DOAM for Evolutionary Portfolio Optimization: a computational study.

In this work, the ability of the Dynamic Objectives Aggregation Methods to solve the portfolio rebalancing problem is investigated conducting a computational study on a set of instances based on real data. The portfolio model considers a set of realistic constraints and entails the simultaneously optimization of the risk on portfolio, the expected return and the transaction cost.

Dynamic Objectives Aggregation in Multi-objective Evolutionary Optimization

Several approaches for solving multi-objective optimization problems entail a form of scalarization of the objectives. This paper proposes a study of different dynamic objectives aggregation methods in the context of evolutionary algorithms. These methods are mainly based on both weighted sum aggregations and curvature variations. A comparison analysis is presented on the basis of a campaign of computational experiments on a set of benchmark problems from the literature.Multi-objective optimization, Evolutionary algorithms, Aggregate objective functions

Clinical Trials in Paediatrics — Regulatory and Methodological Aspects

The photoautotrophic cyanobacterium Synechocystis PCC6803 has received much attention as a model photosynthetic cell factory for the production of a range of important biotech products. The biomass remaining from this activity may then have further utility in processes such as metal bioremediation. In addition Synechocystis being an inhabitant of many natural aquatic environments is seen as an environmentally friendly alternative to using chemical precipitation methodologies for metal remediation. Synechocystis produces a range of extracellular polysaccharide substances (EPS) that can undergo modification as a function of culture age and growth nutrients which have been implicated in metal biosorption. Many studies have demonstrated that high levels of charged groups present in EPS are important in forming polymeric matrices with metallic ions allowing their biosorption. Genetic studies has revealed genes involved in such metal binding indicating that EPS can be modified for potential enhancement of binding or modification of the types of metals bound. The utility of metal binding to live and dead biomass of Synechocystis has been demonstrated for a range of metals including Cr(VI), Cd(II), Cu(II), Pb(II), Sb, Ni(II), Mn(II), Mn(IV), As(III), As(V), Cs and Hg. The potential of using Synechocystis as a biosorption platform is discussed

Dynamic objectives aggregation methods in multi-objective evolutionary optimization

Several approaches for solving multi-objective optimization problems entail a form of scalarization of the objectives. This chapter proposes a study of different dynamic objectives aggregation methods in the context of evolutionary algorithms. These methods are mainly based on both weighted sum aggregations and curvature variations. Since the incorporation of chaotic rules or behaviour in population-based optimization algorithms has been shown to possibly enhance their searching ability, this study proposes to introduce and evaluate also some chaotic rules in the dynamic weights generation process. A comparison analysis is presented on the basis of a campaign of computational experiments on a set of benchmark problems from the literature

Dynamic Objectives Aggregation Methods for Evolutionary Portfolio Optimization. A computational study

This paper proposes a study of different dynamic objectives aggregation methods (DOAMs) in the context of a multi-objective evolutionary approach to portfolio optimisation. Since the incorporation of chaotic rules or behaviour in population-based optimisation algorithms has been shown to possibly enhance their searching ability, this study considers and evaluates also some chaotic rules in the dynamic weights generation process. The ability of the DOAMs to solve the portfolio rebalancing problem is investigated conducting a computational study on a set of instances based on real data. The portfolio model considers a set of realistic constraints and entails the simultaneous optimisation of the risk on portfolio, the expected return and the transaction cost

Chapter Clinical Trials in Paediatrics — Regulatory and Methodological Aspects

The photoautotrophic cyanobacterium Synechocystis PCC6803 has received much attention as a model photosynthetic cell factory for the production of a range of important biotech products. The biomass remaining from this activity may then have further utility in processes such as metal bioremediation. In addition Synechocystis being an inhabitant of many natural aquatic environments is seen as an environmentally friendly alternative to using chemical precipitation methodologies for metal remediation. Synechocystis produces a range of extracellular polysaccharide substances (EPS) that can undergo modification as a function of culture age and growth nutrients which have been implicated in metal biosorption. Many studies have demonstrated that high levels of charged groups present in EPS are important in forming polymeric matrices with metallic ions allowing their biosorption. Genetic studies has revealed genes involved in such metal binding indicating that EPS can be modified for potential enhancement of binding or modification of the types of metals bound. The utility of metal binding to live and dead biomass of Synechocystis has been demonstrated for a range of metals including Cr(VI), Cd(II), Cu(II), Pb(II), Sb, Ni(II), Mn(II), Mn(IV), As(III), As(V), Cs and Hg. The potential of using Synechocystis as a biosorption platform is discussed

Mapping of Data-Sharing Repositories for Paediatric Clinical Research—A Rapid Review

The reuse of paediatric individual patient data (IPD) from clinical trials (CTs) is essential to overcome specific ethical, regulatory, methodological, and economic issues that hinder the progress of paediatric research. Sharing data through repositories enables the aggregation and dissemination of clinical information, fosters collaboration between researchers, and promotes transparency. This work aims to identify and describe existing data-sharing repositories (DSRs) developed to store, share, and reuse paediatric IPD from CTs. A rapid review of platforms providing access to electronic DSRs was conducted. A two-stage process was used to characterize DSRs: a first step of identification, followed by a second step of analysis using a set of eight purpose-built indicators. From an initial set of forty-five publicly available DSRs, twenty-one DSRs were identified as meeting the eligibility criteria. Only two DSRs were found to be totally focused on the paediatric population. Despite an increased awareness of the importance of data sharing, the results of this study show that paediatrics remains an area in which targeted efforts are still needed. Promoting initiatives to raise awareness of these DSRs and creating ad hoc measures and common standards for the sharing of paediatric CT data could help to bridge this gap in paediatric research

Overview of the EU PAS register post-authorization studies performed in Europe from September 2010 to December 2018

BACKGROUND: The European post-authorisation study (EU PAS) register is a repository launched in 2010 by the European Medicines Agency (EMA). All EMA-requested PAS, commonly observational studies, must be recorded in this register. Multi-database studies (MDS) leveraging secondary data have become an important strategy to conduct PAS in recent years, as reflected by the type of studies registered in the EU PAS register. OBJECTIVES: To analyse and describe PAS in the EU PAS register, with focus on MDS. METHODS: Studies in the EU PAS register from inception to 31(st) December 2018 were described concerning transparency, regulatory obligations, scope, study type (e.g. observational study, clinical trial, survey, systematic review/meta-analysis), study design, type of data collection and target population. MDS were defined as studies conducted through secondary use of >1 data source not linked at patient-level. Data extraction was carried out independently by 14 centres with expertise in pharmacoepidemiology, using publicly available information in the EU PAS register including study protocol, whenever available, using a standardised data collection form. For validation purposes, a second revision of key fields for a 15% random sample of studies was carried out by a different centre. The inter-rater reliability (IRR) was then calculated. Finally, to identify predictors of primary data collection-based studies /vs those based on secondary use of healthcare databases) or MDS (vs. non-MDS), odds ratios (OR) and 95% confidence intervals (CI) were calculated fitting univariate logistic regression models. RESULTS: Overall, 1,426 studies were identified. Clinical trials (N=30; 2%), systematic reviews/meta-analyses (N=16; 1%) and miscellaneous study designs (N=46; 3%) were much less common than observational studies (N=1,227; 86%). The protocol was available for 63% (N=360) of 572 observational studies requested by a competent authority. Overall, 36% (N=446) of observational studies were based fully or partially on primary data collection. Of 757 observational studies based on secondary use of data alone, 282 (37%) were MDS. Drug utilisation was significantly more common as a study scope in MDS compared to non-MDS studies. The overall percentage agreement among collaborating centres that collected the data concerning study variables was highest for study type (93.5%) and lowest for type of secondary data (67.8%). CONCLUSIONS: Observational studies were the most common type of studies in the EU PAS register, but 30% used primary data, which is more resource-intensive. Almost half of observational studies using secondary data were MDS. Data recording in the EU PAS register may be improved further, including more widespread availability of study protocols to improve transparency

Diabetes Affects Antibody Response to SARS-CoV-2 Vaccination in Older Residents of Long-term Care Facilities: Data From the GeroCovid Vax Study

Objective: Type 2 diabetes may affect the humoral immune response after vaccination, but data concerning coronavirus disease 19 (COVID-19) vaccines are scarce. We evaluated the impact of diabetes on antibody response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination in older residents of long-term care facilities (LTCFs) and tested for differences according to antidiabetic treatment. Research design and methods: For this analysis, 555 older residents of LTCFs participating in the GeroCovid Vax study were included. SARS-CoV-2 trimeric S immunoglobulin G (anti-S IgG) concentrations using chemiluminescent assays were tested before the first dose and after 2 and 6 months. The impact of diabetes on anti-S IgG levels was evaluated using linear mixed models, which included the interaction between time and presence of diabetes. A second model also considered diabetes treatment: no insulin therapy (including dietary only or use of oral antidiabetic agents) and insulin therapy (alone or in combination with oral antidiabetic agents). Results: The mean age of the sample was 82.1 years, 68.1% were women, and 25.2% had diabetes. In linear mixed models, presence of diabetes was associated with lower anti-S IgG levels at 2 (β = -0.20; 95% CI -0.34, -0.06) and 6 months (β = -0.22; 95% CI -0.37, -0.07) after the first vaccine dose. Compared with those without diabetes, residents with diabetes not using insulin had lower IgG levels at 2- and 6-month assessments (β = -0.24; 95% CI -0.43, -0.05 and β = -0.30; 95% CI -0.50, -0.10, respectively), whereas no differences were observed for those using insulin. Conclusions: Older residents of LTCFs with diabetes tended to have weaker antibody response to COVID-19 vaccination. Insulin treatment might buffer this effect and establish humoral immunity similar to that in individuals without diabetes