Mechanisms of estradiol in fear circuitry: implications for sex differences in psychopathology

Over the past two decades, substantial knowledge has been attained about the mechanisms underlying the acquisition and subsequent extinction of conditioned fear. Knowledge gained on the biological basis of Pavlovian conditioning has led to the general acceptance that fear extinction may be a useful model in understanding the underlying mechanisms in the pathophysiology of anxiety disorders and may also be a good model for current therapies treating these disorders. Lacking in the current knowledge is how men and women may or may not differ in the biology of fear and its extinction. It is also unclear how the neural correlates of fear extinction may mediate sex differences in the etiology, maintenance, and prevalence of psychiatric disorders. In this review, we begin by highlighting the epidemiological differences in incidence rate. We then discuss how estradiol (E2), a primary gonadal hormone, may modulate the mechanisms of fear extinction and mediate some of the sex differences observed in psychiatric disorders

Radiative Heating in MSL Entry: Comparison of Flight Heating Discrepancy to Ground Test and Predictive Models

During the recent entry of the Mars Science Laboratory (MSL), the heat shield was equipped with thermocouple stacks to measure in-depth heating of the thermal protection system (TPS). When only convective heating was considered, the derived heat flux from gauges in the stagnation region was found to be underpredicted by as much as 17 W/sq cm, which is significant compared to the peak heating of 32 W/sq cm. In order to quantify the contribution of radiative heating phenomena to the discrepancy, ground tests and predictive simulations that replicated the MSL entry trajectory were performed. An analysis is carried through to assess the quality of the radiation model and the impact to stagnation line heating. The impact is shown to be significant, but does not fully explain the heating discrepancy

A.R.G! Augmented Reality and Gait: Analyzing the Influence of Cues on Gait Patterns in Augmented Reality

Use of Augmented Reality (AR) technology for rehabilitation has drastically increased in recent years. While theoretically AR can be used to cue gait adaptations such as changes to step length and cadence through visual and auditory cues, it is still unknown how people respond to the technology. PURPOSE: To assess the feasibility of external visual and auditory cues delivered through AR on spatiotemporal gait outcomes in a healthy, young population. METHODS: 20 healthy participants between age 18 and 35 were screened and recruited to perform randomized gait trials consisting of four different cueing conditions. The participants wore a Magic Leap One AR headset with a custom-designed cueing application. Participants were instructed to walk 10 steps under one of four cueing conditions provided by the AR application: No Cues (NC) (i.e., natural gait), Visual (V), Auditory (A), and Visual and Auditory (VA). Each condition was completed three times in a randomized order for a total of 12 trials per participant. An Inertial Measurement Unit (IMU) system was used to collect spatiotemporal gait data. A System Usability Survey (SUS) was administered after each participant completed their trials to determine the usability of our novel application and to determine whether the reported usability of the system was related to changes in gait variability. RESULTS: Preliminary results indicate all cueing conditions exhibited a significantly faster cadence compared to NC trials. Surprisingly, the cadence variability increased across all A trials. Increased system usability SUS results were significantly correlated with increased percent stance variability across A trials. V trials exhibited significantly decreased stride lengths compared to NC. Combined (AV) cues had no effect on gait outcomes. CONCLUSION: Our findings reinforced that certain visual and auditory cues affect gait parameters, albeit in a direction opposite of what was expected (e.g., greater cadence variability with auditory cues). These results provide insight into how healthy populations respond to cues delivered through AR, as well as provide a foundation for future studies to implement this technology with clinical populations such as those with Parkinson’s disease

A review of the dynamic modeling approaches for characterizing fluid flow in naturally fractured reservoirs

Fluid flow in fractured media has been studied for decades and received considerable attention in the oil and gas industry because of the high productivity of naturally fractured reservoirs. Due to formation complexity and reservoir heterogeneity, characterizing fluid flow with an appropriate reservoir model presents a challenging task that differs relatively from homogeneous conventional reservoirs in many aspects of view, including geological, petrophysical, production, and economics. In most fractured reservoirs, fracture networks create complex pathways that affect hydrocarbon flow, well performance, hence reservoir characterization. A better and comprehensive understanding of the available reservoir modeling approaches is much needed to accurately characterize fluid flow behavior in NFRs. Therefore, in this paper, a perspective review of the available modeling approaches was presented for fluid flow characterization in naturally fractured medium. Modeling methods were evaluated in terms of their description, application, advantages, and disadvantages. This study has also included the applications of these reservoir models in fluid flow characterizing studies and governing equations for fluid flow. Dual continuum models were proved to be better than single continuum models in the presence of large scale fractures. In comparison, discrete models were more appropriate for reservoirs that contain a smaller number of fractures. However, hybrid modeling was the best method to provide accurate and scalable fluid flow modeling. It is our understanding that this paper will bridge the gap between the fundamental understanding and application of NFRs modeling approaches and serve as a useful reference for engineers and researchers for present and future applications

Intolerance of uncertainty predicts fear extinction in amygdala-ventromedial prefrontal cortical circuitry

Background: Coordination of activity between the amygdala and ventromedial prefrontal cortex (vmPFC) is important for fear-extinction learning. Aberrant recruitment of this circuitry is associated with anxiety disorders. Here, we sought to determine if individual differences in future threat uncertainty sensitivity, a potential risk factor for anxiety disorders, underly compromised recruitment of fear extinction circuitry. Twenty-two healthy subjects completed a cued fear conditioning task with acquisition and extinction phases. During the task, pupil dilation, skin conductance response, and functional magnetic resonance imaging were acquired. We assessed the temporality of fear extinction learning by splitting the extinction phase into early and late extinction. Threat uncertainty sensitivity was measured using self-reported intolerance of uncertainty (IU). Results: During early extinction learning, we found low IU scores to be associated with larger skin conductance responses and right amygdala activity to learned threat vs. safety cues, whereas high IU scores were associated with no skin conductance discrimination and greater activity within the right amygdala to previously learned safety cues. In late extinction learning, low IU scores were associated with successful inhibition of previously learned threat, reflected in comparable skin conductance response and right amgydala activity to learned threat vs. safety cues, whilst high IU scores were associated with continued fear expression to learned threat, indexed by larger skin conductance and amygdala activity to threat vs. safety cues. In addition, high IU scores were associated with greater vmPFC activity to threat vs. safety cues in late extinction. Similar patterns of IU and extinction learning were found for pupil dilation. The results were specific for IU and did not generalize to self-reported trait anxiety. Conclusions: Overall, the neural and psychophysiological patterns observed here suggest high IU individuals to disproportionately generalize threat during times of uncertainty, which subsequently compromises fear extinction learning. More broadly, these findings highlight the potential of intolerance of uncertainty-based mechanisms to help understand pathological fear in anxiety disorders and inform potential treatment targets

Predicting Impaired Extinction of Traumatic Memory and Elevated Startle

Emotionally traumatic experiences can lead to debilitating anxiety disorders, such as phobias and Post-Traumatic Stress Disorder (PTSD). Exposure to such experiences, however, is not sufficient to induce pathology, as only up to one quarter of people exposed to such events develop PTSD. These statistics, combined with findings that smaller hippocampal size prior to the trauma is associated with higher risk of developing PTSD, suggest that there are pre-disposing factors for such pathology. Because prospective studies in humans are limited and costly, investigating such pre-dispositions, and thus advancing understanding of the genesis of such pathologies, requires the use of animal models where predispositions are identified before the emotional trauma. Most existing animal models are retrospective: they classify subjects as those with or without a PTSD-like phenotype long after experiencing a traumatic event. Attempts to create prospective animal models have been largely unsuccessful.Here we report that individual predispositions to a PTSD-like phenotype, consisting of impaired rate and magnitude of extinction of an emotionally traumatic event coupled with long-lasting elevation of acoustic startle responses, can be revealed following exposure to a mild stressor, but before experiencing emotional trauma. We compare, in rats, the utility of several classification criteria and report that a combination of criteria based on acoustic startle responses and behavior in an anxiogenic environment is a reliable predictor of a PTSD-like phenotype.There are individual predispositions to developing impaired extinction and elevated acoustic startle that can be identified after exposure to a mildly stressful event, which by itself does not induce such a behavioral phenotype. The model presented here is a valuable tool for studying the etiology and pathophysiology of anxiety disorders and provides a platform for testing behavioral and pharmacological interventions that can reduce the probability of developing pathologic behaviors associated with such disorders

Can we identify non-stationary dynamics of trial-to-trial variability?"

Identifying sources of the apparent variability in non-stationary scenarios is a fundamental problem in many biological data analysis settings. For instance, neurophysiological responses to the same task often vary from each repetition of the same experiment (trial) to the next. The origin and functional role of this observed variability is one of the fundamental questions in neuroscience. The nature of such trial-to-trial dynamics however remains largely elusive to current data analysis approaches. A range of strategies have been proposed in modalities such as electro-encephalography but gaining a fundamental insight into latent sources of trial-to-trial variability in neural recordings is still a major challenge. In this paper, we present a proof-of-concept study to the analysis of trial-to-trial variability dynamics founded on non-autonomous dynamical systems. At this initial stage, we evaluate the capacity of a simple statistic based on the behaviour of trajectories in classification settings, the trajectory coherence, in order to identify trial-to-trial dynamics. First, we derive the conditions leading to observable changes in datasets generated by a compact dynamical system (the Duffing equation). This canonical system plays the role of a ubiquitous model of non-stationary supervised classification problems. Second, we estimate the coherence of class-trajectories in empirically reconstructed space of system states. We show how this analysis can discern variations attributable to non-autonomous deterministic processes from stochastic fluctuations. The analyses are benchmarked using simulated and two different real datasets which have been shown to exhibit attractor dynamics. As an illustrative example, we focused on the analysis of the rat's frontal cortex ensemble dynamics during a decision-making task. Results suggest that, in line with recent hypotheses, rather than internal noise, it is the deterministic trend which most likely underlies the observed trial-to-trial variability. Thus, the empirical tool developed within this study potentially allows us to infer the source of variability in in-vivo neural recordings

Low Cost Entry, Descent, and Landing (EDL) Instrumentation for Planetary Missions

No abstract availabl

Alternative lengthening of telomeres, ATRX loss and H3â K27M mutations in histologically defined pilocytic astrocytoma with anaplasia

Anaplasia may be identified in a subset of tumors with a presumed pilocytic astrocytoma (PA) component or piloid features, which may be associated with aggressive behavior, but the biologic basis of this change remains unclear. Fiftyâ seven resections from 36 patients (23 M, 13 F, mean age 32 years, range 3â 75) were included. A clinical diagnosis of NF1 was present in 8 (22%). Alternative lengthening of telomeres (ALT) was assessed by telomereâ specific FISH and/or CISH. A combination of immunohistochemistry, DNA sequencing and FISH were used to study BRAF, ATRX, CDKN2A/p16, mutant IDH1 p.R132H and H3â K27M proteins. ALT was present in 25 (69%) cases and ATRX loss in 20 (57%), mostly in the expected association of ALT+/ATRXâ (20/24, 83%) or ALTâ /ATRX+ (11/11, 100%). BRAF duplication was present in 8 (of 26) (31%). H3â K27M was present in 5 of 32 (16%) cases, all with concurrent ATRX loss and ALT. ALT was also present in 9 (of 11) cases in the benign PA precursor, 7 of which also had ATRX loss in both the precursor and the anaplastic tumor. In a single pediatric case, ALT and ATRX loss developed in the anaplastic component only, and in another adult case, ALT was present in the PAâ A component only, but ATRX was not tested. Features associated with worse prognosis included subtotal resection, adult vs. pediatric, presence of a PA precursor preceding a diagnosis of anaplasia, necrosis, presence of ALT and ATRX expression loss. ALT and ATRX loss, as well as alterations involving the MAPK pathway, are frequent in PA with anaplasia at the time of development of anaplasia or in their precursors. Additionally, a small subset of PA with anaplasia have H3â K27M mutations. These findings further support the concept that PA with anaplasia is a neoplasm with heterogeneous genetic features and alterations typical of both PA and diffuse gliomas.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147190/1/bpa12646_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147190/2/bpa12646.pd