Functional Interplay of Type-2 Corticotrophin Releasing Factor and Dopamine Receptors in the Basolateral Amygdala-Medial Prefrontal Cortex Circuitry

Background: Basolateral amygdala (BLA) excitatory projections to medial prefrontal cortex (PFC) play a key role controlling stress behavior, pain, and fear. Indeed, stressful events block synaptic plasticity at the BLA-PFC circuit. The stress responses involve the action of corticotrophin releasing factor (CRF) through type 1 and type 2 CRF receptors (CRF1 and CRF2). Interestingly, it has been described that dopamine receptor 1 (D1R) and CRF peptide have a modulatory role of BLA-PFC transmission. However, the participation of CRF1 and CRF2 receptors in BLA-PFC synaptic transmission still is unclear. Methods: We used in vivo microdialysis to determine dopamine and glutamate (GLU) extracellular levels in PFC after BLA stimulation. Immunofluorescence anatomical studies in rat PFC synaptosomes devoid of postsynaptic elements were performed to determine the presence of D1R and CRF2 receptors in synaptical nerve endings. Results: Here, we provide direct evidence of the opposite role that CRF receptors exert over dopamine extracellular levels in the PFC. We also show that D1R colocalizes with CRF2 receptors in PFC nerve terminals. Intra-PFC infusion of antisauvagine-30, a CRF2 receptor antagonist, increased PFC GLU extracellular levels induced by BLA activation. Interestingly, the increase in GLU release observed in the presence of antisauvagine-30 was significantly reduced by incubation with SCH23390, a D1R antagonist. Conclusion: PFC CRF2 receptor unmasks D1R effect over glutamatergic transmission of the BLA-PFC circuit. Overall, CRF2 receptor emerges as a new modulator of BLA to PFC glutamatergic transmission, thus playing a potential role in emotional disorders. Keywords: CRF2 receptor; D1 receptor; dopaminergic transmission; glutamatergic transmission; prefrontal cortex

Input variable selection for data-driven models of Coriolis flowmeters for two-phase flow measurement

Input variable selection is an essential step in the development of data-driven models for environmental, biological and industrial applications. Through input variable selection to eliminate the irrelevant or redundant variables, a suitable subset of variables is identified as the input of a model. Meanwhile, through input variable selection the complexity of the model structure is simplified and the computational efficiency is improved. This paper describes the procedures of the input variable selection for the data-driven models for the measurement of liquid mass flowrate and gas volume fraction under two-phase flow conditions using Coriolis flowmeters. Three advanced input variable selection methods, including Partial Mutual Information (PMI), Genetic Algorithm - Artificial Neural Network (GA-ANN) and tree-based Iterative Input Selection (IIS) are applied in this study. Typical data-driven models incorporating Support Vector Machine (SVM) are established individually based on the input candidates resulting from the selection methods. The validity of the selection outcomes is assessed through an output performance comparison of the SVM based data-driven models and sensitivity analysis. The validation and analysis results suggest that the input variables selected from the PMI algorithm provide more effective information for the models to measure liquid mass flowrate while the IIS algorithm provides a fewer but more effective variables for the models to predict gas volume fraction

Dynamic Control of Centrifugal Compressor Surge Using Tailored Structure,"

Introduction The operating range of turbomachinery compression systems is very often limited by the onset of fluid dynamic instabilities. Surge is a self-excited, essentially one-dimensional instability, which is characterized by oscillations in area-averaged mass flow and pressure rise, and is generally the most important instability in centrifugal compression systems. Surge can cause reduced performance and efficiency of the turbomachine, and, in some cases, failure due to the large unsteady aerodynamic forces on the blades To avoid surge, the compression system is generally operated away from the "surge line," the boundary between stable and unstable operation on the pressure rise versus mass flow performance map. Operating the compressor at some distance from this line, on the negatively sloped part of the compressor speedlines, can ensure stable operation. Doing this, however, may result in a performance penalty since peak performance and efficiency often occur near the surge line The goal of the research described here is to develop methods to extend the stable operating range by modifying the dynamic behavior of the compression system to suppress surge. This would allow compressor operation in previously unusable, o

The Impact of COVID-19 on Lung Cancer Incidence in England: Analysis of the National Lung Cancer Audit 2019 and 2020 Rapid Cancer Registration Datasets

Background The Covid-19 pandemic has caused significant disruption to healthcare services and delivery worldwide. The impact of the pandemic and associated national lockdowns on lung cancer incidence in England has yet to be assessed. Research Question What was the impact of the first year of the Covid-19 pandemic on the incidence and presentation of lung cancer in England? Study Design and Methods In this retrospective observational study, incidence rates (IR) for lung cancer were calculated from The National Lung Cancer Audit (NLCA) Rapid Cancer Registration Datasets for 2019 and 2020, using mid-year population estimates from the Office of National Statistics as the denominators. Rates were compared using Poisson regression according to time points related to national lockdowns in 2020. Results 64457 patients were diagnosed with lung cancer across 2019 (n = 33088) and 2020 (n = 31369). During the first national lockdown, there was a 26% reduction in lung cancer incidence compared to the equivalent calendar period of 2019 (adjusted IRR 0.74, 95% CI 0.71 to 0.78). This included a 23% reduction in non-small cell lung cancer (NSCLC) (adjusted IRR 0.77, 95% CI 0.74 to 0.81) and a 45% reduction in small cell lung cancer (SCLC) (adjusted IRR 0.55, 95% CI 0.46 to 0.65) incidence. Incidence rates almost recovered thereafter to baseline, without overcompensation (adjusted IRR 0.96, 95% CI 0.94 to 0.98). Interpretation The incidence rates of lung cancer in England fell significantly by 26% during the first national lockdown in 2020, and did not compensate later in the year