44 research outputs found
Using ODIN for a PharmGKB revalidation experiment
The need for efficient text-mining tools that support curation of the biomedical literature is ever increasing. In this article, we describe an experiment aimed at verifying whether a text-mining tool capable of extracting meaningful relationships among domain entities can be successfully integrated into the curation workflow of a major biological database. We evaluate in particular (i) the usability of the system's interface, as perceived by users, and (ii) the correlation of the ranking of interactions, as provided by the text-mining system, with the choices of the curators
The Stanford Microarray Database accommodates additional microarray platforms and data formats
The Stanford Microarray Database (SMD) (http://smd.stanford.edu) is a research tool for hundreds of Stanford researchers and their collaborators. In addition, SMD functions as a resource for the entire biological research community by providing unrestricted access to microarray data published by SMD users and by disseminating its source code. In addition to storing GenePix (Axon Instruments) and ScanAlyze output from spotted microarrays, SMD has recently added the ability to store, retrieve, display and analyze the complete raw data produced by several additional microarray platforms and image analysis software packages, so that we can also now accept data from Affymetrix GeneChips (MAS5/GCOS or dChip), Agilent Catalog or Custom arrays (using Agilent's Feature Extraction software) or data created by SpotReader (Niles Scientific). We have implemented software that allows us to accept MAGE-ML documents from array manufacturers and to submit MIAME-compliant data in MAGE-ML format directly to ArrayExpress and GEO, greatly increasing the ease with which data from SMD can be published adhering to accepted standards and also increasing the accessibility of published microarray data to the general public. We have introduced a new tool to facilitate data sharing among our users, so that datasets can be shared during, before or after the completion of data analysis. The latest version of the source code for the complete database package was released in November 2004 (http://smd.stanford.edu/download/), allowing researchers around the world to deploy their own installations of SMD
Mitochondrial Cox1 Sequence Data Reliably Uncover Patterns of Insect Diversity But Suffer from High Lineage-Idiosyncratic Error Rates
The demand for scientific biodiversity data is increasing, but taxonomic expertise is often limited or not available. DNA sequencing is a potential remedy to overcome this taxonomic impediment. Mitochondrial DNA is most commonly used, e.g., for species identification ("DNA barcoding"). Here, we present the first study in arthropods based on a near-complete species sampling of a family-level taxon from the entire Australian region. We aimed to assess how reliably mtDNA data can capture species diversity when many sister species pairs are included. Then, we contrasted phylogenetic subsampling with the hitherto more commonly applied geographical subsampling, where sister species are not necessarily captured.
We sequenced 800 bp cox1 for 1,439 individuals including 260 Australian species (78% species coverage). We used clustering with thresholds of 1 to 10% and general mixed Yule Coalescent (GMYC) analysis for the estimation of species richness. The performance metrics used were taxonomic accuracy and agreement between the morphological and molecular species richness estimation. Clustering (at the 3% level) and GMYC reliably estimated species diversity for single or multiple geographic regions, with an error for larger clades of lower than 10%, thus outperforming parataxonomy. However, the rates of error were higher for some individual genera, with values of up to 45% when very recent species formed nonmonophyletic clusters. Taxonomic accuracy was always lower, with error rates above 20% and a larger variation at the genus level (0 to 70%). Sørensen similarity indices calculated for morphospecies, 3% clusters and GMYC entities for different pairs of localities was consistent among methods and showed expected decrease over distance.
Cox1 sequence data are a powerful tool for large-scale species richness estimation, with a great potential for use in ecology and β-diversity studies and for setting conservation priorities. However, error rates can be high in individual lineages
The risk of child and adolescent overweight is related to types of food consumed
<p>Abstract</p> <p>Background/Aims</p> <p>To investigate the association between the risk of overweight and the consumption of food groups in children and adolescents.</p> <p>Methods</p> <p>We studied 1764 healthy children and adolescents (age 6-19y) attending 16 Seventh-Day Adventist schools and 13 public schools using a 106-item non-quantitative food frequency questionnaire from the late 1980 Child-Adolescent Blood Pressure Study. Logistic regression models were used to compute the risk of overweight according to consumption of grains, nuts, vegetables, fruits, meats/fish/eggs, dairy, and, low nutrient-dense foods (LNDF).</p> <p>Results</p> <p>The frequency of consumption of grains, nuts, vegetables and LNDF were inversely related to the risk of being overweight and dairy increased the risk. Specifically, the odds ratio (95% CI) for children in the highest quartile or tertile of consumption compared with the lowest quartile or tertile were as follows: grains 0.59(0.41-0.83); nuts 0.60(0.43-0.85); vegetables 0.67(0.48-0.94); LNDF 0.43(0.29-0.63); and, dairy 1.36(0.97, 1.92).</p> <p>Conclusion</p> <p>The regular intake of specific plant foods may prevent overweight among children and adolescents.</p
<em>CYP2D6 </em>genotype and adjuvant tamoxifen:meta-analysis of heterogeneous study populations
Bio-psychosocial determinants of time lost from work following non life threatening acute orthopaedic trauma
<p>Abstract</p> <p>Background</p> <p>To determine factors predicting the duration of time away from work following acute orthopaedic non life threatening trauma</p> <p>Methods</p> <p>Prospective cohort study conducted at four hospitals in Victoria, Australia. The cohort comprised 168 patients aged 18-64 years who were working prior to the injury and sustained a range of acute unintentional orthopaedic injuries resulting in hospitalization. Baseline data was obtained by survey and medical record review. Multivariate Cox proportional hazards regression analysis was used to examine the association between potential predictors and the duration of time away from work during the six month study. The study achieved 89% follow-up.</p> <p>Results</p> <p>Of the 168 participants recruited to the study, 68% returned to work during the six month study. Multivariate Cox proportional hazards regression analysis identified that blue collar work, negative pain attitudes with respect to work, high initial pain intensity, injury severity, older age, initial need for surgery, the presence of co-morbid health conditions at study entry and an orthopaedic injury to more than one region were associated with extended duration away from work following the injury. Participants in receipt of compensation who reported high social functioning at two weeks were 2.58 times more likely to have returned to work than similar participants reporting low social functioning. When only those who had returned to work were considered, the participant reported reason for return to work " to fill the day" was a significant predictor of earlier RTW [RR 2.41 (95% C.I 1.35-4.30)] whereas "financial security" and "because they felt able to" did not achieve significance.</p> <p>Conclusions</p> <p>Many injury-related and psycho social factors affect the duration of time away from work following orthopaedic injury. Some of these are potentially modifiable and may be amenable to intervention. Further consideration of the reasons provided by participants for returning to work may provide important opportunities for social marketing approaches designed to alleviate the financial and social burden associated with work disability.</p
End-Stage Renal Disease in African Americans With Lupus Nephritis Is Associated With APOL1
Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE) that exhibits familial aggregation and may progress to end-stage renal disease (ESRD). LN is more prevalent among African Americans than among European Americans. This study was undertaken to investigate the hypothesis that the apolipoprotein L1 gene (APOL1) nephropathy risk alleles G1/G2, common in African Americans and rare in European Americans, contribute to the ethnic disparity in risk
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
Thiopurine pathway
The thiopurine drugs are purine antimetabolites widely used in the treatment of acute lymphoblastic leukemia, autoimmune disorders (e.g. Crohn\u2019s disease and rheumatoid arthritis) and of organ transplant recipients. As inactive prodrugs, 6-mercaptopurine (6-MP), 6-thioguanine (6-TG) and azathioprine require intracellular activation, catalyzed by multiple enzymes, to exert cytotoxicity. The first step in azathioprine activation is the release of 6-MP, which involves glutathione transferases and nonenzy-matic conversion. Transport of 6-MP into the cell involves SLC28A2, SLC28A3, SLC29A1 and SLC29A2. After the uptake, 6-MP is converted into thioinosine mono-phosphate by hypoxanthine guanine phosphoribosyl transferase, with 5-phospho-D-ribose-1-pyrophosphate as the phosphoribosyl donor. In a similar way, 6-TG can be converted into thioguanosine monophosphate (TGMP). Thioinosine monophosphate can be converted into TGMP in two steps: first, thioxanthosine monophosphate is formed by inositol monophosphate dehydrogenase; second, TGMP is formed by guanosine monophosphate synthetase. Subsequently, TGMP can be converted into TG nucleotide diphosphates and triphosphates. Cyto-toxic effects of thiopurine drugs are achieved through incorporation of thio-deoxyguanosine triphosphate into DNA and of thioguanosine triphosphate into RNA, by inhibition of de novo purine synthesis by methylmercap-topurine nucleotides and by inhibition of Rac1 (this inhibition induces apoptosis in activated T-cells). The thio-deoxyguanosine triphosphate incorporation inhibits the function of several enzymes involved in DNA replication and repair, and induces DNA damage such as single strand-breaks, DNA\u2013protein cross-links and chromatid exchanges. The pathway that leads to synthesis of active metabolites is in competition with inactivation pathways catalyzed by xanthine oxidase or the polymorphic thiopurine methyltransferase