Synchronous Imaging Research Articles

On the fractional‐order simplified Lorenz models: Dynamics, synchronization, and medical image encryption

This article discusses, for the first time as we know, the basic dynamics of commensurate and noncommensurate fractional‐order simplified Lorenz models, such as invariance, dissipation, stationary points, and the coexistence of chaotic attractors. These models have chaotic attractors and circles of stationary points. Our suggested models are derived from the Lorenz model, which appears in physics, engineering, and medicine (e.g., secure communications). Based on the tracking control method, we investigate a scheme for studying dual compound combination synchronization (DCCS) among 10 fractional‐order chaotic models. This kind of synchronization is a generalization of many other types in the literature. In order to achieve this type of synchronization, a theorem is established and proven to give us the analytical formula for the control functions. These analytical results are supported by numerical calculations. The encryption and decryption of medical image are presented based on DCCS of 10 fractional‐order chaotic models. Information entropy, correlation analysis between adjacent pixels, and histograms are computed together with the experimental results of medical image encryption.

Addressing uncertainties in correlative imaging of exogenous particles with the tissue microanatomy with synchronous imaging strategies.

Exposure to exogenous particles is of increasing concern to human health. Characterizing the concentrations, chemical species, distribution, and involvement of the stimulus with the tissue microanatomy is essential in understanding the associated biological response. However, no single imaging technique can interrogate all these features at once, which confounds and limits correlative analyses. Developments of synchronous imaging strategies, allowing multiple features to be identified simultaneously, are essential to assess spatial relationships between these key features with greater confidence. Here, we present data to first highlight complications of correlative analysis between the tissue microanatomy and elemental composition associated with imaging serial tissue sections. This is achieved by assessing both the cellular and elemental distributions in three-dimensional space using optical microscopy on serial sections and confocal X-ray fluorescence spectroscopy on bulk samples, respectively. We propose a new imaging strategy using lanthanide-tagged antibodies with X-ray fluorescence spectroscopy. Using simulations, a series of lanthanide tags were identified as candidate labels for scenarios where tissue sections are imaged. The feasibility and value of the proposed approach are shown where an exposure of Ti was identified concurrently with CD45 positive cells at sub-cellular resolutions. Significant heterogeneity in the distribution of exogenous particles and cells can be present between immediately adjacent serial sections showing a clear need of synchronous imaging methods. The proposed approach enables elemental compositions to be correlated with the tissue microanatomy in a highly multiplexed and non-destructive manner at high spatial resolutions with the opportunity for subsequent guided analysis.

Bioorthogonal Chemical Imaging of Cell Metabolism Regulated by Aromatic Amino Acids.

Essential aromatic amino acids (AAAs) are building blocks for synthesizing new biomasses in cells and sustaining normal biological functions. For example, an abundant supply of AAAs is important for cancer cells to maintain their rapid growth and division. With this, there is a rising demand for a highly specific, noninvasive imaging approach with minimal sample preparation to directly visualize how cells harness AAAs for their metabolism in situ. Here, we develop an optical imaging platform that combines deuterium oxide (D2O) probing with stimulated Raman scattering (DO-SRS) and integrates DO-SRS with two-photon excitation fluorescence (2PEF) into a single microscope to directly visualize the metabolic activities of HeLa cells under AAA regulation. Collectively, the DO-SRS platform provides high spatial resolution and specificity of newly synthesized proteins and lipids in single HeLa cell units. In addition, the 2PEF modality can detect autofluorescence signals of nicotinamide adenine dinucleotide (NADH) and Flavin in a label-free manner. The imaging system described here is compatible with both in vitro and in vivo models, which is flexible for various experiments. The general workflow of this protocol includes cell culture, culture media preparation, cell synchronization, cell fixation, and sample imaging with DO-SRS and 2PEF modalities.

Three types of bidirectional leader development in triggered lightning flashes

Eight cases of bidirectional leader (BL) development in artificially triggered lightning flashes are reported with synchronous high-speed camera images and electric field signals. Based on optical progressing characteristics, the eight cases can be divided into three types: a reflection type, a discontinuity type, and an inducement type. For the reflection type, the tail of a dart leader may begin to extend backward when the leader’s head reaches a branch point, or the top of the exploded triggering wire. For the discontinuity type, the initiation of a bidirectional leader below a decayed attempted leader may occur more than once preceding one return stroke. For the inducement type, the approach of another leader with the same polarity will turn a dart leader into a bidirectional leader. The reflection type and inducement type are first observed here. Two cases of the discontinuity type are observed, and both are multiple-bidirectional leaders observed for the first time. For the reflection type and inducement type, there are fluctuations in the electric field related to the BL development. The dissipation of the downward leader slows down the negative increase of the electric field. Once the BL development starts, the downward negative end of the BL moves towards the ground with the E-field negatively increasing. For the discontinuity type, the close electric field result shows no fluctuations. The BL development has a much longer duration than the other two BL types.

Electromagnetic Imaging of Passive Intermodulation Sources Based on Virtual Array Expansion Synchronous Imaging Compressed Sensing

Interference caused by passive intermodulation (PIM) has seriously affected system performance. Compressed sensing (CS) can be used to locate radial PIMs. In CS-based electromagnetic imaging methods, the ability to locate the number of targets is usually limited by the number of receiving antennas, and there are flooding problems in the imaging results. To solve these problems, traditional methods are used to increase the number of receiving antennas. To reduce the number of receiving antennas and improve the imaging effect, this paper proposes a virtual array expansion synchronous imaging compressed sensing (SI-CS) method. With the full-wave electromagnetic simulation demonstrations, the proposed method exhibits significant improvement in imaging performance compared to the conventional methods. In addition, the proposed method can discriminate between targets in the presence of the flooding problem in which the paraflap is too large and the location of the PIM source cannot be determined by the amplitude value.

A new effective method for identifying boletes species based on FT-MIR and three dimensional correlation spectroscopy projected image processing

This study proposed the necessity of identifying the species for boletes in combination with the medicinal value, nutritional value and the problems existing in the industrial development of boletes. Based on the preprocessing of Fourier transform mid-infrared spectroscopy (FT-MIR) by 1st, 2nd, SNV, 2nd + MSC and 2nd + SG, Multilayer Perceptron (MLP) and CatBoost models were established. To avoid complex preprocessing and feature extraction, we try deep learning modeling methods based on image processing. In this paper, the concept of three-dimensional correlation spectroscopy (3DCOS) projection image was proposed, and 9 datasets of synchronous, asynchronous and integrative images are generated by computer method. In addition, 18 deep learning models were established for 9 image datasets with different sizes. The results showed that the accuracy of the three types of synchronous spectral models reached 100%, while the accuracy of the asynchronous spectral and integrative spectral models of 3DCOS projection images were 96.97% and 97.98% in the case of big datasets, which overcame the defects of poor modeling effect of asynchronous spectral and integrative spectral in previous two-dimensional correlation spectroscopy (2DCOS) studies. In conclusion, the modeling results of 3DCOS projection images are perfect, and we can apply this method to other identification fields in the future.

Next-generation seismic model of the Australian crust from synchronous and asynchronous ambient noise imaging

The proliferation of seismic networks in Australia has laid the groundwork for high-resolution probing of the continental crust. Here we develop an updated 3D shear-velocity model using a large dataset containing nearly 30 years of seismic recordings from over 1600 stations. A recently-developed ambient noise imaging workflow enables improved data analysis by integrating asynchronous arrays across the continent. This model reveals fine-scale crustal structures at a lateral resolution of approximately 1-degree in most parts of the continent, highlighted by 1) shallow low velocities (<3.2 km/s) well correlated with the locations of known sedimentary basins, 2) consistently faster velocities beneath discovered mineral deposits, suggesting a whole-crustal control on the mineral deposition process, and 3) distinctive crustal layering and improved characterization of depth and sharpness of the crust-mantle transition. Our model sheds light on undercover mineral exploration and inspires future multi-disciplinary studies for a more comprehensive understanding of the mineral systems in Australia.

Synchronous Medical Image Augmentation framework for deep learning-based image segmentation.

Various deep learning (DL) models are widely applied in medical image analysis, and their performance depends on the scale and diversity of available training data. However, medical images often suffer from difficulty in data acquisition, imbalance in sample categories, and high cost of labeling. In addition, most image augmentation approaches mainly focus on image synthesis only for classification tasks, and rarely consider the synthetic image-label pairs for image segmentation tasks. In this paper, we focus on the medical image augmentation for DL-based image segmentation and the synchronization between augmented image samples and their labels. We design a Synchronous Medical Image Augmentation (SMIA) framework, which includes two modules based on stochastic transformation and synthesis, and provides diverse and annotated training sets for DL models. In the transform-based SMIA module, for each medical image sample and its tissue segments, a subset of SMIA factors with a random number of factors and stochastic parameter values are selected to simultaneously generate augmented samples and the paired tissue segments. In the synthesis-based SMIA module, we randomly replace the original tissues with the augmented tissues using an equivalent replacement method to synthesize new medical images, which can well maintain the original medical implications. DL-based image segmentation experiments on bone marrow smear and dermoscopic images demonstrate that the proposed SMIA framework can generate category-balanced and diverse training data, and have a positive impact on the performance of the models.

Verteporfin Loaded Graphitic Carbon Nitride Nanosheets for Combined Photo‐Chemotherapy

AbstractVerteporphin loaded g‐C3N4 represents a multifunctional therapeutic platform for synchronous cancer imaging and treatment through the synergistic effect of phototherapy and chemotherapy. A biocompatible nanocarrier using g‐C3N4 nanosheets for high loading and anticancer activity of photosensitizer drug verteporfin (VP) is designed. The drug encapsulation efficiency (%) of optimized mannose functionalized g‐C3N4 formulation was observed to be 68.5 % for 5 mg of nanocarrier. It was found that 63.3 % and 81 % of the total bound drug was released from the nanocarrier at pH 5.4 and pH 1.2 respectively after 48 h. Under neutral conditions (pH 7.4), 45.2 % of the drug was released from the nanocarrier in the first 48 h. The % cytotoxicity of the free drug, the drug loaded nanocarrier against human breast cancer cell line (MCF‐7) was found to be 91.47 % and 91.23 % respectively at the dose of 40 μg/mL and 5 mg/mL after 48 h. IC50 values also manifest the significantly lower cytotoxicity of drug loaded nanocarriers (IC50=0.195 mg/mL) as compared to free‐drug (IC50=0.156 μg/mL). For mannosylated graphitic carbon nitride (g‐C3N4), verteporfin and man‐g‐C3N4@VP the values of mean ± std. deviation were found to be 4.14±2.46; 55.39±2.76; 63.27±1.74 respectively. Terephthalic acid assay confirmed formation of hydroxyl radicals in the solution treated with nanocarrier. This study suggests that g‐C3N4 is a promising use in drug carrier, cancer diagnosis and therapy. The combined effects of the high efficacy of ROS generation under UV light irradiation, low toxicity, and bio‐compatibility highlight the potential of verteporphin loaded g‐C3N4 for PDT.

Study of the suitable climate factors and geographical origins traceability of Panax notoginseng based on correlation analysis and spectral images combined with machine learning.

The cultivation and sale of medicinal plants are some of the main ways to meet the increased market demand for plant-based drugs. Panax notoginseng is a widely used Chinese medicinal material. The growth and accumulation of bioactive constituents mainly depend on a satisfactory growing environment. Additionally, the occurrence of market fraud means that care should be taken when purchasing. In this study, we report the correlation between saponins and climate factors based on high performance liquid chromatography (HPLC), and evaluate the influence of climate factors on the quality of P. notoginseng. In addition, the synchronous two-dimensional correlation spectroscopy (2D-COS) images of near infrared (NIR) data combined with the deep learning model were applied to traceability of geographic origins of P. notoginseng at two different levels (district and town levels). The results indicated that the contents of saponins in P. notoginseng are negatively related to the annual mean temperature and the temperature annual range. A lower annual mean temperature and temperature annual range are favorable for the content accumulation of saponins. Additionally, high annual precipitation and high humidity are conducive to the content accumulation of Notoginsenoside R1 (NG-R1), Ginsenosides Rg1 (G-Rg1), and Ginsenosides Rb1 (G-Rb1), while Ginsenosides Rd (G-Rd), this is not the case. Regarding geographic origins, classifications at two different levels could be successfully distinguished through synchronous 2D-COS images combined with the residual convolutional neural network (ResNet) model. The model accuracy of the training set, test set, and external validation is achieved at 100%, and the cross-entropy loss function curves are lower. This demonstrated the potential feasibility of the proposed method for P. notoginseng geographic origin traceability, even if the distance between sampling points is small. The findings of this study could improve the quality of P. notoginseng, provide a reference for cultivating P. notoginseng in the future and alleviate the occurrence of market fraud.

Fast-Specific Fluorescent Probes to Visualize Norepinephrine Signaling Pathways and Its Flux in the Epileptic Mice Brain.

Norepinephrine (NE) is synthesized in the locus coeruleus and widely projected throughout the brain and spinal cord. It regulates various actions and consciousness linked to a variety of neurological diseases. A "hunting-shooting" strategy was proposed in this work to improve the specificity and response rate of an NE fluorescent probe: 2-(cyclohex-2-en-1-ylidene)malononitrile derivatives were chosen as a fluorophore. To create a dual-site probe, an aldehyde group was added to the ortho of the ester group (or benzene sulfonate). Because of its excellent electrophilic activity, the aldehyde group could rapidly "hunt" the amino group and then form an intramolecular five-membered ring via the nucleophilic reaction with the β-hydroxyl group. The -NH- in the five-membered ring "shoots" the adjacent ester group, releasing the fluorophore and allowing for rapid and specific NE detection. The NE release and reuptake ″emetic″-″swallow″ transient process is captured and visualized under the action of the primary NE receptor drug. Furthermore, by introducing halogen into the fluorophore to lengthen the absorption wavelength, improve lipid solubility, and adjust the pKa appropriately, the probe successfully penetrated the blood-brain barrier (BBB). In situ synchronous probe imaging was used to detect the NE level in the brains of epileptic and normal mice, and abnormal expression of NE in the brain was discovered during epilepsy. Brain anatomy was used to examine the distribution and level changes of NE in various brain regions before and after epilepsy. This research provides useful tools and a theoretical foundation for diagnosing and treating central nervous system diseases early.

Automatic Dynamic Estimation of On-Orbit Satellites Through Spaceborne ISAR Imaging

With the continuous development of satellite constellations worldwide, dynamic estimation of on-orbit spacecraft plays a more and more important role in space situation awareness applications. Based on high-resolution inverse synthetic aperture radar (ISAR) imaging from the ground, some exploratory methods have been proposed to estimate target dynamic parameters, such as its attitude pointing and spin period. Due to the limited observation view from the ground, most of them rely on the long-term measurement, and the robust association of image features needs to be ensured. In this article, a novel approach based on spaceborne ISAR images is proposed to achieve the dynamic estimation of spin satellites. In order to build a synchronous similar-resolution ISAR imaging system, two adjacent satellites are picked up from low earth orbit constellations according to the radar tracking parameters. With obtained a pair of ISAR images, the explicit expression between target dynamic parameters and projection feature is deduced. Inspired by the existing works on shape extraction of the human body, a feature extraction network is built on the framework of ResNet for achieving the automatic processing in spaceborne equipments. In this way, target dynamic parameters can be solved in instantaneous attitude optimization and spin motion optimization in steps. Simulation experiments of a typical spin spacecraft, Tiangong-I, illustrate the feasibility of the proposed method. Besides, a comparison experiment with an existing ground-based work is also made to analyze its advantage in practical applications.

An Innovative Miniaturized Cell Imaging System Based on Integrated Coaxial Dual Optical Path Structure and Microfluidic Fixed Frequency Sample Loading Strategy

On-site rapid detection of cells is especially of concern for many fields, image-based detection results can directly reflect the multi-dimensional information such as cell contour and aggregation state. This article proposes an innovative miniaturized cell imaging system based on integrated coaxial dual optical path structure and microfluidic fixed frequency sample loading strategy, which performs synchronous imaging of bright field mode and fluorescence field mode on cells. The bright field optical path and fluorescence field optical path are integrated into the coaxial dual optical path structure based on the dichroic mirror with splitting and steering functions. The movement of the shutter’s curtain is controlled by a micro-motor, so that the plane mirrors fixed on the curtain with different light angle can be switched to the optical axis, and the fast switching of the bright field optical path and the fluorescence field optical path can be implemented. A drawer-type filter module can be pulled out of the coaxial dual optical path structure, the emission filter and the dichroic mirror in this module can be replaced according to the fluorescence emission peak of the sample to be tested, thereby expanding the detectable cell types of this system. In addition, based on the force analysis and calculation of the fluid, a fixed frequency was obtained to drive the sample loading. The accumulated kinetic energy of the fluid during this period can be offset by the closing of the pinch valve, and the flow rate of the sample in the imaging field can be rapidly reduced to close to zero to avoid the tailing effect in the image. It is experimentally confirmed that the detection accuracy of this system, the registration matching accuracy of cells and fluorescent dots, the cell survival rate, and the detection sensitivity of cell viability. This system balances the tradeoff between portability, flux and accuracy, offers more functionality in terms of technology and application for on-site cell detection.

Main components determination and rapid geographical origins identification in Gentiana rigescens Franch. based on HPLC, 2DCOS images combined to ResNet

As an important resource in many prescriptions, the geographical origins of Gentiana rigescens Franch. influences its chemical characteristics, quality and price greatly. Hence, a simple and rapid method for the correct classification and identification of the geographical origins of G. rigescens is of significance. In this work, marker components of iridoids were measured by high performance liquid chromatography (HPLC) and were applied as a reference to characterize chemical profiles of samples from different geographical origins. The effects of climate factors on the content differences of G. rigescens were examined by correlation analysis. Afterward, a novel two-dimensional correlation spectroscopy (2DCOS) images acquired based on Fourier transform infrared (FT-IR) spectroscopy was proposed combined to deep learning to identify geographical origins of G. rigescens. Through analyzing the iridoid components of G. rigescens, which discovered that there were significant differences in its five marker components. In addition, the marker components of gentiopicroside based on Northwestern Yunnan (DXB) were higher, and the climate environment of low temperature, temperate, and high precipitation was more suitable for the cultivation and growth of G. rigescens. In the residual convolutional neural network (ResNet), the train set and test set accuracy of synchronous 2DCOS images for the feature bands (1800–400 cm-1) was 100%, and the external validation set of all samples was correctly identified. The results indicated the synchronous 2DCOS images of feature bands were suitable for the correct identification of the geographic origin of G. rigescens, and it reduced the amount of computation and time, and saved computing resources. This study provided a powerful and useful tool for the cultivation and geographical origins identification of G. rigescens.

Integrating a Far-Red Fluorescent Probe with a Microfluidic Platform for Super-Resolution Imaging of Live Erythrocyte Membrane Dynamics.

Living erythrocyte (red blood cell, RBC) membranes present rich ultrastructural and dynamic details, which require synchronous super-resolution imaging and single-molecule tracking to be revealed. Yet, it poses a serious challenge to achieve these dual functions in a single probe, due to the rigid and conflicting photophysical demands of the different techniques. Herein, we rationally developed a far-red boron dipyrromethene membrane probe with blinking capability and persistent single-molecule emission, and constructed a microfluidic platform for noninvasive trapping and long-term imaging of RBCs. By combining them, multi-dimensional super-resolution reconstructions and single-molecule tracking were achieved at the molecular scale on living human RBC membranes in a high-throughput manner. Our integrated system defines a quantitative method for analyzing RBC membranes under physiological and pathological conditions, improving precision and revealing new perspectives for future disease diagnostics.

Fast image encryption algorithm based on multi-parameter fractal matrix and MPMCML system

This paper studies chaotic image encryption technology and fractal matrix theory, and proposes a synchronous permutation-diffusion encryption algorithm based on multi-parameter fractal matrix. First, this paper proposes a new Multiple Parameter Mixed Coupled Map Lattices system (MPMCML). Then, the concept of fractal matrix is introduced, and the construction process of multi-parameter fractal matrix is given. Finally, based on the multi-parameter fractal matrix, a new synchronous permutation-diffusion image encryption algorithm is proposed. Most importantly, the multi-parameter fractal matrix is very sensitive to the change of parameters, any slight change of parameters will produce a completely different fractal matrix, making the encryption result completely different. Compared with the methods of permutation before diffusion and diffusion before permutation, the synchronous permutation-diffusion method greatly improves the privacy of permutation and diffusion, and improves the anti-attack ability of the algorithm. By analyzing the encryption performance and the ability to resist various attacks, it can be determined that the proposed algorithm exhibits good security characteristics.

A strategy of fast evaluation for the raw material of Tiepi Fengdou using FT-NIR and ATR-FTIR spectroscopy coupled with chemometrics tools

Tiepi Fengdou, as a precious traditional Chinese medicinal material in China, is a dried product of Dendrobium officinale that holds unique efficacy of nourishing Yin and clearing heat. However, there are many similar species named Fengdou for trade in the herbal market, leading to confusion about the currently commercially available Tiepi Fengdou medicinal materials, which brings great difficulties to the identification and evaluation of raw materials quality of Dendrobium. Therefore, it is necessary to establish a rapid and effective method for D. officinale and other species. In this study, deep learning (DL) models directly combined the two-dimensional correlation spectroscopy (2DCOS) images based on full bands and four characteristic bands of Fourier transform near-infrared (FT-NIR) and attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy from D. officinale and 9 species of Dendrobium were established, and these identification effect of DL models were optimized and compared. The results show that the separation effect based on the two spectra with second derivative (SD) preprocessing is the best according to different categories via principal component analysis. Then, compared with ATR-FTIR, the DL models of SD full band, 9000–5500 cm−1 and 5250–4100 cm−1 band had absolute advantages to discriminate D. officinale and 9 species of Dendrobium based on FT-NIR. Based on this, the DL model with parameters of 16 bate size and 60 epochs combined with synchronous 2DCOS images is well based on FT-NIR to identify D. officinale and other species of Dendrobium. This method can not only quickly and accurately identify the raw materials (D. officinale) of Tiepi Fengdou, but also provide a theoretical basis for extended further research on other fields of medicinal plants or fungi.

Visualization of micro-agents and surroundings by real-time multicolor fluorescence microscopy

Optical microscopy techniques are a popular choice for visualizing micro-agents. They generate images with relatively high spatiotemporal resolution but do not reveal encoded information for distinguishing micro-agents and surroundings. This study presents multicolor fluorescence microscopy for rendering color-coded identification of mobile micro-agents and dynamic surroundings by spectral unmixing. We report multicolor microscopy performance by visualizing the attachment of single and cluster micro-agents to cancer spheroids formed with HeLa cells as a proof-of-concept for targeted drug delivery demonstration. A microfluidic chip is developed to immobilize a single spheroid for the attachment, provide a stable environment for multicolor microscopy, and create a 3D tumor model. In order to confirm that multicolor microscopy is able to visualize micro-agents in vascularized environments, in vitro vasculature network formed with endothelial cells and ex ovo chicken chorioallantoic membrane are employed as experimental models. Full visualization of our models is achieved by sequential excitation of the fluorophores in a round-robin manner and synchronous individual image acquisition from three-different spectrum bands. We experimentally demonstrate that multicolor microscopy spectrally decomposes micro-agents, organic bodies (cancer spheroids and vasculatures), and surrounding media utilizing fluorophores with well-separated spectrum characteristics and allows image acquisition with 1280 times 1024 pixels up to 15 frames per second. Our results display that real-time multicolor microscopy provides increased understanding by color-coded visualization regarding the tracking of micro-agents, morphology of organic bodies, and clear distinction of surrounding media.

Abstract 5579: First-in-human study of ICAM-1-specific affinity tuned CAR T cells against advanced thyroid cancer

Abstract Background: The use of chimeric antigen receptor (CAR) T cells for solid tumors has a number of challenges, such as lack of tumor-specific targets, CAR T cell exhaustion, and the immunosuppressive tumor microenvironment. To address these challenges, AffyImmune has developed technologies to affinity tune and track CAR T cells in patients. The targeting moiety is affinity tuned to preferentially bind to tumor cells overexpressing the target while leaving normal cells with low basal levels untouched, thereby increasing the therapeutic window and allowing for more physiological T cell killing. The CAR T cells are engineered to co-express somatostatin receptor 2 (SSTR2), which allows for the tracking of CAR T cells in vivo via PET/CT scan using FDA-approved DOTATATE. Methods: AIC100 was generated by affinity tuning the I-domain of LFA-1, the physiological ligand to ICAM-1. Various mutants with 106-fold difference in affinity were evaluated for structure activity relationships using targets with varying antigen densities. The AIC100 with micromolar affinity was clearly the most effective in non-clinical animal models. AIC100 is currently being evaluated to assess safety, CAR T expansion, tumor localization, and preliminary activity in patients with advanced thyroid cancer (ATC) in a phase I study (NCT04420754). Our study uses a modified toxicity probability interval design with three dosage groups of 10 × 106, 100 × 106, and 500 × 106 cells. Results: Preclinical studies demonstrated greater in vivo anti-tumor activity and safety with micromolar affinity CAR T cells. A single dose of AIC100 resulted in tumor elimination and significantly improved survival of animals bearing ATC xenografts. AIC100 activity was confirmed in other high ICAM-1 tumor models including breast cancer, gastric cancer, and multiple myeloma. In a Phase I patient given 10 × 106 CAR T cells, near synchronous imaging of FDG and DOTATATE revealed preliminary evidence of transient CAR T expansion and tumor reduction at multiple tumor lesions, with the peak of CAR T cell density coinciding with the spike in CAR T cell numbers in blood. Conclusion: We have developed affinity tuned CAR T cells designed to selectively target ICAM-1 overexpressing tumor cells and to spatiotemporally image CAR T cells. Near-synchronous FDG and DOTATATE scans will enhance patient safety by early detection of off-tumor CAR T activity and validation of tumor response. We anticipate that our “tune and track” technology will be widely applicable to developing potent yet safe CAR T cells against hard-to-treat solid cancers. Citation Format: Jingmei Hsu, Yen-Michael Hsu, Koen van Besien, Thomas J. Fahey, Jana Ivanidze, Janusz Puc, Karrie Du, Yanping Yang, Yogindra Vedvyas, Irene M. Min, Eric von Hofe, Moonsoo M. Jin. First-in-human study of ICAM-1-specific affinity tuned CAR T cells against advanced thyroid cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5579.

Novel Near‐Infrared Fluorescent Nanoprobe Synthesized by the RAFT‐Mediated PISA Strategy for Hypoxia‐Triggered Tumor Imaging and Azoreductase‐Responsive Drug Release

AbstractDrug carriers and visual tracking play an important role in accurate and efficient drug delivery systems for targeted drug therapy. Polymerization‐induced self‐assembly (PISA), a powerful strategy for the fabrication of stimuli‐responsive polymeric nanoparticles has been a focus over the past decade due to its promising applications in biomedical fields such as targeted drug delivery and fluorescent nanoprobes used for tumor imaging. Herein, hypoxia‐responsive near‐infrared (NIR) fluorescent nanoprobes of amphiphilic block copolymers (PPEGMA14‐ADP‐Azo‐PBzMAx) are reported, the first example synthesized by RAFT‐mediated PISA strategy in situ to realize synchronous drug release and cell imaging. First, a series of nanoparticles with different morphologies and sizes, including spheres and vesicles, are synthesized by the PISA strategy using PPEGMA14‐ADP‐Azo‐CDPA as macro‐RAFT agents link with near‐infrared Aza‐BODIPY fluorogen and azobenzene groups. Hypoxia‐triggered dissociation of the nanoprobes and NIR fluorescence emission is then observed because of the cleavage of azo bonds. Meanwhile, the in situ DOX‐loaded nanoprobes by the PISA demonstrate synchronous drug release and NIR fluorescence enhancement against mouse colon cancer cells (CT26) under hypoxia (1% O2) compared with under normoxia (16% O2).