Monsters: interdisciplinary explorations in monstrosity

There is a continued fascination with all things monster. This is partly due to the popular reception of Mary Shelley’s Monster, termed a “new species” by its overreaching but admiringly determined maker Victor Frankenstein in the eponymous novel first published in 1818. The enduring impact of Shelley’s novel, which spans a plethora of subjects and genres in imagery and themes, raises questions of origin and identity, death, birth and family relationships as well as the contradictory qualities of the monster. Monsters serve as metaphors for anxieties of aberration and innovation. Stephen Asma (2009) notes that monsters represent evil or moral transgression and each epoch, to speak with Michel Foucault, evidences a “particular type of monster” (2003, 66). Academic debates tend to explore how social and cultural threats come to be embodied in the figure of a monster and their actions literalize our deepest fears. Monsters in contemporary culture, however, have become are more humane than ever before. Monsters are strong, resilient, creative and sly creatures. Through their playful and invigorating energy they can be seen to disrupt and unsettle. They still cater to the appetite for horror, but they also encourage us to feel empathy. The encounter with a monster can enable us to stop, wonder and change our attitudes towards technology and our body and each other. This commentary article considers the use of the concepts of ‘monsters’ or ‘monstrosity’ in literature, contemporary research, culture and teaching contexts at the intersection of the Humanities and the Social Sciences

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Re-Arrest Among Juvenile Justice-Involved Youth: An Examination Of The Static And Dynamic Risk Factors

The purpose of this study is to investigate the static and dynamic risk factors for re-arrest among detained youth by examining gender, race/ethnicity, age, special education and mental health variables (i.e., anger/irritability, depression/anxiety, somatic complaints, suicide ideation, thought disturbances, and traumatic experiences). The demographic profiles of detained youth with one admit were also compared with those with multiple admits to the juvenile detention center. With regards to static risk factors, older, white, and special education were significantly at risk of re-arrest. Concerning dynamic risk factors, only anger/irritability predicted re-arrest. Practice implications are also discussed

Production of ultrasonic vocalizations by Peromyscus mice in the wild

BACKGROUND: There has been considerable research on rodent ultrasound in the laboratory and these sounds have been well quantified and characterized. Despite the value of research on ultrasound produced by mice in the lab, it is unclear if, and when, these sounds are produced in the wild, and how they function in natural habitats. RESULTS: We have made the first recordings of ultrasonic vocalizations produced by two free-living species of mice in the genus Peromyscus (P. californicus and P. boylii) on long term study grids in California. Over 6 nights, we recorded 65 unique ultrasonic vocalization phrases from Peromyscus. The ultrasonic vocalizations we recorded represent 7 different motifs. Within each motif, there was considerable variation in the acoustic characteristics suggesting individual and contextual variation in the production of ultrasound by these species. CONCLUSION: The discovery of the production of ultrasonic vocalizations by Peromyscus in the wild highlights an underappreciated component in the behavior of these model organisms. The ability to examine the production of ultrasonic vocalizations in the wild offers excellent opportunities to test hypotheses regarding the function of ultrasound produced by rodents in a natural context

Array-CGH and breast cancer

The introduction of comparative genomic hybridization (CGH) in 1992 opened new avenues in genomic investigation; in particular, it advanced analysis of solid tumours, including breast cancer, because it obviated the need to culture cells before their chromosomes could be analyzed. The current generation of CGH analysis uses ordered arrays of genomic DNA sequences and is therefore referred to as array-CGH or matrix-CGH. It was introduced in 1998, and further increased the potential of CGH to provide insight into the fundamental processes of chromosomal instability and cancer. This review provides a critical evaluation of the data published on array-CGH and breast cancer, and discusses some of its expected future value and developments

First-principles quantum transport modeling of spin-transfer and spin-orbit torques in magnetic multilayers

We review a unified approach for computing: (i) spin-transfer torque in magnetic trilayers like spin-valves and magnetic tunnel junction, where injected charge current flows perpendicularly to interfaces; and (ii) spin-orbit torque in magnetic bilayers of the type ferromagnet/spin-orbit-coupled-material, where injected charge current flows parallel to the interface. Our approach requires to construct the torque operator for a given Hamiltonian of the device and the steady-state nonequilibrium density matrix, where the latter is expressed in terms of the nonequilibrium Green's functions and split into three contributions. Tracing these contributions with the torque operator automatically yields field-like and damping-like components of spin-transfer torque or spin-orbit torque vector, which is particularly advantageous for spin-orbit torque where the direction of these components depends on the unknown-in-advance orientation of the current-driven nonequilibrium spin density in the presence of spin-orbit coupling. We provide illustrative examples by computing spin-transfer torque in a one-dimensional toy model of a magnetic tunnel junction and realistic Co/Cu/Co spin-valve, both of which are described by first-principles Hamiltonians obtained from noncollinear density functional theory calculations; as well as spin-orbit torque in a ferromagnetic layer described by a tight-binding Hamiltonian which includes spin-orbit proximity effect within ferromagnetic monolayers assumed to be generated by the adjacent monolayer transition metal dichalcogenide.Comment: 22 pages, 9 figures, PDFLaTeX; prepared for Springer Handbook of Materials Modeling, Volume 2 Applications: Current and Emerging Material