Vesicle Cycle Research Articles

Transcriptome-wide association study reveals cholesterol metabolism gene Lpl is a key regulator of cognitive dysfunction.

Cholesterol metabolism in the brain plays a crucial role in normal physiological function, and its aberrations are associated with cognitive dysfunction. The present study aimed to determine which cholesterol-related genes play a vital role in cognitive dysfunction and to dissect its underlying molecular mechanisms using a systems genetics approach in the BXD mice family. We first systematically analyzed the association of expression of 280 hippocampal genes related to cholesterol metabolism with cognition-related traits and identified lipoprotein lipase (Lpl) as a critical regulator. This was further confirmed by phenome-wide association studies that indicate Lpl associated with hippocampus volume residuals and anxiety-related traits. By performing expression quantitative trait locus mapping, we demonstrate that Lpl is strongly cis-regulated in the BXD hippocampus. We also identified ∼3,300 genes significantly (p < 0.05) correlated with the Lpl expression. Those genes are mainly involved in the regulation of neuron-related traits through the MAPK signaling pathway, axon guidance, synaptic vesicle cycle, and NF-kappa B signaling pathway. Furthermore, a protein-protein interaction network analysis identified several direct interactors of Lpl, including Rab3a, Akt1, Igf1, Crp, and Lrp1, which indicates that Lpl involves in the regulation of cognitive dysfunction through Rab3a-mediated synaptic vesicle cycle and Akt1/Igf1/Crp/Lrp1-mediated MAPK signaling pathway. Our findings demonstrate the importance of the Lpl, among the cholesterol-related genes, in regulating cognitive dysfunction and highlighting the potential signaling pathways, which may serve as novel therapeutic targets for the treatment of cognitive dysfunction.

Screening Key Pathogenic Genes and Small Molecule Compounds for PNET.

Primitive neuroectodermal tumors (PNET) are rare malignant tumors, but the mortality rate of the patients is extremely high. The aim of this study was to identify the hub genes and pathways involved in the pathogenesis of PNET and to screen the potential small molecule drugs for PNET. We extracted gene expression profiles from the Gene Expression Omnibus database and identified differentially expressed genes (DEGs) through Limma package in R. Two expression profiles (GSE14295 and GSE74195) were downloaded, including 33 and 5 cases separately. Four hundred sixty-eight DEGs (161 upregulated; 307 downregulated) were identified. Functional annotation and KEGG pathway enrichment of the DEGs were performed using DAVID and Kobas. Gene Ontology analysis showed the significantly enriched Gene Ontology terms included but not limited to mitosis, nuclear division, cytoskeleton, synaptic vesicle, syntaxin binding, and GABA A receptor activity. Cancer-related signaling pathways, such as DNA replication, cell cycle, and synaptic vesicle cycle, were found to be associated with these genes. Subsequently, the STRING database and Cytoscape were utilized to construct a protein-protein interaction and screen the hub genes, and we identified 5 hub genes (including CCNB1, CDC20, KIF11, KIF2C, and MAD2L1) as the key biomarkers for PNET. Finally, we identified potential small molecule drugs through CMap. Seven small molecule compounds, including trichostatin A, luteolin, repaglinide, clomipramine, lorglumide, vorinostat, and resveratrol may become potential candidates for PNET drugs.

The Role of Membrane Affinity and Binding Modes in Alpha-Synuclein Regulation of Vesicle Release and Trafficking.

Alpha-synuclein is a presynaptic protein linked to Parkinson's disease with a poorly characterized physiological role in regulating the synaptic vesicle cycle. Using RBL-2H3 cells as a model system, we earlier reported that wild-type alpha-synuclein can act as both an inhibitor and a potentiator of stimulated exocytosis in a concentration-dependent manner. The inhibitory function is constitutive and depends on membrane binding by the helix-2 region of the lipid-binding domain, while potentiation becomes apparent only at high concentrations. Using structural and functional characterization of conformationally selective mutants via a combination of spectroscopic and cellular assays, we show here that binding affinity for isolated vesicles similar in size to synaptic vesicles is a primary determinant of alpha-synuclein-mediated potentiation of vesicle release. Inhibition of release is sensitive to changes in the region linking the helix-1 and helix-2 regions of the N-terminal lipid-binding domain and may require some degree of coupling between these regions. Potentiation of release likely occurs as a result of alpha-synuclein interactions with undocked vesicles isolated away from the active zone in internal pools. Consistent with this, we observe that alpha-synuclein can disperse vesicles from in vitro clusters organized by condensates of the presynaptic protein synapsin-1.

Transcriptome profile and its partly verification of human hepatocellular carcinoma cells exposed to Yuzhizi () seed extract.

To investigate the efficacy of Yuzhizi seed extract (FAQSE) on inhibiting the proliferation of hepatocellular carcinoma (HCC) cells in vitro and to explore the anti-HCC action mechanism of FAQSE. Human HCC HepG2 and Huh7 cells were used to investigate the anti-HCC effect of FAQSE. 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyl tetrazolium bromide (MTT) method was used to measure cell viability. Affymetrix microarray was adopted to detect the expression of transcriptome. The differentially expressed genes (DEGs) of each cell line were identified. For co-DEGs of both cell lines, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were enriched using the Database for Annotation, Visualization and Integrated Discovery (DAVID), and the network analysis of protein-protein interaction (PPI) was mapped using the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape software. Some important genes in the PPI network of co-DEGs were selected to verify by quantitative real-time reverse transcription-polymerase chain reaction, Western blot and enzyme-linked immunosorbent assay. FAQSE decreased the viability of HepG2 and Huh7 cells. There were 211 co-upregulated and 86 co-downregualted genes in both cell lines after FAQSE treatment. The enriched GO terms of co-upregulated DEGs were primarily involved cell-cell adhesion, viral process, transcription initiation from RNA polymerase II promoter, positive regulation of transcription from RNA polymerase II promoter and actin cytoskeleton organization. The GO terms of co-downregulated DEGs were mainly enriched in the processes of SRP-dependent cotranslational protein targeting to membrane, viral transcription, nuclear-transcribed mRNA catabolic process, nonsense-mediated decay, translational initiation and rRNA processing. Main KEGG pathways of co-upregulated DEGs were endocytosis, glutathione metabolism, protein processing in endoplasmic reticulum, synaptic vesicle cycle and lysosome. The major KEGG pathways of co-downregulated DEGs were ribosome, biosynthesis of amino acids, arginine and proline metabolism, systemic lupus erythematosus and complement and coagulation cascades. The top 10 co-DEGs with high hub nodes in STRING analysis were ribosomal protein S27a, transferrin, ribosomal protein S20, ribosomal protein L9, protein phosphatase 2 regulatory subunit B alpha, transthyretin, thioredoxin reductase 1, ribosomal protein L3, ribophorin I and ribosomal protein L24. Alpha-fetoprotein (AFP) was also co-downregulated and contained in the PPI network. The mRNA and protein expression of most verified genes was consistent with the results of co-DEGs analysis. And the AFP level was significantly reduced after FAQSE treatment. A series of genes and pathways of HepG2 and Huh7 cells were changed after FAQSE treatment, which might be the targets of FAQSE against HCC and worthy of further study. AFP might be important one of them.

The Mood Stabilizer Lithium Slows Down Synaptic Vesicle Cycling at Glutamatergic Synapses.

Lithium is a mood stabilizer broadly used to prevent and treat symptoms of mania and depression in people with bipolar disorder (BD). Little is known, however, about its mode of action. Here, we analyzed the impact of lithium on synaptic vesicle (SV) cycling at presynaptic terminals releasing glutamate, a neurotransmitter previously implicated in BD and other neuropsychiatric conditions. We used the pHluorin-based synaptic tracer vGpH and a fully automated image processing pipeline to quantify the effect of lithium on both SV exocytosis and endocytosis in hippocampal neurons. We found that lithium selectively reduces SV exocytic rates during electrical stimulation, and markedly slows down SV recycling post-stimulation. Analysis of single-bouton responses revealed the existence of functionally distinct excitatory synapses with varying sensitivity to lithium-some terminals show responses similar to untreated cells, while others are markedly impaired in their ability to recycle SVs. While the cause of this heterogeneity is unclear, these data indicate that lithium interacts with the SV machinery and influences glutamate release in a large fraction of excitatory synapses. Together, our findings show that lithium down modulates SV cycling, an effect consistent with clinical reports indicating hyperactivation of glutamate neurotransmission in BD.

Confinement induces oxidative damage and synaptic dysfunction in mice.

A confined environment is an enclosed area where entry or exit is highly restricted, which is a risk factor for a work crew's mental health. Previous studies have shown that a crew is more susceptible to developing anxiety or depression in a confined environment. However, the underlying mechanism by which negative emotion is induced by confinement is not fully understood. Hence, in this study, mice were retained in a tube to simulate short-term confinement. The mice exhibited depressive-like behavior. Additionally, the levels of H2O2 and malondialdehyde in the prefrontal cortex were significantly increased in the confinement group. Furthermore, a label-free quantitative proteomic strategy was applied to analyze the abundance of proteins in the prefrontal cortex of mice. A total of 71 proteins were considered differentially abundant proteins among 3,023 identified proteins. Two differentially abundant proteins, superoxide dismutase [Mn] and syntaxin-1A, were also validated by a parallel reaction monitoring assay. Strikingly, the differentially abundant proteins were highly enriched in the respiratory chain, oxidative phosphorylation, and the synaptic vesicle cycle, which might lead to oxidative damage and synaptic dysfunction. The results of this study provide valuable information to better understand the mechanisms of depressive-like behavior induced by confined environments.

Integrated bioinformatics-based identification of diagnostic markers in Alzheimer disease.

Alzheimer disease (AD) is a progressive neurodegenerative disease resulting from the accumulation of extracellular amyloid beta (Aβ) and intracellular neurofibrillary tangles. There are currently no objective diagnostic measures for AD. The aim of this study was to identify potential diagnostic markers for AD and evaluate the role of immune cell infiltration in disease pathogenesis. AD expression profiling data for human hippocampus tissue (GSE48350 and GSE5281) were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using R software and the Human Protein Atlas database was used to screen AD-related DEGs. We performed functional enrichment analysis and established a protein-protein interaction (PPI) network to identify disease-related hub DEGs. The fraction of infiltrating immune cells in samples was determined with the Microenvironment Cell Populations-counter method. The random forest algorithm was used to develop a prediction model and receiver operating characteristic (ROC) curve analysis was performed to validate the diagnostic utility of the candidate AD markers. The correlation between expression of the diagnostic markers and immune cell infiltration was also analyzed. A total of 107 AD-related DEGs were screened in this study, including 28 that were upregulated and 79 that were downregulated. The DEGs were enriched in the Gene Ontology terms GABAergic synapse, Morphine addiction, Nicotine addiction, Phagosome, and Synaptic vesicle cycle. We identified 10 disease-related hub genes and 20 candidate diagnostic genes. Synaptophysin (SYP) and regulator of G protein signaling 4 (RGS4) (area under the ROC curve = 0.909) were verified as potential diagnostic markers for AD in the GSE28146 validation dataset. Natural killer cells, B lineage cells, monocytic lineage cells, endothelial cells, and fibroblasts were found to be involved in AD; additionally, the expression levels of both SYP and RGS4 were negatively correlated with the infiltration of these immune cell types. These results suggest that SYP and RGS4 are potential diagnostic markers for AD and that immune cell infiltration plays an important role in AD development and progression.

Difference analysis of intestinal microbiota and metabolites in piglets of different breeds exposed to porcine epidemic diarrhea virus infection.

The gut microbial composition of the Luchuan (LC) piglet, one of China's native breeds, has rarely been studied, especially when compared to other breeds. This study developed a porcine epidemic diarrhea virus (PEDV) infection model in LC and Largewhite (LW) piglets, and analyzed the patterns and differences of intestinal microbial communities and metabolites in piglets of these two breeds after infection. The diarrhea score, survival time, and distribution of viral antigens in the intestine of piglets infected with PEDV differed among breeds, with the jejunal immunohistochemistry score of LW piglets being significantly higher than that of LC piglets (P < 0.001). The results of 16S rRNA sequencing showed differences in microbial diversity and community composition in the intestine of piglets with different breeds between PEDV infection piglets and the healthy controls. There were differences in the species and number of dominant phyla and dominant genera in the same intestinal segment. The relative abundance of Shigella in the jejunum of LC piglets after PEDV infection was significantly lower than that of LW piglets (P < 0.05). The key microorganisms differed in the microbiota were Streptococcus alactolyticus, Roseburia faecis, Lactobacillus iners, Streptococcus equi, and Lactobacillus mucosae (P < 0.05). The non-targeted metabolite analysis revealed that intestinal metabolites showed great differences among the different breeds related to infection. Spearman correlation analysis was conducted to examine any links between the microbiota and metabolites. The metabolites in the intestine of different breeds related to infection were mainly involved in arginine biosynthesis, synaptic vesicle cycle, nicotinic acid and nicotinamide metabolism and mTOR signaling pathway, with significantly positive or negative correlations (P < 0.05) between the various microorganisms. This study provides a theoretical foundation for investigating the application of core microorganisms in the gut of piglets of different breeds in the digestive tracts of those infected with PEDV, and helps to tackle the antimicrobial resistance problem further.

Computational models of neurotransmission at cerebellar synapses unveil the impact on network computation.

The neuroscientific field benefits from the conjoint evolution of experimental and computational techniques, allowing for the reconstruction and simulation of complex models of neurons and synapses. Chemical synapses are characterized by presynaptic vesicle cycling, neurotransmitter diffusion, and postsynaptic receptor activation, which eventually lead to postsynaptic currents and subsequent membrane potential changes. These mechanisms have been accurately modeled for different synapses and receptor types (AMPA, NMDA, and GABA) of the cerebellar cortical network, allowing simulation of their impact on computation. Of special relevance is short-term synaptic plasticity, which generates spatiotemporal filtering in local microcircuits and controls burst transmission and information flow through the network. Here, we present how data-driven computational models recapitulate the properties of neurotransmission at cerebellar synapses. The simulation of microcircuit models is starting to reveal how diverse synaptic mechanisms shape the spatiotemporal profiles of circuit activity and computation.

Analysis of exosomal competing endogenous RNA network response to paclitaxel treatment reveals key genes in advanced gastric cancer

Exosome is an important component of the tumor immune microenvironment and plays critical role in cancer pathogenesis. The exosome transcriptome of gastric cancer (GC) response to paclitaxel chemotherapy has not been investigated in the past. ceRNA microarrays were performed in exosomes from six advanced GC patients before and after paclitaxel treatment. Bioinformatics tools were used to identify differential expressing genes and construct competing endogenous RNA (ceRNA) networks. The importance of hub genes in the ceRNA network was confirmed by survival analysis and functional analysis. A total of 213 differential mRNAs, 370 lncRNAs, and 376 circRNAs were identified, and hub genes in ceRNA networks were screened. The differential genes were associated with GO terms SNAP complex, gap junction, protein transporter activity, cytokine receptor, and KEGG pathways synaptic vesicle cycle, propanoate metabolism, Epstein-Barr virus infection, heparin, and steroid biosynthesis, and beta-alanine metabolism. ULK2, CYP2R1, BTLA, and miR-105-5p are prognostic genes for overall survival. Paclitaxel may target ULK2 which is involved in mitosis and cell cycle. miR-105-5p may target ULK2 3'UTR. The work for the first time identified exosomal RNA biomarkers and constructed a ceRNA network in GC response to paclitaxel, revealed novel molecular mechanisms of GC, and provided new candidates for GC diagnosis and treatment.

Development and assessment of diabetic nephropathy prediction model using hub genes identified by weighted correlation network analysis

Diabetic nephropathy (DN) is one microvascular complication of diabetes. About 30% of diabetic patients can develop DN, which is closely related to the high incidence and mortality of heart diseases, and then develop end-stage renal diseases. Therefore, early detection and screening of high-risk patients with DN is important. Herein, we explored the differences of serum transcriptomics between DN and non-DN in type II diabetes mellitus (T2DM) patients. We obtained 110 target genes using weighted correlation network analysis. Gene Ontology enrichment analysis indicates these target genes are mainly related to membrane adhesion, alpha-amino acid biosynthesis, metabolism, and binding, terminus, inhibitory synapse, clathrinid-sculpted vesicle, kinase activity, hormone binding, receptor activity, and transporter activity. Kyoto Encyclopedia of Genes and Genomes analysis indicates the process of DN in diabetic patients can involve synaptic vesicle cycle, cysteine and methionine metabolism, N-Glycan biosynthesis, osteoclast differentiation, and cAMP signaling pathway. Next, we detected the expression levels of hub genes in a retrospective cohort. Then, we developed a risk score tool included in the prediction model for early DN in T2DM patients. The prediction model was well applied into clinical practice, as confirmed by internal validation and several other methods. A novel DN risk model with relatively high prediction accuracy was established based on clinical characteristics and hub genes of serum detection. The estimated risk score can help clinicians develop individualized intervention programs for DN in T2DM. External validation data are required before individualized intervention measures.

Synaptophysin transmembrane domain III controls fusion pore dynamics in Ca2+-triggered exocytosis

Synaptophysin (syp) is a major protein of secretory vesicles with four transmembrane domains (TMDs) and a large cytoplasmic C-terminus. Syp has been shown to regulate exocytosis, vesicle cycling, and synaptic plasticity through its C-terminus. However, the roles of its TMDs remain unclear. The TMDs of soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins are thought to line initial fusion pores, and structural work together with sequence analysis suggest that TMD III of syp may play a similar role. To test this hypothesis, we performed tryptophan scanning experiments of TMD III in chromaffin cells and used amperometry to evaluate fusion pores. In contrast to SNARE TMDs, tryptophan substitutions in syp TMD III had no effect on the flux through initial fusion pores. However, a number of these mutants increased the fraction of kiss-and-run events and decreased the initial fusion pore lifetime. These results indicate that TMD III stabilizes the initial fusion pore and controls the initial choice between kiss and run and full fusion. Late-stage fusion pores were not impacted by TMD III mutations. These results indicate that syp TMD III does not line the initial fusion pore. However, its impact on pore dynamics suggests that it interacts with a SNARE protein implicated as a part of the fusion pore that forms at the onset of exocytosis.

Protective effects and regulatory pathways of melatonin in traumatic brain injury mice model: Transcriptomics and bioinformatics analysis.

Traumatic brain injury (TBI) is the leading cause of disability and mortality globally. Melatonin (Mel) is a neuroendocrine hormone synthesized from the pineal gland that protects against TBI. Yet, the precise mechanism of action is not fully understood. In this study, we examined the protective effect and regulatory pathways of melatonin in the TBI mice model using transcriptomics and bioinformatics analysis. The expression profiles of mRNA, long non-coding RNA (lncRNA), microRNA (miRNA), and circular RNA (circRNA) were constructed using the whole transcriptomes sequencing technique. In total, 93 differentially expressed (DE) mRNAs (DEmRNAs), 48 lncRNAs (DElncRNAs), 59 miRNAs (DEmiRNAs), and 59 circRNAs (DEcircRNAs) were identified by the TBI mice with Mel treatment compared to the group without drug intervention. The randomly selected coding RNAs and non-coding RNAs (ncRNAs) were identified by quantitative real-time polymerase chain reaction (qRT-PCR). To further detect the biological functions and potential pathways of those differentially expressed RNAs, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were executed. In our research, the regulatory network was constructed to show the relationship of lncRNA-RBPs. The lncRNA-mRNA co-expression network was established based on the Pearson coefficient to indicate the expression correlations. Moreover, the DEcircRNA–DEmiRNA–DEmRNA and DElncRNA–DEmiRNA–DEmRNA regulatory networks were constructed to demonstrate the regulatory relationship between ncRNAs and mRNA. Finally, to further verify our predicted results, cytoHubba was used to find the hub gene in the synaptic vesicle cycle pathway, and the expression level of SNAP-25 and VAMP-2 after melatonin treatment were detected by Western blotting and immunofluorescence. To sum up, these data offer a new insight regarding the molecular effect of melatonin treatment after TBI and suggest that the high-throughput sequencing and analysis of transcriptomes are useful for studying the drug mechanisms in treatment after TBI.

Exposure to the environmentally toxic pesticide maneb induces Parkinson's disease-like neurotoxicity in mice: A combined proteomic and metabolomic analysis

Maneb is a typical dithiocarbamate fungicide that has been extensively used worldwide. Epidemiological evidence shows that exposure to maneb is an environmental risk factor for Parkinson's disease (PD). However, the mechanisms underlying maneb-induced neurotoxicity have yet to be elucidated. In this study, we exposed SH-SY5Y cells to maneb at environmentally relevant concentrations (0, 0.1, 5, 10 mg/L) and found that maneb dose-dependently decreased the cell viability. Furthermore, maneb (60 mg/kg) induced PD-like motor impairment in α-synuclein A53T transgenic mice. The results of tandem mass tag (TMT) proteomics and metabolomics studies of mouse brain and serum revealed significant changes in proteins and metabolites in the pathways involved in the neurotransmitter system. The omics results were verified by targeted metabolomics and Western blot analysis, which demonstrated that maneb induced disturbance of the PD-related pathways, including the phenylalanine and tryptophan metabolism pathways, dopaminergic synapse, synaptic vesicle cycle, mitochondrial dysfunction, and oxidative stress. In addition, the PD-like phenotype induced by maneb was attenuated by the asparagine endopeptidase (AEP) inhibitor compound #11 (CP11) (10 mg/kg), indicating that AEP may play a role in maneb-induced neurotoxicity. To the best of our knowledge, this is the first study to investigate the molecular mechanisms underlying maneb-induced PD-like phenotypes using multiomics analysis, which identified novel therapeutic targets for PD associated with pesticides and other environmental pollutants.

Application and prospect of quasi-targeted metabolomics in age-related hearing loss

Age-related hearing loss (ARHL) is a common sensory deficit in the elderly, which seriously affects physical and mental health. Therefore, understanding its underlying molecular mechanisms and taking interventions to treat ARHL are urgently needed. In our study, cochlea of 4-week-old C57BL/6 mice as the Youth group (n = 6) and 48-week-old cochlea as the Old group (n = 6) were subjected to quasi-targeted metabolomics analysis by Ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). In total, 208 differential metabolites were identified in 12 cochlea samples, which highlighted the following discriminant compounds: tryptophan, piperidine, methionine, L-arginine, histamine, serotonin, acetylcholine, and 4-aminobutyric acid. Differentially expressed metabolites were identified which were involved in KEGG pathways related to the digestion and absorption of oxidative stress associated amino acids, Synaptic vesicle cycle of serotonin, Pantothenate and CoA Biosynthesis. These findings are a first step toward elucidating the pathophysiological pathways involved in the etiology of ARHL and provide the possibility to further explore the mechanisms of ARHL using metabolomic analysis.

Chronic neurotransmission increases the susceptibility of lateral-line hair cells to ototoxic insults.

Sensory hair cells receive near constant stimulation by omnipresent auditory and vestibular stimuli. To detect and encode these stimuli, hair cells require steady ATP production, which can be accompanied by a buildup of mitochondrial byproducts called reactive oxygen species (ROS). ROS buildup is thought to sensitize hair cells to ototoxic insults, including the antibiotic neomycin. Work in neurons has shown that neurotransmission is a major driver of ATP production and ROS buildup. Therefore, we tested whether neurotransmission is a significant contributor to ROS buildup in hair cells. Using genetics and pharmacology, we disrupted two key aspects of neurotransmission in zebrafish hair cells: presynaptic calcium influx and the fusion of synaptic vesicles. We find that chronic block of neurotransmission enhances hair-cell survival when challenged with the ototoxin neomycin. This reduction in ototoxin susceptibility is accompanied by reduced mitochondrial activity, likely due to a reduced ATP demand. In addition, we show that mitochondrial oxidation and ROS buildup are reduced when neurotransmission is blocked. Mechanistically, we find that it is the synaptic vesicle cycle rather than presynaptic- or mitochondrial-calcium influx that contributes most significantly to this metabolic stress. Our results comprehensively indicate that, over time, neurotransmission causes ROS buildup that increases the susceptibility of hair cells to ototoxins.

A Comprehensive Quantitative and Biological Neural Network Optimization Model of Sports Industry Structure Based on Knowledge Mapping.

In this paper, a comprehensive quantitative and biological neural network optimization model of sports industry structure is thoroughly studied and analyzed using knowledge graphs. To address the problems of poor performance interpretability deficiency of knowledge graph-based recommendation methods in the face of relational sparse graphs, a pretraining-based implicit characterization algorithm strategy is proposed for the recall stage, which can solve the problems of difficulty in going online and high delay in the recall stage of the recommendation system while improving the accuracy, and not only this can be applied in the recall stage, but also the sorting and postsorting modules can be used as features. To study the relationship between signaling activity and energy metabolism of pyramidal neurons, an empirical model of the synaptic vesicle cycle is proposed to simulate the synaptic transmission process, the role played by energy metabolism in synaptic transmission is studied from the perspective of feedback control, and the quantitative relationship between neuronal pulse discharge frequency, energy consumption, and information quantity in dendritic integration is analyzed using the cable theory and atrial chamber model. It was found that, when 0 ≤ ε ≤ 0.6, the chaotic region shrinks and eventually disappears with the increase of the memory factor ε; however, when 0.6 ≤ ε ≤ 1 is used, chaos is recreated and the chaotic area gradually increases with the increase of the memory factor ε. This paper conducts comparative experiments on data sets in the recommendation domain and verifies that the proposed model and the feature intersection module can effectively perform feature interaction between items and entities, thus enhancing the recommendation effect.

Changes in rat spatial learning and memory as well as serum exosome proteins after simultaneous exposure to 1.5 GHz and 4.3 GHz microwaves

This study aimed to elucidate the effects and biological targets sensitive to simultaneous 1.5 and 4.3 GHz microwave exposure in rats. A total of 120 male Wistar rats were divided randomly into four groups: the sham (S group), 1.5 GHz microwave exposure (L group), 4.3 GHz microwave exposure (C group) and simultaneous 1.5 and 4.3 GHz microwave exposure (LC group) groups. Spatial learning and memory, cortical electrical activity, and hippocampal ultrastructure were assessed by the Morris Water Maze, electroencephalography, and transmission electron microscopy, respectively. Additionally, serum exosomes were isolated by ultracentrifugation and assessed by Western blotting, nanoparticle tracking and transmission electron microscopy. The serum exosome protein content was assessed by label-free quantitative proteomics. Impaired spatial learning and memory decreased cortical excitability, and damage to the hippocampal ultrastructure were observed in groups exposed to microwaves, especially the L and LC groups. A total of 54, 145 and 296 exosomal proteins were differentially expressed between the S group and the L, C and LC groups, respectively. These differentially expressed proteins were involved in the synaptic vesicle cycle and SNARE interactions during vesicular transport. Additionally, VAMP8, Syn7 and VMAT are potential serum markers of simultaneous microwave exposure. Thus, exposure to 1.5 and 4.3 GHz microwaves induced impairments in spatial learning and memory, and simultaneous microwave exposure had the most severe effects.

The effects of ruminant milk treatments on hippocampal, striatal, and prefrontal cortex gene expression in pigs as a model for the human infant.

While infant formula is usually bovine milk-based, interest in other ruminant milk-based formulas is growing. However, whether different ruminant milk treatments with varying nutrient compositions influence the infant’s brain development remains unknown. The aim was to determine the effects of consuming bovine, caprine, or ovine milk on brain gene expression in the early postnatal period using a pig model of the human infant. Starting at postnatal day 7 or 8, pigs were exclusively fed bovine, ovine, or caprine milk for 15 days. The mRNA abundance of 77 genes in the prefrontal cortex, hippocampus, and striatum regions was measured at postnatal day 21 or 22 using NanoString. The expression level of two hippocampal and nine striatal genes was most affected by milk treatments, particularly ovine milk. These modulatory genes are involved in glutamate, gamma-aminobutyric acid, serotonin, adrenaline and neurotrophin signaling and the synaptic vesicle cycle. The expression level of genes involved in gamma-aminobutyric acid signaling was associated with pigs’ lactose intake. In contrast, milk treatments did not affect the mRNA abundance of the genes in the prefrontal cortex. This study provides the first evidence of the association of different ruminant milk treatments with brain gene expression related to cognitive function in the first 3 months of postnatal life.

Molecular signatures underlying neurofibrillary tangle susceptibility in Alzheimer’s disease

Tau aggregation in neurofibrillary tangles (NFTs) is closely associated with neurodegeneration and cognitive decline in Alzheimer's disease (AD). However, the molecular signatures that distinguish between aggregation-prone and aggregation-resistant cell states are unknown. We developed methods for the high-throughput isolation and transcriptome profiling of single somas with NFTs from the human AD brain, quantified the susceptibility of 20 neocortical subtypes for NFT formation and death, and identified both shared and cell-type-specific signatures. NFT-bearing neurons shared a marked upregulation of synaptic transmission-related genes, including a core set of 63 genes enriched for synaptic vesicle cycling. Oxidative phosphorylation and mitochondrial dysfunction were highly cell-type dependent. Apoptosis was only modestly enriched, and the susceptibilities of NFT-bearing and NFT-free neurons for death were highly similar. Our analysis suggests that NFTs represent cell-type-specific responses to stress and synaptic dysfunction. We provide a resource for biomarker discovery and the investigation of tau-dependent and tau-independent mechanisms of neurodegeneration.