Abstract Intrinsically magnetic cells naturally occur within organisms and are believed to be linked to iron metabolism and certain cellular functions while the functional significance of this magnetism is largely unexplored. To better understand this property, an approach named Optical Tracking‐based Magnetic Sensor (OTMS) has been developed. This multi‐target tracking system is designed to measure the magnetic moment of individual cells. The OTMS generates a tunable magnetic field and induces movement in magnetic cells that are subsequently analyzed through a learning‐based tracking‐by‐detection system. The magnetic moment of numerous cells can be calculated simultaneously, thereby providing a quantitative tool to assess cellular magnetic properties within populations. Upon deploying the OTMS, a stable population of magnetic cells in human peripheral monocytes is discovered. Further application in the analysis of clinical blood samples reveals an intriguing pattern: the proportion of magnetic monocytes differs significantly between systemic lupus erythematosus (SLE) patients and healthy volunteers. This variation is positively correlated with disease activity, a trend not observed in patients with rheumatoid arthritis (RA). The study, therefore, presents a new frontier in the investigation of the magnetic characteristics of naturally occurring magnetic cells, opening the door to potential diagnostic and therapeutic applications that leverage cellular magnetism.
Vaccine Delivery In article 2301232, Jingyi Sheng, Fang Yang, Ning Gu, and co-workers introduce a magnetic-responsive cancer vaccine, employing antigen-loaded magnetic liposomes (Ag-MLs), for active lymph node targeting. These liposomes, containing mouse melanoma lysate, iron oxide nanoparticles, and CpG adjuvant, display enhanced accumulation in lymph nodes when magnetically guided and demonstrate significant enhancement in anti-tumor immunity in a mouse model. This approach provides potential new avenues for developing effective tumor vaccines.
Therapeutic cancer vaccines offer the greatest advantage of enhancing antigen-specific immunity against tumors, particularly for immunogenic tumors, such as melanoma. However, clinical responses remain unsatisfactory, primarily due to inadequate T cell priming and the development of acquired immune tolerance. A major obstacle lies in the inefficient uptake of antigen by peripheral dendritic cells (DCs) and their migration to lymph nodes for antigen presentation. In this context, the magnetic delivery of antigen-loaded magnetic liposomes (Ag-MLs) to actively target lymph node, is proposed. These magnetic responsive liposomes contain soluble mouse melanoma lysate and iron oxide nanoparticles in the core, along with the immunostimulatory adjuvant CpG-1826 incorporated into the lipid bilayer. When applied through magnetic targeting in the mouse melanoma model, Ag-MLs accumulate significantly in the target lymph nodes. This accumulation results in increased population of active DCs in lymph nodes and cytotoxic T lymphocytes (CTLs) within tumors, correlating with effective tumor growth inhibition. Overall, this study demonstrates the potential of magnetic targeting as an effective strategy for delivering cancer vaccines and activating the immune response, offering a novel platform for cancer immunotherapies.
Abstract The imaging field of view (FOV) of lensless microscope is consistent with the size of image sensor in use, enabling the observation of sample areas larger than 20 mm 2 . Combined with high-performance and even super-resolution phase retrieval algorithms, micron and sub-micron resolution can be achieved, ultimately realizing wide-field and high-resolution imaging performance simultaneously. However, high-throughput lensless imaging poses significant challenges in terms of rapid data acquisition and large-scale phase retrieval. Additionally, when observing biological samples over a large FOV, the focus plane often exhibits inconsistency among different regions, necessitating further parameter calibration. In this study, we propose a fast acquisition and efficient reconstruction strategy for coherent lensless imaging based on a multi-height imaging model. Multiple measurements are manually modulated using an axial translation stage and continuously captured by an image sensor, facilitating rapid data acquisition within seconds and requiring no hardware synchronization. The efficiency and accuracy of phase retrieval are enhanced through precise parameter calibration algorithms, as well as techniques such as region-wise parallel computing and region-wise auto-focusing. Experimental results demonstrate 7.4×5.5 mm 2 FOV and 1.55 μm half-pitch resolution imaging of human skin and lung tumor sections with region-wise focusing, requiring only an approximate 0.5-s acquisition time and 44-s reconstruction time. Furthermore, by incorporating the pixel super-resolution principle, the 1.10 μm half-pitch imaging resolution is demonstrated in full-FOV peripheral blood smears without additional data required, beneficial to the identification of hollow shape and segmentation of blood cells.
Abstract Lensless microscopy provides a wide field of view (FOV) determined by the image sensor size, allowing visualization of large sample areas. Coupled with advanced and even pixel super‐resolution phase retrieval algorithms, it can achieve resolutions up to the sub‐micron level, enabling both large‐FOV and high‐resolution imaging. However, high‐throughput lensless imaging encounters challenges in rapid data acquisition and large‐scale phase retrieval. Furthermore, when examining biological samples over a large FOV, focal plane inconsistencies often emerge among distinct regions. This study introduces a fast acquisition and efficient reconstruction method for coherent lensless imaging. Multiple measurements are manually modulated using an axial translation stage and sequentially captured by an image sensor, requiring no hardware synchronization. Optical parameter calibration, region‐wise auto‐focusing, and region‐wise phase retrieval algorithms are integrated to establish a general parallel computing framework for rapid, efficient, and high‐throughput lensless imaging. Experimental results demonstrate a 7.4 mm × 5.5 mm FOV and 1.38 µm half‐pitch resolution imaging of human skin and lung tumor sections with region‐wise focusing, requiring ≈0.5‐s acquisition time and 17‐s reconstruction time. By incorporating pixel super‐resolution, a 0.98 µm half‐pitch resolution is achieved in full‐FOV peripheral blood smears without additional data required, advantageous for discerning hollow shapes and segmenting blood cells.
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