape, decreasing volumetric change and reducing the reliance on critical metals. This comment addresses the definition and potential improper use of the term “high entropy” in the context of battery materials design, highlights the unique properties of high-entropy materials in battery applications, and outlines the remaining challenges in the synthesis, characterization, and computational modeling of high-entropy battery materials.

Primary angle closure glaucoma (PACG) is higher in Asians than Europeans and Africans, with over 80% of PACG worldwide in Asia. Previous estimates of PACG were based largely on early studies, mostly using inappropriate case definitions. Therefore, we did a systematic review and meta-analysis to estimate the prevalence of PACG in adult Asian populations and to quantify its association with age, gender, and region. All primary reports of population-based studies that reported the prevalence of PACG in adult Asian populations were identified. PACG case definition was compatible with the ISGEO definition. Twenty-nine population-based studies were included. The overall pooled prevalence estimates were calculated using a random effect model, and ethnicity-, age- and gender-specific pooled prevalence estimates were also calculated. The overall pooled prevalence of PACG in those of adult Asians was 0.75% (95% CI, 0.58, 0.96). Ethnicity-specific pooled prevalence estimates were 0.97% (0.22, 4.27) in Middle East group, 0.66% (0.23, 1.86) in South East Asia group, 0.46% (0.32, 0.64) in India group, 1.10% (0.85, 1.44) in China group, and 1.19% (0.35, 3.98) in Japan group, respectively. Age-specific prevalence was 0.21% (0.12, 0.37) for those 40-49 years, 0.54% (0.34, 0.85) for those 50-59 years, 1.26% (0.93, 1.71) for those 60-69 years, and 2.32% (1.74, 3.08) for those 70 years or above. The overall female to male ratio of the PACG prevalence was 1.51∶1 (95% CI 1.01, 2.28). PACG affects approximately 0.75% adult Asians, increasing double per decade, and 60% of cases being female. The prevalence rates vary greatly by ethnic region.

A bstract In this paper, we consider rotating multistate boson stars with quartic self-interactions. In contrast to the nodeless quartic-boson stars in [1], the self-interacting multistate boson stars (SIMBSs) have two types of nodes, including the 1 S 2 S and 1 S 2 P states. We show the mass M of SIMBSs as a function of the synchronized frequency ω , and the nonsynchronized frequency ω 2 for three different cases. Moreover, for the case of two coexisting states with self-interacting potential, we study the mass M of SIMBSs versus the angular momentum J for the synchronized frequency ω and the nonsynchronized frequency ω 2 . Furthermore, for three different cases, we analyze the coexisting phase with both the ground and first excited states for SIMBSs. We also calculate the maximum value of coupling parameter Λ, and find the coupling parameter Λ exists the finite range.

Academic performance is a crucial issue in the field of Online learning analytics. While deep learning-based models have made significant progress in the era of big data, many of these methods need help to capture the complex relationships present in online learning activities and student attributes, which are essential for improving prediction accuracy. We present a novel model for predicting academic performance in this paper. This model harnesses the power of dual graph neural networks to effectively utilize both the structural information derived from interaction activities and the attribute feature spaces of students. The proposed model uses an interaction-based graph neural network module to learn local academic performance representations from online interaction activities and an attribute-based graph neural network to learn global academic performance representations from attribute features of all students using dynamic graph convolution operations. The learned representations from local and global levels are combined in a local-to-global representation learning module to generate predicted academic performances. The empirical study results demonstrate that the proposed model significantly outperforms existing methods. Notably, the proposed model achieves an accuracy of 83.96% for predicting students who pass or fail and an accuracy of 90.18% for predicting students who pass or withdraw on a widely recognized public dataset. The ablation studies confirm the effectiveness and superiority of the proposed techniques.

Although various types of drugs and therapies are available to treat atherosclerosis, it remains a major cause of mortality throughout the world. Macrophages are the major source of foam cells, which are hallmarks of atherosclerotic lesions. Consequently, the roles of macrophages in the pathophysiology of atherosclerosis are increasingly investigated. Autophagy is a self-protecting cellular catabolic pathway. Since its discovery, autophagy has been found to be associated with a variety of diseases, including cardiovascular diseases, malignant tumors, neurodegenerative diseases, and immune system disorders. Accumulating evidence demonstrates that autophagy plays an important role in inhibiting inflammation and apoptosis, and in promoting efferocytosis and cholesterol efflux. These facts sug- gest the induction of autophagy may be exploited as a potential strategy for the treatment of atherosclerosis. In this review we mainly discuss the relationship between macrophage autophagy and atherosclerosis and the molecular mechanisms, as well as the recent advances in targeting the process of autophagy to treat atherosclerosis.

Intrinsic and acquired anti-HER2 resistance remains a major hurdle for treating HER2-positive breast cancer. Using genome-wide CRISPR/Cas9 screening in vitro and in vivo, we identify FGFR4 as an essential gene following anti-HER2 treatment. FGFR4 inhibition enhances susceptibility to anti-HER2 therapy in resistant breast cancer. Mechanistically, m6A-hypomethylation regulated FGFR4 phosphorylates GSK-3β and activates β-catenin/TCF4 signaling to drive anti-HER2 resistance. Notably, suppression of FGFR4 dramatically diminishes glutathione synthesis and Fe 2+ efflux efficiency via the β-catenin/TCF4-SLC7A11/FPN1 axis, resulting in excessive ROS production and labile iron pool accumulation. Ferroptosis, a unique iron-dependent form of oxidative cell death, is triggered after FGFR4 inhibition. Experiments involving patient-derived xenografts and organoids reveals a synergistic effect of anti-FGFR4 with anti-HER2 therapy in breast cancer with either intrinsic or acquired resistance. Together, these results pinpoint a mechanism of anti-HER2 resistance and provide a strategy for overcoming resistance via FGFR4 inhibition in recalcitrant HER2-positive breast cancer. Anti-HER2 resistance causes treatment failure in HER2-positive breast cancers. Here the authors identify FGFR4 as one of the vulnerabilities of anti-HER2 resistant breast cancer and show that FGRR4 inhibition enhances sensitivity to anti-HER2 treatment in these resistant cells by triggering ferroptosis.

The aim of the present study was to determine the effect of the long non-coding RNA (lncRNA) bladder cancer-associated transcript 1 (BLACAT1) in chemoresistance of non-small cell lung cancer (NSCLC) cells. Expression of lncRNA BLACAT1, microRNA (miR)-17, autophagy-related protein 7 (ATG7), multidrug-resistance protein 1 (MRP1), and the autophagy-associated proteins light chain 3 (LC3)-II/LC3-I and Beclin 1 were detected using the reverse transcription-quantitative polymerase chain reaction and western blot analysis. Cell viability was determined using an MTT assay. The interaction between BLACAT1 and miR-17 was determined using RNA immunoprecipitation and RNA pull-down assays. A cisplatin (DDP)-resistant NSCLC cell A549/DDP xenograft model in nude mice was established to investigate the effect of BLACAT1 on the chemoresistance of NSCLC cells. Compared with in DDP-sensitive NSCLC cells, expression of BLACAT1, ATG7, MRP1, LC3-II/LC3-I and Beclin 1 was significantly upregulated in DDP-resistant NSCLC cells, whereas miR-17 was downregulated in DDP-resistant NSCLC cells. Short interfering RNA against BLACAT1 decreased the viability of DDP-resistant NSCLC cells. In addition, BLACAT1 interacted with miR-17, and negatively regulated miR-17. BLACAT1 promoted ATG7 expression through miR-17, and facilitated autophagy and promoted chemoresistance of NSCLC cells through miR-17/ATG7. Finally, in vivo experiments indicated that inhibition of BLACAT1 ameliorated the chemoresistance of NSCLC. BLACAT1 was upregulated in DDP-resistant NSCLC cells, and promoted autophagy and chemoresistance of NSCLC cells through the miR-17/ATG7 signaling pathway.

We present a catalog of 32,162 12CO molecular clouds that covers the northern outer Galactic plane (l = [15°, 165°] and l = [195°, 230°], and b = [−5.°25, +5.°25]). The catalog was produced using a DBSCAN algorithm applied to the Milky Way Imaging Scroll Painting project data. We systematically analyze both the integrated properties and scaling relationships of these molecular clouds across different Galactocentric radii (8 < R GC < 26 kpc). An interesting finding is that each cloud property’s mean, median, and maximum values generally decrease systematically with increasing R GC, approximated quantitatively by exponential functions. The mass and size spectra for the entire sample show power-law indices of γ = −2.00 ± 0.13 and an upper mass limit of M 0 = (4.5 ± 2.8) × 106 M ⊙, and γ = −3.68 ± 0.48 with an upper size limit of R 0 = 144 ± 80 pc, respectively. These spectra exhibit steeper slopes and reduced upper limits as R GC increases. The derived scaling relations are M=12.00Reff2.41±0.003 , σv=0.25Reff0.66±0.003 , and α vir = 37.2M −0.40 ± 0.002 for the whole outer Galaxy clouds. These scaling relations show slightly steeper correlations observed in more distant locations and notably deviate from Larson’s relations. We find that 44.3% of the molecular mass resides in gravitationally bound structures, a proportion significantly higher than systematic studies from the CfA survey and external galaxies. Moreover, comparisons among different R GC subsamples also reveal a decrease in the amount of bound mass with increasing R GC. The scale length of the molecular disk is estimated to be approximately 2 kpc. These results, based on a constant CO conversion factor of XCO=2.0×1020cm−2Kkms−1−1 , may be slightly altered by variations in X CO. In summary, our findings provide robust evidence for the influence of Galactic evolution on molecular cloud properties, at least in the outer Galaxy region studied.

Cancer cells are often addicted to serine synthesis to support growth. How serine synthesis is regulated in cancer is not well understood. We recently demonstrated protein arginine methyltransferase 1 (PRMT1) is upregulated in hepatocellular carcinoma (HCC) to methylate and activate phosphoglycerate dehydrogenase (PHGDH), thereby promoting serine synthesis. However, the mechanisms underlying PRMT1 upregulation and regulation of PRMT1-PHGDH axis remain unclear. Here, we show the E3 ubiquitin ligase F-box-only protein 7 (FBXO7) inhibits serine synthesis in HCC by binding PRMT1, inducing lysine 37 ubiquitination, and promoting proteosomal degradation of PRMT1. FBXO7-mediated PRMT1 downregulation cripples PHGDH arginine methylation and activation, resulting in impaired serine synthesis, accumulation of reactive oxygen species (ROS), and inhibition of HCC cell growth. Notably, FBXO7 is significantly downregulated in human HCC tissues, and inversely associated with PRMT1 protein and PHGDH methylation level. Overall, our study provides mechanistic insights into the regulation of cancer serine synthesis by FBXO7-PRMT1-PHGDH axis, and will facilitate the development of serine-targeting strategies for cancer therapy. How serine synthesis is regulated in cancer remains to be further explored. Here the authors identify FBXO7, an E3 ubiquitin ligase, inhibits serine synthesis in hepatocellular carcinoma by promoting ubiquitination and degradation of PRMT1 methyltransferase.

We study the physical properties and 3D distribution of molecular clouds (MCs) toward the Cygnus region using the MWISP CO survey and Gaia DR3 data. Based on Gaussian decomposition and clustering for 13CO lines, over 70% of the fluxes are recovered. With the identification result of 13CO structures, two models are designed to measure the distances of the molecular gas in velocity crowding regions. The distances of more than 200 large 13CO structures are obtained toward the 150 deg2 region. Additionally, tens of the identified MC structures coincide well with masers and/or intense mid-IR emission. We find multiple gas layers toward the region: (1) the extensive gas structures composing the Cygnus Rift from 700 pc to 1 kpc across the whole region; (2) the ∼1.3 kpc gas layer mainly in the Cygnus X South region; and (3) the 1.5 kpc dense filament at the Cygnus X North region and many cometary clouds shaped by Cygnus OB2. We also note that the spatial distribution of young stellar object candidates is generally consistent with the molecular gas structures. The total molecular mass of the Cygnus region is estimated to be ∼2.7 × 106 M ⊙ assuming an X-factor ratio XCO=2×1020cm−2(Kkms−1)−1 . The foreground Cygnus Rift contributes ∼25% of the molecular mass in the whole region. Our work presents a new 3D view of the MCs' distribution toward the Cygnus X region, as well as the exact molecular gas mass distribution in the foreground Cygnus Rift.