Modelling Creativity: Identifying Key Components through a Corpus-Based Approach.
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ABSTRACT:
SUBMITTER: Jordanous A
PROVIDER: S-EPMC5051932 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In prion disease, direct interaction between the cellular prion protein (PrP(C)) and its misfolded disease-associated conformer PrP(Sc) is a crucial, although poorly understood step promoting the formation of nascent PrP(Sc) and prion infectivity. Recently, we hypothesized that three regions of PrP (corresponding to amino acid residues 23-33, 98-110, and 136-158) interacting specifically and robustly with PrP(Sc), likely represent peptidic components of one flank of the prion replicative interface. In this study, we created epitope-tagged mouse PrP(C) molecules in which the PrP sequences 23-33, 98-110, and 136-158 were modified. These novel PrP molecules were individually expressed in the prion-infected neuroblastoma cell line (ScN2a) and the conversion of each mutated mouse PrP(C) substrate to PrP(Sc) compared with that of the epitope-tagged wild-type mouse PrP(C). Mutations within PrP 98-110, substituting all 4 wild-type lysine residues with alanine residues, prevented conversion to PrP(Sc). Furthermore, when residues within PrP 136-140 were collectively scrambled, changed to alanines, or amino acids at positions 136, 137, and 139 individually replaced by alanine, conversion to PrP(Sc) was similarly halted. However, other PrP molecules containing mutations within regions 23-33 and 101-104 were able to readily convert to PrP(Sc). These results suggest that PrP sequence comprising residues 98-110 and 136-140 not only participates in the specific binding interaction between PrP(C) and PrP(Sc), but also in the process leading to conversion of PrP(Sc)-sequestered PrP(C) into its disease-associated form.
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Project description:The use of high-throughput array technology is omnipresent in diverse areas specifically, early diagnosis of disease, discovery of infectious agents, search for biological markers and screening of potential drug candidates. Here, we integrated gene expression data with the network-based approach to identify novel genes that were playing central role in the network through interconnecting to a number of differentially expressed breast cancer genes. The 62 cancerous genes retrieved from the Breast Cancer Gene Database (BCGD) were mapped in the normalized data accessed from Stanford Microarray Database (SMD) to analyze their pattern. Interaction networks for each gene were constructed to understand the biology of the metastasis at systems level. The individual networks were fused together for the detection of interacting hubs, 38 novel genes were found to be deeply intermingled with the central hub node. Gene Ontology studies were made to depict the biology of the hub nodes not alone through gene ranking but by applying the Hyper geometric test with the Benjamini Hochberg False Discovery Rate (FDR) correction method at a significance level of 0.05. Analyzing p-values from the statistical test indicated that most of the novel genes were involved in the same biological function as the disordered genes like signal transducer, transcription regulator, enzyme binding, molecular transducer and receptor signaling protein activity and same pathway as MAPK signaling, Apoptosis, Wnt Signaling, ErbB signaling and Cell Cycle. Lastly, we identified 3 novel genes CHUK, INSR and CREBBP showing high connections with the 12 novel genes reported in literatures as well with the perturbed genes. As a result, these genes can be considered as significant finding in revealing the basis and pathways responsible for breast cancer.
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Project description:BACKGROUND: Residents demonstrate scholarly activity by presenting posters at academic meetings. Although recommendations from national organizations are available, evidence identifying which components are most important is not. OBJECTIVE: To develop and test an evaluation tool to measure the quality of case report posters and identify the specific components most in need of improvement. DESIGN: Faculty evaluators reviewed case report posters and provided on-site feedback to presenters at poster sessions of four annual academic general internal medicine meetings. A newly developed ten-item evaluation form measured poster quality for specific components of content, discussion, and format (5-point Likert scale, 1 = lowest, 5 = highest). MAIN OUTCOME MEASURE(S): Evaluation tool performance, including Cronbach alpha and inter-rater reliability, overall poster scores, differences across meetings and evaluators and specific components of the posters most in need of improvement. RESULTS: Forty-five evaluators from 20 medical institutions reviewed 347 posters. Cronbach's alpha of the evaluation form was 0.84 and inter-rater reliability, Spearman's rho 0.49 (p < 0.001). The median score was 4.1 (Q1 -Q3, 3.7-4.6)(Q1 = 25th, Q3 = 75th percentile). The national meeting median score was higher than the regional meetings (4.4 vs, 4.0, P < 0.001). We found no difference in faculty scores. The following areas were identified as most needing improvement: clearly state learning objectives, tie conclusions to learning objectives, and use appropriate amount of words. CONCLUSIONS: Our evaluation tool provides empirical data to guide trainees as they prepare posters for presentation which may improve poster quality and enhance their scholarly productivity.
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Project description:Antifreeze proteins are important antifreeze materials that have been widely used in industry, including in cryopreservation, de-icing, and food storage applications. However, the quantity of some commercially produced antifreeze proteins is insufficient for large-scale industrial applications. Further, many antifreeze proteins have properties such as cytotoxicity, severely hindering their applications. Understanding the mechanisms underlying the protein-ice interactions and identifying novel antifreeze proteins are, therefore, urgently needed. In this study, to uncover the mechanisms underlying protein-ice interactions and provide an efficient and accurate tool for identifying antifreeze proteins, we assessed various evolutionary features based on position-specific scoring matrices (PSSMs) and evaluated their importance for discriminating of antifreeze and non-antifreeze proteins. We then parsimoniously selected seven key features with the highest importance. We found that the selected features showed opposite tendencies (regarding the conservation of certain amino acids) between antifreeze and non-antifreeze proteins. Five out of the seven features had relatively high contributions to the discrimination of antifreeze and non-antifreeze proteins, as revealed by a principal component analysis, i.e., the conservation of the replacement of Cys, Trp, and Gly in antifreeze proteins by Ala, Met, and Ala, respectively, in the related proteins, and the conservation of the replacement of Arg in non-antifreeze proteins by Ser and Arg in the related proteins. Based on the seven parsimoniously selected key features, we established a classifier using support vector machine, which outperformed the state-of-the-art tools. These results suggest that understanding evolutionary information is crucial to designing accurate automated methods for discriminating antifreeze and non-antifreeze proteins. Our classifier, therefore, is an efficient tool for annotating new proteins with antifreeze functions based on sequence information and can facilitate their application in industry.
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Project description:ObjectiveConverging research suggests that individuals with schizophrenia show a marked impairment in reinforcement learning, particularly in tasks requiring flexibility and adaptation. The problem has been associated with dopamine reward systems. This study explores, for the first time, the characteristics of this impairment and how it is affected by a behavioral intervention-cognitive remediation.MethodUsing computational modelling, 3 reinforcement learning parameters based on the Wisconsin Card Sorting Test (WCST) trial-by-trial performance were estimated: R (reward sensitivity), P (punishment sensitivity), and D (choice consistency). In Study 1 the parameters were compared between a group of individuals with schizophrenia (n = 100) and a healthy control group (n = 50). In Study 2 the effect of cognitive remediation therapy (CRT) on these parameters was assessed in 2 groups of individuals with schizophrenia, one receiving CRT (n = 37) and the other receiving treatment as usual (TAU, n = 34).ResultsIn Study 1 individuals with schizophrenia showed impairment in the R and P parameters compared with healthy controls. Study 2 demonstrated that sensitivity to negative feedback (P) and reward (R) improved in the CRT group after therapy compared with the TAU group. R and P parameter change correlated with WCST outputs. Improvements in R and P after CRT were associated with working memory gains and reduction of negative symptoms, respectively.ConclusionSchizophrenia reinforcement learning difficulties negatively influence performance in shift learning tasks. CRT can improve sensitivity to reward and punishment. Identifying parameters that show change may be useful in experimental medicine studies to identify cognitive domains susceptible to improvement.
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