Gearing Towards Omnichannel Grocery Retail Through Business Model Innovation

Technological innovations and the advent of digitalization have led retail business into one of its biggest transformations of all time. Consumer behaviour has changed rapidly and the customers are ever more powerful, demanding, tech-savvy and moving on various plat-forms. These attributes will continue to drive the development and robustly restructure the architecture of value creation in the retail business. The largest retail category, grocery yet awaits for a real disruption, but the signals for major change are already on the horizon. The first wave of online grocery retail was introduced in the mid 1990’s and it throve until millennium. Many overreactions, heavy investments and the burst IT-bubble almost stag-nated the whole industry for a long period of time. The second wave started with a venge-ance around 2010. Some research was carried out during the first wave from a single-viewpoint of online grocery retail, but without a comprehensive approach to online-offline business model integration. Now the accelerating growth of e-business has initiated an increased interest to examine the transformation from traditional business models towards e-business models and their integration on the companies’ traditional business models. This research strove to examine how can we recognize and analyze how digitalization and online channels are affecting the business models of grocery retail, by using business mod-el canvas as an analysis tool. Furthermore business model innovation and omnichannel retail were presented and suggested as potential solutions for these changes. 21 experts in online grocery industry were being interviewed. The thoughts of the informants were being qualitatively analysed by using an analysis tool called the business model canvas. The aim of this research was to portray a holistic view on the Omnichannel grocery retail business model, and the value chain, in which the case company Arina along with its partners are operating. The key conclusions exhibited that online grocery retail business model is not an alterna-tive model nor a substitute for the traditional grocery retail business model, though all of the business model elements are to some extent affected by it, but rather a complementary business model that should be integrated into the prevailing, conventional grocery retail business model. A set of business model elements, such as value proposition and distribu-tion channels were recognized as the most important ones and sources of innovation within these components were being illustrated. Segments for online grocery retail were empiri-cally established as polarized niche markets in contrast of the segmented mass-market of the conventional grocery retail. Business model innovation was proven to be a considera-ble method and a conceptual framework, by which to come across with new value proposi-tions that create competitive advantage for the company in the contemporary, changing business environment. Arina as a retailer can be considered as a industry model innovator, since it has initiated an entire industry in its market area, where other players have later on embarked on, and in which the contributors of the value chain, such as Posti depend on it to a great extent. Consumer behaviour clearly affects and appears everywhere in the digi-talized grocery trade and it drives customers to multiple platforms where retailers need to be present. Omnichannel retail business model was suggested to be the solution, in which the new technologies are being utilized, contemporary consumer behaviour is embedded in decision-making and all of the segments and their value propositions are being served seamlessly across the channels.

Targeting oncogenic signaling proteins : new insights using a FRET-based chemical biology approach

Cancer affects more than 20 million people each year and this rate is increasing globally. The Ras/MAPK-pathway is one of the best-studied cancer signaling pathways. Ras proteins are mutated in almost 20% of all human cancers and despite numerous efforts, no effective therapy that specifically targets Ras is available to date. It is now well established that Ras proteins laterally segregate on the plasma membrane into transient nanoscale signaling complexes called nanoclusters. These Ras nanoclusters are essential for the high-fidelity signal transmission. Disruption of nanoclustering leads to reduction in Ras activity and signaling, therefore targeting nanoclusters opens up important new therapeutic possibilities in cancer. This work describes three different studies exploring the idea of membrane protein nanoclusters as novel anti-cancer drug targets. It is focused on the design and implementation of a simple, cell-based Förster Resonance Energy Transfer (FRET)-biosensor screening platform to identify compounds that affect Ras membrane organization and nanoclustering. Chemical libraries from different sources were tested and a number of potential hit molecules were validated on full-length oncogenic proteins using a combination of imaging, biochemical and transformation assays. In the first study, a small chemical library was screened using H-ras derived FRET-biosensors. Surprisingly from this screen, commonly used protein synthesis inhibitors (PSIs) were found to specifically increase H-ras nanoclustering and downstream signalling in a H-ras dependent manner. Using a representative PSI, increase in H-ras activity was shown to induce cancer stem cell (CSC)-enriched mammosphere formation and tumor growth of breast cancer cells. Moreover, PSIs do not increase K-ras nanoclustering, making this screening approach suitable for identifying Ras isoform-specific inhibitors. In the second study, a nanoncluster-directed screen using both H- and K-ras derived FRET biosensors identified CSC inhibitor salinomycin to specifically inhibit K-ras nanocluster organization and downstream signaling. A K-ras nanoclusteringassociated gene signature was established that predicts the drug sensitivity of cancer cells to CSC inhibitors. Interestingly, almost 8% of patient tumor samples in the The Cancer Genome Atlas (TCGA) database had the above gene signature and were associated with a significantly higher mortality. From this mechanistic insight, an additional microbial metabolite screen on H- and K-ras biosensors identified ophiobolin A and conglobatin A to specifically affect K-ras nanoclustering and to act as potential breast CSC inhibitors. In the third study, the Ras FRET-biosensor principle was used to investigate membrane anchorage and nanoclustering of myristoylated proteins such as heterotrimeric G-proteins, Yes- and Src-kinases. Furthermore, Yes-biosensor was validated to be a suitable platform for performing chemical and genetic screens to identify myristoylation inhibitors. The results of this thesis demonstrate the potential of the Ras-derived FRETbiosensor platform to differentiate and identify Ras-isoform specfic inhibitors. The results also highlight that most of the inhibitors identified predominantly perturb Ras subcellular distribution and membrane organization through some novel and yet unknown mechanisms. The results give new insights into the role of Ras nanoclusters as promising new molecular targets in cancer and in stem cells.

Molecular patterns behind immunological and metabolic alterations in lysinuric protein intolerance

Lysinuric protein intolerance (LPI) is a recessively inherited disorder characterised by reduced plasma and increased urinary levels of cationic amino acids (CAAs), protein malnutrition, growth failure and hyperlipidemia. Some patients develop severe immunological, renal and pulmonary complications. All Finnish patients share the same LPIFin mutation in the SLC7A7 gene that encodes CAA transporter y+LAT1. The aim of this study was to examine molecular factors contributing to the various symptoms, systemic metabolic and lipid profiles, and innate immune responses in LPI. The transcriptomes, metabolomes and lipidomes were analysed in whole-blood cells and plasma using RNA microarrays and gas or liquid chromatography-mass spectrometry techniques, respectively. Toll-like receptor (TLR) signalling in monocyte-derived macrophages exposed to pathogens was scrutinised using qRT-PCR and the Luminex technology. Altered levels of transcripts participating in amino acid transport, immune responses, apoptosis and pathways of hepatic and renal metabolism were identified in the LPI whole-blood cells. The patients had increased non-essential amino acid, triacylglycerol and fatty acid levels, and decreased plasma levels of phosphatidylcholines and practically all essential amino acids. In addition, elevated plasma levels of eight metabolites, long-chain triacylglycerols, two chemoattractant chemokines and nitric oxide correlated with the reduced glomerular function in the patients with kidney disease. Accordingly, it can be hypothesised that the patients have increased autophagy, inflammation, oxidative stress and apoptosis, leading to hepatic steatosis, uremic toxicity and altered intestinal microbe metabolism. Furthermore, the LPI macrophages showed disruption in the TLR2/1, TLR4 and TLR9 pathways, suggesting innate immune dysfunctions with an excessive response to bacterial infections but a deficient viral DNA response.