There is a lack of tools that selectively target vagal afferent neurons (VAN) innervating the gut. We use saporin (SAP), a potent neurotoxin, conjugated to the gastronintestinal (GI) hormone cholecystokinin (CCK-SAP) injected into the nodose ganglia (NG) of male Wistar rats to specifically ablate GI-VAN. We report that CCK-SAP ablates a subpopulation of VAN in culture. In vivo, CCK-SAP injection into the NG reduces VAN innervating the mucosal and muscular layers of the stomach and small intestine but not the colon, while leaving vagal efferent neurons intact. CCK-SAP abolishes feeding-induced c-Fos in the NTS, as well as satiation by CCK or glucagon like peptide-1 (GLP-1). CCK-SAP in the NG of mice also abolishes CCK-induced satiation. Therefore, we provide multiple lines of evidence that injection of CCK-SAP in NG is a novel selective vagal deafferentation technique of the upper GI tract that works in multiple vertebrate models. This method provides improved tissue specificity and superior separation of afferent and efferent signaling compared with vagotomy, capsaicin, and subdiaphragmatic deafferentation. We develop a new method that allows targeted lesioning of vagal afferent neurons that innervate the upper GI tract while sparing vagal efferent neurons. This reliable approach provides superior tissue specificity and selectivity for vagal afferent over efferent targeting than traditional approaches. It can be used to address questions about the role of gut to brain signaling in physiological and pathophysiological conditions.
Highlights d CART is a molecular signal that encodes caloric information for meal termination d Vagal CART synthesis is blunted in obesity partly due to reduced sensitivity to CCK d Knockdown of vagal sensory CART increases food intake by preventing negative feedback d NTS administration of CART inhibits food intake in both lean and obese rats
We assessed the relationship between municipality COVID-19 case rates and SARS-CoV-2 concentrations in the primary sludge of corresponding wastewater treatment facilities. Over 1,700 daily primary sludge samples were collected from six wastewater treatment facilities with catchments serving 18 cities and towns in the State of Connecticut, USA. Samples were analyzed for SARS-CoV-2 RNA concentrations during a 10 month time period that overlapped with October 2020 and winter/spring 2021 COVID-19 outbreaks in each municipality. We fit lagged regression models to estimate reported case rates in the six municipalities from SARS-CoV-2 RNA concentrations collected daily from corresponding wastewater treatment facilities. Results demonstrate the ability of SARS-CoV-2 RNA concentrations in primary sludge to estimate COVID-19 reported case rates across treatment facilities and wastewater catchments, with coverage probabilities ranging from 0.94 to 0.96. Lags of 0 to 1 days resulted in the greatest predictive power for the model. Leave-one-out cross validation suggests that the model can be broadly applied to wastewater catchments that range in more than one order of magnitude in population served. The close relationship between case rates and SARS-CoV-2 concentrations demonstrates the utility of using primary sludge samples for monitoring COVID-19 outbreak dynamics. Estimating case rates from wastewater data can be useful in locations with limited testing availability, testing disparities, or delays in individual COVID-19 testing programs.
We assessed the relationship between municipality COVID-19 case rates and SARS-CoV-2 concentrations in the primary sludge of corresponding wastewater treatment facilities. Over 1,000 daily primary sludge samples were collected from six wastewater treatment facilities with catchments serving 18 cities and towns in the State of Connecticut, USA. Samples were analyzed for SARS-CoV-2 RNA concentrations during a six-month time period that overlapped with fall 2020 and winter 2021 COVID-19 outbreaks in each municipality. We fit a single regression model to estimate reported case rates in the six municipalities from SARS-CoV-2 RNA concentrations collected daily from corresponding wastewater treatment facilities. Results demonstrate the ability of SARS-CoV-2 RNA concentrations in primary sludge to estimate COVID-19 reported case rates across treatment facilities and wastewater catchments, with coverage probabilities ranging from 0.94 to 0.96. Leave-one-out cross validation suggests that the model can be broadly applied to wastewater catchments that range in more than one order of magnitude in population served. Estimation of case rates from wastewater data can be useful in locations with limited testing availability or testing disparities, or delays in individual COVID-19 testing programs.
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