Optimal Portfolio Management for Engineering Problems Using Nonconvex Cardinality Constraint: A Computing Perspective

The problem of portfolio management relates to the selection of optimal stocks, which results in a maximum return to the investor while minimizing the loss. Traditional approaches usually model the portfolio selection as a convex optimization problem and require the calculation of gradient. Note that gradient-based methods can stuck at local optimum for complex problems and the simplification of portfolio optimization to convex, and further solved using gradient-based methods, is at a high cost of solution accuracy. In this paper, we formulate a nonconvex model for the portfolio selection problem, which considers the transaction cost and cardinality constraint, thus better reflecting the decisive factor affecting the selection of portfolio in the real-world. Additionally, constraints are put into the objective function as penalty terms to enforce the restriction. Note that this reformulated problem cannot be readily solved by traditional methods based on gradient search due to its nonconvexity. Then, we apply the Beetle Antennae Search (BAS), a nature-inspired metaheuristic optimization algorithm capable of efficient global optimization, to solve the problem. We used a large real-world dataset containing historical stock prices to demonstrate the efficiency of the proposed algorithm in practical scenarios. Extensive experimental results are presented to further demonstrate the efficacy and scalability of the BAS algorithm. The comparative results are also performed using Particle Swarm Optimizer (PSO), Genetic Algorithm (GA), Pattern Search (PS), and gradient-based fmincon (interior-point search) as benchmarks. The comparison results show that the BAS algorithm is six times faster in the worst case (25 times in the best case) as compared to the rival algorithms while achieving the same level of performance

Profiling microRNAs in individuals at risk of progression to rheumatoid arthritis

Background: Individuals at risk of rheumatoid arthritis (RA) demonstrate systemic autoimmunity in the form of anti-citrullinated peptide antibodies (ACPA). MicroRNAs (miRNAs) are implicated in established RA. This study aimed to (1) compare miRNA expression between healthy individuals and those at risk of and those that develop RA, (2) evaluate the change in expression of miRNA from "at-risk" to early RA and (3) explore whether these miRNAs could inform a signature predictive of progression from "at-risk" to RA. Methods: We performed global profiling of 754 miRNAs per patient on a matched serum sample cohort of 12 anti-cyclic citrullinated peptide (CCP) + "at-risk" individuals that progressed to RA. Each individual had a serum sample from baseline and at time of detection of synovitis, forming the matched element. Healthy controls were also studied. miRNAs with a fold difference/fold change of four in expression level met our primary criterion for selection as candidate miRNAs. Validation of the miRNAs of interest was conducted using custom miRNA array cards on matched samples (baseline and follow up) in 24 CCP+ individuals; 12 RA progressors and 12 RA non-progressors. Results: We report on the first study to use matched serum samples and a comprehensive miRNA array approach to identify in particular, three miRNAs (miR-22, miR-486-3p, and miR-382) associated with progression from systemic autoimmunity to RA inflammation. MiR-22 demonstrated significant fold difference between progressors and non-progressors indicating a potential biomarker role for at-risk individuals. Conclusions: This first study using a cohort with matched serum samples provides important mechanistic insights in the transition from systemic autoimmunity to inflammatory disease for future investigation, and with further evaluation, might also serve as a predictive biomarker

Identifying Tightly Regulated and Variably Expressed Networks by Differential Rank Conservation (DIRAC)

A powerful way to separate signal from noise in biology is to convert the molecular data from individual genes or proteins into an analysis of comparative biological network behaviors. One of the limitations of previous network analyses is that they do not take into account the combinatorial nature of gene interactions within the network. We report here a new technique, Differential Rank Conservation (DIRAC), which permits one to assess these combinatorial interactions to quantify various biological pathways or networks in a comparative sense, and to determine how they change in different individuals experiencing the same disease process. This approach is based on the relative expression values of participating genes—i.e., the ordering of expression within network profiles. DIRAC provides quantitative measures of how network rankings differ either among networks for a selected phenotype or among phenotypes for a selected network. We examined disease phenotypes including cancer subtypes and neurological disorders and identified networks that are tightly regulated, as defined by high conservation of transcript ordering. Interestingly, we observed a strong trend to looser network regulation in more malignant phenotypes and later stages of disease. At a sample level, DIRAC can detect a change in ranking between phenotypes for any selected network. Variably expressed networks represent statistically robust differences between disease states and serve as signatures for accurate molecular classification, validating the information about expression patterns captured by DIRAC. Importantly, DIRAC can be applied not only to transcriptomic data, but to any ordinal data type

The role of the ubiquitination-proteasome pathway in breast cancer: Applying drugs that affect the ubiquitin-proteasome pathway to the therapy of breast cancer

The ubiquitin-proteasome pathway is responsible for most eukaryotic intracellular protein degradation. This pathway has been validated as a target for antineoplastic therapy using both in vitro and preclinical models of human malignancies, and is influenced as part of the mechanism of action of certain chemotherapeutic agents. Drugs whose primary action involves modulation of ubiquitin-proteasome activity, most notably the proteasome inhibitor PS-341, are currently being evaluated in clinical trials, and have already been found to have significant antitumor efficacy. On the basis of the known mechanisms by which these agents work, and the available clinical data, they would seem to be well suited for the treatment of breast neoplasms. Such drugs, alone and especially in combination with current chemotherapeutics, may well represent important advances in the therapy of patients with breast cancer

Involvement of microRNAs in physiological and pathological processes in the lung

To date, at least 900 different microRNA (miRNA) genes have been discovered in the human genome. These short, single-stranded RNA molecules originate from larger precursor molecules that fold to produce hairpin structures, which are subsequently processed by ribonucleases Drosha/Pasha and Dicer to form mature miRNAs. MiRNAs play role in the posttranscriptional regulation of about one third of human genes, mainly via degradation of target mRNAs. Whereas the target mRNAs are often involved in the regulation of diverse physiological processes ranging from developmental timing to apoptosis, miRNAs have a strong potential to regulate fundamental biological processes also in the lung compartment. However, the knowledge of the role of miRNAs in physiological and pathological conditions in the lung is still limited. This review, therefore, summarizes current knowledge of the mechanism, function of miRNAs and their contribution to lung development and homeostasis. Besides the involvement of miRNAs in pulmonary physiological conditions, there is evidence that abnormal miRNA expression may lead to pathological processes and development of various pulmonary diseases. Next, the review describes current state-of-art on the miRNA expression profiles in smoking-related diseases including lung cancerogenesis, in immune system mediated pulmonary diseases and fibrotic processes in the lung. From the current research it is evident that miRNAs may play role in the posttranscriptional regulation of key genes in human pulmonary diseases. Further studies are, therefore, necessary to explore miRNA expression profiles and their association with target mRNAs in human pulmonary diseases

Identification, Expression and Target Gene Analyses of MicroRNAs in Spodoptera litura

MicroRNAs (miRNAs) are small RNAs widely present in animals and plants and involved in post-transcriptional regulation of gene transcripts. In this study we identified and validated 58 miRNAs from an EST dataset of Spodoptera litura based on the computational and experimental analysis of sequence conservation and secondary structure of miRNA by comparing the miRNA sequences in the miRbase. RT-PCR was conducted to examine the expression of these miRNAs and stem-loop RT-PCR assay was performed to examine expression of 11 mature miRNAs (out of the 58 putative miRNA) that showed significant changes in different tissues and stages of the insect development. One hundred twenty eight possible target genes against the 11 miRNAs were predicted by using computational methods. Binding of one miRNA (sli-miR-928b) with the three possible target mRNAs was confirmed by Southern blotting, implying its possible function in regulation of the target genes

Regulation of microRNA biogenesis and turnover by animals and their viruses

Item does not contain fulltextMicroRNAs (miRNAs) are a ubiquitous component of gene regulatory networks that modulate the precise amounts of proteins expressed in a cell. Despite their small size, miRNA genes contain various recognition elements that enable specificity in when, where and to what extent they are expressed. The importance of precise control of miRNA expression is underscored by functional studies in model organisms and by the association between miRNA mis-expression and disease. In the last decade, identification of the pathways by which miRNAs are produced, matured and turned-over has revealed many aspects of their biogenesis that are subject to regulation. Studies in viral systems have revealed a range of mechanisms by which viruses target these pathways through viral proteins or non-coding RNAs in order to regulate cellular gene expression. In parallel, a field of study has evolved around the activation and suppression of antiviral RNA interference (RNAi) by viruses. Virus encoded suppressors of RNAi can impact miRNA biogenesis in cases where miRNA and small interfering RNA pathways converge. Here we review the literature on the mechanisms by which miRNA biogenesis and turnover are regulated in animals and the diverse strategies that viruses use to subvert or inhibit these processes

Noncanonical G recognition mediates KSRP regulation of let-7 biogenesis

Let-7 is an important tumor-suppressive microRNA (miRNA) that acts as an on-off switch for cellular differentiation and regulates the expression of a set of human oncogenes. Binding of the human KSRP protein to let-7 miRNA precursors positively regulates their processing to mature let-7, thereby contributing to control of cell proliferation, apoptosis and differentiation. Here we analyze the molecular basis for KSRP-let-7 precursor selectivity and show how the third KH domain of the protein recognizes a G-rich sequence in the pre-let-7 terminal loop and dominates the interaction. The structure of the KH3-RNA complex explains the protein recognition of this noncanonical KH target sequence, and we demonstrate that the specificity of this binding is crucial for the functional interaction between the protein and the miRNA precursor

Carbon Dioxide Utilisation -The Formate Route

UIDB/50006/2020 CEEC-Individual 2017 Program Contract.The relentless rise of atmospheric CO2 is causing large and unpredictable impacts on the Earth climate, due to the CO2 significant greenhouse effect, besides being responsible for the ocean acidification, with consequent huge impacts in our daily lives and in all forms of life. To stop spiral of destruction, we must actively reduce the CO2 emissions and develop new and more efficient “CO2 sinks”. We should be focused on the opportunities provided by exploiting this novel and huge carbon feedstock to produce de novo fuels and added-value compounds. The conversion of CO2 into formate offers key advantages for carbon recycling, and formate dehydrogenase (FDH) enzymes are at the centre of intense research, due to the “green” advantages the bioconversion can offer, namely substrate and product selectivity and specificity, in reactions run at ambient temperature and pressure and neutral pH. In this chapter, we describe the remarkable recent progress towards efficient and selective FDH-catalysed CO2 reduction to formate. We focus on the enzymes, discussing their structure and mechanism of action. Selected promising studies and successful proof of concepts of FDH-dependent CO2 reduction to formate and beyond are discussed, to highlight the power of FDHs and the challenges this CO2 bioconversion still faces.publishersversionpublishe