Current Classification Schemes Research Articles

Knowledge-based query system for the critical minerals

Critical minerals are increasingly used in advanced, modern technologies. Exploration for these minerals require efficient mechanisms to search for the latest geological knowledge about the petrogenesis and spatial distribution of these essential resources. Although the current text-based deposit classification schemes help geoscientists to understand how and where these critical minerals form, they cannot easily be queried by software without extensive natural language processing and knowledge modeling. Ontologies can explicitly specify the knowledge scattered in the texts and tables of these schemes and the Critical Minerals Mapping Initiative (CMMI) database by way of logical structures whose results can automatically be processed and queried. They can also draw new knowledge by inference from the ones that are explicitly specified in them. These qualities make ontologies a perfect choice for digital knowledge storage, search, and extraction. The Critical Minerals Ontology (CMO) is described herein by reusing the logical class and property structures of the top-level Basic Formal Ontology (BFO) and mid-level Common Core Ontologies (CCO) and Relation Ontology (RO). The CMO formally models the knowledge about the critical mineral systems using the latest deposit classification scheme and the CMMI database schema. The ontology specifies the geochemical and geological processes that operate in various geotectonic environments of mineral systems to form the critical minerals in different deposit types. It models the properties of both the host minerals that contain the rare-earth elements and those that bear other types of elements. The CMO also represents uses of specific critical minerals in the manufacturing of industrial products, their alternate substitutes, and countries that produce, import, and export them. A query system, applying the Python programming language, accesses the knowledge modeled in the CMO and allows users through interactive web pages to query the ontology and extract different types of information from it. The ontology and the query system are useful for research in ore mineralogy and critical mineral prospecting. The information modeled by the ontology and served by the query system allows users to classify their ore specimen data into specific deposit types.

Proposing the "Continuum of UTI" for a Nuanced Approach to Diagnosis and Management of Urinary Tract Infections.

Patients with suspected UTIs are categorized into 3 clinical phenotypes based on current guidelines: no UTI, asymptomatic bacteriuria (ASB), or UTI. However, all patients may not fit neatly into these groups. Our objective was to characterize clinical presentations of patients who receive urine tests using the "continuum of UTI" approach. This was a retrospective cohort study of a random sample of adult noncatheterized inpatient and emergency department encounters with paired urinalysis and urine cultures from 5 hospitals in 3 states between January 01, 2017, and December 31, 2019. Trained abstractors collected clinical (eg, symptom) and demographic data. A focus group discussion with multidisciplinary experts was conducted to define the continuum of UTI, a 5-level classification scheme that includes 2 new categories: lower urinary tract symptoms/other urologic symptoms and bacteriuria of unclear significance. The newly defined continuum of UTI categories were compared to the current UTI classification scheme. Of 220,531 encounters, 3392 randomly selected encounters were reviewed. Based on the current classification scheme, 32.1% (n = 704) had ASB and 53% (n = 1614) did not have a UTI. When applying the continuum of UTI categories, 68% of patients (n = 478) with ASB were reclassified as bacteriuria of unclear significance and 29% of patients (n = 467) with "no UTI" were reclassified to lower urinary tract symptoms/other urologic symptoms. Our data suggest the need to reframe our conceptual model of UTI vs ASB to reflect the full spectrum of clinical presentations, acknowledge the diagnostic uncertainty faced by frontline clinicians, and promote a nuanced approach to diagnosis and management of UTIs.

Ethical issues of nosology in disorders of consciousness.

The current classification scheme for severe disorders of consciousness (DoC) has several shortcomings. First, there is no consensus on how to incorporate patients with covert consciousness. Second, there is a mismatch between the definitions of severe DoC, based on consciousness, and the diagnosis of these same DoC, which is based on observable motoric responsiveness. Third, current categories are grouped into large heterogeneous syndromes which share phenotype, but do not incorporate underlying pathophysiology. Here we discuss several ethical issues pertaining to the current nosology of severe DoC. We conclude by proposing a revised nosology which addresses these shortcomings.

Molecular Classification of Chronic Myelomonocytic Leukemia: Results of the Analysis of an International Cohort of 2,471 Patients

Background. Chronic myelomonocytic leukemia (CMML) is a rare myeloid neoplasm that shares both dysplastic and proliferative features and includes patients with highly heterogeneous clinical manifestations and prognosis. Despite known co-mutation patterns that are suggesting of a CMML diagnosis such as TET2 and SRSF2 mutations, the current diagnosis and classification schemes rely solely on morphological criteria that fail to capture the genomic heterogeneity of the disease. Here we perform an unsupervised analysis using only genomic features to generate a novel classification schema of CMML patients with unique clinical features. Methods. A cohort of 2,471 CMML patients defined according to WHO 2016 criteria from European and US centers was analyzed. Bayesian network analysis and hierarchical Dirichlet processes were used to identify genomic associations and subgroups as a basis to define a molecular classification of CMML. Bayesian networks allow to infer the structure of conditional dependencies among mutations. Dirichlet processes were applied to define clusters capturing broad dependencies among all gene mutations and cytogenetic abnormalities. Multivariate logistic regression analysis was applied to compare clinical and hematological characteristics among different groups. ( JCO 2021 39:11, 1223-1233) Results. Baseline clinical and molecular characteristics are summarized in Table 1. We identified 11 clusters defined according to specific genomic features (Table 2). Two clusters were primarily defined by the presence of mutations in splicing genes SRSF2 and ZRSR2, frequently associated with TET2 mutations. Patients assigned to these clusters showed myelodysplastic features according to French American British (FAB) criteria, had a low rate of peripheral blood cytopenias, and low blast counts. Additionally, two clusters were characterized by the same mutations in splicing genes (i.e., SRSF2 or ZRSR2 with associated TET2), together with co-mutations in genes that correlate with a more aggressive phenotype ( RUNX1, ASXL1, EZH2). These groups showed overlapping myelodysplastic and myeloproliferative features by FAB, intermediate-risk per prognostic scores, and decreased survival as compared with the first 2 clusters. A distinct cluster was characterized by SF3B1 gene mutations (frequently associated with TET2 or DNMT3A). The SF3B1 cluster was marked by a dysplastic phenotype and more severe anemia (with a high rate of transfusion-dependence) with respect to the other genomic groups. Four clusters (27.8% of the overall population) were characterized by the presence of mutations in signal transduction and tyrosine kinase pathways genes ( NRAS/KRAS, CBL, JAK2 and SETBP1 often associated with ASXL1/TET2, respectively). Patients within these groups showed a mostly proliferative phenotype and intermediate survival. The presence of JAK2 mutations appeared to confer a better prognosis compared with other proliferative clusters. A minority of patients (4.6%) were assigned to two high-risk clusters, defined by TP53 mutations (often biallelic) with complex karyotype, and AML-like mutations ( NPM1, IDH1/2, FLT3), respectively. Patients in these clusters were predominantly dysplastic by FAB, had a high prevalence of severe cytopenias, higher blast counts, and a dismal outcome. Finally, we identified a cluster of patients defined by the absence of gene mutations and chromosomal abnormalities (4.5%). The majority of patients assigned to this cluster were characterized by a dysplastic phenotype, had low absolute monocyte counts, and favorable outcome. A subset of patients (18.9%) could not be assigned to a specified cluster in this preliminary analysis. An independent validation of this molecular classification is currently being conducted on a US prospective cohort (n=650). Conclusion. Our results provide proof of concept for a molecular classification of CMML based on the identification of homogeneous genomic signatures and associated clinical features. 15% of patients showed clear overlapping features with other myeloid neoplasms, thus providing the rational to refine the boundaries among different clinical entities. A molecular classification of CMML may provide a basis to define a next-generation prognostic tool and improve clinical decision-making.

Tumor heterogeneity: how could we use it to achieve better clinical outcomes?

Differences in tumors related to location, tissue type, and histological subtype have been well documented for decades. Tumors are also molecularly very diverse. In this short review we describe the current classification schemes for tumor heterogeneity. We enlist the various drivers of tumor heterogeneity generation and comment on their clinical significance. New molecular techniques promise to assess tumor heterogeneity at affordable cost, so that these techniques can soon enter the clinic. While tumor heterogeneity currently represents a major unfavorable barrier in the field of oncology, it may also be a key in revolutionizing cancer diagnosis and treatment. Information regarding tumor heterogeneity has the potential to provide more thorough prognostic information, guide more efficacious combination treatment regimens, and lead to the development of novel therapeutic strategies and identification of new targets. For these gains to be realized, assessment of tumor heterogeneity needs to be incorporated into current diagnostic protocols but standardized and reproducible assessment methods are required. Fortunately, when these advances are realized, tumor heterogeneity has the potential to improve clinical outcomes.

Genetic landscape of congenital insensitivity to pain and hereditary sensory and autonomic neuropathies.

Congenital insensitivity to pain (CIP) and hereditary sensory and autonomic neuropathies (HSAN) are clinically and genetically heterogeneous disorders exclusively or predominantly affecting the sensory and autonomic neurons. Due to the rarity of the diseases and findings based mainly on single case reports or small case series, knowledge about these disorders is limited. Here, we describe the molecular workup of a large international cohort of CIP/HSAN patients including patients from normally under-represented countries. We identify 80 previously unreported pathogenic or likely pathogenic variants in a total of 73 families in the >20 known CIP/HSAN-associated genes. The data expand the spectrum of disease-relevant alterations in CIP/HSAN, including novel variants in previously rarely recognized entities such as ATL3-, FLVCR1- and NGF-associated neuropathies and previously under-recognized mutation types such as larger deletions. In silico predictions, heterologous expression studies, segregation analyses and metabolic tests helped to overcome limitations of current variant classification schemes that often fail to categorize a variant as disease-related or benign. The study sheds light on the genetic causes and disease-relevant changes within individual genes in CIP/HSAN. This is becoming increasingly important with emerging clinical trials investigating subtype or gene-specific treatment strategies.

Exploring the genetic and functional diversity of Porphyromonas gingivalis long fimbriae.

Porphyromonas gingivalis is a key pathobiont in periodontitis. Its long fimbriae consist of a single anchor (FimB), a varying number of stalk (FimA), and three accessory (tip-related) proteins (FimC, FimD, and FimE). Based on 133 strains/genomes available, it was our aim to investigate the diversity within FimA and FimB and explain the variety of long fimbriae (super-)structures. Combining the new forward primer fimAnewF with the established fimAunivR, we were able to amplify and sequence fimA including its leader region covering all genotypes and serotypes for phylogenetic analysis. We designed two primer pairs sensing the presence of an internal stop codon in fimB with an impact on fimbrial length. Finally, we examined fimbrial secondary structures by transmission electron microscopy (TEM) and scanning electron microscopy (SEM). The phylogeny of fimA/FimA revealed two new subtypes (IIa and IIb) with specific changes in functional domains and thus adding to the current classification scheme (I, Ib, and II-V). Regarding evolution, we confirm that Porphyromonas gulae fimA-type A is closely related to human P. gingivalis strains of cluster Ib and might be its ancestor genotype. A fimB internal stop codon is rare and was found in ATCC 33277 only. Comparing P. gingivalis TEM/SEM pictures of type I ATCC 33277 with type V OMI622 revealed a broad spectrum of fimbrial structures including bundling, cell-cell knotting, and brick-wall formation. In conclusion, FimA forms more distinct subtypes than previously known. The bundling of long fimbriae, a mechanism known from EPEC/EHEC and Salmonella, is proposed and supported by TEM/SEM pictures for the first time here. The role and variations of terminal accessory FimC-E in superstructure formation and/or (co-) adhesion should be investigated more closely next.

Grey matter heterotopia subtypes show specific morpho-electric signatures and network dynamics.

Grey matter heterotopia (GMH) are neurodevelopmental disorders associated with abnormal cortical function and epilepsy. Subcortical band heterotopia (SBH) and periventricular nodular heterotopia (PVNH) are two well-recognized GMH subtypes in which neurons are misplaced, either forming nodules lining the ventricles in PVNH, or forming bands in the white matter in SBH. Although both PVNH and SBH are commonly associated with epilepsy, it is unclear whether these two GMH subtypes differ in terms of pathological consequences or, on the contrary, share common altered mechanisms. Here, we studied two robust preclinical models of SBH and PVNH, and performed a systematic comparative assessment of the physiological and morphological diversity of heterotopia neurons, as well as the dynamics of epileptiform activity and input connectivity. We uncovered a complex set of altered properties, including both common and distinct physiological and morphological features across heterotopia subtypes, and associated with specific dynamics of epileptiform activity. Taken together, these results suggest that pro-epileptic circuits in GMH are, at least in part, composed of neurons with distinct, subtype-specific, physiological and morphological properties depending on the heterotopia subtype. Our work supports the notion that GMH represent a complex set of disorders, associating both shared and diverging pathological consequences, and contributing to forming epileptogenic networks with specific properties. A deeper understanding of these properties may help to refine current GMH classification schemes by identifying morpho-electric signatures of GMH subtypes, to potentially inform new treatment strategies.

HYDRODYNAMIC CLASSIFICATION OF ESTUARIES: CHALLENGES AND ALTERNATE APPROACHES

Globally, estuaries are environments that are under increasing stressors from dense populations, pollutants, and changing ecosystems with pressures only likely to increase with climate change. Estuaries are systems with widely variable morphology that are typically spatially vast and highly dynamic, hence site-specific investigation is often costly and practically challenging. As such, conceptual approaches that allow the translation of information from one estuary to another due to similar classifications in conceptual models are widely used for management purposes. This paper will use case study examples to identify challenges associated with the current categorical estuary classification schemes and suggest alternate approaches that capture the varying dynamics of the full spectrum of estuary systems.

Pediatric Pilomatrixomas: Four Atypical Clinical Presentations

Pilomatrixoma, also called Malherbe's calcifying epithelioma or pilomatrixoma, is a benign adnexal tumor that originates from keratinocytes (cells of the hair matrix, the internal sheath of the hair root or the cortex) and constitutes the second most prevalent skin neoplasm in children. These lesions are typically slow-growing, firm, nodules located on the head, neck, trunk, and extremities (in decreasing order of frequency). Due to the rarity, combined with their varied clinical presentations, pilomatrixomas are often misdiagnosed. Current pilomatrixoma classification schemes remain controversial. In this article, we present 4 pediatric patients that exemplify different clinical and atypical scenarios of the same tumor. Accordingly, we invite future studies to create a novel system for the classification of pilomatrixomas based on atypical clinical characteristics, including lesion morphology, number, size, and anatomic location.

Histological and molecular glioblastoma, IDH-wildtype: a real-world landscape using the 2021 WHO classification of central nervous system tumors.

Glioblastoma (GBM), the most lethal primary brain malignancy, is divided into histological (hist-GBM) and molecular (mol-GBM) subtypes according to the 2021 World Health Organization classification of central nervous system tumors. This study aimed to characterize the clinical, radiological, molecular, and survival features of GBM under the current classification scheme and explore survival determinants. We re-examined the genetic alterations of IDH-wildtype diffuse gliomas at our institute from 2011 to 2022, and enrolled GBMs for analysis after re-classification. Univariable and multivariable analyses were used to identify survival determinants. Among 209 IDH-wildtype gliomas, 191 were GBMs, including 146 hist-GBMs (76%) and 45 mol-GBMs (24%). Patients with mol-GBMs were younger, less likely to develop preoperative motor dysfunction, and more likely to develop epilepsy than hist-GBMs. Mol-GBMs exhibited lower radiographic incidences of contrast enhancement and intratumoral necrosis. Common molecular features included copy-number changes in chromosomes 1, 7, 9, 10, and 19, as well as alterations in EGFR, TERT, CDKN2A/B, and PTEN, with distinct patterns observed between the two subtypes. The median overall survival (mOS) of GMB was 12.6 months. Mol-GBMs had a higher mOS than hist-GBMs, although not statistically significant (15.6 vs. 11.4 months, p=0.17). Older age, male sex, tumor involvement of deep brain structure or functional area, and genetic alterations in CDK4, CDK6, CIC, FGFR3, KMT5B, and MYB were predictors for a worse prognosis, while MGMT promoter methylation, maximal tumor resection, and treatment based on the Stupp protocol were predictive for better survival. The definition of GBM and its clinical, radiological, molecular, and prognostic characteristics have been altered under the current classification.

An Overview and Countermeasure of Global Wave Energy Classification

Wave energy will be an important support to deal with the energy crisis of human society. A scientific energy classification scheme is a prerequisite support for the macro-scale optimized layout, micro-scale accurate site selection and a blueprinting of development routes for wave energy. Based on the indicator considered, this study first divides the global wave energy classification into three stages: preliminary exploration stage, mid-term development stage and relatively mature stage, and then sorts out the main strengths and weaknesses of each stage. It is found that the current classification scheme has six typical bottlenecks such as inconsistency with physical mechanisms, inability to meet the needs of diverse tasks, inapplicability in some seasons/months, etc. To effectively address them, a dynamic adaptive wave energy classification scheme is proposed, which can consider all elements, is suitable for diverse tasks, is available at all times and is applicable to all regions. Based on this, the concepts of absolute and relative classes, a dynamic mapping of wave energy classification, and a future energy classification are proposed, with the expectation of promoting the industrialization and scaling of wave energy.

Methylation classifier array and classification of solitary fibrous tumors.

e23522 Background: Solitary fibrous tumors (SFTs) are fibroblastic tumors which carry a characteristic NAB2::STAT6 gene rearrangement. SFTs represent a heterogenous group that may arise in multiple locations and have variable risk of progression. Despite a consistent oncogenic driver, there is little biological data explaining this variability. Recently, the German Cancer Research Network (DKFZ) have modified their brain tumor methylation classifier for use in sarcomas. We subjected solitary fibrous tumors diagnosed at our institution to a validated, in-house sarcoma methylation array classifier modeled after that of the DKFZ in order to assess for differences in methylation patterns that may account for biological or clinical variances. Methods: Twenty-eight primary site SFTs from 2011-2021 were subjected to the sarcoma methylation classifier. Histologic diagnosis was confirmed by STAT6 immunohistochemistry or by the presence of the NAB2::STAT6 fusion. The methylation classifier was run on the Illumina iScan platform and the resulting IDAT files were analyzed via a custom bioinformatics pipeline. The sarcoma classifier was trained using the same samples and normalization strategies used by the DKFZ group and validated using the same publicly available samples. Results: Methylation data for each tumor was collected, given a classification score, and visualized by t-distributed stochastic neighbor embedding (t-SNE). We noted three distinct groups of SFTs on the t-SNE plot. Group 1 was comprised of all eight intracranial SFTs and were correctly classified as SFT (classifier score ≥0.9). Group 2 contained nine pleural-based tumors and one SFT each from the mediastinum and bladder wall. Classification was successful in only seven of eleven tumors. Group 3 SFTs predominantly arose in the soft tissues or bone (two pelvis, four extremity, and one mediastinum) and all failed accurate classification. Finally, two orbital SFTs stratified separately from all groups on t-SNE plot but did achieve an appropriate classification. There were no significant differences in grade or risk stratification among the three groups. Conclusions: Our preliminary data show differential clustering based on tumor location, suggesting biological differences between intracranial, pleural/visceral, and connective tissue locations. These results highlight the heterogeneity of these tumors and the inadequacy of the current methylation classification scheme for SFT. Future directions will include analysis of additional cases, gene expression patterns, and outcome data.

Pediatric hepatic vascular tumors: clinicopathologic characteristics of 33 cases and proposed updates to current classification schemes

Pediatric hepatic vascular tumors (HVTs) are rare neoplasms with features distinct from their cutaneous counterparts. Their behavior ranges from benign to malignant, with each subtype having therapeutic differences. Histopathologic descriptions of large cohorts are scarce in the literature. Thirty-three putative HVTs diagnosed from 1970 to 2021 were retrieved. All available clinical and pathologic materials were reviewed. Lesions were reclassified according to the World Health Organization (WHO) classification of pediatric tumors [1] ashepatic congenital hemangioma (HCH; n=13), hepatic infantile hemangioma (HIH; n=10), hepatic angiosarcoma (HA; n=3), and hepatic epithelioid hemangioendothelioma (HEH; n=1). Vascular malformations (n=5) or vascular-dominant mesenchymal hamartoma (n=1) were excluded. HCH frequently showed involutional changes, whereas HIH often had anastomosing channels and pseudopapillae formation. HA had solid areas with epithelioid and/or spindled endothelial morphology, significant atypia, increased mitoses, high proliferation index, and occasionally necrosis. On morphology analysis, a subset of HIH showed features worrisome for progression to HA including solid glomeruloidproliferation, increased mitoses, and epithelioid morphology. The widely metastatic and fatal HEH was observed in a 5-year-old male with multiple liver lesions. Immunohistochemically, HIHs and HA were Glucose transporter isoform 1 (GLUT-1) positive. One HIH patient died from postoperative complications, whereas 3 are alive without disease. Five HCH patients are alive and well. Two of three HA patients died of disease, and 1is alive without recurrence. To our knowledge, this is the largest series of pediatric HVTs reviewing clinicopathologic features based on current Pediatric WHO nomenclature [1]. We highlight diagnostic challenges and propose inclusion of an intermediate category between HIH and HA which warrants closer follow-up.

Experimental Evidence for Shear‐Induced Melting and Generation of Stishovite in Granite at Low (<18 GPa) Shock Pressure

AbstractKnowledge of the shock behavior of planetary materials is essential to interpret shock metamorphism documented in rocks at hypervelocity impact structures on Earth, in meteorites, and in samples retrieved in space missions. Although our understanding of shock metamorphism has improved considerably within the last decades, the effects of friction and plastic deformation on shock metamorphism of complex, polycrystalline, non‐porous rocks are poorly constrained. Here, we report on shock‐recovery experiments in which natural granite was dynamically compressed to 0.5–18 GPa by singular, hemispherically decaying shock fronts. We then combine petrographic observations of shocked samples that retained their pre‐impact stratigraphy with distributions of peak pressures, temperatures, and volumetric strain rates obtained from numerical modeling to systematically investigate progressive shock metamorphism of granite. We find that the progressive shock metamorphism of granite observed here is mainly consistent with current classification schemes. However, we also find that intense shear deformation during shock compression and release causes the formation of highly localized melt veins at peak pressures as low as 6 GPa, which is an order of magnitude lower than currently thought. We also find that melt veins formed in quartz grains compressed to >10–12 GPa contain the high‐pressure silica polymorph stishovite. Our results illustrate the significance of shear and plastic deformation during hypervelocity impact and bear on our understanding of how melt veins containing high‐pressure polymorphs form in moderately shocked terrestrial impactites or meteorites.

Immunohistochemistry in the pathologic diagnosis and management of thyroid neoplasms.

The use of immunohistochemistry cannot be underestimated in the everyday practice of thyroid pathology. It has evolved over the years beyond the traditional confirmation of thyroid origin to molecular profiling and the prediction of clinical behavior. In addition, immunohistochemistry has served to implement changes in the current thyroid tumor classification scheme. It is prudent to perform a panel of immunostains, and the immunoprofile should be interpreted in light of the cytologic and architectural features. Immunohistochemistry can also be easily performed in the limited cellularity specimen preparation generated from thyroid fine-needle aspiration and core biopsy; however, it will require laboratory validation of immunostains specific to these preparations to avoid diagnostic pitfalls. This review discusses the application of immunohistochemistry in thyroid pathology with a focus on limited cellularity preparations.

VirClust-A Tool for Hierarchical Clustering, Core Protein Detection and Annotation of (Prokaryotic) Viruses.

Recent years have seen major changes in the classification criteria and taxonomy of viruses. The current classification scheme, also called "megataxonomy of viruses", recognizes six different viral realms, defined based on the presence of viral hallmark genes (VHGs). Within the realms, viruses are classified into hierarchical taxons, ideally defined by the phylogeny of their shared genes. To enable the detection of shared genes, viruses have first to be clustered, and there is currently a need for tools to assist with virus clustering and classification. Here, VirClust is presented. It is a novel, reference-free tool capable of performing: (i) protein clustering, based on BLASTp and Hidden Markov Models (HMMs) similarities; (ii) hierarchical clustering of viruses based on intergenomic distances calculated from their shared protein content; (iii) identification of core proteins and (iv) annotation of viral proteins. VirClust has flexible parameters both for protein clustering and for splitting the viral genome tree into smaller genome clusters, corresponding to different taxonomic levels. Benchmarking on a phage dataset showed that the genome trees produced by VirClust match the current ICTV classification at family, sub-family and genus levels. VirClust is freely available, as a web-service and stand-alone tool.

880 Electrophysiological Patterns of Glioma-Induced Neuronal Network Remodeling are a General Property of Brain Tumors Regardless of Subtype

INTRODUCTION: Recent evidence indicates that diffuse gliomas engage with neurons at the single-unit and circuit level through differing mechanisms. Certain malignant gliomas form glioma-neuron excitatory glutamatergic synapses and modulate neuron-neuron synapses through activity-dependent paracrine signaling, while others establish glioma-glioma connections via tumor microtubes. It is therefore possible that diffuse gliomas remodel neuronal circuits in a defined and predictable manner and demonstrate distinct electrophysiological profiles with prognostic and therapeutic significance. METHODS: Following spatial-temporal registration, an elastic net logistic regression classifier was used to distinguish between power spectra arising from glioma-remodeled cortex and within-subject control conditions (N = 140). Model significance was determined non-parametrically by re-training each model 1,000 times with randomly permuted class labels and testing the true phi coefficient against the null distribution. RESULTS: In the discovery dataset, glioma infiltration was accurately classified based on tumor intrinsic neuronal activity (p < 0.05) in 127 patients (90.7%). Thirty electrophysiological features were identified, which revealed increased power in the delta range (1-4 Hz) and decreased power in the beta range (12-20 Hz) as a unique signature of glioma remodeling (p < 0.05) which was preserved in the validation dataset as well as across WHO 2021 diffuse glioma subtypes. To identify gene expression programs and signaling mechanisms that may contribute to glioma-induced remodeling but are potentially not identified in the current clinical classification scheme, targeted, next generation sequencing was performed and used as covariates, which again demonstrated the significance of the delta-beta spectral features. CONCLUSIONS: These data support converging mechanisms of glioma-induced neuronal network remodeling across tumor subtypes, setting the stage for novel therapies such as neuromodulation.

Automated Prognostic Assessment of Endometrial Hyperplasia for Progression Risk Evaluation Using Artificial Intelligence

Endometrial hyperplasia is a precursor to endometrial cancer, characterized by excessive proliferation of glands that is distinguishable from normal endometrium. Current classifications define 2 types of EH, each with a different risk of progression to endometrial cancer. However, these schemes are based on visual assessments and, therefore, subjective, possibly leading to overtreatment or undertreatment. In this study, we developed an automated artificial intelligence tool (ENDOAPP) for the measurement of morphologic and cytologic features of endometrial tissue using the software Visiopharm. The ENDOAPP was used to extract features from whole-slide images of PAN-CK+–stained formalin-fixed paraffin-embedded tissue sections from 388 patients diagnosed with endometrial hyperplasia between 1980 and 2007. Follow-up data were available for all patients (mean = 140 months). The most prognostic features were identified by a logistic regression model and used to assign a low-risk or high-risk progression score. Performance of the ENDOAPP was assessed for the following variables: images from 2 different scanners (Hamamatsu XR and S60) and automated placement of a region of interest versus manual placement by an operator. Then, the performance of the application was compared with that of current classification schemes: WHO94, WHO20, and EIN, and the computerized-morphometric risk classification method: D-score. The most significant prognosticators were percentage stroma and the standard deviation of the lesser diameter of epithelial nuclei. The ENDOAPP had an acceptable discriminative power with an area under the curve of 0.765. Furthermore, strong to moderate agreement was observed between manual operators (intraclass correlation coefficient: 0.828) and scanners (intraclass correlation coefficient: 0.791). Comparison of the prognostic capability of each classification scheme revealed that the ENDOAPP had the highest accuracy of 88%-91% alongside the D-score method (91%). The other classification schemes had an accuracy between 83% and 87%. This study demonstrated the use of computer-aided prognosis to classify progression risk in EH for improved patient treatment.

Observation of spin-momentum locked surface states in amorphous Bi2Se3.

Crystalline symmetries have played a central role in the identification and understanding of quantum materials. Here we investigate whether an amorphous analogue of a well known three-dimensional strong topological insulator has topological properties in the solid state. We show that amorphous Bi2Se3 thin films host a number of two-dimensional surface conduction channels. Our angle-resolved photoemission spectroscopy data are consistent with a dispersive two-dimensional surface state that crosses the bulk gap. Spin-resolved photoemission spectroscopy shows this state has an anti-symmetric spin texture, confirming the existence of spin-momentum locked surface states. We discuss these experimental results in light of theoretical photoemission spectra obtained with an amorphous topological insulator tight-binding model, contrasting it with alternative explanations. The discovery of spin-momentum locked surface states in amorphous materials opens a new avenue to characterize amorphous matter, and triggers the search for an overlooked subset of quantum materials outside of current classification schemes.