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"Liu, Renjie"
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Fat mass and obesity-associated protein regulates RNA methylation associated with depression-like behavior in mice
Post-transcriptional modifications of RNA, such as RNA methylation, can epigenetically regulate behavior, for instance learning and memory. However, it is unclear whether RNA methylation plays a critical role in the pathophysiology of major depression disorder (MDD). Here, we report that expression of the fat mass and obesity associated gene (FTO), an RNA demethylase, is downregulated in the hippocampus of patients with MDD and mouse models of depression. Suppressing
Fto
expression in the mouse hippocampus results in depression-like behaviors in adult mice, whereas overexpression of FTO expression leads to rescue of the depression-like phenotype. Epitranscriptomic profiling of N6-methyladenosine (m
6
A) RNA methylation in the hippocampus of
Fto
knockdown (KD),
Fto
knockout (cKO), and FTO-overexpressing (OE) mice allows us to identify adrenoceptor beta 2 (
Adrb2
) mRNA as a target of FTO. ADRB2 stimulation rescues the depression-like behaviors in mice and spine loss induced by hippocampal
Fto
deficiency, possibly via the modulation of hippocampal SIRT1 expression by c-MYC. Our findings suggest that FTO is a regulator of a mechanism underlying depression-like behavior in mice.
Post-transcriptional modification of RNA can contribute to regulating behavior. Here, the authors show that modulating the expression of
Fto
results in epitranscriptomic changes in the mouse hippocampus associated with depression-like behavior.
Journal Article
Association of Life’s Crucial 9 with cognitive function and stroke risk: insights from the NHANES 2011–2014 study
Background
Cognitive impairment and stroke constitute major health challenges for the aging global population, adversely impacting quality of life and increasing healthcare burdens. The American Heart Association’s “Life’s Essential 8” (LE8) framework has served as a key tool for evaluating cardiovascular health (CVH); however, it omits mental health, a critical factor influencing both cognitive function and stroke risk. The introduction of “Life’s Crucial 9” (LC9), which includes depressive symptoms, provides a more comprehensive approach. This study investigates the relationship between LC9, cognitive function, and stroke risk.
Methods
Utilizing the National Health and Nutrition Examination Survey (NHANES) dataset from 2011 to 2014, cross-sectional data from 2,327 participants were analyzed. Stratified analyses were performed according to demographic and health-related factors. A Restricted Cubic Spline (RCS) model was employed to examine potential threshold effects. Additionally, weighted linear regression models were used to evaluate cognitive performance, and logistic regression models were applied to assess stroke risk.
Results
Higher LC9 scores were positively associated with better cognitive function and lower odds of stroke. Within the cognitive function analysis, higher LC9 scores were significantly associated with superior performance on the Digit Symbol Substitution Test (DSST) (β = 0.18, 95% CI: 0.11– 0.26,
P
< 0.001). In the stroke analysis, individuals with higher LC9 scores exhibited decreased odds of experiencing a stroke (OR = 0.97, 95% CI: 0.95–0.99,
P
= 0.005). RCS analysis identified a non-linear relationship between LC9 scores and the odds of stroke, with the greatest decreases in stroke odds observed at lower LC9 scores, plateauing around a score of 70.
Conclusions
Higher LC9 scores are associated with better cognitive function and lower odds of stroke. These findings suggest that incorporating mental health metrics, such as depression, into cardiovascular health assessments enhances the predictive power for cognitive outcomes and stroke prevention.
Journal Article
Using Self-Assembling Peptides to Integrate Biomolecules into Functional Supramolecular Biomaterials
Throughout nature, self-assembly gives rise to functional supramolecular biomaterials that can perform complex tasks with extraordinary efficiency and specificity. Inspired by these examples, self-assembly is increasingly used to fabricate synthetic supramolecular biomaterials for diverse applications in biomedicine and biotechnology. Peptides are particularly attractive as building blocks for these materials because they are based on naturally derived amino acids that are biocompatible and biodegradable; they can be synthesized using scalable and cost-effective methods, and their sequence can be tailored to encode formation of diverse architectures. To endow synthetic supramolecular biomaterials with functional capabilities, it is now commonplace to conjugate self-assembling building blocks to molecules having a desired functional property, such as selective recognition of a cell surface receptor or soluble protein, antigenicity, or enzymatic activity. This review surveys recent advances in using self-assembling peptides as handles to incorporate biologically active molecules into supramolecular biomaterials. Particular emphasis is placed on examples of functional nanofibers, nanovesicles, and other nano-scale structures that are fabricated by linking self-assembling peptides to proteins and carbohydrates. Collectively, this review highlights the enormous potential of these approaches to create supramolecular biomaterials with sophisticated functional capabilities that can be finely tuned to meet the needs of downstream applications.
Journal Article
Assigning channel weights using an attention mechanism: an EEG interpolation algorithm
During the acquisition of electroencephalographic (EEG) signals, various factors can influence the data and lead to the presence of one or multiple bad channels. Bad channel interpolation is the use of good channels data to reconstruct bad channel, thereby maintaining the original dimensions of the data for subsequent analysis tasks. The mainstream interpolation algorithm assigns weights to channels based on the physical distance of the electrodes and does not take into account the effect of physiological factors on the EEG signal. The algorithm proposed in this study utilizes an attention mechanism to allocate channel weights (AMACW). The model gets the correlation among channels by learning from good channel data. Interpolation assigns weights based on learned correlations without the need for electrode location information, solving the difficulty that traditional methods cannot interpolate bad channels at unknown locations. To avoid an overly concentrated weight distribution of the model when generating data, we designed the channel masking (CM). This method spreads attention and allows the model to utilize data from multiple channels. We evaluate the reconstruction performance of the model using EEG data with 1 to 5 bad channels. With EEGLAB’s interpolation method as a performance reference, tests have shown that the AMACW models can effectively reconstruct bad channels.
Journal Article
Causal relationship between Alzheimer’s disease and cerebral small vessel disease: a Mendelian randomization study
Observational studies have produced inconsistent findings regarding the relationship between Alzheimer’s disease (AD) and cerebral small vessel disease (CSVD) risk. Residual confounding and potential reverse causality are inevitable in such conventional observational studies. We tried to examine the causal relationship between AD and CSVD-related phenotypes using genetic methods. Genetic instruments for each AD and CSVD-related phenotypes (cerebral microbleeds, white matter hyperintensity, and lacunar stroke) were derived from large-scale genome-wide association studies. In this study, two-sample Mendelian randomization (MR) tested potential causal associations between AD and CSVD-related phenotypes, followed by a colocalization analysis to corroborate MR findings and explain possible mechanisms. Using univariable MR, we observed that genetic liability to AD was associated with an increased risk of cerebral microbleeds (CMBs) [odds ratio (OR) = 1.149; 95% confidence interval (CI) = 1.070–1.235,
P
< 0.001], and a modest increase in white matter hyperintensities (WMHs) volume (β = 0.031 mm
3
, 95% CI = 0.009–0.054 mm
3
,
P
= 0.005). In multivariable MR, the causal effect of genetic liability for AD on CMBs and WMHs remained after adjusting for risk factors, with the estimate across the IVW method. Colocalization results provided evidence for a shared causal variant between AD with CMBs (PPH4 = 0.996) and WMHs (PPH4 = 0.657), suggesting that the MR estimates were not confounded by linkage disequilibrium. Our MR analyses provided robust evidence for the causal effects of genetic liability for AD on an increased risk of CMBs and WMHs. More work is warranted to confirm the mechanisms of association between AD and CSVD.
Journal Article
Intracellular immune sensing promotes inflammation via gasdermin D–driven release of a lectin alarmin
Inflammatory caspase sensing of cytosolic lipopolysaccharide (LPS) triggers pyroptosis and the concurrent release of damage-associated molecular patterns (DAMPs). Collectively, DAMPs are key determinants that shape the aftermath of inflammatory cell death. However, the identity and function of the individual DAMPs released are poorly defined. Our proteomics study revealed that cytosolic LPS sensing triggered the release of galectin-1, a β-galactoside-binding lectin. Galectin-1 release is a common feature of inflammatory cell death, including necroptosis. In vivo studies using galectin-1-deficient mice, recombinant galectin-1 and galectin-1-neutralizing antibody showed that galectin-1 promotes inflammation and plays a detrimental role in LPS-induced lethality. Mechanistically, galectin-1 inhibition of CD45 (
Ptprc
) underlies its unfavorable role in endotoxin shock. Finally, we found increased galectin-1 in sera from human patients with sepsis. Overall, we uncovered galectin-1 as a bona fide DAMP released as a consequence of cytosolic LPS sensing, identifying a new outcome of inflammatory cell death.
Damage-associated molecular patterns (DAMPs) are released during necrotic cell death and contribute to driving inflammation. Rathinam and colleagues show that galectin-1 is a new DAMP that functions by inhibiting the receptor phosphatase CD45.
Journal Article
Effects of Geometric Parameters on Mixing Efficiency and Optimization in Variable Cross Section Microchannels
Micromixers are important devices used in many fields for various applications which provide high mixing efficiencies and reduce the amount of reagents and samples. In addition, effective premixing of reactants is essential for obtaining high reaction rates. In order to further improve the mixing performance, three-dimensional numerical simulations and optimizations of the flow and mixing characteristics within a variable cross section T-shaped micromixer were carried out. The effects of the geometric parameters containing channel diameter, channel shape, channel contraction and expansion ratio, and number of expansion units on the mixing were investigated with the evaluation criteria of mixing index and performance index. The optimized geometric parameters of the channel were a diameter of 0.2 mm, the shape of Sem channel, an expansion ratio of 1:3, and a number of expansion units of 7, respectively. It can be showed that the mixing efficiency of the optimized micromixer was greatly improved, and the mixing index at different velocities could reach up to more than 0.98.
Journal Article
A prognostic model for hepatocellular carcinoma based on apoptosis-related genes
Background
Dysregulation of the balance between proliferation and apoptosis is the basis for human hepatocarcinogenesis. In many malignant tumors, such as hepatocellular carcinoma (HCC), there is a correlation between apoptotic dysregulation and poor prognosis. However, the prognostic values of apoptosis-related genes (ARGs) in HCC have not been elucidated.
Methods
To screen for differentially expressed ARGs, the expression levels of 161 ARGs from The Cancer Genome Atlas (TCGA) database (
https://cancergenome.nih.gov/
) were analyzed. Gene Ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to evaluate the underlying molecular mechanisms of differentially expressed ARGs in HCC. The prognostic values of ARGs were established using Cox regression, and subsequently, a prognostic risk model for scoring patients was developed. Kaplan–Meier (K-M) and receiver operating characteristic (ROC) curves were plotted to determine the prognostic value of the model.
Results
Compared with normal tissues, 43 highly upregulated and 8 downregulated ARGs in HCC tissues were screened. GO analysis results revealed that these 51 genes are indeed related to the apoptosis function. KEGG analysis revealed that these 51 genes were correlated with MAPK, P53, TNF, and PI3K-AKT signaling pathways, while Cox regression revealed that 5 ARGs (PPP2R5B, SQSTM1, TOP2A, BMF, and LGALS3) were associated with prognosis and were, therefore, obtained to develop the prognostic model. Based on the median risk scores, patients were categorized into high-risk and low-risk groups. Patients in the low-risk groups exhibited significantly elevated 2-year or 5-year survival probabilities (
p
< 0.0001). The risk model had a better clinical potency than the other clinical characteristics, with the area under the ROC curve (AUC = 0.741). The prognosis of HCC patients was established from a plotted nomogram.
Conclusion
Based on the differential expression of ARGs, we established a novel risk model for predicting HCC prognosis. This model can also be used to inform the individualized treatment of HCC patients.
Journal Article
Alteration of N6 -Methyladenosine mRNA Methylation in a Rat Model of Cerebral Ischemia–Reperfusion Injury
Aim: To reveal the alterations in the m6A modification profile of cerebral ischemia-reperfusion injury model rats. Materials & methods: Rats were used to establish the middle cerebral artery occlusion and reperfusion (MCAO/R) model. MeRIP-seq and RNA-seq were performed to identify differences in m6A methylation and gene expression. The expression of m6A methylation regulators was analyzed in three datasets and detected by quantitative real-time polymerase chain reaction, western blot, and immunofluorescence. Results: We identified 1160 differentially expressed genes with hypermethylated or hypomethylated m6A modifications. The differentially expressed genes with hypermethylated m6A modifications were involved in the pathways associated with inflammation, while hypomethylated differentially expressed genes were related to neurons and nerve synapses. Among the m6A regulators, FTO was specifically localized in neurons and significantly downregulated after MCAO/R. Conclusion: Our study provided a m6A transcriptome-wide map of the MACO/R rat samples, which might provide new insights into the mechanisms of cerebral ischemia-reperfusion injury.
Journal Article