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Since their discovery in 1960 1 , metallic glasses based on a wide range of elements have been developed 2 . However, the theoretical prediction of glass-forming compositions is challenging and the discovery of alloys with specific properties has so far largely been the result of trial and error 3 – 8 . Bulk metallic glasses can exhibit strength and elasticity surpassing those of conventional structural alloys 9 – 11 , but the mechanical properties of these glasses are critically dependent on the glass transition temperature. At temperatures approaching the glass transition, bulk metallic glasses undergo plastic flow, resulting in a substantial decrease in quasi-static strength. Bulk metallic glasses with glass transition temperatures greater than 1,000 kelvin have been developed, but the supercooled liquid region (between the glass transition and the crystallization temperature) is narrow, resulting in very little thermoplastic formability, which limits their practical applicability. Here we report the design of iridium/nickel/tantalum metallic glasses (and others also containing boron) with a glass transition temperature of up to 1,162 kelvin and a supercooled liquid region of 136 kelvin that is wider than that of most existing metallic glasses 12 . Our Ir–Ni–Ta–(B) glasses exhibit high strength at high temperatures compared to existing alloys: 3.7 gigapascals at 1,000 kelvin 9 , 13 . Their glass-forming ability is characterized by a critical casting thickness of three millimetres, suggesting that small-scale components for applications at high temperatures or in harsh environments can readily be obtained by thermoplastic forming 14 . To identify alloys of interest, we used a simplified combinatorial approach 6 – 8 harnessing a previously reported correlation between glass-forming ability and electrical resistivity 15 – 17 . This method is non-destructive, allowing subsequent testing of a range of physical properties on the same library of samples. The practicality of our design and discovery approach, exemplified by the identification of high-strength, high-temperature bulk metallic glasses, bodes well for enabling the discovery of other glassy alloys with exciting properties. Bulk metallic glasses made from alloys of iridium, nickel, tantalum and boron are developed by combinatorial methods, with higher strength at high temperature than those previously produced.

Cross-talk between competitive endogenous RNAs (ceRNAs) may play a critical role in revealing potential mechanisms of tumor development and physiology. Glioblastoma is the most common type of malignant primary brain tumor, and the mechanisms of tumor genesis and development in glioblastoma are unclear. Here, to investigate the role of non-coding RNAs and the ceRNA network in glioblastoma, we performed paired-end RNA sequencing and microarray analyses to obtain the expression profiles of mRNAs, lncRNAs, circRNAs and miRNAs. We identified that the expression of 501 lncRNAs, 1999 mRNAs, 2038 circRNAs and 143 miRNAs were often altered between glioblastoma and matched normal brain tissue. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed on these differentially expressed mRNAs and miRNA-mediated target genes of lncRNAs and circRNAs. Furthermore, we used a multi-step computational framework and several bioinformatics methods to construct a ceRNA network combining mRNAs, miRNAs, lncRNAs and circRNA, based on co-expression analysis between the differentially expressed RNAs. We identified that plenty of lncRNAs, CircRNAs and their downstream target genes in the ceRNA network are related to glutamatergic synapse, suggesting that glutamate metabolism is involved in glioma biological functions. Our results will accelerate the understanding of tumorigenesis, cancer progression and even therapeutic targeting in glioblastoma.

Background Mitochondrial genomes of flowering plants (angiosperms) are highly dynamic in genome structure. The mitogenome of the earliest angiosperm Amborella is remarkable in carrying rampant foreign DNAs, in contrast to Liriodendron , the other only known early angiosperm mitogenome that is described as ‘fossilized’. The distinctive features observed in the two early flowering plant mitogenomes add to the current confusions of what early flowering plants look like. Expanded sampling would provide more details in understanding the mitogenomic evolution of early angiosperms. Here we report the complete mitochondrial genome of water lily Nymphaea colorata from Nymphaeales, one of the three orders of the earliest angiosperms. Results Assembly of data from Pac-Bio long-read sequencing yielded a circular mitochondria chromosome of 617,195 bp with an average depth of 601×. The genome encoded 41 protein coding genes, 20 tRNA and three rRNA genes with 25 group II introns disrupting 10 protein coding genes. Nearly half of the genome is composed of repeated sequences, which contributed substantially to the intron size expansion, making the gross intron length of the Nymphaea mitochondrial genome one of the longest among angiosperms, including an 11.4-Kb intron in cox2 , which is the longest organellar intron reported to date in plants. Nevertheless, repeat mediated homologous recombination is unexpectedly low in Nymphaea evidenced by 74 recombined reads detected from ten recombinationally active repeat pairs among 886,982 repeat pairs examined. Extensive gene order changes were detected in the three early angiosperm mitogenomes, i.e. 38 or 44 events of inversions and translocations are needed to reconcile the mitogenome of Nymphaea with Amborella or Liriodendron , respectively. In contrast to Amborella with six genome equivalents of foreign mitochondrial DNA, not a single horizontal gene transfer event was observed in the Nymphaea mitogenome. Conclusions The Nymphaea mitogenome resembles the other available early angiosperm mitogenomes by a similarly rich 64-coding gene set, and many conserved gene clusters, whereas stands out by its highly repetitive nature and resultant remarkable intron expansions. The low recombination level in Nymphaea provides evidence for the predominant master conformation in vivo with a highly substoichiometric set of rearranged molecules.

Water lilies belong to the angiosperm order Nymphaeales. Amborellales, Nymphaeales and Austrobaileyales together form the so-called ANA-grade of angiosperms, which are extant representatives of lineages that diverged the earliest from the lineage leading to the extant mesangiosperms 1 – 3 . Here we report the 409-megabase genome sequence of the blue-petal water lily ( Nymphaea colorata ). Our phylogenomic analyses support Amborellales and Nymphaeales as successive sister lineages to all other extant angiosperms. The N. colorata genome and 19 other water lily transcriptomes reveal a Nymphaealean whole-genome duplication event, which is shared by Nymphaeaceae and possibly Cabombaceae. Among the genes retained from this whole-genome duplication are homologues of genes that regulate flowering transition and flower development. The broad expression of homologues of floral ABCE genes in N. colorata might support a similarly broadly active ancestral ABCE model of floral organ determination in early angiosperms. Water lilies have evolved attractive floral scents and colours, which are features shared with mesangiosperms, and we identified their putative biosynthetic genes in N. colorata . The chemical compounds and biosynthetic genes behind floral scents suggest that they have evolved in parallel to those in mesangiosperms. Because of its unique phylogenetic position, the N. colorata genome sheds light on the early evolution of angiosperms. The genome of the tropical blue-petal water lily Nymphaea colorata and the transcriptomes from 19 other Nymphaeales species provide insights into the early evolution of angiosperms.

Glioma is one of the common tumors in the central nervous system, and its treatment methods (surgery, radiotherapy, and chemotherapy) lack specificity and have a poor prognosis. With the development of immunology, cell biology, and genomics, tumor immunotherapy has ushered in a new era of tumor therapy, achieving significant results in other invasive cancers such as advanced melanoma and advanced non-small cell lung cancer. Currently, the clinical trials of immunotherapy in glioma are also progressing rapidly. Here, this review summarizes promising immunotherapy methods in recent years, reviews the current status of clinical trials, and discusses the challenges and prospects of glioma immunotherapy.

Glucose transporter 1 (GLUT1) overexpression in tumor cells is a potential target for drug therapy, but few studies have reported screening GLUT1 inhibitors from natural or synthetic compounds. With current analysis techniques, it is difficult to accurately monitor the GLUT1 inhibitory effect of drug molecules in real-time. We developed a cell membrane-based glucose sensor (CMGS) that integrated a hydrogel electrode with tumor cell membranes to monitor GLUT1 transmembrane transport and screen for GLUT1 inhibitors in traditional Chinese medicines (TCMs). CMGS is compatible with cell membranes of various origins, including different types of tumors and cell lines with GLUT1 expression knocked down by small interfering RNA or small molecules. Based on CMGS continuous monitoring technique, we investigated the glucose transport kinetics of cell membranes with varying levels of GLUT1 expression. We used CMGS to determine the GLUT1-inhibitory effects of drug monomers with similar structures from Scutellaria baicalensis and catechins families. Results were consistent with those of the cellular glucose uptake test and molecular-docking simulation. CMGS could accurately screen drug molecules in TCMs that inhibit GLUT1, providing a new strategy for studying transmembrane protein-receptor interactions. [Display omitted] •A cell membrane-based sensor is developed to monitor GLUT1 transport in real-time.•The glucose transport kinetics with different GLUT1 expression levels is investigated.•The GLUT1 inhibitors from derivatives of traditional Chinese medicine is screened.

The extensive deployment of quadrotors in complex environmental missions has revealed a critical challenge: degradation of trajectory tracking accuracy due to time-varying wind disturbances. Conventional model-based controllers struggle to adapt to nonlinear wind field dynamics, while data-driven approaches often suffer from catastrophic forgetting that compromises environmental adaptability. This paper proposes a reinforcement learning framework with continual adaptation capabilities to enhance robust tracking performance for quadrotors operating in dynamic wind fields. We develop a continual reinforcement learning framework integrating continual backpropagation algorithms with reinforcement learning. Initially, a foundation model is trained in wind-free conditions. When wind disturbance intensity undergoes gradual variations, a neuron utility assessment mechanism dynamically resets inefficient neurons to maintain network plasticity. Concurrently, a multi-objective reward function is designed to improve both training precision and efficiency. The Gazebo/PX4 simulation platform was utilized to validate the wind disturbance stepwise growth and stochastic variations. This approach demonstrated a reduction in the root mean square error of trajectory tracking when compared to the standard PPO algorithm. The proposed framework resolves the plasticity loss problem in deep reinforcement learning through structured neuron resetting, significantly enhancing the continual adaptation capabilities of quadrotors in dynamic wind fields.

An experimental investigation of circular concrete-filled steel tubular (CFST) columns subjected to very low-elevation lateral impacts was performed. Six circular CFST members were prepared for lateral impact tests according to the typical CFST columns in high-speed railway stations in China, and the impact location was at the height of the 2/9 column. The tests had three variables: the thickness of the steel tube, the impact velocity, and the axial load. The failure modes were determined in the tests, along with the time histories of the impact force and the deflection at the impact location. A finite-element analysis was performed to examine the effects of the axial load and scaling on the maximum deflection. The results show that with the increase of axial compression ratio, the impact resistance of the member first increases and then weakens. According to the travelling plastic hinge theory, a three-stage rigid plastic mechanical model was employed to describe the impact process, in which the impact location was at the non-mid-span, and a deflection calculation method for CFST applicable to any impact position was developed. A comparison with the test results indicated that deflections can be calculated with reasonable accuracy using the proposed method.

Diffuse midline glioma-H3K27M mutant (DMG) and glioblastoma (GBM) are the most lethal brain tumors that primarily occur in pediatric and adult patients, respectively. Both tumors exhibit significant heterogeneity, shaped by distinct genetic/epigenetic drivers, transcriptional programs including RNA splicing, and microenvironmental cues in glioma niches. However, the spatial organization of cellular states and niche-specific regulatory programs remain to be investigated. Here, we perform a spatial profiling of DMG and GBM combining short- and long-read spatial transcriptomics, and single-cell transcriptomic datasets. We identify clinically relevant transcriptional programs, RNA isoform diversity, and multi-cellular ecosystems across different glioma niches. We find that while the tumor core enriches for oligodendrocyte precursor-like cells, radial glial stem-like (RG-like) cells are enriched in the neuron-rich invasive niche in both DMG and GBM. Further, we identify niche-specific regulatory programs for RG-like cells, and functionally confirm that FAM20C mediates invasive growth of RG-like cells in a neuron-rich microenvironment in a human neural stem cell derived orthotopic DMG model. Together, our results provide a blueprint for understanding the spatial architecture and niche-specific vulnerabilities of DMG and GBM. The spatial organisation of diffuse midline glioma-H3K27M mutant (DMG) and glioblastoma (GBM) remains to be investigated. Here, the authors integrate short-read and long-read spatial profiling of DMG and GBM to identify regulatory programs and cellular ecosystems in distinct glioma niches.

The brachistochrone (shortest-time) curve is the path connecting two points that enables the shortest travel time. This work explores the “brachistochrone path” of fire spread connecting two points at the same altitude and with a fixed path length. The starting and ending points are connected by both thermally thin fuels (thin wires) and thermally thick fuels (PMMA bars). Flame-spread paths of triangular, rectangular, and circular shapes with different heights and inclinations are explored. Results show that having a local maximum flame-spread rate does not result in the shortest overall travel time. For thin-wire paths, the fastest overall-path fire spread occurs, when the upward spread path is vertical, and the path height reaches a maximum, as demonstrated by the theoretical analysis. Differently, for thick PMMA-bar paths, the brachistochrone condition occurs when the path length of the vertical upward spread reaches the maximum, because the upward spread is about ten times faster than the downward spread. This study extends the conventional problem of the fastest fire spread to the shortest-time problem of the whole fire path, and it may help optimize the fuel distribution inside the built environment and estimate available safe egress time in building and wildland fires.