Castoffs

These poems concern the entangled relationships people have with landscapes, images, and histories. They explore, in part, how seemingly unimportant experiences continue to provoke perceptions over time

Measuring quality of general reasoning

Machine learning models that automatically assess reasoning quality are trained on human-annotated written products. These “gold-standard” corpora are typically created by prompting annotators to choose, using a forced choice design, which of two products presented side by side is the most convincing, contains the strongest evidence or would be adopted by more people. Despite the increase in popularity of using a forced choice design for assessing quality of reasoning (QoR), no study to date has established the validity and reliability of such a method. In two studies, we simultaneously presented two products of reasoning to participants and asked them to identify which product was ‘better justified’ through a forced choice design. We investigated the criterion validity and inter-rater reliability of the forced choice protocol by assessing the relationship between QoR, measured using the forced choice protocol, and accuracy in objectively answerable problems using naive raters sampled from MTurk (Study 1) and experts (Study 2), respectively. In both studies products that were closer to the correct answer and products generated by larger teams were consistently preferred. Experts were substantially better at picking the reasoning products that corresponded to accurate answers. Perhaps the most surprising finding was just how rapidly raters made judgements regarding reasoning: On average, both novices and experts made reliable decisions in under 15 seconds. We conclude that forced choice is a valid and reliable method of assessing QoR

Validating a forced‑choice method for eliciting quality‑of‑reasoning judgments

In this paper we investigate the criterion validity of forced-choice comparisons of the quality of written arguments with normative solutions. Across two studies, novices and experts assessing quality of reasoning through a forced-choice design were both able to choose arguments supporting more accurate solutions—62.2% (SE = 1%) of the time for novices and 74.4% (SE = 1%) for experts—and arguments produced by larger teams—up to 82% of the time for novices and 85% for experts—with high inter-rater reliability, namely 70.58% (95% CI = 1.18) agreement for novices and 80.98% (95% CI = 2.26) for experts. We also explored two methods for increasing efficiency. We found that the number of comparative judgments needed could be substantially reduced with little accuracy loss by leveraging transitivity and producing quality-of-reasoning assessments using an AVL tree method. Moreover, a regression model trained to predict scores based on automatically derived linguistic features of participants’ judgments achieved a high correlation with the objective accuracy scores of the arguments in our dataset. Despite the inherent subjectivity involved in evaluating differing quality of reasoning, the forced-choice paradigm allows even novice raters to perform beyond chance and can provide a valid, reliable, and efficient method for producing quality-of-reasoning assessments at scale

Molly Users Versus Non-Users in a Sample of College Alcohol Drinkers: Differences in Substance-Related Harms and Sensation Seeking

Background: Molly is one form of MDMA (3,4-methylenedioxymethamphetamine) that is touted to be more pure and potentially less harmful than other forms, such as ecstasy. Media reports and case studies suggest that this drug is popular among college students and is related to adverse health problems. The current study sought to address the knowledge gaps about Molly by examining whether users differ in substance use outcomes and sensation seeking than nonusers. Specifically, this study tested whether Molly users engaged in heavier use of other substances and experienced more substance-related harms in general than nonusers. Further, the current study investigated whether Molly users exhibited higher levels of sensation seeking than nonusers. Lastly, this study examined whether Molly user status would be associated with substance-related harms beyond the confounding influence of other substance use and trait sensation seeking. Methods: Participants were 710 (71.9% female) college alcohol drinkers who completed self-report surveys about substance use (i.e., Molly, alcohol, and other drug use), substance-related problems, and sensation seeking. Results: Results revealed that approximately 12% of the sample reported lifetime Molly use. Molly users compared with nonusers reported higher levels of other drug use, alcohol use, substance-related problems, and sensation seeking. Further, Molly users reported experiencing poorer substance use outcomes (e.g., blacking out, academic/occupational problems, and withdrawal symptoms) after accounting for sensation seeking and other substance use. Conclusions: These findings indicate that Molly users are higher in sensation seeking and that use is uniquely related to greater risk for substance-related harms. These preliminary findings demonstrate a need for correcting possible misperceptions regarding the purity of Molly and educating users on the potential for experiencing associated harms. Such information could be used to develop efficacious prevention programming for college students

Drinking beer, wine or spirits – does it matter for inequalities in alcohol-related hospital admission? A record-linked longitudinal study in Wales

Background: Alcohol-related harm has been found to be higher in disadvantaged groups, despite similar alcohol consumption to advantaged groups. This is known as the alcohol harm paradox. Beverage type is reportedly socioeconomically patterned but has not been included in longitudinal studies investigating record-linked alcohol consumption and harm. We aimed to investigate whether and to what extent consumption by beverage type, BMI, smoking and other factors explain inequalities in alcohol-related harm. Methods: 11,038 respondents to the Welsh Health Survey answered questions on their health and lifestyle. Responses were record-linked to wholly attributable alcohol-related hospital admissions (ARHA) eight years before the survey month and until the end of 2016 within the Secure Anonymised Information Linkage (SAIL) Databank. We used survival analysis, specifically multi-level and multi-failure Cox mixed effects models, to calculate the hazard ratios of ARHA. In adjusted models we included the number of units consumed by beverage type and other factors, censoring for death or moving out of Wales. Results: People living in more deprived areas had a higher risk of admission (HR 1.75; 95% CI 1.23–2.48) compared to less deprived. Adjustment for the number of units by type of alcohol consumed only reduced the risk of ARHA for more deprived areas by 4% (HR 1.72; 95% CI 1.21–2.44), whilst adding smoking and BMI reduced these inequalities by 35.7% (HR 1.48; 95% CI 1.01–2.17). These social patterns were similar for individual-level social class, employment, housing tenure and highest qualification. Inequalities were further reduced by including either health status (16.6%) or mental health condition (5%). Unit increases of spirits drunk were positively associated with increasing risk of ARHA (HR 1.06; 95% CI 1.01–1.12), higher than for other drink types. Conclusions: Although consumption by beverage type was socioeconomically patterned, it did not help explain inequalities in alcohol-related harm. Smoking and BMI explained around a third of inequalities, but lower socioeconomic groups had a persistently higher risk of (multiple) ARHA. Comorbidities also explained a further proportion of inequalities and need further investigation, including the contribution of specific conditions. The increased harms from consumption of stronger alcoholic beverages may inform public health policy

External validation of the electronic Frailty Index using the population of Wales within the Secure Anonymised Information Linkage Databank

Background: frailty has major implications for health and social care services internationally. The development, validation and national implementation of the electronic Frailty Index (eFI) using routine primary care data has enabled change in the care of older people living with frailty in England. Aims: to externally validate the eFI in Wales and assess new frailty-related outcomes. Study design and setting: retrospective cohort study using the Secure Anonymised Information Linkage (SAIL) Databank, comprising 469,000 people aged 65–95, registered with a SAIL contributing general practice on 1 January 2010. Methods: four categories (fit; mild; moderate and severe) of frailty were constructed using recognised cut points from the eFI. We calculated adjusted hazard ratios (HRs) from Cox regression models for validation of existing outcomes: 1-, 3- and 5-year mortality, hospitalisation, and care home admission for validation. We also analysed, as novel outcomes, 1-year mortality following hospitalisation and frailty transition times. Results: HR trends for the validation outcomes in SAIL followed the original results from ResearchOne and THIN databases. Relative to the fit category, adjusted HRs in SAIL (95% CI) for 1-year mortality following hospitalisation were 1.05 (95% CI 1.03-1.08) for mild frailty, 1.24 (95% CI 1.21-1.28) for moderate frailty and 1.51 (95% CI 1.45-1.57) for severe frailty. The median time (lower and upper quartile) between frailty categories was 2,165 days (lower and upper quartiles: 1,510 and 2,831) from fit to mild, 1,155 days (lower and upper quartiles: 756 and 1,610) from mild to moderate and 898 days (lower and upper quartiles: 584 and 1,275) from moderate to severe. Conclusions: further validation of the eFI showed robust predictive validity and utility for new outcomes

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

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

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