Fighting merchants

Selected essays from a conference held in November 2013 to celebrate the contribution to scholarship of the medieval historian Professor James L. Bolton

The service patterns and social-economic status of English archers, 1367-1417: the evidence of the muster rolls and poll tax returns

This thesis is a study of the men who served as archers in the armies of the English kings between 1367 and 1417. However, the focus is not the archers in their military capacity, but the motivations behind their service and their position in late medieval English society. Increasing usage of indentures, recorded in muster rolls, to recruit soldiers for English armies in this period provide historians with rich resources for the study of the military community. Previously this has focused on those of higher socio-economic backgrounds, serving mostly as men-at-arms, and not on those who served as archers. However by combining this muster roll data with information on residency, wealth, and occupations from the poll tax returns of 1377, 1379, and 1381 in a relational database the backgrounds and service links of the archers could be explored. There is a clearly identifiable group of archers whose service was not significantly motivated by political or social obligations and represents a shift towards military service as a ‘free market’, driven by economic considerations. This was apparent in the connections between archers and captains and in the patterns of service they followed, with the more professional archers ranging more widely in both the location and type of military service they performed. Despite this, it is evident that the archers were embedded within society and did not differ greatly in terms of occupation or wealth from their non-military peers. The difference between the careerist and ‘amateur’ archers was more subtle, with ‘amateur’ archers appearing in a wider range of economic backgrounds

covidregionaldata: Subnational data for COVID-19 epidemiology

covidregionaldatais an R (R Core Team, 2020) package that provides an interface tosubnational and national level COVID-19 data. The package provides cleaned and verifiedCOVID-19 test-positive case counts and, where available, counts of deaths, recoveries, andhospitalisations in a consistent and fully transparent framework. The package automatescommon processing steps while allowing researchers to easily and transparently trace theorigin of the underlying data sources. It has been designed to allow users to easily extend thepackage’s capabilities and contribute to shared data handling. All package code is archivedon Zenodo andGitHub

How accurate is patients' anatomical knowledge: a cross-sectional, questionnaire study of six patient groups and a general public sample

<p>Abstract</p> <p>Background</p> <p>Older studies have shown that patients often do not understand the terms used by doctors and many do not even have a rudimentary understanding of anatomy. The present study was designed to investigate the levels of anatomical knowledge of different patient groups and the general public in order to see whether this has improved over time and whether patients with a specific organ pathology (e.g. liver disease) have a relatively better understanding of the location of that organ.</p> <p>Methods</p> <p>Level of anatomical knowledge was assessed on a multiple-choice questionnaire, in a sample of 722 participants, comprising approximately 100 patients in each of 6 different diagnostic groups and 133 in the general population, using a between-groups, cross-sectional design. Comparisons of relative accuracy of anatomical knowledge between the present and earlier results, and across the clinical and general public groups were evaluated using Chi square tests. Associations with age and education were assessed with the Pearson correlation test and one-way analysis of variance, respectively.</p> <p>Results</p> <p>Across groups knowledge of the location of body organs was poor and has not significantly improved since an earlier equivalent study over 30 years ago (χ²= 0.04, df = 1, ns). Diagnostic groups did not differ in their overall scores but those with liver disease and diabetes were more accurate regarding the location of their respective affected organs (χ²= 18.10, p < 0.001, df = 1; χ²= 10.75, p < 0.01, df = 1). Age was significantly negatively correlated (r = -0.084, p = 0.025) and education was positively correlated with anatomical knowledge (F = 12.94, p = 0.000). Although there was no overall gender difference, women were significantly better at identifying organs on female body outlines.</p> <p>Conclusion</p> <p>Many patients and general public do not know the location of key body organs, even those in which their medical problem is located, which could have important consequences for doctor-patient communication. These results indicate that healthcare professionals still need to take care in providing organ specific information to patients and should not assume that patients have this information, even for those organs in which their medical problem is located.</p

The Evolution of tRNA Genes in Drosophila

The structure and function of transfer RNA (tRNA) genes have been extensively studied for several decades, yet the general mechanisms controlling tRNA gene family evolution remain unclear, primarily because previous phylogenetics-based methods fail to distinguish between paralogs and orthologs that are highly similar in sequence. We have developed a system for identifying orthologs of tRNAs using flanking sequences to identify regions of conserved synteny and used it to annotate sets of orthologous tRNA genes across the 12 sequenced species of Drosophila. These data have allowed us to place the gains and losses of individual tRNA genes on each branch of the Drosophila tree and estimate rates of tRNA gene turnover. Our results show extensive rearrangement of the Drosophila tRNA gene complement over the last 60 My. We estimate a combined average rate of 2.18 ± 0.10 tRNA gene gains and losses per million years across the Drosophila lineage. We have identified 192 tRNAs that are ancestral to the genus, of which 157 are “core” tRNAs conserved in at least 11 of 12 extant species. We provide evidence that the core set of tRNA genes encode a nearly complete set of anticodons and have different properties from other “peripheral” tRNA genes, such as preferential location outside large tRNA clusters and higher sequence conservation. We also demonstrate that tRNA isoacceptor and alloacceptor changes by anticodon shifts have occurred several times in Drosophila, annotating 16 such events in functional tRNAs during the evolution of the genus

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

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

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