Seattle’s Golden Dreams: Contemporary Perceptions of the Northern Gold Rushes

The discovery of gold in Alaska in 1897 brought about major changes in Seattle as this sleepy logging town awoke from a period of depression and received a revitalizing jolt as it rapidly developed into an important port for trade with the Alaskan frontier. This sudden growth was celebrated throughout the gold rush years and even up until the Alaska-Yukon-Pacific Exposition in 1909, but by this time, Seattle's greatness was already fading. In spite of a hopeful and expectant population that foresaw Seattle as the new New York of the West, Seattle relapsed into its former struggles. Although numerous critics predicted that Seattle's ";boom"; was solely a consequence of the gold rush, and incapable of sustaining the city's growth and prosperity, Seattleites maintained not only a sense of hope, but of extreme optimism with respect to their city's future. This paper will examine the perceived benefits of the northern gold rushes as reflected in contemporary columns in the Seattle Post-Intelligencer, arguing that, in the eyes of its inhabitants, Seattle was not only fast becoming a premier port city in the world, but her economic growth spurred on by the gold rushes was unmatched, so as to rival and outshine the competing ports of San Francisco and Portland. Additionally, the city's future bore every sign of an enduring continuation of these conditions. This paper will then proceed ten years into the future to consider the changes in these perceptions, showing that while much had changed, Seattle maintained the same expectant and hopeful view for the future

A Lightweight Text Mining Tool for Multisite Research

Background/Aims: The use of electronic medical records provides researchers and care administrators with access to increased patient information. Much of the information, however, is available only as unstructured data in clinical notes, which limits its accessibility. Various natural language processing systems seek to extract information from the clinical notes and present it as structured data, thereby increasing the data’s usability for research, care administration and quality assurance. Many of the available open-source tools, however, require nontrivial installation and configuration. In addition, customizations, debugging and portability can be challenging for some users. Methods: We developed a lightweight Python application that performs basic information extraction tasks, but that is easy to install, configure, customize and share. The application relies on a dictionary to extract content from unstructured data. The dictionary is a mapping of a set of concepts (e.g. “hypoesthesia”) to words and phrases that characterize how that concept would appear in clinical text (e.g. “decreased sensation,” “impaired sensation,” etc.). The application converts these words and phrases to regular expressions and searches the text for matching content, attempting to detect variations in spelling and to recognize when the word or phrase is qualified by negation, uncertainty, historical reference or a reference to someone other than the patient. Results: We tested the application using a dictionary of 792 entries on a set of 205,748 clinical notes. The application completed the information extraction task in less than two hours. We used the more comprehensive Apache Clinical Text Analysis and Knowledge Extraction System (cTAKES) as a comparison using the same dictionary and same notes. We stopped cTAKES after 8.5 days with 144,701 (68.9%) complete. Discussion: The application provides a quick means to access unstructured data with minimal configurations and environmental settings. Multiple sites can use the same algorithm simply by sharing the dictionary and a configuration file

A tracking transducer for following fish movement in shallow waterand at close range

Shallow water studies of fish behavior have used various methods for tracking fish. A new technique is shown to be promising because it can combine acoustic sizing with fish behavior studies. The principle of radar tracking, aligning the antenna beam with a target, was applied with an acoustic splitbeam transducer and dual-axis rotators for tracking individual fish over long periods of time. Deviation of the target from the beam axis produces a correction to point the axis toward the target. Initial studies with active acoustics have also evolved an acoustic tag tracking method. The system has successfully tracked several different types of fish, from juvenile salmon to sharks. The high speed of the rotators allows observations to be made at very short ranges. Much of the development of the tracking transducer targeted fish movement through dams on the Columbia and Snake Rivers. In a recent experiment, adult salmon, returning to the Fraser River, Canada were tracked to measure avoidance to surveying vessels. The feasibility for tracking sharks was shown at the Tacoma WA Point Defiance Aquarium. A proposed method for tracking salmon, sharks or other species with echoes and/or using acoustic tags will allow the determination of behavior, acoustic size, abundance, and associated pelagic assemblages

Prevalence of medical cannabis use and associated health conditions documented in electronic health records among primary care patients in Washington State.

Importance: Many people use cannabis for medical reasons despite limited evidence of therapeutic benefit and potential risks. Little is known about medical practitioners' documentation of medical cannabis use or clinical characteristics of patients with documented medical cannabis use. Objectives: To estimate the prevalence of past-year medical cannabis use documented in electronic health records (EHRs) and to describe patients with EHR-documented medical cannabis use, EHR-documented cannabis use without evidence of medical use (other cannabis use), and no EHR-documented cannabis use. Main Outcomes and Measures: Health conditions for which cannabis use has potential benefits or risks were defined based on National Academies of Sciences, Engineering, and Medicine's review. The adjusted prevalence of conditions diagnosed in the prior year were estimated across 3 categories of EHR-documented cannabis use with logistic regression. Results: A total of 185 565 patients (mean [SD] age, 52.0 [18.1] years; 59% female, 73% White, 94% non-Hispanic, and 61% commercially insured) were screened for cannabis use in a primary care visit during the study period. Among these patients, 3551 (2%) had EHR-documented medical cannabis use, 36 599 (20%) had EHR-documented other cannabis use, and 145 415 (78%) had no documented cannabis use. Patients with medical cannabis use had a higher prevalence of health conditions for which cannabis has potential benefits compared with patients with other cannabis use or no cannabis use. In addition, patients with medical cannabis use had a higher prevalence of health conditions for which cannabis has potential risks compared with patients with other cannabis use or no cannabis use. Conclusions and Relevance: In this cross-sectional study, primary care patients with documented medical cannabis use had a high prevalence of health conditions for which cannabis use has potential benefits, yet a higher prevalence of conditions with potential risks from cannabis use. These findings suggest that practitioners should be prepared to discuss potential risks and benefits of cannabis use with patients

LPA Variants are Associated with Residual Cardiovascular Risk in Patients Receiving Statins

BackgroundCoronary heart disease (CHD) is a leading cause of death globally. Although therapy with statins decreases circulating levels of low-density lipoprotein cholesterol and the incidence of CHD, additional events occur despite statin therapy in some individuals. The genetic determinants of this residual cardiovascular risk remain unknown.MethodsWe performed a 2-stage genome-wide association study of CHD events during statin therapy. We first identified 3099 cases who experienced CHD events (defined as acute myocardial infarction or the need for coronary revascularization) during statin therapy and 7681 controls without CHD events during comparable intensity and duration of statin therapy from 4 sites in the Electronic Medical Records and Genomics Network. We then sought replication of candidate variants in another 160 cases and 1112 controls from a fifth Electronic Medical Records and Genomics site, which joined the network after the initial genome-wide association study. Finally, we performed a phenome-wide association study for other traits linked to the most significant locus.ResultsThe meta-analysis identified 7 single nucleotide polymorphisms at a genome-wide level of significance within the LPA/PLG locus associated with CHD events on statin treatment. The most significant association was for an intronic single nucleotide polymorphism within LPA/PLG (rs10455872; minor allele frequency, 0.069; odds ratio, 1.58; 95% confidence interval, 1.35-1.86; P=2.6×10-10). In the replication cohort, rs10455872 was also associated with CHD events (odds ratio, 1.71; 95% confidence interval, 1.14-2.57; P=0.009). The association of this single nucleotide polymorphism with CHD events was independent of statin-induced change in low-density lipoprotein cholesterol (odds ratio, 1.62; 95% confidence interval, 1.17-2.24; P=0.004) and persisted in individuals with low-density lipoprotein cholesterol ≤70 mg/dL (odds ratio, 2.43; 95% confidence interval, 1.18-4.75; P=0.015). A phenome-wide association study supported the effect of this region on coronary heart disease and did not identify noncardiovascular phenotypes.ConclusionsGenetic variations at the LPA locus are associated with CHD events during statin therapy independently of the extent of low-density lipoprotein cholesterol lowering. This finding provides support for exploring strategies targeting circulating concentrations of lipoprotein(a) to reduce CHD events in patients receiving statins

Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network

Abstract The electronic Medical Records and Genomics (eMERGE) Network assessed the feasibility of deploying portable phenotype rule-based algorithms with natural language processing (NLP) components added to improve performance of existing algorithms using electronic health records (EHRs). Based on scientific merit and predicted difficulty, eMERGE selected six existing phenotypes to enhance with NLP. We assessed performance, portability, and ease of use. We summarized lessons learned by: (1) challenges; (2) best practices to address challenges based on existing evidence and/or eMERGE experience; and (3) opportunities for future research. Adding NLP resulted in improved, or the same, precision and/or recall for all but one algorithm. Portability, phenotyping workflow/process, and technology were major themes. With NLP, development and validation took longer. Besides portability of NLP technology and algorithm replicability, factors to ensure success include privacy protection, technical infrastructure setup, intellectual property agreement, and efficient communication. Workflow improvements can improve communication and reduce implementation time. NLP performance varied mainly due to clinical document heterogeneity; therefore, we suggest using semi-structured notes, comprehensive documentation, and customization options. NLP portability is possible with improved phenotype algorithm performance, but careful planning and architecture of the algorithms is essential to support local customizations

Can Evolution Explain Insanity?

I distinguish three evolutionary explanations of mental illness: first, breakdowns in evolved computational systems; second, evolved systems performing their evolutionary function in a novel environment; third, evolved personality structures. I concentrate on the second and third explanations, as these are distinctive of an evolutionary psychopathology, with progressively less credulity in the light of the empirical evidence. General morals are drawn for evolutionary psychiatry