Confidence Intervals for Comparison of the Squared Multiple Correlation Coefficients of Non-nested Models

Multiple linear regression analysis is used widely to evaluate how an outcome or responsevariable is related to a set of predictors. Once a final model is specified, the interpretation of predictors can be achieved by assessing the relative importance of predictors. A common approach to predictor importance is to compare the increase in squared multiple correlation for a given model when one predictor is added to the increase when another predictor is added to the same model. This thesis proposes asymmetric confidence-intervals for a difference between two correlated squared multiple correlation coefficients of non-nested models. These new proceduresare developed by recovering variance estimates needed for the difference from asymmetric confidence limits for single multiple correlation coefficients. Simulation resultsshow that the new procedure based on confidence limits obtained from the two-moment scaled central F approximation performs much better than the traditional Wald approach. Two examples are used to illustrate the methodology. The application of the procedure indominance analysis and commonality analysis is discussed

Multi-objective improvement of software using co-evolution and smart seeding

Optimising non-functional properties of software is an important part of the implementation process. One such property is execution time, and compilers target a reduction in execution time using a variety of optimisation techniques. Compiler optimisation is not always able to produce semantically equivalent alternatives that improve execution times, even if such alternatives are known to exist. Often, this is due to the local nature of such optimisations. In this paper we present a novel framework for optimising existing software using a hybrid of evolutionary optimisation techniques. Given as input the implementation of a program or function, we use Genetic Programming to evolve a new semantically equivalent version, optimised to reduce execution time subject to a given probability distribution of inputs. We employ a co-evolved population of test cases to encourage the preservation of the program’s semantics, and exploit the original program through seeding of the population in order to focus the search. We carry out experiments to identify the important factors in maximising efficiency gains. Although in this work we have optimised execution time, other non-functional criteria could be optimised in a similar manner

A Novel Unsupervised Method to Identify Genes Important in the Anti-viral Response: Application to Interferon/Ribavirin in Hepatitis C Patients

Background: Treating hepatitis C with interferon/ribavirin results in a varied response in terms of decrease in viral titer and ultimate outcome. Marked responders have a sharp decline in viral titer within a few days of treatment initiation, whereas in other patients there is no effect on the virus (poor responders). Previous studies have shown that combination therapy modifies expression of hundreds of genes in vitro and in vivo. However, identifying which, if any, of these genes have a role in viral clearance remains challenging. Aims: The goal of this paper is to link viral levels with gene expression and thereby identify genes that may be responsible for early decrease in viral titer. Methods: Microarrays were performed on RNA isolated from PBMC of patients undergoing interferon/ribavirin therapy. Samples were collected at pre-treatment (day 0), and 1, 2, 7, 14 and 28 days after initiating treatment. A novel method was applied to identify genes that are linked to a decrease in viral titer during interferon/ribavirin treatment. The method uses the relationship between inter-patient gene expression based proximities and inter-patient viral titer based proximities to define the association between microarray gene expression measurements of each gene and viral-titer measurements. Results: We detected 36 unique genes whose expressions provide a clustering of patients that resembles viral titer based clustering of patients. These genes include IRF7, MX1, OASL and OAS2, viperin and many ISG's of unknown function. Conclusion: The genes identified by this method appear to play a major role in the reduction of hepatitis C virus during the early phase of treatment. The method has broad utility and can be used to analyze response to any group of factors influencing biological outcome such as antiviral drugs or anti-cancer agents where microarray data are available. © 2007 Brodsky et al

Serum microRNA array analysis identifies miR-140-3p, miR-33b-3p and miR-671-3p as potential osteoarthritis biomarkers involved in metabolic processes.

Background: MicroRNAs (miRNAs) in circulation have emerged as promising biomarkers. In this study, we aimed to identify a circulating miRNA signature for osteoarthritis (OA) patients and in combination with bioinformatics analysis to evaluate the utility of selected differentially expressed miRNAs in the serum as potential OA biomarkers. Methods: Serum samples were collected from 12 primary OA patients, and 12 healthy individuals were screened using the Agilent Human miRNA Microarray platform interrogating 2549 miRNAs. Receiver Operating Characteristic (ROC) curves were constructed to evaluate the diagnostic performance of the deregulated miRNAs. Expression levels of selected miRNAs were validated by quantitative real-time PCR (qRT-PCR) in all serum and in articular cartilage samples from OA patients (n = 12) and healthy individuals (n = 7). Bioinformatics analysis was used to investigate the involved pathways and target genes for the above miRNAs. Results: We identified 279 differentially expressed miRNAs in the serum of OA patients compared to controls. Two hundred and five miRNAs (73.5%) were upregulated and 74 (26.5%) downregulated. ROC analysis revealed that 77 miRNAs had area under the curve (AUC) > 0.8 and p < 0.05. Bioinformatics analysis in the 77 miRNAs revealed that their target genes were involved in multiple signaling pathways associated with OA, among which FoxO, mTOR, Wnt, pI3K/akt, TGF-β signaling pathways, ECM-receptor interaction, and fatty acid biosynthesis. qRT-PCR validation in seven selected out of the 77 miRNAs revealed 3 significantly downregulated miRNAs (hsa-miR-33b-3p, hsa-miR-671-3p, and hsa-miR-140-3p) in the serum of OA patients, which were in silico predicted to be enriched in pathways involved in metabolic processes. Target-gene analysis of hsa-miR-140-3p, hsa-miR-33b-3p, and hsa-miR-671-3p revealed that InsR and IGFR1 were common targets of all three miRNAs, highlighting their involvement in regulation of metabolic processes that contribute to OA pathology. Hsa-miR-140-3p and hsa-miR-671-3p expression levels were consistently downregulated in articular cartilage of OA patients compared to healthy individuals. Conclusions: A serum miRNA signature was established for the first time using high density resolution miR-arrays in OA patients. We identified a three-miRNA signature, hsa-miR-140-3p, hsa-miR-671-3p, and hsa-miR-33b-3p, in the serum of OA patients, predicted to regulate metabolic processes, which could serve as a potential biomarker for the evaluation of OA risk and progression.Peer reviewedFinal Published versio

Development of CRISPR-Cas13a-based antimicrobials capable of sequence-specific killing of target bacteria

The emergence of antimicrobial-resistant bacteria is an increasingly serious threat to global health, necessitating the development of innovative antimicrobials. Here we report the development of a series of CRISPR-Cas13a-based antibacterial nucleocapsids, termed CapsidCas13a(s), capable of sequence-specific killing of carbapenem-resistant Escherichia coli and methicillin-resistant Staphylococcus aureus by recognizing corresponding antimicrobial resistance genes. CapsidCas13a constructs are generated by packaging programmed CRISPR-Cas13a into a bacteriophage capsid to target antimicrobial resistance genes. Contrary to Cas9-based antimicrobials that lack bacterial killing capacity when the target genes are located on a plasmid, the CapsidCas13a(s) exhibit strong bacterial killing activities upon recognizing target genes regardless of their location. Moreover, we also demonstrate that the CapsidCas13a(s) can be applied to detect bacterial genes through gene-specific depletion of bacteria without employing nucleic acid manipulation and optical visualization devices. Our data underscore the potential of CapsidCas13a(s) as both therapeutic agents against antimicrobial-resistant bacteria and nonchemical agents for detection of bacterial genes

Precipitate Redistribution During Creep of Alloy 617

Nickel-based superalloys are being considered for applications within advanced nuclear power generation systems due to their high temperature strength and corrosion resistance. Alloy 617, a candidate for use in heat exchangers, derives its strength from both solid solution strengthening and the precipitation of carbide particles. However, during creep, carbides that are supposed to retard grain boundary motion are found to dissolve and re-precipitate on boundaries in tension. To quantify the redistribution, we have used electron backscatter diffraction and energy dispersive spectroscopy to analyze the microstructure of 617 after creep testing at 900 and 1000°C. The data were analyzed with respect to location of the carbides (e.g., intergranular vs. intragranular), grain boundary character, and precipitate type (i.e., Cr-rich or Mo-rich). We find that grain boundary character is the most important factor in carbide distribution; some evidence of preferential distribution to boundaries in tension is also observed at higher applied stresses. Finally, the results suggest that the observed redistribution is due to the migration of carbides to the boundaries and not the migration of boundaries to the precipitates

Exploiting inflammation for therapeutic gain in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy associated with &#60;5% 5-year survival, in which standard chemotherapeutics have limited benefit. The disease is associated with significant intra- and peritumoral inflammation and failure of protective immunosurveillance. Indeed, inflammatory signals are implicated in both tumour initiation and tumour progression. The major pathways regulating PDAC-associated inflammation are now being explored. Activation of leukocytes, and upregulation of cytokine and chemokine signalling pathways, both have been shown to modulate PDAC progression. Therefore, targeting inflammatory pathways may be of benefit as part of a multi-target approach to PDAC therapy. This review explores the pathways known to modulate inflammation at different stages of tumour development, drawing conclusions on their potential as therapeutic targets in PDAC

Pathogenic Connexin-31 Forms Constitutively Active Hemichannels to Promote Necrotic Cell Death

Mutations in Connexin-31 (Cx31) are associated with multiple human diseases including erythrokeratodermia variabilis (EKV). The molecular action of Cx31 pathogenic mutants remains largely elusive. We report here that expression of EKV pathogenic mutant Cx31R42P induces cell death with necrotic characteristics. Inhibition of hemichannel activity by a connexin hemichannel inhibitor or high extracellular calcium suppresses Cx31R42P-induced cell death. Expression of Cx31R42P induces ER stress resulting in reactive oxygen species (ROS) production, in turn, to regulate gating of Cx31R42P hemichannels and Cx31R42P induced cell death. Moreover, Cx31R42P hemichannels play an important role in mediating ATP release from the cell. In contrast, no hemichannel activity was detected with cells expressing wildtype Cx31. Together, the results suggest that Cx31R42P forms constitutively active hemichannels to promote necrotic cell death. The Cx31R42P active hemichannels are likely resulted by an ER stress mediated ROS overproduction. The study identifies a mechanism of EKV pathogenesis induced by a Cx31 mutant and provides a new avenue for potential treatment strategy of the disease

Chromogranin A (CgA) as Poor Prognostic Factor in Patients with Small Cell Carcinoma of the Cervix: Results of a Retrospective Study of 293 Patients

BACKGROUND: Small cell carcinoma of the cervix (SCCC) is a very rare tumor. Due to its rarity and the long time period, there is a paucity of information pertaining to prognostic factors associated with survival. The objective of this study was to determine whether clinicopathologic finings or immunohistochemical presence of molecular markers predictive of clinical outcome in patients with SCCC. METHODOLOGY AND FINDINGS: We retrospectively reviewed a total of 293 patients with SCCC (47 patients from Cancer Center of Sun Yat-sen University in china, 71 patients from case report of china journal, 175 patients from case report in PubMed database). Of those 293 patients with SCCC, the median survival time is 23 months. The 3-year overall survival rates (OS) and 3-year disease-free survival rates (DFS) for all patients were 34.5% and 31.1%, respectively. Univariate and multivariate analysis showed that FIGO stage (IIb-IV VS I-IIa, Hazard Ratio (HR) = 3.08, 95% confidence interval (CI) of ratio = [2.05, 4.63], P<0.001), tumor mass size (≥ 4 cm VS <4 cm, HR = 2.37, 95% CI = [1.28, 4.36], P = 0.006) and chromogranin A (CgA) (Positive VS Negative, HR = 1.81, 95% CI = [1.12, 2.91], P = 0.015) were predictive of poor prognosis. CgA stained positive was found to be highly predictive of death in early-stage (FIGO I-IIa) patient specifically. CONCLUSIONS: Patients with SCCC have poor prognosis. FIGO stage, tumor mass size and CgA stained positive may act as a surrogate for factors prognostic of survival. CgA may serve as a useful marker in prognostic evaluation for early-stage patients with SCCC