Learning to anticipate events based on the predictive relationship between an action and an outcome (operant conditioning) is a form of associative learning shared by humans and most of other living beings, including invertebrates. Several behavioral studies on the mechanisms of operant conditioning have included Melipona quadrifasciata, a honey bee that is easily manipulated due to lack of sting. In this work, brain proteomes of Melipona bees trained using operant conditioning and untrained (control) bees were compared by two-dimensional gel electrophoresis analysis within pI range of 3-10 and 4-7; in order to find proteins specifically related to this type of associative learning.One protein was detected with differential protein abundance in the brains of trained bees, when compared to not trained ones, through computational gel imaging and statistical analysis. This protein was identified by peptide mass fingerprinting and MS/MS peptide fragmentation using a MALDI-TOF/TOF mass spectrometer as one isoform of arginine kinase monomer, apparently dephosphorylated. Brain protein maps were obtained by 2-DE (Two-dimensional gel electrophoresis) from a total proteins and phosphoproteins extract of the bee Melipona quadrifasciata. One isoform of arginine kinase, probably a dephosphorylated isoform, was significantly more abundant in the brain of trained bees using operant conditioning. Arginine kinase has been reported as an important enzyme of the energy releasing process in the visual system of the bee, but it may carry out additional and unexpected functions in the bee brain for learning process.
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http://dx.doi.org/10.1590/0001-3765202320201317 | DOI Listing |
Nat Commun
January 2025
Department of Psychiatry, University of Pittsburgh, Pittsburgh, 15219, USA.
Cue reactivity is the maladaptive neurobiological and behavioral response upon exposure to drug cues and is a major driver of relapse. A widely accepted assumption is that drugs of abuse result in disparate dopamine responses to cues that predict drug vs. natural rewards.
View Article and Find Full Text PDFNat Commun
January 2025
Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal.
The nucleus accumbens (NAc) is a key brain region for motivated behaviors, yet how distinct neuronal populations encode appetitive or aversive stimuli remains undetermined. Using microendoscopic calcium imaging in mice, we tracked NAc shell D1- or D2-medium spiny neurons' (MSNs) activity during exposure to stimuli of opposing valence and associative learning. Despite drift in individual neurons' coding, both D1- and D2-population activity was sufficient to discriminate opposing valence unconditioned stimuli, but not predictive cues.
View Article and Find Full Text PDFeNeuro
January 2025
Department of Pharmacology, Addiction Science and Toxicology, University of Tennessee Health Science Center, Memphis, TN 38163 USA.
The social environment has long been recognized to play an important role in substance use, which is often modeled in rodents using operant conditioning. However, most operant chambers only accommodate one rodent at a time. We present PeerPub - a unique social operant chamber.
View Article and Find Full Text PDFBrain Behav
January 2025
INEUROPA, Instituto de Neurociencias del Principado de Asturias, Oviedo, Spain.
Purpose: Metabolic dysfunction-associated steatohepatitis (MASH) is a prevalent disease caused by high fat and high cholesterol intake, which leads to systemic deterioration. The aim of this research is to conduct a psychobiological exploration of MASH in adult male rats.
Methods: Subjects who were administered a high-fat and high-cholesterol diet for 14 weeks.
BMC Public Health
December 2024
Bengbu Medical University, School of Health Management, Bengbu, China.
Objective: To explore the health information avoidance behaviors and influencing factors of cancer patients, and to construct a structural equation model to analyze the mediating roles of self-efficacy and negative emotions in the process of generating health information avoidance behaviors of cancer patients.
Methods: A face-to-face electronic questionnaire was used to collect data. Applying a chi-square test and multivariate logistic regression model to analyze the role of different socio-demographic factors in influencing health information avoidance behavior of cancer patients; applying structural equation modeling to analyze the role mechanism of health information avoidance behavior of cancer patients.
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