Images Of Sections Research Articles

Peripapillary intrachoroidal cavitation at the crossroads of peripapillary myopic changes.

To analyze the prevalence of peripapillary intra-choroidal cavitation (PICC) in eyes with gamma peripapillary atrophy (γPPA), in eyes with peripapillary staphyloma (PPS) and in those combining γPPA and PPS and to analyze border tissue discontinuity in PICC. This prospective cross-sectional non interventional study included highly myopic eyes. Non-highly myopic eyes were used as control. Radial and linear scans centered on the optic nerve head were performed using spectral-domain optical coherence tomography. Variables were analyzed along the twelve hourly optical coherence tomography sections in both eyes of each subject. A total of 667 eyes of 334 subjects were included: 229 (34.3%) highly myopic eyes and 438 (65.7%) non highly myopic eyes. The mean age of the highly myopic group was 48.99±17.81y. PICC was found in a total of 40 eyes and in 13.2% (29/220) of highly myopic eyes. PICC was found in 10.4% (40/386) of eyes with γPPA, in 20.5% (40/195) of eyes with PPS and in 22.7% (40/176) of those combining γPPA and PPS. All the eyes with PICC showed the co-existence of γPPA and PPS whereas none of the eyes presenting only one of these entities exhibited PICC. A border tissue discontinuity in the γPPA area was found in all eyes with PICC. We confirm the presence of a border tissue discontinuity in the γPPA area of all eyes with PICC. These findings suggest the involvement of mechanical factors in the pathogenesis of PICC which may contribute to PICC-related visual field defects.

The effectiveness of using the software application "geogebra" in the construction of sections

The article provides training in cross-section construction using the GeoGebra software application. In the construction of sections of the GeoGebra software application, the conditions of spatial shapes and bodies of rotation, as well as their coordinate transfer, are fully studied. In order to determine whether students can show the image of sections on spatial bodies, a survey of 24 students on the topic of sections was conducted in Grade 10 "B" of the specialized boarding school "Daryn" in Kentau.In the survey, students were asked to draw a cross-section through given points on parallelepipeds and pyramids. As a result of the survey, it was found that the vast majority of students cannot show cross-section images. In order to compensate for the shortcomings, it was chosen to interpret cross-section imaging for Class 10"B" using the "GeoGebra" software. Effective uses of the "GeoGebra" software have paid off within the prescribed time frame. In particular , we can see an increase in the quality of education by 50% and 86%. Students analyze, prove the idea of change through the visualization process and, as a result, showed a positive conclusion. As a result of the test from students of the 10th grade "B", which was in-depth in the direction of physics and mathematics, the effectiveness of the GeoGebra software was clearly demonstrated.

Detection of chalcopyrite in digital images of copper ore sample sections

Copper ores are mineral formations of natural origin, the concentration of copper or copper compounds in which is sufficient for their commercial mining. Because of this, copper ores are on the list of minerals that are of strategic importance for the sustainable development of the economy and defense capability of Ukraine. In addition, due to the high thermal conductivity, copper and its alloys are widely used for the manufacture of various types of heat exchangers and radiators. The content of copper in ores usually ranges from 1 to 5%; ores containing less than 0.5% copper are unprofitable for processing at the current level of technology. Mining of copper is of strategic importance, as copper is the main material for the production of cable products and other conductive parts in the electrical industry. The efficiency of technological processes in the mining and industry during the production of copper depends on the quality of ores in relation to the content of minerals that contain copper. Copper ore can be considered a heterogeneous material consisting of two homogeneous phases, one phase is host rock, and the other is copper mineral. Modern image processing techniques have allowed as to automate the identification of minerals in ore samples. Automatic recognition and quantification of minerals using X-Ray tomography, scanning electronic microscope, light microscopy, is one of the most important problems in ore processing systems, as the amount of the minerals in the ore must be determined for further processing. A method of segmentation of colour images of sections of test samples of copper ore is proposed to estimate the percentage content of its components in the section of the tested samples. It is based on the use of chalcopyrite colour features in the HSV model. This colour-based segmentation method is proposed to exploit the average value and distribution of HSV colour components of chalcopyrite in an copper ore image. Segmentation parameters are configured. The experimental results of the segmentation of colour images of copper ore slices by the proposed method are analyzed. The effectiveness of the method is checked using synthesized test images. The method provides an absolute error less than 2.5%.

Pore to Core Scale Characterization of Hydraulic Flow Units Using Petrophysical and Digital Rock Analyses

This article illustrates an integrated method for characterizing hydraulic flow units in subsurface reservoirs using multiscale images and petrophysical data analysis from well cores. This method is applied to 35 meters of cores drilled from a Late Jurassic Upper Jubayla Formation outcrop in Saudi Arabia, which is analogous to the lower section of the Arab‐D reservoir. Scanning electron microscope (SEM) imagery, thin‐section petrography, and X‐ray computed tomography (CT) images of whole cores and core plugs are used to visualize and characterize these carbonate rocks across multiple length scales. Core plug porosity and permeability data are used for petrophysical characterization and deriving hydraulic flow units (HFU). The multimodal pore types associated with the HFUs and their connectivity using thin section and SEM image analysis, combined with mercury injection porosimetry are used. Whole‐core CT textures and heterogeneity logs are correlated with HFU and digital image analysis of core plugs. Whole‐core CT data prove to be a highly valuable tool for bridging the scale gap between well data and reservoir models. This methodology can be applied to datasets from a large number of wells, especially when combined with machine learning tools, allowing improved characterization of complex carbonate reservoirs.

Are intravitreal hyperreflective particles alike in eyes with acute toxoplasma chorioretinitis and non-infectious uveitis?

BackgroundTo compare distinctive features of hyperreflective particles observed on spectral-domain optical coherence tomography (OCT) sections in eyes with acute toxoplasma chorioretinitis (TC) and non-infectious uveitis (NIU). MethodsMedical records and the spectral-domain OCT images of the patients with TC and NIU were retrospectively reviewed. The TC and NIU groups were compared in terms of age, sex, mean OCT image quality, mean central macular thickness (CMT), presence of intraretinal fluid (IRF), presence of subretinal fluid (SRF), number of hyperreflective particles in the posterior vitreous area and mean particle measurement in the posterior vitreous area. ResultsNon-infectious uveitis group included nine patients (60 %) with Behcet's uveitis, five patients (33.3 %) with idiopathic posterior uveitis or panuveitis, and the remaining patient (6.7 %) with HLA-B27 associated uveitis. Comparison of the mean age, sex distribution, mean OCT image quality, mean CMT, presence of IRF, presence of SRF and the mean number of hyperreflective particles in the posterior vitreous area between the two groups showed no statistically significant differences (p = 0.085, p = 0.051, p = 0.748, p = 0.431, p = 0.109, p = 0.080 and p = 0.152, respectively). However, the mean length of the hyperreflective particles in the posterior vitreous area was 27.22 ± 8.60 μm in the TC group, and 21.91 ± 3.58 μm in the NIU group, with a significant difference between the two groups (p = 0.036). ConclusionThis pilot study aimed to assess the hyperreflective particles in the posterior vitreous area using spectral-domain OCT images and image processing software. Despite its limitations, such as the small sample size, limited understanding of the nature of hyperreflective particles, and the absence of differentiation between acute and chronic uveitis, our study points out the potential role of the measurement of the hyperreflective particle length located in the posterior vitreous in differentiating the acute infectious versus non-infectious uveitis as the hyperreflective particles tend to be larger in infectious cases.

Treatment Response Assessment in Multiple Myeloma: Histogram Analysis of Total Tumor Apparent Diffusion Coefficient based on Whole-body Diffusion-weighted MR Imaging.

The International Myeloma Working Group (IMWG) consensus criteria for response assessmentin multiple myeloma (MM) has methodological limitations. Whole-body diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) histogram analysis may be complementary to response assessment of MM. To explore the role of histogram analysis of the ADC based on the total tumor volume (ttADC) in response assessment in patients with newly diagnosed MM (NDMM). Retrospective. Thirty-six patients with NDMM. 3.0T/single-shot DWI echo planar imaging (EPI) sequence with an integrated slice-by-slice shimming (iShim) technique. Baseline (median: 1 day before treatment) and post-treatment (median: five cycles of therapy) whole-body DWI were analyzed. A region of interest (ROI) containing lesions on every section of baseline image was drawn to derive the per-patient total tumor data. Post-treatment image analysis was based on the same ROI as the corresponding baseline. Histogram metrics were extracted from both ROIs. Patients were categorized into the very good partial response or better (VGPR+) group and the less than VGPR group per the IMWG response criteria for response assessment. Progression-free survival (PFS) was also calculated. Mann-Whitney test and Fisher's exact or Chi-squared tests, Receiver operating characteristic (ROC) analysis and DeLong test, Kaplan-Meier analysis and Cox proportional hazards model. A two-tailed P-value <0.05 was considered statistically significant. Thirty patients were categorized into the VGPR+ group and six into the less than VGPR group. The ttADC histogram changes between post-treatment and baseline metrics (ΔttADC) revealed significant differences in all percentile values between the VGPR+ and less than VGPR groups. For distinguishing VGPR+, ΔttADC_5th percentile had the largest area under the curve (AUC) (0.950, 95% CI 0.821-0.995). Patients with lower ΔttADC_5th percentile values (cutoff point,188.193) showed significantly longer PFS (HR = 34.911, 95% CI 6.392-190.677). ttADC histogram may facilitate response assessment in patients with NDMM. 3 TECHNICAL EFFICACY: Stage 4.

Application of micro‐CT to resolve textural properties and assess primary sedimentary structures of deep‐marine sandstones

AbstractOver the past decade, there has been growing interest in the sedimentological community to use micro X‐ray computed tomography to analyse microfacies in sediment cores. However, little attention has been paid to the application of micro‐computed tomography in lithified deposits, even though this can allow their texture to be characterised in three dimensions, providing key information about sedimentary structures. A novel application of micro‐computed tomography in lithified sediment‐gravity flow deposits is presented with the objective of characterising their internal 3D sedimentary structures. This technique is applied to three deep‐marine sandstones showing different compositional properties: Cretaceous Gosau Group (Austria), Eocene Hecho Group (Spain) and the Oligocene Annot Formation (France). From micro‐computed tomography data the size of particles and their distribution throughout the sample is reconstructed in 3D permitting a better visualisation of sedimentary textures. Particle distributions computed from micro‐computed tomography are similar to those computed from thin section image analysis, corroborating the reliability of the micro‐computed tomography to evaluate grain‐size trends. Micro‐computed tomography is complemented with micro‐X‐ray fluorescence and thin section petrographic analyses. In cases where mineral composition or grain size are homogeneous or matrix and grains have similar mineral composition, sedimentary structures do not appear visible from micro‐X‐ray fluorescence or thin section analyses. By separating particles based on their computed tomography density, it is possible to isolate the coarsest fraction, highlighting the sedimentary structures. This study demonstrates (i) the potential of micro‐computed tomography in analyses of sedimentary structures from outcrop data and (ii) the importance of the mineralogical composition and degree of grain sorting in assessing the origin of structureless deposits. Considering the importance of visualising sedimentary structures when interpreting depositional processes, micro‐computed tomography is a new and reliable tool to assess the physical properties of sandstones and to analyse their internal 3D sedimentary structures.

Consensus conference statement on fluorescence-guided surgery (FGS) ESSO course on fluorescence-guided surgery

BackgroundFluorescence-guided surgery (FGS) has emerged as an innovative technique with promising applications in various surgical specialties. However, clinical implementation is hampered by limited availability of evidence-based reference work supporting the translation towards standard-of-care use in surgical practice. Therefore, we developed a consensus statement on current applications of FGS. MethodsDuring an international FGS course, participants anonymously voted on 36 statements. Consensus was defined as agreement ≥70% with participation grade of ≥80%. All participants of the questionnaire were stratified for user and handling experience within five domains of applicability (lymphatics & lymph node imaging; tissue perfusion; biliary anatomy and urinary tracts; tumor imaging in colorectal, HPB, and endocrine surgery, and quantification and (tumor-) targeted imaging). Results were pooled to determine consensus for each statement within the respective sections based on the degree of agreement. ResultsIn total 43/52 (81%) course participants were eligible as voting members for consensus, comprising the expert panel (n = 12) and trained users (n = 31). Consensus was achieved in 17 out of 36 (45%) statements with highest level of agreement for application of FGS in tissue perfusion and biliary/urinary tract visualization (71% and 67%, respectively) and lowest within the tumor imaging section (0%). ConclusionsFGS is currently established for tissue perfusion and vital structure imaging. Lymphatics & lymph node imaging in breast cancer and melanoma are evolving, and tumor tissue imaging holds promise in early-phase trials. Quantification and (tumor-)targeted imaging are advancing toward clinical validation. Additional research is needed for tumor imaging due to a lack of consensus.

SPATIAL AND STRUCTURAL COMPLEXITY OF CEREBRAL HEMISPHERES IN MALE AND FEMALE BRAIN: FRACTAL AND QUANTITATIVE ANALYSES OF MRI BRAIN SCANS

Objectives: The aim of the present study was to compare the features of the structural complexity of the cerebral hemispheres in men and women using fractal analysis of outlined and skeletonized images, as well as quantitative analysis of digital skeletons of the cerebral hemispheres. Material and Methods: Magnetic resonance imaging brain scans of 100 individuals aged 18-86 years (44 males and 56 females) were investigated. Five tomographic sections of each brain were selected for morphometric study (4 coronal and 1 axial sections). The sections were preprocessed, and outlined and skeletonized images were obtained. Fractal analysis was conducted using the two-dimensional box counting method, and fractal dimensions of outlined and skeletonized images were determined. Additionally, quantitative analysis of skeletonized images was performed, determining the following parameters: branches, junctions, end-point voxels, junction voxels, slab voxels, triple points, quadruple points, average branch length, and maximum branch length. Results: We observed that both variants of fractal dimension in males and females did not show significant differences, although most quantitative parameters in males were larger than those in females. Conclusions: The spatial and structural complexity of the cerebral hemispheres, as characterized by fractal dimensions, is almost indistinguishable between males and females. However, in some individual tomographic sections, the male brain may exhibit a slightly higher number of end-point voxels, corresponding to the gyri of the cerebral hemispheres. The obtained data can be used in clinical practice for diagnostic purposes (e.g., for detecting malformations) and for theoretical studies in neuroanatomy.

Identification of Ultrastructural Details of the Astrocyte Process System in Nervous Tissue of the Brain Using Correlative Scanning Probe and Transmission Electron Microscopy.

Nanoscale morphological features of branched processes of glial cells may be of decisive importance for neuron-astrocyte interactions in health and disease. The paper presents the results of a correlation analysis of images of thin processes of astrocytes in nervous tissue of the mouse brain, which were obtained by scanning probe microscopy (SPM) and transmission electron microscopy (TEM) with high spatial resolution. Samples were prepared and imaged using a unique hardware combination of ultramicrotomy and SPM. Astrocyte details with a thickness of several tens of nanometers were identifiable in the images, making it possible to reconstruct the three-dimensional structure of astrocytic processes by integrating a series of sequential images of ultrathin sections of nervous tissue in the future.

Asymmetric All-Femtosecond Laser–Cut Corneal Allogenic Intrastromal Ring Segments

Purpose: To describe a novel technique for cutting asymmetric allogenic segments using the femtosecond laser for the management of cases of keratoconus with non-coinciding astigmatism and coma axes. Methods: Four eyes of 2 patients with irregular keratoconus and asymmetric allogenic segments were included. Visual, refractive, tomographic, and aberrometric outcomes, and optical coherence tomography (OCT) sections were measured preoperatively and 6 months postoperatively. Evaluations included slit-lamp examination, manifest refraction, uncorrected (UDVA) and corrected (CDVA) distance visual acuity, and simulated and maximum anterior keratometry (Kmax) using anterior segment OCT. Results: Spherical and cylindrical refractive errors decreased from −2.38 ± 2.96 and −2.94 ± 2.16 to −1.81 ± 2.77 ( P = .04) and −1.75 ± 2.07 ( P = .01) diopters (D), respectively, 6 months postoperatively. There was an average gain of three lines of CDVA. Kmax decreased from 50.02 ± 1.99 to 47.89 ± 3.05 D (P= .03) and coma from 1.05 ± 0.21 to 0.21 ± 0.19 D ( P = .01). Conclusions: Asymmetric femtosecond laser–cut allogenic segments allow a higher level of customization based on size, shape, and arc length, in contrast to the limited range of available synthetic asymmetrical segments. [ J Refract Surg . 2023;39(12):856–862.]

Spatial mapping of ectonucleotidase gene expression in the murine urinary bladder.

Purinergic signaling is important for normal bladder function, as it is thought to initiate the voiding reflex and modulate smooth muscle tone. The availability of adenine nucleotides and nucleosides (aka purines) at receptor sites of various cell types in the bladder wall is regulated by ectonucleotidases (ENTDs). ENTDs hydrolyze purines such as adenosine 5'-triphosphate (ATP) and adenosine 5'-diphosphate (ADP) with varying preference for the individual substrate. Therefore, the end effect of extracellular purines may depend significantly on the type of ENTD that is expressed in close proximity to the target cells. ENTDs likely have distinct cellular associations, but the specific locations of individual enzymes in the bladder wall are poorly understood. We used RNAscope™, an RNA in situ hybridization (ISH) technology, to visualize the distribution and measure the levels of gene expression of the main recognized ectonucleotidases in large high-resolution images of murine bladder sections. The relative gene expression of ENTDs was Entpd3 > Alpl >> Enpp1 = Entpd2 >> Enpp3 > Entpd1 (very low to no signal) in the urothelium, Entpd1 ≥ Entpd2 >> Enpp3 > Enpp1 = Alpl ≥ Nt5e (very low to no signal) in the lamina propria, and Entpd1 >> Nt5e = Entpd2 >> Enpp1 > Alpl = Enpp3 in the detrusor. These layer-specific differences might be important in compartmentalized regulation of purine availability and subsequent functions in the bladder wall and may explain reported asymmetries in purine availability in the bladder lumen and suburothelium/lamina propria spaces.

Comparison of spin-echo echo planar imaging and gradient-recalled echo sequences in magnetic resonance elastography of liver at 1.5T same MRI scanner.

Magnetic resonance elastography (MRE) is used to measure liver stiffness with gradient-recalled echo (GRE)-based and spin-echo echo planar imaging (SE-EPI)-based sequences. We compared the liver stiffness (LS) values of the two sequences on a 1.5-T MR imaging scanner. This is a retrospective study. An MRE imaging section was obtained from a horizontal section of the liver. Region of interest was drawn on the elastogram, and the mean LS and pixel values were measured and compared. The correlations between proton density fat fraction, R2* values, and biochemical data from electronic medical records were confirmed, and multivariate analysis was performed. The mean LS values were 3.01±1.78kPa for GRE and 3.13±1.57kPa for SE-EPI, showing excellent agreement and a strong correlation between the two sequences (correlation coefficient r=0.96). The mean pixel values were 369.5±142.7 pixels for GRE and 490.1±197.9 pixels for SE-EPI, showing a significant difference by the Wilcoxon rank sum test (p<0.01). There were no LS unmeasurable cases in SE-EPI, but seven (2.5%) were unmeasurable in GRE, and multivariate analysis showed a significant difference with p<0.001 in R2* values (mean, 92.7Hz) for the GRE method. The GRE and SE-EPI methods were comparable for LS measurements in 1.5-T liver MRE, indicating that SE-EPI MRE is more useful because GRE MRE may not measure cases with high R2* values and the region of interest tends to be smaller.

Novel technique for the preparation and analysis of powder-based polished sections by automated optical mineralogy: Part 2 – Use of deep learning approach for transparent mineral detection

Automated reflected light optical microscopy represents an alternative and affordable technique compared to automated scanning electron microscopy for quantitative mineralogical analysis. Polished sections are the commonly used sample analysis format, and it is essential to obtain unbiased mineralogical quantification results from those. However, automated optical microscopy does not allow the detection of transparent minerals during reflected light analysis, as the reflectivity of the resin and these minerals is very similar.This work aims to propose an innovative way to automatically detect all particles and minerals, including transparent minerals, in polished sections with acrylic resin using reflected light optical imaging and a deep learning algorithm. To do so, several ore powders and standard mineral mixes were mounted into acrylic resin polished sections at two different particle sizes: < 1 mm and P80 ∼ 75 µm. Optical images of these polished sections were acquired with an automated reflected light optical microscope to train and test the deep learning algorithm to detect mineral particles. The results suggest that the deep learning algorithm easily detected all mineral particles in the acrylic resin matrix, allowing all minerals particles (including transparent minerals) to be well-differentiated under reflected light optical microscopy, and providing an unbiased mineralogical quantification.

TANet: Transmission and atmospheric light driven enhancement of underwater images

Motivated by the adverse impact of light attenuation and scattering, which leads to color distortion and low contrast in underwater images, our study primarily focuses on enhancement techniques for these images using localized transmission feature analysis and global atmospheric light feature extraction. To this end, we propose a novel approach, named TANet, drawing upon the dynamics of transmission and atmospheric light. TANet integrates two primary components: a spatial domain-based Transmission-Driven Refinement module (TDR) and a frequency domain-based Atmospheric Light Removal Fourier Module (ALRF). The TDR module employs a Gated Multipurpose Unit with dual branches, selectively regulating input features. This allows for a refined merging of feature vectors that subsequently interact, enabling cross-channel feature integration. Capitalizing on the correlation between transmission and image quality, TDR facilitates the detailed enhancement of underwater images by depicting the perceived transmission across distinct image sections. Given that atmospheric light exhibits different attenuation rates under water due to varying wavelengths, and considering that atmospheric light is globally constant, thereby influencing underwater image capture, we developed the ALRF module. This caters to the processing of global information within the frequency domain, efficiently negating atmospheric light’s impact on underwater images and enhancing their quality and visibility. Our TANet’s superior performance is affirmed by extensive experimental results, demonstrating its effectiveness in underwater image enhancement.

Mapping the cytoskeletal architecture of renal tubules and surrounding peritubular capillaries in the kidney.

The human kidney includes ~1 million nephrons which are long U-shaped tubules with convoluted segments that serve as filtration units. During the passage of the ultrafiltrate through a nephron, electrolytes and nutrients are re-absorbed into peritubular capillaries. The fluid remaining in the distal end of the renal tubules flows through the collecting ducts into the ureter. In this study, we generated high-resolution images of mouse kidney sections using confocal microscopy with only two fluorescently tagged biomarkers, F-actin binding phalloidin and CD34 antibodies as a marker for blood vessels. In tile-scan images of entire sections of mouse kidney (composed of >1000 images), the tubule segments are easily identifiable by their F-actin bundles on cell borders and the outlines of the peritubular capillaries by CD34 immunofluorescence. In the inner stripe of the medulla, the vascular bundles composed of vasa recta (straight vessels) could be easily distinguished from the peritubular capillaries by their full circular shapes. The highly vascular inner medulla and the papilla similarly have straight capillaries. About 95% of kidney volume is composed of renal tubules and blood vessels. Thus, our results show that relatively simple cytoskeletal mapping can be used to visualize the structural organization of the kidney. This method can also be applied to examine pathological changes in the kidney.

Deep Learning Based Feature Selection and Ensemble Learning for Sintering State Recognition.

Sintering is a commonly used agglomeration process to prepare iron ore fines for blast furnace. The quality of sinter significantly impacts the blast furnace ironmaking process. In the vast majority of sintering plants, the judgment of sintering quality still relies on the intuitive observation of the cross section at sintering machine tail by operators, which is susceptible to the external environment and the experience of operators. In this paper, we propose a new sintering state recognition method using deep learning based feature selection and ensemble learning. First, features from the infrared thermal images of sinter cross section at the tail of the sinterer are extracted based on ResNeXt. Then, to eliminate the irrelevant, redundant and noisy features, an efficient feature selection method based on binary state transition algorithm (BSTA) is proposed to find the truly useful features. Subsequently, an ensemble learning (EL) method based on group decision making (GDM) is proposed to recognize the sintering states. Novel combination strategies considering the varying performance of the base learners are designed to further improve recognition accuracy. Industrial experiments conducted at a steel plant verify the effectiveness and superiority of the proposed method.

Neural Degeneration in Normal-Aging Human Cochleas: Machine-Learning Counts and 3D Mapping in Archival Sections.

Quantifying the survival patterns of spiral ganglion cells (SGCs), the cell bodies of auditory-nerve fibers, is critical to studies of sensorineural hearing loss, especially in human temporal bones. The classic method of manual counting is tedious, and, although stereology approaches can be faster, they can only be used to estimate total cell numbers per cochlea. Here, a machine-learning algorithm that automatically identifies, counts, and maps the SGCs in digitized images of semi-serial human temporal-bone sections not only speeds the analysis, with no loss of accuracy, but also allows 3D visualization of the SGCs and fine-grained mapping to cochlear frequency. Applying the algorithm to 62 normal-aging human ears shows significantly faster degeneration of SGCs in the basal than the apical half of the cochlea. Comparison to fiber counts in the same ears shows that the fraction of surviving SGCs lacking a peripheral axon steadily increases with age, reaching more than 50% in the apical cochlea and almost 66% in basal regions.

IMMU-25. ANALYSIS OF IMMUNOSUPPRESSIVE MYELOID CELLS IN THE GLIOBLASTOMA TUMOR MICROENVIRONMENT REVEALS THERAPEUTICALLY TARGETABLE IMMUNOMODULATORY SIGNALS ACROSS POPULATIONS

Abstract Immunosuppression in glioblastoma (GBM) remains a critical and poorly understood barrier to the development of effective novel therapies. Increasing evidence points to the critical role of immunosuppressive myeloid cells in the immunosuppressive tumor microenvironment and an intriguing target for ameliorating tumor-mediated immune suppression. Efforts to characterize the myeloid milieu in the tumor microenvironment have revealed a highly heterogenous population of cells with the capacity to exert immunosuppressive effects. In order to maximize the efficacy of potential therapeutic targets, we sought to identify immune checkpoint markers expressed across a range of immunomodulatory myeloid cell populations in the tumor microenvironment of patients undergoing resection for GBM. Freshly collected ultrasonic aspirate obtained during the primary surgery for GBM resection (based on preoperative imaging and intraoperative frozen section, later confirmed on final pathology) was prepared for high dimensional flow cytometry to quantify the immune checkpoint marker expression profile of a number of described immunosuppressive myeloid cell populations, including both monocytic and granulocytic myeloid-derived suppressor cells (mMDSC and gMDSC), and CD16+ non-classical monocytes (NCM). mMDSCs expressed particularly high levels of TIGIT (53.9±19.27%), which was also highly expressed in the NCM population (25.03±5.44%). NCMs also demonstrated high levels of B7H3 expression (39.85±18.05%), which has recently been implicated as an important immune checkpoint protein in GBM. gMDSCs demonstrated a rather different expression profile, with significantly higher levels of VISTA expression than other immunomodulatory markers (p&amp;lt; 0.05). These findings underscore the diversity of immunomodulatory signaling in the tumor-associated myeloid cell compartment, emphasizing the challenges in developing single-target immune checkpoint inhibitor therapy in GBM. Nevertheless, this data points to some common patterns of expression across major immunomodulatory cell populations that remain understudied in GBM and could herald more promising avenues of immunotherapy development.

Geometric and topological characterization of the cytoarchitecture of islets of Langerhans.

The islets of Langerhans are critical endocrine micro-organs that secrete hormones regulating energy metabolism in animals. Insulin and glucagon, secreted by beta and alpha cells, respectively, are responsible for metabolic switching between fat and glucose utilization. Dysfunction in their secretion and/or counter-regulatory influence leads to diabetes. Debate in the field centers on the cytoarchitecture of islets, as the signaling that governs hormonal secretion depends on structural and functional factors, including electrical connectivity, innervation, vascularization, and physical proximity. Much effort has therefore been devoted to elucidating which architectural features are significant for function and how derangements in these features are correlated or causative for dysfunction, especially using quantitative network science or graph theory characterizations. Here, we ask if there are non-local features in islet cytoarchitecture, going beyond standard network statistics, that are relevant to islet function. An example is ring structures, or cycles, of α and δ cells surrounding β cell clusters or the opposite, β cells surrounding α and δ cells. These could appear in two-dimensional islet section images if a sphere consisting of one cell type surrounds a cluster of another cell type. To address these issues, we developed two independent computational approaches, geometric and topological, for such characterizations. For the latter, we introduce an application of topological data analysis to determine locations of topological features that are biologically significant. We show that both approaches, applied to a large collection of islet sections, are in complete agreement in the context both of developmental and diabetes-related changes in islet characteristics. The topological approach can be applied to three-dimensional imaging data for islets as well.