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1.
bioRxiv ; 2023 Sep 23.
Article in English | MEDLINE | ID: mdl-37790481

ABSTRACT

Increased brain levels of acetylcholine (ACh) are observed in subsets of patients with depression and increasing ACh levels chronically can precipitate stress-related behaviors in humans and animals. Conversely, optimal ACh levels are required for cognition and memory. We hypothesize that ACh signaling is important for encoding both appetitive and stress-relevant memories, but that excessive increases in ACh result in a negative encoding bias in which memory formation of a stressful event is aberrantly strengthened, potentially contributing to the excessive focus on negative experience that could lead to depressive symptoms. The medial prefrontal cortex (mPFC) is critical to control the limbic system to filter exteroceptive cues and stress-related circuits. We therefore evaluated the role of ACh signaling in the mPFC in a learned helplessness task in which mice were exposed to repeated inescapable stressors followed by an active avoidance task. Using fiber photometry with a genetically-encoded ACh sensor, we found that ACh levels in the mPFC during exposure to inescapable stressors were positively correlated with later escape deficits in an active avoidance test in males, but not females. Consistent with these measurements, we found that both pharmacologically- and chemogenetically-induced increases in mPFC ACh levels resulted in escape deficits in both male and female mice, whereas chemogenetic inhibition of ACh neurons projecting to the mPFC improved escape performance in males, but impaired escape performance in females. These results highlight the adaptive role of ACh release in stress response, but also support the idea that sustained elevated ACh levels contribute to maladaptive behaviors. Furthermore, mPFC ACh signaling may contribute to depressive symptomology differentially in males and females.

2.
J Phys Chem B ; 119(22): 6873-7, 2015 Jun 04.
Article in English | MEDLINE | ID: mdl-25974162

ABSTRACT

We report for the first time the use of click chemistry both to modify the surface morphology and to obtain superhydrophobic properties. Using click chemistry as a postfunctionalization of poly(3,4-ethylenedioxythiophene) nanofibers bearing azido groups, we show that the nanostructures already present on the surface as well as the surface hydrophobicity are highly affected by the used alkyne. These results allow one to envisage widely varied strategies to modify nanostructured surfaces while introducing various functions, for example to produce biosensors or antibacterial surfaces.

3.
Mol Syst Biol ; 7: 535, 2011 Oct 11.
Article in English | MEDLINE | ID: mdl-21988831

ABSTRACT

The initial genome-scale reconstruction of the metabolic network of Escherichia coli K-12 MG1655 was assembled in 2000. It has been updated and periodically released since then based on new and curated genomic and biochemical knowledge. An update has now been built, named iJO1366, which accounts for 1366 genes, 2251 metabolic reactions, and 1136 unique metabolites. iJO1366 was (1) updated in part using a new experimental screen of 1075 gene knockout strains, illuminating cases where alternative pathways and isozymes are yet to be discovered, (2) compared with its predecessor and to experimental data sets to confirm that it continues to make accurate phenotypic predictions of growth on different substrates and for gene knockout strains, and (3) mapped to the genomes of all available sequenced E. coli strains, including pathogens, leading to the identification of hundreds of unannotated genes in these organisms. Like its predecessors, the iJO1366 reconstruction is expected to be widely deployed for studying the systems biology of E. coli and for metabolic engineering applications.


Subject(s)
Computational Biology/methods , Escherichia coli K12 , Genes, Bacterial , Genome, Bacterial , Genomics/methods , Systems Biology/methods , Escherichia coli K12/genetics , Escherichia coli K12/metabolism , Gene Knockout Techniques , Metabolic Engineering , Metabolic Networks and Pathways , Models, Biological
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