Facial masks are often used to treat skin problems, and the introduction of microcurrent ion penetration technology can improve drug penetration and help facial tissue repair. However, most microcurrent stimulation masks contain a direct current power supply and require external power sources, resulting in inconvenient portability and use. Herein, we provide a noninvasive self-powered iontophoresis mask with a water-driven power supply, which is continuously prepared by self-constructing equipment to continually construct a zinc–manganese fiber battery (Zn-Mn@FB) and then seamlessly integrated with a nonwoven cellulose-based superabsorbent fiber substrate. The mask can be activated by water and is simple and portable to use. Zn-Mn@FB demonstrated a capacitance retention of 65.22% (1,000 cycles) and a specific discharge capacity of 27.33 mAh/g (10 cm), which improved with an increase in battery length to up to 41 mAh/g (30 cm). The iontophoresis mask exhibited a stable current within the safe range of 0.09 to 0.59 mA (within 800 s) after water activation, and the drug penetration area increased by 102.64%. The platform is expected to become a practical device for enhanced transdermal drug delivery in the medical field, with the potential to integrate additional components for expanded functionality and productization in the future.

Foxp3⁺ regulatory T (T_reg) cells, as one of the subtypes of CD4⁺ T cells, are the crucial gatekeeper in the pathogenesis of self-antigen reactive diseases. In this context, we demonstrated that the selective ablation of early growth response gene 1 (Egr-1) in CD4⁺ T cells exacerbated experimental autoimmune encephalomyelitis (EAE) in murine models. The absence of Egr-1 in CD4⁺ T cells, obtained from EAE mice and naïve CD4⁺ T cells, impeded the differentiation and influence of T_reg. Importantly, in CD4⁺ T cells of multiple sclerosis patients, both Egr-1 and Foxp3 were found to decrease. Further studies showed that distinct from the classical Smad3 route, TGF-β could activate Egr-1 through the Raf–Erk signaling route to promote Foxp3 genetic modulation, thereby promoting T_reg cell differentiation and reducing EAE inflammation. A novel natural Egr-1 agonist, calycosin, was found to attenuate EAE progression by regulating the differentiation of T_reg. Together, the above results indicate the value of Egr-1, as a novel Foxp3 transactivator, for the differentiation of T_reg cells in the development of self-antigen reactive diseases.

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.

Computed tomography perfusion (CTP) plays a crucial role in guiding reperfusion therapy and patient selection for acute ischemic stroke (AIS) through perfusion parameter maps of the brain; however, its widespread use is limited by the complexity of acquisition protocols and high radiation dose. Previous studies have attempted to reduce radiation exposure by equally lowering the temporal sampling rate; however, it may miss the peak of arterial enhancement, leading to underestimation of blood flow parameter. Here, we investigate the feasibility of using a generative adversarial network (GAN) to generate perfusion maps from 3 phases of CTP (mCTP). The three phases were chosen based on the multiphase computed tomography angiography scanning protocol: the peak arterial input function phase, the peak venous output function phase, and the delayed venous output function phase. The findings demonstrate that the GAN model achieved high visual overlap and performance for cerebral blood flow and time-to-maximum maps, with a mean structural similarity index measure of 0.921 to 0.971 and 0.817 to 0.883, a mean normalized root mean squared error of 0.019 to 0.108 and 0.058 to 0.064, and a mean learned perceptual image patch similarity of 0.039 to 0.088 and 0.141 to 0.146, respectively. For the 2 external datasets, the volume agreement between the model- and CTP-derived infarct and hypoperfusion areas was the intraclass correlation coefficient of 0.731 to 0.883 and 0.499 to 0.635, and the Spearman correlation coefficient of 0.720 to 0.808 and 0.533 to 0.6540, respectively. Qualitative assessments of diagnostic quality further confirmed that the mCTP-derived maps were comparable to those obtained from traditional CTP. In conclusion, the GAN-based model is effective in generating perfusion maps from mCTP, which could serve as a viable alternative to traditional CTP in the diagnostic evaluation of AIS.

Psoriasis, a chronic inflammatory skin disorder, remains challenging to treat due to poor skin barrier penetration, limited efficacy, and adverse effects of current therapies. Natural plant-derived extracellular vesicle-like particles (EVPs) have emerged as biocompatible carriers for bioactive molecules. Among various medicinal plants screened, Perilla frutescens leaf-derived EVPs (PLEVPs) exhibited strong anti-inflammatory and antioxidant effects. By incorporating PLEVPs into a hydrogel formulation, we enhanced their stability, retention at psoriatic lesions, and transdermal delivery efficiency. In vivo studies demonstrated that the PLEVPs markedly alleviated psoriasis symptoms in both preventive and therapeutic mouse models, outperforming conventional treatments. This effect was attributed to reduced oxidative stress, modulation of Treg cells, and promotion of keratinocyte apoptosis. Transcriptomic analysis revealed enrichment of the interleukin-17 (IL-17) signaling pathway, a major driver of psoriasis, while small RNA sequencing identified pab-miR396a-5p, an endogenous microRNA (miRNA) within PLEVPs, as a key regulator. Mechanistic studies showed that pab-miR396a-5p targets the 3′-untranslated region of plant heat shock protein 83a, a homolog of mammalian heat shock protein 90, leading to the suppression of nuclear factor-kappa B and Janus kinase/signal transducers and activators of transcription signaling, inhibiting the IL-17 signaling pathway. Validation using lipid nanoparticles encapsulating pab-miR396a-5p mimics confirmed comparable therapeutic effects. This study highlights the potential of plant-derived EVPs as carriers of endogenous miRNAs, enabling interkingdom communication and offering a scalable platform for psoriasis therapy.

Stress-induced apoptosis presents an obstacle to bone marrow mesenchymal stem cell (BMSC) transplantation to repair steroid-induced osteonecrosis of the femoral head (SONFH). Thus, appropriate intervention strategies should be explored to mitigate this. In our previous study, we discovered a new subgroup of BMSCs—the oxidative stress-resistant BMSCs (OSR-BMSCs)—which can survive the oxidative stress microenvironment in the osteonecrotic area, through a mechanism that currently remains unclear. In this study, we found that B-lymphoid tyrosine kinase (BLK) may be the crucial factor regulating the oxidative stress resistance of OSR-BMSCs, as it is highly expressed in these cells. Knockdown of BLK eliminated oxidative stress resistance, aggravated oxidative stress-induced apoptosis, reduced the survival of OSR-BMSCs in the oxidative stress microenvironment of the osteonecrotic area, and greatly weakened the transplantation efficacy of OSR-BMSCs for SONFH. By contrast, BLK was weakly expressed in oxidative stress-sensitive BMSCs (OSS-BMSCs). Overexpression of BLK in susceptible OSS-BMSCs allowed them to acquire oxidative stress resistance, inhibited oxidative stress-induced apoptosis, promoted their survival in the osteonecrotic area, and improved the transplantation efficacy of OSS-BMSCs for SONFH. Mechanistically, BLK concurrently activates redox and apoptotic signaling networks through its tyrosine kinase activity, which confers oxidative stress resistance to BMSCs and inhibits their stress-induced apoptosis of BMSCs. Herein, we report that OSR-BMSCs have intrinsic oxidative stress resistance that is conferred and mediated by BLK. This finding provides a potential new intervention strategy for improving the survival of transplanted BMSCs and the therapeutic efficacy of BMSC transplantation for SONFH.

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.

Hydrogel microparticles that can effectively deliver mesenchymal stem cells (MSCs) are expected to accelerate wound repair progress. Attempts in the area are focusing on improving the functions of the microparticles and MSCs to promote the therapeutic effect. Here, inspired by the topological morphology of ice branches, we propose novel freeze-derived anisotropic porous microparticles for hepatocyte growth factor (HGF)-overexpressing MSCs (MSCs^HGF) loading and wound healing. The microparticles were fabricated by introducing microfluidic methacrylated gelatin pre-gel droplets into low-temperature silicone oil, followed by photo-cross-linking and freeze-drying processes. Drawing an advantage from the biocompatible chemical composition and the structured pore arrangement of the microparticles, MSCs^HGF can be efficiently encapsulated and released, maintaining continuous HGF secretion to enhance cell migration and support vascular regeneration. Leveraging these characteristics, we have shown that MSCs^HGF-loaded porous microparticles could substantially promote angiogenesis, polarize macrophages toward the M2 phenotype, and reduce inflammation during the wound repair process, consequently enhancing skin wound repair efficiency. Thus, we believe that our MSCs^HGF-integrated freeze-derived anisotropic porous microparticles hold promising prospects for clinical wound-healing applications.

Endometriosis is marked by the ectopic growth, spread, and invasion of endometrial tissue beyond the uterus, resulting in recurrent bleeding, pain, reproductive challenges, and the formation of nodules or masses. Despite advancements in detection methods like ultrasound and laparoscopy, these techniques remain limited by low specificity and invasiveness, underscoring the need for a highly specific, noninvasive in vitro diagnostic method. This study investigates the potential of using menstrual blood as a noninvasive diagnostic sample for endometriosis by targeting genetic and inflammatory markers associated with endometriosis lesions. A novel digital droplet enzyme-linked immunosorbent assay (ddELISA) was developed, leveraging SiO₂ nanoparticles for the femtomolar-sensitive detection of inflammatory cytokines (OPN, IL-10, IL-6) in menstrual blood. Single-cell RNA sequencing revealed differentiation patterns across endometrial tissues and menstrual blood, affirming that menstrual blood replicates key inflammatory and immune properties of endometriosis. Furthermore, endometriosis menstrual blood endometrial cells derived from human menstrual blood displayed similar properties to endometrial stromal cells in endometriosis lesions, validating menstrual blood as a suitable in vitro diagnostic sample. In contrast to traditional ELISA, ddELISA supports multi-target detection with enhanced sensitivity and reduced processing time, allowing precise biomarker analysis from minimal sample volumes. Our ddELISA-based approach shows promise as a rapid, accessible, and accurate diagnostic tool for endometriosis, with potential for practical clinical application.

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, and addressing its intrinsic heterogeneity has emerged as a valuable avenue for novel clinical treatment strategy. Here, we put forward an innovative strategy for TNBC treatment by simultaneously suppressing both p21-activated kinase 1 (PAK1) and histone deacetylase (HDAC) class IIb (HDAC6/10). A series of pyrido [2,3-d]pyrimidin-7(8H)-one moiety derivatives was successfully designed and synthesized to target PAK1/HDAC6/HDAC10 by utilizing structure-based screening and pharmacophore integration. ZMF-25 demonstrates marked inhibitory activity against PAK1, HDAC6, and HDAC10 with respective IC₅₀ values of 33, 64, and 41 nM, remarkable selectivity over HDACs and PAKs, as well as prominent antiproliferative efficiency in MDA-MB-231 cells. Additionally, ZMF-25 effectively suppresses TNBC proliferation and migration by inhibiting PAK1/HDAC6/HDAC10. Moreover, it was found to impair glycolysis and trigger reactive oxygen species generation, resulting in autophagy-related cell death by inhibiting the AKT/mTOR/ULK1 signaling. Furthermore, ZMF-25 exhibits remarkable therapeutic potential with no obvious toxicity in vivo and good pharmacokinetics. In summary, these observations indicate that ZMF-25 is a novel and potent triple-targeting PAK1/HDAC6/HDAC10 inhibitor, which is expected to provide a novel and effective strategy for TNBC treatment.