Early-life stress is normally thought of as a major risk for psychiatric disorders, but many researchers have revealed that adversity early in life may enhance stress resilience later in life. Few ...studies have been performed in rodents to address the possibility that exposure to early-life stress may enhance stress resilience, and the underlying neural mechanisms are far from being understood. Here, we established a "two-hit" stress model in rats by applying two different early-life stress paradigms: predictable and unpredictable maternal separation (MS). Predictable MS during the postnatal period promotes resilience to adult restraint stress, while unpredictable MS increases stress susceptibility. We demonstrate that structural and functional impairments occur in glutamatergic synapses in pyramidal neurons of the medial prefrontal cortex (mPFC) in rats with unpredictable MS but not in rats with predictable MS. Then, we used differentially expressed gene (DEG) analysis of RNA sequencing data from the adult male PFC to identify a hub gene that is responsible for stress resilience. Oxytocin, a peptide hormone, was the highest ranked differentially expressed gene of these altered genes. Predictable MS increases the expression of oxytocin in the mPFC compared to normal raised and unpredictable MS rats. Conditional knockout of the oxytocin receptor in the mPFC was sufficient to generate excitatory synaptic dysfunction and anxiety behavior in rats with predictable MS, whereas restoration of oxytocin receptor expression in the mPFC modified excitatory synaptic function and anxiety behavior in rats subjected to unpredictable MS. These findings were further supported by the demonstration that blocking oxytocinergic projections from the paraventricular nucleus of the hypothalamus (PVN) to the mPFC was sufficient to exacerbate anxiety behavior in rats exposed to predictable MS. Our findings provide direct evidence for the notion that predictable MS promotes stress resilience, while unpredictable MS increases stress susceptibility via mPFC oxytocin signaling in rats.
Two types of coupled neural networks with reaction-diffusion terms are considered in this paper. In the first one, the nodes are coupled through their states. In the second one, the nodes are coupled ...through the spatial diffusion terms. For the former, utilizing Lyapunov functional method and pinning control technique, we obtain some sufficient conditions to guarantee that network can realize synchronization. In addition, considering that the theoretical coupling strength required for synchronization may be much larger than the needed value, we propose an adaptive strategy to adjust the coupling strength for achieving a suitable value. For the latter, we establish a criterion for synchronization using the designed pinning controllers. It is found that the coupled reaction-diffusion neural networks with state coupling under the given linear feedback pinning controllers can realize synchronization when the coupling strength is very large, which is contrary to the coupled reaction-diffusion neural networks with spatial diffusion coupling. Moreover, a general criterion for ensuring network synchronization is derived by pinning a small fraction of nodes with adaptive feedback controllers. Finally, two examples with numerical simulations are provided to demonstrate the effectiveness of the theoretical results.
Abstract
Organic radicals, which have unique doublet spin-configuration, provide an alternative method to overcome the efficiency limitation of organic light-emitting diodes (OLEDs) based on ...conventional fluorescent organic molecules. Further, they have made great breakthroughs in deep-red and near-infrared OLEDs. However, it is difficult to extend their fluorescence into a short-wavelength region because of the natural narrow bandgap of the organic radicals. Herein, we significantly expand the scope of luminescent radicals by showing a new platform of carbon-centered radicals derived from N-heterocyclic carbenes that produce blue to green emissions (444–529 nm). Time-dependent density functional theory calculations and experimental investigations disclose that the fluorescence originates from the high-energy excited states to the ground state, demonstrating an anti-Kasha behavior. The present work provides an efficient and modular approach toward a library of carbon-centered radicals that feature anti-Kasha’s rule emission, rendering them as potential new emitters in the short-wavelength region.
Prescription Drug Monitoring Programs (PDMP) are statewide databases that collect data on prescription of controlled substances. New York State mandates prescribers to consult the PDMP registry ...before prescribing a controlled substance such as opioid analgesics. The effect of mandatory PDMP on opioid drug prescriptions by dentists is not known. This study investigates the impact of mandatory PDMP on frequency and quantity of opioid prescriptions by dentists in a dental urgent care center. Based on the sample size estimate, we collected patient records of a 3-month period before and two consecutive 3-month periods after the mandatory PDMP implementation and analyzed the data on number of visits, treatment types and drug prescriptions using Chi-square tests. For patients who were prescribed pain medications, 452 (30.6%), 190 (14.1%), and 140 (9.6%) received opioid analgesics in the three study periods respectively, signifying a statistically significant reduction in the number of opioid prescriptions after implementation of the mandatory PDMP (p<0.05). Total numbers of prescribed opioid pills in a 3-month period decreased from 5096 to 1120, signifying a 78% reduction in absolute quantity. Prescriptions for non-opioid analgesics acetaminophen increased during the same periods (p<0.05). We conclude that the mandatory PDMP significantly affected the prescription pattern for pain medications by dentists. Such change in prescription pattern represents a shift towards the evidence-based prescription practices for acute postoperative pain.
A complex dynamical network consisting of N identical neural networks with reaction-diffusion terms is considered in this paper. First, several passivity definitions for the systems with different ...dimensions of input and output are given. By utilizing some inequality techniques, several criteria are presented, ensuring the passivity of the complex dynamical network under the designed adaptive law. Then, we discuss the relationship between the synchronization and output strict passivity of the proposed network model. Furthermore, these results are extended to the case when the topological structure of the network is undirected. Finally, two examples with numerical simulations are provided to illustrate the correctness and effectiveness of the proposed results.
Predicting species' potential geographical range by species distribution models (SDMs) is central to understand their ecological requirements. However, the effects of using different modeling ...techniques need further investigation. In order to improve the prediction effect, we need to assess the predictive performance and stability of different SDMs.
We collected the distribution data of five common tree species (Pinus massoniana, Betula platyphylla, Quercus wutaishanica, Quercus mongolica and Quercus variabilis) and simulated their potential distribution area using 13 environmental variables and six widely used SDMs: BIOCLIM, DOMAIN, MAHAL, RF, MAXENT, and SVM. Each model run was repeated 100 times (trials). We compared the predictive performance by testing the consistency between observations and simulated distributions and assessed the stability by the standard deviation, coefficient of variation, and the 99% confidence interval of Kappa and AUC values.
The mean values of AUC and Kappa from MAHAL, RF, MAXENT, and SVM trials were similar and significantly higher than those from BIOCLIM and DOMAIN trials (p<0.05), while the associated standard deviations and coefficients of variation were larger for BIOCLIM and DOMAIN trials (p<0.05), and the 99% confidence intervals for AUC and Kappa values were narrower for MAHAL, RF, MAXENT, and SVM. Compared to BIOCLIM and DOMAIN, other SDMs (MAHAL, RF, MAXENT, and SVM) had higher prediction accuracy, smaller confidence intervals, and were more stable and less affected by the random variable (randomly selected pseudo-absence points).
According to the prediction performance and stability of SDMs, we can divide these six SDMs into two categories: a high performance and stability group including MAHAL, RF, MAXENT, and SVM, and a low performance and stability group consisting of BIOCLIM, and DOMAIN. We highlight that choosing appropriate SDMs to address a specific problem is an important part of the modeling process.
This paper considers a complex dynamical network model, in which the input and output vectors have different dimensions. We, respectively, investigate the passivity and the relationship between ...output strict passivity and output synchronization of the complex dynamical network with fixed and adaptive coupling strength. First, two new passivity definitions are proposed, which generalize some existing concepts of passivity. By constructing appropriate Lyapunov functional, some sufficient conditions ensuring the passivity, input strict passivity and output strict passivity are derived for the complex dynamical network with fixed coupling strength. In addition, we also reveal the relationship between output strict passivity and output synchronization of the complex dynamical network with fixed coupling strength. By employing the relationship between output strict passivity and output synchronization, a sufficient condition for output synchronization of the complex dynamical network with fixed coupling strength is established. Then, we extend these results to the case when the coupling strength is adaptively adjusted. Finally, two examples with numerical simulations are provided to demonstrate the effectiveness of the proposed criteria.
Understanding the genetic changes underlying phenotypic variation in sheep (Ovis aries) may facilitate our efforts towards further improvement. Here, we report the deep resequencing of 248 sheep ...including the wild ancestor (O. orientalis), landraces, and improved breeds. We explored the sheep variome and selection signatures. We detected genomic regions harboring genes associated with distinct morphological and agronomic traits, which may be past and potential future targets of domestication, breeding, and selection. Furthermore, we found non-synonymous mutations in a set of plausible candidate genes and significant differences in their allele frequency distributions across breeds. We identified PDGFD as a likely causal gene for fat deposition in the tails of sheep through transcriptome, RT-PCR, qPCR, and Western blot analyses. Our results provide insights into the demographic history of sheep and a valuable genomic resource for future genetic studies and improved genome-assisted breeding of sheep and other domestic animals.
Marine dinoflagellates produce remarkable organic molecules, particularly those with polyoxygenated long‐carbon‐chain backbones, namely super‐carbon‐chain compounds (SCCCs), characterized by the ...presence of numerous stereogenic carbon centers on acyclic polyol carbon chains. Even today, it is a challenge to determine the absolute configurations of these compounds. In this work, the planar structures and absolute configurations of two highly flexible SCCCs, featuring either a C69‐ or C71‐linear carbon backbone, gibbosols A and B, respectively, each containing thirty‐seven stereogenic carbon centers, were unambiguously established by a combined chemical, spectroscopic, and computational approach. The discovery of gibbosols A and B with two hydrophilic acyclic polyol chains represents an unprecedented class of SCCCs. A reasonable convergent strategy for the biosynthesis of these SCCCs was proposed.
Super‐carbon‐chain compounds: Gibbosols A and B, obtained from the South China Sea dinoflagellate Amphidinium gibbosum, are stereochemically challenging, flexible super‐carbon‐chain compounds. A combined chemical, spectroscopic, and computational approach was successfully employed to establish the absolute configurations of thirty‐seven stereogenic carbon centers within these structurally intriguing marine natural products.
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