Mutations in <em>GRHL2</em> result in an autosomal-recessive ectodermal dysplasia syndrome

Grainyhead-like 2, encoded by GRHL2, is a member of a highly conserved family of transcription factors that play essential roles during epithelial development. Haploinsufficiency for GRHL2 has been implicated in autosomal-dominant deafness, but mutations have not yet been associated with any skin pathology. We investigated two unrelated Kuwaiti families in which a total of six individuals have had lifelong ectodermal defects. The clinical features comprised nail dystrophy or nail loss, marginal palmoplantar keratoderma, hypodontia, enamel hypoplasia, oral hyperpigmentation, and dysphagia. In addition, three individuals had sensorineural deafness, and three had bronchial asthma. Taken together, the features were consistent with an unusual autosomal-recessive ectodermal dysplasia syndrome. Because of consanguinity in both families, we used whole-exome sequencing to search for novel homozygous DNA variants and found GRHL2 mutations common to both families: affected subjects in one family were homozygous for c.1192T>C (p.Tyr398His) in exon 9, and subjects in the other family were homozygous for c.1445T>A (p.Ile482Lys) in exon 11. Immortalized keratinocytes (p.Ile482Lys) showed altered cell morphology, impaired tight junctions, adhesion defects, and cytoplasmic translocation of GRHL2. Whole-skin transcriptomic analysis (p.Ile482Lys) disclosed changes in genes implicated in networks of cell-cell and cell-matrix adhesion. Our clinical findings of an autosomal-recessive ectodermal dysplasia syndrome provide insight into the role of GRHL2 in skin development, homeostasis, and human disease

Considerations on the Castrop formula for calculation of intraocular lens power

Background: To explain the concept of the Castrop lens power calculation formula and show the application and results from a large dataset compared to classical formulae. Methods: The Castrop vergence formula is based on a pseudophakic model eye with 4 refractive surfaces. This was compared against the SRKT, Hoffer-Q, Holladay1, simplified Haigis with 1 optimized constant and Haigis formula with 3 optimized constants. A large dataset of preoperative biometric values, lens power data and postoperative refraction data was split into training and test sets. The training data were used for formula constant optimization, and the test data for cross-validation. Constant optimization was performed for all formulae using nonlinear optimization, minimising root mean squared prediction error. Results: The constants for all formulae were derived with the Levenberg-Marquardt algorithm. Applying these constants to the test data, the Castrop formula showed a slightly better performance compared to the classical formulae in terms of prediction error and absolute prediction error. Using the Castrop formula, the standard deviation of the prediction error was lowest at 0.45 dpt, and 95% of all eyes in the test data were within the limit of 0.9 dpt of prediction error. Conclusion: The calculation concept of the Castrop formula and one potential option for optimization of the 3 Castrop formula constants (C, H, and R) are presented. In a large dataset of 1452 data points the performance of the Castrop formula was slightly superior to the respective results of the classical formulae such as SRKT, Hoffer-Q, Holladay1 or Haigis

A Novel Method for Visually Mapping Intellectual Property Risks and Uncertainties in Evolving Innovation Ecosystems: A Design Science Research Approach for the COVID-19 Pandemic

Prior management science literature proposes different visual methods for mapping ecosystems. These methods, however, largely lack an effective approach to visualizing intellectual property (IP) related risks and uncertainties appearing among stakeholders as the innovation ecosystem evolves. Using the design science research methodology, we develop a novel method that visualizes loci of IP risks and uncertainties, as well as dynamics of IP ownership and usage in evolving innovation ecosystems. We demonstrate and evaluate the effectiveness of the new method in uncovering IP related risks and uncertainties by presenting results from applying the method to the innovation ecosystem for crisis-critical products during the COVID-19 pandemic. The currently ongoing pandemic has caused structural changes to that innovation ecosystem with new relationships being formed between incumbent manufacturers and new entrants that have rushed into that innovation ecosystem to support the upscaling of manufacturing capacities. This article contributes to the literature on visual methods for innovation ecosystems and provides a new method for researchers, practitioners, and policy makers to identify IP related risks and uncertainties that can arise when innovation ecosystems undergo structural changes. The method allows researchers to formulate and test new theories, as well as practitioners and policy makers to develop strategies to anticipate and mitigate IP risks and uncertainties

Crisis-Critical Intellectual Property: Findings from the COVID-19 Pandemic

Within national and international innovation systems a pandemic calls for large-scale action by many actors across sectors, to mobilise resources, developing and manufacturing Crisis-Critical Products (CC-Products) efficiently and in the huge quantities needed. Nowadays, this also includes digital innovations from complex epidemiological models, AI, to open data platforms for prevention, diagnostic and treatment. Amongst the many challenges during a pandemic, innovation and manufacturing stakeholders find themselves engaged in new relationships, and are likely to face intellectual property (IP) related challenges. This paper adopts an IP perspective on the COVID-19 pandemic to identify pandemic related IP considerations and IP challenges. The focus is on challenges related to research, development and urgent upscaling of capacity to manufacture CC-Products in the huge volumes suddenly in demand. Its purpose is to provide a structure for steering clear of IP challenges to avoid delays in fighting a pandemic. We identify 4 stakeholder groups concerned with IP challenges: (i) governments, (ii) organisations owning existing Crisis-Critical IP, described as incumbents in Crisis-Critical Sectors (CC-Sectors), (iii) manufacturing firms from other sectors normally not producing CC-Products suddenly rushing into CC-Sectors to support the manufacturing of CC-Products (new entrants), and (iv) voluntary grassroot initiatives that are formed during a pandemic. This paper discusses IP challenges related to the development and manufacturing of technologies and products for (i) prevention (of spread), (ii) diagnosis of infected patients and (iii) the development of treatments. We offer an initial discussion of potential response measures to reduce IP associated risks among industrial stakeholders during a pandemic

Identifying Crisis-Critical Intellectual Property Challenges during the Covid-19 Pandemic: A scenario analysis and conceptual extrapolation of innovation ecosystem dynamics using a visual mapping approach

The Covid-19 pandemic exposed firms, organisations and their respective supply chains which are directly involved in the manufacturing of products that are critical to alleviating the effects of the health crisis, collectively referred to as the Crisis-Critical Sector,to unprecedented challenges. Firms from other sectors, such as automotive, luxury and home appliances, have rushed into the Crisis-Critical Sector in order to support the effort to upscale incumbent manufacturing capacities, thereby introducing Intellectual Property (IP)related dynamics and challenges. We apply an innovation ecosystem perspective on the Crisis-Critical Sector and adopt a novel visual mapping approach to identify IP associated challenges and IP specific dynamic developments during and potentially beyond the crisis.In this paper, we add methodologically by devising and testing a visual approach to capturing IP related dynamics in evolving innovation ecosystems and contribute to literature on IP management in the open innovation context by proposing paraground IP as a novel IP type.Finally, we also deduce managerial implications for IP management practitioners at both incumbent firms and new entrants for navigating innovation ecosystems subject to crisis-induced dynamic shifts