The 2010 Native American and Indigenous Studies Association Conference

The 2010 Native American Indigenous Studies Conference was held at The Westin La Paloma Resort, Tucson, Arizona, USA from 20-22 May. The conference was scholarly and interdisciplinary and intended for Indigenous and non-Indigenous scholars who work in American Indian/ Native American/ First Nations/ Aboriginal/ Indigenous Studies. The 2010 gathering attracted 768 registrations from the USA, Canada, Hawaii, Mexico, New Zealand and Australia and other countries. This paper is a personal reflection and overview of the 2010 Conference.

Pretreatment malnutrition and quality of life - association with prolonged length of hospital stay among patients with gynecological cancer: A cohort study

Background Length of hospital stay (LOS) is a surrogate marker for patients' well-being during hospital treatment and is associated with health care costs. Identifying pretreatment factors associated with LOS in surgical patients may enable early intervention in order to reduce postoperative LOS. Methods This cohort study enrolled 157 patients with suspected or proven gynecological cancer at a tertiary cancer centre (2004-2006). Before commencing treatment, the scored Patient Generated - Subjective Global Assessment (PG-SGA) measuring nutritional status and the Functional Assessment of Cancer Therapy-General (FACT-G) scale measuring quality of life (QOL) were completed. Clinical and demographic patient characteristics were prospectively obtained. Patients were grouped into those with prolonged LOS if their hospital stay was greater than the median LOS and those with average or below average LOS. Results Patients' mean age was 58 years (SD 14 years). Preoperatively, 81 (52%) patients presented with suspected benign disease/pelvic mass, 23 (15%) with suspected advanced ovarian cancer, 36 (23%) patients with suspected endometrial and 17 (11%) with cervical cancer, respectively. In univariate models prolonged LOS was associated with low serum albumin or hemoglobin, malnutrition (PG-SGA score and PG-SGA group B or C), low pretreatment FACT-G score, and suspected diagnosis of cancer. In multivariable models, PG-SGA group B or C, FACT-G score and suspected diagnosis of advanced ovarian cancer independently predicted LOS. Conclusions Malnutrition, low quality of life scores and being diagnosed with advanced ovarian cancer are the major determinants of prolonged LOS amongst gynecological cancer patients. Interventions addressing malnutrition and poor QOL may decrease LOS in gynecological cancer patients.

A systematic review of the association between physical activity and colorectal cancer risk

This review evaluated the strength of the evidence for a causal relationship between physical activity (PA) and colorectal cancer (CRC). A systematic review of databases through February 2008 was conducted to identify studies that assessed the association between total or recreational PA and incidence or mortality of CRC (including CRC, rectal cancer, colon cancer, and proximal or distal colon cancer). Studies were evaluated for significant associations between PA and risk of CRC endpoints and for evidence of dose–response relationships in the highest quality studies. Twenty cohort studies were evaluated; 11 were high-quality. Fifty percent of all studies and 64%of highest quality studies reported at least one significant association between PA and risk of a CRC endpoint (Po0.05).However, only 28%of all analyses (31% of analyses of highest quality studies) were significant (Po0.05). Only 40% of analyses of highest quality studies resulted in a significant P for trend (Po0.05); however, a non-significant inverse linear association between PA and colon cancer riskwas apparent.Heterogeneity in the evidence from all studies and from the highest quality studies was evident. Evidence from cohort studies is not sufficient to claim a convincing relationship exists between PA and CRC risk.

Is the association between temperature and mortality modified by age, gender and socio-economic status?

Background: A number of studies have examined the relationship between high ambient temperature and mortality. Recently, concern has arisen about whether this relationship is modified by socio-demographic factors. However, data for this type of study is relatively scarce in subtropical/tropical regions where people are well accustomed to warm temperatures. Objective: To investigate whether the relationship between daily mean temperature and daily all-cause mortality is modified by age, gender and socio-economic status (SES) in Brisbane, Australia. Methods: We obtained daily mean temperature and all-cause mortality data for Brisbane, Australia during 1996–2004. A generalised additive model was fitted to assess the percentage increase in all deaths with every one degree increment above the threshold temperature. Different age, gender and SES groups were included in the model as categorical variables and their modification effects were estimated separately. Results: A total of 53,316 non-external deaths were included during the study period. There was a clear increasing trend in the harmful effect of high temperature on mortality with age. The effect estimate among women was more than 20 times that among men. We did not find an SES effect on the percent increase associated with temperature. Conclusions: The effects of high temperature on all deaths were modified by age and gender but not by SES in Brisbane, Australia.

The association between MC1R genotype and BRAF mutation status in cutaneous melanoma : findings from an Australian population

There is increasing epidemiological and molecular evidence that cutaneous melanomas arise through multiple causal pathways. The purpose of this study was to explore the relationship between germline and somatic mutations in a population-based series of melanoma patients to reshape and refine the divergent pathway model for melanoma. Melanomas collected from 123 Australian patients were analyzed for melanocortin-1 receptor (MC1R) variants and mutations in the BRAF and NRAS genes. Detailed phenotypic and sun exposure data were systematically collected from all patients. We found that BRAF-mutant melanomas were significantly more likely from younger patients and those with high nevus counts, and were more likely in melanomas with adjacent neval remnants. Conversely, BRAF-mutant melanomas were significantly less likely in people with high levels of lifetime sun exposure. We observed no association between germline MC1R status and somatic BRAF mutations in melanomas from this population. BRAF-mutant melanomas have different origins from other cutaneous melanomas. These data support the divergent pathways hypothesis for melanoma, which may require a reappraisal of targeted cancer prevention activities.

Availability of advance visual information constrains association-football goalkeeping performance during penalty kicks

A pressing concern within the literature on anticipatory perceptual-motor behaviour is the lack of clarity on the applicability of data, observed under video-simulation task constraints, to actual performance in which actions are coupled to perception, as captured during in-situ experimental conditions. We developed an in-situ experimental paradigm which manipulated the duration of anticipatory visual information from a penalty taker’s actions to examine experienced goalkeepers’ vulnerability to deception for the penalty kick in association football. Irrespective of the penalty taker’s kick strategy, goalkeepers initiated movement responses earlier across consecutively earlier presentation points. Overall goalkeeping performance was better in non-deception trials than in deception conditions. In deception trials, the kinematic information presented up until the penalty taker initiated his/her kicking action had a negative effect on goalkeepers’ performance. It is concluded that goalkeepers are likely to benefit from not anticipating a penalty taker’s performance outcome based on information from the run-up, in preference to later information that emerges just before the initiation of the penalty taker’s kicking action.

Physical function and health-related quality of life of older adults undergoing hospital rehabilitation : how strong is the association?

The purpose of this research is to report preliminary empirical evidence regarding the association between common physical performance measures and health-related quality of life (HRQoL) of hospitalized older adults recovering from illness and injury. Frequently, these patients do not return to premorbid levels of independence and physical ability. Rehabilitation for this population often focuses on improving physical functioning and mobility with the intention of maximizing their HRQoL for discharge and thereafter. For this reason, longitudinal use of physical performance measures as an indicator of improvement in physical functioning (and thus HRQoL) is common. Although this is a logical approach, there have been mixed results from previous investigations into the association between common measures of physical function and HRQoL amongst other adult patient populations.1,2 There has been no previous investigation reporting the association between HRQoL and a variety of common physical performance measures in hospitalized older adults.

Using Association Rules to Solve the Cold-Start Problem in Recommender Systems

Recommender systems are widely used online to help users find other products, items etc that they may be interested in based on what is known about that user in their profile. Often however user profiles may be short on information and thus it is difficult for a recommender system to make quality recommendations. This problem is known as the cold-start problem. Here we investigate using association rules as a source of information to expand a user profile and thus avoid this problem. Our experiments show that it is possible to use association rules to noticeably improve the performance of a recommender system under the cold-start situation. Furthermore, we also show that the improvement in performance obtained can be achieved while using non-redundant rule sets. This shows that non-redundant rules do not cause a loss of information and are just as informative as a set of association rules that contain redundancy.

HapMap tag-SNP analysis confirms a role for COMT in schizophrenia risk and reveals a novel association

Catechol-O-methyl transferase (COMT) encodes an enzyme involved in the metabolism of dopamine and maps to a commonly deleted region that increases schizophrenia risk. A non-synonymous polymorphism (rs4680) in COMT has been previously found to be associated with schizophrenia and results in altered activity levels of COMT. Using a haplotype block-based gene-tagging approach we conducted an association study of seven COMT single nucleotide polymorphisms (SNPs) in 160 patients with a DSM-IV diagnosis of schizophrenia and 250 controls in an Australian population. Two polymorphisms including rs4680 and rs165774 were found to be significantly associated with schizophrenia. The rs4680 results in a Val/Met substitution but the strongest association was shown by the novel SNP, rs165774, which may still be functional even though it is located in intron five. Individuals with schizophrenia were more than twice as likely to carry the GG genotype compared to the AA genotype for both the rs165774 and rs4680 SNPs. This association was slightly improved when males were analysed separately possibly indicating a degree of sexual dimorphism. Our results confirm that COMT is a good candidate for schizophrenia risk, by replicating the association with rs4680 and identifying a novel SNP association.

Analysis of HapMap tag-SNPs in dysbindin (DTNBP1) reveals evidence of consistent association with schizophrenia

Dystrobrevin binding protein 1 (DTNBP1), or dysbindin, is thought to be critical in regulating the glutamatergic system. While the dopamine pathway is known to be important in the aetiology of schizophrenia, it seems likely that glutamatergic dysfunction can lead to the development of schizophrenia. DTNBP1 is widely expressed in brain, levels are reduced in brains of schizophrenia patients and a DTNBP1 polymorphism has been associated with reduced brain expression. Despite numerous genetic studies no DTNBP1 polymorphism has been strongly implicated in schizophrenia aetiology. Using a haplotype block-based gene-tagging approach we genotyped 13 SNPs in DTNBP1 to investigate possible associations with DTNBP1 and schizophrenia. Four polymorphisms were found to be significantly associated with schizophrenia. The strongest association was found with an A/C SNP in intron 7 (rs9370822). Homozygotes for the C allele of rs9370822 were more than two and a half times as likely to have schizophrenia compared to controls. The other polymorphisms showed much weaker association and are less likely to be biologically significant. These results suggest that DTNBP1 is a good candidate for schizophrenia risk and rs9370822 is either functionally important or in disequilibrium with a functional SNP, although our observations should be viewed with caution until they are independently replicated.

Individual differences in the visual control of intercepting a penalty kick in association football

Recent perceptual-motor studies have revealed variations in learning trajectories of novices. Despite such observation, relatively little attention has been paid to studying individual differences in experienced performers’ perceptual-motor behaviors. The present study examined individual differences for a visual anticipation task. Experienced association football goalkeepers attempted to intercept penalty kicks taken with deceptive and non-deceptive kicking actions. Data revealed that differences in the action capabilities of goalkeepers affected the timing and accuracy of movement response behaviors. Faster goalkeepers tended to wait until later before initiating movement in comparison with slower goalkeepers. The study of affordances in sport environments offers a theoretical framework with which to overcome some of the reported methodological limitations in the visual anticipation literature.

The ecological dynamics of 1v1 sub-phases in association football

This paper analyzes effects of different practice task constraints on heart rate (HR) variability during 4v4 smallsided football games. Participants were sixteen football players divided into two age groups (U13, Mean age: 12.4±0.5 yrs; U15: 14.6±0.5). The task consisted of a 4v4 sub-phase without goalkeepers, on a 25x15 m field, of 15 minutes duration with an active recovery period of 6 minutes between each condition. We recorded players’ heart rates using heart rate monitors (Polar Team System, Polar Electro, Kempele, Finland) as scoring mode was manipulated (line goal: scoring by dribbling past an extended line; double goal: scoring in either of two lateral goals; and central goal: scoring only in one goal). Subsequently, %HR reserve was calculated with the Karvonen formula. We performed a time-series analysis of HR for each individual in each condition. Mean data for intra-participant variability showed that autocorrelation function was associated with more short-range dependence processes in the “line goal” condition, compared to other conditions, demonstrating that the “line goal” constraint induced more randomness in HR response. Relative to inter-individual variability, line goal constraints demonstrated lower %CV and %RMSD (U13: 9% and 19%; U15: 10% and 19%) compared with double goal (U13: 12% and 21%; U15: 12% and 21%) and central goal (U13: 14% and 24%; U15: 13% and 24%) task constraints, respectively. Results suggested that line goal constraints imposed more randomness on cardiovascular stimulation of each individual and lower inter-individual variability than double goal and central goal constraints.

Reliable representations for association rules

Association rule mining has contributed to many advances in the area of knowledge discovery. However, the quality of the discovered association rules is a big concern and has drawn more and more attention recently. One problem with the quality of the discovered association rules is the huge size of the extracted rule set. Often for a dataset, a huge number of rules can be extracted, but many of them can be redundant to other rules and thus useless in practice. Mining non-redundant rules is a promising approach to solve this problem. In this paper, we first propose a definition for redundancy, then propose a concise representation, called a Reliable basis, for representing non-redundant association rules. The Reliable basis contains a set of non-redundant rules which are derived using frequent closed itemsets and their generators instead of using frequent itemsets that are usually used by traditional association rule mining approaches. An important contribution of this paper is that we propose to use the certainty factor as the criterion to measure the strength of the discovered association rules. Using this criterion, we can ensure the elimination of as many redundant rules as possible without reducing the inference capacity of the remaining extracted non-redundant rules. We prove that the redundancy elimination, based on the proposed Reliable basis, does not reduce the strength of belief in the extracted rules. We also prove that all association rules, their supports and confidences, can be retrieved from the Reliable basis without accessing the dataset. Therefore the Reliable basis is a lossless representation of association rules. Experimental results show that the proposed Reliable basis can significantly reduce the number of extracted rules. We also conduct experiments on the application of association rules to the area of product recommendation. The experimental results show that the non-redundant association rules extracted using the proposed method retain the same inference capacity as the entire rule set. This result indicates that using non-redundant rules only is sufficient to solve real problems needless using the entire rule set.

Discovery & effective use of quality association rules in multi-level datasets

In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.