Chemical & Biomedical Imaging最新文献

The development of highly efficient photocatalysts for the utilization of solar energy has been extensively explored in the past few decades. Due to the strong light-matter interaction in plasmonic nanostructures, the combination of plasmonic nanomaterials with other poor light-absorbing catalytic materials presents a promising strategy for expanding the scope of light-driven heterogeneous catalysis. Although the photocatalytic performance of these hybridized structures has been greatly improved, how to regulate the charge carrier transfer efficiency in these heterostructures is still ambiguous. In this work, we prepared a metal-semiconductor core-shell heterostructure through precisely coating a thin layer of CdS onto the gold nanocube (AuNC) surface. A noticeable increase in photoelectrical response from the core-shell structure relative to either AuNCs or pure CdS nanoparticles can be observed in photocurrent generation efficiency, electron lifetime, and charge separation efficiency. More importantly, the photoelectrical responses can be well regulated by changing the semiconductor shell thickness on the nanocube surface. An optimum shell thickness for the light-driven photocatalytic reaction is around 8.3 nm, which exhibits the highest charge carrier transfer efficiency and hot-electron generation rate.

High-resolution single-cell spatial proteomics offers transformative insights into cellular diversity, architecture, interactions, and functions within complex biological systems. However, the existing multiplexed protein imaging platforms face challenges such as limited detection sensitivity, constrained target multiplexing capacity, or technically demanding. To address these issues, we report a highly sensitive spatial proteomics approach, using multicolor cleavable fluorescent tyramide and off-the-shelf antibodies. This method employs horseradish peroxidase (HRP) to enzymatically deposit distinct fluorophores to stain varied target proteins. Through reiterative cycles of target labeling, fluorescence imaging, and fluorophore cleavage, this approach allows numerous proteins profiled at the optical resolution in the same specimen. Utilizing this technique, we quantified 38 proteins within a human formalin-fixed paraffin-embedded (FFPE) tonsil tissue, which represents the highest target multiplexing capacity achieved to date using tyramide signal amplification (TSA) methods. Analysis of ∼500,000 individual cells in the same tissue revealed distinct cell clusters based on their protein expression profiles and spatial microenvironment. By mapping the cells back to their original tissue locations, we observed specific tissue subregions are composed of unique cell clusters. Furthermore, we also studied the cell-cell interactions and found the cells from the same cluster often showed strong association, while the cells in the varied clusters usually avoided contact.

Quantifying the shape and stiffness of extracellular vesicles (EVs) is essential for understanding their biophysical properties and roles in intercellular communication. However, achieving single-particle resolution under physiological conditions remains a significant challenge. Here, we introduce an approach that integrates single-molecule diffusivity mapping (SMdM) with diffusion models for spherical and discoidal shapes to quantify the geometric and mechanical properties of individual liposomes and EVs in aqueous solution. Our findings identify charged lipids and cholesterol as critical factors that enhance liposome stiffness, driving their shapes closer to spheres. Applying this method to EVs reveals that those derived from tumor cells exhibit lower stiffness compared to EVs from normal cells, consistent with the biomechanical characteristics of their parent cells. This rapid, high-throughput strategy for characterizing the shape and stiffness of single EVs in aqueous solution offers promising applications in cancer biomarker discovery and the development of EV-based therapeutics.

Molecular imaging has emerged as a transformative tool in cancer diagnosis, enabling the visualization of biological processes at the cellular and molecular levels. Aptamers, single-stranded oligonucleotides with high affinity and specificity for target molecules, have gained significant attention as versatile probes for molecular imaging due to their unique properties, including small size, ease of modification, low immunogenicity, and rapid tissue penetration. This review explores the integration of aptamers with various imaging agents to enhance cancer diagnosis and therapy. Aptamer-based imaging probes offer high sensitivity and real-time visualization of tumor markers. Aptamer-based fluorescence probes and aptamer-conjugated magnetic resonance imaging (MRI) probes, including gadolinium-based contrast agents, improve tumor targeting and imaging resolution. Additionally, aptamers have been utilized in single-photon emission computed tomography (SPECT) and positron emission tomography (PET) imaging to enhance the specificity of radiotracers for cancer detection. Furthermore, aptamer-targeted ultrasound and computed tomography (CT) imaging demonstrate the potential for noninvasive and precise tumor localization. By leveraging the unique advantages of aptamers, these imaging strategies not only improve diagnostic accuracy but also pave the way for image-guided cancer therapies. This review highlights the significant role of aptamers in advancing molecular imaging and their potential to revolutionize cancer diagnosis and treatment.

MRI is an indispensable diagnostic tool in modern medicine; however, understanding the molecular-level processes governing NMR relaxation of water in the presence of MRI contrast agents remains a challenge, hindering the molecular-guided development of more effective contrast agents. By using quantum-based polarizable force fields, the first-of-its-kind molecular dynamics (MD) simulations of Gadobutrol are reported where the ¹H NMR longitudinal relaxivity r ₁ of the aqueous phase is determined without any adjustable parameters. The MD simulations of r ₁ dispersion (i.e., frequency dependence) show good agreement with measurements at frequencies of interest in clinical MRI. Importantly, the simulations reveal key insights into the molecular level processes leading to r ₁ dispersion by decomposing the NMR dipole-dipole autocorrelation function G(t) into a discrete set of molecular modes, analogous to the eigenmodes of a quantum harmonic oscillator. The molecular modes reveal important aspects of the underlying mechanisms governing r ₁, such as its multiexponential nature and the importance of the second eigenmodal decay. By simply analyzing the MD trajectories on a parameter-free approach, the Gadobutrol simulations show that the outer-shell water contributes ∼50% of the total relaxivity r ₁ compared to the inner-shell water, in contrast to simulations of (nonchelated) gadolinium-aqua where the outer shell contributes only ∼15% of r ₁. The deviation between simulations and measurements of r ₁ below clinical MRI frequencies is used to determine the low-frequency electron-spin relaxation time for Gadobutrol, in good agreement with independent studies.

Solvents are known to affect the product yield in photoredox catalysis. Previously, Efforts have been made to understand how solvents affect photoredox catalysis at the ensemble level. However, the underlying mechanism has not yet been fully elucidated. Here, we studied the behavior of single photoredox catalysts in a variety of solvents by using single-molecule fluorescence imaging. By analyzing the trajectories of single eosin Y (EY), we found that the solvent could affect photoredox catalysis both physically and chemically. Evidence of the long-lived triplet excited state of the photoredox catalyst and redox active impurities was found. These two factors may play important roles in photoredox catalysis and thus need to be given attention.

Accurate and automated segmentation of 3D biomedical images is a sophisticated imperative in clinical diagnosis, imaging-guided surgery, and prognosis judgment. Although the burgeoning of deep learning technologies has fostered smart segmentators, the successive and simultaneous garnering global and local features still remains challenging, which is essential for an exact and efficient imageological assay. To this end, a segmentation solution dubbed the mixed parallel shunted transformer (MPSTrans) is developed here, highlighting 3D-MPST blocks in a U-form framework. It enabled not only comprehensive characteristic capture and multiscale slice synchronization but also deep supervision in the decoder to facilitate the fetching of hierarchical representations. Performing on an unpublished colon cancer data set, this model achieved an impressive increase in dice similarity coefficient (DSC) and a 1.718 mm decease in Hausdorff distance at 95% (HD95), alongside a substantial shrink of computational load of 56.7% in giga floating-point operations per second (GFLOPs). Meanwhile, MPSTrans outperforms other mainstream methods (Swin UNETR, UNETR, nnU-Net, PHTrans, and 3D U-Net) on three public multiorgan (aorta, gallbladder, kidney, liver, pancreas, spleen, stomach, etc.) and multimodal (CT, PET-CT, and MRI) data sets of medical segmentation decathlon (MSD) brain tumor, multiatlas labeling beyond cranial vault (BCV), and automated cardiac diagnosis challenge (ACDC), accentuating its adaptability. These results reflect the potential of MPSTrans to advance the state-of-the-art in biomedical imaging analysis, which would offer a robust tool for enhanced diagnostic capacity.

Defect-mediated energy transfer (EnT) is a radiative process that occurs between donor defect states in the forbidden bandgap of semiconductor nanocrystals (NCs) and dye molecules bound to their surfaces. The EnT efficiency depends on the number of dye molecules attached to each NC, the donor–acceptor distance, and the dipole orientation factor between the donor and acceptor, all of which vary across all individual NCs in a sample. While ensemble-level fluorescence spectroscopy measurements have provided average values for donor–acceptor distances, dye-to-NC ratios, and EnT rate constants, questions remain about the impact of donor/acceptor heterogeneity on observed EnT efficiencies. Notably, ensemble-level measurements cannot distinguish between bare NCs and EnT-active versus inactive NC/dye pairs in the same sample batch, limiting the ability to design systems with 100% EnT efficiency. To address this, we studied defect-mediated EnT between AlexaFluor 555 dye acceptors chemically bound to ZnO NC donors at the level of single molecules and single NCs. Interestingly, 20% of bound NC/dye pairs are EnT-inactive, likely contributing to residual defect photoluminescence (PL) observed in ensemble-level measurements and reducing overall EnT efficiency. Single particle-level ZnO defect PL and acceptor fluorescence trajectories exhibited distinct microfluctuations, which are absent in bare ZnO NCs. We hypothesized that our observations can be explained with a competitive dye fluorescence quenching pathway, possibly due to charge transfer between the excited state dye and the ZnO NC. Numerical simulations of single-molecule PL traces for this scenario produced microfluctuations consistent with the experimental results. These findings highlight the impact of sample heterogeneity on EnT processes and provide insights for designing light-harvesting systems with optimized EnT efficiency.

Carbon dots (CDs) have emerged as promising nanomaterials for bioimaging and stress monitoring due to their unique optical and functional properties. CDs were synthesized using citric acid and o-phenylenediamine via microwave-assisted heating, named as CP-CDs. High-resolution transmission electron microscopy observed an average particle size of 3.65 ± 0.40 nm with graphitic cores. Raman spectroscopy and Fourier transform infrared spectroscopy confirmed diverse functional groups. The CDs exhibited excitation-dependent fluorescence with a peak emission at 432 nm, a high quantum yield of 54.91%, and a fluorescence lifetime of 9.50 ± 0.15 ns, making them highly suitable for bioimaging. Confocal microscopy demonstrated tissue-specific localization in lettuce plant cells. In stem cells, CP-CDs predominantly targeted mitochondria, confirmed by a colocalization with Mito-Tracker Red. In contrast, leaf cells showed selective accumulation at the stomatal openings. Under salt- and heat-induced stress, stem cells exhibited an increase in mitochondrial fluorescence, indicating stress-responsive interactions, whereas leaf cells maintained consistent stomatal localization. Further, enhanced fluorescence from chloroplasts under stress conditions suggested synergistic effects with chlorophyll. Also, stress conditions caused CP-CDs to accumulate at the cell boundaries in stem cells, highlighting their sensitivity to stress-induced changes. These findings demonstrate the optical properties, tissue-specific uptake, and organelle-level localization of CP-CDs, underlining their potential for bioimaging, stress detection, and targeted delivery systems in plants.