Developmental Monoamine Signaling Impacts Adult Affective and Aggressive Behaviors

Most neuropsychiatric disorders have developmental origins and an emerging model postulates that such developmental vulnerability is often restricted to sensitive periods. The concept of sensitive developmental periods for the indelible modulation of complex behaviors is similar to that described for sensory systems (e.g. visual cortex, ocular dominance plasticity), but effected behaviors, modulating factors, and underlying mechanisms are much less well understood. Furthering our knowledge of sensitive periods that determine the developmental trajectory of complex behaviors is a necessary step towards improving diagnosis, prevention and treatment approaches for neuropsychiatric disorders. To fulfill this mission, I here investigate how genetic and environmental risk factors act during sensitive periods of brain development to alter adult behavior and thereby confer vulnerability to neuropsychiatric disorders. My thesis is divided into four chapters. Chapter I provides general background and significance information relevant to chapters II-IV. Chapter II focuses on elucidating and comparing the consequences of developmental serotonin (5-HT) transporter (5-HTT) and monoamine oxidase A (MAOA) blockade. Pharmacologic MAOA or 5-HTT blockade in adulthood has antidepressant and anxiolytic efficacy. Yet, genetically conferred MAOA or 5-HTT hypo-activity is associated with altered aggression and increased anxiety/depression. Here I test the hypothesis that increased monoamine signaling during development causes these paradoxical aggressive and affective phenotypes. I find that pharmacologic MAOA blockade during early postnatal development (P2-P21) increases anxiety- and depression-like behavior in mice, mimicking the effect of P2-21 5-HTT inhibition. Moreover, MAOA or dopamine transporter (but not norepinephrine transporter) blockade during peri-adolescence (P22-P41) increases adult aggressive behavior. 5-HTT blockade from P2-P21 or P22-P41 reduces adult aggressive behavior. Altered aggression correlates positively with locomotor response to amphetamine challenge in adulthood and striatal dopamine and DOPAC content is increased while brainstem 5-HIAA content is decreased in high aggression. Taken together, these data suggest that genetic and pharmacologic factors impacting dopamine and serotonin signaling during sensitive developmental periods confer risk for aggressive and emotional dysfunction in humans. Chapter III focuses on refining the 5-HT sensitive period affecting anxiety and depression-like behavior. Specifically, I hypothesized that the identified P2-21 period, which encompasses many developmental processes, contains a narrower critical period, affecting fewer developmental processes but having the same impact on adult behavior. This experiment serves two purposes: First, I seek to gain insight into the neural substrates and possible developmental processes underlying developmental programing of anxiety- and depression-like behaviors through 5-HT signaling. Second, I aim at providing translationally relevant data, informing clinical and epidemiological studies as to which developmental window might be sensitive to 5-HT altering factors in humans. This thesis research shows that postnatal fluoxetine (PN-FLX) treatment from P2-11 leads to increased adult anxiety- and depressive-like behavior in mice, while PN-FLX treatment from P12-21 or P22-41 has no effect in adult anxiety- and depressive-like behavior. In addition, adult chronic FLX treatment could not rescue the behavioral phenotype produced by P2-11 5-HTT blockade. Chapter IV focuses on the role of 5-HT2A receptor signaling in mediating the effect of P2-11 5-HTT blockade on adult behavior. Htr2a-/- mice display reduced conflict anxiety. Because 5-HT2A receptor antagonists do not reduce conflict anxiety in adulthood, I hypothesized that the behavioral htr2a-/- phenotype is at least partially of developmental origin, which would further indicate that increased 5-HT2A receptor signaling during development could increase conflict anxiety. To investigate this hypothesis, I analyzed the effect of P2-11 5-HTT blockade on anxiety and depression-like behaviors in htr2a+/+, +/-, and -/- mice. Supporting my hypothesis, I find that absence of htr2a improved performance of PN-FLX treated mice in the novelty suppressed feeding task, by decreasing the latency to feed to control levels. Absence of htr2a, however, did not have ameliorative effects on PN-FLX phenotypes in the open field and shock escape tests. In summary, these data demonstrate that 5-HT2A receptor signaling mediates some but not all consequences of increased P2-11 5-HT signaling. Taken together, in my thesis work I identified and characterized two sensitive developmental periods whereupon early-life perturbation of monoamine signaling alters adult behavior: an early postnatal (P2-P11) 5-HT-sensitive period that affects anxiety and depression-related behaviors and a later peri-adolescent (P22-P41) DA- and 5-HT-sensitive period altering aggression and behavioral sensitivity amphetamine. These data give insight into the etiology of neuropsychiatric disorders and should ultimately help improving diagnosis, prevention and treatment approaches

Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System

Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system.</p

A Triple-Memristor Hopfield Neural Network With Space Multi-Structure Attractors And Space Initial-Offset Behaviors

© 2023 IEEE. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1109/TCAD.2023.3287760Memristors have recently demonstrated great promise in constructing memristive neural networks with complex dynamics. This paper proposes a memristive Hopfield neural network with three memristive coupling synaptic weights. The complex dynamical behaviors of the triple-memristor Hopfield neural network (TM-HNN), which have never been observed in previous Hopfield-type neural networks, include space multi-structure chaotic attractors and space initial-offset coexisting behaviors. Bifurcation diagrams, Lyapunov exponents, phase portraits, Poincaré maps, and basins of attraction are used to reveal and examine the specific dynamics. Theoretical analysis and numerical simulation show that the number of space multi-structure attractors can be adjusted by changing the control parameters of the memristors, and the position of space coexisting attractors can be changed by switching the initial states of the memristors. Extreme multistability emerges as a result of the TM-HNN’s unique dynamical behaviors, making it more suitable for applications based on chaos. Moreover, a digital hardware platform is developed and the space multi-structure attractors as well as the space coexisting attractors are experimentally demonstrated. Finally, we design a pseudo-random number generator to explore the potential application of the proposed TM-HNN.Peer reviewe

Hydrocode modeling of the spallation process during hypervelocity impacts: Implications for the ejection of Martian meteorites

Hypervelocity ejection of material by impact spallation is considered a plausible mechanism for material exchange between two planetary bodies. We have modeled the spallation process during vertical impacts over a range of impact velocities from 6 to 21 km/s using both grid- and particle-based hydrocode models. The Tillotson equations of state, which are able to treat the nonlinear dependence of density on pressure and thermal pressure in the strongly shocked matter, were used to study the hydrodynamic and thermodynamic response after impacts. The effects of material strength and gravitational acceleration were not considered. A two-dimensional time-dependent pressure field within a 1.5-fold projectile radius from the impact point was investigated in cylindrical coordinates to address the generation of spalled material. A resolution test was also performed to reject ejected materials with peak pressures that were too low due to artificial viscosity. The relationship between ejection velocity veject and peak pressure Ppeak was also derived. Our approach shows that late stage acceleration in an ejecta curtain occurs due to the compressible nature of the ejecta, resulting in an ejection velocity that can be higher than the ideal maximum of the resultant particle velocity after passage of a shock wave. We also calculate the ejecta mass that can escape from a planet like Mars (i.e., veject higher than 5 km/s) that matches the petrographic constraints from Martian meteorites, and which occurs when Ppeak from 30-50 GPa. Although the mass of such ejecta is limited to from 0.1-1 percent of the projectile mass in vertical impacts, this is sufficient for spallation to have been a plausible mechanism for the ejection of Martian meteorites. Finally, we propose that impact spallation is a plausible mechanism for the generation of tektites.Comment: 67 pages, 28 figures, accepted for publication in Icaru

Activation of Orexin System Stimulates CaMKII Expression

Hyperactivity of the orexin system within the paraventricular nucleus (PVN) has been shown to contribute to increased sympathetic nerve activity (SNA) and blood pressure (BP) in rodent animals. However, the underlying molecular mechanisms remain unclear. Here, we test the hypothesis that orexin system activation stimulates calcium/calmodulin-dependent kinase II (CaMKII) expression and activation, and stimulation of CaMKII expressing PVN neurons increases SNA and BP. Real-time PCR and/or western blot were carried out to test the effect of orexin-A administration on CaMKII expression in the PVN of normal Sprague Dawley (SD) rats and orexin receptor 1 (OX1R) expressing PC12 cells. Immunostaining was performed to assess OX1R cellular localization in the PVN of SD rats as well as orexin-A treatment on CaMKII activation in cultured hypothalamic neurons. In vivo sympathetic nerve recordings were employed to test the impact of optogenetic stimulation of CaMKII-expressing PVN neurons on the renal SNA (RSNA) and BP. The results showed that intracerebroventricular injection of orexin-A into the SD rat increases mRNA expression of CaMKII subunits in the PVN. In addition, Orexin-A treatment increases CaMKII expression and its phosphorylation in OX1R-expressing PC12 cells. Furthermore, Orexin-A treatment increases CaMKII activation in cultured hypothalamic neurons from neonatal SD rats. Finally, optogenetic excitation of PVN CaMKII-expressing neurons results in robust increases in RSNA and BP in SD rats. Our results suggest that increased orexin system activity activates CaMKII expression in cardiovascular relevant regions, and this may be relevant to the downstream cardiovascular effects of CaMKII

Target dose conversion modeling from pencil beam (PB) to Monte Carlo (MC) for lung SBRT

Background: A challenge preventing routine clinical implementation of Monte Carlo (MC)-based lung SBRT is the difficulty of reinterpreting historical outcome data calculated with inaccurate dose algorithms, because the target dose was found to decrease to varying degrees when recalculated with MC. The large variability was previously found to be affected by factors such as tumour size, location, and lung density, usually through sub-group comparisons. We hereby conducted a pilot study to systematically and quantitatively analyze these patient factors and explore accurate target dose conversion models, so that large-scale historical outcome data can be correlated with more accurate MC dose without recalculation. Methods: Twenty-one patients that underwent SBRT for early-stage lung cancer were replanned with 6MV 360° dynamic conformal arcs using pencil-beam (PB) and recalculated with MC. The percent D95 difference (PB-MC) was calculated for the PTV and GTV. Using single linear regression, this difference was correlated with the following quantitative patient indices: maximum tumour diameter (MaxD); PTV and GTV volumes; minimum distance from tumour to soft tissue (dmin); and mean density and standard deviation of the PTV, GTV, PTV margin, lung, and 2 mm, 15 mm, 50 mm shells outside the PTV. Multiple linear regression and artificial neural network (ANN) were employed to model multiple factors and improve dose conversion accuracy. Results: Single linear regression with PTV D95 deficiency identified the strongest correlation on mean-density (location) indices, weaker on lung density, and the weakest on size indices, with the following R2 values in decreasing orders: shell2mm (0.71), PTV (0.68), PTV margin (0.65), shell15mm (0.62), shell50mm (0.49), lung (0.40), dmin (0.22), GTV (0.19), MaxD (0.17), PTV volume (0.15), and GTV volume (0.08). A multiple linear regression model yielded the significance factor of 3.0E-7 using two independent features: mean density of shell2mm (P = 1.6E-7) and PTV volume (P = 0.006). A 4-feature ANN model slightly improved the modeling accuracy. Conclusion: Quantifiable density features were proposed, replacing simple central/peripheral location designation, which showed strong correlations with PB-to-MC target dose conversion magnitude, followed by lung density and target size. Density in the immediate outer and inner areas of the PTV showed the strongest correlations. A multiple linear regression model with one such feature and PTV volume established a high significance factor, improving dose conversion accuracy

Target dose conversion modeling from pencil beam (PB) to Monte Carlo (MC) for lung SBRT

Background: A challenge preventing routine clinical implementation of Monte Carlo (MC)-based lung SBRT is the difficulty of reinterpreting historical outcome data calculated with inaccurate dose algorithms, because the target dose was found to decrease to varying degrees when recalculated with MC. The large variability was previously found to be affected by factors such as tumour size, location, and lung density, usually through sub-group comparisons. We hereby conducted a pilot study to systematically and quantitatively analyze these patient factors and explore accurate target dose conversion models, so that large-scale historical outcome data can be correlated with more accurate MC dose without recalculation. Methods: Twenty-one patients that underwent SBRT for early-stage lung cancer were replanned with 6MV 360° dynamic conformal arcs using pencil-beam (PB) and recalculated with MC. The percent D95 difference (PB-MC) was calculated for the PTV and GTV. Using single linear regression, this difference was correlated with the following quantitative patient indices: maximum tumour diameter (MaxD); PTV and GTV volumes; minimum distance from tumour to soft tissue (dmin); and mean density and standard deviation of the PTV, GTV, PTV margin, lung, and 2 mm, 15 mm, 50 mm shells outside the PTV. Multiple linear regression and artificial neural network (ANN) were employed to model multiple factors and improve dose conversion accuracy. Results: Single linear regression with PTV D95 deficiency identified the strongest correlation on mean-density (location) indices, weaker on lung density, and the weakest on size indices, with the following R2 values in decreasing orders: shell2mm (0.71), PTV (0.68), PTV margin (0.65), shell15mm (0.62), shell50mm (0.49), lung (0.40), dmin (0.22), GTV (0.19), MaxD (0.17), PTV volume (0.15), and GTV volume (0.08). A multiple linear regression model yielded the significance factor of 3.0E-7 using two independent features: mean density of shell2mm (P = 1.6E-7) and PTV volume (P = 0.006). A 4-feature ANN model slightly improved the modeling accuracy. Conclusion: Quantifiable density features were proposed, replacing simple central/peripheral location designation, which showed strong correlations with PB-to-MC target dose conversion magnitude, followed by lung density and target size. Density in the immediate outer and inner areas of the PTV showed the strongest correlations. A multiple linear regression model with one such feature and PTV volume established a high significance factor, improving dose conversion accuracy

Wet and Dry Atmospheric Depositions of Inorganic Nitrogen during Plant Growing Season in the Coastal Zone of Yellow River Delta

The ecological problems caused by dry and wet deposition of atmospheric nitrogen have been widespread concern in the world. In this study, wet and dry atmospheric depositions were monitored in plant growing season in the coastal zone of the Yellow River Delta (YRD) using automatic sampling equipment. The results showed that SO42- and Na+ were the predominant anion and cation, respectively, in both wet and dry atmospheric depositions. The total atmospheric nitrogen deposition was ~2264.24 mg m−2, in which dry atmospheric nitrogen deposition was about 32.02%. The highest values of dry and wet atmospheric nitrogen deposition appeared in May and August, respectively. In the studied area, NO3-–N was the main nitrogen form in dry deposition, while the predominant nitrogen in wet atmospheric deposition was NH4+–N with ~56.51% of total wet atmospheric nitrogen deposition. The average monthly attribution rate of atmospheric deposition of NO3-–N and NH4+–N was ~31.38% and ~20.50% for the contents of NO3-–N and NH4+–N in 0–10 cm soil layer, respectively, suggested that the atmospheric nitrogen was one of main sources for soil nitrogen in coastal zone of the YRD