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Metallic alloys containing multiple principal alloying elements have created a growing interest in exploring the property limits of metals and understanding the underlying physical mechanisms. Refractory high-entropy alloys have drawn particular attention due to their high melting points and excellent softening resistance, which are the two key requirements for high-temperature applications. Their compositional space is immense even after considering cost and recyclability restrictions, providing abundant design opportunities. However, refractory high-entropy alloys often exhibit apparent brittleness and oxidation susceptibility, which remain important challenges for their processing and application. Here, utilizing natural-mixing characteristics among refractory elements, we designed a Ti 38 V 15 Nb 23 Hf 24 refractory high-entropy alloy that exhibits >20% tensile ductility in the as-cast state, and physicochemical stability at high temperatures. Exploring the underlying deformation mechanisms across multiple length scales, we observe that a rare β′-phase plays an intriguing role in the mechanical response of this alloy. These results reveal the effectiveness of natural-mixing tendencies in expediting high-entropy alloy discovery. A refractory high-entropy alloy was designed with the composition chosen based on the natural-mixing characteristics among refractory elements; this alloy demonstrates good tensile ductility in the as-cast state and physicochemical stability at high temperatures.

Surface lattice reconstruction is commonly observed in nickel-rich layered oxide battery cathode materials, causing unsatisfactory high-voltage cycling performance. However, the interplay of the surface chemistry and the bulk microstructure remains largely unexplored due to the intrinsic structural complexity and the lack of integrated diagnostic tools for a thorough investigation at complementary length scales. Herein, by combining nano-resolution X-ray probes in both soft and hard X-ray regimes, we demonstrate correlative surface chemical mapping and bulk microstructure imaging over a single charged LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) secondary particle. We reveal that the sub-particle regions with more micro cracks are associated with more severe surface degradation. A mechanism of mutual modulation between the surface chemistry and the bulk microstructure is formulated based on our experimental observations and finite element modeling. Such a surface-to-bulk reaction coupling effect is fundamentally important for the design of the next generation battery cathode materials. The interplay of surface chemistry and bulk microstructure in layered oxides is critical to battery performance. Here, the authors demonstrate a comprehensive understanding of such a reaction mechanism within an individual cathode particle using integrated synchrotron imaging methods.

The success of immune checkpoint inhibitors (ICIs), notably anti-cytotoxic T lymphocyte associated antigen-4 (CTLA-4) as well as inhibitors of CTLA-4, programmed death 1 (PD-1), and programmed death ligand-1 (PD-L1), has revolutionized treatment options for solid tumors. However, the lack of response to treatment, in terms of de novo or acquired resistance, and immune related adverse events (IRAE) remain as hurdles. One mechanisms to overcome the limitations of ICIs is to target other immune checkpoints associated with tumor microenvironment. Immune checkpoints such as lymphocyte activation gene-3 (LAG-3), T cell immunoglobulin and ITIM domain (TIGIT), T cell immunoglobulin and mucin-domain containing-3 (TIM-3), V-domain immunoglobulin suppressor of T cell activation (VISTA), B7 homolog 3 protein (B7-H3), inducible T cell costimulatory (ICOS), and B and T lymphocyte attenuator (BTLA) are feasible and promising options for treating solid tumors, and clinical trials are currently under active investigation. This review aims to summarize the clinical aspects of the immune checkpoints and introduce novel agents targeting these checkpoints.

Although approved programmed cell death protein (PD)-1 inhibitors show durable responses, clinical benefits to these agents are only seen in one-third of patients in most cancer types. Therefore, strategies for improving the response to PD-1 inhibitor for treating various cancers including non-small cell lung cancer (NSCLC) are urgently needed. Compared with genome and transcriptome, tumor DNA methylome in anti-PD-1 response was relatively unexplored. We compared the pre-treatment methylation status of cis-regulatory elements between responders and non-responders to treatment with nivolumab or pembrolizumab using the Infinium Methylation EPIC Array, which can profile ~850,000 CpG sites, including ~350,000 CpG sites located in enhancer regions. Then, we analyzed differentially methylated regions overlapping promoters (pDMRs) or enhancers (eDMRs) between responders and non-responders to PD-1 inhibitors. We identified 1007 pDMRs and 607 eDMRs associated with the anti-PD-1 response. We also identified 1109 and 1173 target genes putatively regulated by these pDMRs and eDMRs, respectively. We found that eDMRs contribute to the epigenetic regulation of the anti-PD-1 response more than pDMRs. Hypomethylated pDMRs of Cytohesin 1 Interacting Protein (CYTIP) and TNF superfamily member 8 (TNFSF8) were more predictive than programmed cell death protein ligand 1 (PD-L1) expression for anti-PD-1 response and progression-free survival (PFS) and overall survival (OS) in a validation cohort, suggesting their potential as predictive biomarkers for anti-PD-1 immunotherapy. The catalog of promoters and enhancers differentially methylated between responders and non-responders to PD-1 inhibitors presented herein will guide the development of biomarkers and therapeutic strategies for improving anti-PD-1 immunotherapy in NSCLC.Cancer: DNA modifications affecting response to treatmentA study into natural regulatory DNA modifications that influence patient responses could guide strategies to help the roughly two-thirds of patients who respond poorly to treatment with anticancer drugs called PD-1 inhibitors. Researchers at Yonsei University in South Korea, led by Hye Ryun Kim and Insuk Lee, investigated the significance in lung cancer patients of pre-treatment levels of DNA methylation, in which methyl (CH3) groups are added to DNA. They identified > 1000 regions of DNA in which varying methylation levels were associated with differing responses to PD-1 inhibitors. These differences affected regions of DNA called enhancers and promoters, which have been implicated in controlling the activity of more than 1000 identified genes. The research could help predict response outcomes to potential treatments and suggest possibilities for new interventions that might improve responses.

The triglyceride-glucose (TyG) index is a reliable indicator of insulin resistance. We aimed to investigate the TyG index in relation to cardio-cerebrovascular diseases (CCVDs and mortality. This retrospective study included 114,603 subjects. The TyG index was categorized into four quartiles by sex: Q1, <8.249 and <8.063; Q2, 8.249‒<8.614 and 8.063‒<8.403; Q3, 8.614‒< 8.998 and 8.403‒<8.752; and Q4, ≥8.998 and ≥8.752, in men and women, respectively. To calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the primary outcomes (CCVDs and all-cause mortality) and secondary outcomes (cardiovascular diseases [CVDs], cerebrovascular diseases [CbVDs], CCVD-related deaths, or all-cause deaths), Cox proportional hazards regression models were adopted. Compared to Q1, the HRs (95% CIs) for the primary outcomes of Q2, Q3, and Q4 were 1.062 (0.981‒1.150), 1.110 (1.024-1.204), and 1.151 (1.058-1.252) in men and 1.099 (0.986-1.226), 1.046 (0.938-1.166), and 1.063 (0.954-1.184) in women, respectively, after adjusted for age, smoking status, drinking status, physical activity, body mass index, systolic blood pressure, low-density lipoprotein cholesterol, economic status, and anti-hypertensive medications. Fully adjusted HRs (95% CIs) for CVDs of Q2, Q3, and Q4 were 1.114 (0.969-1.282), 1.185 (1.031-1.363), and 1.232 (1.068-1.422) in men and 1.238 (1.017-1.508), 1.183 (0.971-1.440), and 1.238 (1.018-1.505) in women, respectively. The adjusted HRs (95% CIs) for ischemic CbVDs of Q2, Q3, and Q4 were 1.005 (0.850-1.187), 1.225 (1.041-1.441), and 1.232 (1.039-1.460) in men and 1.040 (0.821-1.316), 1.226 (0.981-1.532), and 1.312 (1.054-1.634) in women, respectively, while the TyG index was negatively associated with hemorrhagic CbVDs in women but not in men. The TyG index was not significantly associated with CCVD-related death or all-cause death in either sex. Elevated TyG index was positively associated with the primary outcomes (CCVDs and all-cause mortality) in men and predicted higher risk of CVDs and ischemic CbVDs in both sexes.

Strategies involving metastable phases have been the basis of the design of numerous alloys, yet research on metastable high-entropy alloys is still in its infancy. In dual-phase high-entropy alloys, the combination of local chemical environments and loading-induced crystal structure changes suggests a relationship between deformation mechanisms and chemical atomic distribution, which we examine in here in a Cantor-like Cr 20 Mn 6 Fe 34 Co 34 Ni 6 alloy, comprising both face-centered cubic ( fcc ) and hexagonal closed packed ( hcp ) phases. We observe that partial dislocation activities result in stable three-dimensional stacking-fault networks. Additionally, the fraction of the stronger hcp phase progressively increases during plastic deformation by forming at the stacking-fault network boundaries in the fcc phase, serving as the major source of strain hardening. In this context, variations in local chemical composition promote a high density of Lomer-Cottrell locks, which facilitate the construction of the stacking-fault networks to provide nucleation sites for the hcp phase transformation. In dual-phase Cantor-like high entropy alloys, how local chemistry affects enhanced deformation mechanisms remains unclear. Here, the authors image 3D stacking fault networks formation and show they both impede dislocations and facilitate phase transformations via local chemical composition variations.

Single-crystalline nickel-rich cathodes are a rising candidate with great potential for high-energy lithium-ion batteries due to their superior structural and chemical robustness in comparison with polycrystalline counterparts. Within the single-crystalline cathode materials, the lattice strain and defects have significant impacts on the intercalation chemistry and, therefore, play a key role in determining the macroscopic electrochemical performance. Guided by our predictive theoretical model, we have systematically evaluated the effectiveness of regaining lost capacity by modulating the lattice deformation via an energy-efficient thermal treatment at different chemical states. We demonstrate that the lattice structure recoverability is highly dependent on both the cathode composition and the state of charge, providing clues to relieving the fatigued cathode crystal for sustainable lithium-ion batteries. The lattice strain and defects in layered oxides is critical to the intercalation chemistry and battery performance. Here, the authors demonstrate a thermal-healing of lattice defects in single-crystalline cathodes caused by the thermal-induced release of lattice strain and the structure ordering.

IL-2 therapy, which enhances the function of CD8 + T cells, was initially employed as the cornerstone of immunotherapy against cancer. However, the impact of this therapy extends beyond CD8 + T cells to cells expressing IL-2R, such as endothelial cells and regulatory T cells (Tregs), resulting in various side effects. Consequently, IL-2 therapy has taken a step back from the forefront of treatment. Immune checkpoint inhibitors (ICIs), such as anti-PD-1/PD-L1 antibodies and CTLA-4 antibodies, are used because of their durable therapeutic responses and the reduced incidence of side effects. Nevertheless, only a small fraction of cancer patients respond to ICIs, and research on IL-2 as a combination treatment to improve the efficacy of these ICIs is ongoing. To mitigate side effects, efforts have focused on developing IL-2 variants that do not strongly bind to cells expressing IL-2Rα and favor signaling through IL-2Rβγ. However, recent studies have suggested that, in the context of persistent antigen stimulation models, effective stimulation of antigen-specific exhausted CD8 + T cells in combination with PD-1 inhibitors requires either 1) binding to IL-2Rα or 2) delivery via a fusion with PD-1. This review explores the historical context of IL-2 as an immunotherapeutic agent and discusses future directions for its use in cancer immunotherapy. Enhancing cancer immunotherapy: evolution of IL-2 therapy Interleukin-2 is crucial for combating cancer, but its use is restricted due to severe side effects. This article reviews the development of IL-2 therapy and how it affects CD8 T cells—important immune cells that can become dysfunctional or “exhausted.” To reduce the unwanted effects, researchers have been trying to create a safer version of IL-2 that avoids targeting certain immune and body cells that contribute to these side effects. Recent studies, however, indicate that using the original form of IL-2 or specifically targeting exhausted CD8 T cells with a marker called PD-1 could be more effective in fighting tumors. Additionally, combining IL-2 therapy with PD-1 blockade can enhance T cells response to cancer. These findings suggest a promising future for personalized and effective cancer treatments. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.

This study analyzed whether a systematic relationship exists between corporate social responsibility (CSR) performance and corporate financial performance using 191 sample firms listed on the Korea Exchange. The Korea Economic Justice Institute (KEJI) index of 2015 was used to measure CSR performance; profitability and firm value were used to measure corporate financial performance. Return on assets was used as a proxy for profitability, and Tobin’s Q was used as a proxy for firm value. The correlation between these variables and CSR performance was examined through correlation and regression analysis. The results confirm that CSR performance has a partial positive correlation with profitability and firm value. These results are partly consistent with those of previous studies reporting a positive relationship between CSR and Korean firms’ financial performance using the KEJI index before 2011. In the relationship between CSR performance and profitability, only social contribution yields a statistically positive correlation. Analysis of the correlation between CSR performance and financial performance indicators revealed a positive relationship between the growth rate of total assets and corporate soundness and social contribution. Both soundness and social contribution showed a positive correlation with Tobin’s Q, the measure of corporate value.

Autonomous driving represents a transformative advancement with the potential to significantly impact daily mobility, including enabling independent vehicle operation for individuals with visual disabilities. The commercialization of autonomous driving requires guaranteed safety and accuracy, underscoring the need for robust localization and environmental perception algorithms. In cost-sensitive platforms such as delivery robots and electric vehicles, cameras are increasingly favored for their ability to provide rich visual information at low cost. Despite recent progress, existing visual–inertial odometry systems still suffer from degraded accuracy in challenging conditions, which limits their reliability in real-world autonomous navigation scenarios. Estimating 3D positional changes using only 2D image sequences remains a fundamental challenge primarily due to inherent scale ambiguity and the presence of dynamic scene elements. In this paper, we present a visual–inertial odometry framework incorporating a depth estimation model trained without ground-truth depth supervision. Our approach leverages a self-supervised learning pipeline enhanced with knowledge distillation via foundation models, including both self-distillation and geometry-aware distillation. The proposed method improves depth estimation performance and consequently enhances odometry estimation without modifying the network architecture or increasing the number of parameters. The effectiveness of the proposed method is demonstrated through comparative evaluations on both the public KITTI dataset and a custom campus driving dataset, showing performance improvements over existing approaches.