Search

[Objectives]: To describe the etiology of community-acquired pneumonia (CAP) in hospitalized children in Spain and analyze the predictors of the etiology., [Hypothesis]: The different etiological groups of pediatric CAP are associated with different clinical, radiographic, and analytical data., [Design]: Observational, multicenter, and prospective study., [Patient selection]: This study included children aged 1 month to 17 years with CAP, who were hospitalized between April 2012 and May 2019., [Methods]: An extensive microbiological workup was performed. The clinical, radiographic, and analytical parameters were analyzed for three etiological groups., [Results]: Among the 495 children included, at least one causative pathogen was identified in 262 (52.9%): pathogenic viruses in 155/262 (59.2%); atypical bacteria (AB), mainly Mycoplasma pneumonia, in 84/262 (32.1%); and typical bacteria (TyB) in 40/262 (15.3%). Consolidation was observed in 89/138 (64.5%) patients with viral CAP, 74/84 (88.1%) with CAP caused by AB, and 40/40 (100%) with CAP caused by TyB. Para-pneumonic pleural effusion (PPE) was observed in 112/495 (22.6%) patients, of which 61/112 (54.5%) presented a likely causative pathogen: viruses in 12/61 (19.7%); AB in 23/61 (37.7%); and TyB in 26/61 (42.6%). Viral etiology was significantly frequent in young patients and in those with low oxygen saturation, wheezing, no consolidation, and high lymphocyte counts. CAP patients with AB as the etiological agent had a significantly longer and less serious course as compared to those with other causative pathogens., [Conclusions]: Viruses and M. pneumoniae are the main causes of pediatric CAP in Spain. Wheezing, young age, and no consolidation on radiographs are indicative of viral etiology. Viruses and AB can also cause PPE. Since only a few cases can be directly attributed to TyB, the indications for antibiotics must be carefully considered in each patient.

De novo protein synthesis is required for synapse modifications underlying stable memory encoding. Yet neurons are highly compartmentalized cells and how protein synthesis can be regulated at the synapse level is unknown. Here, we characterize neuronal signaling complexes formed by the postsynaptic scaffold GIT1, the mechanistic target of rapamycin (mTOR) kinase, and Raptor that couple synaptic stimuli to mTOR-dependent protein synthesis; and identify NMDA receptors containing GluN3A subunits as key negative regulators of GIT1 binding to mTOR. Disruption of GIT1/mTOR complexes by enhancing GluN3A expression or silencing GIT1 inhibits synaptic mTOR activation and restricts the mTOR-dependent translation of specific activity-regulated mRNAs. Conversely, GluN3A removal enables complex formation, potentiates mTOR-dependent protein synthesis, and facilitates the consolidation of associative and spatial memories in mice. The memory enhancement becomes evident with light or spaced training, can be achieved by selectively deleting GluN3A from excitatory neurons during adulthood, and does not compromise other aspects of cognition such as memory flexibility or extinction. Our findings provide mechanistic insight into synaptic translational control and reveal a potentially selective target for cognitive enhancement

Constraints from surveys of post-common envelope binaries (PCEBs) consisting of a white dwarf plus an M-dwarf companion have led to significant progress in our understanding of the formation of close white dwarf binary stars with low-mass companions. The white dwarf binary pathways project aims at extending these previous surveys to larger secondary masses, i.e. secondary stars of spectral-type AFGK. Here, we present the discovery and observational characterization of three PCEBs with G-type secondary stars and orbital periods between 1.2 and 2.5 d. Using our own tools as well as MESA, we estimate the evolutionary history of the binary stars and predict their future. We find a large range of possible evolutionary histories for all three systems and identify no indications for differences in common envelope evolution compared to PCEBs with lower mass secondary stars. Despite their similarities in orbital period and secondary spectral type, we estimate that the future of the three systems is very different: TYC 4962-1205-1 is a progenitor of a cataclysmic variable system with an evolved donor star, TYC 4700-815-1 will run into dynamically unstable mass transfer that will cause the two stars to merge, and TYC 1380-957-1 may appear as supersoft source before becoming a rather typical cataclysmic variable star.

Epidemics caused by microbial organisms are part of the natural phenomena of increasing biological complexity. The heterogeneity and constant variability of hosts, in terms of age, immunological status, family structure, lifestyle, work activities, social and leisure habits, daily division of time, and other demographic characteristics make it extremely difficult to predict the evolution of epidemics. Such prediction is, however, critical for implementing intervention measures in due time and with appropriate intensity. General conclusions should be precluded, given that local parameters dominate the flow of local epidemics. Membrane computing models allows us to reproduce the objects (viruses, hosts) and their interactions (stochastic but also with defined probabilities) with an unprecedented level of detail. Our LOIMOS model helps reproduce the demographics and social aspects of a hypothetical town of 10,320 inhabitants in an average European country where COVID-19 is imported from the outside. The above-mentioned characteristics of hosts and their lifestyle are minutely considered. The dynamics of the epidemics are reproduced and include the effects on viral transmission of innate and acquired immunity at various ages. The model predicts the consequences of delaying the adoption of non-pharmaceutical interventions (between 15 and 45 days after the first reported cases) and the effect of those interventions on infection and mortality rates (reducing transmission by 20%, 50%, and 80%) in immunological response groups. The lockdown for the elderly population as a single intervention appears to be effective. This modelling exercise exemplifies the application of membrane computing for designing appropriate interventions in epidemic situations.