Expression of the Nuclear Receptor Coactivator, cAMP Response Element-Binding Protein, Is Sexually Dimorphic and Modulates Sexual Differentiation of Neonatal Rat Brain

Recent studies indicate that the transcriptional activity of steroid receptors is governed by proteins called nuclear receptor coactivators. Using immunocytochemistry, we found that on the day of birth (postnatal d 0) males express higher levels of the nuclear receptor coactivator, cAMP response element binding protein-binding protein (CBP), within the ventromedial hypothalamus, medial preoptic area, and arcuate nucleus. Using Western immunoblots, we confirmed that males have higher levels of CBP on postnatal d 0, 1, and 5; however, there was no sex difference on postnatal d 11. To examine the functional role of CBP, we infused oligodeoxynucleotides that were antisense to CBP mRNA or a scrambled sequence as a control into the hypothalamus of female rats on postnatal d 0, 1, and 2. On postnatal d 1, all rats were injected with 100 μg testosterone propionate to both masculinize (increase male) and defeminize (decrease female) sexual behavior. Rats were ovariectomized in adulthood and tested for adult sexual behavior. Neonatal CBP antisense oligodeoxynucleotides treatment interfered with the defeminizing, but not the masculinizing, actions of testosterone. These results indicate that CBP expression in developing rat brain is sexually dimorphic and an important modulator for steroid hormone action

Nuclear Receptor Coactivators Modulate Hormone-Dependent Gene Expression in Brain and Female Reproductive Behavior in Rats

Gonadal steroid hormones act in the brain to elicit changes in gene expression that result in profound effects on behavior and physiology. A variety of in vitro studies indicate that nuclear receptor coactivators are required for efficient transcriptional activity of steroid receptors. Two nuclear receptor coactivators, steroid receptor coactivator-1 (SRC-1) and cAMP response element binding protein-binding protein (CBP), have been shown to act in concert to enhance ER activity in vitro. In the present study, we investigated the function of these important nuclear receptor coactivators in estrogen action in rodent brain. Reduction of SRC-1 and CBP protein in brain disrupted ER-mediated activation of the behaviorally relevant progestin receptor gene. Furthermore, we found that SRC-1 and CBP function in brain to modulate the expression of hormone-dependent female sexual behavior. These findings indicate that these nuclear receptor coactivators function in brain to modulate ER transcriptional activity and the expression of hormone-dependent behavior

Altered Dopamine Signaling in Naturally Occurring Maternal Neglect

Child neglect is the most common form of child maltreatment, yet the biological basis of maternal neglect is poorly understood and a rodent model is lacking.The current study characterizes a population of mice (MaD1) which naturally exhibit maternal neglect (little or no care of offspring) at an average rate of 17% per generation. We identified a set of risk factors that can predict future neglect of offspring, including decreased self-grooming and elevated activity. At the time of neglect, neglectful mothers swam significantly more in a forced swim test relative to nurturing mothers. Cross-fostered offspring raised by neglectful mothers in turn exhibit increased expression of risk factors for maternal neglect and decreased maternal care as adults, suggestive of possible epigenetic contributions to neglect. Unexpectedly, offspring from neglectful mothers elicited maternal neglect from cross-fostered nurturing mothers, suggesting that factors regulating neglect are not solely within the mother. To identify a neurological pathway underlying maternal neglect, we examined brain activity in neglectful and nurturing mice. c-Fos expression was significantly elevated in neglectful relative to nurturing mothers in the CNS, particularly within dopamine associated areas, such as the zona incerta (ZI), ventral tegmental area (VTA), and nucleus accumbens. Phosphorylated tyrosine hydroxylase (a marker for dopamine production) was significantly elevated in ZI and higher in VTA (although not significantly) in neglectful mice. Tyrosine hydroxylase levels were unaltered, suggesting a dysregulation of dopamine activity rather than cell number. Phosphorylation of DARPP-32, a marker for dopamine D1-like receptor activation, was elevated within nucleus accumbens and caudate-putamen in neglectful versus nurturing dams.These findings suggest that atypical dopamine activity within the maternal brain, especially within regions involved in reward, is involved in naturally occurring neglect and that MaD1 mice are a useful model for understanding the basis of naturally occurring neglect

Dopaminergic Activation of Estrogen Receptors Induces Fos Expression within Restricted Regions of the Neonatal Female Rat Brain

Steroid receptor activation in the developing brain influences a variety of cellular processes that endure into adulthood, altering both behavior and physiology. Recent data suggests that dopamine can regulate expression of progestin receptors within restricted regions of the developing rat brain by activating estrogen receptors in a ligand-independent manner. It is unclear whether changes in neuronal activity induced by dopaminergic activation of estrogen receptors are also region specific. To investigate this question, we examined where the dopamine D1-like receptor agonist, SKF 38393, altered Fos expression via estrogen receptor activation. We report that dopamine D1-like receptor agonist treatment increased Fos protein expression within many regions of the developing female rat brain. More importantly, prior treatment with an estrogen receptor antagonist partially reduced D1-like receptor agonist-induced Fos expression only within the bed nucleus of the stria terminalis and the central amygdala. These data suggest that dopaminergic activation of estrogen receptors alters neuronal activity within restricted regions of the developing rat brain. This implies that ligand-independent activation of estrogen receptors by dopamine might organize a unique set of behaviors during brain development in contrast to the more wide spread ligand activation of estrogen receptors by estrogen

Characterizing, modelling and understanding the climate variability of the deep water formation in the North-Western Mediterranean Sea

Observing, modelling and understanding the climate-scale variability of the deep water formation (DWF) in the North-Western Mediterranean Sea remains today very challenging. In this study, we first characterize the interannual variability of this phenomenon by a thorough reanalysis of observations in order to establish reference time series. These quantitative indicators include 31 observed years for the yearly maximum mixed layer depth over the period 1980–2013 and a detailed multi-indicator description of the period 2007–2013. Then a 1980–2013 hindcast simulation is performed with a fully-coupled regional climate system model including the high-resolution representation of the regional atmosphere, ocean, land-surface and rivers. The simulation reproduces quantitatively well the mean behaviour and the large interannual variability of the DWF phenomenon. The model shows convection deeper than 1000 m in 2/3 of the modelled winters, a mean DWF rate equal to 0.35 Sv with maximum values of 1.7 (resp. 1.6) Sv in 2013 (resp. 2005). Using the model results, the winter-integrated buoyancy loss over the Gulf of Lions is identified as the primary driving factor of the DWF interannual variability and explains, alone, around 50 % of its variance. It is itself explained by the occurrence of few stormy days during winter. At daily scale, the Atlantic ridge weather regime is identified as favourable to strong buoyancy losses and therefore DWF, whereas the positive phase of the North Atlantic oscillation is unfavourable. The driving role of the vertical stratification in autumn, a measure of the water column inhibition to mixing, has also been analyzed. Combining both driving factors allows to explain more than 70 % of the interannual variance of the phenomenon and in particular the occurrence of the five strongest convective years of the model (1981, 1999, 2005, 2009, 2013). The model simulates qualitatively well the trends in the deep waters (warming, saltening, increase in the dense water volume, increase in the bottom water density) despite an underestimation of the salinity and density trends. These deep trends come from a heat and salt accumulation during the 1980s and the 1990s in the surface and intermediate layers of the Gulf of Lions before being transferred stepwise towards the deep layers when very convective years occur in 1999 and later. The salinity increase in the near Atlantic Ocean surface layers seems to be the external forcing that finally leads to these deep trends. In the future, our results may allow to better understand the behaviour of the DWF phenomenon in Mediterranean Sea simulations in hindcast, forecast, reanalysis or future climate change scenario modes. The robustness of the obtained results must be however confirmed in multi-model studies

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.Comment: Preprint to be submitted to The European Physical Journal

Design and construction of the MicroBooNE Cosmic Ray Tagger system

The MicroBooNE detector utilizes a liquid argon time projection chamber (LArTPC) with an 85 t active mass to study neutrino interactions along the Booster Neutrino Beam (BNB) at Fermilab. With a deployment location near ground level, the detector records many cosmic muon tracks in each beam-related detector trigger that can be misidentified as signals of interest. To reduce these cosmogenic backgrounds, we have designed and constructed a TPC-external Cosmic Ray Tagger (CRT). This sub-system was developed by the Laboratory for High Energy Physics (LHEP), Albert Einstein center for fundamental physics, University of Bern. The system utilizes plastic scintillation modules to provide precise time and position information for TPC-traversing particles. Successful matching of TPC tracks and CRT data will allow us to reduce cosmogenic background and better characterize the light collection system and LArTPC data using cosmic muons. In this paper we describe the design and installation of the MicroBooNE CRT system and provide an overview of a series of tests done to verify the proper operation of the system and its components during installation, commissioning, and physics data-taking

Ionization Electron Signal Processing in Single Phase LArTPCs II. Data/Simulation Comparison and Performance in MicroBooNE

The single-phase liquid argon time projection chamber (LArTPC) provides a large amount of detailed information in the form of fine-grained drifted ionization charge from particle traces. To fully utilize this information, the deposited charge must be accurately extracted from the raw digitized waveforms via a robust signal processing chain. Enabled by the ultra-low noise levels associated with cryogenic electronics in the MicroBooNE detector, the precise extraction of ionization charge from the induction wire planes in a single-phase LArTPC is qualitatively demonstrated on MicroBooNE data with event display images, and quantitatively demonstrated via waveform-level and track-level metrics. Improved performance of induction plane calorimetry is demonstrated through the agreement of extracted ionization charge measurements across different wire planes for various event topologies. In addition to the comprehensive waveform-level comparison of data and simulation, a calibration of the cryogenic electronics response is presented and solutions to various MicroBooNE-specific TPC issues are discussed. This work presents an important improvement in LArTPC signal processing, the foundation of reconstruction and therefore physics analyses in MicroBooNE.Comment: 54 pages, 36 figures; the first part of this work can be found at arXiv:1802.0870

Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC

The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Current induced on each TPC wire is amplified and shaped by custom low-power, low-noise ASICs immersed in the liquid argon. The digitization of the signal waveform occurs outside the cryostat. Using data from the first year of MicroBooNE operations, several excess noise sources in the TPC were identified and mitigated. The residual equivalent noise charge (ENC) after noise filtering varies with wire length and is found to be below 400 electrons for the longest wires (4.7 m). The response is consistent with the cold electronics design expectations and is found to be stable with time and uniform over the functioning channels. This noise level is significantly lower than previous experiments utilizing warm front-end electronics.Comment: 36 pages, 20 figure