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High-entropy alloys (HEAs) have attracted extensive attention in recent decades due to their unique chemical, physical, and mechanical properties. An in-depth understanding of the structure–property relationship in HEAs is the key to the discovery and design of new compositions with desirable properties. Related to this, materials genome strategy has been increasingly used for discovering new HEAs with better performance. This review paper provides an overview of key advances in this fast-growing area, along with current challenges and potential opportunities for HEAs. We also discuss related topics, such as high-throughput preparation, characterization, and computation of HEAs, and data-driven machine learning for accelerating alloy development. Finally, future research directions and perspectives for the materials genome-assisted design of HEAs are proposed and discussed.High-entropy alloys exhibit attractive property combinations. This review paper discusses the use of the materials genome strategy for identifying promising high-entropy alloys, including high-throughout synthesis, characterization, and data-driven machine learning.

Copper ions are essential for cellular physiology. Cuproptosis is a novel method of copper-dependent cell death, and the cuproptosis-based signature for glioma remains less studied. Several glioma datasets with clinicopathological information were collected from TCGA, GEO and CGGA. Robust Multichip Average (RMA) algorithm was used for background correction and normalization, cuproptosis-related genes (CRGs) were then collected. The TCGA-glioma cohort was clustered using ConsensusClusterPlus. Univariate Cox regression analysis and the Random Survival Forest model were performed on the differentially expressed genes to identify prognostic genes. The cuproptosis-signature was constructed by calculating CuproptosisScore using Multivariate Cox regression analysis. Differences in terms of genomic mutation, tumor microenvironment, and enrichment pathways were evaluated between high- or low-CuproptosisScore. Furthermore, drug response prediction was carried out utilizing pRRophetic. Two subclusters based on CRGs were identified. Patients in cluster2 had better clinical outcomes. The cuproptosis-signature was constructed based on CuproptosisScore. Patients with higher CuproptosisScore had higher WHO grades and worse prognosis, while patients with lower grades were more likely to develop IDH mutations or MGMT methylation. Univariate and Multivariate Cox regression analysis demonstrated CuproptosisScore was an independent prognostic factor. The accuracy of the signature in prognostic prediction was further confirmed in 11 external validation datasets. In groups with high-CuproptosisScore, PIK3CA, MUC16, NF1, TTN, TP53, PTEN, and EGFR showed high mutation frequency. IDH1, TP53, ATRX, CIC, and FUBP1 demonstrated high mutation frequency in low-CuproptosisScore group. The level of immune infiltration increased as CuproptosisScore increased. SubMap analysis revealed patients with high-CuproptosisScore may respond to anti-PD-1 therapy. The IC50 values of Bexarotene, Bicalutamide, Bortezomib, and Cytarabine were lower in the high-CuproptosisScore group than those in the low-CuproptosisScore group. Finally, the importance of IGFBP2 in TCGA-glioma cohort was confirmed. The current study revealed the novel cuproptosis-based signature might help predict the prognosis, biological features, and appropriate treatment for patients with glioma.

Traumatic brain injury (TBI) is a common disease in neurosurgery with a high fatality and disability rate which imposes a huge burden on society and patient's family. Inhibition of neuroinflammation caused by microglia activation is a reasonable strategy to promote neurological recovery after TBI. Myricetin is a natural flavonoid that has shown good therapeutic effects in a variety of neurological disease models, but its therapeutic effect on TBI is not clear. We demonstrated that intraperitoneal injection of appropriate doses of myricetin significantly improved recovery of neurological function after TBI in Sprague Dawley rats and inhibited excessive inflammatory responses around the lesion site. Myricetin dramatically reduced the expression of toxic microglia markers generated by TBI and LPS, according to the outcomes of in vivo and in vitro tests. In particular, the expression of inducible nitric oxide synthase, cyclooxygenase 2, and some pro-inflammatory cytokines was reduced, which protected learning and memory functions in TBI rats. Through network pharmacological analysis, we found that myricetin may inhibit microglia hyperactivation through the EGFR-AKT/STAT pathway. These findings imply that myricetin is a promising treatment option for the management of neuroinflammation following TBI.

As a promising candidate for high-density data storage and neuromorphic computing, cross-point memory arrays provide a platform to overcome the von Neumann bottleneck and accelerate neural network computation. In order to suppress the sneak-path current problem that limits their scalability and read accuracy, a two-terminal selector can be integrated at each cross-point to form the one-selector-one-memristor (1S1R) stack. In this work, we demonstrate a CuAg alloy-based, thermally stable and electroforming-free selector device with tunable threshold voltage and over 7 orders of magnitude ON/OFF ratio. A vertically stacked 64 × 64 1S1R cross-point array is further implemented by integrating the selector with SiO 2 -based memristors. The 1S1R devices exhibit extremely low leakage currents and proper switching characteristics, which are suitable for both storage class memory and synaptic weight storage. Finally, a selector-based leaky integrate-and-fire neuron is designed and experimentally implemented, which expands the application prospect of CuAg alloy selectors from synapses to neurons. Designing efficient selector devices remains a challenge. Here, the authors propose a CuAg alloy-based selector with excellent ON/OFF ratio and thermal stability. It can effectively suppress the sneak-path current in 1S1R arrays, making it suitable for storage class memory and neuromorphic computing applications.

In planar flow casting (PFC) process, the molten alloy from nozzle exerts cyclical thermal shock on the substrate surface of cooling wheel and the cyclical thermal shock causes damage to the substrate surface in the form of defects. In this paper, a 2D numerical model was explored and the cyclical thermal shock on the surface of cooling wheel was simulated by numerical method using practical casting parameters. A batch of hot rolled copper-beryllium (Cu-2Be) cylindrical rings was prepared and subjected to solution annealing and aging treatments. The coefficients of thermal conductivity, thermal expansion coefficients and mechanical properties of Cu-2Be rings with different aging conditions were measured. The metallograph and SEM of the Cu-2Be rings subjected to 105 cycles of thermal shock were examined. The simulation results show that the surface temperature underneath the puddle is heated up drastically to a maximum temperature around 350 °C and cooled down to a minimum temperature around 140 °C in each revolution in quasi-steady process, and the lower thermal conductivity leads to the higher surface temperature for Cu-2Be substrate. The mechanical and physical responses of a Cu-2Be alloy aged at different conditions as a substrate of cooling wheel have been investigated after 105 cycles of thermal shock in practical casting. It was observed that the cyclical thermal shock leads to damage to Cu-2Be surface which affects the surface quality of as-cast ribbon. It was found that higher thermal expansion coefficient of Cu-2Be alloy leads to large magnitude of surface expansion and surface shrinkage which results in crack damage while lower thermal expansion coefficient of Cu-2Be alloy resulting from higher temperature aging is benefit to reducing the magnitude of surface expansion and surface shrinkage but the strength of Cu-2Be substrate is also reduced and intergranular erosion occurs after 105 cycles of thermal shock.

Central nervous system (CNS) diseases encompass spinal cord injuries, brain tumors, neurodegenerative diseases, and ischemic strokes. Recently, there has been a growing global recognition of CNS disorders as a leading cause of disability and death in humans and the second most common cause of death worldwide. The global burdens and treatment challenges posed by CNS disorders are particularly significant in the context of a rapidly expanding global population and aging demographics. The blood-brain barrier (BBB) presents a challenge for effective drug delivery in CNS disorders, as conventional drugs often have limited penetration into the brain. Advances in biomimetic membrane nanomaterials technology have shown promise in enhancing drug delivery for various CNS disorders, leveraging properties such as natural biological surfaces, high biocompatibility and biosafety. This review discusses recent developments in biomimetic membrane materials, summarizes the types and preparation methods of these materials, analyzes their applications in treating CNS injuries, and provides insights into the future prospects and limitations of biomimetic membrane materials.

Prostate stem cell antigen (PSCA) is associated with disease progression, promotion of angiogenesis, invasion, metastasis and immune evasion in cancer. However, its expression pattern and diagnostic and prognostic potential have not been thoroughly analysed from a pan-cancer perspective. This study aimed to examine the effects of PSCA on the prognosis and inflammatory cell infiltration patterns of various cancer types. We analysed the relationship between PSCA expression and immunological subtypes in tumor microenvironment (TME) and the role of molecular subtypes, potentially promising immune biomarkers and tumour-infiltrating lymphocytes (TILs) in various cancer types, especially lung adenocarcinoma (LUAD). In addition, we investigated the prognostic significance of PSCA expression in LUAD. The co-expression network of PSCA was found to be mainly involved in the regulation of immune responses and antigen processing and expression and was significantly enriched in pathological and substance metabolism-related pathways in cancer. Altogether, this study reveals that PSCA is a promising target for immunotherapy in patients with cancer.

Class I KNOTTED-like homeobox ( KNOXI ) genes are parts of the regulatory network that control the evolutionary diversification of leaf morphology. Their specific spatiotemporal expression patterns in developing leaves correlate with the degrees of leaf complexity between simple-leafed and compound-leafed species. However, KNOXI genes are not involved in compound leaf formation in several legume species. Here, we identify a pathway for dual repression of MtKNOXI function in Medicago truncatula . PINNATE-LIKE PENTAFOLIATA1 ( PINNA1 ) represses the expression of MtKNOXI , while PINNA1 interacts with MtKNOXI and sequesters it to the cytoplasm. Further investigations reveal that UNUSUAL FLORAL ORGANS ( MtUFO ) is the direct target of MtKNOXI, and mediates the transition from trifoliate to pinnate-like pentafoliate leaves. These data suggest a new layer of regulation for morphological diversity in compound-leafed species, in which the conserved regulators of floral development, MtUFO , and leaf development, MtKNOXI , are involved in variation of pinnate-like compound leaves in M. truncatula . This study reveals a pathway in which the transformation of trifoliate leaves into pinnate-like pentafoliate leaves is regulated by the conserved regulators of floral development ( MtUFO ) and leaf development ( MtKNOXI ) in M. truncatula .

Fe-based metallic glasses (MGs) have been extensively investigated due to their unique properties, especially the outstanding soft-magnetic properties. However, conventional design of soft-magnetic Fe-based MGs is heavily relied on “trial and error” experiments, and thus difficult to balance the saturation flux density (Bs) and thermal stability due to the strong interplay between the glass formation and magnetic interaction. Herein, we report an eXtreme Gradient Boosting (XGBoost) machine-learning (ML) model for developing advanced Fe-based MGs with a decent combination of Bs and thermal stability. While it is an attempt to apply ML for exploring soft-magnetic property and thermal stability, the developed XGBoost model based on the intrinsic elemental properties (i.e., atomic size and electronegativity) can well predict Bs and Tx (the onset crystallization temperature) with an accuracy of 93.0% and 94.3%, respectively. More importantly, we derived the key features that primarily dictate Bs and Tx of Fe-based MGs from the ML model, which enables the revelation of the physical origins underlying the high Bs and thermal stability. As a proof of concept, several Fe-based MGs with high Tx (>800 K) and high Bs (>1.4 T) were successfully developed in terms of the ML model. This work demonstrates that the XGBoost ML approach is interpretable and feasible in the extraction of decisive parameters for properties of Fe-based magnetic MGs, which might allow us to efficiently design high-performance glassy materials.

TCP proteins, the plant-specific transcription factors, are involved in the regulation of multiple aspects of plant development among different species, such as leaf development, branching, and flower symmetry. However, thus far, the roles of TCPs in legume, especially in nodulation are still not clear. In this study, a genome-wide analysis of genes was carried out to discover their evolution and function in . In total, 21 were identified and classified into class I and class II, and the class II were further divided into two subclasses, CIN and CYC/TB1. The expression profiles of are dramatically different. The universal expression of class I was detected in all organs. However, the in CIN subclass were highly expressed in leaf and most of the members in CYC/TB1 subclass were highly expressed in flower. Such organ-specific expression patterns of suggest their different roles in plant development. In addition, most were down-regulated during the nodule development, except for the putative targets, , and . Overexpression of significantly reduced the expression level of and resulted in the decreased nodule number, indicating the important roles of -targeted in nodulation. Taken together, this study systematically analyzes the gene family at a genome-wide level and their possible functions in nodulation, which lay the basis for further explorations of module in association with nodule development in .