原发性醛固酮增多症大鼠自主活动和学习记忆行为的影响

摘要 目的：探讨原发性醛固酮增多症(primary aldosteronism,PA)大鼠其自主活动和对学习记忆行为的影响。方法：8周龄健康雄SD(Sprague-Dawley)大鼠(n=30)随机分为对照组与模型组各15只。两组都皮下埋置微量渗透泵,模型组泵内灌注醛固酮,对照组泵内灌注等量的生理盐水,记录大鼠自主活动和学习记忆行为的变化情况。结果：所有大鼠均存活,模型组都造模成功,切口愈合良好。模型组造模后的收缩压高于对照组(P<0.05),也高于造模前(P<0.05),两组造模前后心率对比差异无统计学意义(P>0.05)。模型组造模后的逃避潜伏期与穿台次数少于对照组(P<0.05),也少于造模前(P<0.05)。模型组造模后的自主活动次数高于对照组(P<0.05),也高于造模前(P<0.05)。造模后模型组的鼠双微基因2(Mouse Double Microgene 2,MDM2)蛋白相对表达水平高于对照组(P<0.05)。造模后模型组的血清醛固酮含量都高对照组(P<0.05),血清钾离子、钠离子、肾素活性低于对照组(P<0.05)。结论：原发性醛固酮增多症大鼠伴随有血清钾离子、钠离子含量降低与MDM2蛋白的高表达,从而导致大鼠出现自主活动和学习记忆行为障碍。     

Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach

Deep learning techniques have recently made considerable advances in the field of artificial intelligence. These methodologies can assist psychologists in early diagnosis of mental disorders and preventing severe trauma. Major Depression Disorder (MDD) is a common and serious medical condition whose exact manifestations are not fully understood. So, early discovery of MDD patients helps to cure or limit the adverse effects. Electroencephalogram (EEG) is prominently used to study brain diseases such as MDD due to having high temporal resolution information, and being a noninvasive, inexpensive and portable method. This paper has proposed an EEG-based deep learning framework that automatically discriminates MDD patients from healthy controls. First, the relationships among EEG channels in the form of effective brain connectivity analysis are extracted by Generalized Partial Directed Coherence (GPDC) and Direct directed transfer function (dDTF) methods. A novel combination of sixteen connectivity methods (GPDC and dDTF in eight frequency bands) was used to construct an image for each individual. Finally, the constructed images of EEG signals are applied to the five different deep learning architectures. The first and second algorithms were based on one and two-dimensional convolutional neural network (1DCNN–2DCNN). The third method is based on long short-term memory (LSTM) model, while the fourth and fifth algorithms utilized a combination of CNN with LSTM model namely, 1DCNN-LSTM and 2DCNN-LSTM. The proposed deep learning architectures automatically learn patterns in the constructed image of the EEG signals. The efficiency of the proposed algorithms is evaluated on resting state EEG data obtained from 30 healthy subjects and 34 MDD patients. The experiments show that the 1DCNN-LSTM applied on constructed image of effective connectivity achieves best results with accuracy of 99.24% due to specific architecture which captures the presence of spatial and temporal relations in the brain connectivity. The proposed method as a diagnostic tool is able to help clinicians for diagnosing the MDD patients for early diagnosis and treatment.     

Portrait of visual cortical circuits for generating neural oscillation dynamics

The mouse primary visual cortex (V1) has emerged as a classical system to study neural circuit mechanisms underlying visual function and plasticity. A variety of efferent-afferent neuronal connections exists within the V1 and between the V1 and higher visual cortical areas or thalamic nuclei, indicating that the V1 system is more than a mere receiver in information processing. Sensory representations in the V1 are dynamically correlated with neural activity oscillations that are distributed across different cortical layers in an input-dependent manner. Circuits consisting of excitatory pyramidal cells (PCs) and inhibitory interneurons (INs) are the basis for generating neural oscillations. In general, INs are clustered with their adjacent PCs to form specific microcircuits that gate or filter the neural information. The interaction between these two cell populations has to be coordinated within a local circuit in order to preserve neural coding schemes and maintain excitation–inhibition (E–I) balance. Phasic alternations of the E–I balance can dynamically regulate temporal rhythms of neural oscillation. Accumulating experimental evidence suggests that the two major sub-types of INs, parvalbumin-expressing (PV⁺) cells and somatostatin-expressing (SOM⁺) INs, are active in controlling slow and fast oscillations, respectively, in the mouse V1. The review summarizes recent experimental findings on elucidating cellular or circuitry mechanisms for the generation of neural oscillations with distinct rhythms in either developing or matured mouse V1, mainly focusing on visual relaying circuits and distinct local inhibitory circuits.     

Comparison between touchscreen operant chambers and water maze to detect early prefrontal dysfunction in mice

The relative lack of sensitive and clinically valid tests of rodent behavior might be one of the reasons for the limited success of the clinical translation of preclinical Alzheimer's disease (AD) research findings. There is a general interest in innovative behavioral methodology, and protocols have been proposed for touchscreen operant chambers that might be superior to existing cognitive assessment methods. We assessed and analyzed touchscreen performance in several novel ways to examine the possible occurrence of early signs of prefrontal (PFC) functional decline in the APP/PS1 mouse model of AD. Touchscreen learning performance was compared between APP/PS1-21 mice and wildtype littermates on a C57BL/6J background at 3, 6 and 12 months of age in parallel to the assessment of spatial learning, memory and cognitive flexibility in the Morris water maze (MWM). We found that older mice generally needed more training sessions to complete the touchscreen protocol than younger ones. Older mice also displayed defects in MWM working memory performance, but touchscreen protocols detected functional changes beginning at 3 months of age. Histological changes in PFC of APP/PS1 mice indeed occurred as early as 3 months. Our results suggest that touchscreen operant protocols are more sensitive to PFC dysfunction, which is of relevance to the use of these tasks and devices in preclinical AD research and experimental pharmacology.     

Modeling vegetation greenness and its climate sensitivity with deep‐learning technology

Climate sensitivity of vegetation has long been explored using statistical or process‐based models. However, great uncertainties still remain due to the methodologies’ deficiency in capturing the complex interactions between climate and vegetation. Here, we developed global gridded climate–vegetation models based on long short‐term memory (LSTM) network, which is a powerful deep‐learning algorithm for long‐time series modeling, to achieve accurate vegetation monitoring and investigate the complex relationship between climate and vegetation. We selected the normalized difference vegetation index (NDVI) that represents vegetation greenness as model outputs. The climate data (monthly temperature and precipitation) were used as inputs. We trained the networks with data from 1982 to 2003, and the data from 2004 to 2015 were used to validate the models. Error analysis and sensitivity analysis were performed to assess the model errors and investigate the sensitivity of global vegetation to climate change. Results show that models based on deep learning are very effective in simulating and predicting the vegetation greenness dynamics. For models training, the root mean square error (RMSE) is <0.01. Model validation also assure the accuracy of our models. Furthermore, sensitivity analysis of models revealed a spatial pattern of global vegetation to climate, which provides us a new way to investigate the climate sensitivity of vegetation. Our study suggests that it is a good way to integrate deep‐learning method to monitor the vegetation change under global change. In the future, we can explore more complex climatic and ecological systems with deep learning and coupling with certain physical process to better understand the nature.     

Home‐site fidelity and homing behavior of the big‐headed turtle Platysternon megacephalum

Site fidelity refers to the restriction of dispersal distance of an animal and its tendency to return to a stationary site. To our knowledge, the homing ability of freshwater turtles and their fidelity is reportedly very low in Asia. We examined mark–recapture data spanning a 4‐year period in Diaoluoshan National Nature Reserve, Hainan Province, China, to investigate the site fidelity and homing behavior of big‐headed turtles Platysternon megacephalum. A total of 11 big‐headed turtles were captured, and all individuals were used in this mark–recapture study. The site fidelity results showed that the adult big‐headed turtles (n = 4) had a 71.43% recapture rate in the original site after their release at the same site, whereas the juveniles (n = 1) showed lower recapture rates (0%). Moreover, the homing behavior results showed that the adults (n = 5) had an 83.33% homing rate after displacement. Adult big‐headed turtles were able to return to their initial capture sites (home) from 150 to 2,400 m away and precisely to their home sites from either upstream or downstream of their capture sites or even from other streams. However, none of the juveniles (n = 4) returned home, despite only being displaced 25–150 m away. These results indicated that the adult big‐headed turtles showed high fidelity to their home site and strong homing ability. In contrast, the juvenile turtles may show an opposite trend but further research is needed.     

Adaptive signaling behavior in stomatopods under varying light conditions

Stomatopod crustaceans (mantis shrimp) are aggressive benthic marine predators with extraordinary color vision. When communicating with conspecifics, many stomatopods display conspicuously colored body areas, often in combination with other types of signals such as motion and chemical cues. Some species occupy wide depth ranges (>30 m), where changing light conditions can influence color perception. To test the potential effects of differing ambient lights on signaling behavior, stomatopods (Gonodactylus smithii) interacted with conspecifics in aquaria, under full-spectrum, high intensity light or light restricted in either spectrum or intensity. During intrasexual and intersexual trials in full-spectrum, high intensity light, animals performed more aggressive acts using colored body parts (meral spread, lunge, strike). Stomatopods used significantly more antennular flicking, and performed aggressive acts at reduced distances under restricted light conditions. To compare the use of antennules in visual and chemical communication, additional experiments showed more antennular flicking in response to chemical stimuli from food or conspecifics compared to seawater controls. This response ceased immediately after ablation of antennular chemoreceptors but returned to pre-treatment levels after 5 days of recovery. These findings suggest that stomatopods can vary their use of signals during conspecific interactions under different photic conditions. These inducible, plastic behavioral responses can potentially improve signal transfer in varying light environments.     

Study of naïve and memory cells in a cohort of Egyptian chronic granulomatous disease patients

Abstract

Context: Chronic granulomatous disease (CGD) is a primary immunodeficiency disorder caused by inherited defects in the NADPH oxidase complex which may be involved in important pathways that connect innate and adaptive immunity. Objectives: Characterize the naive and memory compartment of B and T lymphocytes in patients with CGD. Methods: Twenty CGD patients and twenty healthy controls matched for age and sex were enrolled in this study. Flow cytometric assessment of the naïve and memory compartments of peripheral blood lymphocytes was done using cell surface markers CD45RO, CD45RA, CD27, CD3 and CD19. Results: There were 15 (79%) autosomal recessive CGD patients (8 females (53%) and 7 males (47%), 100% positive parental consanguinity) and four (21%) X-linked CGD patients. On comparing the 3 groups; AR CGD, X-linked CGD and controls, there was a positive statistical significant difference for the percentage and absolute count of CD19?+?CD27+ memory B cell (p?=?0.028 and p?=?0.047 respectively), CD45RA cells (with p values of p?=?0.000 and 0.033, respectively), the naïve compartment CD3?+?CD45RA+ cells percentage and absolute counts (p?=?0.005, 0.01respectively), CD3?+?CD27?+?cells percentage and absolute counts (p?=?0.001, 0.012 respectively), CD3?+?CD45RA?+?CD27+ cells percentage and absolute counts (p?=?0.015, 0.005, respectively). The significance was mainly attributed to the decrease in the X-linked group than control group. Conclusion: There was an altered naïve and memory B profile in CGD patients, this may increase susceptibility of the patients to opportunistic infections and autoimmune disorders. T-cell alterations have to be interpreted cautiously especially in the presence of infections.     

Variation in hippocampal glial cell numbers in food‐caching birds from different climates

Enhancements to memory are associated with enhanced neural structures that support those capabilities. A great deal of work has examined this relationship in the context of natural variation in spatial memory capability and hippocampal (Hp) structure. Most studies have focused on volumetric and neuron measures, but have seldom examined the role of glial cells. Once considered involved only in supportive functions associated with neurons, the importance of glial cells in cognitive processes, including memory, is gaining more attention. Building upon our previous study on the relationship between the brain, memory, and environmental severity in food‐caching birds, we compared the total number of Hp glial cells in wild‐sampled and in lab‐reared (common garden) black‐capped chickadees (Poecile atricapillus) originating from two different environmental extremes. We found that birds from more harsh climate tended to have significantly more Hp glial cells than those from more mild climate and that lab‐reared chickadees had significantly fewer Hp glial cells compared to the wild‐sampled birds. These results suggest that population differences in glial numbers may be controlled, at least in part, by heritable mechanisms, but glial numbers appear to be additionally regulated by an individual's environment. The pattern of Hp glial cell abundance among our treatment groups closely followed that of the Hp volume, suggesting that Hp glial cell number may be associated with the Hp volume. Unlike Hp neurons, however, the number of Hp glial cells may be, at least in part, affected by an individual's experiences and environment. © 2013 Wiley Periodicals, Inc. Develop Neurobiol 73: 480–485, 2013