Compound particle swarm optimization in dynamic environments

Copyright @ Springer-Verlag Berlin Heidelberg 2008.Adaptation to dynamic optimization problems is currently receiving a growing interest as one of the most important applications of evolutionary algorithms. In this paper, a compound particle swarm optimization (CPSO) is proposed as a new variant of particle swarm optimization to enhance its performance in dynamic environments. Within CPSO, compound particles are constructed as a novel type of particles in the search space and their motions are integrated into the swarm. A special reflection scheme is introduced in order to explore the search space more comprehensively. Furthermore, some information preserving and anti-convergence strategies are also developed to improve the performance of CPSO in a new environment. An experimental study shows the efficiency of CPSO in dynamic environments.This work was supported by the Key Program of the National Natural Science Foundation (NNSF) of China under Grant No. 70431003 and Grant No. 70671020, the Science Fund for Creative Research Group of NNSF of China under Grant No. 60521003, the National Science and Technology Support Plan of China under Grant No. 2006BAH02A09 and the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant No. EP/E060722/1

Beware Cold Agglutinins in Organ Donors! Ex Vivo Lung Perfusion From an Uncontrolled Donation After Circulatory-Determination-of-Death Donor With a Cold Agglutinin: A Case Report

Background We began to recover lungs from uncontrolled donation after circulatory determination of death to assess for transplant suitability by means of ex vivo lung perfusion (EVLP) and computerized tomographic (CT) scan. Our first case had a cold agglutinin with an interesting outcome. Case report A 60-year-old man collapsed at home and was pronounced dead by Emergency Medical Services personnel. Next-of-kin consented to lung retrieval, and the decedent was ventilated and transported. Lungs were flushed with cold Perfadex, removed, and stored cold. The lungs did not flush well. Medical history revealed a recent hemolytic anemia and a known cold agglutinin. Warm nonventilated ischemia time was 51 minutes. O2-ventilated ischemia time was 141 minutes. Total cold ischemia time was 6.5 hours. At cannulation for EVLP, established clots were retrieved from both pulmonary arteries. At initiation of EVLP with Steen solution, tiny red aggregates were observed initially. With warming, the aggregates disappeared and the perfusate became red. After 1 hour, EVLP was stopped because of florid pulmonary edema. The lungs were cooled to 20°C; tiny red aggregates formed again in the perfusate. Ex vivo CT scan showed areas of pulmonary edema and a pyramidal right middle lobe opacity. Dissection showed multiple pulmonary emboli—the likely cause of death. However, histology showed agglutinated red blood cells in the microvasculature in pre- and post-EVLP biopsies, which may have contributed to inadequate parenchymal preservation. Conclusions Organ donors with cold agglutinins may not be suitable owing to the impact of hypothermic preservation

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

Health Care Utilization During the COVID-19 Pandemic Among Individuals Born Preterm

Importance: Limited data exist on pediatric health care utilization during the COVID-19 pandemic among children and young adults born preterm. Objective: To investigate differences in health care use related to COVID-19 concerns during the pandemic among children and young adults born preterm vs those born at term. Design, Setting, and Participants: In this cohort study, questionnaires regarding COVID-19 and health care utilization were completed by 1691 mother-offspring pairs from 42 pediatric cohorts in the National Institutes of Health Environmental Influences on Child Health Outcomes Program. Children and young adults (ages 1-18 years) in these analyses were born between 2003 and 2021. Data were recorded by the August 31, 2021, data-lock date and were analyzed between October 2021 and October 2022. Exposures: Premature birth (<37 weeks' gestation). Main Outcomes and Measures: The main outcome was health care utilization related to COVID-19 concerns (hospitalization, in-person clinic or emergency department visit, phone or telehealth evaluations). Individuals born preterm vs term (≥37 weeks' gestation) and differences among preterm subgroups of individuals (<28 weeks', 28-36 weeks' vs ≥37 weeks' gestation) were assessed. Generalized estimating equations assessed population odds for health care used and related symptoms, controlling for maternal age, education, and psychiatric disorder; offspring history of bronchopulmonary dysplasia (BPD) or asthma; and timing and age at COVID-19 questionnaire completion. Results: Data from 1691 children and young adults were analyzed; among 270 individuals born preterm, the mean (SD) age at survey completion was 8.8 (4.4) years, 151 (55.9%) were male, and 193 (71.5%) had a history of BPD or asthma diagnosis. Among 1421 comparison individuals with term birth, the mean (SD) age at survey completion was 8.4 (2.4) years, 749 (52.7%) were male, and 233 (16.4%) had a history of BPD or asthma. Preterm subgroups included 159 individuals (58.5%) born at less than 28 weeks' gestation. In adjusted analyses, individuals born preterm had a significantly higher odds of health care utilization related to COVID-19 concerns (adjusted odds ratio [aOR], 1.70; 95% CI, 1.21-2.38) compared with term-born individuals; similar differences were also seen for the subgroup of individuals born at less than 28 weeks' gestation (aOR, 2.15; 95% CI, 1.40-3.29). Maternal history of a psychiatric disorder was a significant covariate associated with health care utilization for all individuals (aOR, 1.44; 95% CI, 1.17-1.78). Conclusions and Relevance: These findings suggest that during the COVID-19 pandemic, children and young adults born preterm were more likely to have used health care related to COVID-19 concerns compared with their term-born peers, independent of a history of BPD or asthma. Further exploration of factors associated with COVID-19-related health care use may facilitate refinement of care models

Sexuality, disability, and reproductive issues through the lifespan

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45558/1/11195_2005_Article_BF01102578.pd

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees

A major challenge in evaluating the contribution of rare variants to complex disease is identifying enough copies of the rare alleles to permit informative statistical analysis. To investigate the contribution of rare variants to the risk of type 2 diabetes (T2D) and related traits, we performed deep whole-genome analysis of 1,034 members of 20 large Mexican-American families with high prevalence of T2D. If rare variants of large effect accounted for much of the diabetes risk in these families, our experiment was powered to detect association. Using gene expression data on 21,677 transcripts for 643 pedigree members, we identified evidence for large-effect rare-variant cis-expression quantitative trait loci that could not be detected in population studies, validating our approach. However, we did not identify any rare variants of large effect associated with T2D, or the related traits of fasting glucose and insulin, suggesting that large-effect rare variants account for only a modest fraction of the genetic risk of these traits in this sample of families. Reliable identification of large-effect rare variants will require larger samples of extended pedigrees or different study designs that further enrich for such variants