Accumulating studies consistently show that methylphenidate (MPD), the first line drug for treating Attention-Deficit Hyperactivity Disorder (ADHD), is abused by patients to whom the drug is prescribed. Like other psychostimulants, only low doses of MPD improve cognitive performance while higher doses impair it. Preventing the use of high doses of MPD is important for retaining its therapeutic efficacy. Previously, it has been shown that performance in Morris water maze test is improved in rats treated, orally, with MPD in doses of 2.5 mg/kg; but higher doses (5 mg/kg) impair it. The present study is designed to monitor rewarding effects of 2.5 mg/kg MPD in conditioned place preference (CPP) paradigm and its potential inhibition in buspirone co-treated animals. Our results show that rewarding effects of MPD in CPP paradigm are prevented in rats co-treated with buspirone in doses of 0.1 and 0.3 mg/kg. Animals treated with MPD exhibit a downregulation of 5-HT1A receptor mRNA in the nucleus accumbens which is also prevented in rats co-treated with 0.1 and 0.3 mg/kg but not 1.0 and 2.0 mg/kg buspirone. Administration of buspirone in these doses is not rewarding in CPP test and upregulates 5-HT1A receptor mRNA in the nucleus accumbens. The findings suggest that co-use of low doses of buspirone can prevent rewarding effects of MPD to help retain its therapeutic efficacy.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.bbr.2021.113660 | DOI Listing |
Acta Psychol (Amst)
January 2025
Department of English Language, College of Arts, King Faisal University, Al Ahsa, Saudi Arabia.
This study investigates the combined impact of artificial intelligence (AI) tools and Uncertain Motivation (UM) strategies on the argumentative writing performance of Saudi EFL learners, using the Toulmin Model. Sixty Saudi EFL students participated in four writing tasks, with results demonstrating significant improvements in essay quality, particularly in clarity, structure, and depth. AI tools provided real-time feedback, enhancing students' ability to refine claims, data, backing, and counterarguments.
View Article and Find Full Text PDFPhytother Res
January 2025
Department of Molecular and Developmental Medicine, School of Medicine, University of Siena, Polo Universitario San Miniato, Siena, Italy.
Drugs generally used in major depressive disorder are considered inappropriate for the more common milder forms. The efficacy of saffron extracts has been demonstrated in mild to moderate depression and in preclinical models of depression. However, evidence of saffron activity on reduced hedonic responsiveness and motivational anhedonia is limited.
View Article and Find Full Text PDFSci Rep
January 2025
Neuro-Robotics Lab, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan.
Humans exploit motor synergies for motor control; however, how they emerge during motor learning is not clearly understood. Few studies have dealt with the computational mechanism for generating synergies. Previously, optimal control generated synergistic motion for the upper limb; however, it has not yet been applied to the high-dimensional whole-body system.
View Article and Find Full Text PDFDrug Alcohol Depend
December 2024
Department of Psychiatry, University of Florida, Gainesville, FL, USA. Electronic address:
Tobacco use disorder is a chronic disorder that affects more than one billion people worldwide and causes the death of millions each year. The rewarding properties of nicotine are critical for the initiation of smoking. Previous research has shown that the activation of glucocorticoid receptors (GRs) plays a role in nicotine self-administration in rats.
View Article and Find Full Text PDFBioinspir Biomim
January 2025
Chongqing Jiaotong University, No. 66, Xuefu Avenue, Nanan District, Chongqing City, Chongqing, Chongqing, 400074, CHINA.
The study of fish swimming behaviours and locomotion mechanisms holds significant scientific and engineering value. With the rapid advancements in artificial intelligence, a new method combining deep reinforcement learning (DRL) with computational fluid dynamics (CFD) has emerged and been applied to simulate the autonomous behavior of higher organisms like fish. However, the scale of this cross-disciplinary method is directly affected by the efficiency of the DRL model.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!