Imaging Mode Research Articles

How to see the South African black people in Santu Mofokeng’s image-text archive?

South African artist Santu Mofokeng’s The Black Photo Album—Look at Me: 1890–1950 (1997) displays black people’s photographic portraits and text through a slide projection. For this archive project, he collected, restored, and re-contextualized the old portraits and added text. The presented figures depict the black South Africans who lived at the end of the nineteenth century. Most of them are well-dressed and take a pose in a European studio. Different from the well-prepared photographic representation, pieces of text include a disorder of alphabets, varied size of letters, inconsistent ground color, and misprinting effect. In a sense, the ambivalent mode of images and text seems to appeal the black people’s inner conflicts between being modernized versus colonized. In fact, Mofokeng once said that such a middle-class of black people did not exist in his education. Thus, this research analyzes the ways in which intertextuality of images and text in The Black Photo Album fills with the incomplete part of South African history. Reconsidering the functional limits of the TRC(Truth and Reconciliation Commission, 1995) in South Africa, this research argues that Mofokeng’s archive project delivers emotions of memories of the black people, which were not registered in the nation’s history.

Medical image fusion with deep neural networks

Medical image fusion aims to fuse multiple images from a single or multiple imaging modes to enhance their corresponding clinical applications in diagnosing and evaluating medical problems, a trend that has attracted increasing attention. However, most recent medical image fusion methods require prior knowledge, making it difficult to select image features. In this paper, we propose a novel deep medical image fusion method based on a deep convolutional neural network (DCNN) for directly learning image features from original images. Specifically, source images are first decomposed by low rank representation to obtain the principal and salient components, respectively. Following that, the deep features are extracted from the decomposed principal components via DCNN and fused by a weighted-average rule. Then, considering the complementary between the salient components obtained by the low rank representation, a simple yet effective sum rule is designed to fuse the salient components. Finally, the fused result is obtained by reconstructing the principal and salient components. The experimental results demonstrate that the proposed method outperforms several state-of-the-art medical image fusion approaches in terms of both objective indices and visual quality.

Using ICG navigation in resection of a horseshoe kidney

BACKGROUND: In this publication, we present a new area of application of indocyanine green (ICG) imaging in pediatric surgery. We used this advanced method to evaluate the resection margins of a functional segment of the horseshoe kidney after intravenous indocyanine green. CLINICAL CASE DESCRIPTION: The article presents a case of treatment of a horseshoe kidney complicated by vesicorenal reflux in the left segment and loss of function of the left segment. Resection of the left half of the horseshoe kidney was performed using fluoroscopic control with intravenous administration of indocyanine green. The surgery was performed using the RUBINA™ endovideosurgical system manufactured by KARL STORZ (Germany). RUBINA™ components offer a variety of ICG in near-infrared fluorescence signal imaging modes. Depending on the surgeon and the application, ICG in near-infrared fluorescence data can be used in different modes: image overlay mode, backup mode, color mapping mode. After confirming the boundaries of the perfused part of the kidney, laparoscopic resection of the functional half was performed at the level of the isthmus. The use of ICG imaging was very important in identifying healthy tissue that stained intensely green 2 minutes after intravenous indocyanine green administration. This margin check verifies the functioning renal parenchyma and allows the correct selection of the nephrectomy margin. The next day after the operation, an ultrasound examination of the renal remnant and perinephric space was performed — the rotation to the right hour of the horseshoe-shaped kidney was good and no accumulation of fluid was detected in the bed of the removed segment. A control ultrasound examination 6 months after the operation showed the preservation of the parenchyma of the right half of the kidney, which indicates the positive effect of the surgical procedure. CONCLUSION: ICG navigation is a promising method for noninvasive assessment of resection margins in patients with horseshoe kidneys.

PEAKFORCE QUANTITATIVE NANOMECHANICAL MAPPING FOR SURFACE ENERGY CHARACTERIZATION ON THE NANOSCALE: A MINI-REVIEW

Surface energy characterization is important to design the fabrication process of reliable electronic devices. Surface energy is influenced by various factors such as surface functionality and morphology. Owing to the high surface-to-volume ratio, surface energy at the nanoscale can be different from that of the bulk. However, the conventional methods for characterization of surface energy such as a sessile drop or Washburn methods cannot be used for nanoscale samples, owing to the limited volume for characterization. Recently, surface energy characterization on the nanoscale using atomic force microscopy (AFM) with Peak Force-Quantitative Nanomechanical Mapping (PF-QNM) imaging mode has been proposed. The nanoscale AFM tips measure the adhesion forces at the nanoscale, which are converted into surface energy through pre-calibrated curves. Successful surface energy characterization of nanoscale metal samples using AFM with the PF-QNM method has been reported previously. This mini-review discusses the recent progress on surface energy characterization at the nanoscale using AFM with the PF-QNM method. The fundamentals of the PF-QNM mode are introduced, and the results of surface energy characterization are summarized. Consequently, the future research direction for surface energy characterization at the nanoscale is discussed.

The Utility of a Novel Stacked Microvascular Imaging for Enhanced Detection of Fibrosis in Chronic Liver Diseases

Ultrasonographic imaging plays a primary role to detect fibrotic changes in patients with chronic liver disease (CLD). To enhance detectability of fibrosis in its early stage, we developed a novel stacked microvascular imaging (SMVI) that enables continuous visualization of fibrotic changes in intrahepatic vessels. SMVI was produced by accumulating 3-5 seconds of high-definition color images in tilted-scan mode. An SMVI score was devised by quantitating three hallmark vascular changes in liver fibrosis in 0-2 grades (total 0-6): narrowing, caliber irregularity, and tortuosity. To evaluate the clinical utility of the SMVI score, 469 well-defined CLD patients were enrolled and subgrouped by the stage of liver fibrosis defined based on elastography: F0-1Low, F0-1High, F2, F3, and F4. The diagnostic performance of the SMVI score was compared to conventional B-mode liver morphology score and various laboratory test markers of fibrosis. Unlike conventional microvascular imaging that relies on a single image, SMVI enabled an undisrupted view of intrahepatic vessels for easy detection of fibrotic changes. SMVI detected microvascular narrowing in 92% at stage F0-1High. While detection rates for caliber irregularity and tortuosity were low at early stages but increased proportionately in advanced stages. Multiple logistic regression analysis revealed that SMVI score was most accurate in distinguishing F0-1Low from F0-1High cases compared to B-mode or laboratory test scores. SMVI provides enhanced vascular images of liver fibrosis in CLD, especially in its early stage. The SMVI score can be used as a primary tool for determining fibrotic stages in CLD.

COMPARISON OF THE CHOROIDAL VASCULARITY INDEX MEASUREMENTS OF IMAGES ACQUIRED WITH DIFFERENT OPTICAL COHERENCE TOMOGRAPHY SCAN SCALE TYPES.

To evaluate the differences in choroidal vascularity index (CVI) measurements between images acquired at the 1:1 pixel scale and at the 1:1 µ m scale of the Heidelberg optical coherence tomography device. Forty-five healthy eyes of 45 healthy subjects were included for this study. Fovea-centered scans were obtained with an enhanced-depth imaging mode with a high-speed protocol scan. Each scan was exported in 3 different types: 1) 1:1 pixel scale type; 2) 1:1 µ m scale type (MST); and 3) 4×-magnified MST (4×MST; 400%-magnified 1:1 µ m images exported via screenshot). A comparison between CVI measurements based on the different scale types of optical coherence tomography images was conducted using the Bland-Altman analysis and intraclass correlation coefficient. The image with the worst clarity was acquired via the MST, and the CVI was found to be higher in MST images (69.05 ± 3.21) compared with the other groups. The intraclass correlation coefficient between the CVI values of the 4×MST and pixel scale type images was 0.92, between those of the 4×MST and MST images was 0.33, and between those of the pixel scale type and MST images was 0.44. The optical coherence tomography scale and export method type significantly influence the image resolution, CVI, and choroidal area measurements.

Three-Dimensional Shear Wave Elastography Using Acoustic Radiation Force and a 2-D Row-Column Addressing (RCA) Array.

Acoustic radiation force (ARF)-based shear wave elastography (SWE) is a clinically available ultrasound imaging mode that noninvasively and quantitatively measures tissue stiffness. Current implementations of ARF-SWE are largely limited to 2-D imaging, which does not provide a robust estimation of heterogeneous tissue mechanical properties. Existing 3-D ARF-SWE solutions that are clinically available are based on wobbler probes, which cannot provide true 3-D shear wave motion detection. Although 3-D ARF-SWE based on 2-D matrix arrays have been previously demonstrated, they do not provide a practical solution because of the need for a high channel-count ultrasound system (e.g., 1024-channel) to provide adequate volume rates and the delicate circuitries (e.g., multiplexers) that are vulnerable to the long-duration "push" pulses. To address these issues, here we propose a new 3-D ARF-SWE method based on the 2-D row-column addressing (RCA) array which has a much lower element count (e.g., 256), provides an ultrafast imaging volume rate (e.g., 2000 Hz), and can withstand the push pulses. In this study, we combined the comb-push shear elastography (CUSE) technique with 2-D RCA for enhanced SWE imaging field-of-view (FOV). In vitro phantom studies demonstrated that the proposed method had robust 3-D SWE performance in both homogenous and inclusion phantoms. An in vivo study on a breast cancer patient showed that the proposed method could reconstruct 3-D elasticity maps of the breast lesion, which was validated using a commercial ultrasound scanner. These results demonstrate strong potential for the proposed method to provide a viable and practical solution for clinical 3-D ARF-SWE.

Lightweight and Stable Multi-Feature Databases for Efficient Geometric Localization of Remote Sensing Images

The surge in remote sensing satellites and diverse imaging modes poses substantial challenges for ground systems. Swift and high-precision geolocation is the foundational requirement for subsequent remote sensing image applications. Breakthroughs in intelligent on-orbit processing now enable on-orbit geometric processing. In the absence of control data on board, a recent trend is to introduce reference data onto satellites. However, the pre-storage of traditional reference images or control point databases presents a significant challenge to the limited on-board data storage capacity. Therefore, oriented to the demand for control information acquisition during on-orbit geometry processing, we propose the construction of lightweight and stable feature databases. Initially, stable feature classes are obtained through iterative matching filtering, followed by re-extracting feature descriptors for each stable feature point location on the training images. Subsequently, the descriptors of each point location are clustered and fused using affinity propagation (AP) to eliminate redundancy. Finally, LDAHash is utilized to quantize floating-point descriptors into binary descriptors, further reducing the storage space. In our experiments, we utilize a variety of feature algorithms to assess the generality of our proposed method, thus extending the scope of the feature database and its applicability to various scenarios. This work plays a crucial role in advancing the technology of on-orbit geometry processing for remote sensing satellites.

JWST/NIRCam Imaging of Young Stellar Objects. III. Detailed Imaging of the Nebular Environment around the HL Tau Disk

As part of the James Webb Space Telescope (JWST) Guaranteed Time Observation program “Direct Imaging of YSOs” (program ID 1179), we use JWST NIRCam’s direct imaging mode in F187N, F200W, F405N, and F410M to perform high-contrast observations of the circumstellar structures surrounding the protostar HL Tau. The data reveal the known stellar envelope, outflow cavity, and streamers, but do not detect any companion candidates. We detect scattered light from an inflowing spiral streamer previously detected in HCO+ by the Atacama Large Millimeter/submillimeter Array, and part of the structure connected to the c-shaped outflow cavity. For detection limits in planet mass we use BEX evolutionary tracks when M p < 2 M J and AMES-COND evolutionary tracks otherwise, assuming a planet age of 1 Myr (youngest available age). Inside the disk region, due to extended envelope emission, our point-source sensitivities are ∼5 mJy (37 M J) at 40 au in F187N and ∼0.37 mJy (5.2 M J) at 140 au in F405N. Outside the disk region, the deepest limits we can reach are ∼0.01 mJy (0.75 M J) at a projected separation ∼ 525 au.

Design and Optimization of Silver Nanostructured Arrays in Plasmonic Metamaterials for Sensitive Imaging Applications

This paper delves into the strategic design and optimization of silver (Ag) nanostructured arrays within plasmonic metamaterials, targeting the enhancement of imaging sensitivity. Leveraging Finite-Difference Time-Domain (FDTD) simulations, our research rigorously compares various Ag nanostructured geometries, including nanospheres, nanocones, nanodisks, and nanocubes. The aim is to pinpoint configurations that significantly enhance electric field localization on the surfaces of nanostructures, a pivotal factor. The nanocube array exhibits superior field enhancement, particularly in narrow nanogaps, suggesting its suitability for high-sensitivity applications. Further exploration into nanocube arrays reveals the crucial role of nanogap size and spacer layer thickness in tuning the optical properties through the manipulation of Fabry–Pérot and mirror image modes in metal–insulator–metal (MIM) structures. By presenting a thorough analysis of these nanostructured arrays, the study not only contributes to our understanding of the fundamental principles governing plasmonic metamaterials but also provides a solid foundation for future innovation in highly sensitive imaging applications. It underscores the importance of nanostructure design and optimization in achieving significant improvements in the performance of plasmonic devices, marking a pivotal step forward in the field of nanophotonics and its application to sensitive imaging technologies.

Dual biomarkers-activatable hollow MnO2-Based theranostic nanoplatform for efficient breast cancer-specific multisite fluorescence imaging and synergistic therapy

BackgroundTheranostic nanoplatforms with integrated diagnostic imaging and multiple therapeutic functions play a vital role in precise diagnosis and efficient treatment for breast cancer, but unfortunately, these nanoplatforms are usually stuck in single-site imaging and single mode of treatment, causing unsatisfactory diagnostic and therapeutic efficiency. Herein, a dual biomarkers-activatable facile hollow mesoporous MnO2 (H–MnO2)-based theranostic nanoplatform, DNAzyme@H–MnO2-MUC1 aptamer (DHMM), was constructed for the simultaneous multi-site diagnosis and multiple treatment of breast cancer. ResultsThe DHMM acted as an integrated diagnostic and therapeutic nanoplatform that realizes multi-site fluorescence imaging-guided high-efficient photothermal/chemodynamic/gene synergistic therapy (PTT/CDT/GT) for breast cancer. The H–MnO2 exhibits high loading capacity for Cy5-MUC1 aptamer (3.05 pmoL μg−1) and FAM-DNAzyme (3.37 pmoL μg−1), and excellent quenching for the probes. In the presence of MUC1 on the cell membrane and GSH in the cytoplasm, Cy5-MUC1 aptamer and FAM-DNAzyme was activated triggering dual-channel fluorescence imaging at different sites. Moreover, the self-supplied Mn2+ was further supplied as DNAzyme cofactors to catalytic cleavage intracellular EGR-1 mRNA for high-efficient GT and stimulated the Fenton-like reaction for CDT. The H–MnO2 also showcases a favorable photothermal performance with a photothermal conversion efficiency of 44.16%, which ultimately contributes to multi-site fluorescence imaging-guided synergistic treatment with an apoptosis rate of 71.82%. SignificanceThis dual biomarker-activatable multiple therapeutic nanoplatform was realized multi-site fluorescence imaging-guided PTT/CDT/GT combination therapy for breast cancer with higher specificity and efficiency, which provides a promising theranostic nanoplatform for the precision and efficiency of breast cancer treatment.

Abstract 3800: Next generation of spatial biology: High-throughput multiplexed Imaging Mass Cytometry™ with whole slide modes

Abstract Gaining spatial insights into the cellular composition of tumor tissue has tremendous potential to inform clinical and translational researchers about mechanisms behind spatial predictors of immunotherapy success, disease etiology and progression. Imaging Mass Cytometry™ (IMC™) is a high-plex spatial biology imaging technique that enables deep characterization of the diversity and complexity of the tumor microenvironment (TME). IMC supports detailed assessment of cell phenotype and function using 40-plus metal-tagged antibodies simultaneously on a single slide without issues associated with fluorescence-based spectral overlap, tissue autofluorescence or implementation of multiple washing and acquisition cycles. Currently, IMC enables user-defined regions of interest (ROI) in tissues to evaluate cellular and structural composition. To enhance the IMC user experience, we developed two new whole slide imaging (WSI) modes which enable streamlined workflows using ultrafast preview mode (PM) and high-throughput tissue mode (TM). PM samples the entire tissue at predefined spacing to rapidly capture a low-resolution image of all expressed markers in the antibody panel. PM generates an image in minutes to enable informed ROI placements while leaving the stained tissue intact for higher-resolution imaging. PM and TM are designed so acquisitions can easily occur on the same slide without additional processing steps. TM rapidly acquires images of the whole tissue at lower resolution (7 μm pixel size) at a quality that can be used for quantitative analysis of the tissue spatial biology. Specifically designed for high-throughput applications, TM in combination with a newly available 40-slide loader for the Hyperion XTi™ Imaging System permits automated and continuous imaging of more than 40 large tissue samples (400 mm2 per tissue) per week. We showcase the application of WSI modes using the newly developed Maxpar® Human Immuno-Oncology IMC Panel Kit. The 31-marker panel was combined with catalog antibodies to create a 40-plus-marker panel that expands the ability to conduct comprehensive high-plex tumor and immune cell profiling. Tumor tissue microarrays (TMA) and whole tumor tissue sections were stained with the expanded panel. Single-cell analysis of selected ROIs, on whole tumor sections and TMAs, guided by PM data successfully provided quantitative analyses of spatial biology at single-cell resolution. In parallel, TM on whole tumor sections followed by pixel-based analysis provided a spatially resolved quantitative assessment of specific tumor and immune components of the TME. This work demonstrates the expanded capabilities of IMC and establishes it as a reliable high-plex spatial biology imaging platform with high-throughput imaging capabilities ideally suited for translational and clinical applications. For Research Use Only. Not for use in diagnostic procedures. Citation Format: Qanber Raza, Thomas D. Pfister, Jyh Yun Chwee, Liang Lim, David Howell, Nikesh Parsotam, David King, Christina Loh. Next generation of spatial biology: High-throughput multiplexed Imaging Mass Cytometry™ with whole slide modes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3800.

Abstract 1450: Novel whole slide imaging modes for imaging mass cytometry reveal cellular and structural composition of mouse glioblastoma

Abstract Mouse tumors have become widely used models in translational research of brain malignancies, helping to address the difficulties related to studying the human brain. Mouse brain can be regarded as a miniaturized model of the human brain, permitting visualization of the whole tissue to provide spatial cellular context. Imaging Mass Cytometry™ (IMC™) is a highly relevant tool capable of quantitative evaluation of the multiparametric protein composition in brain tumor microenvironment (TME) without the complications of autofluorescence, tissue degradation, and spectral overlap. The Hyperion XTi™ Imaging System (Standard BioTools™) utilizes IMC technology to simultaneously assess more than 40 individual structural and functional markers in tissue, providing insight into the organization and function of the TME. We demonstrate the whole slide imaging (WSI) application using a 40-marker panel composed of the Maxpar OnDemand™ Mouse Immuno-Oncology IMC Panel Kit and the Maxpar® Neuro Phenotyping IMC Panel Kit on mouse normal and glioblastoma (GBM) brain tissue. The panel was composed of mouse-specific antibodies, which highlight tumor and immune components of the mouse TME. We performed imaging using two new features of Hyperion™ XTi. Ultrafast preview mode (PM) was applied to rapidly screen entire brain sections for marker expression signatures associated with various immuno-oncology processes. This enabled biomarker-guided selection of areas in tumor tissue that were imaged using region of interest-based IMC and analyzed using single-cell analysis (SCA). In parallel, a high-throughput tissue mode (TM) was applied to perform a detailed whole-slide scan of normal and GBM mouse brain tissues that were quantified using pixel-based analysis (PBA) to unravel the composition of the TME. Using TM, we were able to successfully visualize the entire coronal and sagittal sections of normal mouse brain as well as mouse GBM tissue. PBA on TM data provided quantitative spatial expression patterns of structural and immune markers across the whole tissue. In normal tissue, we visualized the highly organized structure of the normal brain and detected neurons, oligodendrocytes, vascular-adjacent astrocytes, and axonal tracks. In GBM tissue, necrotic cores, areas with high immune infiltration, extracellular matrix deposits, and activated tumor cells were detected. SCA of GBM tissue demonstrated expansive vascularization, replicating Olig2+ cells, activation of Ras signaling, and high abundance of infiltrating immune cells. Overall, we demonstrate the successful application of two novel WSI modes and highlight the power of IMC technology to simultaneously explore dozens of relevant biological outputs to better understand the TME of GBM and other tumors. For research use only. Not for use in diagnostic procedures. Citation Format: Qanber Raza, Nick Zabinyakov, Thomas D. Pfister, Nikesh Parsotam, David Howell, Liang Lim, Christina Loh. Novel whole slide imaging modes for imaging mass cytometry reveal cellular and structural composition of mouse glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1450.

Abstract 4169: A deep learning approach to guide acquisition region selection for imaging mass cytometry

Abstract The growth in cancer immunotherapy agents requires an understanding of the immune contexture of the tumor microenvironment. This can be aided by high-plex imaging and analysis to obtain phenotypes of specific cells and study their biodistribution and interactions. Imaging Mass Cytometry™ (IMC) is the method of choice for single-step staining and high-plex imaging of tissues, avoiding the complications of autofluorescence and cyclic imaging. IMC has expanded its capabilities with three distinct imaging modes: Preview, Cell, and Tissue. The Preview Mode is a rapid scanning system that captures a comprehensive overview of the stained tissue, mapping out the distribution of over 40 markers and revealing tissue heterogeneity. This enables researchers to make informed decisions about which areas warrant closer examination on the same. Building on this, Cell Mode offers high-resolution imaging for detailed analysis of the Regions of Interest (ROI) identified during Preview, all using the same slide. Tissue Mode complements these by providing a fast acquisition of the entire tissue at a lower resolution, which is optimal for quantitative pixel-based analysis of tissue biology. These modes support automated, continuous imaging of more than 40 large tissue samples (400 mm2) weekly. Following Preview Mode, the selection of ROIs for high-resolution imaging is a critical step, enhanced by automated AI algorithms to ensure it is informed by biomarker expression. Tissue sections of colon adenocarcinoma were stained with a 30-marker IMC panel of structural, tumor, stroma, immune cell, and immune activation markers. Images were acquired on Hyperion XTi™ (Standard BioTools), first in Preview Mode, then in Cell Mode with automatic selection of ROIs using Phenoplex™ (Visiopharm). ROIs were automatically selected based on two criteria: 1) actively proliferating and non-proliferating tumor regions; 2) cold and hot tumor regions as identified by hotspots of lymphoid and myeloid immune markers within stromal or epithelial tumor regions. Single cell analysis of the high-resolution images obtained in Cell Mode, was performed as a multi-step workflow using Phenoplex. Tissue segmentation was used to divide the tissue into epithelial tumor (E-Cadherin/panCK), stromal, and tumor margin regions; cell segmentation was based on Iridium DNA channels; and phenotyping was performed using the guided highplex workflow. These data were used to compare the immune contexture through a series of t-SNE plots partitioned by spatial region and clinical variables. This work demonstrates that the multi-modal features of Hyperion XTi can greatly accelerate the ability of IMC users to gain useful insights from complex biological samples. Phenoplex enables a comprehensive workflow for the analysis of this complex data, providing automated ROI selection, and phenotyping and spatial analyses of high-resolution IMC images for biological assessment. Citation Format: Fabian Schneider, Smriti Kala, Sam Lim, Clinton Hupple, Nina Lane, James Robert Mansfield. A deep learning approach to guide acquisition region selection for imaging mass cytometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4169.

Abstract 5501: Novel whole slide imaging modes for imaging mass cytometry unveil extensive cellular heterogeneity in human glioma

Abstract Gliomas present a complex form of cancer that is challenging to diagnose and treat, with a median survival of just over one year after diagnosis for primary glioblastoma (GBM). GBM can occur as multi-lesion, remote, or diffuse tumors, and often contains a tumor microenvironment (TME) that is devoid of peripheral immune cells. Additional hallmark features of GBM include necrosis, hemorrhage, and pseudo palisades, making it a highly heterogeneous disease requiring further investigation. Identification of the cellular and spatial level composition of the TME is vital for interpretation of GBM disease origin, progression, prediction, and treatment. A 40-plus-marker neuro-oncology Imaging Mass Cytometry™ (IMC™) antibody panel was used to determine the cellular and structural landscape of the brain TME. We applied the panel on a tissue microarray (TMA) containing dozens of human glioma cores and uncovered the spatial distribution of over 40 distinct molecular markers. We performed imaging using two new features of the Hyperion XTi™ Imaging System that provide whole slide scanning capabilities. Ultrafast preview mode was applied to rapidly screen tumor cores for expression signatures associated with tumor immuno-oncology processes. This enabled biomarker-guided selection of areas in tumor tissue that were imaged at higher resolution and analyzed using single-cell analysis. In parallel, a high-throughput tissue mode was applied to perform a detailed scan of the brain tumor TMA followed by pixel-based analysis to unravel the spatial composition of the TME. Using tissue mode imaging, we successfully mapped the spatial location of cell populations making up human gliomas, such as neurons, astrocytes, microglia, and oligodendrocytes, across the entire TMA. Various tumor cell phenotypes, resident and infiltrating cells, and resting and activated microglia were detected across all TMA cores. Subsequent single-cell analysis of select regions of interest provided a quantitative assessment of the cellular composition of the brain TME. We classified the distinct states of neurons and quantified myeloid and lymphoid immune cell infiltration across normal, astrocytoma, and GBM tissues. Striking cellular and protein heterogeneity was observed between acquired cores, indicating the complexity of each case that is impossible to capture with low-plex visualization techniques. Therefore, IMC is a highly relevant tool capable of quantitative spatial evaluation of the high-plex protein composition in the brain TME without the complications of autofluorescence, tissue degradation, and spectral overlap. Empowered by the neuro-oncology panel and new whole slide imaging modes, IMC accelerates neurological research and provides insights into the spatial complexity of gliomas and other tumors. For research purpose only. Not for use in diagnostic procedures. Citation Format: Nick Zabinyakov, Qanber Raza, Thomas D. Pfister, Nikesh Parsotam, David Howell, Liang Lim, Christina Loh. Novel whole slide imaging modes for imaging mass cytometry unveil extensive cellular heterogeneity in human glioma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5501.

Participation of calcium-permeable AMPA receptors in the regulation of epileptiform activity of hippocampal neurons.

Epileptiform activity is the most striking result of hyperexcitation of a group of neurons that can occur in different brain regions and then spread to other sites. Later it was shown that these rhythms have a cellular correlate in vitro called paroxysmal depolarization shift (PDS). In 13-15 DIV neuron-glial cell culture, inhibition of the GABA(A) receptors induces bursts of action potential in the form of clasters PDS and oscillations of intracellular Ca2+ concentration ([Ca2+]i). We demonstrate that GABAergic neurons expressing calcium-permeable AMPA receptors (CP-AMPARs) as well as Kv7-type potassium channels regulate hippocampal glutamatergic neurons' excitability during epileptiform activity in culture. A combination of whole-cell patch-clamp in current clamp mode and calcium imaging microscopy was used to simultaneously register membrane potential and [Ca2+]i level. To identify GABAergic cell cultures were fixed and stained with antibodies against glutamate decarboxylase GAD 65/67 and neuron-specific enolase (NSE) after vital [Ca2+]i imaging. It was shown that CP-AMPARs are involved in the regulation of the PDS clusters and [Ca2+]i pulses accompanied them. Activation of CP-AMPARs of GABAergic neurons is thought to cause the release of GABA, which activates the GABA(B) receptors of other GABAergic interneurons. It is assumed that activation of these GABA(B) receptors leads to the release of beta-gamma subunits of Gi protein, which activate potassium channels, resulting in hyperpolarization and inhibition of these interneurons. The latter causes disinhibition of glutamatergic neurons, the targets of these interneurons. In turn, the CP-AMPAR antagonist, NASPM, has the opposite effect. Measurement of membrane potential in GABAergic neurons by the patch-clamp method in whole-cell configuration demonstrated that NASPM suppresses hyperpolarization in clusters and individual PDSs. It is believed that Kv7-type potassium channels are involved in the control of hyperpolarization during epileptiform activity. The blocker of Kv7 channels, XE 991, mimicked the effect of the CP-AMPARs antagonist on PDS clusters. Both drugs increased the duration of the PDS cluster. In turn, the Kv7 activator, retigabine, decreased the duration of the PDS cluster and Ca2+ pulse. In addition, retigabine led to deep posthyperpolarization at the end of the PDS cluster. The Kv7 channel is believed to be involved in the formation of PDS, as the channel blocker reduced the rate of hyperpolarization in the PDS almost three times. Thus, GABAergic neurons expressing CP-AMPARs, regulate the membrane potential of innervated glutamatergic neurons by modulating the activity of postsynaptic potassium channels of other GABAergic neurons.

GPS displacement dataset for the study of elastic surface mass variations

Abstract. Quantification of uncertainty in surface mass change signals derived from Global Positioning System (GPS) measurements poses challenges, especially when dealing with large datasets with continental or global coverage. We present a new GPS station displacement dataset that reflects surface mass load signals and their uncertainties. We assess the structure and quantify the uncertainty of vertical land displacement derived from 3045 GPS stations distributed across the continental US. Monthly means of daily positions are available for 15 years. We list the required corrections to isolate surface mass signals in GPS estimates and screen the data using GRACE(-FO) as external validation. Evaluation of GPS time series is a critical step, which identifies (a) corrections that were missed, (b) sites that contain non-elastic signals (e.g., close to aquifers), and (c) sites affected by background modeling errors (e.g., errors in the glacial isostatic model). Finally, we quantify uncertainty of GPS vertical displacement estimates through stochastic modeling and quantification of spatially correlated errors. Our aim is to assign weights to GPS estimates of vertical displacements, which will be used in a joint solution with GRACE(-FO). We prescribe white, colored, and spatially correlated noise. To quantify spatially correlated noise, we build on the common mode imaging approach by adding a geophysical constraint (i.e., surface hydrology) to derive an error estimate for the surface mass signal. We study the uncertainty of the GPS displacement time series and find an average noise level between 2 and 3 mm when white noise, flicker noise, and the root mean square (rms) of residuals about a seasonality and trend fit are used to describe uncertainty. Prescribing random walk noise increases the error level such that half of the stations have noise &gt; 4 mm, which is systematic with the noise level derived through modeling of spatially correlated noise. The new dataset is available at https://doi.org/10.5281/zenodo.8184285 (Peidou et al., 2023) and is suitable for use in a future joint solution with GRACE(-FO)-like observations.

Two cases of breast pseudoaneurysm following core biopsy: A very rare complication with different treatment options

Introduction: Breast pseudoaneurysm is a rare complication following breast interventional procedures such as core biopsies and vacuum-assisted biopsies. The occurrence of pseudoaneurysm increases with the conditions of increased breast vascularity like cancer, pregnancy and lactation. Case Report: We present two cases of pseudoaneurysm formation secondary to core biopsies of the breasts. The first patient was an 82-year-old female patient who presented with breast swelling and bruising after multiple clinical core biopsies of the left breast. Our second patient was a 47-year-old lady who presented with a palpable lump following ultrasound-guided core biopsies of the left breast. Ultrasound showed hypoechoic pulsating area with evidence of internal colour flow in connection with a vessel in both cases. Imaging appearances were in keeping with a pseudoaneurysm of the breast. Discussion: Most pseudoaneurysms are secondary to interventional procedures in the breast. Common clinical presentation is a pulsatile, palpable mass at the biopsy site soon after the biopsy or later. On B mode imaging, it presents as a well-circumscribed mass of mixed echogenicity. Typical waveform in spectral Doppler and ‘yin-yang’ sign in colour Doppler is demonstrated with a turbulent internal flow. There are different treatment options to manage pseudoaneurysms of the breast. Conclusion: Pseudoaneurysm of the breast should be considered if a patient presents with a breast mass/lump close to a recent biopsy site. On clinical examination, pulsatility of the mass should raise the suspicion and definite diagnosis can be made with spectral and colour Doppler US scan.

Novel Small Molecule Matrix Screening for Simultaneous MALDI Mass Spectrometry Imaging of Multiple Lipids and Phytohormones.

Most of the traditional matrices cannot simultaneously image multiple lipids and phytohormones, so screening and discovery of novel matrices stand as essential approaches for broadening the application scope of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). In this work, 12 organic small molecule compounds were comprehensively screened and investigated as potential MALDI matrices for simultaneous imaging analysis of various lipids and phytohormones. In the positive ionization mode, p-nitroaniline, m-nitroaniline, and 2-aminoterephthalic acid displayed good performance for the highly sensitive detection of lysophosphatidylcholines (LPCs), phosphatidylcholines (PCs), and triacylglycerols (TGs). Furthermore, p-nitroaniline possessed excellent characteristics of strong ultraviolet absorption and homogeneous cocrystallization, making it a desirable matrix for MALDI-MSI analysis of eight plant hormones. Compared with conventional matrices (2,5-dihydroxybenzoic acid (DHB), α-cyano-4-hydroxycinnamic acid (CHCA), and 9-aminoacridine (9-AA), the use of p-nitroaniline resulted in higher ionization efficiency, superior sensitivity, and clearer imaging images in dual polarity mode. Our research offers valuable guidance and new ideas for future endeavors in matrix screening.

Analysis of Image Data Augmentation in Smart Agriculture

The demand for agricultural production automation in smart agriculture has made deep learning widely used in tasks, e.g., disease identification, weed-crop segment and fruit detection based on image processing. However, in agricultural production environments, there are limitations in data acquisition, so data enhancement technology has also been widely used. This study introduces two data enhancement methods commonly used in smart agriculture, namely image transformation and GAN-based, and analyzes their specific applications and roles in three common task scenarios: disease identification, weed-crop segment, and fruit detection. According to the analysis, the data enhancement is mainly used to deal with class imbalance problems and over-fitting problems, and can significantly improve model performance in specific scenarios; the complexity of tasks and image structures has an impact on the application effects of different methods, and image segmentation tasks. It is necessary to increase the number of image modes, so methods such as GAN-based are adopted. However, due to the complexity of the image, fruit detection uses simple transformation methods to achieve better results. In addition, data enhancement methods designed for specific tasks, such as simulating synthetic images, can also achieve good results. However, data augmentation technology still has mode collapse problems and is too cumbersome in its application, which points out the direction for subsequent research. Overall, this research sorts out the applications of common data enhancement methods, analyzes the characteristics and limitations of these methods, and hopes to provide guidance for subsequent research.