In this study, we developed a novel theranostic nanomedicine formulation that integrates multimodal imaging with controlled drug release in reactive oxygen species (ROS)-rich microenvironments. A fluorinated oxalate compound (FOC) was synthesized through a one-step condensation reaction between 1,1,1,3,3,3-hexafluoro-2-propanol and oxalyl chloride, characterized by ¹H, ¹³C, and ¹⁹F NMR spectroscopy. The FOC and luminophore-incorporated nanomedicine formulations reacted rapidly with hydrogen peroxide via the peroxyoxalate chemiluminescence (POCL) mechanism, producing strong chemiluminescence and inducing a notable 19-fold increase in ratiometric ¹⁹F NMR signal upon conversion to fluorinated alcohol (FAH), demonstrating promising potential for high-contrast ¹⁹F MRI in deep tissue. Following ROS stimulation, the chemical conversion from hydrophobic FOC to hydrophilic FAH led to the degradation of the nanomedicines, facilitating payload release. In vitro experiments with A-431 cancer cells under hypoxic conditions confirmed ROS-responsive drug release, evidenced by enhanced fluorescence from model luminophores. Additionally, doxorubicin-loaded FOC nanomedicines reduced cell viability to 32% under hypoxia while remaining non-toxic in normoxic conditions. These results indicate that FOC-based nanomedicine formulations provide a promising platform for combined chemiluminescence and ¹⁹F MRI with targeted therapeutic efficacy in ROS-rich inflammatory and cancerous tissues.

This review provides an in-depth examination of the critical functions served by the Field Free Point (FFP) and Field Free Line (FFL) within Magnetic Particle Imaging (MPI), particularly highlighting their importance for improving imaging accuracy and resolution. Basic FFP and FFL configurations and experimental conditions are presented first, followed by an evaluation of their impact on MPI protocol optimization. It delves deeper into the synthesis and functionalization of magnetic nanoparticles, highlighting their uses in targeted MPI and theragnostic. A comparison of FFP and FFL designs is presented to emphasize their benefits, limits, and possible contributions to trajectory optimization. The analysis continues with prospective future research areas that try to address existing challenges while improving MPI technology for both medical diagnostics and industrial applications.

Accurate quantification of wound closure in cell migration assays is crucial yet challenging. Still, existing methods often underperform due to omitting cell detection within the wound area, resulting in biased outcomes. We developed the CSMA standalone and ImageJ-compatible tool, which utilizes advanced image processing techniques, including contrast enhancement, edge detection, and morphological operations, to precisely identify and quantify cells in the wound region. CSMA offers user-friendly features and adjustable parameters to accommodate different imaging conditions, ensuring robust performance across diverse experimental setups. Validation against conventional tools confirms CSMA’s superior ability to delineate wound boundaries and provide accurate estimations of area and width at every time point. As applied to SW480-ADH colon cancer cells treated with various compounds, CSMA proves valuable in biomedical research. CSMA represents a significant advancement in wound healing assay analysis, providing researchers with a simple and reliable tool for studying cell migration dynamics with enhanced precision and reproducibility. CSMA is available as a standalone and ImageJ-compatible tool with its source code at https://github.com/AminaSagymbayeva/CSMA_WoundHealing.

Accurate quantification of wound closure in cell migration assays is crucial yet challenging. Still, existing methods often underperform due to omitting cell detection within the wound area, resulting in biased outcomes. To overcome this limitation, we developed the CSMA plugin for ImageJ. CSMA utilizes advanced image processing techniques, including contrast enhancement, edge detection, and morphological operations, to precisely identify and quantify cells in the wound region. The plugin offers user-friendly features and adjustable parameters to accommodate different imaging conditions, ensuring robust performance across diverse experimental setups. Validation against conventional tools confirms CSMA’s superior ability to delineate wound boundaries and provide accurate estimations of area and width at every time point. As applied to SW480-ADH colon cancer cells treated with various compounds, CSMA proves valuable in biomedical research. It represents a significant advancement in wound healing assay analysis, providing researchers with a simple and reliable tool for studying cell migration dynamics with enhanced precision and reproducibility. CSMA is available as an ImageJ plugin and source code at https://github.com/AminaSagymbayeva/CSMA_WoundHealing .