Neuroscience
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We investigated proprioceptive acuity for location and motion of a never seen hand-held tool (30 cm long rod) and the accuracy of movements to place tool parts in the location of remembered visual targets. Ten blindfolded right-handed subjects (5 females) reached with the tool held in the right hand to touch the tip and midpoint to the stationary and moving left index-tip, to the right and left ear lobes and to remembered visual target locations. We also tested accuracy of left hand rod reaches to the ear lobes to determine if rod dimensions and control of tool movements experienced during right hand tool use could be used to accurately localize the rod parts when held in the left hand. ⋯ The tool-tip was localized with lower mean distance errors (about 1 cm) than the tool-midpoint (5.5-6.5 cm) when reaching to touch the ear lobes with the rod in right and left hands. Right hand reaches to place the tool- tip and midpoint in remembered visual target locations were inaccurate with large overshoots of close targets and undershoots of far targets, similar to previous reports for reaching with the right hand to remembered visual targets. These results support the distalization hypothesis, that the tool endpoint becomes the effective upper limb endpoint when using the tool.
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Diabetes mellitus is recognized as an important cause of cognitive dysfunction. Ferroptosis plays a key role in diabetic cognitive dysfunction (DCD). Dihydromyricetin (DHM) has promising neuronal protective effects, but it is unclear the mechanism. ⋯ Meanwhile, JNK agonist Anisomycin could attenuate these effects of DHM. Taken together, our data suggest that DHM can ameliorate HG-induced neurotoxicity in HT22 cells by inhibiting ferroptosis via the JNK-inflammatory signaling pathway. Hence, DHM may represent a novel and promising therapeutic intervention for DCD.
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In the last years, there has been a growing interest in the brain-heart connection. A core aspect of this connection appears to be the autonomic nervous system, particularly through the vagus nerve. Accordingly, vagally mediated heart rate variability (vmHRV) is currently considered as an index of top-down control processes involved in cognition and emotion regulation. ⋯ Participants with higher resting vagal tone showed superior cognitive performance in tasks requiring cognitive control, motor and cognitive inhibition, cognitive flexibility, and working memory in comparison to those with lower resting vagal tone. Furthermore, vagal-mediated heart rate variability was also found to be associated with memory, attention, and executive performance. The current research provides new insights into the interactions between cognitive and autonomic systems, further supporting evidence for body-brain interactions.
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A decline in mitochondrial functions associated with ageing is the key factor of free radical generation which contributes to age-related pathologies. Protecting healthy functional mitochondrial networks with antioxidants is critical in promoting healthy ageing. This study aimed to investigate the protective effect of ergothioneine (EGT)-rich Lentinula edodes extract (LE-ETH) against tert-butyl hydroperoxide (t-BHP) assaulted senescent HT22 cells. ⋯ A total of 23 compounds consisting of phenols, fatty acids, and sterols were identified in the ethanolic extract. Pentanoic acid was the major compound identified in LE-ETH. These findings demonstrated that EGT-rich L.edodes mushroom is a potential neuroprotective agent which could serve as a potential therapeutic strategy for the preservation of mitochondrial functions in healthy ageing explorations.
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Accurate analysis of anxiety behaviors in animal models is pivotal for advancing neuroscience research and drug discovery. This study compares the potential of DeepLabCut, ZebraLab, and machine learning models to analyze anxiety-related behaviors in adult zebrafish. Using a dataset comprising video recordings of unstressed and pre-stressed zebrafish, we extracted features such as total inactivity duration/immobility, time spent at the bottom, time spent at the top and turn angles (large and small). ⋯ The effectiveness of these machine learning models was validated and tested on independent datasets. We found that some machine learning models, such as Decision Tree and Random Forests, performed excellently to differentiate between anxious and non-anxious behavior, even in the control group, where the differences between subjects were more subtle. Our findings show that upcoming technologies, such as machine learning models, are able to effectively and accurately analyze anxiety behaviors in zebrafish and provide a cost-effective method to analyze animal behavior.