Doing referring in Murriny Patha conversation

Successful communication hinges on keeping track of who and what we are talking about. For this reason, person reference sits at the heart of the social sciences. Referring to persons is an interactional process where information is transferred from current speakers to the recipients of their talk. This dissertation concerns itself with the work that is achieved through this transfer of information. The interactional approach adopted is one that combines the “micro” of conversation analysis with the “macro” of genealogically grounded anthropological linguistics. Murriny Patha, a non-Pama-Nyungan language spoken in the north of Australia, is a highly complex polysynthetic language with kinship categories that are grammaticalized as verbal inflections. For referring to persons, as well as names, nicknames, kinterms, minimal descriptions and free pronouns, Murriny Patha speakers make extensive use of pronominal reference markers embedded within polysynthetic verbs. Murriny Patha does not have a formal “mother-in-law” register. There are however numerous taboos on naming kin in avoidance relationships, and on naming and their namesakes. Similarly, there are also taboos on naming the deceased and on naming their namesakes. As a result, for every speaker there is a multitude of people whose names should be avoided. At any one time, speakers of the language have a range of referential options. Speakers’ decisions about which category of reference forms to choose (names, kinterms etc.) are governed by conversational preferences that shape “referential design”. Six preferences – a preference for associating the referent to the co-present conversationalists, a preference for avoiding personal names, a preference for using recognitionals, a preference for being succinct, and a pair of opposed preferences relating to referential specificity – guide speakers towards choosing a name on one occasion, a kinterm on the next occasion and verbal cross-reference on yet another occasion. Different classes of expressions better satisfy particular conversational preferences. There is a systematicity to the referential choices that speakers make. The interactional objectives of interlocutors are enacted through the regular placement of particular forms in particular sequential environments. These objectives are then revealed through the turn-by-turn unfolding of conversational interaction

Bias in protein and potassium intake collected with 24-h recalls (EPIC-Soft) is rather comparable across European populations

Purpose: We investigated whether group-level bias of a 24-h recall estimate of protein and potassium intake, as compared to biomarkers, varied across European centers and whether this was influenced by characteristics of individuals or centers. Methods: The combined data from EFCOVAL and EPIC studies included 14 centers from 9 countries (n = 1,841). Dietary data were collected using a computerized 24-h recall (EPIC-Soft). Nitrogen and potassium in 24-h urine collections were used as reference method. Multilevel linear regression analysis was performed, including individual-level (e.g., BMI) and center-level (e.g., food pattern index) variables. Results: For protein intake, no between-center variation in bias was observed in men while it was 5.7% in women. For potassium intake, the between-center variation in bias was 8.9% in men and null in women. BMI was an important factor influencing the biases across centers (p <0.01 in all analyses). In addition, mode of administration (p = 0.06 in women) and day of the week (p = 0.03 in men and p = 0.06 in women) may have influenced the bias in protein intake across centers. After inclusion of these individual variables, between-center variation in bias in protein intake disappeared for women, whereas for potassium, it increased slightly in men (to 9.5%). Center-level variables did not influence the results. Conclusion: The results suggest that group-level bias in protein and potassium (for women) collected with 24-h recalls does not vary across centers and to a certain extent varies for potassium in men. BMI and study design aspects, rather than center-level characteristics, affected the biases across center

3-D Inlet Shock-Boundary Layer Interactions - PIV Database for the Second SBLI Workshop

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97090/1/AIAA2012-3214.pd

Comparison of characteristics of patients with lung cancer in U.K. primary care databases: Clinical Practice Research Datalink Aurum and GOLD

INTRODUCTION: In recent years, the number of general practices contributing to the Clinical Practice Research Datalink (CPRD) database GOLD is decreasing. Therefore, for research questions addressing for instance novel treatments requiring up-to-date data, sample size will become an important consideration in study feasibility. In recent years, CPRD Aurum, containing information of practices that use EMIS software, has become an additional data source that is being used for CPRD studies. In order to establish whether Aurum is suited to act as data source for future studies in the field of lung cancer research, we aimed to compare characteristics between patients with lung cancer in Aurum and GOLD. METHODS: A retrospective study was performed comparing characteristics and overall survival (OS) of patients with lung cancer in Aurum and GOLD. To further evaluate similarity, hypothetical eligibility of these patients in Aurum and GOLD was compared for 11 randomized clinical trials (RCTs). RESULTS: Baseline characteristics registered in Aurum and GOLD were largely similar, with some clinically irrelevant differences for previous malignancies, deviant laboratory values and drug use. Median OS was 9.8 and 9.0 months for patients in Aurum and GOLD, respectively. Potential RCT eligibility varied between 49.4% and 79.5% and 49.1% and 78.1% for patients in Aurum and GOLD, respectively. Mortality rates and the comparison of the obtained HRs per hypothetical eligibility cohort per RCT were similar in Aurum and GOLD. CONCLUSION: This study showed that data of patients with lung cancer in Aurum and GOLD are largely comparable, suggesting that Aurum is suitable for future epidemiological lung cancer research

Genotype determination for polymorphisms in linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Genome-wide association studies with single nucleotide polymorphisms (SNPs) show great promise to identify genetic determinants of complex human traits. In current analyses, genotype calling and imputation of missing genotypes are usually considered as two separated tasks. The genotypes of SNPs are first determined one at a time from allele signal intensities. Then the missing genotypes, i.e., no-calls caused by not perfectly separated signal clouds, are imputed based on the linkage disequilibrium (LD) between multiple SNPs. Although many statistical methods have been developed to improve either genotype calling or imputation of missing genotypes, treating the two steps independently can lead to loss of genetic information.</p> <p>Results</p> <p>We propose a novel genotype calling framework. In this framework, we consider the signal intensities and underlying LD structure of SNPs simultaneously by estimating both cluster parameters and haplotype frequencies. As a result, our new method outperforms some existing algorithms in terms of both call rates and genotyping accuracy. Our studies also suggest that jointly analyzing multiple SNPs in LD provides more accurate estimation of haplotypes than haplotype reconstruction methods that only use called genotypes.</p> <p>Conclusion</p> <p>Our study demonstrates that jointly analyzing signal intensities and LD structure of multiple SNPs is a better way to determine genotypes and estimate LD parameters.</p

Effect of metabolic genetic variants on long-term disease comorbidity in patients with type 2 diabetes

Underlying genetic determinants contribute to developing type 2 diabetes (T2D) future diseases. The present study aimed to identify which genetic variants are associated with the incident of the major T2D co-morbid disease. First, we conducted a discovery study by investigating the genetic associations of comorbid diseases within the framework of the Utrecht Cardiovascular Pharmacogenetic studies by turning information of > 25 years follow-up data of 1237 subjects whom were genotyped and included in the discovery study. We performed Cox proportional-hazards regression to examine associations between genetic variants and comorbid diseases including cardiovascular diseases (CVD), chronic eye disease, cancer, neurologic diseases and chronic kidney disease. Secondly, we replicated our findings in two independent cohorts consisting of 1041 subjects. Finally, we performed a meta-analysis by combining the discovery and two replication cohorts. We ascertained 390 (39.7%) incident cases of CVD, 182 (16.2%) of chronic eye disease, 155 (13.8%) of cancer, 31 (2.7%) of neurologic disease and 13 (1.1%) of chronic kidney disease during a median follow-up of 10.2 years. In the discovery study, we identified a total of 39 Single Nucleotide Polymorphisms (SNPs) associated with comorbid diseases. The replication study, confirmed that rs1870849 and rs8051326 may play a role in the incidence of chronic eye disease in T2D patients. Half of patients developed at least one comorbid disease, with CVD occurring most often and earliest followed by chronic eye disease. Further research is needed to confirm the associations of two associated SNPs with chronic eye disease in T2D

Improving 10-year cardiovascular risk prediction in apparently healthy people : flexible addition of risk modifiers on top of SCORE2

AIMS: In clinical practice, factors associated with cardiovascular disease (CVD) like albuminuria, education level, or coronary artery calcium (CAC) are often known, but not incorporated in cardiovascular risk prediction models. The aims of the current study were to evaluate a methodology for the flexible addition of risk modifying characteristics on top of SCORE2 and to quantify the added value of several clinically relevant risk modifying characteristics. METHODS AND RESULTS: Individuals without previous CVD or DM were included from the UK Biobank; Atherosclerosis Risk in Communities (ARIC); Multi-Ethnic Study of Atherosclerosis (MESA); European Prospective Investigation into Cancer, The Netherlands (EPIC-NL); and Heinz Nixdorf Recall (HNR) studies (n = 409 757) in whom 16 166 CVD events and 19 149 non-cardiovascular deaths were observed over exactly 10.0 years of follow-up. The effect of each possible risk modifying characteristic was derived using competing risk-adjusted Fine and Gray models. The risk modifying characteristics were applied to individual predictions with a flexible method using the population prevalence and the subdistribution hazard ratio (SHR) of the relevant predictor. Risk modifying characteristics that increased discrimination most were CAC percentile with 0.0198 [95% confidence interval (CI) 0.0115; 0.0281] and hs-Troponin-T with 0.0100 (95% CI 0.0063; 0.0137). External validation was performed in the Clinical Practice Research Datalink (CPRD) cohort (UK, n = 518 015, 12 675 CVD events). Adjustment of SCORE2-predicted risks with both single and multiple risk modifiers did not negatively affect calibration and led to a modest increase in discrimination [0.740 (95% CI 0.736-0.745) vs. unimproved SCORE2 risk C-index 0.737 (95% CI 0.732-0.741)]. CONCLUSION: The current paper presents a method on how to integrate possible risk modifying characteristics that are not included in existing CVD risk models for the prediction of CVD event risk in apparently healthy people. This flexible methodology improves the accuracy of predicted risks and increases applicability of prediction models for individuals with additional risk known modifiers