According to rational expectation models, uninformed or liquidity trading make market price volatility rise. This paper sets out to analyze the impact of herding, which may be interpreted as one of the components of uninformed trading, on the volatility of the Spanish stock market. Herding is examined at the intraday level, considered the most reliable sampling frequency for detecting this type of investor behavior, and measured using the Patterson and Sharma (2006) herding intensity measure. Different volatility measures (historical, realized and implied) are employed. The results confirm that herding has a direct linear impact on volatility for all of the volatility measures considered although the corresponding intensity is not always the same. In fact, herding variables seem to be useful in volatility forecasting and therefore in decision making when volatility is considered a key factor.

Universities have a critical role in achieving the Sustainable Development Goals (SDGs), both for implementing active policies and for encouraging other actors to participate. This requires having the skills and mind-sets to contribute to these challenges. The relevance and the commitment of universities to sustainability has led to the inclusion of SDGs in the strategies and agendas of these institutions. This requires the involvement of all the actors and some structural and cultural changes that put SDGs at the core of the governance and management of the university, embracing all the stakeholders. Various internal and external factors may influence the impact and success of the policies and activities aiming at achieving the SDGs, both from an overall perspective and for individual SDGs. This paper assesses the influence of some internal factors, such as the presence of universities on the internet, the level of internationalization or the availability of financial resources. Through both regression analyses and the Gephi method, our results confirm the importance of the presence on the internet, the internationalization of the university and the financial resources for research and infrastructure received from regional governments for Spanish public universities to make a greater contribution to SDGs.

Background The coronavirus disease (COVID-19) pandemic has already affected more than 400 million people, with increasing numbers of survivors. These data indicate that a myriad of people may be affected by pulmonary sequelae of the infection. The aim of this study was to evaluate pulmonary sequelae in patients with bilateral COVID-19 pneumonia according to severity 1 year after hospital discharge. Methods COVID-FIBROTIC is a multicenter prospective observational cohort study for admitted patients with bilateral COVID-19 pneumonia. Pulmonary functional outcomes and chest computed tomography sequelae were analyzed 12 months after hospital discharge and we classified patients into three groups according to severity. A post hoc analysis model was designed to establish how functional test changed between groups and over time. A multivariable logistic regression model was created to study prognostic factors for lung diffusion impairment and radiological fibrotic-like changes at 12 months. Results Among 488 hospitalized patients with COVID-19 pneumonia, 284 patients had completed the entire evaluation at 12 months. Median age was 60.5 ± 11.9 and 55.3% were men. We found between-group differences in male sex, length of hospital stay, radiological involvement and inflammatory laboratory parameters. The functional evaluation of pulmonary sequelae showed that severe patients had statistically worse levels of lung diffusion at 2 months but no between group differences were found in subsequent controls. At 12-month follow up, however, we found impaired lung diffusion in 39.8% unrelated to severity. Radiological fibrotic-like changes at 12 months were reported in 22.7% of patients (102/448), only associated with radiological involvement at admission (OR: 1.55, 95% CI 1.06–2.38; p = 0.02) and LDH (OR: 0.99, 95% CI 0.98–0.99; p = 0.046). Conclusion Our data suggest that a significant percentage of individuals would develop pulmonary sequelae after COVID 19 pneumonia, regardless of severity of the acute process. Trial registration clinicaltrials.gov NCT04409275 (June 1, 2020)

The endonuclease G gene (Endog), which codes for a mitochondrial nuclease, was identified as a determinant of cardiac hypertrophy. How ENDOG controls cardiomyocyte growth is still unknown. Thus, we aimed at finding the link between ENDOG activity and cardiomyocyte growth. Endog deficiency induced reactive oxygen species (ROS) accumulation and abnormal growth in neonatal rodent cardiomyocytes, altering the AKT-GSK3β and Class-II histone deacethylases (HDAC) signal transduction pathways. These effects were blocked by ROS scavengers. Lack of ENDOG reduced mitochondrial DNA (mtDNA) replication independently of ROS accumulation. Because mtDNA encodes several subunits of the mitochondrial electron transport chain, whose activity is an important source of cellular ROS, we investigated whether Endog deficiency compromised the expression and activity of the respiratory chain complexes but found no changes in these parameters nor in ATP content. MtDNA also codes for humanin, a micropeptide with possible metabolic functions. Nanomolar concentrations of synthetic humanin restored normal ROS levels and cell size in Endog-deficient cardiomyocytes. These results support the involvement of redox signaling in the control of cardiomyocyte growth by ENDOG and suggest a pathway relating mtDNA content to the regulation of cell growth probably involving humanin, which prevents reactive oxygen radicals accumulation and hypertrophy induced by Endog deficiency.