Dopamine and opioid systems interact within the nucleus accumbens to maintain monogamous pair bonds
- University of Michigan, United States
- University of Alabama at Birmingham, United States
- Wayne State University, United States
- Georgia State University, United States
- University of Michigan-Ann Arbor, United States
Abstract
Prairie vole breeder pairs form monogamous pair bonds, which are maintained through the expression of selective aggression toward novel conspecifics. Here, we utilize behavioral and anatomical techniques to extend the current understanding of neural mechanisms that mediate pair bond maintenance. For both sexes, we show that pair bonding up-regulates mRNA expression for genes encoding D1-like dopamine (DA) receptors and dynorphin as well as enhances stimulated DA release within the nucleus accumbens (NAc). We next show that D1-like receptor regulation of selective aggression is mediated through downstream activation of kappa-opioid receptors (KORs) and that activation of these receptors mediates social avoidance. Finally, we also identified sex-specific alterations in KOR binding density within the NAc shell of paired males and demonstrate that this alteration contributes to the neuroprotective effect of pair bonding against drug reward. Together, these findings suggest motivational and valence processing systems interact to mediate the maintenance of social bonds.
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Animal experimentation: All experiments in this study were performed in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#5531) of the University of Michigan. Experiments conducted in this study were approved by the Institutional Biosafety Committee (#1331) at the University of Michigan. All surgery was performed under ketamine and xylazine anesthesia, and every effort was made to minimize suffering.
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© 2016, Resendez et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Dopamine and opioid systems interact within the nucleus accumbens to maintain monogamous pair bonds
eLife 5:e15325.
https://doi.org/10.7554/eLife.15325
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Background:
Post-stroke epilepsy (PSE) is a critical complication that worsens both prognosis and quality of life in patients with ischemic stroke. An interpretable machine learning model was developed to predict PSE using medical records from four hospitals in Chongqing.
Methods:
Medical records, imaging reports, and laboratory test results from 21,459 ischemic stroke patients were collected and analyzed. Univariable and multivariable statistical analyses identified key predictive factors. The dataset was split into a 70% training set and a 30% testing set. To address the class imbalance, the Synthetic Minority Oversampling Technique combined with Edited Nearest Neighbors was employed. Nine widely used machine learning algorithms were evaluated using relevant prediction metrics, with SHAP (SHapley Additive exPlanations) used to interpret the model and assess the contributions of different features.
Results:
Regression analyses revealed that complications such as hydrocephalus, cerebral hernia, and deep vein thrombosis, as well as specific brain regions (frontal, parietal, and temporal lobes), significantly contributed to PSE. Factors such as age, gender, NIH Stroke Scale (NIHSS) scores, and laboratory results like WBC count and D-dimer levels were associated with increased PSE risk. Tree-based methods like Random Forest, XGBoost, and LightGBM showed strong predictive performance, achieving an AUC of 0.99.
Conclusions:
The model accurately predicts PSE risk, with tree-based models demonstrating superior performance. NIHSS score, WBC count, and D-dimer were identified as the most crucial predictors.
Funding:
The research is funded by Central University basic research young teachers and students research ability promotion sub-projec t(2023CDJYGRH-ZD06), and by Emergency Medicine Chongqing Key Laboratory Talent Innovation and development joint fund project (2024RCCX10).
