Morphological Signatures Research Articles

Mineralogical and geochemical constraints on the origin of alunite and APS minerals from advanced argillic alteration systems: A case study from Kuh-e-Lakht Au-Ag-Cu mineralization, NE Isfahan, Iran

A significant association of alunite supergroup minerals commonly associated with quartz and pyrite is found in the Kuh-e-Lakht district of NE Isfahan, Iran. These minerals occur as pervasive alterations and within hydrothermal quartz veins. Based on field observations, microscopic studies, and geochemical analyses, the alunite subgroup exhibits noticeable variations in morphology, composition, and geochemical signatures between areas with moderate to high mineralization and those with poor mineralization. Poorly mineralized regions contain aluminum-phosphate-sulfate (APS)-free minerals of the alunite subgroup formed from steam-heated acid or supergene processes at an estimated temperature of about 200 °C, with a higher K2O than Na2O content. These crystals exhibit pseudocubic or acicular habits and zoned formations with rhythmic bands and lack APS minerals. Moderately to highly mineralized areas in Kuh-e-Lakht host tabular to platy and bladed alunite subgroup crystals with a hypogene origin, formed at around 250 °C, characterized by a higher or equal Na2O content compared to K2O. These areas also feature APS minerals with different modes of occurrence. In the southwestern, north-central, and northwestern parts, a strong genetic link with high-sulfidation minerals like pyrite, enargite, and chalcopyrite is observed. Alunite subgroup crystals with the highest Na2O/K2O ratio or equal values, as well as APS minerals with svanbergite-woodhouseite composition, occur within alunite crystals or as individual euhedral crystals exhibiting complex oscillatory zoning. These characteristics confirm a close association with the ore formation period and also the influence of higher-temperature fluids with magmatic-hydrothermal components, likely originating in closer proximity to intrusive sources. The estimated temperature for the alunite subgroup and associated ore minerals in these areas falls in the range of approximately 250 °C to 300 °C.

Kinematic modeling of neotectonic thrusts at the Andean orogenic front (southern Precordillera, Argentina)

The south-central Andes located between 32°-33° S are considered to be a transitional zone between the flat-lying and the normal subduction zones of the Nazca Plate. The active mountain-building processes are mainly concentrated between the Andean eastern foothills and the adjacent broken foreland, as highlighted by crustal seismicity, historic destructive earthquakes, and Quaternary-active contractional structures. Between 32° 10′ and 32° 40′ S, the Andean orogenic front is exposed at the Las Peñas-Las Higueras range, where east- and west-verging thrusts interact, resulting in an antithetic linkage transfer zone. We built kinematically-balanced structural sections through the integration of surface and subsurface data (2D seismic lines) to achieve a 3D characterization of the Quaternary-active thrusts and to estimate shortening rates of ∼1.8–3.4 mm/a during the last ∼8.5 Ma, thus extending the spatial and temporal penetration achieved by surface geology data. Our results indicate that the main east-verging thrusts detach at a depth of ∼10 km within Paleozoic basement rocks. This outcome implies larger potential rupture areas than if rooted at Neogene layers. West-verging thrusts present detachment levels at ∼5 km, also linked to Paleozoic basement rocks. The analysis of 2D seismic lines has also contributed to the recognition of blind thrusts without a morphologic signature, which could be regarded as relevant seismogenic structures.

Abstract 6934: Integrating deep learning morphology profiling, cell sorting, and scRNASeq reveals sample diversity and enriched sub-populations

Abstract Advances in single cell technologies have ushered in a new multi-omics era that has provided more granular information on cell types and functions at unprecedented resolution. Morpholomics (the information encoded by cell morphology) has traditionally been used as a readout of cell identity, state, and function; but scalability, interpretation, and sorting based on morphology has remained challenging. The Deepcell® platform, REM-I, performs high-dimensional morphology analysis of unlabeled, single cells using deep-learning on high-resolution bright-field images captured in microfluidic flow to profile and sort target cells in real-time and at scale. Morphology analysis of single cells is achieved by a self-supervised deep learning foundation model, ‘Human Foundation Model’ (HFM), which combines deep learning features with morphometrics. HFM determines cell identities using morphological features associated with distinct processes characterized by granules, vesicles, cell size, pigmentation. and others. To demonstrate the ability of HFM modeling to distinguish and characterize a diversity of cell types representative of tumor microenvironments, we processed various sample types on the REM-I platform. Human melanoma, immune cells, stromal cells, and dissociated biopsies were combined to recapitulate heterogeneous tumor samples. HFM analysis enabled morphology-based exploration of the resulting bright-field images, revealing the presence of various morphologically distinct populations within each sample. Tumor cells were morphologically distinct and clustered separately from non-tumor cells. Immune cells exhibited subtle but separable morphologies, including T cells of distinct activation states. To demonstrate the morphology-based sorting capabilities of REM-I, we applied it to a ‘reference sample’ consisting of several fixed cell lines, at proportions ranging from 1% to >90%. Using only brightfield images of single cells analyzed through HFM, we used the platform to enrich each cell line from the ‘reference sample’ with high yield and purity, and identified cell types constituting a small percentage (~1%) of the total population. We next showed that unlabeled cells enriched on REM-I that are characterized as unperturbed and viable are amenable to downstream molecular analyses. These cell populations were sorted and the retrieved live cells were analyzed by scRNA-Seq (10x Chromium), demonstrating enrichment of various cell types of the tumor microenvironment in each cell population relative to the pre-sorted sample. These results illustrate: 1) the ability to perform downstream molecular analyses on sorted cells from REM-I, 2) the platform can be used to parse the tumor microenvironment, and 3) the link between morphology, cell identity, and molecular signatures. Citation Format: Andreja Jovic, Christian Corona, Kiran Saini, Tiffine Pham, Ryan Carelli, Vivian Lu, Senzeyu Zhang, Stephane C. Boutet, Maddison Masaeli. Integrating deep learning morphology profiling, cell sorting, and scRNASeq reveals sample diversity and enriched sub-populations [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 6934.

Abstract 2304: Detection of early-disseminated cancer cells with deep learning-enabled holographic imaging

Abstract Recent research increasingly validates the early dissemination of tumor cells in peripheral blood during the nascent stages of cancer, often preceding clinical identification of the primary tumor. This emerging evidence emphasizes the potential of Circulating Tumor Cells (CTCs) as early indicators for cancer. Despite their significance, CTCs are exceptionally rare compared to normal blood cells, which presents a considerable challenge in detection, particularly during early stages of cancer. Traditional detection methods, such as those based on nucleated cell enrichment, antibody labeling and fluorescence imaging, encounter notable limitations when applied in the context of early detection. These limitations arise from the inherent heterogeneity of CTCs, and the multistep process involved in labeling and manual enumeration, compromising cell viability and resulting in cell loss. This loss becomes particularly problematic in the context of early cancer detection scenarios where the tumor burden is extremely low, and any cell loss can significantly impact assay sensitivity. To overcome these challenges, we propose an innovative CTC detection approach employing a deep learning framework combined with holographic imaging. This technique utilizes coherent light to generate holograms from cell samples, capturing detailed 3D morphological and optical properties of individual cells. We developed a custom convolutional neural network designed to facilitate high-throughput cell sorting in real-time. Trained on healthy blood samples and diverse cancer cell lines, the dataset consists of more than 50 million cellular holograms enhanced by proprietary Gaussian annotation and image augmentation strategies. Moreover, by combining the morphological signatures from holography with antigen signatures (e.g. HER2/ER/PR) in real-time, our model demonstrates the ability to detect less than 1 false positive per 1 million nucleated cells, highlighting its potential as a robust tool for targeted early-stage breast cancer detection. Our technology represents highly sensitive alternative to traditional screening methods, with the promise of enhancing patient outcomes. Citation Format: Nicholas Heller, Kevin Mallery, Nathaniel Bristow, Yash Travadi, Eng Hock Lee, Jiarong Hong. Detection of early-disseminated cancer cells with deep learning-enabled holographic imaging [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 2304.

Morphological profiling in human neural progenitor cells classifies hits in a pilot drug screen for Alzheimer's disease.

Alzheimer's disease accounts for 60-70% of dementia cases. Current treatments are inadequate and there is a need to develop new approaches to drug discovery. Recently, in cancer, morphological profiling has been used in combination with high-throughput screening of small-molecule libraries in human cells in vitro. To test feasibility of this approach for Alzheimer's disease, we developed a cell morphology-based drug screen centred on the risk gene, SORL1 (which encodes the protein SORLA). Increased Alzheimer's disease risk has been repeatedly linked to variants in SORL1, particularly those conferring loss or decreased expression of SORLA, and lower SORL1 levels are observed in post-mortem brain samples from individuals with Alzheimer's disease. Consistent with its role in the endolysosomal pathway, SORL1 deletion is associated with enlarged endosomes in neural progenitor cells and neurons. We, therefore, hypothesized that multi-parametric, image-based cell phenotyping would identify features characteristic of SORL1 deletion. An automated morphological profiling method (Cell Painting) was adapted to neural progenitor cells and used to determine the phenotypic response of SORL1-/- neural progenitor cells to treatment with compounds from a small internationally approved drug library (TargetMol, 330 compounds). We detected distinct phenotypic signatures for SORL1-/- neural progenitor cells compared to isogenic wild-type controls. Furthermore, we identified 16 compounds (representing 14 drugs) that reversed the mutant morphological signatures in neural progenitor cells derived from three SORL1-/- induced pluripotent stem cell sub-clones. Network pharmacology analysis revealed the 16 compounds belonged to five mechanistic groups: 20S proteasome, aldehyde dehydrogenase, topoisomerase I and II, and DNA synthesis inhibitors. Enrichment analysis identified DNA synthesis/damage/repair, proteases/proteasome and metabolism as key pathways/biological processes. Prediction of novel targets revealed enrichment in pathways associated with neural cell function and Alzheimer's disease. Overall, this work suggests that (i) a quantitative phenotypic metric can distinguish induced pluripotent stem cell-derived SORL1-/- neural progenitor cells from isogenic wild-type controls and (ii) phenotypic screening combined with multi-parametric high-content image analysis is a viable option for drug repurposing and discovery in this human neural cell model of Alzheimer's disease.

Investigating the impact of vitrification on bovine ovarian tissue morphology, follicle survival, and transcriptomic signature

PurposeOvarian tissue cryopreservation is vital for fertility preservation, yet its effect on ovarian tissue follicle survival and transcriptomic signature requires further investigation. This study delves into the effects of vitrification on tissue morphology, function, and transcriptomic changes, helping to find possibilities for vitrification protocol improvements.MethodsOvarian cortex from 19 bovine animals were used to conduct pre- and post-vitrification culture followed by histological assessment, immunohistochemistry, and TUNEL assay. Follicles’ functionality was assessed for viability and growth within the tissue and in isolated cultures. RNA-sequencing of ovarian tissue was used to explore the transcriptomic alterations caused by vitrification.ResultsFollicle density, cell proliferation, and DNA damage in ovarian stroma were unaffected by vitrification. However, vitrified cultured tissue exhibited reduced follicle density of primordial/primary and antral follicles, while freshly cultured tissue manifested reduction of antral follicles. Increased stromal cell proliferation and DNA damage occurred in both groups post-culture. Isolated follicles from vitrified tissue exhibited similar viability to fresh follicles until day 4, after which the survival dropped. RNA-sequencing revealed minor effects of vitrification on transcriptomic signatures, while culture induced significant gene expression changes in both groups. The altered expression of WNT and hormonal regulation pathway genes post-vitrification suggests the molecular targets for vitrification protocol refinement.ConclusionVitrification minimally affects tissue morphology, follicle density, and transcriptomic signature post-thawing. However, culture revealed notable changes in vitrified tissue samples, including reduced follicle density, decreased isolated follicle survival, and alteration in WNT signalling and ovarian hormonal regulation pathways, highlighted them as possible limitations of the current vitrification protocol.

Longitudinal reduction in brain volume in patients with schizophrenia and its association with cognitive function.

Establishing a brain biomarker for schizophrenia is strongly desirable not only to support diagnosis by psychiatrists but also to help track the progressive changes in the brain over the course of the illness. A brain morphological signature of schizophrenia was reported in a recent study and is defined by clusters of brain regions with reduced volume in schizophrenia patients compared to healthy individuals. This signature was proven to be effective at differentiating patients with schizophrenia from healthy individuals, suggesting that it is a good candidate brain biomarker of schizophrenia. However, the longitudinal characteristics of this signature have remained unclear. In this study, we examined whether these changes occurred over time and whether they were associated with clinical outcomes. We found a significant change in the brain morphological signature in schizophrenia patients with more brain volume loss than the natural, age-related reduction in healthy individuals, suggesting that this change can capture a progressive morphological change in the brain. We further found a significant association between changes in the brain morphological signature and changes in the full-scale intelligence quotient (IQ). The patients with IQ improvement showed preserved brain morphological signatures, whereas the patients without IQ improvement showed progressive changes in the brain morphological signature, suggesting a link between potential recovery of intellectual abilities and the speed of brain pathology progression. We conclude that the brain morphological signature is a brain biomarker that can be used to evaluate progressive changes in the brain that are associated with cognitive impairment due to schizophrenia.

Associations Between Hyperactive Neuropsychiatric Symptoms and Brain Morphology in Mild Cognitive Impairment and Alzheimer's Disease.

Hyperactive neuropsychiatric symptoms (NPS) (i.e., agitation, disinhibition, and irritability) are among the most challenging symptoms to manage in Alzheimer's disease (AD). However, their underlying brain correlates have been poorly studied. We aimed to investigate the associations between the total score of hyperactive NPS and brain structures in participants with AD, mild cognitive impairment (MCI), and cognitively normal older adults (CN). Neuropsychiatric and 3T MRI data from 216 AD, 564 MCI, and 660 CN participants were extracted from the Alzheimer's Disease Neuroimaging Initiative database. To define NPS and brain structures' associations, we fitted a general linear model (GLM) in two ways: 1) an overall GLM including all three groups (AD, MCI, CN) and 2) three pair-wise GLMs (AD versus MCI, MCI versus CN, AD versus CN). The cortical changes as a function of NPS total score were investigated using multiple regression analyses. Results from the overall GLM include associations between 1) agitation and the right parietal supramarginal surface area in the MCI-CN contrast, 2) disinhibition and the cortical thickness of the right frontal pars opercularis and temporal inferior in the AD-MCI contrast, and 3) irritability and the right frontal pars opercularis, frontal superior, and temporal superior volumes in the MCI-CN contrast. Our study shows that each hyperactive NPS is associated with distinct brain regions in AD, MCI, and CN (groups with different levels of cognitive performance). This suggests that each NPS is associated with a unique signature of brain morphology, including variations in volume, thickness, or area.

Parallel evolution of morphological and genomic selfing syndromes accompany the breakdown of heterostyly.

Evolutionary transitions from outcrossing to selfing in flowering plants have convergent morphological and genomic signatures and can involve parallel evolution within related lineages. Adaptive evolution of morphological traits is often assumed to evolve faster than nonadaptive features of the genomic selfing syndrome. We investigated phenotypic and genomic changes associated with transitions from distyly to homostyly in the Primula oreodoxa complex. We determined whether the transition to selfing occurred more than once and investigated stages in the evolution of morphological and genomic selfing syndromes using 22 floral traits and both nuclear and plastid genomic data from 25 populations. Two independent transitions were detected representing an earlier and a more recently derived selfing lineage. The older lineage exhibited classic features of the morphological and genomic selfing syndrome. Although features of both selfing syndromes were less developed in the younger selfing lineage, they exhibited parallel development with the older selfing lineage. This finding contrasts with the prediction that some genomic changes should lag behind adaptive changes to morphological traits. Our findings highlight the value of comparative studies on the timing and extent of transitions from outcrossing to selfing between related lineages for investigating the tempo of morphological and molecular evolution.

Signatures of Massive Black Hole Merger Host Galaxies from Cosmological Simulations. I. Unique Galaxy Morphologies in Imaging

Low-frequency gravitational-wave experiments such as the Laser Interferometer Space Antenna and pulsar timing arrays are expected to detect individual massive black hole (MBH) binaries and mergers. However, secure methods of identifying the exact host galaxy of each MBH merger among the large number of galaxies in the gravitational-wave localization region are currently lacking. We investigate the distinct morphological signatures of MBH merger host galaxies, using the Romulus25 cosmological simulation. We produce mock telescope images of 201 simulated galaxies in Romulus25 hosting recent MBH mergers through stellar population synthesis and dust radiative transfer. Based on comparisons to mass- and redshift-matched control samples, we show that combining multiple morphological statistics via a linear discriminant analysis enables identification of the host galaxies of MBH mergers, with accuracies that increase with chirp mass and mass ratio. For mergers with high chirp masses (≳108.2 M ⊙) and high mass ratios (≳0.5), the accuracy of this approach reaches ≳80%, and does not decline for at least ∼1 Gyr after numerical merger. We argue that these trends arise because the most distinctive morphological characteristics of MBH merger and binary host galaxies are prominent classical bulges, rather than relatively short-lived morphological disturbances from their preceding galaxy mergers. Since these bulges are formed though major mergers of massive galaxies, they lead to (and become permanent signposts for) MBH binaries and mergers that have high chirp masses and mass ratios. Our results suggest that galaxy morphology can aid in identifying the host galaxies of future MBH binaries and mergers.

Geospatial Analysis for Tectonic Assessment and Soil Erosion Prioritization: A Case Study of Wadi Al-Lith, Red Sea Coast, Saudi Arabia

An investigation into tectonics and erosion reveals that they play an important role in causing uplifting, valley incision, and soil erosion. The analysis of drainage basins at different scales is irreplaceable in the development of sustainable plans, particularly in arid regions. Morphotectonics and morphometric characterization analyses are very effective methods for defining the evolution of different landforms, current-day tectonic activity, and hydrological and morphological signatures of basins under investigation. The reorganization of critical drainage basins and sub-basin risk priority ranking are essential for effective and accurate sustainable plans for drainage basin management and water resources. In this study, the coupling of geospatial techniques and statistical strategies was used to examine the tectonic activity and priorities in terms of soil erosion for 15 sub-basins of Wadi Al-Lith along the Red Sea coast of Saudi Arabia. Two effective models, namely, the relative tectonic activity model and the weighted sum analysis model, were applied for examining each geomorphological and hydrological characteristic based on an analysis of the morphotectonics and morphometric parameters. Regarding the relative tectonic activity model, the 15 sub-basins were classified into three classes of tectonic activity: low, moderate, and high. Sub-basins 5, 6, 13, and 15 were considered to be in class 1 (high relative tectonic activity). On the other hand, the weighted sum analysis model assigned the sub-basins into three different ranks: low-, moderate-, and high-soil-erosion priorities. The current study’s results suggest that sub-basins 5, 6, 10, 13, and 15 were recorded within the high-soil-erosion zone and highly relative tectonic activity, covering approximately 53.52% of the total sub-basin areas. The relative tectonic activity and weighted sum analysis models proved their validity in the risk studies, which will be very useful for decision makers in various fields, including natural resources and agriculture.

Statistically derived morphological signatures of large river channels extracted from topo‐bathymetric LiDAR data

AbstractWith the development of LiDAR technology and the availability of topo‐bathymetric data of high quality, new methods are emerging to describe and understand more accurately fluvial geomorphology. We explore the capacities of probability density functions (PDFs) of detrended dimensionless elevations extracted from digital elevation models (DEMs) to document channels morphology and configuration. These DEMs were obtained from a topo‐bathymetric LiDAR survey of 450 km performed on the middle and lower reaches of the largest river of France: the Loire River. The objective is to propose a thorough and complete method for PDF analysis in order to assess the vertical structuration of river reaches presenting various fluvial patterns. The analysis was conducted on the PDFs of active channel belt of four sites selected for the diversity of their morphological configurations (anabranching, braided, channelized and meandering). Results showed that PDFs appear to be specific of a reach and that they are useful for describing its vertical structure. The simplification with Gaussian mixture model (GMM) is effective in slicing PDF and the resulting Gaussians components are related to morphological units (MUs). The distance between Gaussian curves obtained using GMMs can be considered as an indicator of topo‐bathymetric connectivity between MUs (e.g., main and side channels) on sites presenting multichannel or channelized channel configurations. The study showed the high potential of PDF and GMM analysis in the field of fluvial geomorphology and suggests interesting developments for river management and restoration.

Three-dimensional echocardiography reveals early mitral valve alterations in hypertrophic cardiomyopathy genetic mutation carriers

BackgroundThe mitral valve undergoes structural modifications in response to cardiac functional changes, often predating cardiac decompensation and overt clinical signs. Our study assessed the potential of mitral valve morphological changes as early indicators for detecting carriers of hypertrophic cardiomyopathy (HCM)-associated gene mutations. MethodsWe studied 505 participants: 189 without the pathogenic gene mutations and left ventricular hypertrophy (G-/LVH-), 149 carriers without LV hypertrophy (G+/LVH-), and 167 manifest HCM patients (G+/LVH+). We juxtaposed the mitral valve morphology and associated metrics across these groups, emphasizing those carrying MYH7 and MYBPC3 mutations. ResultsWe discerned pronounced disparities in the mitral annulus and leaflet structures across the groups. The mitral valve apparatus in mutation carriers exhibited a tendency towards a flattened profile. Detailed analysis spotlighted MYBPC3 mutation carriers, whose mitral valves were notably flatter (with notably lower AHCWR values than non-carriers); this contrast was not evident in MYH7 mutation carriers. This mitral valve flattening, manifest in the mutation carriers, suggests it might be an adaptive response to incipient cardiac dysfunction in HCM's nascent stages. ConclusionsThree-dimensional echocardiography illuminates the initial mitral valve structural changes in HCM patients bearing pathogenic gene mutations. These morphological signatures hold promise as sensitive imaging markers, especially for asymptomatic carriers of the MYBPC3 mutation.

Bioactive and chemically defined hydrogels with tunable stiffness guide cerebral organoid formation and modulate multi-omics plasticity in cerebral organoids.

Organoids are an emerging technology with great potential in human disease modelling, drug development, diagnosis, tissue engineering, and regenerative medicine. Organoids as 3D-tissue culture systems have gained special attention in the past decades due to their ability to faithfully recapitulate the complexity of organ-specific tissues. Despite considerable successes in culturing physiologically relevant organoids, their real-life applications are currently limited by challenges such as scarcity of an appropriate biomimetic matrix. Peptide amphiphiles (PAs) due to their well-defined chemistry, tunable bioactivity, and extracellular matrix (ECM)-like nanofibrous architecture represent an attractive material scaffold for organoids development. Using cerebral organoids (COs) as exemplar, we demonstrate the possibility to create bio-instructive hydrogels with tunable stiffness ranging from 0.69kPa to 2.24kPa to culture and induce COs growth. We used orthogonal chemistry involving oxidative coupling and supramolecular interactions to create two-component hydrogels integrating the bio-instructive activity and ECM-like nanofibrous architecture of a laminin-mimetic PAs (IKVAV-PA) and tunable crosslinking density of hyaluronic acid functionalized with tyramine (HA-Try). Multi-omics technology including transcriptomics, proteomics, and metabolomics reveals the induction and growth of COs in soft HA-Tyr hydrogels containing PA-IKVAV such that the COs display morphology and biomolecular signatures similar to those grown in Matrigel scaffolds. Our materials hold great promise as a safe synthetic ECM for COs induction and growth. Our approach represents a well-defined alternative to animal-derived matrices for the culture of COs and might expand the applicability of organoids in basic and clinical research. STATEMENT OF SIGNIFICANCE: Synthetic bio-instructive materials which display tissue-specific functionality and nanoscale architecture of the native extracellular matrix are attractive matrices for organoids development. These synthetic matrices are chemically defined and animal-free compared to current gold standard matrices such as Matrigel. Here, we developed hydrogel matrices with tunable stiffness, which incorporate laminin-mimetic peptide amphiphiles to grow and expand cerebral organoids. Using multi-omics tools, the present study provides exciting data on the effects of neuro-inductive cues on the biomolecular profiles of brain organoids.

A Drosophila glial cell atlas reveals a mismatch between transcriptional and morphological diversity.

Morphology is a defining feature of neuronal identity. Like neurons, glia display diverse morphologies, both across and within glial classes, but are also known to be morphologically plastic. Here, we explored the relationship between glial morphology and transcriptional signature using the Drosophila central nervous system (CNS), where glia are categorised into 5 main classes (outer and inner surface glia, cortex glia, ensheathing glia, and astrocytes), which show within-class morphological diversity. We analysed and validated single-cell RNA sequencing data of Drosophila glia in 2 well-characterised tissues from distinct developmental stages, containing distinct circuit types: the embryonic ventral nerve cord (VNC) (motor) and the adult optic lobes (sensory). Our analysis identified a new morphologically and transcriptionally distinct surface glial population in the VNC. However, many glial morphological categories could not be distinguished transcriptionally, and indeed, embryonic and adult astrocytes were transcriptionally analogous despite differences in developmental stage and circuit type. While we did detect extensive within-class transcriptomic diversity for optic lobe glia, this could be explained entirely by glial residence in the most superficial neuropil (lamina) and an associated enrichment for immune-related gene expression. In summary, we generated a single-cell transcriptomic atlas of glia in Drosophila, and our extensive in vivo validation revealed that glia exhibit more diversity at the morphological level than was detectable at the transcriptional level. This atlas will serve as a resource for the community to probe glial diversity and function.

CIC-DUX4 Sarcoma Involving the Skull Base: A Rare Presentation and Review of the Literature.

Background CIC-DUX4 sarcoma is a rare, aggressive tumor that is difficult to diagnose. Although it is closely related to Ewing's sarcoma, each is a distinct pathologic entity and both have been previously reported in the skin, lymph nodes, and viscera. We report the first description of CIC-DUX4 involving the posterior cranial fossa and review the distinctive symptomatology, morphology, immunoprofile, and genetic signature that differentiate this rare tumor. Case Report A 32-year-old man presented with an enlarging right lateral neck mass, progressive hoarseness, and orofacial pain. Biopsy revealed a high-grade undifferentiated malignant neoplasm. Imaging demonstrated an 8-cm mass in the right neck extending to the skull base and abutting the carotid sheath, in addition to pulmonary nodules and pelvic lymphadenopathy. Despite initial response to chemotherapy, he experienced disease progression and underwent surgical resection, radical neck dissection, and brachytherapy. Definitive pathologic diagnosis was achieved with next-generation sequencing. Within weeks of treatment, he developed symptoms reflecting progression of disease involving the neck, posterior cranial fossa, and lung. Adjuvant chemotherapy was planned, but the patient succumbed to his disease prior to initiation of further therapy. Conclusion CIC-DUX4 sarcomas are uncommon and can progress rapidly. Diagnosis requires either fluorescence in situ hybridization or next-generation sequencing. Due to its rarity, there is no standard-of-care treatment for this tumor and further investigations are needed to understand disease behavior and develop targeted therapeutic modalities.

High-content microscopy reveals a morphological signature of bortezomib resistance.

Drug resistance is a challenge in anticancer therapy. In many cases, cancers can be resistant to the drug prior to exposure, i.e., possess intrinsic drug resistance. However, we lack target-independent methods to anticipate resistance in cancer cell lines or characterize intrinsic drug resistance without a priori knowledge of its cause. We hypothesized that cell morphology could provide an unbiased readout of drug resistance. To test this hypothesis, we used HCT116 cells, a mismatch repair-deficient cancer cell line, to isolate clones that were resistant or sensitive to bortezomib, a well-characterized proteasome inhibitor and anticancer drug to which many cancer cells possess intrinsic resistance. We then expanded these clones and measured high-dimensional single-cell morphology profiles using Cell Painting, a high-content microscopy assay. Our imaging- and computation-based profiling pipeline identified morphological features that differed between resistant and sensitive cells. We used these features to generate a morphological signature of bortezomib resistance. We then employed this morphological signature to analyze a set of HCT116 clones (five resistant and five sensitive) that had not been included in the signature training dataset, and correctly predicted sensitivity to bortezomib in seven cases, in the absence of drug treatment. This signature predicted bortezomib resistance better than resistance to other drugs targeting the ubiquitin-proteasome system. Our results establish a proof-of-concept framework for the unbiased analysis of drug resistance using high-content microscopy of cancer cells, in the absence of drug treatment.

Morphometric and Nanomechanical Screening of Peripheral Blood Cells with Atomic Force Microscopy for Label-Free Assessment of Alzheimer's Disease, Parkinson's Disease, and Amyotrophic Lateral Sclerosis.

Neurodegenerative disorders (NDDs) are complex, multifactorial disorders with significant social and economic impact in today's society. NDDs are predicted to become the second-most common cause of death in the next few decades due to an increase in life expectancy but also to a lack of early diagnosis and mainly symptomatic treatment. Despite recent advances in diagnostic and therapeutic methods, there are yet no reliable biomarkers identifying the complex pathways contributing to these pathologies. The development of new approaches for early diagnosis and new therapies, together with the identification of non-invasive and more cost-effective diagnostic biomarkers, is one of the main trends in NDD biomedical research. Here we summarize data on peripheral biomarkers, biofluids (cerebrospinal fluid and blood plasma), and peripheral blood cells (platelets (PLTs) and red blood cells (RBCs)), reported so far for the three most common NDDs-Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). PLTs and RBCs, beyond their primary physiological functions, are increasingly recognized as valuable sources of biomarkers for NDDs. Special attention is given to the morphological and nanomechanical signatures of PLTs and RBCs as biophysical markers for the three pathologies. Modifications of the surface nanostructure and morphometric and nanomechanical signatures of PLTs and RBCs from patients with AD, PD, and ALS have been revealed by atomic force microscopy (AFM). AFM is currently experiencing rapid and widespread adoption in biomedicine and clinical medicine, in particular for early diagnostics of various medical conditions. AFM is a unique instrument without an analog, allowing the generation of three-dimensional cell images with extremely high spatial resolution at near-atomic scale, which are complemented by insights into the mechanical properties of cells and subcellular structures. Data demonstrate that AFM can distinguish between the three pathologies and the normal, healthy state. The specific PLT and RBC signatures can serve as biomarkers in combination with the currently used diagnostic tools. We highlight the strong correlation of the morphological and nanomechanical signatures between RBCs and PLTs in PD, ALS, and AD.

Assessment of Drug-Induced Liver Injury through Cell Morphology and Gene Expression Analysis.

Drug-induced liver injury (DILI) is a significant concern in drug development, often leading to drug withdrawal. Although many studies aim to identify biomarkers and gene/pathway signatures related to liver toxicity and aim to predict DILI compounds, this remains a challenge in drug discovery. With a strong development of high-content screening/imaging (HCS/HCI) for phenotypic screening, we explored the morphological cell perturbations induced by DILI compounds. In the first step, cell morphological signatures were associated with two datasets of DILI chemicals (DILIRank and eTox). The mechanisms of action were then analyzed for chemicals having transcriptomics data and sharing similar morphological perturbations. Signaling pathways associated with liver toxicity (cell cycle, cell growth, apoptosis, ...) were then captured, and a hypothetical relation between cell morphological perturbations and gene deregulation was illustrated within our analysis. Finally, using the cell morphological signatures, machine learning approaches were developed to predict chemicals with a potential risk of DILI. Some models showed relevant performance with validation set balanced accuracies between 0.645 and 0.739. Overall, our findings demonstrate the utility of combining HCI with transcriptomics data to identify the morphological and gene expression signatures related to DILI chemicals. Moreover, our protocol could be extended to other toxicity end points, offering a promising avenue for comprehensive toxicity assessment in drug discovery.

Clinical trajectory of intraductal papillary mucinous neoplasms progressing to pancreatic carcinomas during long-term surveillance: a prospective series of 100 carcinoma cases.

Trajectories of serological and morphological signatures have not been documented in pancreatic carcinogenesis related to intraductal papillary mucinous neoplasms (IPMNs). Using a prospective cohort of 3437 IPMN patients, we identified 100 IPMN patients who developed pancreatic carcinomas during long-term surveillance. We examined serial changes of blood markers (carbohydrate antigen 19-9 [CA19-9], hemoglobin A1c [HbA1c], and pancreatic enzymes) and morphological features (worrisome features and high-risk stigmata) during the prediagnostic period of pancreatic carcinomas, overall and by carcinoma types (IPMN-derived vs. concomitant pancreatic carcinomas). CA19-9 elevation was observed in 39 patients and was associated with a metastatic stage. Compared to IPMN-derived carcinomas, concomitant carcinomas were more likely to represent CA19-9 elevation (60% vs. 30%, respectively; P = 0.005). HbA1c levels elevated only in 3 patients. Pancreatic enzyme elevation was observed in 18 patients with no differences in frequencies between the carcinoma types. All patients with elevated levels of blood markers had positive findings on cross-sectional imaging. High-risk stigmata or worrisome features were observed in all patients but one with concomitant carcinoma. The most common types of worrisome features were the main pancreatic duct dilatation and CA19-9 elevation in IPMN-derived and concomitant carcinomas, respectively. Compared to IPMN-derived carcinomas, concomitant carcinomas were less likely to harbor high-risk stigmata (16% vs. 86%, respectively; P < 0.001). The usefulness of currently available blood biomarkers was limited in early detection of pancreatic carcinomas related to IPMNs. Morphological alterations were well correlated with long-term risk of IPMN-derived carcinomas, but not with that of concomitant carcinomas.