Detecting neurodevelopmental trajectories in congenital heart diseases with a machine-learning approach

We aimed to delineate the neuropsychological and psychopathological profiles of children with congenital heart disease (CHD) and look for associations with clinical parameters. We conducted a prospective observational study in children with CHD who underwent cardiac surgery within five years of age. At least 18\ua0months after cardiac surgery, we performed an extensive neuropsychological (intelligence, language, attention, executive function, memory, social skills) and psychopathological assessment, implementing a machine-learning approach for clustering and influencing variable classification. We examined 74 children (37 with CHD and 37 age-matched controls). Group comparisons have shown differences in many domains: intelligence, language, executive skills, and memory. From CHD questionnaires, we identified two clinical subtypes of psychopathological profiles: a small subgroup with high symptoms of psychopathology and a wider subgroup of patients with ADHD-like profiles. No associations with the considered clinical parameters were found. CHD patients are prone to high interindividual variability in neuropsychological and psychological outcomes, depending on many factors that are difficult to control and study. Unfortunately, these dysfunctions are under-recognized by clinicians. Given that brain maturation continues through childhood, providing a significant window for recovery, there is a need for a lifespan approach to optimize the outcome trajectory for patients with CHD

Pre-surgery urine metabolomics may predict late neurodevelopmental outcome in children with congenital heart disease

Background: From fetal life until cardiac surgery, complex congenital heart diseases (CHD) exhibit different hemodynamic and oxygenation patterns that can lead to alteration of the metabolic profile. We used a metabolomic approach to identify urine metabolic markers before cardiac surgery, aiming to define the physiology of patients with complex CHD and to contribute to predict their neurodevelopmental outcome. Methods: In a prospective, observational, single-center study we enrolled 28 patients with complex biventricular and univentricular CHD aged less than 5 years, on stable hemodynamic conditions, and with no genetic anomalies. We analyzed urine samples, collected at the induction of anesthesia, by 1H NMR spectroscopy. Profiles of 1H NMR spectra were submitted to unsupervised (principal component) and supervised (partial least squares-discriminant) multivariate analysis. Neurodevelopment was assessed by neuropsychological and adaptive functioning testing. Results: Principal components analysis divided CHD patients metabolic profiles in two distinct clusters (RED and BLACK). Metabolic profiles belonging to the RED cluster showed higher levels of accumulation of citric acid cycle intermediates and glucose compared to the profiles in the BLACK cluster, indicating a possible switching to anaerobic metabolism. Patients belonging to the RED cluster were significantly more prone to show an adverse neurodevelopment pattern (p = 0.01). Conclusions: The application of metabolomic analysis to CHD children permitted a deeper insight on their metabolic status that could help to obtain a better understanding of the physiological implications and to predict long-term neurodevelopmental outcome. © 201

SME Performance, Innovation and Networking - Evidence on Complementarities for a Local Economic System

The paper addresses the relevancy of networking activities and R&D as main drivers of productivity performance and ouput innovation, for small and medium enterprises (SME) playing in a local economic system. Given the intangible nature of many techno organisational innovation and networking strategies, original recent survey data for manufacturing and services are exploited. The aim is to provide new evidence on the complementarity relationships concerning different networking activities and R&D in a local SME oriented system in Northern Italy. We first introduce a methodological framework to empirically test complementarity among R&D and networking, in a discrete setting. Secondly, we consequently present empirical evidence on productivity drivers and on complementarity between R&D and networking strategies, with respect to firm productivity and process/product output innovation. R&D is a main driver of innovation and productivity, even without networking. This may signify, in association with the evidence on complementarity, that firm expenditures on R&D are a primary driver for performance. The complementarity with networking is a consequential step. Networking by itself cannot thus play a role in stimulating productivity and innovation. It can be a complementary factor in situations where cooperation and networking are needed to achieve economies of scale and/or to merge and integrate diverse skills, technologies and competencies. This is compatible with a framework where networking is the public good part of an impure public good wherein R&D plays the part of the private-led driving force towards structural break from the business as usual scenario. Managers and policy makers should be aware that in order to exploit asset complementarity, possibly transformed into competitive advantages, both R&D and networking are to be sustained and favoured. our evidence suggests that R&D may be a single main driver of performance. Since R&D expenditures are associated with firm size, a policy sustain is to be directed towards firm enlargement. After a certain threshold firms have the force to increase expenditures. The size effect is nevertheless non monotonous. Then, but not least important, for the majority of firms still remaining under a critical size threshold, policy incentives should be directed to R&D in connection with networking, through which a virtuous circle may arise. It is worth noting that it is not networking as such the main engine. Networking elements are crucially linked to innovation dynamics; it is nevertheless innovation that explains and drives networking, and not the often claimed mere existence of local spillovers or of a civic associative culture in the territory. Such public good factors exist but are likely to evolve with and be sustained by firm innovative dynamics

The Link between Innovation and Productivity in Estonia’s Service Sectors

The emerging literature on the characteristics of innovation processes in the service sector has paid relatively little attention to the links between innovation and productivity. In this paper we investigate how the innovation-productivity relationship differs across various subbranches of the service sector. For the analysis we use the CDM structural model consisting of equations for innovation expenditures, innovation output, productivity and exports. We use data from the community innovation surveys for Estonia. We show that innovation is associated with increased productivity in the service sector. The results indicate surprisingly that the effect of innovation on productivity is stronger in the less knowledge-intensive service sectors, despite the lower frequency of innovative activities and the results of earlier literature. Non-technological innovation only plays a positive role in some specifications, despite its expected importance especially among the service firms. An additional positive channel of the effects of innovation on productivity may function through increased exports.http://deepblue.lib.umich.edu/bitstream/2027.42/133027/1/wp1012.pd

Heuristic Optimization Methods for Dynamic Panel Data Model Selection: Application on the Russian Innovative Performance

Innovations, be they radical new products or technology improvements are widely recognized as a key factor of economic growth. To identify the factors triggering innovative activities is a main concern for economic theory and empirical analysis. As the number of hypotheses is large, the process of model selection becomes a crucial part of the empirical implementation. The problem is complicated by the fact that unobserved heterogeneity and possible endogeneity of regressors have to be taken into account. A new efficient solution to this problem is suggested, applying optimization heuristics, which exploits the inherent discrete nature of the problem. The model selection is based on information criteria and the Sargan test of overidentifying restrictions. The method is applied to Russian regional data within the framework of a log-linear dynamic panel data model. To illustrate the performance of the method, we also report the results of Monte-Carlo simulations

The Relationship between Environmental Efficiency and Manufacturing Firm's Growth

This paper investigates the empirical link between emission intensity and economic growth, using a very large data set of 61,219 Italian manufacturing firms over the period 2000-2004. As a measure of lagged environmental performance (efficiency) at firm level we exploit NAMEA sector for CO2, NOx, SOx data over 1990-1999. The paper tests the extent to which (past) environmental efficiency/intensity, which is driven by structural features and firm strategic actions, including responses to policies, influences firms growth. Our results show, first, a typical trade off generally appearing for the three core environmental emissions we analyse: lower environmentally efficiency in the recent past allows higher degrees of freedom to firms and relax the constraints for growth, at least in this short/medium term scenario. Nevertheless, the size of the estimated coefficients is not large. Trade offs are significant for two emission indicators out of two, but quite negligible in terms of impacts, besides the case of CO2. For example, growth is reduced by far less than 0.1% in association to a 1% increase of environmental efficiency. In addition, non-linearity seems to characterise the economic growth-environmental performance relationship. Signals of inverted U shape appear: this may be a signal that both firm strategies and recent policy efforts are affecting the dynamic relationship between environmental efficiency and economic productivity, turning it from an usual trade off to a possible joint complementary/co-dynamics

Cross-Reactivity of Herpesvirus-Specific CD8 T Cell Lines Toward Allogeneic Class I MHC Molecules

Although association between persistent viral infection and allograft rejection is well characterized, few examples of T-cell cross-reactivity between self-MHC/viral and allogeneic HLA molecules have been documented so far. We appraised in this study the alloreactivity of CD8 T cell lines specific for immunodominant epitopes from human cytomegalovirus (HCMV) and Epstein-Barr virus (EBV). CD8 T cell lines were generated after sorting with immunomagnetic beads coated with either pp65495–503/A*0201, BMLF1259–267/A*0201, or BZLF154–64/B*3501 multimeric complexes. Alloreactivity of the CD8 T cell lines against allogeneic class I MHC alleles was assessed by screening of (i) TNF-α production against COS-7 cells transfected with as many as 39 individual HLA class I-encoding cDNA, and (ii) cytotoxicity activity toward a large panel of HLA-typed EBV-transformed B lymphoblastoid cell lines. We identified several cross-reactive pp65/A*0201-specific T cell lines toward allogeneic HLA-A*3001, A*3101, or A*3201. Moreover, we described here cross-recognition of HLA-Cw*0602 by BZLF1/B*3501-specific T cells. It is noteworthy that these alloreactive CD8 T cell lines showed efficient recognition of endothelial cells expressing the relevant HLA class I allele, with high level TNF-α production and cytotoxicity activity. Taken together, our data support the notion that herpes virus-specific T cells recognizing allo-HLA alleles may promote solid organ rejection

The Major Antigenic Membrane Protein of “Candidatus Phytoplasma asteris” Selectively Interacts with ATP Synthase and Actin of Leafhopper Vectors

Phytoplasmas, uncultivable phloem-limited phytopathogenic wall-less bacteria, represent a major threat to agriculture worldwide. They are transmitted in a persistent, propagative manner by phloem-sucking Hemipteran insects. Phytoplasma membrane proteins are in direct contact with hosts and are presumably involved in determining vector specificity. Such a role has been proposed for phytoplasma transmembrane proteins encoded by circular extrachromosomal elements, at least one of which is a plasmid. Little is known about the interactions between major phytoplasma antigenic membrane protein (Amp) and insect vector proteins. The aims of our work were to identify vector proteins interacting with Amp and to investigate their role in transmission specificity. In controlled transmission experiments, four Hemipteran species were identified as vectors of “Candidatus Phytoplasma asteris”, the chrysanthemum yellows phytoplasmas (CYP) strain, and three others as non-vectors. Interactions between a labelled (recombinant) CYP Amp and insect proteins were analysed by far Western blots and affinity chromatography. Amp interacted specifically with a few proteins from vector species only. Among Amp-binding vector proteins, actin and both the α and β subunits of ATP synthase were identified by mass spectrometry and Western blots. Immunofluorescence confocal microscopy and Western blots of plasma membrane and mitochondrial fractions confirmed the localisation of ATP synthase, generally known as a mitochondrial protein, in plasma membranes of midgut and salivary gland cells in the vector Euscelidius variegatus. The vector-specific interaction between phytoplasma Amp and insect ATP synthase is demonstrated for the first time, and this work also supports the hypothesis that host actin is involved in the internalization and intracellular motility of phytoplasmas within their vectors. Phytoplasma Amp is hypothesized to play a crucial role in insect transmission specificity

Generation of a colony of homozygous K18-hACE2 transgenic mice for the evaluation of vaccine and therapeutic candidates against SARS-CoV-2

EL SARS-CoV-2 es el agente etiológico responsable de la enfermedad COVID-19 que inició una pandemia desde finales de 2019. Existen distintos modelos animales para esta enfermedad siendo el modelo de ratón transgénico K18-hACE2, originalmente desarrollado para el estudio del SARS CoV-1, de gran relevancia en el contexto actual. Considerando que los ratones se comercializan como hemicigotas y dada la ausencia de ratones homocigotas para el transgén K18-hACE2, el objetivo de este trabajo fue generar una colonia de ratones homocigotas K18-hACE2-Tg/Tg bajo condiciones ambientales controladas. Para la F1 se utilizaron 10 ratones hemicigotas (7 hembras y 3 machos), de 6-8 semanas de edad, provenientes de The Jackson Laboratory (USA). De la F1 se identificaron mediante genotipificación por PCR 78 animales: 62 hemicigotas (Tg/0) y 16 salvajes (0/0). Aquellos animales identificados como transgénicos se cruzaron con ratones C57BL/6J para seleccionar los parentales homocigotas que generaron 100% de hemicigotas en la F2. De 224 crías analizadas, se obtuvieron 7 parentales homocigotas K18-hACE2-Tg/Tg que fueron utilizados para la colonia fundación de ratones homocigotas K18-hACE2-Tg/Tg. El modelo de ratón homocigota K18 hACE2-Tg/Tg desarrollado en este trabajo podrá ser empleado para el estudio de la patogénesis de la enfermedad y la evaluación de posibles terapéuticos contra el SARS-CoV-2.SARS-CoV-2 is the causative etiological agent of the COVID-19 disease that started a pandemic in late 2019. Among different animal models for this disease, the K8-hACE2 transgenic mouse model, originally developed for the study of SARS-CoV-1, proved to be of great relevance in the current context. Considering that those mice are marketed as hemizygous and given that homozygous mice for the K18-hACE2 transgene are not commercially available, this work aimed to describe the creation of a colony of homozygous K18-hACE2-Tg/Tg mice under controlled environmental conditions. For the F1 progeny 10 hemizygous mice (7 females and 3 males), between 6-8 weeks of age, from The Jackson Laboratory (USA) were used. From the F1, 78 animals were identified by PCR genotyping: 62 hemizygous (Tg/0) and 16 wild types (0/0). Those animals identified as transgenic were crossed with C57BL/6J mice to select the homozygous parents that generated 100% hemizygous in F2. From a total of 224 analyzed offspring, 7 homozygous K18-hACE2-Tg/Tg parents were obtained, which were used for the foundation colony of homozygous K18-hACE2-Tg/Tg mice. The homozygous K18-hACE2-Tg/Tg mouse colony developed in this work will be able to use for the study of pathogenesis and the evaluation of possible therapeutics against SARS-CoV-2.Fil: Berengeno, Andrea Lorena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Matiller, Valentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Díaz, Pablo Uriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Rebelindo, Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Rodríguez, Fernanda Mariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Anweg, Ayelen. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Silvestrini, Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Cattaneo, M. L.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Peralta, María Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Durante, Leandro Ivan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Notaro, Ulises Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Cainelli, Sofía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Taborda, Paula Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Stalder, Veronica Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Etchevers, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Rey, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Salvetti, Natalia Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Ortega, Hugo Hector. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; Argentin