Genetic modulation during thymocyte development an integrative approach based on microarray meta-analysis

2015 ◽  
Author(s):  
Cintia C. Palu ◽  
Leandra Linhares-Lacerda ◽  
Wilson Savino ◽  
Marcelo Ribeiro-Alves
Keyword(s):  
Meta Analysis ◽  
Integrative Approach ◽  
Thymocyte Development ◽  
Genetic Modulation

scholarly journals Integrative transcriptomics reveals sexually dimorphic microRNA control of the cholinergic/neurokine interface in schizophrenia and bipolar disorder

2019 ◽  
Author(s):  
Sebastian Lobentanzer ◽  
Geula Hanin ◽  
Jochen Klein ◽  
Hermona Soreq
Keyword(s):  
Bipolar Disorder ◽  
Rna Sequencing ◽  
Large Scale ◽  
Meta Analysis ◽  
Integrative Approach ◽  
P Value ◽  
Sexually Dimorphic ◽  
Sequencing Data ◽  
Sexual Dimorphisms ◽  
Human Male

SummaryRNA-sequencing analyses are often limited to identifying lowest p-value transcripts, which does not address polygenic phenomena. To overcome this limitation, we developed an integrative approach that combines large scale transcriptomic meta-analysis of patient brain tissues with single-cell sequencing data of CNS neurons, short RNA-sequencing of human male- and female-originated cell lines, and connectomics of transcription factor- and microRNA-interactions with perturbed transcripts. We used this pipeline to analyze cortical transcripts of schizophrenia and bipolar disorder patients. While these pathologies show massive transcriptional parallels, their clinically well-known sexual dimorphisms remain unexplained. Our method explicates the differences between afflicted men and women, and identifies disease-affected pathways of cholinergic transmission and gp130-family neurokine controllers of immune function, interlinked by microRNAs. This approach may open new perspectives for seeking biomarkers and therapeutic targets, also in other transmitter systems and diseases.

scholarly journals Meta-Analysis: An integrative approach to Islamic values in biology learning

2021 ◽  
Vol 9 (2) ◽  
pp. 75
Author(s):  
Viina Miratun Nisa ◽  
Ria Yulia Gloria ◽  
Mujib Ubaidillah
Keyword(s):  
Meta Analysis ◽  
Integrative Approach ◽  
Biology Learning ◽  
Islamic Values

scholarly journals The Interplay of Objectivity and Subjectivity in Landscape Character Assessment: Qualitative and Quantitative Approaches and Challenges

Land ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 53
Author(s):  
Theano S. Terkenli ◽  
Aikaterini Gkoltsiou ◽  
Dimitris Kavroudakis
Keyword(s):  
Qualitative Data ◽  
Meta Analysis ◽  
Integrative Approach ◽  
Extensive Literature ◽  
Time Space ◽  
Qualitative Variables ◽  
Character Assessment ◽  
Landscape Character ◽  
Landscape Types ◽  
Analytical Tools

Landscape character assessment (LCA) methods have been used in the past few decades to analyze, classify, and map landscape types, using objective and subjective approaches, with the aid of both quantitative and qualitative data. This paper addresses and critically evaluates the compromises and ways in which contemporary LCA methodologies employ (or profess they employ) objective versus subjective and quantitative versus qualitative data and analytical tools, in their conceptualization and implementation. It begins with an extensive literature review of the ways in which the objective/subjective and the quantitative/qualitative variables interweave in currently practiced or proposed versions of LCA. With the aid of meta-analysis, the paper traces and discusses the recent evolution, methods, concessions, and risks of such endeavors, and develops an integrative conceptual model for critical assessment, analysis, and negotiation of the interplay between objective–subjective and quantitative–qualitative constituent parts of existing LCA methodologies. It concludes by pointing to pitfalls and prospects, in the broader attempt towards a more concerted, integrative approach to LCA development and practice, both appropriate to its challenges and adaptable to time–space–culture–discipline landscape particularities and means of implementation.

scholarly journals Evaluation of the Effectiveness of Herbal Components Based on Their Regulatory Signature on Carcinogenic Cancer Cells

Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3139
Author(s):  
Fazileh Esmaeili ◽  
Tahmineh Lohrasebi ◽  
Manijeh Mohammadi-Dehcheshmeh ◽  
Esmaeil Ebrahimie
Keyword(s):  
Machine Learning ◽  
Transcription Factors ◽  
Drug Discovery ◽  
Cancer Cells ◽  
Meta Analysis ◽  
Herbal Extract ◽  
Integrative Approach ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Herbal Components

Predicting cancer cells’ response to a plant-derived agent is critical for the drug discovery process. Recently transcriptomes advancements have provided an opportunity to identify regulatory signatures to predict drug activity. Here in this study, a combination of meta-analysis and machine learning models have been used to determine regulatory signatures focusing on differentially expressed transcription factors (TFs) of herbal components on cancer cells. In order to increase the size of the dataset, six datasets were combined in a meta-analysis from studies that had evaluated the gene expression in cancer cell lines before and after herbal extract treatments. Then, categorical feature analysis based on the machine learning methods was applied to examine transcription factors in order to find the best signature/pattern capable of discriminating between control and treated groups. It was found that this integrative approach could recognize the combination of TFs as predictive biomarkers. It was observed that the random forest (RF) model produced the best combination rules, including AIP/TFE3/VGLL4/ID1 and AIP/ZNF7/DXO with the highest modulating capacity. As the RF algorithm combines the output of many trees to set up an ultimate model, its predictive rules are more accurate and reproducible than other trees. The discovered regulatory signature suggests an effective procedure to figure out the efficacy of investigational herbal compounds on particular cells in the drug discovery process.

Working with addiction: an intercultural-integrative approach to substance dependency during a seven-year delivery of a psychotherapy service in North London

2020 ◽  
Vol 20 (2) ◽  
pp. 135-146
Author(s):  
Antony Sigalas
Keyword(s):  
Clinical Practice ◽  
Design Methodology ◽  
Meta Analysis ◽  
Third Sector ◽  
Statistical Information ◽  
Integrative Model ◽  
Integrative Approach ◽  
Dimensional Approach ◽  
Content Type ◽  
Case Vignettes

Purpose This paper aims to focus on a meta-analysis of an applied integrative model of clinical practice at community level in a third-sector organisation. The psychotherapeutic work was exclusively aimed at those who struggled with their abstinence from their substance use. Design/methodology/approach The model adapted to the needs of those who accessed the service, combined culturally sensitive psychoanalytic, systemic and relational frameworks. Findings The analysis reflects how such a multi-dimensional approach may be used to address the experience of self-destructiveness in the context of inferiorisation. This paper also presents some statistical information as well as three case vignettes. Originality/value The analysis reflects how such a multi-dimensional approach may be used to address the experience of self-destructiveness in the context of inferiorisation.

Identifying and modeling the antecedents of counterproductive knowledge behavior: a three-study analysis

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yasha Afshar-Jalili ◽  
Helena D. Cooper-Thomas ◽  
Mahshad Fatholahian
Keyword(s):  
Design Methodology ◽  
Meta Analysis ◽  
Integrative Approach ◽  
Relative Role ◽  
Content Type ◽  
Aggregate Information ◽  
The Matrix ◽  
Strength Of Effects ◽  
Qualitative Literature

Purpose This study aims to identify and classify the range of antecedents of counterproductive knowledge behavior (CKB) to provide a better understanding of their implications for addressing CKB. Design/methodology/approach The study includes three studies. Using meta-analysis (Study 1) and meta-synthesis (Study 2), the authors reviewed extant primary quantitative and qualitative studies to aggregate information on the antecedents of CKB identified to date. In Study 3, these antecedents were modeled schematically by using the matrix of cross-impact multiplications (MICMAC) analysis. Findings The meta-analysis and meta-synthesis (Studies 1 and 2) yielded 28 antecedents of CKB. These were categorized into five groups of characteristics, relating to the workplace, leadership, interpersonal, individual differences and knowledge. Then, in Study 3, the antecedents were categorized according to their interrelatedness and strength of effects (using four quadrants comprising autonomous, dependence, driving and linkage factors). Originality/value This study takes an integrative approach to the CKB literature, both by aggregating underlying constructs (knowledge hoarding, hiding, etc.) and in aggregating quantitative and qualitative literature. This prevents silos and integrates knowledge across a range of CKB studies. Besides, the authors reveal the relative role of antecedents by modeling them.

scholarly journals Trans-ethnic eQTL meta-analysis of human brain reveals regulatory architecture and candidate causal variants for brain-related traits

2021 ◽  
Author(s):  
Gabriel Hoffman ◽  
Biao Zeng ◽  
Jaroslav Bendl ◽  
Roman Kosoy ◽  
John Fullard ◽  
...  
Keyword(s):  
Sample Size ◽  
Fine Mapping ◽  
Large Scale ◽  
Association Studies ◽  
Meta Analysis ◽  
Integrative Approach ◽  
Effective Sample Size ◽  
Strong Linkage Disequilibrium ◽  
Genome Wide Association Studies ◽  
Causal Variants

Abstract While large-scale genome-wide association studies (GWAS) have identified hundreds of loci associated with neuropsychiatric and neurodegenerative traits, identifying the variants, genes and molecular mechanisms underlying these traits remains challenging. Integrating GWAS results with expression quantitative trait loci (eQTLs) and identifying shared genetic architecture has been widely adopted to nominate genes and candidate causal variants. However, this integrative approach is often limited by the sample size, the statistical power of the eQTL dataset, and the strong linkage disequilibrium between variants. Here we developed the multivariate multiple QTL (mmQTL) approach and applied it to perform a large-scale trans-ethnic eQTL meta-analysis to increase power and fine-mapping resolution. Importantly, this method also increases power to identify conditional eQTL’s that are enriched for cell type specific regulatory effects. Analysis of 3,188 RNA-seq samples from 2,029 donors, including 444 non-European individuals, yields an effective sample size of 2,974, which is substantially larger than previous brain eQTL efforts. Joint statistical fine-mapping of eQTL and GWAS identified 301 variant-trait pairs for 23 brain-related traits driven by 189 unique candidate causal variants for 179 unique genes. This integrative analysis identifies novel disease genes and elucidates potential regulatory mechanisms for genes underlying schizophrenia, bipolar disorder and Alzheimer’s disease.

scholarly journals The effectiveness of workplace coaching: a meta-analysis of contemporary psychologically informed coaching approaches

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Qing Wang ◽  
Yi-Ling Lai ◽  
Xiaobo Xu ◽  
Almuth McDowall
Keyword(s):  
Meta Analysis ◽  
Full Range ◽  
Self Regulation ◽  
Well Being ◽  
Cognitive Behavioral ◽  
Learning Performance ◽  
Integrative Approach ◽  
Psychological Well Being ◽  
Content Type ◽  
Significant Difference

PurposeThe authors examine psychologically informed coaching approaches for evidence-based work-applied management through a meta-analysis. This analysis synthesized previous empirical coaching research evidence on cognitive behavioral and positive psychology frameworks regarding a range of workplace outcomes, including learning, performance and psychological well-being.Design/methodology/approachThe authors undertook a systematic literature search to identify primary studies (k = 20, n = 957), then conducted a meta-analysis with robust variance estimates (RVEs) to test the overall effect size and the effects of each moderator.FindingsThe results confirm that psychologically informed coaching approaches facilitated effective work-related outcomes, particularly on goal attainment (g = 1.29) and self-efficacy (g = 0.59). Besides, these identified coaching frameworks generated a greater impact on objective work performance rated by others (e.g. 360 feedback) than on coachees' self-reported performance. Moreover, a cognitive behavioral-oriented coaching process stimulated individuals' internal self-regulation and awareness to promote work satisfaction and facilitated sustainable changes. Yet, there was no statistically significant difference between popular and commonly used coaching approaches. Instead, an integrative coaching approach that combines different frameworks facilitated better outcomes (g = 0.71), including coachees' psychological well-being.Practical implicationsEffective coaching activities should integrate cognitive coping (e.g. combining cognitive behavioral and solution-focused technique), positive individual traits (i.e. strength-based approach) and contextual factors for an integrative approach to address the full range of coachees' values, motivators and organizational resources for yielding positive outcomes.Originality/valueBuilding on previous meta-analyses and reviews of coaching, this synthesis offers a new insight into effective mechanisms to facilitate desired coaching results. Frameworks grounded in psychotherapy and positive appear most prominent in the literature, yet an integrative approach appears most effective.

scholarly journals Trans-ethnic eQTL meta-analysis of human brain reveals regulatory architecture and candidate causal variants for brain-related traits

2021 ◽  
Author(s):  
Biao Zeng ◽  
Jaroslav Bendl ◽  
Roman Kosoy ◽  
John F. Fullard ◽  
Gabriel E. Hoffman ◽  
...  
Keyword(s):  
Sample Size ◽  
Fine Mapping ◽  
Large Scale ◽  
Association Studies ◽  
Meta Analysis ◽  
Integrative Approach ◽  
Effective Sample Size ◽  
Strong Linkage Disequilibrium ◽  
Genome Wide Association Studies ◽  
Causal Variants

AbstractWhile large-scale genome-wide association studies (GWAS) have identified hundreds of loci associated with neuropsychiatric and neurodegenerative traits, identifying the variants, genes and molecular mechanisms underlying these traits remains challenging. Integrating GWAS results with expression quantitative trait loci (eQTLs) and identifying shared genetic architecture has been widely adopted to nominate genes and candidate causal variants. However, this integrative approach is often limited by the sample size, the statistical power of the eQTL dataset, and the strong linkage disequilibrium between variants. Here we developed the multivariate multiple QTL (mmQTL) approach and applied it to perform a large-scale trans-ethnic eQTL meta-analysis to increase power and fine-mapping resolution. Importantly, this method also increases power to identify conditional eQTL’s that are enriched for cell type specific regulatory effects. Analysis of 3,188 RNA-seq samples from 2,029 donors, including 444 non-European individuals, yields an effective sample size of 2,974, which is substantially larger than previous brain eQTL efforts. Joint statistical fine-mapping of eQTL and GWAS identified 301 variant-trait pairs for 23 brain-related traits driven by 189 unique candidate causal variants for 179 unique genes. This integrative analysis identifies novel disease genes and elucidates potential regulatory mechanisms for genes underlying schizophrenia, bipolar disorder and Alzheimer’s disease.

Sign in / Sign up

Export Citation Format

Share Document