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Most extrauterine high-grade serous carcinomas (HGSCs) are thought to develop first in the distal fallopian tube. Most models of HGSC assume origin from relatively stable, noninvasive serous tubal intraepithelial carcinomas. However, widespread tumor involvement in the absence of a serous tubal intraepithelial carcinoma could occur after catastrophic genomic events (CGEs; such as chromothripsis or polyploidy). Twenty-six HGSCs assigned to fallopian tube (n = 9, group 1) and/or ovary (n = 9, group 2), and primary peritoneal (n = 8, group 3) were assessed by microarray (Oncoscan). CGEs were identified in 15/26 (57.7%); chromothripsis-like pattern in 13/26 (50.0%) and polyploidy in 6/26 (23.1%). CGE was seen in 4/9 (44.4%), 9/9 (100%), and 2/8 (25%) cases in groups 1. 2, and 3, respectively. Overall, CGEs were seen in 9/9 (100%) cases with grossly evident ovarian parenchymal involvement versus 6/17 (35.3%) without ( P = 0.0024). Ovarian size (measured on the long axis) correlated with CGE positivity ( P = 0.016). CGEs are significantly more common in HGSCs with ovarian parenchymal involvement compared with those limited to the fallopian tube and/or extraovarian tissues. These associations suggest geographically different tumor growth patterns and support the subdivision of HGSCs according to not only the stage but also tumor distribution. They have implications for clinical and pathologic presentation, trajectory of tumor evolution, and in the case of primary peritoneal HGSCs, potentially unique precursors to tumor transitions that could inform or influence cancer prevention efforts., Competing Interests: Conflicts of Interest and Source of Funding: The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Copy number variants (CNVs) comprise a class of mutation which includes deletion, duplication, or amplification events that range in size from smaller than a single-gene or exon, to the size of a full chromosome. These changes can affect gene expression levels and are thus implicated in disease, including cancer. Although a variety of tools and methodologies exist to detect CNVs using data from massively parallel sequencing (also referred to as next-generation sequencing), it can be difficult to appreciate the copy number profile in a list format or as a static image. CNViz is a freely accessible R/Bioconductor package that launches an interactive R/Shiny visualization tool to facilitate review of copy number data. As inputs, it requires genomic locations and corresponding copy number ratios for probe, gene, and/or segment-level data. If supplied, loss of heterozygosity (LOH), focal variant data [single nucleotide variants (SNVs) and small insertions and deletions (indels)], and metadata (e.g., specimen purity and ploidy) can also be incorporated into the visualization. The CNViz R/Bioconductor package is an easy-to-use tool built with the intent of encouraging visualization and exploration of copy number variation. CNViz can be used in a clinical setting as well as for research to study patterns in human cancers more broadly. The intuitive interface allows users to visualize the copy number profile of a specimen, dynamically change resolution to explore gene and probe-level copy number changes, and simultaneously integrate LOH, SNV, and indel findings. CNViz is available for download as an R package via Bioconductor. An example of the application is available at rebeccagreenblatt.shinyapps.io/cnviz_example., (© 2022 The Authors.)

Visual stimulus-induced gamma oscillations in electroencephalogram (EEG) recordings have been recently shown to be compromised in subjects with preclinical Alzheimer's Disease (AD), suggesting that gamma could be an inexpensive biomarker for AD diagnosis provided its characteristics remain consistent across multiple recordings. Previous magnetoencephalography studies in young subjects have reported consistent gamma power over recordings separated by a few weeks to months. Here, we assessed the consistency of stimulus-induced slow (20-35 Hz) and fast gamma (36-66 Hz) oscillations in subjects ( n  = 40) (age: 50-88 years) in EEG recordings separated by a year, and tested the consistency in the magnitude of gamma power, its temporal evolution and spectral profile. Gamma had distinct spectral/temporal characteristics across subjects, which remained consistent across recordings (average intraclass correlation of ~0.7). Alpha (8-12 Hz) and steady-state-visually evoked-potentials were also reliable. We further tested how EEG features can be used to identify 2 recordings as belonging to the same versus different subjects and found high classifier performance (AUC of ~0.89), with temporal evolution of slow gamma and spectral profile being most informative. These results suggest that EEG gamma oscillations are reliable across sessions separated over long durations and can also be a potential tool for subject identification., (© The Author(s) 2022. Published by Oxford University Press.)

Alzheimer's disease (AD) in elderly adds substantially to socioeconomic burden necessitating early diagnosis. While recent studies in rodent models of AD have suggested diagnostic and therapeutic value for gamma rhythms in brain, the same has not been rigorously tested in humans. In this case-control study, we recruited a large population (N = 244; 106 females) of elderly (>49 years) subjects from the community, who viewed large gratings that induced strong gamma oscillations in their electroencephalogram (EEG). These subjects were classified as healthy (N = 227), mild cognitively impaired (MCI; N = 12), or AD (N = 5) based on clinical history and Clinical Dementia Rating scores. Surprisingly, stimulus-induced gamma rhythms, but not alpha or steady-state visually evoked responses, were significantly lower in MCI/AD subjects compared to their age- and gender-matched controls. This reduction was not due to differences in eye movements or baseline power. Our results suggest that gamma could be used as a potential screening tool for MCI/AD in humans., Competing Interests: DM, KM, WK, RR, SP, BN, AM, AB, MJ, NR, SR No competing interests declared, (© 2021, Murty et al.)

Gamma rhythms (~20-70 ​Hz) are abnormal in mental disorders such as autism and schizophrenia in humans, and Alzheimer's disease (AD) models in rodents. However, the effect of normal aging on these oscillations is unknown, especially for elderly subjects in whom AD is most prevalent. In a first large-scale (236 subjects; 104 females) electroencephalogram (EEG) study on gamma oscillations in elderly subjects (aged 50-88 years), we presented full-screen visual Cartesian gratings that induced two distinct gamma oscillations (slow: 20-34 ​Hz and fast: 36-66 ​Hz). Power decreased with age for gamma, but not alpha (8-12 ​Hz). Reduction was more salient for fast gamma than slow. Center frequency also decreased with age for both gamma rhythms. The results were independent of microsaccades, pupillary reactivity to stimulus, and variations in power spectral density with age. Steady-state visual evoked potentials (SSVEPs) at 32 ​Hz also reduced with age. These results are crucial for developing gamma/SSVEP-based biomarkers of cognitive decline in elderly., Competing Interests: Declaration of competing interest The authors declare no competing financial interests., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)