Chemical & Biomedical Imaging最新文献

The development of peptide-based, radiometal-labeled PET imaging agents has seen an increase in attention due to the favorable properties the peptide backbone exhibits. These include high selectivity and affinity to proteins and cells directly linked to various types of cancers. In addition, rapid clearance from circulation and low toxicity allow for unique approaches to engineering a viable peptide-based imaging agent. Utilizing peptides as the backbone allows for various modifications to improve metabolic stability, target cell affinity, and image quality and imaging capabilities and reduce toxicity. Select radiolabeled peptides have already been FDA approved, with many more in late-stage trials. This review summarizes the current state of the radiometal-labeled PET peptide imaging field as well as explores methods used by researchers to modify peptides, concluding with a look at the future of peptide-based therapy and diagnostics.

The development of peptide-based, radiometal-labeled PET imaging agents has seen an increase in attention due to the favorable properties the peptide backbone exhibits. These include high selectivity and affinity to proteins and cells directly linked to various types of cancers. In addition, rapid clearance from circulation and low toxicity allow for unique approaches to engineering a viable peptide-based imaging agent. Utilizing peptides as the backbone allows for various modifications to improve metabolic stability, target cell affinity, and image quality and imaging capabilities and reduce toxicity. Select radiolabeled peptides have already been FDA approved, with many more in late-stage trials. This review summarizes the current state of the radiometal-labeled PET peptide imaging field as well as explores methods used by researchers to modify peptides, concluding with a look at the future of peptide-based therapy and diagnostics.

Milk-derived exosomes are widely used for diagnosis, delivery, imaging, and theranostic applications. Near-Infrared (NIR) based fluorescence bioimaging is an attractive and safer technique that is used for clinical applications. However, almost all NIR imaging agents tend to have poor photostability, short half-life, nonspecific protein binding, and concentration-dependent aggregation(s). Therefore, there is an unmet clinical need to develop newer and safer modalities to package and deliver NIR imaging agents. Bovine milk exosomes are natural, biocompatible, safe, and efficient nanocarriers that facilitate the delivery of micro- and macromolecules. Herein, we developed an exosome-based NIR dye loaded nanoimaging formulation that offers improved solubility and photostability of NIR dye. Following the acetic acid based extracellular vesicle (EV) treatment method, we extracted the bovine milk exosomes from a variety of pasteurized grade milk. The EVs were screened for their physicochemical properties such as particle size and concentration and zeta potential. The stability of these exosomes was also determined under different conditions, including storage temperatures, pH, and salt concentrations. Next, indocyanine green, a model NIR dye was loaded into these exosomes (Exo-Glow) via a sonication method and further assessed for their improved fluorescence intensity and photostability using an IVIS imaging system. Initial screening suggested that size of the selected bovine milk exosomes was ∼100-135 nm with an average particle concentration of 5.8 × 10² particles/mL. Exo-Glow further demonstrated higher fluorescence intensity in cancer cells and tissues when compared to free dye. These results showed that Exo-Glow has the potential to serve as a safer NIR imaging tool for cancer cells/tissues.

Milk-derived exosomes are widely used for diagnosis, delivery, imaging, and theranostic applications. Near-Infrared (NIR) based fluorescence bioimaging is an attractive and safer technique that is used for clinical applications. However, almost all NIR imaging agents tend to have poor photostability, short half-life, nonspecific protein binding, and concentration-dependent aggregation(s). Therefore, there is an unmet clinical need to develop newer and safer modalities to package and deliver NIR imaging agents. Bovine milk exosomes are natural, biocompatible, safe, and efficient nanocarriers that facilitate the delivery of micro- and macromolecules. Herein, we developed an exosome-based NIR dye loaded nanoimaging formulation that offers improved solubility and photostability of NIR dye. Following the acetic acid based extracellular vesicle (EV) treatment method, we extracted the bovine milk exosomes from a variety of pasteurized grade milk. The EVs were screened for their physicochemical properties such as particle size and concentration and zeta potential. The stability of these exosomes was also determined under different conditions, including storage temperatures, pH, and salt concentrations. Next, indocyanine green, a model NIR dye was loaded into these exosomes (Exo-Glow) via a sonication method and further assessed for their improved fluorescence intensity and photostability using an IVIS imaging system. Initial screening suggested that size of the selected bovine milk exosomes was ∼100–135 nm with an average particle concentration of 5.8 × 10² particles/mL. Exo-Glow further demonstrated higher fluorescence intensity in cancer cells and tissues when compared to free dye. These results showed that Exo-Glow has the potential to serve as a safer NIR imaging tool for cancer cells/tissues.

Photodynamic therapy (PDT) has long been receiving increasing attention for the minimally invasive treatment of cancer. The performance of PDT depends on the photophysical and biological properties of photosensitizers (PSs). The always-on fluorescence signal of conventional PSs makes it difficult to real-time monitor phototherapeutic efficacy in the PDT process. Therefore, functional PSs with good photodynamic therapy effect and self-reporting properties are highly desired. Here, two nonemissive iridium(III) solvent complexes, [(dfppy)₂Ir(DMSO)]Cl (Ir-DMSO, dfppy = 2,4-difluorophenyl)pyridine, DMSO = dimethyl sulfoxide) and [(dfppy)₂Ir(ACN)]Cl (Ir-ACN, ACN = acetonitrile) as PSs, were synthesized. Both of them exhibit intense high-energy absorption bands, low photoluminescence (PL) emission, and low dark toxicity. Thanks to the lower dark toxicity of Ir-DMSO, we chose it as a PS for further PDT. In this work, Ir-DMSO functions as a specific PL "signal on" PS for self-reporting therapeutic efficacy during its own PDT process. Colocalization experiments indicated that Ir-DMSO accumulated in the endoplasmic reticulum and mitochondria. Under light irradiation, Ir-DMSO not only exhibited the ability to kill cancer cells but also presented a "signal on" PL response toward cell death. During Ir-DMSO-induced PDT, cell death modality was further investigated and immunogenic cell death was revealed, in which main hallmarks, including ROS generation, upregulation of surface-exposed calreticulin, high-mobility group box 1, and adenosine triphosphate secretion, were observed. Thanks to the specific coordination reaction between Ir-DMSO and histidine (His)/His-containing proteins, the phototherapeutic efficacy can be monitored in real time without other signal probes. This work provides a new and promising strategy for the development of PSs with self-reporting ability, which is of great importance for imaging-guided PDT.

Photodynamic therapy (PDT) has long been receiving increasing attention for the minimally invasive treatment of cancer. The performance of PDT depends on the photophysical and biological properties of photosensitizers (PSs). The always-on fluorescence signal of conventional PSs makes it difficult to real-time monitor phototherapeutic efficacy in the PDT process. Therefore, functional PSs with good photodynamic therapy effect and self-reporting properties are highly desired. Here, two nonemissive iridium(III) solvent complexes, [(dfppy)₂Ir(DMSO)]Cl (Ir-DMSO, dfppy = 2,4-difluorophenyl)pyridine, DMSO = dimethyl sulfoxide) and [(dfppy)₂Ir(ACN)]Cl (Ir-ACN, ACN = acetonitrile) as PSs, were synthesized. Both of them exhibit intense high-energy absorption bands, low photoluminescence (PL) emission, and low dark toxicity. Thanks to the lower dark toxicity of Ir-DMSO, we chose it as a PS for further PDT. In this work, Ir-DMSO functions as a specific PL “signal on” PS for self-reporting therapeutic efficacy during its own PDT process. Colocalization experiments indicated that Ir-DMSO accumulated in the endoplasmic reticulum and mitochondria. Under light irradiation, Ir-DMSO not only exhibited the ability to kill cancer cells but also presented a “signal on” PL response toward cell death. During Ir-DMSO-induced PDT, cell death modality was further investigated and immunogenic cell death was revealed, in which main hallmarks, including ROS generation, upregulation of surface-exposed calreticulin, high-mobility group box 1, and adenosine triphosphate secretion, were observed. Thanks to the specific coordination reaction between Ir-DMSO and histidine (His)/His-containing proteins, the phototherapeutic efficacy can be monitored in real time without other signal probes. This work provides a new and promising strategy for the development of PSs with self-reporting ability, which is of great importance for imaging-guided PDT.

Hyperspectral photothermal mid-infrared spectroscopic imaging (HP-MIRSI) is an emerging technology with promising applications in cervical cancer diagnosis and quantitative, label-free histopathology. This study pioneers the application of HP-MIRSI to the evaluation of clinical cervical cancer tissues, achieving excellent tissue type segmentation accuracy of over 95%. This achievement stems from an integrated approach of optimized data acquisition, computational data reconstruction, and the application of machine learning algorithms. The results are statistically robust, drawing from tissue samples of 98 cervical cancer patients and incorporating over 40 million data points. Traditional cervical cancer diagnosis methods entail biopsy, staining, and visual evaluation by a pathologist. This process is qualitative, subject to variations in staining and subjective interpretations, and requires extensive tissue processing, making it costly and time-consuming. In contrast, our proposed alternative can produce images comparable to those from histological analyses without the need for staining or complex sample preparation. This label-free, quantitative method utilizes biochemical data from HP-MIRSI and employs machine-learning algorithms for the rapid and precise segmentation of cervical tissue subtypes. This approach can potentially transform histopathological analysis by offering a more accurate and label-free alternative to conventional diagnostic processes.

Hyperspectral photothermal mid-infrared spectroscopic imaging (HP-MIRSI) is an emerging technology with promising applications in cervical cancer diagnosis and quantitative, label-free histopathology. This study pioneers the application of HP-MIRSI to the evaluation of clinical cervical cancer tissues, achieving excellent tissue type segmentation accuracy of over 95%. This achievement stems from an integrated approach of optimized data acquisition, computational data reconstruction, and the application of machine learning algorithms. The results are statistically robust, drawing from tissue samples of 98 cervical cancer patients and incorporating over 40 million data points. Traditional cervical cancer diagnosis methods entail biopsy, staining, and visual evaluation by a pathologist. This process is qualitative, subject to variations in staining and subjective interpretations, and requires extensive tissue processing, making it costly and time-consuming. In contrast, our proposed alternative can produce images comparable to those from histological analyses without the need for staining or complex sample preparation. This label-free, quantitative method utilizes biochemical data from HP-MIRSI and employs machine-learning algorithms for the rapid and precise segmentation of cervical tissue subtypes. This approach can potentially transform histopathological analysis by offering a more accurate and label-free alternative to conventional diagnostic processes.

Correlation signal processing of optical three-dimensional (x, y, t) data can produce super-resolution images. The second-order cross-correlation function XC ₂ has been documented to produce super-resolution imaging with static and blinking emitters but not for diffusing emitters. Here, we both analytically and numerically demonstrate cross-correlation analysis for diffusing particles. We then expand our fluorescence correlation spectroscopy super-resolution optical fluctuation imaging (fcsSOFI) analysis to use cross-correlation as a postprocessing computational technique to extract both dynamic and structural information on particle diffusion in nanoscale structures simultaneously. Cross-correlation maintains the same super-resolution as auto-correlation while also increasing the sampling rates to reduce aliasing for spatial information in both simulated and experimental data. Our work demonstrates how fcsSOFI with cross-correlation can be a powerful signal-processing tool to resolve the nanoscale dynamics and structure in samples relevant to biological and soft materials.