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.