TASK channel deletion in mice causes primary hyperaldosteronism

When inappropriate for salt status, the mineralocorticoid aldosterone induces cardiac and renal injury. Autonomous overproduction of aldosterone from the adrenal zona glomerulosa (ZG) is also the most frequent cause of secondary hypertension. Yet, the etiology of nontumorigenic primary hyperaldosteronism caused by bilateral idiopathic hyperaldosteronism remains unknown. Here, we show that genetic deletion of TWIK-related acid-sensitive K (TASK)-1 and TASK-3 channels removes an important background K current that results in a marked depolarization of ZG cell membrane potential. Although TASK channel deletion mice (TASK^−/−) adjust urinary Na excretion and aldosterone production to match Na intake, they produce more aldosterone than control mice across the range of Na intake. Overproduction of aldosterone is not the result of enhanced activity of the renin–angiotensin system because circulating renin concentrations remain either unchanged or lower than those of control mice at each level of Na intake. In addition, TASK^−/− mice fail to suppress aldosterone production in response to dietary Na loading. Autonomous aldosterone production is also demonstrated by the failure of an angiotensin type 1 receptor blocker, candesartan, to normalize aldosterone production to control levels in TASK^−/− mice. Thus, TASK^−/− channel knockout mice exhibit the hallmarks of primary hyperaldosteronism. Our studies establish an animal model of nontumorigenic primary hyperaldosteronism and identify TASK channels as a possible therapeutic target for primary hyperaldosteronism.     

Melatonin restores hippocampal neural precursor cell proliferation and prevents cognitive deficits induced by jet lag simulation in adult mice

Frequent flyers and shift workers undergo circadian dysrhythmia with adverse impact on body and mind. The circadian rhythm disorder “jet lag” disturbs hippocampal neurogenesis and spatial cognition, which represent morphological and functional adult brain plasticity. This raises the question if pro‐neurogenic stimuli might prevent those consequences. However, suitable measures to mitigate jet lag‐induced adverse effects on brain plasticity have been neglected so far. Here, we used adult C57Bl6 mice to investigate the pro‐neurogenic stimuli melatonin (8 mg/kg i.p.) as well as environmental enrichment as potential measures. We applied photoperiod alterations to simulate “jet lag” by shortening the dark period every third day by 6 hours for 3 weeks. We found that “jet lag” simulation reduced hippocampal neural precursor cell proliferation by 24% and impaired spatial memory performance in the water maze indicated by a prolonged swim path to the target (~23%). While melatonin prevented both the cellular (~1%) as well as the cognitive deficits (~5%), environmental enrichment only preserved precursor cell proliferation (~12%). Our results indicate that lifestyle interventions are insufficient to completely compensate jet lag‐induced consequences. Instead, melatonin is required to prevent cognitive impairment caused by the same environmental factors to which frequent flyers and shift workers are typically exposed to.     

A general model of hippocampal and dorsal striatal learning and decision making

Humans and other animals use multiple strategies for making decisions. Reinforcement-learning theory distinguishes between stimulus–response (model-free; MF) learning and deliberative (model-based; MB) planning. The spatial-navigation literature presents a parallel dichotomy between navigation strategies. In “response learning,” associated with the dorsolateral striatum (DLS), decisions are anchored to an egocentric reference frame. In “place learning,” associated with the hippocampus, decisions are anchored to an allocentric reference frame. Emerging evidence suggests that the contribution of hippocampus to place learning may also underlie its contribution to MB learning by representing relational structure in a cognitive map. Here, we introduce a computational model in which hippocampus subserves place and MB learning by learning a “successor representation” of relational structure between states; DLS implements model-free response learning by learning associations between actions and egocentric representations of landmarks; and action values from either system are weighted by the reliability of its predictions. We show that this model reproduces a range of seemingly disparate behavioral findings in spatial and nonspatial decision tasks and explains the effects of lesions to DLS and hippocampus on these tasks. Furthermore, modeling place cells as driven by boundaries explains the observation that, unlike navigation guided by landmarks, navigation guided by boundaries is robust to “blocking” by prior state–reward associations due to learned associations between place cells. Our model, originally shaped by detailed constraints in the spatial literature, successfully characterizes the hippocampal–striatal system as a general system for decision making via adaptive combination of stimulus–response learning and the use of a cognitive map.

Behavioral and neuroscientific studies suggest that animals can apply multiple strategies to the problem of maximizing future reward, referred to as the reinforcement-learning (RL) problem (1, 2). One strategy is to build a model of the environment that can be used to simulate the future to plan optimal actions (3) and the past for episodic memory (4–6). An alternative, model-free (MF) approach uses trial and error to estimate a direct mapping from the animal’s state to its expected future reward, which the agent caches and looks up at decision time (7, 8), potentially supporting procedural memory (9). This computation is thought to be carried out in the brain through prediction errors signaled by phasic dopamine responses (10). These strategies are associated with different tradeoffs (2). The model-based (MB) approach is powerful and flexible, but computationally expensive and, therefore, slow at decision time. MF methods, in contrast, enable rapid action selection, but these methods learn slowly and adapt poorly to changing environments. In addition to MF and MB methods, there are intermediate solutions that rely on learning useful representations that reduce burdens on the downstream RL process (11–13).In the spatial-memory literature, a distinction has been observed between “response learning” and “place learning” (14–16). When navigating to a previously visited location, response learning involves learning a sequence of actions, each of which depends on the preceding action or sensory cue (expressed in egocentric terms). For example, one might remember a sequence of left and right turns starting from a specific landmark. An alternative place-learning strategy involves learning a flexible internal representation of the spatial layout of the environment (expressed in allocentric terms). This “cognitive map” is thought to be supported by the hippocampal formation, where there are neurons tuned to place and heading direction (17–19). Spatial navigation using this map is flexible because it can be used with arbitrary starting locations and destinations, which need not be marked by immediate sensory cues.We posit that the distinction between place and response learning is analogous to that between MB and MF RL (20). Under this view, associative reinforcement is supported by the DLS (21, 22). Indeed, there is evidence from both rodents (23–25) and humans (26, 27) that spatial-response learning relies on the same basal ganglia structures that support MF RL. Evidence also suggests an analogy between MB reasoning and hippocampus (HPC)-based place learning (28, 29). However, this equivalence is not completely straightforward. For example, in rodents, multiple hippocampal lesion and inactivation studies failed to elicit an effect on action-outcome learning, a hallmark of MB planning (30–35). Nevertheless, there are indications that HPC might contribute to a different aspect of MB RL: namely, the representation of relational structure. Tasks that require memory of the relationships between stimuli do show dependence on HPC (36–42).Here, we formalize the perspective that hippocampal contributions to MB learning and place learning are the same, as are the dorsolateral striatal contributions to MF and response learning. In our model, HPC supports flexible behavior by representing the relational structure among different allocentric states, while dorsolateral striatum (DLS) supports associative reinforcement over egocentric sensory features. The model arbitrates between the use of these systems by weighting each system’s action values by the reliability of the system, as measured by a recent average of prediction errors, following Wan Lee et al. (43). We show that HPC and DLS maintain these roles across multiple task domains, including a range of spatial and nonspatial tasks. Our model can quantitatively explain a range of seemingly disparate findings, including the choice between place and response strategies in spatial navigation (23, 44) and choices on nonspatial multistep decision tasks (45, 46). Furthermore, it explains the puzzling finding that landmark-guided navigation is sensitive to the blocking effect, whereas boundary-guided navigation is not (27), and that these are supported by the DLS and HPC, respectively (26). Thus, different RL strategies that manage competing tradeoffs can explain a longstanding body of spatial navigation and decision-making literature under a unified model.     

One-trial perceptual learning in the absence of conscious remembering and independent of the medial temporal lobe

A degraded, black-and-white image of an object, which appears meaningless on first presentation, is easily identified after a single exposure to the original, intact image. This striking example of perceptual learning reflects a rapid (one-trial) change in performance, but the kind of learning that is involved is not known. We asked whether this learning depends on conscious (hippocampus-dependent) memory for the images that have been presented or on an unconscious (hippocampus-independent) change in the perception of images, independently of the ability to remember them. We tested five memory-impaired patients with hippocampal lesions or larger medial temporal lobe (MTL) lesions. In comparison to volunteers, the patients were fully intact at perceptual learning, and their improvement persisted without decrement from 1 d to more than 5 mo. Yet, the patients were impaired at remembering the test format and, even after 1 d, were impaired at remembering the images themselves. To compare perceptual learning and remembering directly, at 7 d after seeing degraded images and their solutions, patients and volunteers took either a naming test or a recognition memory test with these images. The patients improved as much as the volunteers at identifying the degraded images but were severely impaired at remembering them. Notably, the patient with the most severe memory impairment and the largest MTL lesions performed worse than the other patients on the memory tests but was the best at perceptual learning. The findings show that one-trial, long-lasting perceptual learning relies on hippocampus-independent (nondeclarative) memory, independent of any requirement to consciously remember.

A striking visual effect can be demonstrated by using a grayscale image of an object that has been degraded to a low-resolution, black-and-white image (1, 2). Such an image is difficult to identify (Fig. 1) but can be readily recognized after a single exposure to the original, intact image (Fig. 2) (3–6). Neuroimaging studies have found regions of the neocortex, including high-level visual areas and the medial parietal cortex, which exhibited a different pattern of activity when a degraded image was successfully identified (after seeing the intact image) than when the same degraded image was first presented and not identified (4, 5, 7). This phenomenon reflects a rapid change in performance based on experience, in this case one-trial learning, but the kind of learning that is involved is unclear.Open in a separate windowFig. 1.A sample degraded image. Most people cannot identify what is depicted. See Fig. 2.Open in a separate windowFig. 2.An intact version of the image in Fig. 1. When the intact version is presented just once directly after presentation of the degraded version, the ability to later identify the degraded image is greatly improved, even after many months. Reprinted from ref. (42), which is licensed under CC BY 4.0.One possibility is that successful identification of degraded images reflects conscious memory of having recently seen degraded images followed by their intact counterparts. When individuals see degraded images after seeing their “solutions,” they may remember what is represented in the images, at least for a time. In one study, performance declined sharply from 15 min to 1 d after the solutions were presented and then declined more gradually to a lower level after 21 d (3). Alternatively, the phenomenon might reflect a more automatic change in perception not under conscious control (8). Once the intact image is presented, the object in the degraded image may be perceived directly, independently of whether it is remembered as having been presented. By this account, successful identification of degraded images is reminiscent of the phenomenon of priming, whereby perceptual identification of words and objects is facilitated by single encounters with the same or related stimuli (9–11). Some forms of priming persist for quite a long time (weeks or months) (12–14).These two possibilities describe the distinction between declarative and nondeclarative memory (15, 16). Declarative memory affords the capacity for recollection of facts and events and depends on the integrity of the hippocampus and related medial temporal lobe structures (17, 18). Nondeclarative memory refers to a collection of unconscious memory abilities including skills, habits, and priming, which are expressed through performance rather than recollection and are supported by other brain systems (19–21). Does one-trial learning of degraded images reflect declarative or nondeclarative memory? How long does it last? In an early report that implies the operation of nondeclarative memory, two patients with traumatic amnesia improved the time needed to identify hidden images from 1 d to the next, but could not recognize which images they had seen (22). Yet, another amnesic patient reportedly failed such a task (23). The matter has not been studied in patients with medial temporal lobe (MTL) damage.To determine whether declarative (hippocampus-dependent) or nondeclarative (hippocampus-independent) memory supports the one-trial learning of degraded images, we tested five patients with bilateral hippocampal lesions or larger MTL lesions who have severely impaired declarative memory. The patients were fully intact at perceptual learning, and performance persisted undiminished from 1 d to more than 5 mo. At the same time, the patients were severely impaired at remembering both the structure of the test and the images themselves.     

重度间歇低氧大鼠学习记忆功能与氧化应激的关系

目的 通过建立重度间歇低氧动物模型,探讨OSAHS大鼠学习记忆功能与氧化应激的关系.方法 成年雄性Wistar大鼠48只,体重(170±10)g,采用随机数字法分为5％间歇性低氧组和对照组,每组又分为2、4、6和8周时间组,每组6只,其中实验组给予5％间歇低氧,并分别在2、4、6、8周进行Morris水迷宫检测学习记忆功能,随后处死大鼠,取脑组织于透射电子显微镜下观察海马区超微结构的变化,通过化学比色法测定海马组织超氧化物歧化酶(SOD)活性和丙二醛水平.结果 与对照组比较,实验组大鼠水迷宫测试大鼠逃避潜伏期时间延长、跨越目标象限时间缩短、穿台次数减少,与对照组相比差异具有统计学意义(P＜0.05);随着间歇低氧持续时间延长,实验组各时间点学习功能的改变差异组间比较差异均有统计学意义(均P＜0.05).对照组大鼠海马组织于电子显微镜下神经元结构完整,细胞器丰富,而实验组大鼠海马组织的神经元和突触数量明显减少,细胞核皱缩,突触结构模糊,突触间隙增宽,且随着暴露时间的延长,细胞损伤改变愈加明显.与对照组比较,实验组海马组织丙二醛含量明显增高,而SOD活性降低,且随间歇低氧时间延长其变化更为明显,差异有统计学意义(均P＜0.05).结论 间歇重度低氧大鼠海马组织存在氧化应激损伤,可能通过引起神经元及突触数量与结构的改变,从而导致学习记忆功能障碍,且随着缺氧时间的延长逐渐加重.     

有氧运动对血管性脑痴呆小鼠学习记忆能力的影响

目的探讨有氧运动对血管性脑痴呆小鼠记忆能力的影响及其作用机制。方法暴露小鼠双侧颈总动脉,重复夹闭动脉3次,尾静脉放血建立血管性脑痴呆小鼠模型,小鼠随机分为三组:假手术组、模型组和有氧运动组。术后第二天开始进行有氧运动,连续7周。训练结束后进行行为学检测,术后30天收集小鼠脑组织样本(海马、前额叶、全脑和血清)。HE染色观察海马CA1区的病理学变化、TUNEL法检测海马CA1区神经细胞凋亡、Western blot和紫外分光光度计检测Bcl-2、Bax、丙二醛(MDA)、超氧化物歧化酶(SOD)、生长相关蛋白(GAP-43)、脑源性神经营养因子(BDNF)、乙酰胆碱合成酶(ACHE)、乙酰胆碱转移酶(CHAT)、突触素(SYP)、神经细胞黏附分子(NCAM)及神经细胞黏附分子受体(NR2B)的变化。结果与假手术组相比,模型组小鼠的僵直时间显著缩短,CA1区神经元细胞病变严重,凋亡细胞增加,MDA和ACHE蛋白的表达明显上升,SYP、NCAM、NR2B、SOD、BDNF、CHAT、GAP-43和Bcl-2蛋白表达降低,Bax蛋白表达没有明显变化。与模型组相比,有氧运动组小鼠的僵直时间显著延长,海马区的组织病变情况改善,且凋亡细胞减少,MDA和ACHE蛋白的表达明显降低,SYP、NCAM、NR2B、SOD、BDNF、CHAT、GAP-43和Bcl-2蛋白的表达升高,Bax蛋白表达没有明显变化。结论有氧训练可能通过上调Bcl-2、SOD、BDNF、CHAT、GAP-43、SYP、NCAM及NR2B蛋白表达,下调MDA和ACHE蛋白表达,减少自由基损伤和海马区神经元细胞凋亡,从而改善血管性痴呆小鼠的学习记忆功能。     

咪达唑仑多次使用对小鼠学习记忆的影响

目的观察不同剂量的咪达唑仑多次使用对小鼠学习记忆的影响。方法100只KM小鼠分层随机区组设计,分为M1、M2、M3、M4组和生理盐水（NS）组,每组20只,各组再随机选取10只,参加跳台实验或避暗实验。M1、M2、M3和M4组分别以咪达唑仑0.5、1、2和4 mg/kg,NS组以10 ml/kg生理盐水腹腔注射,3次/d,连续10 d后,进行训练,24 h后进行记忆测验,以潜伏期和错误次数作为记忆成绩的指标。结果M1、M2、M3、M4组与NS组比较,M2、M3和M4组与M1组比较,M3和M4组与M2组比较,潜伏期缩短、错误次数次数增多（P〈0.05）;但M3组与M4组比较,潜伏期和错误次数相似（P〉0.05）。结论多次使用咪达唑仑对记忆的影响有一定剂量依赖性,但其记忆抑制作用有封顶效应。     

A multiplicative reinforcement learning model capturing learning dynamics and interindividual variability in mice

Both in humans and in animals, different individuals may learn the same task with strikingly different speeds; however, the sources of this variability remain elusive. In standard learning models, interindividual variability is often explained by variations of the learning rate, a parameter indicating how much synapses are updated on each learning event. Here, we theoretically show that the initial connectivity between the neurons involved in learning a task is also a strong determinant of how quickly the task is learned, provided that connections are updated in a multiplicative manner. To experimentally test this idea, we trained mice to perform an auditory Go/NoGo discrimination task followed by a reversal to compare learning speed when starting from naive or already trained synaptic connections. All mice learned the initial task, but often displayed sigmoid-like learning curves, with a variable delay period followed by a steep increase in performance, as often observed in operant conditioning. For all mice, learning was much faster in the subsequent reversal training. An accurate fit of all learning curves could be obtained with a reinforcement learning model endowed with a multiplicative learning rule, but not with an additive rule. Surprisingly, the multiplicative model could explain a large fraction of the interindividual variability by variations in the initial synaptic weights. Altogether, these results demonstrate the power of multiplicative learning rules to account for the full dynamics of biological learning and suggest an important role of initial wiring in the brain for predispositions to different tasks.It is commonly observed in animal behavior experiments, as much as in the classroom, that different individuals eventually learn the same task with strikingly different dynamics. Many factors were shown to influence learning speed and/or performance at the group level, including genetic background (1), early experience (2), or contextual factors such as stress (3). In all these cases, the underlying idea is that these factors act on synaptic plasticity mechanisms to change different parameters that modulate or gate synaptic updates, thereby modifying learning dynamics at the system scale (e.g., ref. 4). These ideas are in line with most theoretical models of biological learning (5), such as reinforcement learning (6, 7), which are based on the trial-by-trial update of mathematical variables that can be directly or indirectly related to updates of synaptic weights between neurons. In these models, one essential parameter controlling the speed of learning is the learning rate that scales the learning rule (i.e., the rule according to which synapses are updated). Other factors are also known to have an influence on learning speed such as the level of noise and the particular learning rule (8) or metaparameters that dynamically control the balance between different aspects of learning behavior like the exploration vs. exploitation or memory storage vs. renewal trade-offs (3, 9). However, importantly, all these potential variability factors represent core parameters of the system that directly influence the dynamics throughout the entire learning process.Whereas most theoretical models efficiently capture the dynamics of group learning curves, it is known that in many basic operant conditioning protocols, individual learning curves strongly deviate from the gradually increasing and negatively accelerated learning curves resulting from group averaging (10). Individual learning curves in fact often display a step-like increase from the untrained to the trained performance level after a delay, sometimes termed the “presolution period” (11, 12), whose duration strongly varies from one animal to another. Little is known about the biological underpinning of the learning delays and of their interindividual variations. Delays were tentatively explained by a threshold between the experience accumulated by the animal and its behavioral response (12); however, the biological nature of such a threshold remains elusive.Here, we combine theoretical modeling and learning experiments in mice and show that both the presence and the variability of learning delays across individuals can be quantitatively explained by variations of the initial connectivity between the representation of the relevant stimuli and the action selection network in a model using a multiplicative learning rule. Hence, we propose that initial connectivity could be a crucial, yet unidentified factor of variability in learning.     

CASY-1, an ortholog of calsyntenins/alcadeins, is essential for learning in Caenorhabditis elegans

Calsyntenins/alcadeins are type I transmembrane proteins with two extracellular cadherin domains highly expressed in mammalian brain. They form a tripartite complex with X11/X11L and APP (amyloid precursor protein) and are proteolytically processed in a similar fashion to APP. Although a genetic association of calsyntenin-2 with human memory performance has recently been reported, physiological roles and molecular functions of the protein in the nervous system are poorly understood. Here, we show that CASY-1, the Caenorhabditis elegans ortholog of calsyntenins/alcadeins, is essential for multiple types of learning. Through a genetic screen, we found that casy-1 mutants show defects in salt chemotaxis learning. casy-1 mutants also show defects in temperature learning, olfactory adaptation, and integration of two sensory signals. casy-1 is widely expressed in the nervous system. Expression of casy-1 in a single sensory neuron and at the postdevelopmental stage is sufficient for its function in salt chemotaxis learning. The fluorescent protein-tagged ectodomain of CASY-1 is released from neurons. Moreover, functional domain analyses revealed that both cytoplasmic and transmembrane domains of this protein are dispensable, whereas the ectodomain, which contains the LG/LNS-like domain, is critically required for learning. These results suggest that learning is modulated by the released ectodomain of CASY-1.     

A point mutation in TRPC3 causes abnormal Purkinje cell development and cerebellar ataxia in moonwalker mice

The hereditary ataxias are a complex group of neurological disorders characterized by the degeneration of the cerebellum and its associated connections. The molecular mechanisms that trigger the loss of Purkinje cells in this group of diseases remain incompletely understood. Here, we report a previously undescribed dominant mouse model of cerebellar ataxia, moonwalker (Mwk), that displays motor and coordination defects and loss of cerebellar Purkinje cells. Mwk mice harbor a gain-of-function mutation (T635A) in the Trpc3 gene encoding the nonselective transient receptor potential cation channel, type C3 (TRPC3), resulting in altered TRPC3 channel gating. TRPC3 is highly expressed in Purkinje cells during the phase of dendritogenesis. Interestingly, growth and differentiation of Purkinje cell dendritic arbors are profoundly impaired in Mwk mice. Our findings define a previously unknown role for TRPC3 in both dendritic development and survival of Purkinje cells, and provide a unique mechanism underlying cerebellar ataxia.     

槲皮素对衰老小鼠学习记忆行为的影响

目的　检测槲皮素 (1 0mg·kg- 1 ·d- 1 )对衰老小鼠学习记忆行为的影响。方法　开场行为实验、避暗法实验和Morris水迷宫实验。结果　在开场行为实验中 ,槲皮素作用组在新异环境中自发行为有显著增加 ,其爬格子数、站立 /贴壁次数、梳洗次数比衰老模型组分别增加了 38.88%(P <0 .0 5)、57.2 3 % (P <0 .0 1 )和 2 8.49% (P <0 .0 5) ;在避暗法实验中 ,槲皮素作用组记忆保持能力显著增加 ,其电击 2 4小时后的步入潜伏期比衰老模型组升高了 55 .72 % (P <0 .0 1 ) ;在水迷宫实验中 ,槲皮素作用组空间学习记忆能力显著增加 ,在第 4天第 4轮训练中的逃避潜伏期比衰老模型组下降了 53 .7% (P <0 .0 1 ) ,而 5mg·kg- 1 ·d- 1 槲皮素灌喂组有相似结果 ,但表现剂量效应。结论　槲皮素可增加衰老小鼠的学习记忆能力。     

A pair of dopamine neurons mediate chronic stress signals to induce learning deficit in Drosophila melanogaster

Chronic stress could induce severe cognitive impairments. Despite extensive investigations in mammalian models, the underlying mechanisms remain obscure. Here, we show that chronic stress could induce dramatic learning and memory deficits in Drosophila melanogaster. The chronic stress–induced learning deficit (CSLD) is long lasting and associated with other depression-like behaviors. We demonstrated that excessive dopaminergic activity provokes susceptibility to CSLD. Remarkably, a pair of PPL1-γ1pedc dopaminergic neurons that project to the mushroom body (MB) γ1pedc compartment play a key role in regulating susceptibility to CSLD so that stress-induced PPL1-γ1pedc hyperactivity facilitates the development of CSLD. Consistently, the mushroom body output neurons (MBON) of the γ1pedc compartment, MBON-γ1pedc>α/β neurons, are important for modulating susceptibility to CSLD. Imaging studies showed that dopaminergic activity is necessary to provoke the development of chronic stress–induced maladaptations in the MB network. Together, our data support that PPL1-γ1pedc mediates chronic stress signals to drive allostatic maladaptations in the MB network that lead to CSLD.

Stress has significant and complex effects on cognitive function. In general, these effects follow an inverted U–shaped dose–response relationship in intensity and duration. So that moderate acute stress could promote learning and memory, while chronic stress very often induces detrimental effects (1). Since chronic stress–induced learning and memory impairments are closely associated with many neural disorders, such as depression, schizophrenia, and Alzheimer''s disease, understanding the underlying neurobiology is of importance for developing effective drugs and treatments (2, 3). To this end, animal models, especially mammalian models, have been extensively investigated. Current findings suggest that the effects of chronic stress on learning and memory could be influenced by many internal and external factors that involve multiple brain regions, genes, and complex mechanisms that have not yet been fully elucidated (3–6).Stress could have consequential effects on aversive olfactory memory in Drosophila melanogaster. For example, moderate fast promotes long term memory (LTM) formation (7, 8), while sleep deprivation promotes forgetting and impairs memory capacity (9–11). Recent reports have shown that chronic stress can induce depression-like symptoms in Drosophila, as manifested by characteristic behaviors that indicate anhedonia, lack of motivation, prone to despair, and sleep disorder (12–14). However, investigation of the effect of chronic stress on Drosophila learning and memory is still lacking.In the present study, we report that a 4-d chronic stress treatment (CST) effectively induces strong learning and memory deficits in Drosophila. We focused on the learning deficit phenotype and found that the Drosophila dopaminergic (DAergic) system plays an important role in modulating susceptibility to chronic stress–induced learning deficit (CSLD), suggesting that DAergic modulation is an evolutionary conserved chronic stress–coping mechanism. We pinpointed the key CSLD regulating dopamine neurons (DANs) to a pair of PPL1-γ1pedc neurons that project to the mushroom body (MB) γ1pedc compartment and further showed that MBON-γ1pedc>α/β, the output neurons of γ1pedc compartment, modulates susceptibility to CSLD as well. Imaging studies identified chronic stress–induced abnormal neural activities in learning-related neurons, which require DAergic activity during CST. Overall, our studies delineate a model that chronic stress signals can be mediated by a pair of DANs, PPL1-γ1pedc, to drive maladaptations in the MB network that lead to CSLD.     

A missense mutation in the previously undescribed gene Tmhs underlies deafness in hurry-scurry (hscy) mice

Mouse deafness mutations provide valuable models of human hearing disorders and entry points into molecular pathways important to the hearing process. A newly discovered mouse mutation named hurry-scurry (hscy) causes deafness and vestibular dysfunction. Scanning electron microscopy of cochleae from 8-day-old mutants revealed disorganized hair bundles, and by 50 days of age, many hair cells are missing. To positionally clone hscy, 1,160 F(2) mice were produced from an intercross of (C57BL/6-hscy x CAST/EiJ) F(1) hybrids, and the mutation was localized to a 182-kb region of chromosome 17. A missense mutation causing a critical cysteine to phenylalanine codon change was discovered in a previously undescribed gene within this candidate interval. The gene is predicted to encode an integral membrane protein with four transmembrane helices. A synthetic peptide designed from the predicted protein was used to produce specific polyclonal antibodies, and strong immunoreactivity was observed on hair bundles of both inner and outer hair cells in cochleae of newborn +/+ controls and +/hscy heterozygotes but was absent in hscy/hscy mutants. Accordingly, the gene was given the name "tetraspan membrane protein of hair cell stereocilia," symbol Tmhs. Two related proteins (>60% amino acid identity) are encoded by genes on mouse chromosomes 5 and 6 and, together with the Tmhs-encoded protein (TMHS), comprise a distinct tetraspan subfamily. Our localization of TMHS to the apical membrane of inner ear hair cells during the period of stereocilia formation suggests a function in hair bundle morphogenesis.     

弓形虫感染对大鼠记忆力影响及其机制的实验研究

目的观察弓形虫感染对大鼠学习记忆能力和海马组织细胞因子(白细胞介素-1β、肿瘤坏死因子-α、白细胞介素-6)水平以及大脑皮层一氧化氮合酶(NOS)活性的影响,探讨其可能机制。方法40只清洁级SD大鼠随机分成4组,即对照组和高、中、低感染剂量的弓形虫感染组(2×107/ml×2ml、2×105/ml×2ml、2×103/ml×2ml)。9周后进行被动回避实验和Morris水迷宫试验,观察弓形虫感染对大鼠的学习记忆能力等行为学变化。放射免疫法检测大鼠海马组织IL-1β、IL-6、TNF-α水平,免疫组化检测NOS活性。结果弓形虫感染对大鼠的记忆获得没有影响,但高、中剂量弓形虫感染组大鼠的记忆消失要早于对照组(P<0.05),低感染剂量组大鼠记忆消失与正常对照大鼠比较,差异无统计学意义(P>0.05)。各感染组大鼠Morris水迷宫测试中逃避潜伏期均明显延长,其距离百分比明显降低(P<0.05)。各感染组大鼠海马组织IL-1β、TNF-α水平明显高于对照组(P<0.05);但IL-6水平与对照组相比差异无显著性(P>0.05)。感染组大鼠大脑皮层NOS阳性细胞数增加。结论弓形虫感染对大鼠的学习记忆能力有影响,其作用机制之一可能与大鼠海马组织IL-1β、TNF-α细胞因子水平升高有关。     

杜仲粕对D-半乳糖致衰老小鼠学习记忆能力的影响

目的 研究杜仲粕对D-半乳糖致衰老小鼠学习记忆能力的影响及其作用机制.方法 小鼠随机分为三组:空白对照组,衰老模型组(350 mg· kg-1·d-1),杜仲粕实验组(300mg·kg-1 ·d-1).除空白对照组外,其余各组小鼠每天按照350 mg/kg剂量颈部皮下注射D-半乳糖,空白对照组注射同等容量生理盐水,1次/d,连续6w.检测衰老小鼠学习记忆能力,测定小鼠肝组织、脑组织中单胺氧化酶(MAO)活性和谷胱苷肽过氧化物酶(GSH-Px)活力.结果 杜仲粕实验组潜伏期明显缩短,穿越原平台的次数明显增加;杜仲粕实验组肝组织、脑组织中MAO活性降低,GSH-Px活力增强.结论 杜仲粕能明显改善D-半乳糖致衰老小鼠学习记忆能力,其机制可能与降低MAO活性,增强GSH-Px活力有关.