Self-propulsion enzymatic nanomotors have shown tremendous potential in the field of diagnostics. In a study led by Wang and coworkers, nanoenzyme-driven cup-shaped nanomotors were designed for enhanced cell penetration and synergistic photodynamic/thermal treatments under single near-infrared laser irradiation. By combining the concepts of self-propulsion enzymatic nanomotors and synergistic dual-modal therapy, this work provides a new idea and tool for the application of nanomotors in the biomedical field.

Fusobacterium nucleatum (Fn), an oral anaerobic commensal, has recently been identified as a crucial oncogenic contributor to colorectal cancer pathogenesis through its ectopic colonization in the gastrointestinal tract. Accumulating evidence reveals its multifaceted involvement in colorectal cancer initiation, progression, metastasis, and therapeutic resistance to conventional treatments, including chemotherapy, radiotherapy, and immunotherapy. This perspective highlights recent advances in anti-Fn strategies, including small-molecule inhibitors, nanomedicines, and biopharmaceuticals, while critically analyzing the translational barriers in developing targeted antimicrobial interventions. We further propose potential strategies to overcome current challenges in Fn modulation, aiming to pave the way for more effective therapeutic interventions and better clinical outcomes.

The Hopf whole-brain model, based on structural connectivity, overcomes limitations of traditional structural or functional connectivity-focused methods by incorporating heterogeneity parameters, quantifying dynamic brain characteristics in healthy and diseased states. Traditional parameter fitting techniques lack precision, restricting broader use. To address this, we validated parameter fitting methods using simulated networks and synthetic models, introducing improvements such as individual-specific initialization and optimized gradient descent, which reduced individual data loss. We also developed an approximate loss function and gradient adjustment mechanism, enhancing parameter fitting accuracy and stability. Applying this refined method to datasets for major depressive disorder (MDD) and autism spectrum disorder (ASD), we identified differences in brain regions between patients and healthy controls, explaining related anomalies. This rigorous validation is crucial for clinical application, paving the way for precise neuropathological identification and novel treatments in neuropsychiatric research, demonstrating substantial potential in clinical neurology.

Epidermal growth factor receptor/mitogen-activated protein kinase (EGFR/MAPK) signaling is highly activated in various types of cancer. The long noncoding RNAs induced by this pathway and their roles in colorectal cancer (CRC) have not been fully elucidated. In this study, based on the profiling of long noncoding RNAs triggered by EGFR/MAPK signaling, we identified that ESSENCE (EGF [epidermal growth factor] Signal Sensing CAD's Effect; ENST00000415336), which is mediated by the transcription factor early growth response factor 1, functions as a potent oncogenic molecule that predicts poor prognosis in CRC. Mechanistically, ESSENCE directly interacts with carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD) and competitively attenuates CAD degradation mediated by its newly discovered E3 ligase KEAP1, thereby suppressing ferroptosis and promoting CRC progression. Importantly, combinational treatment of the mitogen-activated extracellular signal-regulated kinase inhibitor selumetinib and ferroptosis inducer sulfasalazine synergistically suppresses ESSENCE-high CRC in a patient-derived xenograft mouse model. Taken together, these findings demonstrate the crucial role of ESSENCE in mediating CRC progression by regulating CAD stabilization and suggest a therapeutic strategy of targeting the ESSENCE–CAD axis in CRC.

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.

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.

A new photoelectrocatalytic water purification system was investigated by combining photocatalysis and electrochemistry. This configuration achieves simultaneous removal of both organic compounds and inorganic heavy metal ions from water by taking a carbon electrode as the working electrode and another electrode coated with a photocatalyst as the counter electrode. A negative bias potential is imparted onto the working electrode to induce the reduction of heavy metal ions, whereas the photocatalytic degradation of organic pollutants on the counter electrode is amplified via the transfer of photoexcited electrons from the counter electrode to the working electrode. Evaluations conducted in bulk solutions demonstrated that photoelectrocatalysis surpassed photocatalysis by yielding an organic matter degradation efficiency 2.3 times higher, successfully degrading 98% of a 10 μM methylene blue solution within 2 h. Simultaneously, the system realized the recovery of heavy metal ions, including copper, lead, and cadmium. This new photoelectrocatalytic water purification system was further integrated with microchannels, and the testing data affirm the substantial potential for system miniaturization.

Background: A century ago, a mystery between a virus and Parkinson’s disease (PD) was described. Owing to the limitation of human brain biopsy and the challenge of electron microscopy in observing virions in human brain tissue, it has been difficult to study the viral etiology of PD. Recent discovery of virobiota reveals that viruses coexist with humans as symbionts. Newly developed transcriptomic sequencing and novel bioinformatic approaches for mining the encrypted virome in human transcriptome make it possible to study the relationship between symbiotic viruses and PD. Nevertheless, whether viruses exist in the human substantia nigra (SN) and whether symbiotic viruses underlie PD pathogenesis remain unknown. Methods: We collected current worldwide human SN transcriptomic datasets from the United States, the United Kingdom, the Netherlands, and Switzerland. We used bioinformatic approaches including viruSITE and the Viral-Track to identify the existence of viruses in the SN of patients. The comprehensive RNA sequencing-based virome analysis pipeline was used to characterize the virobiota in the SN. The Pearson’s correlation analysis was used to examine the association between the viral RNA fragment counts (VRFCs) and PD-related human gene sequencing reads in the SN. The differentially expressed genes (DEGs) in the SN between PD patients and non-PD individuals were used to examine the molecular signatures of PD and also evaluate the impact of symbiotic viruses on the SN. Findings: We observed the existence of viruses in the human SN. A dysbiosis of virobiota was found in the SN of PD patients. A marked correlation between VRFC and PD-related human gene expression was detected in the SN of PD patients. These PD-related human genes correlated to VRFC were named as the virus-correlated PD-related genes (VPGs). We identified 3 bacteriophages (phages), including the Proteus phage VB_PmiS-Isfahan, the Escherichia phage phiX174, and the Lactobacillus phage Sha1, that might impair the gene expression of neural cells in the SN of PD patients. The Proteus phage VB_PmiS-Isfahan was a common virus in the SN of patients from the United Kingdom, the Netherlands, and Switzerland. VPGs and DEGs together highlighted that the phages might dampen dopamine biosynthesis and weaken the cGAS-STING function. Interpretation: This is the first study to discover the involvement of phages in PD pathogenesis. A lifelong low symbiotic viral load in the SN may be a contributor to PD pathogenesis. Our findings unlocked the black box between brain virobiota and PD, providing a novel insight into PD etiology from the perspective of phage–human symbiosis.

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.

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.

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.

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.

Stimuli-responsive materials have shown promising applications in the areas of sensing, bioimaging, information encryption, and bioinspired camouflage. In particular, multi-stimuli-responsive materials represent a hot topic due to their modulated properties under multiple stimuli. Herein, we successfully developed multi-stimuli-responsive inks and a series of complex multi-stimuli-responsive 3-dimensional (3D) structures were fabricated via digital light processing 3D-printing technology. Notably, these complex 3D structures show shape memory, fast-response photochromic and thermochromic behavior, and excellent repeatability due to the combination of photochromic molecules (4-(2,2-bis(4-fluorophenyl)vinyl) benzyl methacrylate) and thermochromic pigments. Furthermore, a programmable encrypted box that changes colors and morphology by controlling temperature and ultraviolet irradiation was designed and printed, and this encrypted box exhibits strong security using OpenCV-based image recognition technology. This strategy provides a promising approach for the design of multi-stimuli-responsive materials and complex encryption systems in the future.

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.

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.

Pulmonary arterial hypertension (PAH) is a devastating disease characterized by perivascular inflammation, immune dysregulation, and vascular remodeling. Recent studies have unveiled a potential link between the gut microbiome and PAH pathogenesis, suggesting that microbial dysbiosis and increased intestinal permeability may contribute to the inflammatory pathology in PAH and ultimately disease progression. This perspective highlights the emerging evidence of the role of leaky gut in PAH, the interplay between microbiota-induced immune responses, and the activation of endogenous retroviruses like human endogenous retrovirus K. Understanding these complex interactions opens new interdisciplinary avenues for research and therapeutic interventions, potentially transforming PAH management through microbiome-targeted strategies.

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.

High-grade lung neuroendocrine carcinomas (Lu-NECs) are clinically refractory malignancies with poor prognosis and limited therapeutic advances. The biological and molecular features underlying the histological heterogeneity of Lu-NECs are not fully understood. In this study, we present a multi-omics integration of whole-exome sequencing and deep proteomic profiling in 93 Chinese Lu-NECs to establish the first comprehensive proteogenomic atlas of this disease spectrum. Our analyses revealed a high degree of mutational concordance among the subtypes at the genomic level; however, distinct proteomic profiles enabled a clear differentiation of histological subtypes, unveiling subtype-specific molecular and biological features related to tumor metabolism, immunity, and proliferation. Furthermore, RB1 mutations confer divergent prognostic effects through subtype-specific cis- and trans-proteomic regulation. In addition, we identified potential protein biomarkers for histological subtype classification and risk stratification, which were validated by immunohistochemistry in an independent cohort. This study provides a valuable proteogenomic resource and insight into Lu-NEC heterogeneity.

Bacterial infections markedly strain healthcare systems financially, compounded by the rise of drug-resistant strains and biofilm-associated infections. Gas therapy has emerged as a notable solution, disrupting biofilms and targeting resistant bacteria through controlled gas release mechanisms. However, achieving precise and controlled gas release remains a critical challenge for the successful implementation of gas therapy. In this perspective, we summarize recent advancements in photocatalytic gas release for treating bacterial infections. It also outlines crucial challenges that must be addressed to fully leverage this promising therapeutic strategy, enhancing its precision and effectiveness in clinical settings.

Proteins play a critical role in biology and biopharma due to their specificity and minimal side effects. Predicting the effects of mutations on protein stability is vital but experimentally challenging. Deep learning offers an efficient solution to this problem. In the present work, we introduced ProstaNet, a deep learning framework that predicts stability changes resulting from single- and multiple-point mutations using geometric vector perceptrons–graph neural network for 3-dimensional feature processing. For training ProstaNet, we meticulously crafted ProstaDB, a comprehensive and pristine thermodynamics repository, including 3,784 single-point mutations and 1,642 multiple-point mutations. We also created thermodynamic looping for enlarging the limited data size of multiple-point mutation and applied an innovative clustering method to generate a standard testing set of multiple-point mutation. Besides, we identified residue scoring as the most important encoding method in protein properties prediction. With these innovations, ProstaNet accurately predicts thermostability changes for both single-point and multiple-point mutations without showing any bias. ProstaNet achieves an accuracy of 0.75, outperforming existing methods for single-point mutation prediction, including ThermoMPNN (0.63), PoPMuSiC^sym (0.66), MUPRO (0.52), and FoldX (0.71). ProstaNet also achieves a 1.3-fold increase in accuracy compared to FoldX for multiple-point mutation predictions. Validated by experiment, 4 out of 5 single-point mutation predictions (80%) and all multiple-point mutation predictions (100%) for HuJ3 mutants were accurate, demonstrating the potential benefits of ProstaNet for protein engineering and drug development.

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.

Increasing evidence indicates that oligodendrocyte (OL) numbers and myelin as a dynamic cellular compartment perform a key role in the maintenance of neuronal function. Inhibiting white matter (WM) demyelination or promoting remyelination has garnered interest for its potential therapeutic strategy against ischemic stroke. Our previous work has shown that low-intensity pulsed ultrasound (LIPUS) could improve stroke recovery. However, it is unclear whether LIPUS can maintain WM integrity early after stroke or promote late WM repair. This study evaluated the efficacy of LIPUS on WM repair and long-term neurologic recovery after stroke. Male adult C57BL/6 mice underwent a focal cerebral ischemia model and were randomized to receive ultrasound stimulation (30 min once daily for 14 days). The effect of LIPUS on sensorimotor function was assessed by modified neurological severity score, rotarod test, grip strength test, and gait analysis up to 28 days after stroke. We found that ischemic stroke-induced WM damage was severe on day 7 and partially recovered on day 28. LIPUS prevented neuronal and oligodendrocyte progenitor cell (OPC) death during the acute phase of stroke (d7), protected WM integrity, and reduced brain atrophy and tissue damage during the recovery phase (d28). To further confirm the effect of LIPUS on remyelination, we assessed the proliferation and differentiation of OPCs. We found that LIPUS did not increase the number of OPCs (PDGFRα⁺ or NG2⁺), but markedly increased the number of newly produced mature OLs (APC⁺) and myelin protein levels. Mechanistically, LIPUS may promote OL maturation and remyelination by down-regulating the interleukin-17A/Notch1 signaling pathway. In summary, LIPUS can protect OLs and neurons early after stroke and promote long-term WM repair and functional recovery. LIPUS will be a viable strategy for the treatment of ischemic stroke in the future.

Sample barcoding-based multiplex single-cell and single-nucleus sequencing (sc/sn-seq) offers substantial advantages by reducing costs, minimizing batch effects, and identifying artifacts, thereby advancing biological and biomedical research. Despite these benefits, universal sample barcoding has been hindered by challenges such as inhomogeneous expression of tagged biomolecules, limited tagging affinity, and insufficient genetic insertion. To overcome these limitations, we developed Toti-N-Seq, a universal sample multiplex method, by tagging Toti-N-glycan on cell surfaces or nuclear membranes via our engineered streptavidin–Fbs1 GYR variant fusion protein, which could be used not only for sc-seq but also for sn-seq. Instead of targeting lipids or proteins, we focused on targeting the ubiquitous N-glycans found on any species with accessible membranes, which minimizes the exchange between barcoded samples and avoids biased barcoding. Our technology can be broadly applied to multiple species and nearly all eukaryotic cell types, with an overall classification accuracy of 0.969 for sc-seq and of 0.987 for sn-seq. As a demonstration with clinical human peripheral blood mononuclear cells, our Toti-N-Seq achieved rapid one-step sample preparation (<3 min) for easily scaling up while keeping high fidelity of sample ratios, removing artifacts, and detecting rare cell populations (~0.5%). Consequently, we offer a versatile platform suitable for various cell types and applications.

Recent investigations into the mechanisms underlying inflammation have highlighted the pivotal role of immune cells in regulating cardiac pathophysiology. Notably, these immune cells modulate cardiac processes through alternations in intracellular metabolism, including glycolysis and oxidative phosphorylation, whereas the extracellular metabolic environment is changed during cardiovascular disease, influencing function of immune cells. This dynamic interaction between immune cells and their metabolic environment has given rise to the novel concept of “immune metabolism”. Consequently, both the extracellular and intracellular metabolic environment modulate the equilibrium between anti- and pro-inflammatory responses. This regulatory mechanism subsequently influences the processes of myocardial ischemia, cardiac fibrosis, and cardiac remodeling, ultimately leading to a series of cardiovascular events. This review examines how local microenvironmental and systemic environmental changes induce metabolic reprogramming in immune cells and explores the subsequent effects of aberrant activation or polarization of immune cells in the progression of cardiovascular disease. Finally, we discuss potential therapeutic strategies targeting metabolism to counteract abnormal immune activation.

Magnetic continuum robots offer flexibility and controllability, making them promising for minimally invasive surgery (MIS). However, the clinical application of these robots is relatively limited due to the difficulty of integrating miniaturized triaxial force sensors and their single functionality. This paper proposes a multifunctional magnetic catheter robot with magnetic actuation steering and triaxial force-sensing capabilities. The robot features 3 channels at its tip that integrate multi-segmented magnets, a novel triaxial force sensor, and various functional instruments. The sensor is calibrated, demonstrating high sensitivity and accuracy. The steering characterization of the robot confirms that the catheter tip exhibits effective flexibility and force sensing. Palpation experiments involving various hard lumps are performed on porcine kidney, with results verifying that the robot can reliably detect abnormal hard lumps within tissues. Additionally, palpation experiments in bronchial phantom demonstrate the robot's imaging and palpation capabilities for lung nodules with an integrated endoscope. Further, the robot, equipped with biopsy forceps, successfully performs palpation and biopsy functions on simulated stomach polyps, demonstrating its capability for effective tissue manipulation. By leveraging force-sensing capabilities and integrating multifunctional instruments, the robot shows potential for expanded applications in MIS, paving the way for important advancements in clinical procedures.

Peripartum dairy cows commonly experience energy metabolism disorders, which lead to passive culling of postpartum cows and a decrease in milk quality. By using ketosis peripartum dairy cows as a model, this study aims to elucidate the metabolic mechanism of peripartum cows and provide a novel way for managing energy metabolic disorders. From a cohort of 211 cows, we integrated multi-omics data (metagenomics, metabolomics, and transcriptomics) to identify key microbes and then utilized an in vitro rumen fermentation simulation system and ketogenic hepatic cells to validate the potential mechanisms and the effects of postbiotics derived from key microbes. Postpartum cows with metabolic disorders compensate for glucose deficiency through mobilizing muscle proteins, which leads to marked decreases in milk protein content. Concurrently, these cows experience rumen microbiota disturbance, with marked decreases in the concentrations of volatile fatty acids and microbial protein, and the deficiency of alanine (Ala) in microbial protein is correlated with the metabolic disorder phenotype. Metagenomic binning and in vitro fermentation assays reveal that Ruminococcus_E bovis (MAG 189) is enriched in amino acid biosynthesis functions and responsible for Ala synthesis. Furthermore, transcriptomic and metabolomic analyses of the liver in metabolic disorder cows also show impaired amino acid metabolism. Supplementation with Ala can alleviate ketogenesis in liver cell models by activating the gluconeogenesis pathway. This study reveals that Ruminococcus_E bovis is associated with host energy metabolism homeostasis by supplying glucogenic precursors to the liver and suggests the use of Ala as a method for the treatment of energy metabolism disorders in peripartum cows.

Docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) have been proposed to benefit cardiometabolic health. However, the relationship between the intake of DHA and EPA and type 2 diabetes (T2D) risk remains equivocal, and the effects of DHA and EPA on skeletal muscle, the primary organ for glucose metabolism, merit further investigation. Here, we show that habitual fish oil supplementation was associated with a 9% lower T2D risk and significantly interacted with variants at GLUT4 in a prospective cohort of 48,358 people with prediabetes. Muscular metabolome analysis in the animal study revealed that DHA and EPA altered branched-chain amino acids, creatine, and glucose oxidation-related metabolites, concurrently with elevated muscular glycogen synthase and pyruvate dehydrogenase contents that promoted glucose disposal. Further myotube investigation revealed that DHA and EPA promoted muscular GLUT4 translocation by elevating Rab GTPases and target-SNARE expression. Together, DHA and EPA supplementation provides a promising approach for T2D prevention through targeting muscular glucose homeostasis, including enhancing GLUT4 translocation, glycogen synthesis, and aerobic glycolysis.

Microrobotic swarms hold great promise for the revolution of cancer treatment. The coordination of miniaturized microrobots offers a unique approach to treating cancers at the cellular level with enhanced delivery efficiency and environmental adaptability. Prior studies have summarized the design, functionalization, and biomedical applications of microrobotic swarms. The strategies for actuation and motion control of swarms have also been introduced. In this review, we first give a detailed introduction to microrobot swarming. We then explore the design of microrobots and microrobotic swarms specifically engineered for cancer therapy, with a focus on tumor targeting, infiltration, and therapeutic efficacy. Moreover, the latest developments in active delivery methods and imaging techniques that enhance the precision of these systems are discussed. Finally, we categorize and analyze the various cancer therapies facilitated by functional microrobotic swarms, highlighting their potential to revolutionize treatment strategies for different cancer types.

Gecko-inspired dry adhesives have shown great potential in the field of robotics. However, there is still a large gap between current artificial adhesive-based grippers and natural geckos, especially in terms of precise and fast control of adhesion, which is an important capability for robotic gripper systems, since the targets to be gripped may vary in size and weight (including thin, fragile, soft, and deformable), and manipulation must be fast to meet high productivity requirements. Here, we propose a robotic gripper that is able to switch adhesion rapidly (in less than 0.5 s) to grasp and release objects of various sizes and weights (such as glass substrates, fragile silicon wafers, and deformable polyethylene terephthalate films) by mimicking the self-peeling behavior of gecko toe pads. The gripper retains the fast and stable manipulation of the conventional mechanical gripper, which is more reliable and has a higher load capacity than stimulus-responsive switchable adhesives. Systematic experimental and theoretical studies provide insights into the construction and analysis of the self-peeling model and mechanism to identify certain crucial parameters affecting the self-peeling behavior. Furthermore, a strategy for active adhesion control (i.e., precise adhesion modulation) is integrated by introducing a preset peeling angle θ_B, providing the gripper with a quantitative criterion for adjusting the adhesion strength (0 to 82.77 kPa) according to the requirements of practical applications. The gripper has great potential to be an alternative end-operating gripper for robotic systems, opening an avenue for the development of robotic manipulation.

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.

Cyanobacteria play pivotal roles in global biogeochemical cycles and aquatic ecosystems due to their widespread distribution and significant contributions to primary production. Yet, the interactions between cyanobacteria and antibiotics remain unclear. This study revealed that Synechocystis sp., a cyanobacterial species, removed 94.27% of 0.1 mg l⁻¹ chloramphenicol (CAP) through enzyme-mediated degradation. While cytochrome P450 enzymes (CYP450s) were found unnecessary for CAP removal, a gene encoding cyanobacterial nitroreductase was significantly up-regulated (7.85-fold) under CAP exposure. The purified nitroreductase exhibited strong binding affinity to CAP (K _d = 2.9 nM) and a Michaelis constant (K _m) of 104.0 μM. By engineering a bacterial strain with nitroreductase, 94.43% of 0.1 mg l⁻¹ CAP was removed within 2 h. Metagenomic and metatranscriptomic analyses showed that nitroreductase genes and transcripts are globally distributed across diverse microbial phyla. These findings uncover a novel enzyme for CAP degradation and advance sustainable biotechnologies to mitigate antibiotic pollution, addressing critical environmental challenges in aquaculture and other industries globally.

DEAD-box ATPase 10 (DDX10), a prominent RNA-binding protein in the DDX family, has a critical function in cancer progression. Nevertheless, its well-defined mechanisms in oral squamous cell carcinoma (OSCC) are still not well understood. Here, we identify that DDX10 is substantially increased in OSCC, which is positively correlated with poor prognosis and malignant behavior. Mechanistically, we found that DDX10 had physical interaction with Rab27b by undergoing phase separation. Knockdown of DDX10 inhibited Rab27b-mediated exosome secretion and the expression of programmed cell death-ligand 1 (PD-L1) within its contents. Furthermore, knocking down DDX10 could restore the function and infiltration of T cells, hence inhibiting the progression of OSCC. These findings highlight that the oncogenic role of DDX10 in promoting exosomal PD-L1 secretion via phase separation with Rab27b has been preliminarily validated in T cell exhaustion in OSCC. A potential strategy for improving OSCC immunotherapy may involve the inhibition of DDX10.