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We propose a two-step method for studying the history of political thought roughly in line with the contextualism of the Cambridge School. It reframes the early Cambridge School as a bug-detecting program for the outdated conceptual baggage we unknowingly accommodate with our political terminology. Such accommodation often entails propositions that are inconsistent with even our most cherished political opinions. These bugs can cause political arguments to crash. This reframing takes seriously the importance of theories of meaning in the formative methodological arguments of the Cambridge School and updates the argument in light of new developments. We argue the new orthodoxy of Saul Kripke's causal theory of meaning in the philosophy of language better demonstrates the importance of contextual analysis to modern political theory.
While our fascination with understanding the past is sufficient to warrant an increased focus on synthesis, solutions to important problems facing modern society require understandings based on data that only archaeology can provide. Yet, even as we use public monies to collect ever-greater amounts of data, modes of research that can stimulate emergent understandings of human behavior have lagged behind. Consequently, a substantial amount of archaeological inference remains at the level of the individual project. We can more effectively leverage these data and advance our understandings of the past in ways that contribute to solutions to contemporary problems if we adapt the model pioneered by the National Center for Ecological Analysis and Synthesis to foster synthetic collaborative research in archaeology. We propose the creation of the Coalition for Archaeological Synthesis coordinated through a U.S.-based National Center for Archaeological Synthesis. The coalition will be composed of established public and private organizations that provide essential scholarly, cultural heritage, computational, educational, and public engagement infrastructure. The center would seek and administer funding to support collaborative analysis and synthesis projects executed through coalition partners. This innovative structure will enable the discipline to address key challenges facing society through evidentially based, collaborative synthetic research.
Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990–1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.
The Square Kilometre Array will be an amazing instrument for pulsar astronomy. While the full SKA will be sensitive enough to detect all pulsars in the Galaxy visible from Earth, already with SKA1, pulsar searches will discover enough pulsars to increase the currently known population by a factor of four, no doubt including a range of amazing unknown sources. Real time processing is needed to deal with the 60 PB of pulsar search data collected per day, using a signal processing pipeline required to perform more than 10 POps. Here we present the suggested design of the pulsar search engine for the SKA and discuss challenges and solutions to the pulsar search venture.
Risk adjustment is needed to fairly compare central-line–associated bloodstream infection (CLABSI) rates between hospitals. Until 2017, the Centers for Disease Control and Prevention (CDC) methodology adjusted CLABSI rates only by type of intensive care unit (ICU). The 2017 CDC models also adjust for hospital size and medical school affiliation. We hypothesized that risk adjustment would be improved by including patient demographics and comorbidities from electronically available hospital discharge codes.
Using a cohort design across 22 hospitals, we analyzed data from ICU patients admitted between January 2012 and December 2013. Demographics and International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) discharge codes were obtained for each patient, and CLABSIs were identified by trained infection preventionists. Models adjusting only for ICU type and for ICU type plus patient case mix were built and compared using discrimination and standardized infection ratio (SIR). Hospitals were ranked by SIR for each model to examine and compare the changes in rank.
Overall, 85,849 ICU patients were analyzed and 162 (0.2%) developed CLABSI. The significant variables added to the ICU model were coagulopathy, paralysis, renal failure, malnutrition, and age. The C statistics were 0.55 (95% CI, 0.51–0.59) for the ICU-type model and 0.64 (95% CI, 0.60–0.69) for the ICU-type plus patient case-mix model. When the hospitals were ranked by adjusted SIRs, 10 hospitals (45%) changed rank when comorbidity was added to the ICU-type model.
Our risk-adjustment model for CLABSI using electronically available comorbidities demonstrated better discrimination than did the CDC model. The CDC should strongly consider comorbidity-based risk adjustment to more accurately compare CLABSI rates across hospitals.
This study aimed to assess the feasibility of a low-literacy adaptation of the Alzheimer’s Disease Assessment Scale – Cognitive (ADAS-Cog) for use in rural sub-Saharan Africa (SSA) for interventional studies in dementia. No such adaptations currently exist.
Tanzanian and Nigerian health professionals adapted the ADAS-Cog by consensus. Validation took place in a cross-sectional sample of 34 rural-dwelling older adults with mild/moderate dementia alongside 32 non-demented controls in Tanzania. Participants were oversampled for lower educational level. Inter-rater reliability was conducted by two trained raters in 22 older adults (13 with dementia) from the same population. Assessors were blind to diagnostic group.
Median ADAS-Cog scores were 28.75 (interquartile range (IQR), 22.96–35.54) in mild/moderate dementia and 12.75 (IQR 9.08–16.16) in controls. The area under the receiver operating characteristic curve (AUC) was 0.973 (95% confidence interval (CI) 0.936–1.00) for dementia. Internal consistency was high (Cronbach’s α 0.884) and inter-rater reliability was excellent (intra-class correlation coefficient 0.905, 95% CI 0.804–0.964).
The low-literacy adaptation of the ADAS-Cog had good psychometric properties in this setting. Further evaluation in similar settings is required.
To determine which comorbid conditions are considered causally related to central-line associated bloodstream infection (CLABSI) and surgical-site infection (SSI) based on expert consensus.
Using the Delphi method, we administered an iterative, 2-round survey to 9 infectious disease and infection control experts from the United States.
Based on our selection of components from the Charlson and Elixhauser comorbidity indices, 35 different comorbid conditions were rated from 1 (not at all related) to 5 (strongly related) by each expert separately for CLABSI and SSI, based on perceived relatedness to the outcome. To assign expert consensus on causal relatedness for each comorbid condition, all 3 of the following criteria had to be met at the end of the second round: (1) a majority (>50%) of experts rating the condition at 3 (somewhat related) or higher, (2) interquartile range (IQR)≤1, and (3) standard deviation (SD)≤1.
From round 1 to round 2, the IQR and SD, respectively, decreased for ratings of 21 of 35 (60%) and 33 of 35 (94%) comorbid conditions for CLABSI, and for 17 of 35 (49%) and 32 of 35 (91%) comorbid conditions for SSI, suggesting improvement in consensus among this group of experts. At the end of round 2, 13 of 35 (37%) and 17 of 35 (49%) comorbid conditions were perceived as causally related to CLABSI and SSI, respectively.
Our results have produced a list of comorbid conditions that should be analyzed as risk factors for and further explored for risk adjustment of CLABSI and SSI.
Thirty-seven lines from a population derived from the hull-less barley cultivar, Penthouse, were grown in a replicated trial over three seasons and assessed for grain yield. Following harvest, a rapid test to measure grain dimensions was applied to all samples, to look for novel variation in grain size and shape, as a possible way of detecting mutations. A range of grain and malt quality traits was also measured in two of the seasons, to detect genotype × season interactions and determine relationships between the measured traits. There were significant differences between years for all traits and between genotypes for most. Genotype × season interaction was significant for grain dimensions and some malting traits, but a correlation between malting quality and grain dimensions was only observed in one season. Line 30 showed very high yield potential in a comparatively wet season and gave a higher alcohol yield per unit area than a hulled control variety, while lines 21 and 33 contained putative additional mutations. Line 21, previously observed to have higher enzyme activity, appeared to contain an additional dwarfing gene and was characterized by smaller grain, later ear emergence and lower yield. Line 33, with malting potential, showed considerably altered grain length to width ratio and will be further investigated as a possible globosum type.
Medical factors including tuberculosis, scurvy, lead poisoning and botulism have been proposed to explain the high death rate prior to desertion of the ships on Sir John Franklin's expedition of 1845–1848 but their role remains unclear because the surgeons’ Sick books which recorded illness on board have eluded discovery. In their absence, this study examines the Sick books of Royal Naval search squadrons sent in search of Franklin, and which encountered similar conditions to his ships, to consider whether their morbidity and mortality might reflect that of the missing expedition. The Sick books of HMS Assistance, Enterprise, Intrepid, Investigator, Pioneer and Resolute yielded 1,480 cases that were coded for statistical analysis. On the basis of the squadrons’ patterns of illness it was concluded that Franklin's crews would have suffered common respiratory and gastro-intestinal disorders, injuries and exposure and that deaths might have occurred from respiratory, cardiovascular and tubercular conditions. Scurvy occurred commonly and it was shown that the method of preparing ‘antiscorbutic’ lemon juice for the search squadrons and Franklin's ships would have reduced its capacity to prevent the disease but there were no grounds to conclude that scurvy was significant at the time of deserting the ships. There was no clear evidence of lead poisoning despite the relatively high level of lead exposure that was inevitable on ships at that time. There was no significant difference between the deaths of non-officer ranks on Franklin's ships and several of the search ships. The greater number of deaths of Franklin's officers was proposed to be more probably a result of non-medical factors such as accidents and injuries sustained while hunting and during exploration.
The prevalence of dementia is increasing in Asia than in any other continent. However, the applicability of the existing cognitive assessment tools is limited by differences in educational and cultural factors in this setting. We conducted a systematic review of published studies on cognitive assessments tools in Asia. We aimed to rationalize the results of available studies which evaluated the validity of cognitive tools for the detection of cognitive impairment and to identify the issues surrounding the available cognitive impairment screening tools in Asia.
Five electronic databases (CINAHL, MEDLINE, Embase, Cochrane Library, and Science Direct) were searched using the keywords dementia Or Alzheimer Or cognitive impairment And screen Or measure Or test Or tool Or instrument Or assessment, and 2,381 articles were obtained.
Thirty-eight articles, evaluating 28 tools in seven Asian languages, were included. Twenty-nine (76%) of the studies had been conducted in East Asia with only four studies conducted in South Asia and no study from northern, western, or central Asia or Indochina. Local language translations of the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were assessed in 15 and six studies respectively. Only three tools (the Korean Dementia Screening Questionnaire, the Picture-based Memory Intelligence Scale, and the revised Hasegawa Dementia Screen) were derived de novo from Asian populations. These tools were assessed in five studies. Highly variable cut-offs were reported for the MMSE (17–29/30) and MoCA (21–26/30), with 13/19 (68%) of studies reporting educational bias.
Few cognitive assessment tools have been validated in Asia, with no published validation studies for many Asian nations and languages. In addition, many available tools display educational bias. Future research should include concerted efforts to develop culturally appropriate tools with minimal educational bias.
A trend toward greater body size in dizygotic (DZ) than in monozygotic (MZ) twins has been suggested by some but not all studies, and this difference may also vary by age. We analyzed zygosity differences in mean values and variances of height and body mass index (BMI) among male and female twins from infancy to old age. Data were derived from an international database of 54 twin cohorts participating in the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins), and included 842,951 height and BMI measurements from twins aged 1 to 102 years. The results showed that DZ twins were consistently taller than MZ twins, with differences of up to 2.0 cm in childhood and adolescence and up to 0.9 cm in adulthood. Similarly, a greater mean BMI of up to 0.3 kg/m2 in childhood and adolescence and up to 0.2 kg/m2 in adulthood was observed in DZ twins, although the pattern was less consistent. DZ twins presented up to 1.7% greater height and 1.9% greater BMI than MZ twins; these percentage differences were largest in middle and late childhood and decreased with age in both sexes. The variance of height was similar in MZ and DZ twins at most ages. In contrast, the variance of BMI was significantly higher in DZ than in MZ twins, particularly in childhood. In conclusion, DZ twins were generally taller and had greater BMI than MZ twins, but the differences decreased with age in both sexes.
For over 100 years, the genetics of human anthropometric traits has attracted scientific interest. In particular, height and body mass index (BMI, calculated as kg/m2) have been under intensive genetic research. However, it is still largely unknown whether and how heritability estimates vary between human populations. Opportunities to address this question have increased recently because of the establishment of many new twin cohorts and the increasing accumulation of data in established twin cohorts. We started a new research project to analyze systematically (1) the variation of heritability estimates of height, BMI and their trajectories over the life course between birth cohorts, ethnicities and countries, and (2) to study the effects of birth-related factors, education and smoking on these anthropometric traits and whether these effects vary between twin cohorts. We identified 67 twin projects, including both monozygotic (MZ) and dizygotic (DZ) twins, using various sources. We asked for individual level data on height and weight including repeated measurements, birth related traits, background variables, education and smoking. By the end of 2014, 48 projects participated. Together, we have 893,458 height and weight measures (52% females) from 434,723 twin individuals, including 201,192 complete twin pairs (40% monozygotic, 40% same-sex dizygotic and 20% opposite-sex dizygotic) representing 22 countries. This project demonstrates that large-scale international twin studies are feasible and can promote the use of existing data for novel research purposes.
Archaeological data and research results are essential to addressing such fundamental questions as the origins of human culture; the origin, waxing, and waning of civilizations and cities; the response of societies to long-term climate changes; and the systemic relationships implicated in human-induced changes in the environment. However, we lack the capacity for acquiring, managing, analyzing, and synthesizing the data sets needed to address important questions such as these. We propose investments in computational infrastructure that would transform archaeology’s ability to advance research on the field’s most compelling questions with an evidential base and inferential rigor that have heretofore been impossible. At the same time, new infrastructure would make archaeological data accessible to researchers in other disciplines. We offer recommendations regarding data management and availability, cyberinfrastructure tool building, and social and cultural changes in the discipline. We propose funding synthetic case studies that would demonstrate archaeology’s ability to contribute to transdisciplinary research on long-term social dynamics and serve as a context for developing computational tools and analytical workflows that will be necessary to attack these questions. The case studies would explore how emerging research in computer science could empower this research and would simultaneously provide productive challenges for computer science research.
Central line–associated bloodstream infection (BSI) rates are a key quality metric for comparing hospital quality and safety. Traditional BSI surveillance may be limited by interrater variability. We assessed whether a computer-automated method of central line–associated BSI detection can improve the validity of surveillance.
Retrospective cohort study.
Eight medical and surgical intensive care units (ICUs) in 4 academic medical centers.
Traditional surveillance (by hospital staff) and computer algorithm surveillance were each compared against a retrospective audit review using a random sample of blood culture episodes during the period 2004–2007 from which an organism was recovered. Episode-level agreement with audit review was measured with κ statistics, and differences were assessed using the test of equal κ coefficients. Linear regression was used to assess the relationship between surveillance performance (κ) and surveillance-reported BSI rates (BSIs per 1,000 central line–days).
We evaluated 664 blood culture episodes. Agreement with audit review was significantly lower for traditional surveillance (κ [95% confidence interval (CI)] = 0.44 [0.37–0.51]) than computer algorithm surveillance (κ [95% CI] [0.52–0.64]; P = .001). Agreement between traditional surveillance and audit review was heterogeneous across ICUs (P = .001); furthermore, traditional surveillance performed worse among ICUs reporting lower (better) BSI rates (P = .001). In contrast, computer algorithm performance was consistent across ICUs and across the range of computer-reported central line–associated BSI rates.
Compared with traditional surveillance of bloodstream infections, computer automated surveillance improves accuracy and reliability, making interfacility performance comparisons more valid.
Infect Control Hosp Epidemiol 2014;35(12):1483–1490