Using Optimality Theory and Reference Points to Improve the Diversity and Convergence of a Fuzzy-Adaptive Multi-Objective Particle Swarm Optimizer

Particle Swarm Optimization (PSO) has received increasing attention from the evolutionary optimization research community in the last twenty years. PSO is a metaheuristic approach based on collective intelligence obtained by emulating the swarming behavior of bees. A number of multi-objective variants of the original PSO algorithm that extend its applicability to optimization problems with conflicting objectives have also been developed; these multi-objective PSO (MOPSO) algorithms demonstrate comparable performance to other state-of-the-art metaheuristics. The existence of multiple optimal solutions (Pareto-optimal set) in optimization problems with conflicting objectives is not the only challenge posed to an optimizer, as the latter needs to be able to identify and preserve a well-distributed set of solutions during the search of the decision variable space. Recent attempts by evolutionary optimization researchers to incorporate mathematical convergence conditions into genetic algorithm optimizers have led to the derivation of a point-wise proximity measure, which is based on the solution of the achievement scalarizing function (ASF) optimization problem with a complementary slackness condition that quantifies the violation of the Karush-Kuhn-Tucker necessary conditions of optimality. In this work, the aforementioned KKT proximity measure is incorporated into the original Adaptive Coevolutionary Multi-Objective Swarm Optimizer (ACMOPSO) in order to monitor the convergence of the sub-swarms towards the Pareto-optimal front and provide feedback to Mamdani-type fuzzy logic controllers (FLCs) that are utilized for online adaptation of the algorithmic parameters. The proposed Fuzzy-Adaptive Multi-Objective Optimization Algorithm with the KKT proximity measure (FAMOPSOkkt) utilizes a set of reference points to cluster the computed nondominated solutions. These clusters interact with their corresponding sub-swarms to provide the swarm leaders and are also utilized to manage the external archive of nondominated solutions. The performance of the proposed algorithm is evaluated on benchmark problems chosen from the multi-objective optimization literature and compared to the performance of state-of-the-art multi-objective optimization algorithms with similar features

Artificial Neural Network Model for Suspended Rectangular Microstrip Antennas

AbstractThe broadband microstrip antenna is more commonly realized by fabricating the patch on lower dielectric constant thicker substrate. While using thicker substrate, close form expressions for calculating edge extension length due to fringing fields is not available. In this paper, an artificial neural network model for suspended rectangular microstrip antenna is proposed. The resonance frequency calculated by using the proposed neural network model closely agrees with simulated and measured results over wide frequency range and for varying thicker substrates. Thus the proposed model can be used to accurately calculate the side length of rectangular microstrip antenna

Definition, conservation and epigenetics of housekeeping and tissue-enriched genes

<p>Abstract</p> <p>Background</p> <p>Housekeeping genes (HKG) are constitutively expressed in all tissues while tissue-enriched genes (TEG) are expressed at a much higher level in a single tissue type than in others. HKGs serve as valuable experimental controls in gene and protein expression experiments, while TEGs tend to represent distinct physiological processes and are frequently candidates for biomarkers or drug targets. The genomic features of these two groups of genes expressed in opposing patterns may shed light on the mechanisms by which cells maintain basic and tissue-specific functions.</p> <p>Results</p> <p>Here, we generate gene expression profiles of 42 normal human tissues on custom high-density microarrays to systematically identify 1,522 HKGs and 975 TEGs and compile a small subset of 20 housekeeping genes which are highly expressed in all tissues with lower variance than many commonly used HKGs. Cross-species comparison shows that both the functions and expression patterns of HKGs are conserved. TEGs are enriched with respect to both segmental duplication and copy number variation, while no such enrichment is observed for HKGs, suggesting the high expression of HKGs are not due to high copy numbers. Analysis of genomic and epigenetic features of HKGs and TEGs reveals that the high expression of HKGs across different tissues is associated with decreased nucleosome occupancy at the transcription start site as indicated by enhanced DNase hypersensitivity. Additionally, we systematically and quantitatively demonstrated that the CpG islands' enrichment in HKGs transcription start sites (TSS) and their depletion in TEGs TSS. Histone methylation patterns differ significantly between HKGs and TEGs, suggesting that methylation contributes to the differential expression patterns as well.</p> <p>Conclusion</p> <p>We have compiled a set of high quality HKGs that should provide higher and more consistent expression when used as references in laboratory experiments than currently used HKGs. The comparison of genomic features between HKGs and TEGs shows that HKGs are more conserved than TEGs in terms of functions, expression pattern and polymorphisms. In addition, our results identify chromatin structure and epigenetic features of HKGs and TEGs that are likely to play an important role in regulating their strikingly different expression patterns.</p

Outcomes of treatment of unresectable esophageal carcinoma treated with chemoradiotherapy and oral metronomic chemotherapy: An experience from a rural cancer center

Introduction: Esophageal carcinoma is the eight most common cancer in the world. The management of locally advancedcarcinoma esophagus is mainly palliative with chemoradiotherapy. The outcome data of such a modality along with oralmetronomic chemotherapy after treatment completion are sparse. Here, we present the outcomes of treatment of locally advancedunresectable esophageal cancer after palliative chemoradiotherapy and oral metronomic therapy from a rural setting in India.Methods: Retrospective analysis of all patients of locally advanced unresectable nonmetastatic esophageal carcinoma treatedwith short course of induction chemotherapy followed by radiotherapy/chemoradiotherapy and oral metronomic chemotherapywas performed. The primary aim was estimation of progression free-survival (PFS) and overall survival (OS). Results: A total of45 patients were analyzed. Mean age was 55 years (30-85 years). A total of 32 patients had tumors in upper and middle esophagus,with the most common histology being squamous cell carcinoma (N-41). The estimated 2 year PFS is 47.2% and the estimated2 years OS is 57.8%. Conclusion: Combined modality therapy with adjuvant oral metronomic therapy shows promising results inthe management and should be the basis of further trials

A simple method to combine multiple molecular biomarkers for dichotomous diagnostic classification

BACKGROUND: In spite of the recognized diagnostic potential of biomarkers, the quest for squelching noise and wringing in information from a given set of biomarkers continues. Here, we suggest a statistical algorithm that – assuming each molecular biomarker to be a diagnostic test – enriches the diagnostic performance of an optimized set of independent biomarkers employing established statistical techniques. We validated the proposed algorithm using several simulation datasets in addition to four publicly available real datasets that compared i) subjects having cancer with those without; ii) subjects with two different cancers; iii) subjects with two different types of one cancer; and iv) subjects with same cancer resulting in differential time to metastasis. RESULTS: Our algorithm comprises of three steps: estimating the area under the receiver operating characteristic curve for each biomarker, identifying a subset of biomarkers using linear regression and combining the chosen biomarkers using linear discriminant function analysis. Combining these established statistical methods that are available in most statistical packages, we observed that the diagnostic accuracy of our approach was 100%, 99.94%, 96.67% and 93.92% for the real datasets used in the study. These estimates were comparable to or better than the ones previously reported using alternative methods. In a synthetic dataset, we also observed that all the biomarkers chosen by our algorithm were indeed truly differentially expressed. CONCLUSION: The proposed algorithm can be used for accurate diagnosis in the setting of dichotomous classification of disease states

The value of allied health professional research engagement on healthcare performance: a systematic review

Background Existing evidence suggests that clinician and organisation engagement in research can improve healthcare performance. However, current evidence has considered the relationship across all healthcare professions collectively. With the increase in allied health professional (AHP) clinical academic and research activity, it is imperative for healthcare organisations, leaders and managers to understand research engagement within these specific clinical fields. This systematic review aims to examine the value of research engagement by allied health professionals and organisations on healthcare performance. Methods This systematic review had a two-stage search strategy. Firstly, the papers from a previous systematic review examining the effect of research engagement in healthcare were screened to identify relevant papers published pre-2012. Secondly, a multi-database search was used to update the previous review but with a specific focus on allied health to identify publications from 2012 to date. Studies which explored the value of allied health research engagement on healthcare performance were included. All stages of the review were conducted by two reviewers independently, plus documented discussions with the wider research team when discrepancies occurred. Each study was assessed using the appropriate critical appraisal tool developed by the Joanna Briggs Institute. Results Twenty-two studies were included, of which six were ranked as high importance. This sample comprised mixed research designs. Overall, the findings indicated positive improvements in processes of care. The review also identified the most common mechanisms which may link research engagement with improvements to processes of care. Conclusion This landmark review is the first benchmark of evidence that explicitly shows improved processes of care and outcomes from AHP research engagement. The lack of transparent reporting of AHP research engagement highlights the need for clear recommendations in the design of future prospective studies. These proposals specifically include greater transparency in relation to AHP involvement, mechanisms and types of research engagement. The inclusion of these aspects as an integral component of future intervention study designs may contribute essential evidence of the value and impact of AHP research engagement

Unregulated Sale of Nimesulide in India

IntroductionNimesulide has been withdrawn from a number of countries. However it continues to be available over the counter in India.MethodsA survey of 1460 drug stores and 1531 families in India on their perceptions of the potential side effects of Nimesulide.Results A high proportion (78.96%) of the drug stores sold the drug without prescription from a licensed physician. More than one in four families (26.95%) preferred Nimesulide to other drugs. A relatively small proportion drug store owners and families (12.14% and 9.6% respectively) were aware of the potential adverse effects of this drug. DiscussionThere is an urgent need to tighten regulation of dangerous drugs freely available to Indian consumers. Further research to increase public awareness about drug side effects is required in order to reduce the potential for harm from under regulation

Editorial Perspective: Speaking up for developmental language disorder - the top 10 priorities for research

Developmental language disorder (DLD) is one of the most common neurodevelopmental conditions, yet is chronically underserved, with far fewer children receiving clinical services than expected from prevalence estimates, and very little research attention relative to other neurodevelopmental conditions of similar prevalence and severity. This editorial describes a research priority-setting exercise undertaken by the Royal College of Speech and Language Therapists, which aims to redress this imbalance. From consultations with researchers, practitioners and individuals with lived experience, 10 research priorities emerge. Our goal is to share these priorities with the wider research community, to raise awareness and encourage research collaboration to improve outcomes for young people with DLD

Lung eQTLs to Help Reveal the Molecular Underpinnings of Asthma

Genome-wide association studies (GWAS) have identified loci reproducibly associated with pulmonary diseases; however, the molecular mechanism underlying these associations are largely unknown. The objectives of this study were to discover genetic variants affecting gene expression in human lung tissue, to refine susceptibility loci for asthma identified in GWAS studies, and to use the genetics of gene expression and network analyses to find key molecular drivers of asthma. We performed a genome-wide search for expression quantitative trait loci (eQTL) in 1,111 human lung samples. The lung eQTL dataset was then used to inform asthma genetic studies reported in the literature. The top ranked lung eQTLs were integrated with the GWAS on asthma reported by the GABRIEL consortium to generate a Bayesian gene expression network for discovery of novel molecular pathways underpinning asthma. We detected 17,178 cis- and 593 trans- lung eQTLs, which can be used to explore the functional consequences of loci associated with lung diseases and traits. Some strong eQTLs are also asthma susceptibility loci. For example, rs3859192 on chr17q21 is robustly associated with the mRNA levels of GSDMA (P = 3.55 × 10(-151)). The genetic-gene expression network identified the SOCS3 pathway as one of the key drivers of asthma. The eQTLs and gene networks identified in this study are powerful tools for elucidating the causal mechanisms underlying pulmonary disease. This data resource offers much-needed support to pinpoint the causal genes and characterize the molecular function of gene variants associated with lung diseases

Human NK Cells Differ More in Their KIR2DL1-Dependent Thresholds for HLA-Cw6-Mediated Inhibition than in Their Maximal Killing Capacity

In this study we have addressed the question of how activation and inhibition of human NK cells is regulated by the expression level of MHC class I protein on target cells. Using target cell transfectants sorted to stably express different levels of the MHC class I protein HLA-Cw6, we show that induction of degranulation and that of IFN-γ secretion are not correlated. In contrast, the inhibition of these two processes by MHC class-I occurs at the same level of class I MHC protein. Primary human NK cell clones were found to differ in the amount of target MHC class I protein required for their inhibition, rather than in their maximum killing capacity. Importantly, we show that KIR2DL1 expression determines the thresholds (in terms of MHC I protein levels) required for NK cell inhibition, while the expression of other receptors such as LIR1 is less important. Furthermore, using mathematical models to explore the dynamics of target cell killing, we found that the observed delay in target cell killing is exhibited by a model in which NK cells require some activation or priming, such that each cell can lyse a target cell only after being activated by a first encounter with the same or a different target cell, but not by models which lack this feature