A Somatically Diversified Defense Factor, FREP3, Is a Determinant of Snail Resistance to Schistosome Infection

Schistosomiasis, a neglected tropical disease, owes its continued success to freshwater snails that support production of prolific numbers of human-infective cercariae. Encounters between schistosomes and snails do not always result in the snail becoming infected, in part because snails can mount immune responses that prevent schistosome development. Fibrinogen-related protein 3 (FREP3) has been previously associated with snail defense against digenetic trematode infection. It is a member of a large family of immune molecules with a unique structure consisting of one or two immunoglobulin superfamily domains connected to a fibrinogen domain; to date fibrinogen containing proteins with this arrangement are found only in gastropod molluscs. Furthermore, specific gastropod FREPs have been shown to undergo somatic diversification. Here we demonstrate that siRNA mediated knockdown of FREP3 results in a phenotypic loss of resistance to Schistosoma mansoni infection in 15 of 70 (21.4%) snails of the resistant BS-90 strain of Biomphalaria glabrata. In contrast, none of the 64 control BS-90 snails receiving a GFP siRNA construct and then exposed to S. mansoni became infected. Furthermore, resistance to S. mansoni was overcome in 22 of 48 snails (46%) by pre-exposure to another digenetic trematode, Echinostoma paraensei. Loss of resistance in this case was shown by microarray analysis to be associated with strong down-regulation of FREP3, and other candidate immune molecules. Although many factors are certainly involved in snail defense from trematode infection, this study identifies for the first time the involvement of a specific snail gene, FREP3, in the phenotype of resistance to the medically important parasite, S. mansoni. The results have implications for revealing the underlying mechanisms involved in dictating the range of snail strains used by S. mansoni, and, more generally, for better understanding the phenomena of host specificity and host switching. It also highlights the role of a diversified invertebrate immune molecule in defense against a human pathogen. It suggests new lines of investigation for understanding how susceptibility of snails in areas endemic for S. mansoni could be manipulated and diminished

Effects of Cu/Zn Superoxide Dismutase (sod1) Genotype and Genetic Background on Growth, Reproduction and Defense in Biomphalaria glabrata

Resistance of the snail Biomphalaria glabrata to the trematode Schistosoma mansoni is correlated with allelic variation at copper-zinc superoxide dismutase (sod1). We tested whether there is a fitness cost associated with carrying the most resistant allele in three outbred laboratory populations of snails. These three populations were derived from the same base population, but differed in average resistance. Under controlled laboratory conditions we found no cost of carrying the most resistant allele in terms of fecundity, and a possible advantage in terms of growth and mortality. These results suggest that it might be possible to drive resistant alleles of sod1 into natural populations of the snail vector for the purpose of controlling transmission of S. mansoni. However, we did observe a strong effect of genetic background on the association between sod1 genotype and resistance. sod1 genotype explained substantial variance in resistance among individuals in the most resistant genetic background, but had little effect in the least resistant genetic background. Thus, epistatic interactions with other loci may be as important a consideration as costs of resistance in the use of sod1 for vector manipulation

Specific versus Non-Specific Immune Responses in an Invertebrate Species Evidenced by a Comparative de novo Sequencing Study

Our present understanding of the functioning and evolutionary history of invertebrate innate immunity derives mostly from studies on a few model species belonging to ecdysozoa. In particular, the characterization of signaling pathways dedicated to specific responses towards fungi and Gram-positive or Gram-negative bacteria in Drosophila melanogaster challenged our original view of a non-specific immunity in invertebrates. However, much remains to be elucidated from lophotrochozoan species. To investigate the global specificity of the immune response in the fresh-water snail Biomphalaria glabrata, we used massive Illumina sequencing of 5′-end cDNAs to compare expression profiles after challenge by Gram-positive or Gram-negative bacteria or after a yeast challenge. 5′-end cDNA sequencing of the libraries yielded over 12 millions high quality reads. To link these short reads to expressed genes, we prepared a reference transcriptomic database through automatic assembly and annotation of the 758,510 redundant sequences (ESTs, mRNAs) of B. glabrata available in public databases. Computational analysis of Illumina reads followed by multivariate analyses allowed identification of 1685 candidate transcripts differentially expressed after an immune challenge, with a two fold ratio between transcripts showing a challenge-specific expression versus a lower or non-specific differential expression. Differential expression has been validated using quantitative PCR for a subset of randomly selected candidates. Predicted functions of annotated candidates (approx. 700 unisequences) belonged to a large extend to similar functional categories or protein types. This work significantly expands upon previous gene discovery and expression studies on B. glabrata and suggests that responses to various pathogens may involve similar immune processes or signaling pathways but different genes belonging to multigenic families. These results raise the question of the importance of gene duplication and acquisition of paralog functional diversity in the evolution of specific invertebrate immune responses

Effect of exploitation and exploration on the innovative as outcomes in entrepreneurial firms

[EN] The main aim of this study is to establish the effect of the Exploitation and Exploration; and the influence of these learning flows on the Innovative Outcome (IO). The Innovative Outcome refers to new products, services, processes (or improvements) that the organization has obtained as a result of an innovative process. For this purpose, a relationship model is defined, which is empirically contrasted, and can explains and predicts the cyclical dynamization of learning flows on innovative outcome in knowledge intensive firms. The quantitative test for this model use the data from entrepreneurial firms biotechnology sector. The statistical analysis applies a method based on variance using Partial Least Squares (PLS). Research results confirm the hypotheses, that is, they show a positive dynamic effect between the Exploration and the Innovative as outcomes. In the same vein, they results confirm the presence of the cyclic movement of innovative outcome with the Exploitation.In addition, this research is part of the Project ECO2015-71380-R funded by the Spanish Ministry of Economy, Industry and Competitiveness and the State Research Agency. Co-financed by the European Regional Development Fund (ERDF).Vargas-Mendoza, NY.; Lloria, MB.; Salazar Afanador, A.; Vergara Domínguez, L. (2018). Effect of exploitation and exploration on the innovative as outcomes in entrepreneurial firms. International Entrepreneurship and Management Journal. 14(4):1053-1069. https://doi.org/10.1007/s11365-018-0496-5S10531069144Alegre, J., & Chiva, R. (2008). Assessing the impact of organizational learning capability on product innovation performance: an empirical test. Technovation, 28, 315–326.Amara, N., Landry, R., Becheikh, N., & Ouimet, M. (2008). Learning and novelty of innovation in established manufacturing SMEs. Technovation, 28, 450–463.Aragón-Mendoza, J., Pardo del Val, M., & Roig, S. (2016). The influence of institutions development in venture creation decision: a cognitive view. Journal of Business Research, 69(11), 4941–4946.Ardichvili, A. (2008). Learning and knowledge sharing in virtual communities of practice: motivators, barriers, and enablers. Advances in Developing Human Resources, 10(4), 541–554.Argyris, C., & Schön, D. (1978). Organizational learning: a theory of action perspective. Reading: Addison Wesley.Bagozzi, R. P., Yi, Y., & Singh, S. (1991). On the use of structural equation models in experimental designs: two extensions international. Journal of Research in Marketing, 8, 125–140.Belda, J., Vergara L., Salazar, A., & Safont G. (2018). Estimating the Laplacian matrix of Gaussian mixtures for signal processing on graphs, accepted for publication in Signal Processing.Boland, R. J. J., & Tenkasi, R. V. (1995). Perspective making and perspective taking in communities of knowing. Organization Science, 6(4), 350–372.Bontis, N., (1998). Intellectual capital: an exploratory study that develops measures models. Management Decision, 36, 63–76.Bontis, N. (1999). Managing an organizational learning system by aligning stocks and flows of knowledge: an empirical examination of intellectual capital, knowledge management, and business performance. 1999. Management of Innovation and New Technology Research Centre, McMaster University.Bontis, N., Keow, W., & Richardson, S. (2000). Intellectual capital and the nature of business in Malaysia. Journal of Intellectual Capital, 1(1), 85–100Bontis, N., Hullan, J., & Crossan, M. (2002). Managing an organizational learning system by aligning stocks and flows. Journal of Management Studies, 39, 438–469.Brachos, D., Kostopulos, K., Sodersquist, K. E., & Prastacos, G. (2007). Knowledge effectiveness, social context and innovation. Journal of Knowledge Management, 11(5), 31–44.Calantone, R. J., Cavusgil, S. T., & Zhao, Y. (2002). Learning orientation, firm innovation capability, and firm performance. Industrial Marketing Management, 31, 515–524.Chang, T. J., Yeh, S. P., & Yeh, I. J. (2007). The effects of joint rewards system in new product development. International Journal of Manpower, 28(3/4), 276–297.Chin, W. (1998). The partial least square approach to structural equation modeling. In G. A. Marcoulides (Ed.) (pp. 294–336). New Jersey: Lawrence Erlbaum Associates.Cho, N., Li, G., & Su, C. (2007). An empirical study on the effect of individual factors on knowledge sharing by knowledge type. Journal of Global Business and Technology, 3(2), 1–15.Cohen, W. M., & Levin, R. C. (1989). Empirical studies of innovation and market structure. In R. Schmalansee & R. D. Willing (Eds.), Handbook of industrial organization II. New York: Elsevier.Cohen, W. M., & Levinthal, D. A. (1990). Absorptive-capacity – a new perspective on learning and innovation. Administrative Science Quarterly, 35, 128–152.Cooper, R. G. (2000). New product performance: what distinguishes the star products. Austrian Journal of Management, 25, 17–45.Crossan, M., & Berdrow, I. (2003). Organizational learning and strategic renewal. Strategic Management Journal, 24, 1087–1105.Crossan, M., & Apaydin, M. (2010). A multi-dimensional framework of organizational innovation: a systematic review of the literature. Journal of Management Studies, 47(6), 1154–1191.Crossan, M., Lane, H. W., & White, R. E. (1999). An organizational learning framework: from intuition to institution. Academy of Management Review, 24, 522–537.Damanpour, F., & Aravind, D. (2012). Managerial innovation: conceptions, processes, and antecedents. Management and Organization Review, 8(2), 423–454.Damanpour, F., & Shanthi, G. (2001). The dynamics of the adoption of products and process innovations in organizations. Journal of Management Studies, 38(1), 21–65.Decarolis, D. M., & Deeds, D. L. (1999). The impact of stock and flows of organizational knowledge on firm performance: An empirical investigation of the biotechnology industry. Strategic Management Journal, 20, 953–968.Demartini, C. (2015). Relationships between social and intellectual capital: empirical Evidence from IC statements. Knowledge and Process Management, 22(2), 99–111.Dupuy, F. (2004). Sharing knowledge: they why and how of organizational change. Hampshire: Palgrave Macmillan.Fornell, C., & Bookstein, F. I. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19, 440–452.Ganter, A., & Hecker, A. (2013). Deciphering antecedents of organizational innovation. Journal of Business Research, 66(5), 575–584.Ganter, A., & Hecker, A. (2014). Configurational paths to organizational innovation: qualitative comparative analyses of antecedents and contingencies. Journal of Business Research, 67, 1285–1292.Gopalakrishnan, S., & Damanpour, F. (1997). A review of innovation research in economics, sociology and technology management. International Journal of Management Science, 25, 15–28.Hedberg, B. (1981). How organizations learn and unlearn. In P. Nystrom & W. Starbuck (Eds.), Handbook of organizational design. New York: Oxford University.Hedlund, G., & Nonaka, I. (1993). Models of knowledge management in the west and Japan. In: P. Lorange, B. Chacravrarthy, J. Ross, and J. Van de ven (Eds.) Cambridge: Basil Blackwell.Henseler, J., Ringle, C.M., & Sinkovics, R.R. (2009). The use the partial least squares path modeling. In: R. Sinkovics and N. Pervez (Eds.) 277–319.Hsu, I. (2006). Enhancing employee tendencies to share knowledge-case studies on nine companies in Taiwan. International Journal of Information Management, 26(4), 326–338.Hsu, I. (2008). Knowledge sharing practices as a facilitating factor for improving organizational performance though human capital: a preliminary test. Expert Systems with Application, 35, 316–1326.Huang, Q., Davison, R., & Gu, J. (2008). Impact of personal and cultural factors on knowledge sharing in China. Asia Pacific Journal Management, 25(3), 451–471.Ibarra, H. (1993). Network centrality, power, and innovation involvement – determinants of technical and administrative roles. Academy of Management Journal, 36(3), 471–501.Iebra, I. L., Zegarra, P. S., & Zegarra, A. S. (2011). Learning for sharing: an empirical analysis of organizational learning and knowledge sharin. International Entrepreneurship Management Journal, 7, 509–518.Ipe, M. (2003). Knowledge sharing in organizations: a conceptual framework. Human Resource Development Review, 2(4), 337–359.Jenkin, T. (2013). Extending the 4I organizational learning model: information sources, foraging processes and tools. Administrative Sciences, 3, 96–109.Jiménez-Jiménez, D., & Sanz-Valle, R. (2011). Innovation, organizational learning, and performance. Journal of Business Research, 64, 408–417.Kane, G. C., & Alavi, M. (2007). Information technology and organizational learning: an investigation of exploration and exploitation processes. Organization Science, 18(5), 796–812.Kleinbaum, D. G., Kupper, N. N., Muller, K. E. (1988). Applied regression analysis and other Multivariable’s methods, PWS KENT.Klomp, L., & Van Leeuwen, G. (2001). Linking innovation and firm performance: a new approach. International Journal of the Economics of Business, 8(3), 343–364.Lansisalmi, H., Kivimaki, M., Aalto, P., & Ruoranen, R. (2006). Innovation in healthcare: a systematic review of recent research. Nursing Science Quarterly, 19(1), 66–72.Laperrière, A., & Spence, M. (2015). Enacting international opportunities: the role of organizational learning in knowledge-intensive business services. Journal of International Entrepreneurship, 13(3), 212–241.Levitt, B., & March, J. G. (1988). Organizational learning. Annual Review of Sociology, 14, 319–340.Lin, H. (2007). Knowledge sharing and firm innovation capability: an empirical study. International Journal of Manpower, 28(3/4), 315–332.Lloria, M. B., & Moreno-Luzón, M. D. (2014). Organizational learning: proposal of an integrative scale and research instrument. Journal of Business Research, 67, 692–697.March, J. G. (1991). Exploration and exploitation in organizational learning. Organizational Science, 2, 71–87.Matikainen, M., Terho, H., Parvinen, P., & Juppo, A. (2016). The role and impact of firm’s strategic orientations on launch performance: significance of relationship orientation. Journal of Business & Industrial Marketing, 31(5), 625–639.Mone, M. A., McKinley, W., & Barker, V. L. (1998). Organizational decline and innovation: a contingency framework. Academy of Management Review, 23, 115–132.Moreno-Luzón, M. D., & Lloria, B. (2008). The role of non-structural and informal mechanisms of integration and integration as forces in knowledge creation. British Journal of Management, 19, 250–276.Moskaliuk, J., Bokhorst, F., & Cress, U. (2016). Learning from others' experiences: how patterns foster interpersonal transfer of knowledge-in-use. Computers in Human Behavior, 55, 69–75.Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company. How Japanese companies create the dynamics of innovation. New York: Oxford University Press.Nonaka, I., & von Krogh, G. (2009). Perspective tacit knowledge and knowledge conversion: controversy and advancement in organizational knowledge creation theory. Organization Science, 20(3), 635–652.Parida, V., Lahti, T., & Wincent, J. (2016). Exploration and exploitation and firm performance variability: a study of ambidexterity in entrepreneurial firms. International Entrepreneurship Management Journal, 12, 1147–1164.Pew, H., Plowman, D., & Hancock, P. (2008). The involving research on intellectual capital. Journal of Intellectual Capital, 9, 585–608.Potter, R. E., & Balthazard, P. A. (2004). The role of individual memory and attention processes during electronic brainstorming. MIS Quarterly, 28(4), 621–643.Ramadani, V., Hyrije, A. A., Léo-Paul, D., Gadaf, R., & Sadudin, I. (2017). The impact of knowledge spillovers and innovation on firm-performance: findings from the Balkans countries. International Entrepreneurship Management Journal, 13, 299–325.Ren, S., Shu, R., Bao, Y., & Chen, X. (2016). Linking network ties to entrepreneurial opportunity discovery and exploitation: the role of affective and cognitive trust. International Entrepreneurship and Management Journal, 12(2), 465–485.Ringle, C. M., Wende, S., & Will, A. (2005). Smart PLS 2.0 (M3) beta, Hamburg: http://www.smartpls.de .Ringle, C. M., Sarstedt, M., & Straub, D. (2012). A critical look at the use of PLS-SEM. MIS Quarterly, 36(1), iii–xiv.Sanchez, R., & Heene, A. (1997). A competence perspective on strategic learning and knowledge management. En Sanchez, R. and Heene, A. (eds.) Strategic learning and knowledge management. John Wiley and Sons.Seidler-de Alwis, R., & Hartmann, E. (2008). The use of tacit knowledge within innovative companies: knowledge management in innovative enterprises. Journal of Knowledge Management, 12(1), 133–147.Shrivastava, P. (1983). A typology of organizational learning systems. Journal of Management Studies, 20, 7–28.Tansky, J., Ribeiro, D., & Roig, S. (2010). Linking entrepreneurship and human resources in globalization. Human Resource Management, 49(2), 217–223.Teece, D. (2012). Dynamic capabilities: routines versus entrepreneurial action. Journal of Management Studies, 49(8), 1395–1401.Tenenhaus, M., Vinzi, V., Chatelin, Y., & Lauro, C. (2005). PLS path modeling. Computational Statistics and Data Analysis, 49, 159–205.vande Vrande, V., de Jong, J., Vanhaverbeke, W., & Rochemont, M. (2009). Open innovation in SMEs: trends, motives and management challenges. Technovation, 29, 423–437.Vargas, N., & Lloria, M. B. (2014). Dynamizing intellectual capital through enablers and learning flows. Industrial Management and Data Systems, 114(1), 2–20.Vargas, N., & Lloria, M. B. (2017). Performance and intellectual capital: how enablers drive value creation in organisations. Knowledge and Process Management, 24(2), 114–124.Vargas, N., Lloria, M. B., & Roig-Dobón, S. (2016). Main drivers of human capital, learning and performance. The Journal of Technology Transfer, 41(5), 961–978.Vergara, L., Salazar, A., Belda, J., Safont, G., Moral, S., & Iglesias, S. (2017). Signal processing on graphs for improving automatic credit card fraud detection. Proceeding of 2017 I.E. 51st international Carnahan Conference on Security Technology (ICCST 2017), https://doi.org/10.1109/CCST.2017.8167820 , 23–26 Oct, 2017, Madrid, Spain.Wallin, M. W., & Von Krogh, G. (2010). Organizing for open innovation: focus o the integration of knowledge. Organizational Dynamics, 39(2), 145–154.Wang, C. L., & Ahmed, P. K. (2004). Linking innovation and firm performance: a new approach. European International Journal of Technology Management, 27, 674–688.Wold, H. (1980). Model construction and evaluation when theoretical knowledge is scarce. In J. Kmenta & J. B. Ramsey (Eds.), Evaluation of econometric models (pp. 47–74). Cambridge: Academic Press.Wold, H. (1985). Factors influencing the outcome of economic sanctions. In Sixto Ríos Honorary. Trabajos de Estadística and de Investigación Operativa, 36(3), 325–337

Occurrence of thyroid autoimmunity and dysfunction throughout a nine-month follow-up in patients undergoing interferon-beta therapy for multiple sclerosis.

Thyroid autoimmunity and dysfunction are a well known side effect of IFN alpha therapy for viral hepatitis and tumors, while the IFN beta effects on the thyroid gland in neurological patients have not been studied. The aim of this longitudinal study was to look for the appearance of thyroid autoimmunity as well as for the occurrence of overt thyroid disease in the patients affected by multiple sclerosis (MS) treated with IFN beta 1b. Eight patients (4 males, 4 females) undergoing r-IFN beta 1b treatment (8 M.U. every other day for 9 months) for relapsing remitting multiple sclerosis entered the study. We have analyzed thyroid function parameters and auto antibody levers before and after 1, 2, 3, 6 and 9 months of therapy. None of them referred to familiar thyroid pathology or presented clinically overt thyroid disease except for one patient (case 4) who showed TPO-Ab pretreatment positivity and another (case 8) who was in therapy with Levothyroxine 100 mu g/die for multinodular goiter. The number of patients with appearance of thyroid antibodies has slowly increased, until the third month of therapy with 3 patients out of 7 positive for TPO-Ab. The only case of overt thyroid dysfunction reported by us appeared after nine months of therapy and consisted of a hypothyroidism. Our data suggest that short-term interferon beta treatment is able to induce thyroid autoimmunity (42.8%) and dysfunction (12.5%)

Diabetes insipidus and increased serum levels of leptin and lactate-dehydrogenase (LDH) in an adolescent boy with a primary intracranial germinoma. Case report and an endocrinological revaluation of literature.

A 16-year-old boy presented with a four-month history of polyuria-polydipsia and a diplopia which had reverted after treatment. The neuroimaging studies performed had been strongly suggestive of an optic nerve glioma, while endocrinological investigation (beta-hCG 420 IU/L) has lead to the correct diagnosis later confirmed at the immunohystochemical analysis performed at biopsy. The high serum level of hCG was unaffected by bromocriptine nor octreotide, while the PRL level (80.0 microg/L) was reduced only by bromocriptine. Among the several tumor markers which may be secreted by such lesions, ours is the first reported case of an elevation of serum LDH for a primary intracranial germinoma. Moreover, the elevated value of serum leptin reported by us might be due to the insensitivity of the hypothalamic structures to endogenous leptin

Occurrence of thyroid autoimmunity and dysfunction throughout a nine-month follow-up in patients undergoing interferon-beta therapy for multiple sclerosis.

Thyroid autoimmunity and dysfunction are a well known side effect of IFN alpha therapy for viral hepatitis and tumors, while the IFN beta effects on the thyroid gland in neurological patients have not been studied. The aim of this longitudinal study was to look for the appearance of thyroid autoimmunity as well as for the occurrence of overt thyroid disease in the patients affected by multiple sclerosis (MS) treated with IFN beta 1b. Eight patients (4 males, 4 females) undergoing r-IFN beta 1b treatment (8 M.U. every other day for 9 months) for relapsing remitting multiple sclerosis entered the study. We have analyzed thyroid function parameters and auto antibody levels before and after 1, 2, 3, 6 and 9 months of therapy. None of them referred to familiar thyroid pathology or presented clinically overt thyroid disease except for one patient (case 4) who showed TPO-Ab pretreatment positivity and another (case 8) who was in therapy with Levothyroxine 100 microg/die for multinodular goiter. The number of patients with appearance of thyroid antibodies has slowly increased, until the third month of therapy with 3 patients out of 7 positive for TPO-Ab. The only case of overt thyroid dysfunction reported by us appeared after nine months of therapy and consisted of a hypothyroidism. Our data suggest that short-term interferon beta treatment is able to induce thyroid autoimmunity (42.8%) and dysfunction (12.5%)