276 resultados para Graham, Andrew J. (Andrew Jackson), 1830-1894.
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This structural magnetic resonance imaging study examined the relationship between pituitary gland volume (PGV) and lifetime number of parasuicidal behaviors in a first-presentation, teenage borderline personality disorder (BPD) sample with minimal exposure to treatment. Hierarchical regression analysis revealed that age and number of parasuicidal behaviors were significant predictors of PGV. These findings indicate that parasuicidal behavior in BPD might be associated with greater activation of the hypothalamic-pituitary-adrenal (HPA) axis. Further studies are required using direct neuroendocrine measures and exploring other parameters of self-injurious behavior, such as recency of self-injurious behavior, intent to die and medical threat.
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This study used magnetic resonance imaging to examine pituitary gland volume (PGV) in teenage patients with a first presentation of borderline personality disorder (BPD). No difference in PGV was observed between healthy controls (n=20) and the total BPD cohort (n=20). However, within the BPD cohort, those exposed to childhood trauma (n=9) tended to have smaller pituitaries (-18%) than those with no history of childhood trauma (n=10). These preliminary findings suggest that exposure to childhood trauma, rather than BPD, per se, might be associated with reduced PGV, possibly reflecting hypothalamic-pituitary-adrenal axis dysfunction.
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This work describes the development of a model of cerebral atrophic changes associated with the progression of Alzheimer's disease (AD). Linear registration, region-of-interest analysis, and voxel-based morphometry methods have all been employed to elucidate the changes observed at discrete intervals during a disease process. In addition to describing the nature of the changes, modeling disease-related changes via deformations can also provide information on temporal characteristics. In order to continuously model changes associated with AD, deformation maps from 21 patients were averaged across a novel z-score disease progression dimension based on Mini Mental State Examination (MMSE) scores. The resulting deformation maps are presented via three metrics: local volume loss (atrophy), volume (CSF) increase, and translation (interpreted as representing collapse of cortical structures). Inspection of the maps revealed significant perturbations in the deformation fields corresponding to the entorhinal cortex (EC) and hippocampus, orbitofrontal and parietal cortex, and regions surrounding the sulci and ventricular spaces, with earlier changes predominantly lateralized to the left hemisphere. These changes are consistent with results from post-mortem studies of AD.
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Antigen selection of B cells within the germinal center reaction generally leads to the accumulation of replacement mutations in the complementarity-determining regions (CDRs) of immunoglobulin genes. Studies of mutations in IgE-associated VDJ gene sequences have cast doubt on the role of antigen selection in the evolution of the human IgE response, and it may be that selection for high affinity antibodies is a feature of some but not all allergic diseases. The severity of IgE-mediated anaphylaxis is such that it could result from higher affinity IgE antibodies. We therefore investigated IGHV mutations in IgE-associated sequences derived from ten individuals with a history of anaphylactic reactions to bee or wasp venom or peanut allergens. IgG sequences, which more certainly experience antigen selection, served as a control dataset. A total of 6025 unique IgE and 5396 unique IgG sequences were generated using high throughput 454 pyrosequencing. The proportion of replacement mutations seen in the CDRs of the IgG dataset was significantly higher than that of the IgE dataset, and the IgE sequences showed little evidence of antigen selection. To exclude the possibility that 454 errors had compromised analysis, rigorous filtering of the datasets led to datasets of 90 core IgE sequences and 411 IgG sequences. These sequences were present as both forward and reverse reads, and so were most unlikely to include sequencing errors. The filtered datasets confirmed that antigen selection plays a greater role in the evolution of IgG sequences than of IgE sequences derived from the study participants.
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Background The growing awareness of transfusion-associated morbidity and mortality necessitates investigations into the underlying mechanisms. Small animals have been the dominant transfusion model but have associated limitations. This study aimed to develop a comprehensive large animal (ovine) model of transfusion encompassing: blood collection, processing and storage, compatibility testing right through to post-transfusion outcomes. Materials and methods Two units of blood were collected from each of 12 adult male Merino sheep and processed into 24 ovine-packed red blood cell (PRBC) units. Baseline haematological parameters of ovine blood and PRBC cells were analysed. Biochemical changes in ovine PRBCs were characterized during the 42-day storage period. Immunological compatibility of the blood was confirmed with sera from potential recipient sheep, using a saline and albumin agglutination cross-match. Following confirmation of compatibility, each recipient sheep (n = 12) was transfused with two units of ovine PRBC. Results Procedures for collecting, processing, cross-matching and transfusing ovine blood were established. Although ovine red blood cells are smaller and higher in number, their mean cell haemoglobin concentration is similar to human red blood cells. Ovine PRBC showed improved storage properties in saline–adenine–glucose–mannitol (SAG-M) compared with previous human PRBC studies. Seventy-six compatibility tests were performed and 17·1% were incompatible. Only cross-match compatible ovine PRBC were transfused and no adverse reactions were observed. Conclusion These findings demonstrate the utility of the ovine model for future blood transfusion studies and highlight the importance of compatibility testing in animal models involving homologous transfusions.
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Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10−8). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10−4, Bonferroni corrected), of which six reached P < 5 × 10−8, including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.
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The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1–3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region4, 5, 6, 7, 8, 9, 10, 11. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods—recursive partitioning and regression...
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Background The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age–sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development. Methods We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time. Findings Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6–6·6), from 65·3 years (65·0–65·6) in 1990 to 71·5 years (71·0–71·9) in 2013, HALE at birth rose by 5·4 years (4·9–5·8), from 56·9 years (54·5–59·1) to 62·3 years (59·7–64·8), total DALYs fell by 3·6% (0·3–7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6–29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non–communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries. Interpretation Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition—in which increasing sociodemographic status brings structured change in disease burden—is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions.
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Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.
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Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10−8). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
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Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10−8), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ~2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
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Background An Advanced Pharmacy Practice Framework for Australia (the ‘APPF’) was published in October 2012. Further to the release of the APPF, the Advanced Pharmacy Practice Framework Steering Committee planned to develop an advanced practice recognition model for Australian pharmacists. Aim To gauge the perspectives of the pharmacy profession relating to advanced practice, via an online survey, in order to inform the design of the model. Method A survey was developed and administered to Australian pharmacists through SurveyMonkey . The survey content was based on findings from a review of national and international initiatives for recognition of advanced practice in pharmacy and other health disciplines, including medicine and nursing. Results The results of the survey showed that a high proportion of respondents considered they were already working at, or working towards achieving, an advanced level of practice. The responses relating to the assessment methods showed a clear preference for ‘submission of a professional portfolio’. A ‘written examination’ had a low level of support and in relation to an ‘oral examination by a panel’ there was a marked preference for a panel of multidisciplinary health professionals over a panel of pharmacists. Conclusion The survey outcomes will inform the development of an advanced pharmacy practice recognition model for Australian pharmacists, particularly in relation to the assessment methods. Survey outcomes also demonstrated that there is scope to further enhance the application of the APPF in the development and recognition of advanced practitioners, and to build greater awareness of the breadth of competencies encompassed by ‘advanced practice’.
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The need to develop An Advanced Pharmacy Practice Framework for Australia (the “APPF”) was identified during the 2010 review of the competency standards for Australian pharmacists. The Advanced Pharmacy Practice Framework Steering Committee, a collaborative profession-wide committee comprised of representatives of ten pharmacy organisations, examined and adapted existing advanced practice frameworks, all of which were found to have been based on the Competency Development and Evaluation Group (CoDEG) Advanced and Consultant Level Framework (the “CoDEG Framework”) from the United Kingdom. Its competency standards were also found to align well with the Domains of the National Competency Standards Framework for Pharmacists in Australia (the “National Framework”). Adaptation of the CoDEG Framework created an APPF that is complementary to the National Framework, sufficiently flexible to customise for recognising advanced practice in any area of professional practice and has been approved by the boards/councils of all participating organisations. The primary purpose of the APPF is to assist the development of the profession to meet the changing health care needs of the community. However, it is also a valuable tool for assuring members of the public of the competence of an advanced practice pharmacist and the quality and safety of the services they deliver.
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There is evidence across several species for genetic control of phenotypic variation of complex traits1, 2, 3, 4, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ~170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)5, 6, 7, is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ~0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation9, 10. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
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Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10−9 to P = 1.8 × 10−40) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10−3 to P = 1.2 × 10−13). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.