The price of empire: Anglo-French rivalry for the Great Lakes fur trades, 1700-1760

As the English and French grappled for North American hegemony in the first half of the eighteenth century, trade with the Indian groups of the Great Lakes and Ohio Valley transcended mere financial calculations and assumed a broader imperial significance. to the native peoples who exchanged their peltry for European manufactured goods, trade was the material manifestation of mutual obligation, political dialogue, and military alliance. If the contest for empire inevitably became a battle for the hearts and minds of potential Indian allies, the spoils of victory were most visibly reckoned in furs and skins.;Yet, despite the outspoken criticism of William J. Eccles, historians of Anglo-French trade rivalry continue to embrace the dubious claims of Cadwallader Colden and other eighteenth-century American imperialists that Canadian traders could not compete on level economic ground with their New York and Pennsylvania counterparts. Allegedly beset with shoddy and costly French goods, a jealous monopoly company that greedily fixed the price of furs and skins, and the levies and restrictions of a militaristic state, Canadians were deemed unable to match the success of their Anglo-American competitors, who conversely reaped the benefits of cheap and superior trade merchandise in a commerce largely free of meddling monopolists and obtrusive officials.;A rigorous cross-border comparison of trade-good costs, transportation charges, and peltry prices deflates this hoary myth of Anglo-American economic superiority. With few exceptions, French-Canadian fur traders supplied goods of equal or better quality at rates of exchange competitive with their New York and Pennsylvania rivals. Purely economic considerations, however, never determined success in the trade. as frustrated Anglo-American officials readily admitted, the cohesive and scrupulously-managed French-Canadian trade network proved aptly suited to winning and maintaining Indian friendship and alliance, while unregulated and unscrupulous American traders perennially poisoned Anglo-Indian relations. The persistence of characteristically Canadian commercial practices and Indian trade loyalties despite the 1760 conquest of New France is, perhaps, the most compelling measure of French-Canadian preeminence in the eighteenth-century contest for North American trade and empire

Non-steroidal anti-inflammatory drugs (NSAIDs) in cancer pain:A database analysis to determine recruitment feasibility for a clinical trial

BACKGROUND: Insufficient evidence exists to support or refute use of NSAIDs for managing cancer pain. Palliative physicians support a placebo-controlled trial of NSAIDs as strong opioid adjuncts for cancer-induced bone pain as the most pragmatic design to benefit clinical practice. AIM: We aimed to determine patient numbers receiving palliative radiotherapy for cancer-induced bone pain, estimate the suitability of NSAID prescription and determine survival, guiding future trial feasibility. DESIGN: A retrospective observational database analysis was undertaken using 5 years of routinely collected regional radiotherapy and healthcare data, filtered to achieve a cohort with cancer-induced bone pain. Demographics and survival were linked to available serology and co-morbidity data. SETTING/PARTICIPANTS: Data was sourced from the regional Leeds Cancer Centre, a tertiary care setting. Patients who underwent palliative single fraction 8 gray (Gy) radiotherapy treatment for cancer-induced bone pain were included, totalling 2411 over 5 years. RESULTS: A mean of 478 patients received palliative radiotherapy for cancer-induced bone pain annually. Median age (IQR) was 70 (62–77); negatively skewed (−0.69). 65.3% died within 1 year of radiotherapy; 48.0% within 6 months. Age was not associated with survival on univariable analysis (HR 0.999 (95% CI 0.996–1.003)). Serology from 1063 patients (44.2%) were available; eGFR was ⩾60 mL/min/1.73 m(2) in 83.0%. From available data (1352 pts; 51.6% of sample), 20.2% had a coded co-morbidity contra-indicating NSAIDs. Combining serology and co-morbidities, 68.5% could be considered for NSAID prescription. CONCLUSIONS: Patient numbers at a regional radiotherapy centre support the feasibility of trial recruitment. Available serology and co-morbidity data suggest two-thirds may be suitable for NSAID prescription

InnateDB: systems biology of innate immunity and beyond—recent updates and continuing curation

peer-reviewedInnateDB (http://www.innatedb.com) is an integrated analysis platform that has been specifically designed to facilitate systems-level analyses of mammalian innate immunity networks, pathways and genes. In this article, we provide details of recent updates and improvements to the database. InnateDB now contains >196 000 human, mouse and bovine experimentally validated molecular interactions and 3000 pathway annotations of relevance to all mammalian cellular systems (i.e. not just immune relevant pathways and interactions). In addition, the InnateDB team has, to date, manually curated in excess of 18 000 molecular interactions of relevance to innate immunity, providing unprecedented insight into innate immunity networks, pathways and their component molecules. More recently, InnateDB has also initiated the curation of allergy- and asthma-related interactions. Furthermore, we report a range of improvements to our integrated bioinformatics solutions including web service access to InnateDB interaction data using Proteomics Standards Initiative Common Query Interface, enhanced Gene Ontology analysis for innate immunity, and the availability of new network visualizations tools. Finally, the recent integration of bovine data makes InnateDB the first integrated network analysis platform for this agriculturally important model organism.This work was supported by Genome BC through the Pathogenomics of Innate Immunity (PI2) project and by the Foundation for the National Institutes of Health and the Canadian Institutes of Health Research under the Grand Challenges in Global Health Research Initiative [Grand Challenges ID: 419]. Further funding was also provided by AllerGen grants 12ASI1 and 12B&B2. D.J.L. was funded in part during this project by a postdoctoral trainee award from the Michael Smith Foundation for Health Research (MSFHR). F.S.L.B. is a MSFHR Senior Scholar and R.E.W.H. holds a Canada Research Chair (CRC). Funding to enable bovine systems biology in InnateDB is provided by Teagasc [RMIS6018] and the Teagasc Walsh Fellowship scheme. IMEx is funded by the European Commission under the PSIMEx project [contract number FP7-HEALTH-2007-223411]. Funding for open access charge: Teagasc [RMIS6018]

PSORTdb: a protein subcellular localization database for bacteria

Information about bacterial subcellular localization (SCL) is important for protein function prediction and identification of suitable drug/vaccine/diagnostic targets. PSORTdb (http://db.psort.org/) is a web-accessible database of SCL for bacteria that contains both information determined through laboratory experimentation and computational predictions. The dataset of experimentally verified information (∼2000 proteins) was manually curated by us and represents the largest dataset of its kind. Earlier versions have been used for training SCL predictors, and its incorporation now into this new PSORTdb resource, with its associated additional annotation information and dataset version control, should aid researchers in future development of improved SCL predictors. The second component of this database contains computational analyses of proteins deduced from the most recent NCBI dataset of completely sequenced genomes. Analyses are currently calculated using PSORTb, the most precise automated SCL predictor for bacterial proteins. Both datasets can be accessed through the web using a very flexible text search engine, a data browser, or using BLAST, and the entire database or search results may be downloaded in various formats. Features such as GO ontologies and multiple accession numbers are incorporated to facilitate integration with other bioinformatics resources. PSORTdb is freely available under GNU General Public License

Chronic cigarette smoking is linked with structural alterations in brain regions showing acute nicotinic drug-induced functional modulations

Background Whereas acute nicotine administration alters brain function which may, in turn, contribute to enhanced attention and performance, chronic cigarette smoking is linked with regional brain atrophy and poorer cognition. However, results from structural magnetic resonance imaging (MRI) studies comparing smokers versus nonsmokers have been inconsistent and measures of gray matter possess limited ability to inform functional relations or behavioral implications. The purpose of this study was to address these interpretational challenges through meta-analytic techniques in the service of clarifying the impact of chronic smoking on gray matter integrity and more fully contextualizing such structural alterations. Methods We first conducted a coordinate-based meta-analysis of structural MRI studies to identify consistent structural alterations associated with chronic smoking. Subsequently, we conducted two additional meta-analytic assessments to enhance insight into potential functional and behavioral relations. Specifically, we performed a multimodal meta-analytic assessment to test the structural?functional hypothesis that smoking-related structural alterations overlapped those same regions showing acute nicotinic drug-induced functional modulations. Finally, we employed database driven tools to identify pairs of structurally impacted regions that were also functionally related via meta-analytic connectivity modeling, and then delineated behavioral phenomena associated with such functional interactions via behavioral decoding. Results Across studies, smoking was associated with convergent structural decreases in the left insula, right cerebellum, parahippocampus, multiple prefrontal cortex (PFC) regions, and the thalamus. Indicating a structural?functional relation, we observed that smoking-related gray matter decreases overlapped with the acute functional effects of nicotinic agonist administration in the left insula, ventromedial PFC, and mediodorsal thalamus. Suggesting structural-behavioral implications, we observed that the left insula?s task-based, functional interactions with multiple other structurally impacted regions were linked with pain perception, the right cerebellum?s interactions with other regions were associated with overt body movements, interactions between the parahippocampus and thalamus were linked with memory processes, and interactions between medial PFC regions were associated with face processing. Conclusions Collectively, these findings emphasize brain regions (e.g., ventromedial PFC, insula, thalamus) critically linked with cigarette smoking, suggest neuroimaging paradigms warranting additional consideration among smokers (e.g., pain processing), and highlight regions in need of further elucidation in addiction (e.g., cerebellum). Electronic supplementary material The online version of this article (doi:10.1186/s12993-016-0100-5) contains supplementary material, which is available to authorized users

Automated Annotation of Functional Imaging Experiments via Multi-Label Classification

Identifying the experimental methods in human neuroimaging papers is important for grouping meaningfully similar experiments for meta-analyses. Currently, this can only be done by human readers. We present the performance of common machine learning (text mining) methods applied to the problem of automatically classifying or labeling this literature. Labeling terms are from the Cognitive Paradigm Ontology (CogPO), the text corpora are abstracts of published functional neuroimaging papers, and the methods use the performance of a human expert as training data. We aim to replicate the expert’s annotation of multiple labels per abstract identifying the experimental stimuli, cognitive paradigms, response types, and other relevant dimensions of the experiments. We use several standard machine learning methods: naive Bayes (NB), k -nearest neighbor, and support vector machines (specifically SMO or sequential minimal optimization). Exact match performance ranged from only 15% in the worst cases to 78% in the best cases. NB methods combined with binary relevance transformations performed strongly and were robust to overfitting. This collection of results demonstrates what can be achieved with off-the-shelf software components and little to no pre-processing of raw text

Percutaneous cervical cordotomy for cancer-related pain : national data

Objectives: Percutaneous cervical cordotomy (PCC) is an interventional ablative procedure in the armamentarium for cancer pain treatment, but there is limited evidence to support its use. This study aimed to assess the effectiveness and safety of PCC. Methods: Analysis was undertaken of the first national (UK) prospective data repository of adult patients with cancer undergoing PCC for pain treatment. The relationship between pain and other outcomes before and after PCC was examined using appropriate statistical methods. Results: Data on 159 patients’ PCCs (performed from 1 January 2012 to 6 June 2017 in three centres) were assessed: median (IQR) age was 66 (58–71) years, 47 (30%) were female. Mesothelioma was the most common primary malignancy (57%). The median (IQR) time from cancer diagnosis to PCC assessment was 13.3 (6.2–23.2) months; PCC to follow-up was 9 (8–25) days; and survival after PCC was 1.3 (0.6–2.8) months. The mean (SD) for ‘average pain’ using a numerical rating scale was 6 (2) before PCC and 2 (2) at follow-up, and for ‘worst pain’ 9 (1) and 3 (3), respectively. The median (IQR) reduction in strong opioid dose at follow-up was 50% (34–50). With the exception of ‘activity’, all health-related quality of life scores (5-level version of EuroQol-5 Dimension) either improved or were stable after PCC. Six patients (4%) had PCC-related adverse events. Conclusions: PCC is an effective treatment for cancer pain; however, findings in this study suggest PCC referrals tended to be late in patients’ disease trajectories. Further study into earlier treatment and seeking international consensus on PCC outcomes will further enhance opportunities to improve patient care

Automated, Efficient, and Accelerated Knowledge Modeling of the Cognitive Neuroimaging Literature Using the ATHENA Toolkit

Neuroimaging research is growing rapidly, providing expansive resources for synthesizing data. However, navigating these dense resources is complicated by the volume of research articles and variety of experimental designs implemented across studies. The advent of machine learning algorithms and text-mining techniques has advanced automated labeling of published articles in biomedical research to alleviate such obstacles. As of yet, a comprehensive examination of document features and classifier techniques for annotating neuroimaging articles has yet to be undertaken. Here, we evaluated which combination of corpus (abstract-only or full-article text), features (bag-of-words or Cognitive Atlas terms), and classifier (Bernoulli naïve Bayes, k-nearest neighbors, logistic regression, or support vector classifier) resulted in the highest predictive performance in annotating a selection of 2,633 manually annotated neuroimaging articles. We found that, when utilizing full article text, data-driven features derived from the text performed the best, whereas if article abstracts were used for annotation, features derived from the Cognitive Atlas performed better. Additionally, we observed that when features were derived from article text, anatomical terms appeared to be the most frequently utilized for classification purposes and that cognitive concepts can be identified based on similar representations of these anatomical terms. Optimizing parameters for the automated classification of neuroimaging articles may result in a larger proportion of the neuroimaging literature being annotated with labels supporting the meta-analysis of psychological constructs

Neural response to monetary loss among youth with disruptive behavior disorders and callous-unemotional traits in the ABCD study

Etiological models highlight reduced punishment sensitivity as a core risk factor for disruptive behavior disorders (DBD) and callous-unemotional (CU) traits. The current study examined neural sensitivity to the anticipation and receipt of loss, one key aspect of punishment sensitivity, among youth with DBD, comparing those with and without CU traits. Data were obtained from the Adolescent Brain and Cognitive Development (ABCD)SM Study (N = 11,874; Mage = 9.51; 48% female). Loss-related fMRI activity during the monetary incentive delay task was examined across 16 empirically-derived a priori brain regions (e.g., striatum, amygdala, insula, anterior cingulate cortex, medial prefrontal cortex) and compared across the following groups: (1) typically developing (n = 693); (2) DBD (n = 995), subdivided into those (3) with CU traits (DBD + CU, n = 198), and (4) without CU traits (DBD-only, n = 276). Latent variable modeling was also employed to examine network-level activity. There were no significant between-group differences in brain activity to loss anticipation or receipt. Null findings were confirmed with and without covariates, using alternative grouping approaches, and in dimensional models. Network-level analyses also demonstrated comparable activity across groups during loss anticipation and receipt. Findings suggest that differences in punishment sensitivity among youth with DBD are unrelated to loss anticipation or receipt. More precise characterizations of other aspects punishment sensitivity are needed to understand risk for DBD and CU traits