Construction Of Fe/Co-Based Single-Atom Catalysts And Evaluation Of Their Antitumor And Antibacterial Activity

The brain is a complex system which dynamically processes information according to external stimuli and self desires,generating a wide range of functions such as cognition,thinking,behavior,and so on.The specific collaborative patterns of functional networks in the brain while performing specific tasks have been a hotspot of interest for scientists.However,due to the limitations of research and technical methods,this problem has not been well addressed.Non-invasive functional brain imaging techniques provide an opportunity to solve this problem.Positron emission tomography(PET)is one of the most commonly used imaging techniques of brain function,which utilizes positron radionuclide labeled imaging agents to trace specific physiological and pathological processes in living organisms.18F-fluoro-2-deoxyglucose(FDG)is the most commonly used tracer in PET imaging to trace the metabolic processes of glucose in living organisms.Since glucose is the main energy source for brain functional activity,the FDG-PET image signal directly reflects the normality or abnormality of brain functional activity.By investigating the interconnections of brain regions,the FDG-PET brain metabolic network reflects the brain functional network connectivity patterns in normal physiological state or disease state,and has been currently preliminarily applied in basic and clinical brain functional network research.Animal experiments play an irreplaceable role in biomedical research.However,due to their difficulty in cooperating with the experiment,animals need to be anesthetized during brain imaging experiments.But anesthesia will inhibit the activity of brain neurons,and functional brain imaging under anesthesia will not reflect the real function of the brain.Thus,the functional magnetic resonance imaging(fMRI)technique which is commonly used in the study of the human brain is not suitable for animal brain functional network research.Unlike fMRI,the imaging process of FDG-PET is that firstly injecting the animal with FDG as an imaging agent,and then letting the animal perform a certain task,during which the task-related neuronal excitability increases and the glucose uptake increases.Since the metabolically processing of FDG is similar to glucose,the uptake of FDG by excited nerve cells is also increased.After a certain period,the cumulative amount of FDG in the excited brain region will be significantly higher than in other regions.Thus,FDG-PET imaging records the amount of FDG uptake in a period of time before the imaging scan,characterizing the brain metabolic activity of the conscious animals,and is unaffected by the anesthetized animal during the imaging scan.Therefore,FDG-PET imaging is a key technique for studying brain functional activity in conscious animals.Brain metabolic network analysis can provide spatiotemporal dynamics of brain functional cooperation in animals from a brain-wide level.However,no systematic analysis method has yet been proposed for brain metabolic networks in animals.This dissertation is studied in terms of methodology and applications as follows:1.An analytical method of FDG-PET brain metabolic network in animals has been established.The reliability of this method is evaluated with the help of FDG-PET brain imaging data in healthy rats and rats with brain disease models.It lays the foundation for the application of analytical methods of the FDG-PET brain metabolic network in different animal model studies.2.The established brain metabolic network analysis method was applied in a contextual fear memory FDG-PET imaging study in rats,and explored the spatiotemporal dynamics of the brain network cooperation patterns involved in fear memory formation and retrieval.Fear memory is a protective mechanism for animals to adapt to complex survival environments as well as a common model for studying memory mechanisms.We first acquired the FDG-PET brain images in rats during the fear memory formation and retrieval,and then constructed brain metabolic networks in rats during the fear memory formation and retrieval.Subsequently,we obtained the variation of the hub nodes of the brain metabolic network across memory formation and retrieval.Finally,the memory encoding module,memory storage module and memory retrieval module were found in the brain metabolic network through the analysis of the modular properties of the network.Our results revealed the spatiotemporal dynamic patterns of brain metabolic networks involved in the encoding,storage,and retrieval of fear memories and provided insight into understanding the mechanisms underlying the formation and retrieval of memories.3.The functional differentiation of the rat retrosplenial cortex(RSC)in the contextual fear memory formation was explored by using the established brain metabolic network analysis method combined with pharmacological genetic techniques.The metabolic decline of the RSC is one of the earliest features of mild cognitive impairment,and the RSC plays an important role in memory formation.The rat RSC is one of the largest cortices in this species,but whether there is functional heterogeneity in its two major subregions(the retrosplenial dysgranular cortex,RSCd,and retrosplenial granular cortex,RSCg)during the memory formation is unknown.We used a pharmacogenetic technique to specifically inhibit the functional activity of RSCd or RSCg in rats during the formation of fear memory and acquired rat FDG-PET brain images.The behavioral data revealed that functional abnormalities in RSCd caused a significant impairment in fear memory formation,while functional abnormalities in RSCg did not significantly affect fear memory formation.Metabolic connectivity analysis of the network revealed that suppression of RSCd activity resulted in a significant reduction in network connectivity of the hippocampus-amygdala circuit.Our results indicate that there is functional differentiation in RSC during fear memory formation,and RSCd is an indispensable part of fear memory formation.Our study provides valuable clues in exploring the pathogenesis of memory impairment.4.The established brain metabolic network analysis method is combined with the reversal learning model to investigate the brain network cooperation patterns involved in the cognitive flexibility of animals.Cognitive flexibility is the basis for animals to rapidly learn new rules and adapt to new environments.The reversal learning model is commonly used to study the neural mechanisms of cognitive flexibility.Previous studies have demonstrated that the execution of cognitive flexibility involves the participation of multiple functional systems of the brain.However,the core brain regions that trigger cognitive flexibility and the cooperative mechanisms of these functional systems are unknown.We investigated the brain network mechanisms underlying cognitive flexibility using FDG-PET imaging and the reversal learning model in tree shrews.We found that the behavioral monitoring functional system with the nucleus accumbens as a key structure and the executive control system with the prefrontal cortex as a key node comprise the reversal learning network in tree shrews.These findings provide a direct molecular imaging basis for understanding the neural mechanisms of cognitive flexibility and searching for underlying pathomechanisms associated with impaired cognitive flexibility function.