Carbonic anhydrase (CA) is abundant in glial cells in the brain and CA type II isoform (CA II) activity in the hippocampus plays an important role in buffering extracellular pH transients produced by neural activity. Chronic ethanol exposure results in respiratory and metabolic acidosis, producing shifts in extracellular pH in the brain and body. These neurophysiological changes by ethanol are hypothesized to contribute to the continued drinking behavior and physical withdrawal behavior in subjects consuming ethanol chronically. We explored whether chronic ethanol self-administration (ethanol drinking, 10% v/v; ED) without or under the influence of chronic intermittent ethanol vapor (CIE-ED) experience alters the expression of CA II in the hippocampus. Postmortem hippocampal tissue analyses demonstrated that CA II levels were enhanced in the hilus region of the hippocampus in ED and CIE-ED rats. We used a novel molecule—4-fluoro-N-(4-sulfamoylphenyl) benzenesulfonamide (4-FS)—a selective CA II inhibitor, to determine whether CA II plays a role in ethanol self-administration in ED and CIE-ED rats and physical withdrawal behavior in CIE-ED rats. 4-FS (20 mg/kg, i.p.) reduced ethanol self-administration in ED rats and physical withdrawal behavior in CIE-ED rats. Postmortem hippocampal tissue analyses demonstrated that 4-FS reduced CA II expression in ED and CIE-ED rats to control levels. In parallel, 4-FS enhanced GABAA receptor expression, reduced ratio of glutamatergic GluN2A/2B receptors and enhanced the expression of Fos, a marker of neuronal activation in the ventral hippocampus in ED rats. These findings suggest that 4-FS enhanced GABAergic transmission and increased activity of neurons of inhibitory phenotypes. Taken together, these findings support the role of CA II in assisting with negative affective behaviors associated with moderate to severe alcohol use disorders (AUD) and that CA II inhibitors are a potential therapeutic target to reduce continued drinking and somatic withdrawal symptoms associated with moderate to severe AUD.
Analyzing data from the verbal fluency task (e.g., “name all the animals you can in a minute”) is of interest to both memory researchers and clinicians due to its broader implications for memory search and retrieval. Recent work has proposed several computational models to examine nuanced differences in search behavior, which can provide insights into the mechanisms underlying memory search. A prominent account of memory search within the fluency task was proposed by Hills, Jones, and Todd (2012), where mental search is modeled after how animals forage for food in physical space. Despite the broad potential utility of these models to scientists and clinicians, there is currently no open-source program to apply and compare existing foraging models or clustering algorithms without extensive, often redundant programming. To remove this barrier to studying search patterns in the fluency task, we created forager, a Python package (https://github.com/thelexiconlab/forager) and web interface (https://forager.research.bowdoin.edu/). forager provides multiple automated methods to designate clusters and switches within a fluency list, implements a novel set of computational models that can examine the influence of multiple lexical sources (semantic, phonological, and frequency) on memory search using semantic embeddings, and also enables researchers to evaluate relative model performance at the individual and group level. The package and web interface cater to users with various levels of programming experience. In this work, we introduce forager’s basic functionality and use cases that demonstrate its utility with pre-existing behavioral and clinical data sets of the semantic fluency task.
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