The potential anxiolytic effects of a novel positive allosteric modulator (PAM) of the metabotropic glutamate receptor subgroup 2 (mGluR₂) were investigated using a self-referencing recording technique with enzyme-based microelectrode arrays (MEAs) that reliably measures tonic and phasic changes in extracellular glutamate levels in awake rats. Studies involved glutamate measures in the rat prefrontal cortex during subcutaneous injections of the following: vehicle, a mGluR₂/₃ agonist, LY354740 (10 mg/kg), or a mGluR₂ PAM, 1-Methyl-2-((cis-(R,R)-3-methyl-4-(4-trifluoromethoxy-2-fluoro)phenyl)piperidin-1-yl)methyl)-1H-imidazo[4,5-b]pyridine ((+)-TFMPIP; 1.0 or 17.8 mg/kg). Studies assessed changes in tonic glutamate levels and the glutamatergic responses to a 5-min restraint stress. Subcutaneous injection of (+)-TFMPIP at a dose of 1.0 mg/kg (day 3: -7.1 ± 15.1 net AUC; day 5: -24.8 ± 24.9 net AUC) and 17.8 mg/kg (day 3: -46.5 ± 33.0 net AUC; day 5: 34.6 ± 36.8 net AUC) significantly attenuated the stress-evoked glutamate release compared to vehicle controls (day 3: 134.7 ± 50.6 net AUC; day 5: 286.6 ± 104.5 net AUC), whereas the mGluR₂/₃ agonist LY354740 had no effect. None of the compounds significantly affected resting glutamate levels, which we have recently shown to be extensively derived from neurons. Taken together, these data support that systemic administration of (+)-TFMPIP produces phasic rather than tonic release of glutamate that may play a major role in the effects of stress on glutamate neuronal systems in the prefrontal cortex.
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http://dx.doi.org/10.1111/j.1471-4159.2012.07784.x | DOI Listing |
Genes (Basel)
December 2024
Department of Psychology, Middlesex University, London NW4 4BT, UK.
Background/objectives: Metabolic syndrome (MetS) is a complex condition linking obesity, diabetes, and hypertension, representing a major challenge in clinical care. Its rising global prevalence, driven by urbanization, sedentary lifestyles, and dietary changes, underscores the need for effective management. This study aims to explore the genetic mechanisms behind MetS, including adiposity, inflammation, neurotransmitters, and β-cell function, to develop a prognostic tool for MetS risk.
View Article and Find Full Text PDFCancers (Basel)
January 2025
Clinic for Radiology, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, DE-48149 Muenster, Germany.
Background/objectives: In recent years, numerous studies have been published on determining the WHO grade of central nervous system (CNS) tumors using machine learning algorithms. These studies are usually based on magnetic resonance imaging (MRI) and sometimes also on positron emission tomography (PET) images. To date, however, there are virtually no corresponding studies based on routinely generated computed tomography (CT) images.
View Article and Find Full Text PDFBiomedicines
January 2025
Perception, Robotics, and Intelligent Machines Lab (PRIME), Department of Computer Science, Université de Moncton, Moncton, NB E1A 3E9, Canada.
Retinal blood vessel segmentation plays an important role in diagnosing retinal diseases such as diabetic retinopathy, glaucoma, and hypertensive retinopathy. Accurate segmentation of blood vessels in retinal images presents a challenging task due to noise, low contrast, and the complex morphology of blood vessel structures. In this study, we propose a novel ensemble learning framework combining four deep learning architectures: U-Net, ResNet50, U-Net with a ResNet50 backbone, and U-Net with a transformer block.
View Article and Find Full Text PDFBMC Psychiatry
January 2025
School of Nursing, Dalian University, No. 24 Luxun Road, Zhongshan District, Dalian, China.
Objective: To construct a recurrence prediction model for Elderly Schizophrenia Patients (ESCZP) and validate the model's spatial external applicability.
Methods: The modeling cohort consisted of 365 ESCZP cases from the Seventh People's Hospital of Dalian, admitted between May 2022 and April 2024. Variables were selected using Lasso-Logistic regression to construct the recurrence prediction model, with a nomogram plotted using the "RMS" package in R 4.
Respir Med
January 2025
Department of Respiratory Medicine, The Affiliated Wuxi People's Hospital, Wuxi Children's Hospital of Nanjing Medical University, Wuxi, 214023,China; Department of Respiratory Medicine & Clinical Allergy Center, Affiliated Children's Hospital of Jiangnan University (Wuxi Children's Hospital), Wuxi 214023, China. Electronic address:
Objective: This study aimed to develop and internally validate a nomogram in predicting the risk of recurrent respiratory tract infection (RRTI) in children.
Methods: A retrospective analysis was performed, involving 150 children with RRTI and 151 healthy controls, aged 0-14 years, admitted to or selected from the Pediatric Department of Yixing Hospital of Traditional Chinese Medicine between June 2022 and June 2023. Data were gathered through a comprehensive questionnaire survey on risk factors associated with RRTI.
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