The microfoundations of university-industry interactions

In the last three decades universities have experienced major changes, which have affected both their research objectives and their sources of funding. Universities are increasingly asked to contribute to economic growth by increasing their commercialization and technology transfer efforts. The relationship between university and industry has attracted a great deal of interest because of both the opportunities that can be generated by collaboration and the controversy surrounding universities‘ commercial activities. Previous research has analysed in depth these issue at the level of institutions and universities. Collaborating with industry, however, constitute discretionary behaviour for academics: while literature has examined the role of individual characteristics such as demographics and productivity, aspects related to psychological traits, perceptions and social influence are poorly understood. To address this gap, I employ an interdisciplinary approach to investigate the drivers of university-industry interactions at the level of the individuals. The analysis draws upon data on the characteristics and activities of a sample of academic scientists in different scientific disciplines in Italy and in the UK. The datasets integrate information collected through surveys, as well as data on scientists, department and universities gathered through several secondary sources. Results show that researchers‘ evaluation of potential benefits and costs of collaboration with industry are a major driver of academic engagement. Moreover, this thesis highlights the crucial role of scientists‘ personality in determining academic engagement and entrepreneurship, while putting back into perspective the role of organizational support mechanisms. The role of the academics‘ immediate social context is also assessed, showing that individuals look to their immediate peers for their orientation, both collaboratively via learning as well as competitively via social comparison. Finally, this research informs policy on how to devise more effective strategies to promote university-industry interactions

The engagement gap: Exploring gender differences in University – Industry collaboration activities

AbstractIn recent years, the debate about the marginality of women in academic science has been extended to academics’ engagement with industry and their commercial efforts. Analyzing multi-source data for a large sample of UK physical and engineering scientists and employing a matching technique, this study suggests women academics to engage less and in different ways than their male colleagues of similar status in collaboration activities with industry. We then argue – and empirical assess – these differences can be mitigated by the social context in which women scientists operate, including the presence of women in the local work setting and their wider discipline, and the institutional support for women’s careers in their organization. We explore the implications of these findings for policies to support women’s scientific and technical careers and engagement with industry

Academic Engagement:A review of the literature 2011-2019

We provide a systematic review of the literature on academic engagement from 2011 onwards, which was the cut-off year of a previous review article published in Research Policy. Academic engagement refers to knowledge-related interactions of academic scientists with external organisations. It includes activities such as collaborative research with industry, contract research, consulting and informal ties. We consolidate what is known about the individual, organisational and institutional antecedents of academic engagement, and its consequences for research, commercialisation, and society at large. Our results suggest that individual characteristics associated with academic engagement include being scientifically productive, senior, male, locally trained, and commercially experienced. Academic engagement is also socially conditioned by peer effects and disciplinary characteristics. In terms of consequences, academic engagement is positively associated with academics’ subsequent scientific productivity. We propose new areas of investigation where evidence remains inconclusive, including individual life cycle effects, the role of organisational contexts and incentives, cross-national comparisons, and the impact of academic engagement on the quality of subsequent research as well as the educational, commercial and society-wide impact

Characterization of Detergent-Insoluble Proteins in ALS Indicates a Causal Link between Nitrative Stress and Aggregation in Pathogenesis

BACKGROUND:Amyotrophic lateral sclerosis (ALS) is a progressive and fatal motor neuron disease, and protein aggregation has been proposed as a possible pathogenetic mechanism. However, the aggregate protein constituents are poorly characterized so knowledge on the role of aggregation in pathogenesis is limited. METHODOLOGY/PRINCIPAL FINDINGS:We carried out a proteomic analysis of the protein composition of the insoluble fraction, as a model of protein aggregates, from familial ALS (fALS) mouse model at different disease stages. We identified several proteins enriched in the detergent-insoluble fraction already at a preclinical stage, including intermediate filaments, chaperones and mitochondrial proteins. Aconitase, HSC70 and cyclophilin A were also significantly enriched in the insoluble fraction of spinal cords of ALS patients. Moreover, we found that the majority of proteins in mice and HSP90 in patients were tyrosine-nitrated. We therefore investigated the role of nitrative stress in aggregate formation in fALS-like murine motor neuron-neuroblastoma (NSC-34) cell lines. By inhibiting nitric oxide synthesis the amount of insoluble proteins, particularly aconitase, HSC70, cyclophilin A and SOD1 can be substantially reduced. CONCLUSION/SIGNIFICANCE:Analysis of the insoluble fractions from cellular/mouse models and human tissues revealed novel aggregation-prone proteins and suggests that nitrative stress contribute to protein aggregate formation in ALS

What Stimulates Researchers to Make Their Research Usable? Towards an Openness Approach

Ambiguity surrounding the effect of external engagement on academic research has raised questions about what motivates researchers to collaborate with third parties. We argue that what matters for society is research that can be absorbed by users. We define openness as a willingness by researchers to make research more usable by external partners by responding to external influences in their own research practices. We ask what kinds of characteristics define those researchers who are more open to creating usable knowledge. Our empirical study analyses a sample of 1583 researchers working at the Spanish Council for Scientific Research (CSIC). Results demonstrate that it is personal factors (academic identity and past experience) that determine which researchers have open behaviours. The paper concludes that policies to encourage external engagement should focus on experiences which legitimate and validate knowledge produced through user encounters, both at the academic formation career stage as well as through providing ongoing opportunities to engage with third parties.The data used for this study comes from the IMPACTO project funded by the Spanish Council for Scientific Research - CSIC (Ref. 200410E639). The work also benefited from a mobility grant awarded by Eu-Spri Forum to Julia Olmos Penuela & Paul Benneworth for her visiting research to the Center of Higher Education Policy Studies. Finally, Julia Olmos Penuela also benefited from a post-doctoral grant funded by the Generalitat Valenciana (APOSTD-2014-A-006).Olmos-Peñuela, J.; Benneworth, P.; Castro-Martínez, E. (2015). What Stimulates Researchers to Make Their Research Usable? Towards an Openness Approach. 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Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information

Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Identification of candidate Parkinson disease genes by integrating genome-wide association study, expression, and epigenetic data sets

Importance Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. Objective To investigate what genes and genomic processes underlie the risk of sporadic PD. Design and Setting This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. Main Outcomes and Measures It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role. Results Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. Conclusions and Relevance Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies

Come engage with me: The role of behavioural and attitudinal cohort effects on academic's levels of engagement with industry

Trabajo presentado a la DRUID-DIME Academy Winter Conference 2010 for doctoral students in "Innovation, Knowledge and Entrepreneurship" celebrada en Aalborg (Dinamarca) del 21 al 23 de Enero de 2010.Although academics have considerable autonomy, they work in a highly institutionalized environment and are subject to social expectations and pressures from a range of domains, including their colleagues, their department leadership, their university and members of their discipline. Recent efforts to understand how the behavior of an academic’s peers shapes the nature of academic’s engagement with industry have suggested that there are strong cohort effects, in that the entrepreneurial behavior of one’s colleagues in the same department will encourage academics to become entrepreneurs themselves. This study builds on and extends this work by exploring how both the behaviors and attitudes of colleagues shape an academic’s engagement with industry. In doing so, it separates out the effects of what local peers do from what they think about industry engagement in order to gain better understanding the nature of the social processes that shape an academic’s decision to engage with industry. The analysis builds on a set of rich datasets that cover the industrial engagements of large sample of UK academics from physical and engineering sciences. The paper argues - and empirically demonstrates - that both behavioral and attitudinal cohort effects shape individual engagement behavior and attitudes, yet behavioral effects have a stronger impact than attitudinal effects. It explores the implications of these findings our understanding of cohort effects in professional organizations and for policies designed to encourage academics to engage with industry.Peer Reviewe