sj-pdf-3-imr-10.1177_03000605231213781 - Supplemental material for Prediction of diagnostic gene biomarkers for hypertrophic cardiomyopathy by integrated machine learning

Supplemental material, sj-pdf-3-imr-10.1177_03000605231213781 for Prediction of diagnostic gene biomarkers for hypertrophic cardiomyopathy by integrated machine learning by Hongjun You and Mengya Dong in Journal of International Medical Research</p

sj-pdf-2-imr-10.1177_03000605231213781 - Supplemental material for Prediction of diagnostic gene biomarkers for hypertrophic cardiomyopathy by integrated machine learning

Supplemental material, sj-pdf-2-imr-10.1177_03000605231213781 for Prediction of diagnostic gene biomarkers for hypertrophic cardiomyopathy by integrated machine learning by Hongjun You and Mengya Dong in Journal of International Medical Research</p

sj-pdf-1-imr-10.1177_03000605231213781 - Supplemental material for Prediction of diagnostic gene biomarkers for hypertrophic cardiomyopathy by integrated machine learning

Supplemental material, sj-pdf-1-imr-10.1177_03000605231213781 for Prediction of diagnostic gene biomarkers for hypertrophic cardiomyopathy by integrated machine learning by Hongjun You and Mengya Dong in Journal of International Medical Research</p

Composition-Dependent Formation of Platinum Silver Nanowires

The understanding of shape control of colloidal nanoparticles is still rather limited even after well over a decade of intensive research efforts. While surface capping agents can greatly influence the growth habit of nanocrystals in solution, the formation of certain morphology can hardly be understood based on both experimental data and simulations. Without a good understanding of the origins for shape formation, deterministic approaches to the synthesis of nanostructures can be hard to realize. In this paper, we describe the synthesis and formation of PtAg alloy nanowires in the presence of oleylamine and oleic acid through the oriented attachment. Transmission electron microscopy study shows the formation of wormlike nanowires occurs largely at the composition around Pt50Ag50. Both Pt and Ag rich alloy nanostructures form sphere-like or faceted nanoparticles under the same reaction conditions. Density functional theory calculation is used to understand the interactions between the functional groups of capping agents and low index planes of PtAg alloys. The structural order of interfaces after collision between primary particles is obtained by molecular dynamic simulation. The results indicate that the formation of alloy nanowires is mostly driven by the interplay between the binding energy of capping agents on alloy surfaces and the diffusion of atoms at the interface upon the collision of primary nanoparticles

Composition-Dependent Formation of Platinum Silver Nanowires

The understanding of shape control of colloidal nanoparticles is still rather limited even after well over a decade of intensive research efforts. While surface capping agents can greatly influence the growth habit of nanocrystals in solution, the formation of certain morphology can hardly be understood based on both experimental data and simulations. Without a good understanding of the origins for shape formation, deterministic approaches to the synthesis of nanostructures can be hard to realize. In this paper, we describe the synthesis and formation of PtAg alloy nanowires in the presence of oleylamine and oleic acid through the oriented attachment. Transmission electron microscopy study shows the formation of wormlike nanowires occurs largely at the composition around Pt50Ag50. Both Pt and Ag rich alloy nanostructures form sphere-like or faceted nanoparticles under the same reaction conditions. Density functional theory calculation is used to understand the interactions between the functional groups of capping agents and low index planes of PtAg alloys. The structural order of interfaces after collision between primary particles is obtained by molecular dynamic simulation. The results indicate that the formation of alloy nanowires is mostly driven by the interplay between the binding energy of capping agents on alloy surfaces and the diffusion of atoms at the interface upon the collision of primary nanoparticles

Composition-Dependent Formation of Platinum Silver Nanowires

The understanding of shape control of colloidal nanoparticles is still rather limited even after well over a decade of intensive research efforts. While surface capping agents can greatly influence the growth habit of nanocrystals in solution, the formation of certain morphology can hardly be understood based on both experimental data and simulations. Without a good understanding of the origins for shape formation, deterministic approaches to the synthesis of nanostructures can be hard to realize. In this paper, we describe the synthesis and formation of PtAg alloy nanowires in the presence of oleylamine and oleic acid through the oriented attachment. Transmission electron microscopy study shows the formation of wormlike nanowires occurs largely at the composition around Pt50Ag50. Both Pt and Ag rich alloy nanostructures form sphere-like or faceted nanoparticles under the same reaction conditions. Density functional theory calculation is used to understand the interactions between the functional groups of capping agents and low index planes of PtAg alloys. The structural order of interfaces after collision between primary particles is obtained by molecular dynamic simulation. The results indicate that the formation of alloy nanowires is mostly driven by the interplay between the binding energy of capping agents on alloy surfaces and the diffusion of atoms at the interface upon the collision of primary nanoparticles

A Universal Rule for Organic Ligand Exchange

Most synthetic routes to high-quality nanocrystals with tunable morphologies predominantly employ long hydro-carbon molecules as ligands, which are detrimental for electronic and catalytic applications. Here, a rule is found that the adsorption energy of an organic ligand is related to its carbon-chain length. Using the density functional theory method, the adsorption energies of some commonly used ligand molecules with different carbon-chain lengths are calculated, including carboxylate, hydroxyl, and amine molecules adsorbed on metal or metal oxide crystal surface. The results indicate that the adsorption energy of the ligand molecule with a long carbon chain is weaker than that of a smaller molecule with same functional group. This rule provides a theoretical support for a new kind of ligand exchange method in which large organic ligand molecules can be exchanged by small molecules with same functional group to improve the catalytic properties

Electrochemical Synthesis and Catalytic Property of Sub-10 nm Platinum Cubic Nanoboxes

We report an electrochemical synthesis of ultrafine Pt cubic nanoboxes from Pt-on-Ag heteronanostructures. These cubic nanoboxes have an average edge length of about 6 nm and a wall thickness of 1.5 nm. Several reaction parameters including the profile of applied potentials were examined to develop an optimal procedure for controlling the size, shape, and surface morphology of the nanoboxes. A strong shape-dependent catalytic property is observed for Pt cubic nanoboxes, which is 1.5 times more active than hollow spheres in terms of turn over frequency for catalytic oxidation of methanol

Free-Standing Pt–Au Hollow Nanourchins with Enhanced Activity and Stability for Catalytic Methanol Oxidation

Controlling the morphology of Pt–Au bimetal nanostructures can provide a great opportunity to increase their catalytic activity on a Pt mass basis and improve their durability at the same time. In this study, we synthesized Pt-on-Au hollow urchinlike nanoparticles (NPs), which present a structure consisting of a monolayer of small Pt NPs uniformly overgrown on an Au hollow nanourchin (HNU). The Pt–Au HNUs demonstrated an ultrahigh density of sharp tips and uniform coating of 2 nm Pt NPs. This well-controlled bimetal nanostructure exhibited a large electrochemical surface area, more than 2 times higher than that of Pt black, and a relatively high electrocatalytic activity toward the methanol oxidation reaction, more than 3 times greater than the Pt black and Pt/C commercial reference catalysts. Simultaneously, the Pt–Au HNUs showed greatly improved durability because of the small Pt NPs on the surface of Pt–Au HNUs which were effectively stabilized by the Au metal support

Table_13_Diagnostic potential of energy metabolism-related genes in heart failure with preserved ejection fraction.xlsx

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.</p