Crecimiento de firmas de ingreso tardío a mercados de software estandarizado: un enfoque desde la modelación de la difusión competitiva multigeneracional, con efectos de red.

Según el orden de entrada al mercado, las firmas se clasifican como Pioneras, Seguidoras Tempranas y Entrantes Tardías (en adelante, estas últimas se denominarán ET) (Ansoff and Stewart, 1967). En la industria de software, existe abundante evidencia de que tanto el tiempo de entrada de una innovación disruptiva en el mercado (Keller and Hüsig, 2009), como las ventajas comparativas de la región en la que emerge (Arora and Gambardella, 2005)y la trayectoria tomada por el paradigma tecnológico en el cual están inscritos sus productos, tienden a un crecimiento dependiente de la trayectoria (D'Costa, 2002). Podría interpretarse entonces, que la adopción de los productos de las firmas de software es sensible a factores aleatorios e idiosincráticos presentes al inicio de la difusión, los cuales tienen impactos en los resultados finales. Estas condiciones pueden ubicar a la Pionera en una posición ventajosa frente a sus seguidores. Sin embargo, la incertidumbre tecnológica y de mercado puede hacer que una Pionera quede en condición de desventaja frente a las ET (Lieberman and Montgomery, 1998). Adicionalmente, la Pionera enfrenta el riesgo de seguir una trayectoria tecnológicamente inferior ante la llegada de una ET capaz de introducir en el mercado nuevas generaciones de producto compatibles con el estándar, como en el caso Microsoft Corp. y Google Inc. descrito por Keller and Hüsig (2009). El fenómeno del crecimiento de firmas ET es un desafío que ha venido ganado atención por más de una década, tanto en la literatura de pronóstico tecnológico (Rousseva, 2008),como en economía (Arora and Gambardella, 2005)y política (Schware, 1992; Soete, 1985; Steinmueller, 2001).Sin embargo, si las firmas ET pueden sostener o no sus tasas de crecimiento, sigue siendo una cuestión que se ha abordado empíricamente. Dadas las características del crecimiento de firmas en mercados de software, dos instrumentos teóricos parecen promisorios para el modelamiento del fenómeno. Por un lado la teoría de la difusión de la innovación, enfocada en la explicación y el pronóstico del proceso de adopción de productos por una población de usuarios potenciales de la firma. Por otro, la teoría de los efectos de red, que considera una dinámica en la que los adoptadores potenciales se benefician por comprar el producto de la firma que cuente con mayor base instalada -externalidades de red directas- y con compatibilidad con múltiples productos–externalidades de red indirectas-. Se dispone de abundante literatura para el modelado de la difusión de la innovación (Bass F. , 1969; Bass and Bass, 2001; Maier, 1998; Meade and Islam, 2006; Chanda and Bardhan, 2008)y el modelado de los efectos de red (Oren, Smith, and Wilson, 1982; Katz and Shapiro, 1985; Economides, 1996; Farrell and Saloner, 1986; Church and Gandal, 1996). Von Westarp (2003)y Kemper (2010)hacen contribuciones al modelado de mercados de software; sin embargo, no consideran la difusión competitiva multi-generacional y con efectos de red, presente en el crecimiento a largo plazo de firmas de software. Esta investigación se enmarcada y valida en seis postulados que pueden explicar el crecimiento de ET a mercados de software estandarizado, a saber: i) el indicador de crecimiento de las firmas es la venta anual (Peres, R., Muller, E., and Mahajan, V., 2010); ii) el potencial de mercado es dinámico en función de los efectos de red (β) considerados por Liu et al. (2011); iv) una firma de software sale del mercado cuando no difunde nuevos productos después de dos años de la introducción del producto anterior (Giarratana, 2004); v) en la fabricación de software estandarizado, los principales costos para el desarrollo del producto ocurren en la fase de I and D (OECD, 2009); la inversión en I and D es un indicador de capacidad de innovación. La entrada necesaria para acumular capacidad en I and D es el porcentaje anual de ventas destinado a inversión en I and D y la salida se mide en número de nuevas generaciones de producto que se difunden en el mercado (Li, Shang, and Slaughter, 2010; OECD, 2009). En esta investigación doctoral se explica el fenómeno de crecimiento de firmas ET inmersas en un ambiente de competencia contra un Pionera, mediante la simulación de un modelo y se evalúa la sensibilidad del comportamiento de las ventas, a la inversión en I+D y al tiempo de entrada de sucesivas generaciones del producto. Las múltiples simulaciones del modelo muestran que invertir en I+D, aumentar la base instalada mediante los beneficios de las externalidades de red en la demanda, e introducir en el mercado múltiples generaciones de productos más rápidamente que la Pionera, son estrategias promisorias para que las ET sobrevivan en el mercado./ Abstract. According to their order of market entry, firms are classified as Pioneers, Early Followers and Late Starters(hereinafter, the latter will be referred to as LS) (Ansoff and Stewart, 1967).In the software industry, there is abundant evidence that both the time of entry of a disruptive innovation in the market(Keller and Hüsig, 2009), as the region’s comparative advantages where it emerges(Arora and Gambardella, 2005)and the trajectory taken by the technological paradigm in which their products are inscribed, tend to a trajectory dependent growth (D'Costa, 2002). It could be interpreted then that the adoption of the products of the software firms is sensitive to random and idiosyncratic factors present at the beginning of the diffusion which have impacts on the final results. These conditions can place the Pioneer firms at an advantage against its followers. However, the technological and market uncertainty can place a Pioneer firm in a position of disadvantage compare to the LS firm (Lieberman and Montgomery, 1998). Additionally, the Pioneer firm faces the risk of following a trajectory technologically inferior to the arrival of a LS firm capable of introducing into the market new generations of products compatible with the standard, as in the case of Microsoft Corp. and Google Inc. described by Keller and Hüsig (2009). The phenomenon of LS firms growth is a challenge that has increasingly gained attention for more than a decade, both in technological forecasting literature(Rousseva, 2008),economics(Arora and Gambardella, 2005)and politics(Schware, 1992; Soete, 1985; Steinmueller, 2001).However, whether the LS firms can sustain their growth rates, remains an issue which has been addressed empirically. Given the growth characteristics of firms within the software markets, two theoretical tools seem promising for the modeling of the phenomenon. On the one hand the theory of innovation diffusion, focused on explaining and predicting the product adoption process by a population of potential users of the firm. On the other hand, the theory of network effects, which considers a dynamic in which potential adopters benefit by purchasing the product of the firm that has the largest installed base –direct network externalities- and with compatibility with multiple products–indirect network externalities-. There is abundant literature for modeling the diffusion of innovation (Bass F. , 1969; Bass and Bass, 2001; Maier, 1998; Meade and Islam, 2006; Chanda and Bardhan, 2008)and modeling of network effects (Oren, Smith, and Wilson, 1982; Katz and Shapiro, 1985; Economides, 1996; Farrell and Saloner, 1986; Church and Gandal, 1996). Von Westarp (2003)and Kemper (2010)make contributions to the modeling of software markets; however, they do not consider the multi-generational competitive diffusion and network effects, present in long-term growth of software firms. This research is framed and validated in six principles that can explain the growth of LS firms to standardized software markets, namely: i) the indicator of firm growth is the annual sale (Peres, R., Muller, E., and Mahajan, V., 2010); ii) the potential market is dynamic in terms of network effects(β)considered by Liu et al. (2011); iv) a software firm drops out from the market when it does not disseminate new products after two years of the introduction of the last product (Giarratana, 2004); v) in the manufacture of standardized software, the main costs for the development of a product occur in the I and D phase (OECD, 2009); investment in I and D is an indicator of innovation capacity. The input required to build capacity in I and D is the annual percentage of sales allocated to investment in I and D and the output is measured in the number of new product generations that are spread out in the market (Li, Shang, and Slaughter, 2010; OECD, 2009). This doctoral research explains the growth phenomenon of LS firms immersed in a competitive environment against a Pioneer firm, by simulating a model and evaluating the sensitivity of sales performance, investment in I+D and the time of entrance of successive product generations. The multiple model simulations show that investing in I+D, increasing the installed base through the benefits of network externalities in demand, and bringing to market multiple generations of products faster than the Pioneer firm, are promising strategies for the LS firms survival in the market.Doctorad

The new pharmacological chaperones PBXs increase α-galactosidase a activity in Fabry disease cellular models

Fabry disease is an X-linked multisystemic disorder caused by the impairment of lysosomal α-Galactosidase A, which leads to the progressive accumulation of glycosphingolipids and to defective lysosomal metabolism. Currently, Fabry disease is treated by enzyme replacement therapy or the orally administrated pharmacological chaperone Migalastat. Both therapeutic strategies present limitations, since enzyme replacement therapy has shown low half-life and bioavailability, while Migalastat is only approved for patients with specific mutations. The aim of this work was to assess the efficacy of PBX galactose analogues to stabilize α-Galactosidase A and therefore evaluate their potential use in Fabry patients with mutations that are not amenable to the treatment with Migalastat. We demonstrated that PBX compounds are safe and effective concerning stabilization of α-Galactosidase A in relevant cellular models of the disease, as assessed by enzymatic activity measurements, molecular modelling, and cell viability assays. This experimental evidence suggests that PBX compounds are promising candidates for the treatment of Fabry disease caused by mutations which affect the folding of α-Galactosidase A, even for GLA variants that are not amenable to the treatment with Migalastat.Fundación Biomédica Galicia Sur | Ref. OT-02-CNFXunta de Galicia | Ref. CN2012 / 18

Inter- and intracontinental migrations and local differentiation have shaped the contemporary epidemiological landscape of canine parvovirus in South America

Canine parvovirus (CPV) is a fast-evolving single-stranded DNA virus that causes one of the most significant infectious diseases of dogs. Although the virus dispersed over long distances in the past, current populations are considered to be spatially confined and with only a few instances of migration between specific localities. It is unclear whether these dynamics occur in South America where global studies have not been performed. The aim of this study is to analyze the patterns of genetic variability in South American CPV populations and explore their evolutionary relationships with global strains. Genomic sequences of sixty-three strains from South America and Europe were generated and analyzed using a phylodynamic approach. All the obtained strains belong to the CPV-2a lineage and associate with global strains in four monophyletic groups or clades. European and South American strains from all the countries here analyzed are representative of a widely distributed clade (Eur-I) that emerged in Southern Europe during 1990–98 to later spread to South America in the early 2000s. The emergence and spread of the Eur-I clade were correlated with a significant rise in the CPV effective population size in Europe and South America. The Asia-I clade includes strains from Asia and Uruguay. This clade originated in Asia during the late 1980s and evolved locally before spreading to South America during 2009–10. The third clade (Eur-II) comprises strains from Italy, Brazil, and Ecuador. This clade appears in South America as a consequence of an early introduction from Italy to Ecuador in the middle 1980s and has experienced extensive local genetic differentiation. Some strains from Argentina, Uruguay, and Brazil constitute an exclusive South American clade (SA-I) that emerged in Argentina in the 1990s. These results indicate that the current epidemiological scenario is a consequence of inter- and intracontinental migrations of strains with different geographic and temporal origins that set the conditions for competition and local differentiation of CPV populations. The coexistence and interaction of highly divergent strains are the main responsible for the drastic epidemiological changes observed in South America in the last two decades. This highlights the threat of invasion from external sources and the importance of whole-genome resolution to robustly infer the origin and spread of new CPV variants. From a taxonomic standpoint, the findings herein show that the classification system that uses a single amino acid to identify variants (2a, 2b, and 2c) within the CPV-2a lineage does not reflect phylogenetic relationships and is not suitable to analyze CPV evolution. In this regard, the identification of clades or sublineages within circulating CPV strains is the first step towards a genetic and evolutionary classification of the virus

A deletion in SARS-CoV- 2 ORF7 identified in COVID-19 outbreak in Uruguay

The analysis of genetic diversity in SARS-CoV-2 is the focus of several studies, providing insights into how the virus emerged and evolves. Most common changes in SARS-CoV-2 are single or point nucleotide substitutions; meanwhile, insertions and deletions (indels) have been identified as a less frequent source of viral genetic variability. Here, we report the emergence of a 12-nucleotide deletion in ORF7a, resulting in a 4-amino acid in-frame deletion. The Δ12 variant was identified in viruses from patients of a single outbreak and represents the first report of this deletion in South American isolates. Phylogenetic analysis revealed that Δ12 strains belong to the lineage B.1.1 and clustered separated from the remaining Uruguayan strains. The ∆12 variant was detected in 14 patients of this outbreak by NGS sequencing and/or two rapid and economic methodologies: Sanger amplicon sequencing and capillary electrophoresis. The presence of strong molecular markers as the deletion described here are useful for tracking outbreaks and reveal a significant aspect of the SARS-CoV-2 evolution on the robustness of the virus to keep its functionality regardless loss of genetic material

Genome sequences of SARS-CoV-2 P.1 (Variant of Concern) and P.2 (Variant of Interest) identified in Uruguay

Two severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants associated with increased transmission and immune evasion, P.1 and P.2, emerged in Brazil and spread throughout South America. Here, we report genomes corresponding to these variants that were recently detected in Uruguay. These P.1 and P.2 genomes share all substitutions that are characteristic of these variants

5to. Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad. Memoria académica

El V Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad, CITIS 2019, realizado del 6 al 8 de febrero de 2019 y organizado por la Universidad Politécnica Salesiana, ofreció a la comunidad académica nacional e internacional una plataforma de comunicación unificada, dirigida a cubrir los problemas teóricos y prácticos de mayor impacto en la sociedad moderna desde la ingeniería. En esta edición, dedicada a los 25 años de vida de la UPS, los ejes temáticos estuvieron relacionados con la aplicación de la ciencia, el desarrollo tecnológico y la innovación en cinco pilares fundamentales de nuestra sociedad: la industria, la movilidad, la sostenibilidad ambiental, la información y las telecomunicaciones. El comité científico estuvo conformado formado por 48 investigadores procedentes de diez países: España, Reino Unido, Italia, Bélgica, México, Venezuela, Colombia, Brasil, Estados Unidos y Ecuador. Fueron recibidas un centenar de contribuciones, de las cuales 39 fueron aprobadas en forma de ponencias y 15 en formato poster. Estas contribuciones fueron presentadas de forma oral ante toda la comunidad académica que se dio cita en el Congreso, quienes desde el aula magna, el auditorio y la sala de usos múltiples de la Universidad Politécnica Salesiana, cumplieron respetuosamente la responsabilidad de representar a toda la sociedad en la revisión, aceptación y validación del conocimiento nuevo que fue presentado en cada exposición por los investigadores. Paralelo a las sesiones técnicas, el Congreso contó con espacios de presentación de posters científicos y cinco workshops en temáticas de vanguardia que cautivaron la atención de nuestros docentes y estudiantes. También en el marco del evento se impartieron un total de ocho conferencias magistrales en temas tan actuales como la gestión del conocimiento en la universidad-ecosistema, los retos y oportunidades de la industria 4.0, los avances de la investigación básica y aplicada en mecatrónica para el estudio de robots de nueva generación, la optimización en ingeniería con técnicas multi-objetivo, el desarrollo de las redes avanzadas en Latinoamérica y los mundos, la contaminación del aire debido al tránsito vehicular, el radón y los riesgos que representa este gas radiactivo para la salud humana, entre otros

Growth of late entrant firms of the software industry: a model of multigenerational product diffusion with network effects

RESUMEN: En este artículo se presenta un modelo de crecimiento de dos firmas -Pionera y Entrante tardía- (en adelante ET) en mercados de software estandarizado. El modelo propuesto está definido en función del comportamiento dinámico de las ventas de múltiples generaciones de producto, sujetas a efectos de red. En la validación se comparan las simulaciones del modelo con los históricos de dos Pioneras: ANSYS INC y SYMANTEC Corp. y dos ET: CIMATRON Group y Check Point Software Technologies Ltd.. Se concluye que las estrategias para que una Entrante Tardía sobreviva en el mercado son: i) invertir en I&D para difundir generaciones sucesivas de productos; ii) aumentar la base instalada mediante el fortalecimiento de los efectos de red; y iii) controlar los retardos en la entrada de sus productos frente a los del Pionera.ABSTRACT: This article presents a growth model of two companies -Pioneer and Late Entrant- in markets of standardized software. The model proposed is defined in terms of the dynamic behavior of sales of multiple product generations subject to network effects. The validation compares model simulations with historical data from two pioneer companies ANSYS INC. and SYMANTEC Corp. and from two late entrants CIMATRON Group and Check Point Software Technologies Ltd.. It is finally concluded that the strategies for a late entrant to survive in the market are as follows: i) investing in R&D to spread and replace successive product generations; ii) increasing the installed base by reinforcing network effects; and iii) controlling the timing of the market entry of its products with regards to those of pioneer companies

Elevated Anti-SARS-CoV-2 Antibodies and IL-6, IL-8, MIP-1β, Early Predictors of Severe COVID-19

Viral and host immune kinetics during acute COVID-19 and after remission of acute symptoms need better characterization. SARS-CoV-2 RNA, anti-SARS-CoV-2 IgA, IgM, and IgG antibodies, and proinflammatory cytokines were measured in sequential samples from hospitalized COVID-19 patients during acute infection and six months following diagnosis. Twenty four laboratory confirmed COVID-19 patients with mild/moderate and severe COVID-19 were included. Most were males (83%) with a median age of 61 years. Twenty one percent were admitted to the intensive care unit (ICU) and eight of them (33.3%) met the criteria for severe COVID-19 disease. A delay in SARS-CoV-2 levels' decline during the first six days of follow up, and viral load persistence until month 3 were related to severe COVID-19, but not viral load levels at the diagnosis. Higher levels of anti-SARS-CoV-2 IgA, IgM, IgG and the cytokines IL-6, IL-8 and MIP-1β at the diagnosis time were related to the severe COVID-19 outcome. Higher levels of MIP-1β, IL-1β, MIP-1α and IFN-γ were observed at month 1 and 3 during mild/moderate disease, compared to severe COVID-19. IgG persisted at low levels after six months of diagnosis. In conclusion, higher concentrations of IgA, IgM, and IgG, and IL-6, IL-8 and MIP-1β are identified as early predictors of COVID-19 severity, whereas no significant association is found between baseline SARS-COV-2 viral load and COVID-19 severity.This work was supported by the Plan Estatal de I+D+I 2013-2016 and 2017–2020 and cofinanced by the Instituto de Salud Carlos III (ISCIII)—Subdirección General de Evaluación y Fomento de la investigación del Fondo Europeo de Desarrollo Regional (FEDER), Fondo COVID19 of Instituto de Salud Carlos III (COV20/00698), RETICS, Red de Investigación en SIDA [RD16/0025/0026]; and Fundación Biomédica Galicia Sur. E.R-M. was supported by the Spanish Research Council (CSIC) and by the research grant CV20-85418 from the Consejería de Transformación Económica, Industria, Conocimiento y Universidades (Junta de Andalucía). A.P. was supported by the Instituto de Salud Carlos III, Subprograma Rio Hortega (CM20/00243). A.G.-V. was supported by the Instituto de Salud Carlos III, cofinanced by the European Development Regional Fund (“A way to achieve Europe”), Subprograma Miguel Servet (CP19/00159). E.M.M. was supported by the Instituto de Salud Carlos III, cofinanced by the European Development Regional Fund (“A way to achieve Europe”), Subprogram PFIS (FI19/00304). C.K. was supported by Fondo COVID19 of Instituto de Salud Carlos III (COV20/00823).Ye

Elevated anti-SARS-CoV-2 antibodies and IL-6, IL-8, MIP-1β, early predictors of severe COVID-19

Background: Viral and host immune kinetics during acute COVID-19 and after remission of acute symptoms need better characterization. Methods: SARS-CoV-2 RNA, anti-SARS-CoV-2 IgA, IgM, and IgG antibodies, and pro-inflammatory cytokines were measured in sequential samples among hospitalized COVID-19 patients during acute infection and 6 months following diagnosis. Results: 24 laboratory-confirmed COVID-19 patients with mild/moderate and severe COVID-19 were included. Most were males 83%, median age of 61 years. 21% were admitted to the ICU and 8 of them (33.3%) met criteria for severe COVID-19 disease. A delay in SARS-CoV-2 levels decline during the first 6 days of follow-up and viral load persistence until month 3 were related with severe COVID-19, but not viral load levels at the diagnosis. Higher levels of anti-SARS-CoV-2 IgA, IgM, IgG and the cytokines IL-6, IL-8 and MIP-1β at the diagnosis time were related with severe COVID-19 outcome. Higher levels of MIP-1β, IL-1β, MIP-1α and IFN-γ were observed at month 1-3 during mild/moderate disease compared to severe COVID-19. IgG persisted at low levels after 6 months of diagnosis. Conclusions: Higher concentrations of IgA, IgM, and IgG, and IL-6, IL-8 and MIP-1β are identified as early predictors of COVID-19 severity, but not SARS-CoV-2 RNA levels at diagnosis.This work was supported by Plan Estatal de I+D+I 2013-2016 and 2017-2020 and cofinanced by Instituto de Salud Carlos III (ISCIII) - Subdirección General de Evaluación y Fomento de la investigación del Fondo Europeo de Desarrollo Regional (FEDER), Fondo COVID19 of Instituto de Salud Carlos III (COV20/00698), RETICS, Red de Investigación en SIDA [RD16/0025/0026]; and Fundación Biomédica Galicia Sur. E.R-M. was supported by Spanish Research Council (CSIC) and by the research grant CV20-85418 from the Consejería de Transformación Económica, Industria, Conocimiento y Universidades (Junta de Andalucía). A.G-V was supported by the Instituto de Salud Carlos III, cofinanced by the European Development Regional Fund (“A way to achieve Europe”), Subprograma Miguel Servet (CP19/00159). E.M.M. was supported by the Instituto de Salud Carlos III, cofinanced by the European Development Regional Fund (“A way to achieve Europe”), Subprogram PFIS (FI19/00304). C.K was supported by Fondo COVID19 of Instituto de Salud Carlos III (COV20/00823).N