Departamento de Farmacologia, Laboratório de Fisiologia e Farmacologia do Sistema Nervoso Centra, C.P. 19.031, 81.531-980 UFPR, Curitiba, PR, Brazil.
Published: January 2012
AI Article Synopsis
Article Abstract
Rationale: Aversively motivated learning is more poorly understood than appetitively motivated learning in many aspects, including the role of dopamine receptors in different regions of the striatum.
Objectives: The present study investigated the roles of the D1-like DA receptors in the nucleus accumbens (NAc) and dorsolateral striatum (DLS) on learning and performance of conditioned avoidance responses (CARs).
Methods: Adult male Wistar rats received intraperitoneal (i.p.), intra-NAc, or intra-DLS injections of the D1 dopamine receptor agonist SKF 81297 or the D1 receptor antagonist SCH 23390 20 min before or immediately after a training session in the CAR task two-way active avoidance, carried out 24 h before a test session.
Results: Pre-training administration of SCH 23390, but not SKF 81297, caused a significant decrease in the number of CARs in the test, but not in the training session, when injected into the DLS, or in either session when injected into the NAc. It also caused a significant increase in the number of escape failures in the training session when injected into the NAc. Systemic administration caused a combination of these effects. Post-training administrations of these drugs caused no significant effect.
Conclusions: The results suggest that the D1-like receptors in the NAc and DLS play important, though different, roles in learning and performance of CAR.
Objectives: We studied the acceptability, feasibility, tolerability, and preliminary effectiveness of combined cue exposure and anodal high-definition transcranial direct current stimulation (HD-tDCS) on the right dorsolateral prefrontal cortex (DLPFC) on cannabis craving in cannabis use disorder (CUD).
Methods: We randomly assigned 48 participants equally in 4 groups: A, tDCS and cannabis cue exposure; B, tDCS and neutral image; C, sham tDCS and cue exposure; and D, sham tDCS and neutral image. The images were validated by Delphi consensus.
Background: The quality of gynaecological surgical training has faced mounting criticism internationally with multiple countries publishing potential remedies for improvement. Simulation has the indisputable ability to mitigate against training deficiencies, however, access to and the quality of simulation varies across regions, never mind nations.
Objectives: To assess the effect on surgical skills by the introduction of a structured and integrated simulation programme with the unique aspect of being completely free of cost with the provision of a take-home laparoscopy box trainer (LBT).
Purpose: This study aimed to compare the effectiveness of 3 artificial intelligence language models-GPT-3.5, GPT-4o, and Gemini, in delivering patient-centered information about thyroid eye disease (TED). We evaluated their performance based on the accuracy and comprehensiveness of their responses to common patient inquiries regarding TED.
Department of Neurosurgery, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
Background: Spine surgical training faces increasing challenges due to restricted working hours and greater sub specialization. Modern simulators offer a promising approach to teaching both simple and complex spinal procedures. This study evaluated the acceptance and efficacy of spine simulator training using a lumbar herniated disc model tested by 16 neurosurgical residents (PGY-1-6), and compared 3D and 2D teaching methods.
Background: Fully automatic skull-stripping and tumor segmentation are crucial for monitoring pediatric brain tumors (PBT). Current methods, however, often lack generalizability, particularly for rare tumors in the sellar/suprasellar regions and when applied to real-world clinical data in limited data scenarios. To address these challenges, we propose AI-driven techniques for skull-stripping and tumor segmentation.
