Neuroscience
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Epilepsy, a neurological disorder causing recurring seizures, is often studied in zebrafish by exposing animals to pentylenetetrazol (PTZ), which induces clonic- and tonic-like behaviors. While adult zebrafish seizure-like behaviors are well characterized, manual assessment remains challenging due to its time-consuming nature, potential for human error/bias, and the risk of overlooking subtle behaviors. Aiming to circumvent these issues, we developed a machine learning model for automating the analysis of subtle abnormal and seizure-like behaviors in PTZ-exposed adult zebrafish. ⋯ Altogether, our novel data highlights the use of machine learning models to better understand complex behavioral phenotypes associated to PTZ-induced seizures. The ability to detect frame-by-frame and distinct actions of anticonvulsant drugs provides new perspectives on measuring seizure-like responses, as well as possible therapeutic strategies. The approach used here constitutes an important leap on behavioral analysis that can accelerate the discovery of new treatments for seizure disorders.
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Motor actions adapt dynamically to external changes through the brain's ability to predict sensory outcomes and adjust for discrepancies between anticipated and actual sensory inputs. In this study, we investigated how changes in target speed (vT) and direction influenced visuomotor responses, focusing on gaze and manual joystick control during an interception task. Participants tracked a moving target with sinusoidal variations in vT and directional changes, generating sensory prediction errors and requiring real-time adjustments. ⋯ Participants also exhibited rapid within-trial adjustments, with peak gaze and joystick gains increasing linearly with vT frequency, highlighting the critical role of manual control in matching or exceeding vT for successful interception. Additionally, responses to sudden phase changes in the vT sinusoid revealed the continuous monitoring of prediction errors driven by the magnitude of phase shifts. These findings illustrate the brain's predictive system's ability to integrate continuous visual feedback and sensory prediction errors to fine-tune motor responses and anticipate future target speeds.
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Parkinson's disease (PD) is a prevalent neurodegenerative disorder caused by degeneration of dopaminergic neurons, originating from the substantia nigra pars compacta, and characterized by motor symptoms such as bradykinesia, muscle rigidity, resting tremor, and postural instability, as well as non-motor symptoms such as anxiety, depression, reduced sense of smell, cognitive impairment, and visual dysfunction. Emerging evidence highlights the retina as a promising site for non-invasive exploration of PD pathology, due to its shared embryonic origin with the central nervous system. ⋯ This review provides a comprehensive synthesis of retinal dysfunctions in PD, focusing on structural and functional changes as potential biomarkers for early diagnosis and clinical assessment. By integrating findings from advanced imaging and electrophysiological studies, this review introduces novel perspectives on the correlation between retinal changes and PD pathophysiology, offering innovative approaches for early detection, disease progression monitoring, and therapeutic stratification.
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The present study investigated the involvement of hippocampal nicotinic acetylcholine receptors (nAChRs) in the anti-allodynic effect of ketamine/morphine on neuropathic pain in adult male Wistar rats. Morphine or ketamine administration decreased the percentage of maximum possible effect (MPE%), indicating an analgesic effect. The most significant decrease occurred with a 5 mg/kg dose of morphine (average MPE% = 98), while a 0.5 mg/kg dose of ketamine resulted in a high response (average MPE% = 91), using decision trees as a machine learning tool. ⋯ Each 0.1 mg/kg increase in ketamine dose, when combined with morphine (3 mg/kg), led to a 30.85 higher average MPE%. A tenfold impact of increasing mecamylamine dosage on MPE% was observed when paired with morphine. Thus, hippocampal nAChRs play a significant role in mediating the anti-allodynic effect of ketamine and morphine in neuropathic pain.
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Review Meta Analysis Comparative Study
Comparison of the efficacy of updated drugs for the treatment on the improvement of cognitive function in patients with Alzheimer 's disease: A systematic review and network meta- analysis.
The recent emergence of updated drugs for the treatment of Alzheimer's disease (AD) has produced encouraging cognitive and clinical results in clinical trials, but there is still controversy over how to choose effective treatment options among these numerous drugs. The purpose of this network meta-analysis (NMA) is to compare and rank these drugs based on their efficacy. ⋯ Donanemab and Lecanemab showed good efficacy in ADCS-ADL and CDR-SB, respectively. GV-971 is the best choice to improve ADAS cogs and NPI.