Nested evolutionary algorithms for computationally expensive bilevel optimization problems: Variants and their systematic analysis

© 2019 Elsevier B.V. Bilevel optimization problems involve a hierarchical model where an upper level optimization problem is solved with a constraint on the optimality of a nested lower level problem. The use of evolutionary algorithms (EAs) and other metaheuristics has been gaining attention to solve bilevel problems, especially when they contain non-linear/black-box objective(s) and/or constraint(s). However, EAs typically operate in a nested mode wherein a lower level optimization is executed for each upper level solution. Evidently, this process requires excessive number of function evaluations, which might become untenable if the underlying functions are computationally expensive. In order to reduce this expense, the use of approximations (also referred to as surrogates or meta-models) has been suggested previously. However, the previous works have focused only on the use of surrogates for the lower level problem, whereas the computational expense of the upper level problem has not been considered. In this paper, we aim to make two contributions to address this research gap. The first is to introduce an improved nested EA which uses surrogate-assisted search at both levels in order to solve bilevel problems using limited number of function evaluations. The second is the revelation and a systematic investigation of a previously overlooked aspect of bilevel search – that the objective/constraints at the upper and lower levels may involve different computational expense. Consideration of this aspect can help in deciding a suitable strategy, i.e., in which level is the use of surrogates most appropriate for the given problem. Towards this end, four different nested strategies – with surrogate at either level, none or at both levels, are compared under various experimental settings. Numerical experiments are presented on a wide range of problems to demonstrate the efficacy and utility of the proposed contributions

Erratum: Association between suicidal ideation and suicide: Meta-analyses of odds ratios, sensitivity, specificity and positive predictive value (BJPsych Open (2019) 5:2 (e18) DOI: 10.1192/bjo.2018.88)

The publishers regret to announce that the above paper was published with the incorrect article number. The correct citation details are as follows: McHugh CM, Corderoy A, Ryan CJ, Hickie IB, Large MM. Association between suicidal ideation and suicide: Meta-analyses of odds ratios, sensitivity, specificity and positive predictive value. BJPsych Open 2019; 5(2): e18. doi:10.1192/bjo.2018.88. This has now been updated in the original article online. The publisher sincerely apologises for this error

Association between suicidal ideation and suicide: Meta-analyses of odds ratios, sensitivity, specificity and positive predictive value

Background The expression of suicidal ideation is considered to be an important warning sign for suicide. However, the predictive properties of suicidal ideation as a test of later suicide are unclear.Aims To assess the strength of the association between suicidal ideation and later suicide measured by odds ratio (OR), sensitivity, specificity and positive predictive value (PPV).Method We located English-language studies indexed in PubMed that reported the expression or non-expression of suicidal ideation among people who later died by suicide or did not. A random effects meta-analysis was used to assess the pooled OR, sensitivity, specificity and PPV of suicidal ideation for later suicide among groups of people from psychiatric and non-psychiatric settings.Results There was a moderately strong but highly heterogeneous association between suicidal ideation and later suicide (n = 71, OR = 3.41, 95% CI 2.59-4.49, 95% prediction interval 0.42-28.1, I2 = 89.4, Q-value = 661, d.f.(Q) = 70, P ≤0.001). Studies conducted in primary care and other non-psychiatric settings had similar pooled odds to studies of current and former psychiatric patients (OR = 3.86 v. OR = 3.23, P = 0.7). The pooled sensitivity of suicidal ideation for later suicide was 41% (95% CI 35-48) and the pooled specificity was 86% (95% CI 76-92), with high between-study heterogeneity. Studies of suicidal ideation expressed by current and former psychiatric patients had a significantly higher pooled sensitivity (46% v. 22%) and lower pooled specificity (81% v. 96%) than studies conducted in non-psychiatric settings. The PPV among non-psychiatric cohorts (0.3%, 95% CI 0.1%-0.5%) was significantly lower (Q-value = 35.6, P < 0.001) than among psychiatric samples (3.9%, 95% CI 2.2-6.6).Conclusions Estimates of the extent of the association between suicidal ideation and later suicide are limited by unexplained between-study heterogeneity. The utility of suicidal ideation as a test for later suicide is limited by a modest sensitivity and low PPV.Declaration interest M.M.L. and C.J.R. have provided expert evidence in civil, criminal and coronial matters. I.B.H. has been a Commissioner in Australia's National Mental Health Commission since 2012. He is the Co-Director, Health and Policy at the Brain and Mind Centre (BMC) University of Sydney. The BMC operates an early-intervention youth services at Camperdown under contract to Headspace. I.B.H. has previously led community-based and pharmaceutical industry-supported (Wyeth, Eli Lily, Servier, Pfizer, AstraZeneca) projects focused on the identification and better management of anxiety and depression. He is a Board Member of Psychosis Australia Trust and a member of Veterans Mental Health Clinical Reference group. He was a member of the Medical Advisory Panel for Medibank Private until October 2017. He is the Chief Scientific Advisor to, and an equity shareholder in, InnoWell. InnoWell has been formed by the University of Sydney and PricewaterhouseCoopers to administer the $30 M Australian Government Funded Project Synergy. Project Synergy is a 3-year programme for the transformation of mental health services through the use of innovative technologies

Analytical transmission electron microscopy at organic interfaces

Organic materials are ubiquitous in all aspects of our daily lives. Increasingly there is a need to understand interactions between different organic phases, or between organic and inorganic materials (hybrid interfaces), in order to gain fundamental knowledge about the origin of their structural and functional properties. In order to understand the complex structure–property–processing relationships in (and between) these materials, we need tools that combine high chemical sensitivity with high spatial resolution to allow detailed interfacial characterisation. Analytical transmission electron microscopy (TEM) is a powerful and versatile technique that can fulfil both criteria. However, the application of analytical TEM to organic systems presents some unique challenges, such as low contrast between phases, and electron beam sensitivity. In this review recent analytical TEM approaches to the nanoscale characterisation of two systems will be discussed: the hybrid collagen/mineral interface in bone, and the all-organic donor/acceptor interface in OPV devices

RepSeq-A database of amino acid repeats present in lower eukaryotic pathogens

BACKGROUND Amino acid repeat-containing proteins have a broad range of functions and their identification is of relevance to many experimental biologists. In human-infective protozoan parasites (such as the Kinetoplastid and Plasmodium species), they are implicated in immune evasion and have been shown to influence virulence and pathogenicity. RepSeq http://repseq.gugbe.com is a new database of amino acid repeat-containing proteins found in lower eukaryotic pathogens. The RepSeq database is accessed via a web-based application which also provides links to related online tools and databases for further analyses. RESULTS The RepSeq algorithm typically identifies more than 98% of repeat-containing proteins and is capable of identifying both perfect and mismatch repeats. The proportion of proteins that contain repeat elements varies greatly between different families and even species (3 - 35% of the total protein content). The most common motif type is the Sequence Repeat Region (SRR) - a repeated motif containing multiple different amino acid types. Proteins containing Single Amino Acid Repeats (SAARs) and Di-Peptide Repeats (DPRs) typically account for 0.5 - 1.0% of the total protein number. Notable exceptions are P. falciparum and D. discoideum, in which 33.67% and 34.28% respectively of the predicted proteomes consist of repeat-containing proteins. These numbers are due to large insertions of low complexity single and multi-codon repeat regions. CONCLUSION The RepSeq database provides a repository for repeat-containing proteins found in parasitic protozoa. The database allows for both individual and cross-species proteome analyses and also allows users to upload sequences of interest for analysis by the RepSeq algorithm. Identification of repeat-containing proteins provides researchers with a defined subset of proteins which can be analysed by expression profiling and functional characterisation, thereby facilitating study of pathogenicity and virulence factors in the parasitic protozoa. While primarily designed for kinetoplastid work, the RepSeq algorithm and database retain full functionality when used to analyse other species

Time-dependent changes in gene expression induced by secreted amyloid precursor protein-alpha in the rat hippocampus

Background: Differential processing of the amyloid precursor protein liberates either amyloid-ß, a causative agent of Alzheimer's disease, or secreted amyloid precursor protein-alpha (sAPPα), which promotes neuroprotection, neurotrophism, neurogenesis and synaptic plasticity. The underlying molecular mechanisms recruited by sAPPα that underpin these considerable cellular effects are not well elucidated. As these effects are enduring, we hypothesised that regulation of gene expression may be of importance and examined temporally specific gene networks and pathways induced by sAPPα in rat hippocampal organotypic slice cultures. Slices were exposed to 1 nM sAPPα or phosphate buffered saline for 15 min, 2 h or 24 h and sAPPα-associated gene expression profiles were produced for each time-point using Affymetrix Rat Gene 1.0 ST arrays (moderated t-test using Limma: p < 0.05, and fold change ± 1.15).Results: Treatment of organotypic hippocampal slice cultures with 1 nM sAPPα induced temporally distinct gene expression profiles, including mRNA and microRNA associated with Alzheimer's disease. Having demonstrated that treatment with human recombinant sAPPα was protective against N-methyl d-aspartate-induced toxicity, we next explored the sAPPα-induced gene expression profiles. Ingenuity Pathway Analysis predicted that short-term exposure to sAPPα elicited a multi-level transcriptional response, including upregulation of immediate early gene transcription factors (AP-1, Egr1), modulation of the chromatin environment, and apparent activation of the constitutive transcription factors CREB and NF-κB. Importantly, dynamic regulation of NF-κB appears to be integral to the transcriptional response across all time-points. In contrast, medium and long exposure to sAPPα resulted in an overall downregulation of gene expression. While these results suggest commonality between sAPPα and our previously reported analysis of plasticity-related gene expression, we found little crossover between these datasets. The gene networks formed following medium and long exposure to sAPPα were associated with inflammatory response, apoptosis, neurogenesis and cell survival; functions likely to be the basis of the neuroprotective effects of sAPPα.Conclusions: Our results demonstrate that sAPPα rapidly and persistently regulates gene expression in rat hippocampus. This regulation is multi-level, temporally specific and is likely to underpin the neuroprotective effects of sAPPα. © 2013 Ryan et al.; licensee BioMed Central Ltd

Skewness and Staging: Does the Floor Effect Induce Bias in Multilevel AR(1) Models?

Multilevel autoregressive models are popular choices for the analysis of intensive longitudinal data in psychology. Empirical studies have found a positive correlation between autoregressive parameters of affective time series and the between-person measures of psychopathology, a phenomenon known as the staging effect. However, it has been argued that such findings may represent a statistical artifact: Although common models assume normal error distributions, empirical data (for instance, measurements of negative affect among healthy individuals) often exhibit the floor effect, that is response distributions with high skewness, low mean, and low variability. In this paper, we investigated whether—and to what extent—the floor effect leads to erroneous conclusions by means of a simulation study. We describe three dynamic models which have meaningful substantive interpretations and can produce floor-effect data. We simulate multilevel data from these models, varying skewness independent of individuals’ autoregressive parameters, while also varying the number of time points and cases. Analyzing these data with the standard multilevel AR(1) model we found that positive bias only occurs when modeling with random residual variance, whereas modeling with fixed residual variance leads to negative bias. We discuss the implications of our study for data collection and modeling choices

A novel targeted/untargeted GC-Orbitrap metabolomics methodology applied to Candida albicans and Staphylococcus aureus biofilms

Introduction: Combined infections from Candida albicans and Staphylococcus aureus are a leading cause of death in the developed world. Evidence suggests that Candida enhances the virulence of Staphylococcus—hyphae penetrate through tissue barriers, while S. aureus tightly associates with the hyphae to obtain entry to the host organism. Indeed, in a biofilm state, C. albicans enhances the antimicrobial resistance characteristics of S. aureus. The association of these microorganisms is also associated with significantly increased morbidity and mortality. Due to this tight association we hypothesised that metabolic effects were also in evidence. Objectives: To explore the interaction, we used a novel GC-Orbitrap-based mass spectrometer, the Q Exactive GC, which combines the high peak capacity and chromatographic resolution of gas chromatography with the sub-ppm mass accuracy of an Orbitrap system. This allows the capability to leverage the widely available electron ionisation libraries for untargeted applications, along with expanding accurate mass libraries and targeted matches based around authentic standards. Methods: Optimised C. albicans and S. aureus mono- and co-cultured biofilms were analysed using the new instrument in addition to the fresh and spent bacterial growth media. Results: The targeted analysis experiment was based around 36 sugars and sugar phosphates, 22 amino acids and five organic acids. Untargeted analysis resulted in the detection of 465 features from fresh and spent medium and 405 from biofilm samples. Three significantly changing compounds that matched to high scoring library fragment patterns were chosen for validation. Conclusion: Evaluation of the results demonstrates that the Q Exactive GC is suitable for metabolomics analysis using a targeted/untargeted methodology. Many of the results were as expected: e.g. rapid consumption of glucose and fructose from the medium regardless of the cell type. Modulation of sugar-phosphate levels also suggest that the pentose phosphate pathway could be enhanced in the cells from co-cultured biofilms. Untargeted metabolomics results suggested significant production of cell-wall biosynthesis components and the consumption of non-proteinaceous amino-acids