Papel y expectativas de los parques científicos como elementos de atracción y apoyo de empresas y emprendedores sociales: Un estudio FSQCA

Los parques científicos (PC) son uno de agentes más comunes, pero también más controvertidos, de las políticas públicas de innovación. Los resultados divergentes sobre su impacto y aportación de valor ponen de manifiesto que no ejercen un efecto homogéneo en todas las tipologías de empresa. Mediante este trabajo se ha querido explorar e identificar las vías por las que los PC crean valor para el emprendimiento social y mostrar su potencial relevancia como elementos dinamizadores de este tipo de emprendimientos. Este estudio busca determinar de forma exploratoria en qué medida ciertos atributos de los parques influyen en la percepción de valor y en las motivaciones de las empresas y entidades de economía social para ubicarse en estos espacios. Para ello se acomete un estudio empírico sobre una muestra de 25 empresas sociales ubicadas en cinco PC de España y se aplica un análisis fsQCA para vincular distintos perfiles de empresa social con los posibles beneficios percibidos por la ubicación en un PC. Nuestros resultados revelan que las empresas con una mayor motivación prosocial decidieron localizarse en un PC fundamentalmente atraídas por las facilidades de acceso a financiación pública y por las condiciones preferentes en el alquiler. Se identifican también los perfiles de empresas sociales más atraídas por la proximidad a la universidad y por los efectos de aglomeración que les aporta el parque donde se ubican

VAASI: Crafting valid and abnormal adversarial samples for anomaly detection systems in industrial scenarios

In the realm of industrial anomaly detection, machine and deep learning models face a critical vulnerability to adversarial attacks. In this context, existing attack methodologies primarily target continuous features, often in the context of images, making them unsuitable for the categorical or discrete features prevalent in industrial systems. To fortify the cybersecurity of industrial environments, this paper introduces a groundbreaking adversarial attack approach tailored to the unique demands of these settings. Our novel technique enables the creation of targeted adversarial samples that are valid within the framework of supervised cyberattack detection models in industrial scenarios, preserving the consistency of discrete values and correcting cases where an adversarial sample transitions into a normal one. Our approach leverages the SHAP interpretability method to identify the most salient features for each sample. Subsequently, the Projected Gradient Descent technique is employed to perturb continuous features, ensuring adversarial sample generation. To handle categorical features for a specific adversarial sample, our method scrutinizes the closest sample within the normal training dataset and replicates its categorical feature values. Additionally, Decision Trees trained within a Random Forest are utilized to ensure that the resulting adversarial samples maintain the essential abnormal behavior required for detection. The validation of our proposal was conducted using the WADI dataset obtained from a water distribution plant, providing a realistic industrial context. During validation, we assessed the mean error and the total number of adversarial samples generated by our approach, comparing it with the original Projected Gradient Descent method and the Carlini & Wagner attack across various parameter configurations. Remarkably, our proposal consistently achieved the best trade-off between mean error and the number of generated adversarial samples, showcasing its superiority in safeguarding industrial systems

An interpretable semi‐supervised system for detecting cyberattacks using anomaly detection in industrial scenarios

When detecting cyberattacks in Industrial settings, it is not sufficient to determine whether the system is suffering a cyberattack. It is also fundamental to explain why the system is under a cyberattack and which are the assets affected. In this context, the Anomaly Detection based on Machine Learning (ML) and Deep Learning (DL) techniques showed great performance when detecting cyberattacks in industrial scenarios. However, two main limitations hinder using them in a real environment. Firstly, most solutions are trained using a supervised approach, which is impractical in the real industrial world. Secondly, the use of black‐box ML and DL techniques makes it impossible to interpret the decision made by the model. This article proposes an interpretable and semi‐supervised system to detect cyberattacks in Industrial settings. Besides, our proposal was validated using data collected from the Tennessee Eastman Process. To the best of our knowledge, this system is the only one that offers interpretability together with a semi‐supervised approach in an industrial setting. Our system discriminates between causes and effects of anomalies and also achieved the best performance for 11 types of anomalies out of 20 with an overall recall of 0.9577, a precision of 0.9977, and a F1‐score of 0.9711

A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios

Anomaly Detection systems based on Machine and Deep learning are the most promising solutions to detect cyberattacks in the industry. However, these techniques are vulnerable to adversarial attacks that downgrade prediction performance. Several techniques have been proposed to measure the robustness of Anomaly Detection in the literature. However, they do not consider that, although a small perturbation in an anomalous sample belonging to an attack, i.e., Denial of Service, could cause it to be misclassified as normal while retaining its ability to damage, an excessive perturbation might also transform it into a truly normal sample, with no real impact on the industrial system. This paper presents a methodology to calculate the robustness of Anomaly Detection models in industrial scenarios. The methodology comprises four steps and uses a set of additional models called support models to determine if an adversarial sample remains anomalous. We carried out the validation using the Tennessee Eastman process, a simulated testbed of a chemical process. In such a scenario, we applied the methodology to both a Long-Short Term Memory (LSTM) neural network and 1-dimensional Convolutional Neural Network (1D-CNN) focused on detecting anomalies produced by different cyberattacks. The experiments showed that 1D-CNN is significantly more robust than LSTM for our testbed. Specifically, a perturbation of 60% (empirical robustness of 0.6) of the original sample is needed to generate adversarial samples for LSTM, whereas in 1D-CNN the perturbation required increases up to 111% (empirical robustness of 1.11)

Akt phosphorylation of HCV NS5B regulates polymerase activity and HCV infection

Hepatitis C virus (HCV) is a single-stranded RNA virus of positive polarity [ssRNA(+)] that replicates its genome through the activity of one of its proteins, called NS5B. This viral protein is responsible for copying the positive-polarity RNA genome into a negative-polarity RNA strand, which will be the template for new positive-polarity RNA genomes. The NS5B protein is phosphorylated by cellular kinases, including Akt. In this work, we have identified several amino acids of NS5B that are phosphorylated by Akt, with positions S27, T53, T267, and S282 giving the most robust results. Site-directed mutagenesis of these residues to mimic (Glu mutants) or prevent (Ala mutants) their phosphorylation resulted in a reduced NS5B in vitro RNA polymerase activity, except for the T267E mutant, the only non-conserved position of all those that are phosphorylated. In addition, in vitro transcribed RNAs derived from HCV complete infectious clones carrying mutations T53E/A and S282E/A were transfected in Huh-7.5 permissive cells, and supernatant viral titers were measured at 6 and 15 days post-transfection. No virus was rescued from the mutants except for T53A at 15 days post-transfection whose viral titer was statistically lower as compared to the wild type. Therefore, phosphorylation of NS5B by cellular kinases is a mechanism of viral polymerase inactivation. Whether this inactivation is a consequence of interaction with cellular kinases or a way to generate inactive NS5B that may have other functions are questions that need further experimental workMinisterio de Ciencia, Innovación y Universidades (MCIU), PI18/00210 from Instituto de Salud Carlos III, and S2018/BAA-4370 (PLATESA2 from Comunidad de Madrid/FEDER). CP was supported by the Miguel Servet program of the Instituto de Salud Carlos III (CPII19/00001), cofinanced by the European Regional Development Fund (ERDF). CG-C was supported by the predoctoral contract PRE2018-083422 from MCIU. CIBERehd (Centro de Investigación en Red de Enfermedades Hepáticas y Digestivas) was funded by the Instituto de Salud Carlos III. Institutional grants from the Fundación Ramón Areces and Banco Santander to the CBMS

Allotopic expression of mitochondrial-encoded genes in mammals: achieved goal, undemonstrated mechanism or impossible task?

Mitochondrial-DNA diseases have no effective treatments. Allotopic expression—synthesis of a wild-type version of the mutated protein in the nuclear-cytosolic compartment and its importation into mitochondria—has been proposed as a gene-therapy approach. Allotopic expression has been successfully demonstrated in yeast, but in mammalian mitochondria results are contradictory. The evidence available is based on partial phenotype rescue, not on the incorporation of a functional protein into mitochondria. Here, we show that reliance on partial rescue alone can lead to a false conclusion of successful allotopic expression. We recoded mitochondrial mt-Nd6 to the universal genetic code, and added the N-terminal mitochondrial-targeting sequence of cytochrome c oxidase VIII (C8) and the HA epitope (C8Nd6HA). The protein apparently co-localized with mitochondria, but a significant part of it seemed to be located outside mitochondria. Complex I activity and assembly was restored, suggesting successful allotopic expression. However, careful examination of transfected cells showed that the allotopically-expressed protein was not internalized in mitochondria and that the selected clones were in fact revertants for the mt-Nd6 mutation. These findings demonstrate the need for extreme caution in the interpretation of functional rescue experiments and for clear-cut controls to demonstrate true rescue of mitochondrial function by allotopic expression

Mitochondrial cristae shape determines respiratory chain supercomplexes assembly and respiratory efficiency

Respiratory chain complexes assemble into functional quaternary structures called supercomplexes (RCS) within the folds of the inner mitochondrial membrane, or cristae. Here, we investigate the relationship between respiratory function and mitochondrial ultrastructure and provide evidence that cristae shape determines the assembly and stability of RCS and hence mitochondrial respiratory efficiency. Genetic and apoptotic manipulations of cristae structure affect assembly and activity of RCS in vitro and in vivo, independently of changes to mitochondrial protein synthesis or apoptotic outer mitochondrial membrane permeabilization. We demonstrate that, accordingly, the efficiency of mitochondria-dependent cell growth depends on cristae shape. Thus, RCS assembly emerges as a link between membrane morphology and function.We thank A. Gross (Weizmann Institute) for anti-BID antibody, A. Latorre-Pellicer (CNIC) for mtDNA RT-PCR, and M. Albiero (VIMM) for tail vein injections. L.S. is a senior scientist of the Dulbecco-Telethon Institute. This work is supported by Telethon Italy (GGP12162, GPP10005B, and TCR02016), AIRC Italy, MOH Italy (GR 09.021), and Swiss National Foundation (31-118171). J.A.E. is supported by MINECO (SAF2012-32776 and CSD2007-00020), DGA (B55, PIPAMER O905), and CAM (S2011/BMD-2402). S.C. was supported by a Journal of Cell Science Travelling Fellowship. C.F. was supported by an AIRC Biennial Fellowship. The CNIC is funded by the Instituto de Salud Carlos III-MICINN and the Pro-CNIC Foundation.S

Induction of the mitochondrial NDUFA4L2 protein by HIF-1α decreases oxygen consumption by inhibiting complex i activity

The fine regulation of mitochondrial function has proved to be an essential metabolic adaptation to fluctuations in oxygen availability. During hypoxia, cells activate an anaerobic switch that favors glycolysis and attenuates the mitochondrial activity. This switch involves the hypoxia-inducible transcription factor-1 (HIF-1). We have identified a HIF-1 target gene, the mitochondrial NDUFA4L2 (NADH dehydrogenase [ubiquinone] 1 alpha subcomplex, 4-like 2). Our results, obtained employing NDUFA4L2-silenced cells and NDUFA4L2 knockout murine embryonic fibroblasts, indicate that hypoxia-induced NDUFA4L2 attenuates mitochondrial oxygen consumption involving inhibition of Complex I activity, which limits the intracellular ROS production under low-oxygen conditions. Thus, reducing mitochondrial Complex I activity via NDUFA4L2 appears to be an essential element in the mitochondrial reprogramming induced by HIF-1This work was supported by Ministerio de Ciencia e Innovación (SAF 2007-06592, SAF2010-14851), Comunidad Autónoma de Madrid (SAL 2006/ 0311), Metoxia Project-Health (F2 2009-222741), and Recava Network (RD 06/0014/0031) to M.O.L.; PS09/00101 and CP07/00143 to A.M.-R.; PI060701, PS09/00116, and CP08/00204 to S.C.; BFU2008-03407/BMC to J.A.; SAF2009-08007 to J.A.E.; and CSD2007-00020 to A.M.-R. and J.A.E. The CNIC is supported by the Instituto de Salud Carlos III-MICINN and the Pro-CNIC Foundation. We are grateful to Mike Murphy (Mitochondrial Biology Unit, MRC, Cambridge, UK) for the gift of MitoQ. We also thank Stephen Y. Chan and Joseph Loscalzo (Harvard Medical School, Boston, MA) for providing us ISCU expression vector

The long non-coding rna cerox1 is a post transcriptional regulator of mitochondrial complex i catalytic activity

To generate energy efficiently, the cell is uniquely challenged to co-ordinate the abundance of electron transport chain protein subunits expressed from both nuclear and mitochondrial genomes. How an effective stoichiometry of this many constituent subunits is co- ordinated post-transcriptionally remains poorly understood. Here we show that Cerox1, an unusually abundant cytoplasmic long noncoding RNA (lncRNA), modulates the levels of mitochondrial complex I subunit transcripts in a manner that requires binding to microRNA-488-3p. Increased abundance of Cerox1 cooperatively elevates complex I subunit protein abundance and enzymatic activity, decreases reactive oxygen species production, and protects against the complex I inhibitor rotenone. Cerox1 function is conserved across placental mammals: Human and mouse orthologues effectively modulate complex I enzymatic activity in mouse and human cells, respectively. Cerox1 is the first lncRNA demonstrated, to our knowledge, to regulate mitochondrial oxidative phosphorylation and, with miR-488-3p, represent novel targets for the modulation of complex I activity