RADIC II : a fault tolerant architecture with flexible dynamic redundancy

The demand for computational power has been leading the improvement of the High Performance Computing (HPC) area, generally represented by the use of distributed systems like clusters of computers running parallel applications. In this area, fault tolerance plays an important role in order to provide high availability isolating the application from the faults effects. Performance and availability form an undissociable binomial for some kind of applications. Therefore, the fault tolerant solutions must take into consideration these two constraints when it has been designed. In this dissertation, we present a few side-effects that some fault tolerant solutions may presents when recovering a failed process. These effects may causes degradation of the system, affecting mainly the overall performance and availability. We introduce RADIC-II, a fault tolerant architecture for message passing based on RADIC (Redundant Array of Distributed Independent Fault Tolerance Controllers) architecture. RADIC-II keeps as maximum as possible the RADIC features of transparency, decentralization, flexibility and scalability, incorporating a flexible dynamic redundancy feature, allowing to mitigate or to avoid some recovery side-effects.La demanda de computadores más veloces ha provocado el incremento del área de computación de altas prestaciones, generalmente representado por el uso de sistemas distribuidos como los clusters de computadores ejecutando aplicaciones paralelas. En esta área, la tolerancia a fallos juega un papel muy importante a la hora de proveer alta disponibilidad, aislando los efectos causados por los fallos. Prestaciones y disponibilidad componen un binomio indisociable para algunos tipos de aplicaciones. Por eso, las soluciones de tolerancia a fallos deben tener en consideración estas dos restricciones desde el momento de su diseño. En esta disertación, presentamos algunos efectos colaterales que se puede presentar en ciertas soluciones tolerantes a fallos cuando recuperan un proceso fallado. Estos efectos pueden causar una degradación del sistema, afectando las prestaciones y disponibilidad finales. Presentamos RADIC-II, una arquitectura tolerante a fallos para paso de mensajes basada en la arquitectura RADIC (Redundant Array of Distributed Independent Fault Tolerance Controllers). RADIC-II mantiene al máximo posible las características de transparencia, descentralización, flexibilidad y escalabilidad existentes en RADIC, e incorpora una flexible funcionalidad de redundancia dinámica, que permite mitigar o evitar algunos efectos colaterales en la recuperación

Prevalence of COVID-19-related risk factors and risk of severe influenza outcomes in cancer survivors: A matched cohort study using linked English electronic health records data.

BACKGROUND: People with active cancer are recognised as at risk of COVID-19 complications, but it is unclear whether the much larger population of cancer survivors is at elevated risk. We aimed to address this by comparing cancer survivors and cancer-free controls for (i) prevalence of comorbidities considered risk factors for COVID-19; and (ii) risk of severe influenza, as a marker of susceptibility to severe outcomes from epidemic respiratory viruses. METHODS: We included survivors (≥1 year) of the 20 most common cancers, and age, sex and general practice-matched cancer-free controls, derived from English primary care data linked to cancer registrations, hospital admissions and death registrations. Comorbidity prevalences were calculated 1 and 5 years from cancer diagnosis. Risk of hospitalisation or death due to influenza was compared using Cox models adjusted for baseline demographics and comorbidities. FINDINGS: 108,215 cancer survivors and 523,541 cancer-free controls were included. Cancer survivors had more diabetes, asthma, other respiratory, cardiac, neurological, renal, and liver diseases, and less obesity, compared with controls, but there was variation by cancer site. There were 205 influenza hospitalisations/deaths, with cancer survivors at higher risk than controls (adjusted HR 2.78, 95% CI 2.04-3.80). Haematological cancer survivors had large elevated risks persisting for >10 years (HR overall 15.17, 7.84-29.35; HR >10 years from cancer diagnosis 10.06, 2.47-40.93). Survivors of other cancers had evidence of raised risk up to 5 years from cancer diagnosis only (HR >5 years 2.22, 1.31-3.74). INTERPRETATION: Risks of severe COVID-19 outcomes are likely to be elevated in cancer survivors. This should be taken into account in policies targeted at clinical risk groups, and vaccination for both influenza, and, when available, COVID-19, should be encouraged in cancer survivors

Fertility treatment, twin births, and unplanned pregnancies in women with eating disorders: Findings from a population-based birth cohort

Objective: To investigate fertility treatment, twin births, and unplanned pregnancies in pregnant women with eating disorders in a population-based sample. Design: A longitudinal population-based birth cohort (Generation R). Setting: Rotterdam, the Netherlands. Sample: Women from the Generation R study who reported a history of (recent or past) anorexia nervosa (n = 160), bulimia nervosa (n = 265), or both (n = 130), and a history of psychiatric disorders other than eating disorders (n = 1396) were compared with women without psychiatric disorders (n = 4367). Methods: Women were compared on the studied outcomes using logistic regression. We performed crude and adjusted analyses (adjusting for relevant confounding factors). Main outcome measures: Fertility treatment, twin births, unplanned pregnancies, and women's feelings towards unplanned pregnancies. Results: Relative to women without psychiatric disorders, women with bulimia nervosa had increased odds (odds ratio, OR, 2.3; 95% confidence interval, 95% CI, 1.1-5.2) of having undergone fertility treatment. Women with all eating disorders had increased odds of twin births (anorexia nervosa, OR 2.7, 95% CI 1.0-7.7; bulimia nervosa, OR 2.7, 95% CI 1.1-6.6; anorexia and bulimia nervosa, OR 3.795% CI 1.3-10.7). Anorexia nervosa was associated with increased odds of unplanned pregnancies (OR 1.8, 95% CI 1.2-2.6) and mixed feelings about these pregnancies (adjusted OR 5.0, 95% CI 1.7-14.4). Pre-pregnancy body mass index did not explain the observed associations. Conclusions: Eating disorders are associated with increased odds of receiving fertility treatment and twin births. Women with anorexia nervosa were more likely to have an unplanned pregnancy and have mixed feelings about the unplanned pregnancy. Fertility treatment specialists should be aware that both active and past eating disorders (both anorexia nervosa and bulimia nervosa) might underlie fertility problems

Sex steroids, growth factors and mammographic density: a cross-sectional study of UK postmenopausal Caucasian and Afro-Caribbean women

INTRODUCTION: Sex steroids, insulin-like growth factors (IGFs) and prolactin are breast cancer risk factors but whether their effects are mediated through mammographic density, one of the strongest risk factors for breast cancer, is unknown. If such a hormonal basis of mammographic density exists, hormones may underlie ethnic differences in both mammographic density and breast cancer incidence rates. METHODS: In a cross-sectional study of 270 postmenopausal Caucasian and Afro-Caribbean women attending a population-based breast screening service in London, UK, we investigated whether plasma biomarkers (oestradiol, oestrone, sex hormone binding globulin (SHBG), testosterone, prolactin, leptin, IGF-I, IGF-II and IGF binding protein 3 (IGFBP3)) were related to and explained ethnic differences in mammographic percent density, dense area and nondense area, measured in Cumulus using the threshold method. RESULTS: Mean levels of oestrogens, leptin and IGF-I:IGFBP3 were higher whereas SHBG and IGF-II:IGFBP3 were lower in Afro-Caribbean women compared with Caucasian women after adjustment for higher mean body mass index (BMI) in the former group (by 3.2 kg/m(2) (95% confidence interval (CI): 1.8, 4.5)). Age-adjusted percent density was lower in Afro-Caribbean compared with Caucasian women by 5.4% (absolute difference), but was attenuated to 2.5% (95% CI: -0.2, 5.1) upon BMI adjustment. Despite ethnic differences in biomarkers and in percent density, strong ethnic-age-adjusted inverse associations of oestradiol, leptin and testosterone with percent density were completely attenuated upon adjustment for BMI. There were no associations of IGF-I, IGF-II or IGFBP3 with percent density or dense area. We found weak evidence that a twofold increase in prolactin and oestrone levels were associated, respectively, with an increase (by 1.7% (95% CI: -0.3, 3.7)) and a decrease (by 2.0% (95% CI: 0, 4.1)) in density after adjustment for BMI. CONCLUSIONS: These findings suggest that sex hormone and IGF levels are not associated with BMI-adjusted percent mammographic density in cross-sectional analyses of postmenopausal women and thus do not explain ethnic differences in density. Mammographic density may still, however, be influenced by much higher premenopausal hormone levels

Human Paraoxonase Gene Polymorphisms and Coronary Artery Disease Risk

Introdução: As doenças complexas como a doença das artérias coronárias (DAC), a hipertensão e a diabetes, são usualmente causadas pela susceptibilidade individual a múltiplos genes, factores ambientais e pela interacção entre eles. As enzimas da paraoxonase humana (PON), particularmente a PON1, têm sido implicadas na patogenia da aterosclerose e da DAC. Dois polimorfismos comuns na região codificante do gene, com substituição Glutamina (Q) /Arginina (R) na posição 192 e Leucina /Metionina na posição 55 influenciam a actividade da PON1. Vários estudos têm investigado a associação entre os polimorfismos da PON1 e a DAC, com resultados contraditórios. Objectivo: 1- Avaliar a associação dos polimorfismos da PON1 com o risco de DAC. 2-Estudar a interacção destes polimorfismos com outros situados em genes candidatos diferentes, na susceptibilidade para o aparecimento da DAC. Material e Métodos: Estudámos em 298 doentes coronários e 298 controlos saudáveis, através de um estudo caso/controlo, o risco de DAC associado aos polimorfismos da PON1, 192Q/R e 55L/M. Numa segunda fase avaliámos o risco das interacções polimórficas PON1 192 RR + MTHFR 1298 AA; PON1 192 R/R + ECA DD; PON1 192 R/R + ECA 8 GG. Finalmente construímos um modelo de regressão logística (no qual entraram todas as variáveis genéticas, ambientais e bioquímicas, que tinham mostrado significância estatística na análise univariada), para determinar quais as que se relacionavam de forma significativa e independente com DAC. Resultados: Verificámos que o genótipo PON155 MM tinha uma distribuição superior na população doente mas não atingia significância estatística como factor de risco para DAC. O PON1 199 RR apresentou um risco relativo 80% superior relativamente à população que o não possuía (p=0,04). A interacção da PON1 192 RR e da MTHFR 1298 AA, polimorfismos sedeados em genes diferentes, apresentou um risco relativo de DAC de 2,76 (OR=2,76;IC=1,20- 6,47; P=0,009), bastante superior ao risco de cada polimorfismo isolado, assim como a associação da PON1 RR + ECA DD (com polimorfismos também sedeados em genes diferentes), que apresentou um risco 337% superior relativamente aos que não possuíam esta associação (OR=4,37;IC=1,47- 13,87; P=0,002). Da mesma forma a associação entre a PON1 RR e ECA 8 GG, revelou um risco ainda mais elevado (OR=6;23; IC=1,67- 27,37; P<0,001). Após modelo de Regressão Logística as variáveis que ficaram na equação representando factores de risco significativos e independentes para DAC, foram os hábitos tabágicos, doença familiar, diabetes, fibrinogénio, Lp (a) e a associação PON1 192 RR + ECA 8 GG. Esta última associação apresentou, na regressão logística, um OR=14,113; p=0,018 Conclusões: O genótipo PON1 192 RR apresentou, se avaliado isoladamente, um risco relativo de DAC 80% superior relativamente à população que não possuía este genótipo. A associação deste polimorfismo com outros polimorfismos sedeados em genes diferentes, codificando para diferentes enzimas e pertencendo a sistemas fisiopatológicos distintos (MTHFR1298 AA, ECA DD e ECA 8 GG), aumentou sempre o risco de eclosão da DAC. Após correcção para os outros factores de risco clássicos e bioquímicos, a associação PON1 192 RR + ECA 8 GG, continuou a ser um factor de risco significativo e independente para CAD.Background: Complex diseases such as coronary artery disease (CAD), hypertension and diabetes are usually caused by individual susceptibility to multiple genes, environmental factors, and the interaction between them. The paraoxonase 1 (PON1) enzyme has been implicated in the pathogenesis of atherosclerosis and CAD. Two common polymorphisms in the coding region of the PON1 gene, which lead to a glutamine (Q)/arginine (R) substitution at position 192 and a leucine (L)/methionine (M) substitution at position 55, influence PON1 activity. Studies have investigated the association between these polymorphisms and CAD, but with conflicting results. Aims: 1) To evaluate the association between PON1 polymorphisms and CAD risk; and 2) to study the interaction between PON1 polymorphisms and others in different candidate genes. Methods: We evaluated the risk of CAD associated with PON1 Q192R and L55M polymorphisms in 298 CAD patients and 298 healthy individuals. We then evaluated the risk associated with the interaction of the PON1 polymorphisms with ACE DD, ACE 8 GG and MTHFR 1298AA. Finally, using a logistic regression model, we evaluated which variables (genetic, biochemical and environmental) were linked significantly and independently with CAD. Results: We found that the PON1 55MM genotype was more common in the CAD population, but this did not reach statistical significance as a risk factor for CAD, while PON1 192RR presented an 80% higher relative risk compared to the population without this polymorphism. The interaction between PON1 192RR and MTHFR 1298AA, sited in different genes, increased the risk for CAD, compared with the polymorphisms in isolation (OR=2.76; 95% CI=1.20-6.47; p=0.009), as did the association of PON1 192RR with ACE DD, which presented a 337% higher risk compared to the population without this polymorphic association (OR=4.37; 95% CI=1.47-13.87; p=0.002). Similarly, the association between PON1 192RR and ACE 8 GG was linked to an even higher risk (OR=6.23; 95% CI=1.67-27.37; p<0.001). After logistic regression, smoking, family history, fibrinogen, diabetes, Lp(a) and the association of PON1 192RR + ACE 8 GG remained in the regression model and proved to be significant and independent risk factors for CAD. In the regression model the latter association had OR=14.113; p=0.018. Conclusion: When analyzed separately, the PON1 192RR genotype presented a relative risk for CAD 80% higher than in the population without this genotype. Its association with other genetic polymorphisms sited in different genes, coding for different enzymes and belonging to different physiological systems, always increased the risk for CAD. After correction for other conventional and biochemical risk factors, the PON1 192RR + ACE 8 GG association remained a significant and independent risk factor for CAD.info:eu-repo/semantics/publishedVersio

The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer.

Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM -/- patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors

Genomic epidemiology unveils the dynamics and spatial corridor behind the Yellow Fever virus outbreak in Southern Brazil

Despite the considerable morbidity and mortality of yellow fever virus (YFV) infections in Brazil, our understanding of disease outbreaks is hampered by limited viral genomic data. Here, through a combination of phylogenetic and epidemiological models, we reconstructed the recent transmission history of YFV within different epidemic seasons in Brazil. A suitability index based on the highly domesticated Aedes aegypti was able to capture the seasonality of reported human infections. Spatial modeling revealed spatial hotspots with both past reporting and low vaccination coverage, which coincided with many of the largest urban centers in the Southeast. Phylodynamic analysis unraveled the circulation of three distinct lineages and provided proof of the directionality of a known spatial corridor that connects the endemic North with the extra-Amazonian basin. This study illustrates that genomics linked with eco-epidemiology can provide new insights into the landscape of YFV transmission, augmenting traditional approaches to infectious disease surveillance and control

Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures.

Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk.ABCFS: The Australian Breast Cancer Family Registry (ABCFR; 1992-1995) was supported by the Australian NHMRC, the New South Wales Cancer Council, and the Victorian Health Promotion Foundation (Australia), and by grant UM1CA164920 from the USA National Cancer Institute. The Genetic Epidemiology Laboratory at the University of Melbourne has also received generous support from Mr B. Hovey and Dr and Mrs R.W. Brown to whom we are most grateful. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Breast Cancer Susceptibility Variants and Mammographic Density 5 Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. BBCC: This study was funded in part by the ELAN-Program of the University Hospital Erlangen; Katharina Heusinger was funded by the ELAN program of the University Hospital Erlangen. BBCC was supported in part by the ELAN program of the Medical Faculty, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg. EPIC-Norfolk: This study was funded by research programme grant funding from Cancer Research UK and the Medical Research Council with additional support from the Stroke Association, British Heart Foundation, Department of Health, Research into Ageing and Academy of Medical Sciences. MCBCS: This study was supported by Public Health Service Grants P50 CA 116201, R01 CA 128931, R01 CA 128931-S01, R01 CA 122340, CCSG P30 CA15083, from the National Cancer Institute, National Institutes of Health, and Department of Health and Human Services. MCCS: Melissa C. Southey is a National Health and Medical Research Council Senior Research Fellow and a Victorian Breast Cancer Research Consortium Group Leader. The study was supported by the Cancer Council of Victoria and by the Victorian Breast Cancer Research Consortium. MEC: National Cancer Institute: R37CA054281, R01CA063464, R01CA085265, R25CA090956, R01CA132839. MMHS: This work was supported by grants from the National Cancer Institute, National Institutes of Health, and Department of Health and Human Services. (R01 CA128931, R01 CA 128931-S01, R01 CA97396, P50 CA116201, and Cancer Center Support Grant P30 CA15083). Breast Cancer Susceptibility Variants and Mammographic Density 6 NBCS: This study has been supported with grants from Norwegian Research Council (#183621/S10 and #175240/S10), The Norwegian Cancer Society (PK80108002, PK60287003), and The Radium Hospital Foundation as well as S-02036 from South Eastern Norway Regional Health Authority. NHS: This study was supported by Public Health Service Grants CA131332, CA087969, CA089393, CA049449, CA98233, CA128931, CA 116201, CA 122340 from the National Cancer Institute, National Institutes of Health, Department of Health and Human Services. OOA study was supported by CA122822 and X01 HG005954 from the NIH; Breast Cancer Research Fund; Elizabeth C. Crosby Research Award, Gladys E. Davis Endowed Fund, and the Office of the Vice President for Research at the University of Michigan. Genotyping services for the OOA study were provided by the Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096. OFBCR: This work was supported by grant UM1 CA164920 from the USA National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. SASBAC: The SASBAC study was supported by Märit and Hans Rausing’s Initiative against Breast Cancer, National Institutes of Health, Susan Komen Foundation and Agency for Science, Technology and Research of Singapore (A*STAR). Breast Cancer Susceptibility Variants and Mammographic Density 7 SIBS: SIBS was supported by program grant C1287/A10118 and project grants from Cancer Research UK (grant numbers C1287/8459). COGS grant: Collaborative Oncological Gene-environment Study (COGS) that enabled the genotyping for this study. Funding for the BCAC component is provided by grants from the EU FP7 programme (COGS) and from Cancer Research UK. Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692), the National Institutes of Health (CA128978) and Post- Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 - the GAMEON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund.This is the author accepted manuscript. The final version is available via American Association for Cancer Research at http://cancerres.aacrjournals.org/content/early/2015/04/10/0008-5472.CAN-14-2012.abstract

Identification of new genetic susceptibility loci for breast cancer through consideration of gene-environment interactions

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10(−07)), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m(2) (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m(2) or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10(−05)). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci