Multiple Museum Construct Motivators: a Multivariable Analysis with Repertory Grid Analysis (RGA) Approach

This paper aims to present and highlight the importance of factors resulting from Repertory Grid Analysis (R.G.A.). Strategic planning management issues concerning the management of museum audience are studied. A short description of the R.G.A. and the corresponding literature is cited, and an empirical application of the aforementioned method in a sample of 128 university students, takes place. The application of RGA produced 1345 interpretation models (constructs) which were coded and analyzed with three multivariable statistical techniques. The paper clearly demonstrates the importance of the analysis of constructs in relation to the management (local authorities or private institutions) suggestions that concern the museums of a specific area. Also, it contributes to the evolution of a new research area for the Destination Marketing Management with emphasis on Place design practices and development. Cultural offers and special managerial suggestions about particular groups of museums (strategic museum groups), are also discussed

Multiple Museum Construct Motivators: a Multivariable Analysis with Repertory Grid Analysis (RGA) Approach

This paper aims to present and highlight the importance of factors resulting from Repertory Grid Analysis (R.G.A.). Strategic planning management issues concerning the management of museum audience are studied. A short description of the R.G.A. and the corresponding literature is cited, and an empirical application of the aforementioned method in a sample of 128 university students, takes place. The application of RGA produced 1345 interpretation models (constructs) which were coded and analyzed with three multivariable statistical techniques. The paper clearly demonstrates the importance of the analysis of constructs in relation to the management (local authorities or private institutions) suggestions that concern the museums of a specific area. Also, it contributes to the evolution of a new research area for the Destination Marketing Management with emphasis on Place design practices and development. Cultural offers and special managerial suggestions about particular groups of museums (strategic museum groups), are also discussed

The Role of Exporters’ Emotional Intelligence in Building Foreign Customer Relationships

Despite the critical importance of emotional intelligence in effectively interacting with other people, its role has been overlooked in scholarly research on cross-border interorganizational relationships. Drawing on Emotion Regulation Theory, we propose a model that conceptualizes links among exporters’ emotional intelligence, key behavioral dimensions characterizing the atmosphere of the relationship with import buyers, and the resulting relational performance. We test the model with data collected from 262 Greek exporters using structural equation modeling. The results indicate that higher levels of exporter emotional intelligence enhances communication and social bonding with the importer, while diminishing distance and conflict in their working relationship. Relational performance is positively influenced by communication and social bonding, but negatively affected by distance and conflict. The results also reveal the moderating effect of both opportunism and interpartner incompatibility on the association between the exporter’s emotional intelligence and the behavioral atmosphere of the relationship with import buyers

Functional imaging and circulating biomarkers of response to regorafenib in treatment-refractory metastatic colorectal cancer patients in a prospective phase II study

Objective: Regorafenib demonstrated efficacy in patients with metastatic colorectal cancer (mCRC). Lack of predictive biomarkers, potential toxicities and cost-effectiveness concerns highlight the unmet need for better patient selection. Design: Patients with RAS mutant mCRC with biopsiable metastases were enrolled in this phase II trial. Dynamic contrast-enhanced (DCE) MRI was acquired pretreatment and at day 15 post-treatment. Median values of volume transfer constant (Ktrans), enhancing fraction (EF) and their product KEF (summarised median values of Ktrans× EF) were generated. Circulating tumour (ct) DNA was collected monthly until progressive disease and tested for clonal RAS mutations by digital-droplet PCR. Tumour vasculature (CD-31) was scored by immunohistochemistry on 70 sequential tissue biopsies. Results: Twenty-seven patients with paired DCE-MRI scans were analysed. Median KEF decrease was 58.2%. Of the 23 patients with outcome data, >70% drop in KEF (6/23) was associated with higher disease control rate (p=0.048) measured by RECIST V. 1.1 at 2 months, improved progression-free survival (PFS) (HR 0.16 (95% CI 0.04 to 0.72), p=0.02), 4-month PFS (66.7% vs 23.5%) and overall survival (OS) (HR 0.08 (95% CI 0.01 to 0.63), p=0.02). KEF drop correlated with CD-31 reduction in sequential tissue biopsies (p=0.04). RAS mutant clones decay in ctDNA after 8 weeks of treatment was associated with better PFS (HR 0.21 (95% CI 0.06 to 0.71), p=0.01) and OS (HR 0.28 (95% CI 0.07–1.04), p=0.06). Conclusions: Combining DCE-MRI and ctDNA predicts duration of anti-angiogenic response to regorafenib and may improve patient management with potential health/economic implications

Addressing the clinical unmet needs in primary Sjögren's Syndrome through the sharing, harmonization and federated analysis of 21 European cohorts

For many decades, the clinical unmet needs of primary Sjögren's Syndrome (pSS) have been left unresolved due to the rareness of the disease and the complexity of the underlying pathogenic mechanisms, including the pSS-associated lymphomagenesis process. Here, we present the HarmonicSS cloud-computing exemplar which offers beyond the state-of-the-art data analytics services to address the pSS clinical unmet needs, including the development of lymphoma classification models and the identification of biomarkers for lymphomagenesis. The users of the platform have been able to successfully interlink, curate, and harmonize 21 regional, national, and international European cohorts of 7,551 pSS patients with respect to the ethical and legal issues for data sharing. Federated AI algorithms were trained across the harmonized databases, with reduced execution time complexity, yielding robust lymphoma classification models with 85% accuracy, 81.25% sensitivity, 85.4% specificity along with 5 biomarkers for lymphoma development. To our knowledge, this is the first GDPR compliant platform that provides federated AI services to address the pSS clinical unmet needs. © 2022 The Author(s

Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal.

The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with >10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance

Genomic and Transcriptomic Determinants of Therapy Resistance and Immune Landscape Evolution during Anti-EGFR Treatment in Colorectal Cancer

Despite biomarker stratification, the anti-EGFR antibody cetuximab is only effective against a subgroup of colorectal cancers (CRCs). This genomic and transcriptomic analysis of the cetuximab resistance landscape in 35 RAS wild-type CRCs identified associations of NF1 and non-canonical RAS/RAF aberrations with primary resistance and validated transcriptomic CRC subtypes as non-genetic predictors of benefit. Sixty-four percent of biopsies with acquired resistance harbored no genetic resistance drivers. Most of these had switched from a cetuximab-sensitive transcriptomic subtype at baseline to a fibroblast- and growth factor-rich subtype at progression. Fibroblast-supernatant conferred cetuximab resistance in vitro, confirming a major role for non-genetic resistance through stromal remodeling. Cetuximab treatment increased cytotoxic immune infiltrates and PD-L1 and LAG3 immune checkpoint expression, potentially providing opportunities to treat cetuximab-resistant CRCs with immunotherapy

Genomic and Transcriptomic Determinants of Therapy Resistance and Immune Landscape Evolution during Anti-EGFR Treatment in Colorectal Cancer.

Despite biomarker stratification, the anti-EGFR antibody cetuximab is only effective against a subgroup of colorectal cancers (CRCs). This genomic and transcriptomic analysis of the cetuximab resistance landscape in 35 RAS wild-type CRCs identified associations of NF1 and non-canonical RAS/RAF aberrations with primary resistance and validated transcriptomic CRC subtypes as non-genetic predictors of benefit. Sixty-four percent of biopsies with acquired resistance harbored no genetic resistance drivers. Most of these had switched from a cetuximab-sensitive transcriptomic subtype at baseline to a fibroblast- and growth factor-rich subtype at progression. Fibroblast-supernatant conferred cetuximab resistance in vitro, confirming a major role for non-genetic resistance through stromal remodeling. Cetuximab treatment increased cytotoxic immune infiltrates and PD-L1 and LAG3 immune checkpoint expression, potentially providing opportunities to treat cetuximab-resistant CRCs with immunotherapy

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease