The cognitive symptoms of schizophrenia are poorly understood and difficult to treat. Estrogens may mitigate these symptoms via unknown mechanisms. To examine these mechanisms, we tested whether increasing estradiol (E) or decreasing luteinizing hormone (LH) could mitigate short-term episodic memory loss in a phencyclidine (PCP) model of schizophrenia. We then assessed whether changes in cortical or hippocampal GABA may underlie these effects. Female rats were ovariectomized and injected subchronically with PCP. To modulate E and LH, animals received estradiol capsules or Antide injections. Short-term episodic memory was assessed using the novel object recognition task (NORT). Brain expression of GAD67 was analyzed via western blot, and parvalbumin-containing cells were counted using immunohistochemistry. Some rats received hippocampal infusions of a GABA agonist, GABA antagonist, or GAD inhibitor before behavioral testing. We found that PCP reduced hippocampal GAD67 and abolished recognition memory. Antide restored hippocampal GAD67 and rescued recognition memory in PCP-treated animals. Estradiol prevented PCP's amnesic effect in NORT but failed to restore hippocampal GAD67. PCP did not cause significant differences in number of parvalbumin-expressing cells or cortical expression of GAD67. Hippocampal infusions of a GABA agonist restored recognition memory in PCP-treated rats. Blocking hippocampal GAD or GABA receptors in ovx animals reproduced recognition memory loss similar to PCP and inhibited estradiol's protection of recognition memory in PCP-treated animals. In summary, decreasing LH or increasing E can lessen short-term episodic memory loss, as measured by novel object recognition, in a PCP model of schizophrenia. Alterations in hippocampal GABA may contribute to both PCP's effects on recognition memory and the hormones' ability to prevent or reverse them.
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http://dx.doi.org/10.1016/j.psyneuen.2018.02.024 | DOI Listing |
Support Care Cancer
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The Bellvitge Biomedical Research Institute IDIBELL, Psychooncology and Digital Health Group, Hospitalet de Llobregat, Spain.
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Department of Psychology, Jagiellonian University, ul. Ingardena 6, 30-060, Kraków, Poland.
Mirror-invariance enables recognition of mirrored objects as identical. During reading acquisition, sighted readers must overcome this innate bias to distinguish between mirror-inverted letters ('d' vs. 'b').
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December 2024
Departmment of Anesthesia, College of Medicine and Health Sciences, Addis Abeba University, Addis Abeba, Ethiopia.
In the field of healthcare, ensuring patient safety is a critical priority that has garnered global recognition as a pressing public health concern. Despite notable progress in medical treatments and diagnostic technologies, patients continue to be at risk of adverse events and harm during the perioperative period. Anesthetists hold a pivotal position in this phase of patient care and have the potential to greatly impact safety and outcomes.
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December 2024
Department of Communications and Electronics, Delta University for Science and Technology, Mansoura, Egypt.
Human activity recognition (HAR) is one of the most important segments of technology advancement in applications of smart devices, healthcare systems & fitness. HAR uses details from wearable sensors that capture the way human beings move or engage with their surrounding. Several researchers have thus presented different ways of modeling human motion, and some have been as follows: Many researchers have presented different methods of modeling human movements.
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December 2024
New Technology Research Institute, BYD Auto Industry Co., Ltd., Shenzhen, 518118, China.
Effective road terrain recognition is crucial for enhancing the driving safety, passability, and comfort of autonomous vehicles. This study addresses the challenges of accurately identifying diverse road surfaces using deep learning in complex environments. We introduce a novel end-to-end Tire Noise Recognition Residual Network (TNResNet) integrated with a time-frequency attention module, designed to capture and leverage time-frequency information from tire noise signals for road terrain classification.
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