A fundamental impediment to understanding the brain is the availability of inexpensive and robust methods for targeting and manipulating specific neuronal populations. The need to overcome this barrier is pressing because there are considerable anatomical, physiological, cognitive, and behavioral differences between mice and higher mammalian species in which it is difficult to specifically target and manipulate genetically defined functional cell-types. In particular, it is unclear the degree to which insights from mouse models can shed light on the neural mechanisms that mediate cognitive functions in higher species including humans. Here we describe a novel recombinant adeno-associated virus (rAAV) that restricts gene expression to GABAergic interneurons within the telencephalon. We demonstrate that the viral expression is specific and robust, allowing for morphological visualization, activity monitoring and functional manipulation of interneurons in both mice and non-genetically tractable species, thus opening the possibility to study GABA-ergic function in virtually any vertebrate species.

Recent success in identifying gene regulatory elements in the context of recombinant adeno-associated virus vectors have enabled cell type-restricted gene expression. However, within the cerebral cortex these tools are presently limited to broad classes of neurons. To overcome this limitation, we developed a strategy that led to the identification of multiple novel enhancers to target functionally distinct neuronal subtypes. By investigating the regulatory landscape of the disease gene Scn1a, we identified enhancers that target the breadth of its expression, including two that are selective for parvalbumin and vasoactive intestinal peptide cortical interneurons. Demonstrating the functional utility of these elements, we found that the PV-specific enhancer allowed for the selective targeting and manipulation of these neurons across species, from mice to humans. Finally, we demonstrate that our selection method is generalizable to other genes and characterize four additional PV-specific enhancers with exquisite specificity for distinct regions of the brain. Altogether, these viral tools can be used for cell-type specific circuit manipulation and hold considerable promise for use in therapeutic interventions.Large-scale transcriptomic studies are rapidly revealing where and when genes associated with neuropsychiatric disease are expressed within specific cell types (1-4). Approaches for understanding and treating these disorders will require methods for targeting and manipulating specific neuronal subtypes. Thus, gaining access to these populations in non-human primates and humans has become paramount. AAVs are the method of choice for gene delivery in the nervous system but have a limited genomic payload and are not intrinsically selective for particular neuronal populations (5). We and others have identified short regulatory elements capable of restricting viral expression to broad neuronal classes. In addition, systematic enhancer discovery has been accelerated by the recent development of technologies allowing for transcriptomic and epigenetic studies at single-cell resolution (6-12). Despite these advances, the search space for enhancer selection remains enormous and to date success has been limited. To focus our enhancer selection, we chose to specifically examine the regulatory landscape of Scn1a, a gene expressed in distinct neuronal populations and whose disruption is associated with severe epilepsy (13).Combining single-cell ATAC-seq data with sequence conservation across species, we nominated ten candidate regulatory sequences in the vicinity of this gene. By thoroughly investigating each of these elements for their ability to direct viral expression, we identified three enhancers that collectively target the breadth of neuronal populations expressing Scn1a. Among these, one particular short regulatory sequence was capable of restricting viral expression to parvalbumin-expressing cortical interneurons (PV cINs). To fully assess the utility of this element beyond reporter expression, we validated it in a v...

The expression of VDR and CAMP in the gastric epithelium is up-regulated in the case of H. pylori infection; thus, VDR plays an important role in gastric mucosa homeostasis and host protection from H. pylori infection.

Daily rhythms are disrupted in patients with mood disorders. The lateral habenula (LHb) and dorsal raphe nucleus (DRN) contribute to circadian timekeeping and regulate mood. Thus, pathophysiology in these nuclei may be responsible for aberrations in daily rhythms during mood disorders. Using the 15-day chronic social defeat stress (CSDS) paradigm and in vitro slice electrophysiology, we measured the effects of stress on diurnal rhythms in firing of LHb cells projecting to the DRN (cellsLHb→DRN) and unlabeled DRN cells. We also performed optogenetic experiments to investigate if increased firing in cellsLHb→DRN during exposure to a weak 7-day social defeat stress (SDS) paradigm induces stress-susceptibility. Last, we investigated whether exposure to CSDS affected the ability of mice to photoentrain to a new light–dark (LD) cycle. The cellsLHb→DRN and unlabeled DRN cells of stress-susceptible mice express greater blunted diurnal firing compared to stress-näive (control) and stress-resilient mice. Daytime optogenetic activation of cellsLHb→DRN during SDS induces stress-susceptibility which shows the direct correlation between increased activity in this circuit and putative mood disorders. Finally, we found that stress-susceptible mice are slower, while stress-resilient mice are faster, at photoentraining to a new LD cycle. Our findings suggest that exposure to strong stressors induces blunted daily rhythms in firing in cellsLHb→DRN, DRN cells and decreases the initial rate of photoentrainment in susceptible-mice. In contrast, resilient-mice may undergo homeostatic adaptations that maintain daily rhythms in firing in cellsLHb→DRN and also show rapid photoentrainment to a new LD cycle.

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Background Preventing relapse of schizophrenic patients is really a challenge. The present study sought to provide more explicit evidence and factors of different grades and weights by a series of step-by-step analysis through χ 2 test, logistic regression analysis and decision-tree model. The results of this study may contribute to controlling relapse of schizophrenic patients. Methods A total of 1,487 schizophrenia patients were included who were 18–65 years of age and discharged from 10 hospitals in China from January 2009 to August 2009 and from September 2011 to February 2012 with improvements or recovery of treatment effect. We used a questionnaire to collect information about relapse and correlative factors during one year after discharge by medical record collection and telephone interview. The χ 2 test and logistic regression analysis were used to identify risk factors and high-risk factors firstly, and then a decision-tree model was used to find predictive factors. Results The χ 2 test found nine risk factors which were associated with relapse. Logistic regression analysis also showed four high-risk factors further (medication adherence, occupational status, ability of daily living, payment method of medical costs). At last, a decision-tree model revealed four predictors of relapse; it showed that medication adherence was the first grade and the most powerful predictor of relapse (relapse rate for adherence vs. nonadherence: 22.9 vs. 55.7%, χ 2 = 116.36, p < 0.001). The second grade factor was occupational status (employment vs. unemployment: 19.7 vs. 42.7%, χ 2 = 17.72, p < 0.001); the third grade factors were ability of daily living (normal vs. difficult: 28.4 vs. 54.3%, χ 2 = 8.61, p = 0.010) and household income (household income ≥ 3000 RMB vs. <3000 RMB: 28.6 vs. 42.4%, χ 2 = 6.30, p = 0.036). The overall positive predictive value (PPV) of the logistic regression was 0.740, and the decision-tree model was 0.726. Both models were reliable. Conclusions For schizophrenic patients discharged from hospital, who had good medication adherence, more higher household income, be employed and normal ability of daily living, would be less likely to relapse. Decision tree provides a new path for doctors to find the schizophrenic inpatient’s relapse risk and give them reasonable treatment suggestions after discharge.