Research status of pathogenesis of anxiety or depression after percutaneous coronary intervention and Traditional Chinese Medicine intervention.

ETHNIC PHARMACOLOGICAL RELEVANCE: Anxiety or depression after percutaneous coronary intervention (PCI) is a common clinical disease. Currently, conventional pharmacotherapy primarily involves the administration of anxiolytic or antidepressant medications in conjunction with anticoagulants, antiplatelet agents, and other cardiovascular drugs. However, challenges such as drug dependence, adverse reactions and related concerns persist in the treatment of this disease. Numerous pertinent studies have demonstrated that Traditional Chinese Medicine (TCM) exhibits significant therapeutic efficacy and distinctive advantages in managing post-PCI anxiety or depression. AIM OF THIS REVIEW: This review attempted to summarize the characteristics of TCM for treating anxiety or depression after PCI, including single Chinese herbs, Chinese medicine monomers, compound TCM prescriptions, TCM patented drugs, and other TCM-related treatment methods, focusing on the analysis of the relevant mechanism of TCM treatment of this disease. METHODS: By searching the literature on treating anxiety or depression after PCI with TCM in PubMed, Web of Science, CNKI, and other relevant databases, this review focuses on the latest research progress of TCM treatment of this disease. RESULTS: In the treatment of anxiety or depression after PCI, TCM exerts significant pharmacological effects such as anti-inflammatory, antioxidant, anti-anxiety or anti-depression, cardiovascular and cerebrovascular protection, and neuroprotection, mainly by regulating the levels of related inflammatory factors, oxidative stress markers, neurotransmitter levels, and related signaling pathways. TCM has a good clinical effect in treating anxiety or depression after PCI with individualized treatment. CONCLUSIONS: TCM has terrific potential and good prospects in the treatment of anxiety or depression after PCI. The main direction of future exploration is the study of the mechanism related to Chinese medicine monomers and the large sample clinical study related to compound TCM prescriptions.

Covalent conjugation of Inca peanut albumin and polyphenols with different phenolic hydroxyl numbers through laccase catalysis to improve functional properties.

BACKGROUND: Enzymatic crosslinking is a method that can be used to modify Inca peanut albumin (IPA) using polyphenols, and provides desirable functionalities; however, the effect of polyphenol structures on conjugate properties is unclear. In this study, we selected four polyphenols with different numbers of phenolic hydroxyl groups [para-hydroxybenzoic acid (HBA), protocatechuic acid (PCA), gallic acid (GA), and epigallocatechin gallate (EGCG)] for covalent modification of IPA by enzymatic crosslinking, and explored the structure-function changes of the IPA-polyphenol conjugates. RESULTS: Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) analysis showed that laccase successfully promoted covalent crosslinking of IPA with polyphenols, with the order of degree of conjugation as EGCG > GA > PCA > HBA, the IPA-EGCG conjugate showed the highest polyphenol binding equivalents (98.35 g kg-1 protein), and a significant reduction in the content of free amino, sulfhydryl, and tyrosine group. The oxidation of polyphenols by laccase forms quinone or semiquinone radicals that are covalently crosslinked to the reactive groups of IPA, leading to significant changes in the secondary and tertiary structures of IPA, with spherical structures transforming into dense lamellar structures. The 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging ability and emulsification stability of IPA-EGCG conjugates improved by almost 6-fold and 2.7-fold, respectively, compared with those of unmodified IPA. CONCLUSION: These data suggest that the higher the number of polyphenol hydroxyl groups, the higher the degree of IPA-polyphenol conjugation; additionally, enzymatic crosslinking can significantly improve the functional properties of IPA. © 2024 Society of Chemical Industry.

Differences in the structural properties of three OSA starches and their effects on the performance of high internal phase Pickering emulsions.

The emulsifying properties of emulsions are significantly influenced by the structural properties of octenyl succinic anhydride (OSA) starch. The purpose of this work was to elucidate the effect of the structure of OSA starch on its performance as an emulsifier to stabilize Pickering high-internal-phase emulsions (HIPEs). The degrees of substitution (DS) of the three OSA starches were 0.0137, 0.0177 and 0.0236, and their degrees of branching (DB) were 13.96 %, 14.20 % and 14.32 % measured by 1H NMR, which were sequentially labeled as OSA1, OSA2, and OSA3. The OSA3 starch with higher DS and DB had a lower critical micelle concentration (CMC) (0.11 mg/mL). Its emulsification activity (EAI) and emulsion stability (ES) were 61.8 m2/g and 72.5 min, respectively, which were higher than OSA1 and OSA2 starches. The contact angle of the three OSA starches increased from 45.35° to 80.03° with increasing DS and DB. Therefore, it is hypothesized that OSA3 starches have better emulsification properties. The results of physical stability of HIPEs confirmed the above results. These results indicated that DS and DB have a synergistic effect on emulsion properties, and OSA starch with higher DS and DB values were more conducive to the construction of stable HIPEs systems.

Role of Brain-Derived Neurotrophic Factor in Anxiety or Depression After Percutaneous Coronary Intervention.

Anxiety or depression after percutaneous coronary intervention (PCI) is one of the key clinical problems in cardiology that need to be solved urgently. Brain-derived neurotrophic factor (BDNF) may be a potential biomarker for the pathogenesis and treatment of anxiety or depression after PCI. This article reviews the correlation between BDNF and cardiovascular system and nervous system from the aspects of synthesis, release and action site of BDNF, and focuses on the latest research progress of the mechanism of BDNF in anxiety or depression after PCI. It includes the specific mechanisms by which BDNF regulates the levels of inflammatory factors, reduces oxidative stress damage, and mediates multiple signaling pathways. In addition, this review summarizes the therapeutic potential of BDNF as a potential biomarker for anxiety or depression after PCI.

MicroRNA-specific therapeutic targets and biomarkers of apoptosis following myocardial ischemia-reperfusion injury.

MicroRNAs are single-stranded non-coding RNAs that participate in post-transcriptional regulation of gene expression, it is involved in the regulation of apoptosis after myocardial ischemia-reperfusion injury. For example, the alteration of mitochondrial structure is facilitated by MicroRNA-1 through the regulation of apoptosis-related proteins, such as Bax and Bcl-2, thereby mitigating cardiomyocyte apoptosis. MicroRNA-21 not only modulates the expression of NF-κB to suppress inflammatory signals but also activates the PI3K/AKT pathway to mitigate ischemia-reperfusion injury. Overexpression of MicroRNA-133 attenuates reactive oxygen species (ROS) production and suppressed the oxidative stress response, thereby mitigating cellular apoptosis. MicroRNA-139 modulates the extrinsic death signal of Fas, while MicroRNA-145 regulates endoplasmic reticulum calcium overload, both of which exert regulatory effects on cardiomyocyte apoptosis. Therefore, the article categorizes the molecular mechanisms based on the three classical pathways and multiple signaling pathways of apoptosis. It summarizes the targets and pathways of MicroRNA therapy for ischemia-reperfusion injury and analyzes future research directions.

Multi-omics data integration for hepatocellular carcinoma subtyping with multi-kernel learning.

Hepatocellular carcinoma (HCC) is a leading malignant liver tumor with high mortality and morbidity. Patients at the same stage can be defined as different molecular subtypes associated with specific genomic disorders and clinical features. Thus, identifying subtypes is essential to realize efficient treatment and improve survival outcomes of HCC patients. Here, we applied a regularized multiple kernel learning with locality preserving projections method to integrate mRNA, miRNA and DNA methylation data of HCC patients to identify subtypes. We identified two HCC subtypes significantly correlated with the overall survival. The patient 3-years mortality rates in the high-risk and low-risk group was 51.0% and 23.5%, respectively. The high-risk group HCC patients were 3.37 times higher in death risk compared to the low-risk group after adjusting for clinically relevant covariates. A total of 196 differentially expressed mRNAs, 2,151 differentially methylated genes and 58 differentially expressed miRNAs were identified between the two subtypes. Additionally, pathway activity analysis showed that the activities of six pathways between the two subtypes were significantly different. Immune cell infiltration analysis revealed that the abundance of nine immune cells differed significantly between the two subtypes. We further applied the weighted gene co-expression network analysis to identify gene modules that may affect patients prognosis. Among the identified modules, the key module genes significantly associated with prognosis were found to be involved in multiple biological processes and pathways, revealing the mechanism underlying the progression of HCC. Hub gene analysis showed that the expression levels of CDK1, CDCA8, TACC3, and NCAPG were significantly associated with HCC prognosis. Our findings may bring novel insights into the subtypes of HCC and promote the realization of precision medicine.

Subtypes identification on heart failure with preserved ejection fraction via network enhancement fusion using multi-omics data.

Heart failure with preserved ejection fraction (HFpEF) is associated with multiple etiologic and pathophysiologic factors. HFpEF leads to significant cardiovascular morbidity and mortality. There are various reasons that fail to identify effective therapeutic interventions for HFpEF, primarily due to its clinical heterogeneity causing significant difficulties in determining physiologic and prognostic implications for this syndrome. Thus, identifying clinical subtypes using multi-omics data has great implications for efficient treatment and prognosis of HFpEF patients. Here we proposed to integrate mRNA, DNA methylation and microRNA (miRNA) expression data of HFpEF with a similarity network fusion (SNF) method following a network enhancement (ne-SNF) denoising technique to form a fused network. A spectral clustering method was then used to obtain clusters of patient subtypes. Experiments on HFpEF datasets demonstrated that ne-SNF significantly outperforms single data subtype analysis and other integrated methods. The identified subgroups were shown to have statistically significant differences in survival. Two HFpEF subtypes were defined: a high-risk group (16.8%) and a low-risk group (83.2%). The 5-year mortality rates were 63.3% and 33.0% for the high- and low-risk group, respectively. After adjusting for the effects of clinical covariates, HFpEF patients in the high-risk group were 2.43 times more likely to die than the low-risk group. A total of 157 differentially expressed (DE) mRNAs, 2199 abnormal methylations and 121 DE miRNAs were identified between two subtypes. They were also enriched in many HFpEF-related biological processes or pathways. The ne-SNF method provides a novel pipeline for subtype identification in integrated analysis of multi-omics data.

Risk Prediction in Patients With Heart Failure With Preserved Ejection Fraction Using Gene Expression Data and Machine Learning.

Heart failure with preserved ejection fraction (HFpEF) has become a major health issue because of its high mortality, high heterogeneity, and poor prognosis. Using genomic data to classify patients into different risk groups is a promising method to facilitate the identification of high-risk groups for further precision treatment. Here, we applied six machine learning models, namely kernel partial least squares with the genetic algorithm (GA-KPLS), the least absolute shrinkage and selection operator (LASSO), random forest, ridge regression, support vector machine, and the conventional logistic regression model, to predict HFpEF risk and to identify subgroups at high risk of death based on gene expression data. The model performance was evaluated using various criteria. Our analysis was focused on 149 HFpEF patients from the Framingham Heart Study cohort who were classified into good-outcome and poor-outcome groups based on their 3-year survival outcome. The results showed that the GA-KPLS model exhibited the best performance in predicting patient risk. We further identified 116 differentially expressed genes (DEGs) between the two groups, thus providing novel therapeutic targets for HFpEF. Additionally, the DEGs were enriched in Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways related to HFpEF. The GA-KPLS-based HFpEF model is a powerful method for risk stratification of 3-year mortality in HFpEF patients.

Time-Varying Gene Network Analysis of Human Prefrontal Cortex Development.

The prefrontal cortex (PFC) constitutes a large part of the human central nervous system and is essential for the normal social affection and executive function of humans and other primates. Despite ongoing research in this region, the development of interactions between PFC genes over the lifespan is still unknown. To investigate the conversion of PFC gene interaction networks and further identify hub genes, we obtained time-series gene expression data of human PFC tissues from the Gene Expression Omnibus (GEO) database. A statistical model, loggle, was used to construct time-varying networks and several common network attributes were used to explore the development of PFC gene networks with age. Network similarity analysis showed that the development of human PFC is divided into three stages, namely, fast development period, deceleration to stationary period, and recession period. We identified some genes related to PFC development at these different stages, including genes involved in neuronal differentiation or synapse formation, genes involved in nerve impulse transmission, and genes involved in the development of myelin around neurons. Some of these genes are consistent with findings in previous reports. At the same time, we explored the development of several known KEGG pathways in PFC and corresponding hub genes. This study clarified the development trajectory of the interaction between PFC genes, and proposed a set of candidate genes related to PFC development, which helps further study of human brain development at the genomic level supplemental to regular anatomical analyses. The analytical process used in this study, involving the loggle model, similarity analysis, and central analysis, provides a comprehensive strategy to gain novel insights into the evolution and development of brain networks in other organisms.

RSS-Based Target Localization in Underwater Acoustic Sensor Networks via Convex Relaxation.

The received signal strength (RSS) based target localization problem in underwater acoustic wireless sensor networks (UWSNs) is considered. Two cases with respect to target transmit power are considered. For the first case, under the assumption that the reference of the target transmit power is known, we derive a novel weighted least squares (WLS) estimator by using an approximation to the RSS expressions, and then transform the originally non-convex problem into a mixed semi-definite programming/second-order cone programming (SD/SOCP) problem for reaching an efficient solution. For the second case, there is no knowledge on the target transmit power, and we treat the reference power as an additional unknown parameter. In this case, we formulate a WLS estimator by using a further approximation, and present an iterative ML and mixed SD/SOCP algorithm for solving the derived WLS problem. For both cases, we also derive the closed form expressions of the Cramer-Rao Lower Bounds (CRLBs) on root mean square error (RMSE). Computer simulation results show the superior performance of the proposed methods over the existing ones in the underwater acoustic environment.

Synchronization of fractional fuzzy cellular neural networks with interactions.

In this paper, we introduce fuzzy theory into the fractional cellular neural networks to dynamically enhance the coupling strength and propose a fractional fuzzy neural network model with interactions. Using the Lyapunov principle of fractional differential equations, we design the adaptive control schemes to realize the synchronization and obtain the synchronization criteria. Finally, we provide some numerical examples to show the effectiveness of our obtained results.

Reversal of pathological cardiac hypertrophy via the MEF2-coregulator interface.

Cardiac hypertrophy, as a response to hemodynamic stress, is associated with cardiac dysfunction and death, but whether hypertrophy itself represents a pathological process remains unclear. Hypertrophy is driven by changes in myocardial gene expression that require the MEF2 family of DNA-binding transcription factors, as well as the nuclear lysine acetyltransferase p300. Here we used genetic and small-molecule probes to determine the effects of preventing MEF2 acetylation on cardiac adaptation to stress. Both nonacetylatable MEF2 mutants and 8MI, a molecule designed to interfere with MEF2-coregulator binding, prevented hypertrophy in cultured cardiac myocytes. 8MI prevented cardiac hypertrophy in 3 distinct stress models, and reversed established hypertrophy in vivo, associated with normalization of myocardial structure and function. The effects of 8MI were reversible, and did not prevent training effects of swimming. Mechanistically, 8MI blocked stress-induced MEF2 acetylation, nuclear export of class II histone deacetylases HDAC4 and -5, and p300 induction, without impeding HDAC4 phosphorylation. Correspondingly, 8MI transformed the transcriptional response to pressure overload, normalizing almost all 232 genes dysregulated by hemodynamic stress. We conclude that MEF2 acetylation is required for development and maintenance of pathological cardiac hypertrophy, and that blocking MEF2 acetylation can permit recovery from hypertrophy without impairing physiologic adaptation.

Structure of a domain-swapped FOXP3 dimer on DNA and its function in regulatory T cells.

The transcription factor FOXP3 is essential for the suppressive function of regulatory T cells that are required for maintaining self-tolerance. We have solved the crystal structure of the FOXP3 forkhead domain as a ternary complex with the DNA-binding domain of the transcription factor NFAT1 and a DNA oligonucleotide from the interleukin-2 promoter. A striking feature of this structure is that FOXP3 forms a domain-swapped dimer that bridges two molecules of DNA. Structure-guided or autoimmune disease (IPEX)-associated mutations in the domain-swap interface diminished dimer formation by the FOXP3 forkhead domain without compromising FOXP3 DNA binding. These mutations also eliminated T cell-suppressive activity conferred by FOXP3, both in vitro and in a murine model of autoimmune diabetes in vivo. We conclude that FOXP3-mediated suppressor function requires dimerization through the forkhead domain and that mutations in the dimer interface can lead to the systemic autoimmunity observed in IPEX patients.

Effects of the nano-tubular anodic TiO2 buffer layer on bioactive hydroxyapatite coating.

We studied the effect of nano-tubular anodic TiO2 buffer layers on hydroxyapatite (HA) coating. The pulsed laser deposition (PLD) method was used to deposit HA on a well arranged nano-tubular anodic TiO2 (NT-ATO) buffer layer prepared by an electrochemical anodization technique. The surface morphology and chemical composition of HA coatings were characterized by using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and contact angle measurement. We found that crystalline HA coatings show well arranged porous morphologies with a favorable surface wettability. We also found that an anodic nano-tubular TiO2 buffer layer with a relatively short tube length shows a better coating morphology. The deposition process of HA on the nanotubular TiO2 buffer layer was also proposed.

Optical and electrical properties of ultralong ZnO nanorod fabricated from preheating hydrothermal method.

Ultralong ZnO nanorod arrays with a length of 10 microm were synthesized using a preheated hydrothermal-solution precursor, and their optical and electrical properties were studied using photoluminescence (PL) spectra and field effect transistors (FETs). The PL spectra showed ultraviolet, orange, and red emissions and had different temperature dependences with increasing temperature. The high-resolution photoluminescence spectra showed that the ultraviolet (UV) emission had different origins within different temperature ranges. The parameters describing the temperature dependence of the peak position shift, intensity, and full width at half maximum were evaluated using different models. After the fabrication of individual nanorod FETs, the ultralong ZnO NRs showed a clear n-type gate modulation with a typical electron concentration of 10(17) cm(-3) and a typical electron mobility of 35.7 cm2/V x s.

Annealing effects of sapphire substrate on the structure and properties of ZnO films grown via pulsed laser deposition.

The structure, morphology, and properties of ZnO films were examined in relation to an annealed sapphire substrate prepared via pulsed laser deposition. The annealing effects of the sapphire substrate on the ZnO films were studied via X-ray diffraction (XRD), atomic-force microscopy (AFM), and photoluminescence (PL) measurements. The XRD patterns and PL spectra results showed that the optical quality of the ZnO films was significantly affected by the annealing temperature of the sapphire substrate. The optimum annealing temperature of the sapphire substrate was 1400 degrees C. Atomically-flat-surface and high-density atomic steps were formed after annealing treatment, which were qualified to be good nucleation sites for ZnO film growth.

Structure of the MADS-box/MEF2 domain of MEF2A bound to DNA and its implication for myocardin recruitment.

Myocyte enhancer factor 2 (MEF2) regulates specific gene expression in diverse developmental programs and adaptive responses. MEF2 recognizes DNA and interacts with transcription cofactors through a highly conserved N-terminal domain referred to as the MADS-box/MEF2 domain. Here we present the crystal structure of the MADS-box/MEF2 domain of MEF2A bound to DNA. In contrast to previous structural studies showing that the MEF2 domain of MEF2A is partially unstructured, the present study reveals that the MEF2 domain participates with the MADS-box in both dimerization and DNA binding as a single domain. The sequence divergence at and immediately following the C-terminal end of the MEF2 domain may allow different MEF2 dimers to recognize different DNA sequences in the flanking regions. The current structure also suggests that the ligand-binding pocket previously observed in the Cabin1-MEF2B-DNA complex and the HDAC9 (histone deacetylase 9)-MEF2B-DNA complex is not induced by cofactor binding but rather preformed by intrinsic folding. However, the structure of the ligand-binding pocket does undergo subtle but significant conformational changes upon cofactor binding. On the basis of these observations, we generated a homology model of MEF2 bound to a myocardin family protein, MASTR, that acts as a potent coactivator of MEF2-dependent gene expression. The model shows excellent shape and chemical complementarity at the binding interface and is consistent with existing mutagenesis data. The apo structure presented here can also serve as a target for virtual screening and soaking studies of small molecules that can modulate the function of MEF2 as research tools and therapeutic leads.

Crystal structure of NFAT bound to the HIV-1 LTR tandem kappaB enhancer element.

The host factor, nuclear factor of activated T-cells (NFAT), regulates the transcription and replication of HIV-1. Here, we have determined the crystal structure of the DNA binding domain of NFAT bound to the HIV-1 long terminal repeat (LTR) tandem kappaB enhancer element at 3.05 A resolution. NFAT binds as a dimer to the upstream kappaB site (Core II), but as a monomer to the 3' end of the downstream kappaB site (Core I). The DNA shows a significant bend near the 5' end of Core I, where a lysine residue from NFAT bound to the 3' end of Core II inserts into the minor groove and seems to cause DNA bases to flip out. Consistent with this structural feature, the 5' end of Core I become hypersensitive to dimethylsulfate in the in vivo footprinting upon transcriptional activation of the HIV-1 LTR. Our studies provide a basis for further investigating the functional mechanisms of NFAT in HIV-1 transcription and replication.

FOXP3 controls regulatory T cell function through cooperation with NFAT.

Antigen stimulation of immune cells activates the transcription factor NFAT, a key regulator of T cell activation and anergy. NFAT forms cooperative complexes with the AP-1 family of transcription factors and regulates T cell activation-associated genes. Here we show that regulatory T cell (Treg) function is mediated by an analogous cooperative complex of NFAT with the forkhead transcription factor FOXP3, a lineage specification factor for Tregs. The crystal structure of an NFAT:FOXP2:DNA complex reveals an extensive protein-protein interaction interface between NFAT and FOXP2. Structure-guided mutations of FOXP3, predicted to progressively disrupt its interaction with NFAT, interfere in a graded manner with the ability of FOXP3 to repress expression of the cytokine IL2, upregulate expression of the Treg markers CTLA4 and CD25, and confer suppressor function in a murine model of autoimmune diabetes. Thus by switching transcriptional partners, NFAT converts the acute T cell activation program into the suppressor program of Tregs.

Structure of the forkhead domain of FOXP2 bound to DNA.

FOXP (FOXP1-4) is a newly defined subfamily of the forkhead box (FOX) transcription factors. A mutation in the FOXP2 forkhead domain cosegregates with a severe speech disorder, whereas several mutations in the FOXP3 forkhead domain are linked to the IPEX syndrome in human and a similar autoimmune phenotype in mice. Here we report a 1.9 A crystal structure of the forkhead domain of human FOXP2 bound to DNA. This structure allows us to revise the previously proposed DNA recognition mechanism and provide a unifying model of DNA binding for the FOX family of proteins. Our studies also reveal that the FOXP2 forkhead domain can form a domain-swapped dimer, made possible by a strategic substitution of a highly conserved proline in conventional FOX proteins with alanine in the P subfamily. Disease-causing mutations in FOXP2 and FOXP3 map either to the DNA binding surface or the domain-swapping dimer interface, functionally corroborating the crystal structure.