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Abstract Background Specific alterations in gut microbiota and metabolites have been linked to AMI, with CBLB potentially playing an essential role. However, the precise interactions remain understudied, creating a significant gap in our understanding. This study aims to address this by exploring these interactions in CBLB-intervened AMI mice using transcriptome sequencing, 16 S rDNA, and non-targeted metabolite analysis. Methods To probe the therapeutic potential and mechanistic underpinnings of CBLB overexpression in AMI, we utilized an integrative multi-omics strategy encompassing transcriptomics, metabolomics, and 16s rDNA sequencing. We selected these particular methods as they facilitate a holistic comprehension of the intricate interplay between the host and its microbiota, and the potential effects on the host’s metabolic and gene expression profiles. The uniqueness of our investigation stems from utilizing a multi-omics approach to illuminate the role of CBLB in AMI, an approach yet unreported to the best of our knowledge. Our experimental protocol encompassed transfection of CBLB lentivirus-packaged vectors into 293T cells, followed by subsequent intervention in AMI mice. Subsequently, we conducted pathological staining, fecal 16s rDNA sequencing, and serum non-targeted metabolome sequencing. We applied differential expression analysis to discern differentially expressed genes (DEGs), differential metabolites, and differential microbiota. We performed protein-protein interaction analysis to identify core genes, and conducted correlation studies to clarify the relationships amongst these core genes, paramount metabolites, and key microbiota. Results Following the intervention of CBLB in AMI, we observed a significant decrease in inflammatory cell infiltration and collagen fiber formation in the infarcted region of mice hearts. We identified key changes in microbiota, metabolites, and DEGs that were associated with this intervention. The findings revealed that CBLB has a significant correlation with DEGs, differential metabolites and microbiota, respectively. This suggests it could play a pivotal role in the regulation of AMI. Conclusion This study confirmed the potential of differentially expressed genes, metabolites, and microbiota in AMI regulation post-CBLB intervention. Our findings lay groundwork for future exploration of CBLB’s role in AMI, suggesting potential therapeutic applications and novel research directions in AMI treatment strategies.

Background: The implication of necroptosis in cardiovascular disease was already recognized. However, the molecular mechanism of necroptosis has not been extensively studied in coronary heart disease (CHD). Methods: The differentially expressed genes (DEGs) between CHD and control samples were acquired in the GSE20681 dataset downloaded from the GEO database. Key necroptosis-related DEGs were captured and ascertained by bioinformatics analysis techniques, including weighted gene co-expression network analysis (WGCNA) and two machine learning algorithms, while single-gene gene set enrichment analysis (GSEA) revealed their molecular mechanisms. The diagnostic biomarkers were selected via receiver operating characteristic (ROC) analysis. Moreover, an analysis of immune elements infiltration degree was carried out. Authentication of pivotal gene expression at the mRNA level was investigated in vitro utilizing quantitative real-time PCR (qRT-PCR). Results: A total of 94 DE-NRGs were recognized here, among which, FAM166B, NEFL, POLDIP3, PRSS37, and ZNF594 were authenticated as necroptosis-related biomarkers, and the linear regression model based on them presented an acceptable ability to different sample types. Following regulatory analysis, the ascertained biomarkers were markedly abundant in functions pertinent to blood circulation, calcium ion homeostasis, and the MAPK/cAMP/Ras signaling pathway. Single-sample GSEA exhibited that APC co-stimulation and CCR were more abundant, and aDCs and B cells were relatively scarce in CHD patients. Consistent findings from bioinformatics and qRT-PCR analyses confirmed the upregulation of NEFL and the downregulation of FAM166B, POLDIP3, and PRSS37 in CHD. Conclusion: Our current investigation identified 5 necroptosis-related genes that could be diagnostic markers for CHD and brought a novel comprehension of the latent molecular mechanisms of necroptosis in CHD.

Objectives Hypertrophic cardiomyopathy (HCM), a leading cause of heart failure and sudden death, requires early diagnosis and treatment. This study investigated the underlying pathogenesis and explored potential diagnostic gene biomarkers for HCM. Methods Transcriptional profiles of myocardial tissues from patients with HCM (dataset GSE36961) were downloaded from the Gene Expression Omnibus database and subjected to bioinformatics analyses, including differentially expressed gene (DEG) identification, enrichment analyses, and protein–protein interaction (PPI) network analysis. Least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination were performed to identify candidate diagnostic gene biomarkers. mRNA expression levels of candidate biomarkers were tested in an external dataset (GSE141910); area under the receiver operating characteristic curve (AUC) values were obtained to validate diagnostic efficacy. Results Overall, 156 DEGs (109 downregulated, 47 upregulated) were identified. Enrichment and PPI network analyses indicated that the DEGs were involved in biological functions and molecular pathways including inflammatory response, platelet activity, complement and coagulation cascades, extracellular matrix organization, phagosome, apoptosis, and VEGFA–VEGFR2 signaling. RASD1, CDC42EP4, MYH6, and FCN3 were identified as diagnostic biomarkers for HCM. Conclusions RASD1, CDC42EP4, MYH6, and FCN3 might be diagnostic gene biomarkers for HCM and can provide insights concerning HCM pathogenesis.

BackgroundHeart failure with preserved ejection fraction (HFpEF) is associated with changes in cardiac metabolism that affect energy supply in the heart. However, there is limited research on energy metabolism-related genes (EMRGs) in HFpEF.MethodsThe HFpEF mouse dataset (GSE180065, containing heart tissues from 10 HFpEF and five control samples) was sourced from the Gene Expression Omnibus database. Gene expression profiles in HFpEF and control groups were compared to identify differentially expressed EMRGs (DE-EMRGs), and the diagnostic biomarkers with diagnostic value were screened using machine learning algorithms. Meanwhile, we constructed a biomarker-based nomogram model for its predictive power, and functionality of diagnostic biomarkers were conducted using single-gene gene set enrichment analysis, drug prediction, and regulatory network analysis. Additionally, consensus clustering analysis based on the expression of diagnostic biomarkers was utilized to identify differential HFpEF-related genes (HFpEF-RGs). Immune microenvironment analysis in HFpEF and subtypes were performed for analyzing correlations between immune cells and diagnostic biomarkers as well as HFpEF-RGs. Finally, qRT-PCR analysis on the HFpEF mouse model was used to validate the expression levels of diagnostic biomarkers.ResultsWe selected 5 biomarkers (Chrna2, Gnb3, Gng7, Ddit4l, and Prss55) that showed excellent diagnostic performance. The nomogram model we constructed demonstrated high predictive power. Single-gene gene set enrichment analysis revealed enrichment in aerobic respiration and energy derivation. Further, various miRNAs and TFs were predicted by Gng7, such as Gng7-mmu-miR-6921-5p, ETS1-Gng7. A lot of potential therapeutic targets were predicted as well. Consensus clustering identified two distinct subtypes of HFpEF. Functional enrichment analysis highlighted the involvement of DEGs-cluster in protein amino acid modification and so on. Additionally, we identified five HFpEF-RGs (Kcnt1, Acot1, Kcnc4, Scn3a, and Gpam). Immune analysis revealed correlations between Macrophage M2, T cell CD4+ Th1 and diagnostic biomarkers, as well as an association between Macrophage and HFpEF-RGs. We further validated the expression trends of the selected biomarkers through experimental validation.ConclusionOur study identified 5 diagnostic biomarkers and provided insights into the prediction and treatment of HFpEF through drug predictions and network analysis. These findings contribute to a better understanding of HFpEF and may guide future research and therapy development.

The authors demonstrate a sensing approach for effectively monitoring organic micropollutants in water. They first use mesoporous nanosponge and magnetic nanoparticles for fast enrichment of micropollutants, and demonstrate SERS-based sensing with 2-3 orders of magnitude improvement in detection limits.

Plasmonic-enhanced nanosensors are limited in practical applications, as it remains challenging to detect molecules at low concentrations. Here, the authors introduce a buoyant particulate strategy in order to enrich analytes in the plasmonic hot spots.

Metal species are highly mobile within mesoporous silica, making it difficult to template growth of metallic nanocrystals inside the channels. Here, the authors introduce a solid-liquid-solution interfacial strategy to suppress migration of the metal species, achieving control over a variety of mesostructured nanomaterials.

Using a simple aqueous synthesis method, Ag hierarchical mesoparticles with tunable surface topography were obtained. The mechanism of tuning the topographies of the hierarchical mesoparticles in this particle-mediated anisotropic growth system was studied. A series of Ag mesoparticles with well-tuned surface topographies were synthesized as an ideal research target for a systematic investigation of the effect of surface nanostructures on the performance of surface enhanced Raman spectroscopy (SERS). Highly-branched Ag mesoparticles were shown to have the highest SERS sensitivity both as single-particle SERS substrates and particle-array SERS substrates, which have an enhancement factor greater than 109. Using the finite difference time domain method, the distribution of the localized electromagnetic field near the particle surface was simulated. Based on the simulation results, the mechanism of the effect of topography on the SERS properties was systematically studied. [ABSTRACT FROM AUTHOR]

Self-assembling Au mesoflower arrays are prepared using a polymethylmethacrylate (PMMA) template on an iron substrate via a combined top-down/bottom-up nanofabrication strategy. The PMMA template with the holes around 300-500 nm in diameter is first fabricated by using polymer blend lithography on iron substrates, and the highly homogeneous Au mesoflower arrays with less than 10 nm intraparticle gaps are subsequently obtained by an in situ galvanic reaction between HAuCl4 solution and the iron substrate under optimal stirring of the solution as well as reaction time. Owing to the unique mesostructures and uniformity, Raman measurements show that the gold mesoflower arrays obtained demonstrated a strong and reproducible surface enhanced Raman scattering (SERS) enhancement on the order of ∼107-108. The development of a SERS substrate based on the Au mesoflowers with high spatial density of hot spots, relatively low cost and facial synthesis provides a novel strategy for applications in chemical and biomolecular sensing. [ABSTRACT FROM AUTHOR]

Understanding of the nanoparticle (NP)-mediated crystal growth mechanism is essential for the syntheses of nanostructures with desired physical and chemical properties. A facile protocol is developed to study the size effect of primary NPs on the silver NP-mediated crystal growth process. Experimental observation shows that the primary NPs size performs a key role for the crystal final shape and structure. Theory study discloses that water solution will promote an amorphous structure of small primary NPs which thus perform a different assembly process for NP-mediated crystal formation compared with larger crystalline primary NPs. [ABSTRACT FROM AUTHOR]

In this study, a well-defined dendritic silver nanostructure can be large-scale synthesized in AgNO3(aqueous) at room temperature. The nonequilibrium and anisotropic growth at different silver ion concentrations result in controllable morphologies and morphological evolution. At high silver ion concentrations, a strong anisotropic growth contributes to a fine single crystalline silver dendrite. As the reaction proceeds, the dendritic structure transforms into a thermodynamically stable hexagonal structure. At a relatively low silver ion concentration, a particle-aggregated fractal pattern can be obtained due to relatively small anisotropy. As the reaction time increases, the transition from polycrystalline aggregates to a single crystal during silver dendritic growth can be observed. An oriented attachment mechanism can be used to explain the structural and morphological evolution of silver nanostructures. Silver nanostructures with various morphologies are expected to have significant potential applications in superhydrophobic surfaces, surface-enhanced Raman scattering, and others. [ABSTRACT FROM AUTHOR]

The paper introduces the mechanism and kinetics of the alkylation of benzene with ethylene to produce ethylbenzene. The alkylation reaction mechanism that takes place in the surface of the ZSM-5 catalyst and the [bmim]Cl/FeCl 3 ionic liquid catalyst is described; at the same time the alkylation reaction kinetics is put forward based on the corresponding mechanism. The method obtained aids in the understanding of the microcosmic process of alkylation for adapting to the necessity of industrialization. [ABSTRACT FROM AUTHOR]

This paper introduces the coke and deactivation of the catalyst in the aromatization reaction. The catalyst characterizations including thermogravimetric (TG) method and temperature-programmed oxidation (TPO) and coke calculation are discussed in detail. At the same time, the influence of the aromatization reaction conditions on the catalyst's coke and deactivation and the catalyst's deactivation kinetics are studied. The methods obtained are beneficial to improve the catalyst activity of aromatization reaction to adapt to the necessity of industrialization. [ABSTRACT FROM AUTHOR]

The reaction conditions include temperature, weight hourly space velocity (WHSV), catalyst loading amount Ga and Si/Al, vapor, calcination temperature, soaking order, pretreatment, oxygen, and microwave heating method. The study introduces the influence of aromatization reaction conditions over HZSM-5 catalyst in detail. The proper temperature, low weight hourly space velocity (WHSV), modified HZSM-5, non-oxygen and microwave heating method are beneficial to the aromatization reaction. [ABSTRACT FROM AUTHOR]

The reaction mechanism of propane includes dehydrogenation, oxidative dehydrogenation by applying oxygen and carbon dioxide as oxidative resource, catalyst, catalytic method, kinetics, and so on. This study introduces the reaction system of propane oxidative dehydrogenation in detail. Propane dehydrogenation catalyst, its support, and assistant catalyst are discussed, as well as Biloen, Kaidong Chen, Chen Guangwen, and J. Gascón C's catalytic processing and kinetics, which includes the isotope tracing method, the mechanism of surface adsorption, and Langmuir-Hinshelood. [ABSTRACT FROM AUTHOR]

Catalytic reaction of a C5 fraction has been studied by using a C5 fraction as raw material and big hole cationic exchanger resin D115 as catalyst, and curve equations of a C5 fraction have been put forward on the basis of the conversion under different reactive conditions, such as temperature, molecule ratio, and weight hourly space velocity (WHSV). A mathematical method is first introduced lo study on the relationship between the conversion of C5 fraction and the different reactive conditions. The results from experimental data are in accordance with the quantitatively analytical conclusions drawn from the calculated data. [ABSTRACT FROM AUTHOR]

A size-dependent crystal growth mechanism is studied by molecular dynamics simulations. The amorphous silver firstly deposits under the coordinated actions between the lattice mismatch and interactions between silver atoms and the surrounding water. Then, silver nuclei spontaneously form once the amorphous layer exceeds a critical thickness. Water molecule absorption on the outmost surface of silver clusters contributes to the continuous deposition of silver amorphous phase. [ABSTRACT FROM AUTHOR]

An ideal supporting material improves both activity and durability of noble metal nanoparticles in electrocatalytic reactions. Graphene possesses a high transport rate of electrons in-plane, a low cost, and stability, but, the restacking of graphene layers trap noble metal nanoparticles and make them inaccessible to reactants and results in reduced catalytic activity. Here, holey-graphene as the supporting materials for Pt nanoparticle catalysts is deeply investigated in the electrocatalytic reaction of methanol oxidation. The holey-graphene can be scalable to synthesize using our simple method described herein. The holes on the holey-graphene layer promote the access of reactants with Pt nanoparticle catalysts compared with carbon black and graphene when used as supporting materials. Density functional theory calculations and molecule dynamic simulation further explain the function of holey-graphene in the promotion of electrocatalytic activity. Holey-graphene may open extraordinary possibilities as a supporting material for electrocatalysts. [ABSTRACT FROM AUTHOR]