Abused drug-induced intracranial self-stimulation is correlated with the alteration of dopamine transporter availability in the medial prefrontal cortex and nucleus accumbens of mice.

Intracranial self-stimulation (ICSS) of the medial forebrain bundle in mice is an experimental model use to assess the relative potential of reward-seeking behaviors. Here, we used the ICSS model to evaluate the abuse potential of 18 abused drugs: 3-Fluoroethamphetamine (3-FEA); methylphenidate; cocaine; dextroamphetamine; alpha-Pyrrolidinobutyrophenone (α-PBT); 4'-Fluoro-4-methylaminorex (4-FPO); methamphetamine; larocaine; phentermine; paramethoxymethamphetamine (PMMA); phendimetrazine; N-(1-adamantyl)-1-pentyl-1H-indazole-3-carboxamide (AKB-48); Naphthalen-1-yl-(4-pentyloxynaphthalen-1-yl)methanone (CB-13); 4-Ethylnaphthalen-1-yl-(1-pentylindol-3-yl)methanone (JWH-210); Naphthalen-1-yl-(1-pentylindol-3-yl)methanone (JWH-018); N-(ortho-methoxybenzyl)-4-ethylamphetamine (4-EA-NBOMe); N-[(2-Methoxyphenyl)methyl]-N-methyl-1-(4-methylphenyl)propan-2-amine (4-MMA-NBOMe); and 1-[1-(4-methoxyphenyl)cyclohexyl]piperidine (4-MeO-PCP). We determined dopamine transporter (DAT) availability in the medial prefrontal cortex (mPFC), striatum, and nucleus accumbens (NAc) after drug treatment.

Derivatives of 3, 4, 5-Trimethoxycinnamic Acid Ameliorate Stress-Induced Anxiety in Mice and Rats.

Stress is an overwhelming problem associated with neuronal damage leading to anxiety and depression. The compound 3, 4, 5-trimethoxycinnamic acid (TMCA) has shown anti-stress effects; however, its derivatives remained unknown for their anxiolytic properties. Here, therefore, we investigated derivatives of TMCA (dTMCA) for their anxiolytic effects using immobilization and electric shock-induced stress in rats.

Rewarding and reinforcing effects of two dissociative-based new psychoactive substances, deschloroketamine and diphenidine, in mice.

Dissociative-based new psychoactive substances (NPSs) are increasingly available through the Internet, and public health problems related to the recreational use of these substances have been increasing globally. Two such NPSs are deschloroketamine and diphenidine, which are primarily used recreationally as ketamine substitutes. However, there is little scientific evidence to describe the dependence liability of NPSs.

Pharmacology and adverse effects of new psychoactive substances: synthetic cannabinoid receptor agonists.

Over the last decade, new psychoactive substances (NPS) have continuously been the focus of the international society since their emergence on the illicit drug market. NPS can be classified into six groups including; synthetic cannabinoid receptor agonists (SCRAs), stimulants, opioids, dissociatives, sedatives/hypnotics, and classic hallucinogens with psychoactive effects. These are sold as "herbal incense," "bath salts," "legal highs," and "research chemicals".

D-limonene Inhibits Pentylenetetrazole-Induced Seizure via Adenosine A2A Receptor Modulation on GABAergic Neuronal Activity.

Background: Epilepsy is a chronic neurological disorder characterized by the recurrence of seizures. One-third of patients with epilepsy may not respond to antiseizure drugs.

Purpose: We aimed to examine whether D-limonene, a cyclic monoterpene, exhibited any antiseizure activity in the pentylenetetrazole (PTZ)-induced kindling mouse model and in vitro.

Development of a Deep-Learning-Based Artificial Intelligence Tool for Differential Diagnosis between Dry and Neovascular Age-Related Macular Degeneration.

The use of deep-learning-based artificial intelligence (AI) is emerging in ophthalmology, with AI-mediated differential diagnosis of neovascular age-related macular degeneration (AMD) and dry AMD a promising methodology for precise treatment strategies and prognosis. Here, we developed deep learning algorithms and predicted diseases using 399 images of fundus. Based on feature extraction and classification with fully connected layers, we applied the Visual Geometry Group with 16 layers (VGG16) model of convolutional neural networks to classify new images.