Comparison of bio-inspired algorithms applied to the hospital mortality risk stratification

The construction of patient classification (or risk adjustment) systems allows comparison of the effectiveness and quality of hospitals and hospital services, providing useful information for management decision making and management of hospitals. Risk adjustment systems to stratify patients’ severity in a clinical outcome are generally constructed from care variables and using statistical techniques based on logistic regression (RL). The objective of this investigation is to compare the hospital mortality prediction capacity of an artificial neural network (RNA) with other methods already known

Genome-wide SNP identification by high-throughput sequencing and selective mapping allows sequence assembly positioning using a framework genetic linkage map

<p>Abstract</p> <p>Background</p> <p>Determining the position and order of contigs and scaffolds from a genome assembly within an organism's genome remains a technical challenge in a majority of sequencing projects. In order to exploit contemporary technologies for DNA sequencing, we developed a strategy for whole genome single nucleotide polymorphism sequencing allowing the positioning of sequence contigs onto a linkage map using the bin mapping method.</p> <p>Results</p> <p>The strategy was tested on a draft genome of the fungal pathogen <it>Venturia inaequalis</it>, the causal agent of apple scab, and further validated using sequence contigs derived from the diploid plant genome <it>Fragaria vesca</it>. Using our novel method we were able to anchor 70% and 92% of sequences assemblies for <it>V. inaequalis </it>and <it>F. vesca</it>, respectively, to genetic linkage maps.</p> <p>Conclusions</p> <p>We demonstrated the utility of this approach by accurately determining the bin map positions of the majority of the large sequence contigs from each genome sequence and validated our method by mapping single sequence repeat markers derived from sequence contigs on a full mapping population.</p

Comparative analysis of rosaceous genomes and the reconstruction of a putative ancestral genome for the family

Abstract Background Comparative genome mapping studies in Rosaceae have been conducted until now by aligning genetic maps within the same genus, or closely related genera and using a limited number of common markers. The growing body of genomics resources and sequence data for both Prunus and Fragaria permits detailed comparisons between these genera and the recently released Malus × domestica genome sequence. Results We generated a comparative analysis using 806 molecular markers that are anchored genetically to the Prunus and/or Fragaria reference maps, and physically to the Malus genome sequence. Markers in common for Malus and Prunus, and Malus and Fragaria, respectively were 784 and 148. The correspondence between marker positions was high and conserved syntenic blocks were identified among the three genera in the Rosaceae. We reconstructed a proposed ancestral genome for the Rosaceae. Conclusions A genome containing nine chromosomes is the most likely candidate for the ancestral Rosaceae progenitor. The number of chromosomal translocations observed between the three genera investigated was low. However, the number of inversions identified among Malus and Prunus was much higher than any reported genome comparisons in plants, suggesting that small inversions have played an important role in the evolution of these two genera or of the Rosaceae.Apple genome research at FEM is supported by the research office of the Provincia autonoma di Trento. DJS and ELG acknowledge a grant from the East Malling Trust. Fragaria genomics at EMR is funded by the BBSRC. JMB is supported by a grant by Plant & Food Research's Excellence Programme. Apple genomics at Plant & Food Research is partially supported by the New Zealand Foundation for Research Science and Technology project C06X0812 "Exploiting Opportunities from Horticultural Genomics". Research conducted at IRTA was partly funded by the CONSOLIDER-INGENIO 2010 Program (CSD2007-00036) and project INIA-RTA2007-00063-00-00, both from the Spanish Ministry of Science and Innovation. RosCOS development at OSU/MSU was funded by the National Research Initiative Competitive Grant 2005-35300-15454 of USDA's National Institute of Food and Agriculture.Peer Reviewe

Additive QTLs on three chromosomes control flowering time in woodland strawberry (Fragaria vesca L.)

Flowering time is an important trait that affects survival, reproduction and yield in both wild and cultivated plants. Therefore, many studies have focused on the identification of flowering time quantitative trait locus (QTLs) in different crops, and molecular control of this trait has been extensively investigated in model species. Here we report the mapping of QTLs for flowering time and vegetative traits in a large woodland strawberry mapping population that was phenotyped both under field conditions and in a greenhouse after flower induction in the field. The greenhouse experiment revealed additive QTLs in three linkage groups (LG), two on both LG4 and LG7, and one on LG6 that explain about half of the flowering time variance in the population. Three of the QTLs were newly identified in this study, and one co-localized with the previously characterized FvTFL1 gene. An additional strong QTL corresponding to previously mapped PFRU was detected in both field and greenhouse experiments indicating that gene(s) in this locus can control the timing of flowering in different environments in addition to the duration of flowering and axillary bud differentiation to runners and branch crowns. Several putative flowering time genes were identified in these QTL regions that await functional validation. Our results indicate that a few major QTLs may control flowering time and axillary bud differentiation in strawberries. We suggest that the identification of causal genes in the diploid strawberry may enable fine tuning of flowering time and vegetative growth in the closely related octoploid cultivated strawberry.Peer reviewe

Large Scale Structure of the Universe

Galaxies are not uniformly distributed in space. On large scales the Universe displays coherent structure, with galaxies residing in groups and clusters on scales of ~1-3 Mpc/h, which lie at the intersections of long filaments of galaxies that are >10 Mpc/h in length. Vast regions of relatively empty space, known as voids, contain very few galaxies and span the volume in between these structures. This observed large scale structure depends both on cosmological parameters and on the formation and evolution of galaxies. Using the two-point correlation function, one can trace the dependence of large scale structure on galaxy properties such as luminosity, color, stellar mass, and track its evolution with redshift. Comparison of the observed galaxy clustering signatures with dark matter simulations allows one to model and understand the clustering of galaxies and their formation and evolution within their parent dark matter halos. Clustering measurements can determine the parent dark matter halo mass of a given galaxy population, connect observed galaxy populations at different epochs, and constrain cosmological parameters and galaxy evolution models. This chapter describes the methods used to measure the two-point correlation function in both redshift and real space, presents the current results of how the clustering amplitude depends on various galaxy properties, and discusses quantitative measurements of the structures of voids and filaments. The interpretation of these results with current theoretical models is also presented.Comment: Invited contribution to be published in Vol. 8 of book "Planets, Stars, and Stellar Systems", Springer, series editor T. D. Oswalt, volume editor W. C. Keel, v2 includes additional references, updated to match published versio

Hip fracture risk assessment: Artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study

Copyright @ 2013 Tseng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background - Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared. Methods - The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests. Results - In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively). Conclusions - The risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.National Health Research Institutes in Taiwa

A randomised, open label, active comparator trial assessing the effects of 26 weeks of liraglutide or sitagliptin on cardiovascular function in young obese adults with type 2 diabetes

Aim To compare the effects of a glucagon‐like peptide‐1 receptor agonist and a dipeptidyl peptidase‐4 inhibitor on magnetic resonance imaging‐derived measures of cardiovascular function. Materials and methods In a prospective, randomized, open‐label, blinded endpoint trial liraglutide (1.8 mg) and sitagliptin (100 mg) were compared in asymptomatic, non‐insulin treated young (aged 18‐50 years) adults with obesity and type 2 diabetes. The primary outcome was difference in circumferential peak early diastolic strain rate change (PEDSR), a biomarker of cardiac diastolic dysfunction 26 weeks after randomization. Secondary outcomes included other indices of cardiac structure and function, HbA1c and body weight. Results Seventy‐six participants were randomized (54% female, mean ± SD age 44 ± 6 years, diabetes duration 4.4 years, body mass index 35.3 ± 6.1 kg m−2), of whom 65% had ≥1 cardiovascular risk factor. Sixty‐one participants had primary outcome data available. There were no statistically significant between‐group differences (intention‐to‐treat; mean [95% confidence interval]) in PEDSR change (−0.01 [−0.07, +0.06] s−1), left ventricular ejection fraction (−1.98 [−4.90, +0.94]%), left ventricular mass (+1.14 [−5.23, +7.50] g) or aortic distensibility (−0.35 [−0.98, +0.28] mmHg−1 × 10−3) after 26 weeks. Reductions in HbA1c (−4.57 [−9.10, −0.37] mmol mol−1) and body weight (−3.88 [−5.74, −2.01] kg) were greater with liraglutide. Conclusion There were no differences in cardiovascular structure or function after short‐term use of liraglutide and sitagliptin in younger adults with obesity and type 2 diabetes. Longer studies in patients with more severe cardiac dysfunction may be necessary before definitive conclusions can be made about putative pleiotropic properties of incretin‐based therapies

Survival endpoints in colorectal cancer and the effect of second primary other cancer on disease free survival

<p>Abstract</p> <p>Background</p> <p>In cancer research the selection and definitions of survival endpoints are important and yet they are not used consistently. The aim of this study was to compare different survival endpoints in patients with primary colorectal cancer (CRC) and to understand the effect of second primary other cancer on disease-free survival (DFS) calculations.</p> <p>Methods</p> <p>A population-based cohort of 415 patients with CRC, 332 of whom were treated with curative intention between the years 2000-2003, was analysed. Events such as locoregional recurrence, distant metastases, second primary cancers, death, cause of death and loss to follow-up were recorded. Different survival endpoints, including DFS, overall survival, cancer-specific survival, relapse-free survival, time to treatment failure and time to recurrence were compared and DFS was calculated with and without inclusion of second primary other cancers.</p> <p>Results</p> <p>The events that occurred most often in patients treated with curative intention were non-cancer-related death (n = 74), distant metastases (n = 66) and death from CRC (n = 59). DFS was the survival endpoint with most events (n = 170) followed by overall survival (n = 144) and relapse-free survival (n = 139). Fewer events were seen for time to treatment failure (n = 80), time to recurrence (n = 68) and cancer-specific survival (n = 59). Second primary other cancer occurred in 26 patients and its inclusion as an event in DFS calculations had a detrimental effect on the survival. The DFS for patients with stage I-III disease was 62% after 5 years if second primary other cancer was not included as an event, compared with 58% if it was. However, the difference was larger for stage II (68 vs 60%) than for stage III (49 vs 47%).</p> <p>Conclusions</p> <p>The inclusion of second primary other cancer as an endpoint in DFS analyses significantly alters the DFS for patients with CRC. Researchers and journals must clearly define survival endpoints in all trial protocols and published manuscripts.</p