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Observing subcellular structural dynamics in living cells has become the goal of super-resolution (SR) fluorescence microscopy. Among typical SRM techniques, structured illumination microscopy (SIM) stands out for its fast imaging speed and low photobleaching. However, 2D-SIM requires nine raw images to obtain a SR image, leading to undesirable artifacts in the fast dynamics of live-cell imaging. In this paper, we propose a single-frame structured illumination microscopy (SF-SIM) method based on deep learning that achieves SR imaging using only a single image modulated by a hexagonal lattice pattern. The SF-SIM method used the prior knowledge to complete the structure enhancement of SR images in the spatial domain and the expansion of the Fourier spectrum through deep learning, achieving the same resolution as conventional 2D-SIM. Temporal resolution is improved nine times, and photobleaching is reduced by 2.4 times compared to conventional 2D-SIM. Based on this, we observed the fast dynamics of multiple subcellular structures and the dynamic interaction of two organelles. The SF-SIM methods provide a powerful tool for live-cell imaging.

There exists a bidirectional relationship between oral health and general well-being, with an imbalance in oral symbiotic flora posing a threat to overall human health. Disruptions in the commensal flora can lead to oral diseases, while systemic illnesses can also impact the oral cavity, resulting in the development of oral diseases and disorders. Porphyromonas gingivalis and Fusobacterium nucleatum, known as pathogenic bacteria associated with periodontitis, play a crucial role in linking periodontitis to accompanying systemic diseases. In periodontal tissues, these bacteria, along with their virulence factors, can excessively activate the host immune system through local diffusion, lymphatic circulation, and blood transmission. This immune response disruption contributes to an imbalance in osteoimmune mechanisms, alveolar bone resorption, and potential systemic inflammation. To restore local homeostasis, a deeper understanding of microbiota–host interactions and the immune network phenotype in local tissues is imperative. Defining the immune network phenotype in periodontal tissues offers a promising avenue for investigating the complex characteristics of oral plaque biofilms and exploring the potential relationship between periodontitis and associated systemic diseases. This review aims to provide an overview of the mechanisms underlying Porphyromonas gingivalis- and Fusobacterium nucleatum-induced alveolar bone resorption, as well as the immunophenotypes observed in host periodontal tissues during pathological conditions.

Increasing bacterial infections and growing resistance to available drugs pose a serious threat to human health and the environment. Although antibiotics are crucial in fighting bacterial infections, their excessive use not only weakens our immune system but also contributes to bacterial resistance. These negative effects have caused doctors to be troubled by the clinical application of antibiotics. Facing this challenge, it is urgent to explore a new antibacterial strategy. MXene has been extensively reported in tumor therapy and biosensors due to its wonderful performance. Due to its large specific surface area, remarkable chemical stability, hydrophilicity, wide interlayer spacing, and excellent adsorption and reduction ability, it has shown wonderful potential for biopharmaceutical applications. However, there are few antimicrobial evaluations on MXene. The current antimicrobial mechanisms of MXene mainly include physical damage, induced oxidative stress, and photothermal and photodynamic therapy. In this paper, we reviewed MXene-based antimicrobial composites and discussed the application of MXene in bacterial infections to guide further research in the antimicrobial field.

As a supplement to optical super-resolution microscopy techniques, computational super-resolution methods have demonstrated remarkable results in alleviating the spatiotemporal imaging trade-off. However, they commonly suffer from low structural fidelity and universality. Therefore, we herein propose a deep-physics-informed sparsity framework designed holistically to synergize the strengths of physical imaging models (image blurring processes), prior knowledge (continuity and sparsity constraints), a back-end optimization algorithm (image deblurring), and deep learning (an unsupervised neural network). Owing to the utilization of a multipronged learning strategy, the trained network can be applied to a variety of imaging modalities and samples to enhance the physical resolution by a factor of at least 1.67 without requiring additional training or parameter tuning. Given the advantages of high accessibility and universality, the proposed deep-physics-informed sparsity method will considerably enhance existing optical and computational imaging techniques and have a wide range of applications in biomedical research.

Smoking is a pathogenic factor for pulmonary hypertension (PH). Our previous study showed that serum miR-21 levels are elevated in smokers. miR-21 is considered as engaged in the PH process; however, its mechanisms remain unclear. In this investigation, we found that in the lung tissue of smoking-induced PH patients, the levels of miR-21 and aging markers (p21 and p16) were upregulated, and the function of pulmonary vascular endothelial cells was also impaired. Exposure of mice to cigarette smoke (CS) for four months caused similar changes in lung tissues and increased pulmonary arterial pressure, which were attenuated by knockout of miR-21. Further, human umbilical vein endothelial cells (HUVECs) exposed to cigarette smoke extract (CSE) revealed upregulation of miR-21 levels, depression of PTEN, activation of PI3K/AKT/mTOR signaling, an increase in senescence indexes, and enhanced dysfunction. Inhibiting miR-21 overexpression reversed the PTEN-mTOR signaling pathway and prevented senescence and dysfunction of HUVECs. In sum, our data indicate that miR-21-mediated endothelial senescence and dysfunction are involved in CS-induced PH through the activation of PI3K/AKT/mTOR signaling, which suggests that selective miR-21 inhibition offers the potential to attenuate PH.