Previous studies have indicated that major depressive disorder (MDD) patients with suicidal ideation (SI) present abnormal functional connectivity (FC) and network organization in node-centric brain networks, ignoring the interactions among FCs. Whether the abnormalities of edge interactions affect the emergence of SI and are related to the gene expression remains largely unknown. In this study, resting-state functional magnetic resonance imaging (fMRI) data were collected from 90 first-episode, drug-naive MDD with suicidal ideation (MDDSI) patients, 60 first-episode, drug-naive MDD without suicidal ideation (MDDNSI) patients, and 98 healthy controls (HCs). We applied the methodology of edge-centric network analysis to construct the functional brain networks and calculate the nodal entropy. Furthermore, we examined the relationships between nodal entropy alterations and gene expression. The MDDSI group exhibited significantly lower subnetwork entropy in the dorsal attention network (DAN) and significantly greater subnetwork entropy in the default mode network than the MDDNSI group. The visual learning score of the measurement and treatment research to improve cognition in schizophrenia (MATRICS) consensus cognitive battery was negatively correlated with the subnetwork entropy of DAN in the MDDSI group. The support vector machine model based on nodal entropy achieved an accuracy of 81.87% when distinguishing the MDDNSI and MDDSI. Additionally, the changes in SI-related nodal entropy were associated with the expression of genes in cell signaling and interactions, as well as immune and inflammatory responses. These findings reveal the abnormalities in nodal entropy between the MDDSI and MDDNSI groups, demonstrated their association with molecular functions, and provided novel insights into the neurobiological underpinnings and potential markers for the prediction and prevention of suicide.

Graded hypoxia is a common microenvironment in malignant solid tumors. As a central regulator in the hypoxic response, hypoxia-inducible factor-1 (HIF-1) can induce multiple cellular processes including glycolysis, angiogenesis, and necroptosis. How cells exploit the HIF-1 pathway to coordinate different processes to survive hypoxia remains unclear. We developed an integrated model of the HIF-1α network to elucidate the mechanism of cellular adaptation to hypoxia. By numerical simulations and bifurcation analysis, we found that HIF-1α is progressively activated with worsening hypoxia due to the sequential deactivation of the hydroxylases prolyl hydroxylase domain enzymes and factor inhibiting HIF (FIH). Bistable switches control the activation and deactivation processes. As a result, glycolysis, immunosuppression, angiogenesis, and necroptosis are orderly elicited in aggravating hypoxia. To avoid the excessive accumulation of lactic acid during glycolysis, HIF-1α induces monocarboxylate transporter and carbonic anhydrase 9 sequentially to export intracellular hydrogen ions, facilitating tumor cell survival. HIF-1α-induced miR-182 facilitates vascular endothelial growth factor production to promote angiogenesis under moderate hypoxia. The imbalance between accumulation and removal of lactic acid in severe hypoxia may result in acidosis and induce cell necroptosis. In addition, the deactivation of FIH results in the destabilization of HIF-1α in anoxia. Collectively, HIF-1α orchestrates the adaptation of tumor cells to hypoxia by selectively inducing its targets according to the severity of hypoxia. Our work may provide clues for tumor therapy by targeting the HIF-1 pathway.

Sepsis, a life-threatening inflammatory disorder characterized by multiorgan failure, arises from a dysregulated immune response to infection. Modulating macrophage polarization has emerged as a promising strategy to control sepsis-associated inflammation. The endogenous metabolite itaconate has shown anti-inflammatory potential by suppressing the stimulator of interferon genes (STING) pathway, but its efficacy is inhibited by hyperactive glycolysis, which sustains macrophage overactivation. Here, we revealed a critical crosstalk between the itaconate–STING axis and glycolysis in macrophage-mediated inflammation. Building on this interplay, we developed a novel nanoparticle LDO (lonidamine disulfide 4-octyl-itaconate), a self-assembled metabolic regulator integrating an itaconate derivative with the glycolysis inhibitor Lonidamine. By concurrently targeting glycolysis and STING pathways, LDO reprograms macrophages to restore balanced polarization. In sepsis models, LDO effectively attenuates CCL2-driven cytokine storms, alleviates acute lung injury, and significantly enhances survival via metabolic reprogramming. This study offers a cytokine-regulatory strategy rooted in immunometabolism, providing a foundation for the translational development of immune metabolite-based sepsis therapies.

The convergence of the Metaverse and the Internet of Things (IoT) paves the way for extensive data interaction between connected devices and digital twins; however, this simultaneously introduces considerable cybersecurity threats, including data breaches, ransomware, and device tampering. Existing intrusion detection algorithms struggle to effectively defend against emerging cyberattacks in the rapidly evolving Metaverse environment. Designing effective neural networks for intrusion detection algorithms relies heavily on expert experience, making the manual process time-consuming and often yielding suboptimal results. This paper addresses a critical gap in cybersecurity for Metaverse devices, which are often overlooked in traditional detection methods, and proposes an adaptive multiobjective evolutionary generative adversarial network (AME-GAN) as a novel, scalable solution for optimizing network intrusion detection. An inversely proportional hybrid attention-based long short-term memory GAN is proposed, combining GANs to generate minority class samples and alleviate the imbalance problem in training datasets, which has long hindered accurate intrusion detection. Additionally, an adaptive evolutionary neural architecture search algorithm for the supernet of the GAN is designed to guide the mutation direction of the supernet, enhancing the training stability. This paper further introduces a double mutation multiobjective evolutionary neural architecture search algorithm, integrating both the multiobjective evolutionary algorithm and the neural architecture search to optimize accuracy, real-time performance, and model diversity—a crucial aspect for Metaverse devices with diverse hardware constraints. Experiments conducted on 3 well-known datasets—NSL-KDD, UNSW-NB15, and CIC-IDS2017—demonstrate that AME-GAN outperforms state-of-the-art approaches, with improvements of 0.32% in accuracy, 0.31% in F1 score, 0.47% in precision, and 0.37% in recall. This paper offers a promising, adaptive framework to enhance cybersecurity in the Metaverse, improving detection performance and real-time applicability, and contributing to the future of network intrusion detection in next-generation digital environments.

Since the scarcity of bandwidth resources has become increasingly critical in modern communication systems, orbital angular momentum (OAM) with a higher degree of freedom in information modulation has become a promising solution to alleviate the shortage of spectrum resources. Consequently, the integration of OAM with millimeter-wave technology has emerged as a focal point in next-generation communication research. Recently, programmable metasurfaces have gained considerable attention as essential devices for OAM generation due to real-time tunability, but their profiles are relatively high as a result of the external feed source. This paper proposes a conformal radiation-type programmable metasurface operating in the millimeter-wave band. By employing a series–parallel hybrid feed network to replace conventional external feed sources, the overall profile of the metasurface system can be reduced to less than 0.1λ. Furthermore, the proposed innovation design could also achieve a conformal cross-shaped architecture, which is ultraportable and very effective in integrating with the front ends of satellites or aircraft and eliminating issues such as feed source blockage as well as energy spillover losses in conventional metasurfaces. The proposed metasurface could achieve a realized gain of 22.54 dB with an aperture efficiency of 21.75%, thus generating high-purity OAM waves with topological charges of l = 0, l = +1, l = +2, and l = +3. Additionally, by incorporating beam scanning techniques, OAM waves could be deflected to accommodate scenarios with moving receivers, demonstrating substantial potential for future high-speed wireless communication applications.

Prussian blue and Prussian blue analogs are widely used in sodium-ion batteries (SIBs). In this study, we upcycle the degraded Prussian blue directly into layered materials for SIBs through thermal treatment. Prussian blue thermally decomposes to form metal oxides, which then recrystallize into layered metal oxides with metal–nitrogen bond on their surface under suitable temperature conditions. This transformation method is similar to solid-state synthesis, allowing for the pre-addition of necessary components before material conversion to optimize the composition and integrity of the target materials. Based on in situ x-ray diffraction observations of the crystal structure changes of Prussian blue at different temperatures, we demonstrate 1,000 °C as the optimal temperature for converting to layered materials. These materials exhibit an initial discharge capacity of 122.3 mAh g⁻¹ and good rate and cycling stability. We hope that this research will promote the sustainable development of the SIB industry.

Adoptive T cell therapy has shown great promise in the treatment of solid tumors, which, however, poses a great challenge to obtain autologous tumor-reactive T cells in a cost-effective manner. Here, we present a dynamic tumor immunology-on-a-chip, mimicking immune responses, for achieving the enrichment and expansion of tumor-reactive T cells. Tumor spheroids with uniform size can be generated by seeding tumor cells in hydrogel-embedded micropillar arrays, and could be trapped upon removal of hydrogel. Then, T cells were infused and fully contacted with these tumor spheroids under biomimetic flow conditions provided by herringbone-patterned microgrooves arrays. We found that the tamed tumor-reactive T cells could be fully activated and a rapid clonal proliferation was realized during the cultivation. In addition, these tumor-reactive T cells exhibited a specific and powerful tumor-killing capability in vitro. Thus, the suggested dynamic microfluidic chips with staged structure-transformable properties realize both the producible formation of tumor spheroids and the recapitulation of tumor-immune crosstalk to expand tumor-reactive T cells. These features indicate that the dynamic and reproducible tumor immunology-on-a-chip has potential in the preparation of therapeutic T cell products for clinical cancer immunotherapy.

The intricate relationship between cancer, circadian rhythms, and aging is increasingly recognized as a critical factor in understanding the mechanisms underlying tumorigenesis and cancer progression. Aging is a well-established primary risk factor for cancer, while disruptions in circadian rhythms are intricately associated with the tumorigenesis and progression of various tumors. Moreover, aging itself disrupts circadian rhythms, leading to physiological changes that may accelerate cancer development. Despite these connections, the specific interplay between these processes and their collective impact on cancer remains inadequately explored in the literature. In this review, we systematically explore the physiological mechanisms of circadian rhythms and their influence on cancer development. We discuss how core circadian genes impact tumor risk and prognosis, highlighting the shared hallmarks of cancer and aging such as genomic instability, cellular senescence, and chronic inflammation. Furthermore, we examine the interplay between circadian rhythms and aging, focusing on how this crosstalk contributes to tumorigenesis, tumor proliferation, and apoptosis, as well as the impact on cellular metabolism and genomic stability. By elucidating the common pathways linking aging, circadian rhythms, and cancer, this review provides new insights into the pathophysiology of cancer and identifies potential therapeutic strategies. We propose that targeting the circadian regulation of cancer hallmarks could pave the way for novel treatments, including chronotherapy and antiaging interventions, which may offer important benefits in the clinical management of cancer.

Disruption of acylcarnitine homeostasis results in life-threatening outcomes in humans. Carnitine–acylcarnitine translocase deficiency (CACTD) is a scarce autosomal recessive genetic disease and may result in patients' death due to heart arrest or respiratory insufficiency. However, the reasons and mechanism of CACTD inducing respiratory insufficiency have never been elucidated. Herein, we employed lipidomic techniques to create comprehensive lipidomic maps of entire lungs throughout both prenatal and postnatal developmental stages in mice. We found that the acylcarnitines manifested notable variations and coordinated the expression levels of carnitine–acylcarnitine translocase (Cact) across these lung developmental stages. Cact-null mice were all dead with a symptom of respiratory distress and exhibited failed lung development. Loss of Cact resulted in an accumulation of palmitoyl-carnitine (C16-acylcarnitine) in the lungs and promoted the proliferation of mesenchymal progenitor cells. Mesenchymal cells with elevated C16-acylcarnitine levels displayed minimal changes in energy metabolism but, upon investigation, revealed an interaction with sterile alpha motif domain and histidine-aspartate domain-containing protein 1 (Samhd1), leading to decreased protein abundance and enhanced cell proliferation. Thus, our findings present a mechanism addressing respiratory distress in CACTD, offering a valuable reference point for both the elucidation of pathogenesis and the exploration of treatment strategies for neonatal respiratory distress.

Plant diseases caused by vegetable viruses are an important threat to global food security, presenting a major challenge for the development of antiviral agrochemicals. Functional proteins of plant viruses play a crucial role in the viral life cycle, and targeted inhibition of these proteins has emerged as a promising strategy. However, the current discovery of antiviral small molecules is hampered by the limitations of synthetic approaches and the narrow range of targets. Herein, we report a practical application of organocatalysis for serving pesticide discovery that bears a unique molecular basis. An N-heterocyclic carbene-modulated reaction is first designed to asymmetrically functionalize diverse natural phenols with phthalides. Our designed method is capable of producing a series of new phthalidyl ethers under mild conditions with good yields, enantioselectivity, and functional group tolerance. Among these, compound (R)-3w exhibits excellent and enantioselectivity-preferred curative activity against potato virus Y (PVY). Mechanistically, it is proposed that (R)-3w interacts with the nuclear inclusion body A (Nia) protein of PVY at the His150 residue. This binding impairs Nia's function to cleavage polyprotein, thereby inhibiting formation of viral replication complex. The study provides insights into advancing synthetic protocol to facilitate agrochemical discovery, and our identified (R)-3w may serve as a potential lead for future research and development PVY-Nia inhibitors.