The prioritization of processing emotional stimuli usually produces deleterious effects on task performance when it distracts from a task. One common explanation is that brain resources are consumed by emotional stimuli, diverting resources away from executing the task. Viewing unpleasant stimuli also generates defensive reactions, and these responses may be at least partially responsible for the effect of the emotional modulation observed in various reaction time (RT) paradigms. We investigated whether modulatory effects on RT vary if we presented threat stimuli to prompt different defensive responses. To trigger different responses, we manipulated threat perception by moving the direction of threatening stimuli. Threatening or neutral stimuli were presented as distractors during a bar orientation discrimination task. The results demonstrated that threat stimuli directed toward the observer produced a decrease in RT; in contrast, threat stimuli directed away from the observer produced an increase in RT, when compared to neutral stimuli. Accelerated RT during directed toward threat stimuli was attributed to increased motor preparation resulting from strong activation of the defense response cascade. In contrast, directed away threat stimuli likely activated the defense cascade, but less intensively, prompting immobility. Different threat stimuli produced varying effects, which was interpreted as evidence that the modulation of RT by emotional stimuli represents the summation of attentional and motivational effects. Additionally, participants who had been previously exposed to diverse types of violent crime were more strongly influenced by threat stimuli directed toward the observer. In sum, our data support the concept that emotions are indeed action tendencies.

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Mycobacterium avium subsp. paratuberculosis (MAP) and adherent-invasive Escherichia coli (AIEC) have been implicated as primary triggers in Crohn's disease (CD). In this study, we evaluated the prevalence of MAP and E. coli (EC) DNA in peripheral blood from 202 inflammatory bowel disease (IBD) patients at various disease periods and compared against 24 cirrhotic patients with ascites (CIR) (non-IBD controls) and 29 healthy controls (HC). MAP DNA was detected by IS900-specific nested PCR, EC DNA by malB-specific nested PCR and AIEC identity, in selected samples, by sequencing of fimH gene. CD patients with active disease showed the highest MAP DNA prevalence among IBD patients (68 %). Infliximab treatment resulted in decreased MAP detection. CIR patients had high individual and coinfection rates (75 % MAP, 88 % EC and 67 % MAP and EC), whilst HC controls had lower MAP prevalence (38 %) and EC was undetectable in this control group. EC DNA prevalence in IBD patients was highly associated with CD, and 80 % of EC from the selected samples of CD patients analyzed carried the fimH30 allele, with a mutation strongly associated with AIEC. Our results show that coinfection with MAP and AIEC is common and persistent in CD, although the high MAP and EC detection in CIR patients suggested that colonization is, at least, partially dependent on increased gut permeability. Nevertheless, facilitative mechanisms between a susceptible host and these two potential human pathogens may allow their implication in CD pathogenesis.

MYC amplification is a frequent event in SCLC and is related to a short survival time. MYC amplification may be an independent prognostic factor for SCLC. Further studies are required to support this finding and clarify the role of MYC in SCLC tumorigenesis.

Urban wastewater sector is being pushed to optimize processes in order to reduce energy consumption without compromising its quality standards. Energy costs can represent a significant share of the global operational costs (between 50% and 60%) in an intensive energy consumer. Pumping is the largest consumer of electrical energy in a wastewater treatment plant. Thus, the optimal control of pump units can help the utilities to decrease operational costs. This work describes an innovative predictive control policy for wastewater variable-frequency pumps that minimize electrical energy consumption, considering uncertainty forecasts for wastewater intake rate and information collected by sensors accessible through the Supervisory Control and Data Acquisition system. The proposed control method combines statistical learning (regression and predictive models) and deep reinforcement learning (Proximal Policy Optimization). The following main original contributions are produced: i) model-free and data-driven predictive control;ii) control philosophy focused on operating the tank with a variable wastewater setpoint level; iii) use of supervised learning to generate synthetic data for pre-training the reinforcement learning policy, without the need to physically interact with the system.The results for a real case-study during 90 days show a 16.7% decrease in electrical energy consumption while still achieving a 97% reduction in the number of alarms (tank level above 7.2 meters) when compared with the current operating scenario (operating with a fixed set-point level). The numerical analysis showed that the proposed data-driven method is able to explore the trade-off between number of alarms and consumption minimization, offering different options to decision-makers.