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Molecular imaging of viral pathogenesis and opportunities for the future

Molecular imaging is used in clinical and research settings. Since tools to study viral pathogenesis longitudinally and systemically are limited, molecular imaging is an attractive and largely unexplored tool. This review discusses molecular imaging probes and techniques for studying viruses, particularly those currently used in oncology that are applicable to virology. Expanding the repertoire of probes to better detect viral disease may make imaging even more valuable in (pre-)clinical settings.

Robust self-supervised denoising of voltage imaging data using CellMincer

Voltage imaging is a powerful technique for studying neuronal activity, but its effectiveness is often constrained by low signal-to-noise ratios (SNR). Traditional denoising methods, such as matrix factorization, impose rigid assumptions about noise and signal structures, while existing deep learning approaches fail to fully capture the rapid dynamics and complex dependencies inherent in voltage imaging data. Here, we introduce CellMincer, a novel self-supervised deep learning method specifically developed for denoising voltage imaging datasets. CellMincer operates by masking and predicting sparse pixel sets across short temporal windows and conditions the denoiser on precomputed spatiotemporal auto-correlations to effectively model long-range dependencies without large temporal contexts. We developed and utilized a physics-based simulation framework to generate realistic synthetic datasets, enabling rigorous hyperparameter optimization and ablation studies. This approach highlighted the critical role of conditioning on spatiotemporal auto-correlations, resulting in an additional 3-fold SNR gain. Comprehensive benchmarking on both simulated and real datasets, including those validated with patch-clamp electrophysiology (EP), demonstrates CellMincer’s state-of-the-art performance, with substantial noise reduction across the frequency spectrum, enhanced subthreshold event detection, and high-fidelity recovery of EP signals. CellMincer consistently outperforms existing methods in SNR gain (0.5–2.9 dB) and reduces SNR variability by 17–55%. Incorporating CellMincer into standard workflows significantly improves neuronal segmentation, peak detection, and functional phenotype identification, consistently surpassing current methods in both SNR gain and consistency.

In vivo surface-enhanced Raman scattering techniques: nanoprobes, instrumentation, and applications

Surface-enhanced Raman scattering (SERS) has emerged as a powerful tool in various biomedical applications, including in vivo imaging, diagnostics, and therapy, largely due to the development of near-infrared (NIR) active SERS substrates. This review provides a comprehensive overview of SERS-based applications in vivo, focusing on key aspects such as the design considerations for SERS nanoprobes and advancements in instrumentation. Topics covered include the development of NIR SERS substrates, Raman label compounds (RLCs), protective coatings, and the conjugation of bioligands for targeted imaging and therapy. The review also discusses microscope-based configurations such as scanning, widefield imaging, and fiber-optic setups. Recent advances in using SERS nanoprobes for in vivo sensing, diagnostics, biomolecule screening, multiplex imaging, intraoperative guidance, and multifunctional cancer therapy are highlighted. The review concludes by addressing challenges in the clinical translation of SERS nanoprobes and outlines future directions, emphasizing opportunities for advancing biomedical research and clinical applications.

Airborne optical imaging technology: a road map in CIOMP

Airborne optical imaging can flexibly obtain the intuitive information of the observed scene from the air, which plays an important role of modern optical remote sensing technology. Higher resolution, longer imaging distance, and broader coverage are the unwavering pursuits in this research field. Nevertheless, the imaging environment during aerial flights brings about multi-source dynamic interferences such as temperature, air pressure, and complex movements, which forms a serious contradiction with the requirements of precision and relative staticity in optical imaging. As the birthplace of Chinese optical industry, the Changchun Institute of Optics, Fine Mechanics and Physics (CIOMP) has conducted the research on airborne optical imaging for decades, resulting in rich innovative achievements, completed research conditions, and exploring a feasible development path. This article provides an overview of the innovative work of CIOMP in the field of airborne optical imaging, sorts out the milestone nodes, and predicts the future development direction of this discipline, with the aim of providing inspiration for related research.

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