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.

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.

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.

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.

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.

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.

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.

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.

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.