Integrating intellectual property and sustainable business models: The SBM-IP canvas

Companies attempt to address global sustainability challenges through innovating products, services, and business models. This paper focuses on sustainable business model (SBM) innovations as a way to systemically transform businesses towards sustainability. It has been widely recognized that strategic approaches to using intellectual property (IP) need to be aligned with business model innovation for commercial success. Here we suggest that IP, aligned with SBMs, can also be used to create not only commercial, but also societal and environmental impact. Knowledge about how to best align IP with SBMs to drive sustainability transitions remains limited. We address this gap by developing an SBM-IP canvas that integrates IP considerations into each of the SBM canvas building blocks. We do this by employing relevant theoretical concepts from three literature streams, namely the business model (including SBM), IP, and innovation literature. We use case examples to illustrate different IP considerations that are relevant for the SBM-IP building blocks. These examples show that different IP types (e.g., patents, trademarks) and ways of using them (e.g., more or less restrictive licensing) are applied by companies in relation to the different building blocks. While covering new theoretical ground, the proposed SBM-IP canvas can help decision makers understand how they can use different IP types strategically to propose, create, deliver, and capture sustainable value for society, environment, and the business.</jats:p

History of malaria treatment as a predictor of subsequent subclinical parasitaemia: A cross-sectional survey and malaria case records from three villages in Pailin, western Cambodia

Background: Treatment of the sub-clinical reservoir of malaria, which may maintain transmission, could be an important component of elimination strategies. The reliable detection of asymptomatic infections with low levels of parasitaemia requires high-volume quantitative polymerase chain reaction (uPCR), which is impractical to conduct on a large scale. It is unknown to what extent sub-clinical parasitaemias originate from recent or older clinical episodes. This study explored the association between clinical history of malaria and subsequent sub-clinical parasitaemia. Methods: In June 2013 a cross-sectional survey was conducted in three villages in Pailin, western Cambodia. Demographic and epidemiological data and blood samples were collected. Blood was tested for malaria by high-volume qP

Automatic prediction of catalytic residues by modeling residue structural neighborhood

Background: Prediction of catalytic residues is a major step in characterizing the function of enzymes. In its simpler formulation, the problem can be cast into a binary classification task at the residue level, by predicting whether the residue is directly involved in the catalytic process. The task is quite hard also when structural information is available, due to the rather wide range of roles a functional residue can play and to the large imbalance between the number of catalytic and non-catalytic residues.Results: We developed an effective representation of structural information by modeling spherical regions around candidate residues, and extracting statistics on the properties of their content such as physico-chemical properties, atomic density, flexibility, presence of water molecules. We trained an SVM classifier combining our features with sequence-based information and previously developed 3D features, and compared its performance with the most recent state-of-the-art approaches on different benchmark datasets. We further analyzed the discriminant power of the information provided by the presence of heterogens in the residue neighborhood.Conclusions: Our structure-based method achieves consistent improvements on all tested datasets over both sequence-based and structure-based state-of-the-art approaches. Structural neighborhood information is shown to be responsible for such results, and predicting the presence of nearby heterogens seems to be a promising direction for further improvements.Journal ArticleResearch Support, N.I.H. Extramuralinfo:eu-repo/semantics/publishe

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease

Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker

Tumor-Targeted Delivery of IL-2 by NKG2D Leads to Accumulation of Antigen-Specific CD8+ T Cells in the Tumor Loci and Enhanced Anti-Tumor Effects

Interleukin-2 (IL-2) has been shown to promote tumor-specific T-cell proliferation and differentiation but systemic administration of IL-2 results in significant toxicity. Therefore, a strategy that can specifically deliver IL-2 to the tumor location may alleviate concerns of toxicity. Because NKG2D ligands have been shown to be highly expressed in many cancer cells but not in healthy cells, we reason that a chimeric protein consisting of NKG2D linked to IL-2 will lead to the specific targeting of IL-2 to the tumor location. Therefore, we created chimeric proteins consisting of NKG2D linked to Gaussia luciferase (GLuc; a marker protein) or IL-2 to form NKG2D-Fc-GLuc and NKG2D-Fc-IL2, respectively. We demonstrated that NKG2D linked to GLuc was able to deliver GLuc to the tumor location in vivo. Furthermore, we showed that TC-1 tumor-bearing mice intramuscularly injected with DNA encoding NKG2D-Fc-IL2, followed by electroporation, exhibited an increased number of luciferase-expressing E7-specific CD8+ T cells at the tumor location. More importantly, treatment with the DNA construct encoding NKG2D-Fc-IL2 significantly enhanced the therapeutic anti-tumor effects generated by intradermal vaccination with therapeutic HPV DNA in tumor-bearing mice. Therefore, by linking NKG2D to IL2, we are able to specifically deliver IL-2 to the tumor location, enhancing antigen-specific T-cell immune response and controlling tumor growth. Our approach represents a platform technology to specifically deliver proteins of interest to tumor loci

Optimising Strategies for Plasmodium falciparum Malaria Elimination in Cambodia: Primaquine, Mass Drug Administration and Artemisinin Resistance

Malaria elimination requires a variety of approaches individually optimized for different transmission settings. A recent field study in an area of low seasonal transmission in South West Cambodia demonstrated dramatic reductions in malaria parasite prevalence following both mass drug administration (MDA) and high treatment coverage of symptomatic patients with artemisinin-piperaquine plus primaquine. This study employed multiple combined strategies and it was unclear what contribution each made to the reductions in malaria.A mathematical model fitted to the trial results was used to assess the effects of the various components of these interventions, design optimal elimination strategies, and explore their interactions with artemisinin resistance, which has recently been discovered in Western Cambodia. The modelling indicated that most of the initial reduction of P. falciparum malaria resulted from MDA with artemisinin-piperaquine. The subsequent continued decline and near elimination resulted mainly from high coverage with artemisinin-piperaquine treatment. Both these strategies were more effective with the addition of primaquine. MDA with artemisinin combination therapy (ACT) increased the proportion of artemisinin resistant infections, although much less than treatment of symptomatic cases with ACT, and this increase was slowed by adding primaquine. Artemisinin resistance reduced the effectiveness of interventions using ACT when the prevalence of resistance was very high. The main results were robust to assumptions about primaquine action, and immunity.The key messages of these modelling results for policy makers were: high coverage with ACT treatment can produce a long-term reduction in malaria whereas the impact of MDA is generally only short-term; primaquine enhances the effect of ACT in eliminating malaria and reduces the increase in proportion of artemisinin resistant infections; parasite prevalence is a better surveillance measure for elimination programmes than numbers of symptomatic cases; combinations of interventions are most effective and sustained efforts are crucial for successful elimination

Computational Prediction of Heme-Binding Residues by Exploiting Residue Interaction Network

Computational identification of heme-binding residues is beneficial for predicting and designing novel heme proteins. Here we proposed a novel method for heme-binding residue prediction by exploiting topological properties of these residues in the residue interaction networks derived from three-dimensional structures. Comprehensive analysis showed that key residues located in heme-binding regions are generally associated with the nodes with higher degree, closeness and betweenness, but lower clustering coefficient in the network. HemeNet, a support vector machine (SVM) based predictor, was developed to identify heme-binding residues by combining topological features with existing sequence and structural features. The results showed that incorporation of network-based features significantly improved the prediction performance. We also compared the residue interaction networks of heme proteins before and after heme binding and found that the topological features can well characterize the heme-binding sites of apo structures as well as those of holo structures, which led to reliable performance improvement as we applied HemeNet to predicting the binding residues of proteins in the heme-free state. HemeNet web server is freely accessible at http://mleg.cse.sc.edu/hemeNet/

Novel Feature for Catalytic Protein Residues Reflecting Interactions with Other Residues

Owing to their potential for systematic analysis, complex networks have been widely used in proteomics. Representing a protein structure as a topology network provides novel insight into understanding protein folding mechanisms, stability and function. Here, we develop a new feature to reveal correlations between residues using a protein structure network. In an original attempt to quantify the effects of several key residues on catalytic residues, a power function was used to model interactions between residues. The results indicate that focusing on a few residues is a feasible approach to identifying catalytic residues. The spatial environment surrounding a catalytic residue was analyzed in a layered manner. We present evidence that correlation between residues is related to their distance apart most environmental parameters of the outer layer make a smaller contribution to prediction and ii catalytic residues tend to be located near key positions in enzyme folds. Feature analysis revealed satisfactory performance for our features, which were combined with several conventional features in a prediction model for catalytic residues using a comprehensive data set from the Catalytic Site Atlas. Values of 88.6 for sensitivity and 88.4 for specificity were obtained by 10fold crossvalidation. These results suggest that these features reveal the mutual dependence of residues and are promising for further study of structurefunction relationship

Allogeneic Lymphocytes Persist and Traffic in Feral MHC-Matched Mauritian Cynomolgus Macaques

Thus far, live attenuated SIV has been the most successful method for vaccinating macaques against pathogenic SIV challenge; however, it is not clear what mechanisms are responsible for this protection. Adoptive transfer studies in mice have been integral to understanding live attenuated vaccine protection in models like Friend virus. Previous adoptive transfers in primates have failed as transferred cells are typically cleared within hours after transfer.Here we describe adoptive transfer studies in Mauritian origin cynomolgus macaques (MCM), a non-human primate model with limited MHC diversity. Cells transferred between unrelated MHC-matched macaques persist for at least fourteen days but are rejected within 36 hours in MHC-mismatched macaques. Cells trafficked from the blood to peripheral lymphoid tissues within 12 hours of transfer.MHC-matched MCM provide the first viable primate model for adoptive transfer studies. Because macaques infected with SIV are the best model for HIV/AIDS pathogenesis, we can now directly study the correlates of protective immune responses to AIDS viruses. For example, plasma viral loads following pathogenic SIV challenge are reduced by several orders of magnitude in macaques previously immunized with attenuated SIV. Adoptive transfer of lymphocyte subpopulations from vaccinated donors into SIV-naïve animals may define the immune mechanisms responsible for protection and guide future vaccine development

Amyloid and Tau Pathology Associations With Personality Traits, Neuropsychiatric Symptoms, and Cognitive Lifestyle in the Preclinical Phases of Sporadic and Autosomal Dominant Alzheimer's Disease

Background: Major prevention trials for Alzheimer’s disease (AD) are now focusing on multidomain lifestyle interventions. However, the exact combination of behavioral factors related to AD pathology remains unclear. In 2 cohorts of cognitively unimpaired individuals at risk of AD, we examined which combinations of personality traits, neuropsychiatric symptoms, and cognitive lifestyle (years of education or lifetime cognitive activity) related to the pathological hallmarks of AD, amyloid-β, and tau deposits. Methods: A total of 115 older adults with a parental or multiple-sibling family history of sporadic AD (PREVENT-AD [PRe-symptomatic EValuation of Experimental or Novel Treatments for AD] cohort) underwent amyloid and tau positron emission tomography and answered several questionnaires related to behavioral attributes. Separately, we studied 117 mutation carriers from the DIAN (Dominant Inherited Alzheimer Network) study group cohort with amyloid positron emission tomography and behavioral data. Using partial least squares analysis, we identified latent variables relating amyloid or tau pathology with combinations of personality traits, neuropsychiatric symptoms, and cognitive lifestyle. Results: In PREVENT-AD, lower neuroticism, neuropsychiatric burden, and higher education were associated with less amyloid deposition (p = .014). Lower neuroticism and neuropsychiatric features, along with higher measures of openness and extraversion, were related to less tau deposition (p = .006). In DIAN, lower neuropsychiatric burden and higher education were also associated with less amyloid (p = .005). The combination of these factors accounted for up to 14% of AD pathology. Conclusions: In the preclinical phase of both sporadic and autosomal dominant AD, multiple behavioral features were associated with AD pathology. These results may suggest potential pathways by which multidomain interventions might help delay AD onset or progression