Seeing glutamate at central synapses

Exploring the L-shaped relationship between Atherogenic Index of Plasma and depression: Results from NHANES 2005-2018

BACKGROUND

The Atherogenic Index of Plasma (AIP) is a novel metric linked to several diseases. However, there is inadequate evidence to investigate the relationship between AIP and depression. Therefore, we aim to elucidate the non-linear association between AIP and depression.

METHODS

12,453 participants from the National Health and Nutrition Examination Survey (NHANES) 2005-2018 were included. The AIP was calculated as log10 (triglycerides/high-density lipoprotein cholesterol). The Patient Health Questionnaire (PHQ-9) was used to identify depression (PHQ-9 ≥ 10). Weighted multivariate logistic regression, restricted cubic splines (RCS) models, subgroup analysis, and interaction tests were employed to reveal the relationship between AIP and depression.

RESULTS

AIP was found to be significantly correlated with depression. In the fully adjusted model, elevated AIP levels were associated with higher odds of depression (odds ratio [OR] = 1.50; 95 % CI: 1.06-2.12). The RCS analysis indicated an L-shaped pattern in the relationship between depression and AIP, with inflection points at -0.289. Beyond this inflection point, individuals with elevated AIP levels were associated with higher odds of depression (OR = 2.25; 95 % CI: 1.49-3.39). Notably, the association was particularly pronounced among individuals with diabetes.

LIMITATION

This cross-sectional study is unable to establish causal relationships.

CONCLUSION

There was an L-shaped association between AIP and depression among US adults. AIP has the potential value as a biological marker for depression, and maintaining AIP values below a certain threshold may help in managing depression.

Integrated UHPLC-MS untargeted metabolomics and gut microbe metabolism pathway-targeted metabolomics to reveal the prevention mechanism of Gushudan on kidney-yang-deficiency-syndrome rats

Gushudan (GSD) was a traditional Chinese prescription with the remarkable effect of kidney-tonifying and bone-strengthening. However, the potential prevention mechanisms of the GSD on kidney-yang-deficiency-syndrome (KYDS) and its regulation on gut microbe metabolism still need to be further systematically investigated. This study established untargeted urinary metabolomics based on RP/HILIC-UHPLC-Q-Orbitrap HRMS and combined with multivariate statistical analysis to discover differential metabolites and key metabolic pathways. And the gut microbe metabolism pathway-targeted metabolomic based on HILIC-UHPLC-MS/MS was developed and validated to simultaneously determine 15 gut microbe-mediated metabolites in urine samples from the control group (CON), KYDS model group (MOD), GSD-treatment group (GSD) and positive group (POS). The results showed that a total of 36 differential metabolites were discovered in untargeted metabolomics. These differential metabolites included proline, cytosine, butyric acid and nicotinic acid, which were primarily involved in the gut microbe metabolism, amino acid metabolism, energy metabolism and nucleotide metabolism. And GSD played a role in preventing KYDS by regulating these metabolic pathways. The targeted metabolomics found that the levels of 10 gut microbe-mediated metabolites had significant differences in different groups. Among them, compared with the CON group, the levels of lysine, tryptophan, phenylacetylglycine and hippuric acid were increased in the MOD group, while the levels of threonine, leucine, dimethylamine, trimethylamine, succinic acid and butyric acid were decreased, which verified the disorders of gut microbe metabolism in the KYDS rats and GSD had a significant regulatory effect on this disorder. As well as by comparing analysis, it was found that the experimental results were consistent with previous metabolomics and microbiomics of fecal samples. Therefore, this integrated strategy of untargeted and targeted metabolomics not only elucidated the potential prevention mechanism of GSD on KYDS, but also provided a scientific basis for GSD preventing KYDS via the "gut-kidney" axis.

γ-Oryzanol from Rice Bran Antagonizes Glutamate-Induced Excitotoxicity in an In Vitro Model of Differentiated HT-22 Cells

The excessive activation of glutamate in the brain is a factor in the development of vascular dementia. γ-Oryzanol is a natural compound that has been shown to enhance brain function, but more research is needed to determine its potential as a treatment for vascular dementia. This study investigated if γ-oryzanol can delay or improve glutamate neurotoxicity in an in vitro model of differentiated HT-22 cells and explored its neuroprotective mechanisms. The differentiated HT-22 cells were treated with 0.1 mmol/L glutamate for 24 h then given γ-oryzanol at appropriate concentrations or memantine (10 µmol/L) for another 24 h. Glutamate produced reactive oxygen species and depleted glutathione in the cells, which reduced their viability. Mitochondrial dysfunction was also observed, including the inhibition of mitochondrial respiratory chain complex I activity, the collapse of mitochondrial transmembrane potential, and the reduction of intracellular ATP levels in the HT-22 cells. Calcium influx triggered by glutamate subsequently activated type II calcium/calmodulin-dependent protein kinase (CaMKII) in the HT-22 cells. The activation of CaMKII-ASK1-JNK MAP kinase cascade, decreased Bcl-2/Bax ratio, and increased Apaf-1-dependent caspase-9 activation were also observed due to glutamate induction, which were associated with increased DNA fragmentation. These events were attenuated when the cells were treated with γ-oryzanol (0.4 mmol/L) or the N-methyl-D-aspartate receptor antagonist memantine. The results suggest that γ-oryzanol has potent neuroprotective properties against glutamate excitotoxicity in differentiated HT-22 cells. Therefore, γ-oryzanol could be a promising candidate for the development of therapies for glutamate excitotoxicity-associated neurodegenerative diseases, including vascular dementia.

Major depressive disorder: hypothesis, mechanism, prevention and treatment

Worldwide, the incidence of major depressive disorder (MDD) is increasing annually, resulting in greater economic and social burdens. Moreover, the pathological mechanisms of MDD and the mechanisms underlying the effects of pharmacological treatments for MDD are complex and unclear, and additional diagnostic and therapeutic strategies for MDD still are needed. The currently widely accepted theories of MDD pathogenesis include the neurotransmitter and receptor hypothesis, hypothalamic-pituitary-adrenal (HPA) axis hypothesis, cytokine hypothesis, neuroplasticity hypothesis and systemic influence hypothesis, but these hypothesis cannot completely explain the pathological mechanism of MDD. Even it is still hard to adopt only one hypothesis to completely reveal the pathogenesis of MDD, thus in recent years, great progress has been made in elucidating the roles of multiple organ interactions in the pathogenesis MDD and identifying novel therapeutic approaches and multitarget modulatory strategies, further revealing the disease features of MDD. Furthermore, some newly discovered potential pharmacological targets and newly studied antidepressants have attracted widespread attention, some reagents have even been approved for clinical treatment and some novel therapeutic methods such as phototherapy and acupuncture have been discovered to have effective improvement for the depressive symptoms. In this work, we comprehensively summarize the latest research on the pathogenesis and diagnosis of MDD, preventive approaches and therapeutic medicines, as well as the related clinical trials.

Nonlinear slow-timescale mechanisms in synaptic plasticity

Learning and memory rely on synapses changing their strengths in response to neural activity. However, there is a substantial gap between the timescales of neural electrical dynamics (1-100 ms) and organism behaviour during learning (seconds-minutes). What mechanisms bridge this timescale gap? What are the implications for theories of brain learning? Here I first cover experimental evidence for slow-timescale factors in plasticity induction. Then I review possible underlying cellular and synaptic mechanisms, and insights from recent computational models that incorporate such slow-timescale variables. I conclude that future progress in understanding brain learning across timescales will require both experimental and computational modelling studies that map out the nonlinearities implemented by both fast and slow plasticity mechanisms at synapses, and crucially, their joint interactions.

Targeted sensors for glutamatergic neurotransmission

Optical report of neurotransmitter release allows visualisation of excitatory synaptic transmission. Sensitive genetically-encoded fluorescent glutamate reporters operating with a range of affinities and emission wavelengths are available. However, without targeting to synapses, the specificity of the fluorescent signal is uncertain, compared to sensors directed at vesicles or other synaptic markers. We fused the state-of-the-art reporter iGluSnFR to glutamate receptor auxiliary proteins in order to target it to postsynaptic sites. Chimeras of Stargazin and gamma-8 that we named SnFR-γ2 and SnFR-γ8, were enriched at synapses, retained function and reported spontaneous glutamate release in rat hippocampal cells, with apparently diffraction-limited spatial precision. In autaptic mouse neurons cultured on astrocytic microislands, evoked neurotransmitter release could be quantitatively detected at tens of synapses in a field of view whilst evoked currents were recorded simultaneously. These experiments revealed a specific postsynaptic deficit from Stargazin overexpression, resulting in synapses with normal neurotransmitter release but without postsynaptic responses. This defect was reverted by delaying overexpression. By working at different calcium concentrations, we determined that SnFR-γ2 is a linear reporter of the global quantal parameters and short-term synaptic plasticity, whereas iGluSnFR is not. On average, half of iGluSnFR regions of interest (ROIs) showing evoked fluorescence changes had intense rundown, whereas less than 5% of SnFR-γ2 ROIs did. We provide an open-source analysis suite for extracting quantal parameters including release probability from fluorescence time series of individual and grouped synaptic responses. Taken together, postsynaptic targeting improves several properties of iGluSnFR and further demonstrates the importance of subcellular targeting for optogenetic actuators and reporters.