阻断子宫动脉建立FGR大鼠模型的研究

目的通过暂时阻断妊娠期大鼠子宫血供的方法建立子宫缺血引起胎儿生长受限的动物模型。方法根据大鼠子宫动脉是卵巢动脉的一个分支的解剖特点,于孕鼠妊娠第15天时施行手术暂时阻断卵巢动脉并于第21天行剖宫产术,术后称量新生胎仔体重及胎盘、脑、心、肝、肺、肾等重要脏器重量,对比各组间新生胎仔的预后的不同,并对照研究阻断血供10、20、30及40 min对胎仔的不同影响。结果妊娠晚期阻断孕鼠卵巢动脉20min可成功构建胎儿生长受限模型,这种方法与阻断动脉血流30或40 min相比,手术时间短,技术要求不高,胎仔死亡率与对照组差异无显著性(P>0.05)。各实验组较对照组新生胎仔体重及胎盘、各重要脏器重量均明显降低(P<0.05)。结论通过阻断卵巢动脉从而阻断子宫动脉血流,成功建立缺血缺氧性FGR孕鼠模型。该模型重复性好,操作简便,并可成功设立同体对照,为进行FGR相关的产科理论研究提供了一个有利的技术平台。     

Inhibition in Adults with Attention Deficit/Hyperactivity Disorder: Event-Related Potentials in the Stop Task

The core deficit in Attention Deficit/Hyperactivity Disorder (ADHD) may be a deficiency in executive functions, particularly the processes that are associated with the inhibition of predominant responses. To test this notion in the adult population, healthy undergraduate volunteers and students with ADHD symptoms performed a visual Stop Signal Task (Logan et al. J Exp Psychol: Hum Percept Perform 10:276–291, 1984) while Event-Related brain Potentials were recorded. The two groups did not differ on behavioral measures of performance, but there was a significant difference in the N2–P3 component. These results underline the robustness of an N2–P3 difference between healthy adults and people with ADHD symptoms that have persisted into young adulthood.     

Quercetin, a flavonoid antioxidant, modulates endothelium-derived nitric oxide bioavailability in diabetic rat aortas

The present work examined the effect of chronic oral administration of quercetin, a flavonoid antioxidant, on blood glucose, vascular function and oxidative stress in STZ-induced diabetic rats. Male Wistar-Kyoto (WKY) rats were randomized into euglycemic, untreated diabetic, vehicle (1% w/v methylcellulose)-treated diabetic, which served as control, or quercetin (10mgkg(-1) body weight)-treated diabetic groups and treated orally for 6 weeks. Quercetin treatment reduced blood glucose level in diabetic rats. Impaired relaxations to endothelium-dependent vasodilator acetylcholine (ACh) and enhanced vasoconstriction responses to alpha(1)-adrenoceptor agonist phenylephrine (PE) in diabetic rat aortic rings were restored to euglycemic levels by quercetin treatment. Pretreatment with N(omega)-nitro-l-arginine methyl ester (l-NAME, 10microM) or methylene blue (10microM) completely blocked but indomethacin (10microM) did not affect relaxations to ACh in aortic rings from vehicle- or quercetin-treated diabetic rats. PE-induced vasoconstriction with an essentially similar magnitude in vehicle- or quercetin-treated diabetic rat aortic rings pretreated with l-NAME (10microM) plus indomethacin (10microM). Quercetin treatment reduced plasma malonaldehyde (MDA) plus 4-hydroxyalkenals (4-HNE) content as well as increased superoxide dismutase activity and total antioxidant capacity in diabetic rats. From the present study, it can be concluded that quercetin administration to diabetic rats restores vascular function, probably through enhancement in the bioavailability of endothelium-derived nitric oxide coupled to reduced blood glucose level and oxidative stress.     

Novel optimal temperature profile for acidification process of <Emphasis Type="Italic">Lactobacillus bulgaricus</Emphasis> and <Emphasis Type="Italic">Streptococcus thermophilus</Emphasis> in yoghurt fermentation using artificial neural network and genetic algorithm

The acidification behavior of Lactobacillus bulgaricus and Streptococcus thermophilus for yoghurt production was investigated along temperature profiles within the optimal window of 38–44 °C. For the optimal acidification temperature profile search, an optimization engine module built on a modular artificial neural network (ANN) and genetic algorithm (GA) was used. Fourteen batches of yoghurt fermentations were evaluated using different temperature profiles in order to train and validate the ANN sub-module. The ANN captured the nonlinear relationship between temperature profiles and acidification patterns on training data after 150 epochs. This served as an evaluation function for the GA. The acidification slope of the temperature profile was the performance index. The GA sub-module iteratively evolved better temperature profiles across generations using GA operations. The stopping criterion was met after 11 generations. The optimal profile showed an acidification slope of 0.06117 compared to an initial value of 0.0127 and at a set point sequence of 43, 38, 44, 43, and 39 °C. Laboratory evaluation of three replicates of the GA suggested optimum profile of 43, 38, 44, 43, and 39 °C gave an average slope of 0.04132. The optimization engine used (to be published elsewhere) could effectively search for optimal profiles of different physico-chemical parameters of fermentation processes.     

Some conceptual problems with the classical theory of behaviour

Behaviour is usually assumed to depend on the reach of a critical intensity--termed reactivity threshold--by its motivation. This view represents a simple, predictive theoretical framework in ethology and animal psychology. However, it is here argued that only the influence of an isolated motivation on behaviour can be explained that way; that such a view fails to account for behaviour when several motivations are jointly activated. Upon analysis, the classical theory of behaviour (CTB) proves to be under-specified and thus leads to three conceptual problems that make it logically inconsistent for the study of multiple motivations. A revision of the CTB, called anticipatory dynamics model (ADM), is then developed in order to bring a theoretical solution to these conceptual problems. The ADM hypothesizes that an organism's motivational interactions are due to the limitation of the organism's attentional resources.     

Shifts in the psychophysical function in rats

The primary goal was to compare results from a free-operant procedure with pigeons [Machado, A., Guilhardi, P., 2000. Shifts in the psychometric function and their implications for models of timing. J. Exp. Anal. Behav. 74, 25-54, Experiment 2] with new results obtained with rats. The secondary goal was to compare the results of both experiments with dependent variables that were not used in the original publication. As in the original study with pigeons, rats were trained on a two-alternative free-operant psychophysical procedure in which left lever press responses were reinforced during the first and second quarters of a 60-s trial, and right lever press responses were reinforced during the third and fourth quarters of the trial. The quarters were reinforced according to four independent variable interval (VI) schedules of reinforcement. The VI duration was manipulated in each quarter, and shifts in the psychophysical functions that relate response rate with time since trial onset were measured. The results obtained with rats were consistent with those previously obtained with pigeons. In addition, results not originally reported were also consistent between rats and pigeons, and provided insights into the perception, memory, and decision processes in Scalar Expectancy Theory and Learning-to-Time Theory.     

QNet: an agglomerative method for the construction of phylogenetic networks from weighted quartets

We present QNet, a method for constructing split networks from weighted quartet trees. QNet can be viewed as a quartet analogue of the distance-based Neighbor-Net (NNet) method for network construction. Just as NNet, QNet works by agglomeratively computing a collection of circular weighted splits of the taxa set which is subsequently represented by a planar split network. To illustrate the applicability of QNet, we apply it to a previously published Salmonella data set. We conclude that QNet can provide a useful alternative to NNet if distance data are not available or a character-based approach is preferred. Moreover, it can be used as an aid for determining when a quartet-based tree-building method may or may not be appropriate for a given data set. QNet is freely available for download.     

Neuromodulation by Glutamate and Acetylcholine can Change Circuit Dynamics by Regulating the Relative Influence of Afferent Input and Excitatory Feedback

Substances such as acetylcholine and glutamate act as both neurotransmitters and neuromodulators. As neuromodulators, they change neural information processing by regulating synaptic transmitter release, altering baseline membrane potential and spiking activity, and modifying long-term synaptic plasticity. Slice physiology research has demonstrated that many neuromodulators differentially modulate afferent, incoming information compared to intrinsic and recurrent processing in cortical structures such as piriform cortex, neocortex, and the hippocampus. The enhancement of afferent (external) pathways versus the suppression at recurrent (internal) pathways could cause cortical dynamics to switch between a predominant influence of external stimulation to a predominant influence of internal recall. Modulation of afferent versus intrinsic processing could contribute to the role of neuromodulators in regulating attention, learning, and memory effects in behavior.     

Optimal deep brain stimulation of the subthalamic nucleus—a computational study

Deep brain stimulation (DBS) of the subthalamic nucleus, typically with periodic, high frequency pulse trains, has proven to be an effective treatment for the motor symptoms of Parkinson’s disease (PD). Here, we use a biophysically-based model of spiking cells in the basal ganglia (Terman et al., Journal of Neuroscience, 22, 2963–2976, 2002; Rubin and Terman, Journal of Computational Neuroscience, 16, 211–235, 2004) to provide computational evidence that alternative temporal patterns of DBS inputs might be equally effective as the standard high-frequency waveforms, but require lower amplitudes. Within this model, DBS performance is assessed in two ways. First, we determine the extent to which DBS causes Gpi (globus pallidus pars interna) synaptic outputs, which are burstlike and synchronized in the unstimulated Parkinsonian state, to cease their pathological modulation of simulated thalamocortical cells. Second, we evaluate how DBS affects the GPi cells’ auto- and cross-correlograms. In both cases, a nonlinear closed-loop learning algorithm identifies effective DBS inputs that are optimized to have minimal strength. The network dynamics that result differ from the regular, entrained firing which some previous studies have associated with conventional high-frequency DBS. This type of optimized solution is also found with heterogeneity in both the intrinsic network dynamics and the strength of DBS inputs received at various cells. Such alternative DBS inputs could potentially be identified, guided by the model-free learning algorithm, in experimental or eventual clinical settings. Action Editor: Steven J. Schiff Xiao-Jiang Feng and Eric Shea-Brown contributed equally to this work.