Thermal Stability and Electronic Properties of N‑Heterocyclic Carbene-Protected Au₁₃ Nanocluster and Phosphine-Protected Analogues

Despite significant advances in manufacturing atomically precise gold nanoclusters protected by various ligands, there is a limited understanding of the thermal stability dynamics and electronic properties of ligand effects. We conducted ab initio molecular dynamics (AIMD) simulations on the well-characterized [Au13(NHCMe)9Cl3]2+ nanocluster and its counterpart [Au13(PMe3)9Cl3]2+ cluster to evaluate the thermal stability induced by N-heterocyclic carbene (NHC) and phosphine ligands. The result shows that under vacuum conditions, [Au13(PMe3)9Cl3]2+ is more stable than [Au13(NHCMe)9Cl3]2+, and both lead to metal nucleation decomposition, breaking into the Au12 fragment and L–Au–Cl (L = NHCMe or PMe3) complexes eventually. The optical and electronic properties of these two clusters change significantly due to ligand alteration. Furthermore, we have designed a novel [Au13(NHCMe)­(PMe3)8Cl3]2+ cluster coprotected by NHC and phosphine ligands, displaying higher thermal stability than the homoligand protected [Au13(NHCMe)9Cl3]2+ and [Au13(PMe3)9Cl3]2+. Our hypothetical species are an interesting model for nanostructured materials, facilitating the experimental exploration of cluster synthesis and catalytic applications

Thermal Stability and Electronic Properties of N‑Heterocyclic Carbene-Protected Au₁₃ Nanocluster and Phosphine-Protected Analogues

Despite significant advances in manufacturing atomically precise gold nanoclusters protected by various ligands, there is a limited understanding of the thermal stability dynamics and electronic properties of ligand effects. We conducted ab initio molecular dynamics (AIMD) simulations on the well-characterized [Au13(NHCMe)9Cl3]2+ nanocluster and its counterpart [Au13(PMe3)9Cl3]2+ cluster to evaluate the thermal stability induced by N-heterocyclic carbene (NHC) and phosphine ligands. The result shows that under vacuum conditions, [Au13(PMe3)9Cl3]2+ is more stable than [Au13(NHCMe)9Cl3]2+, and both lead to metal nucleation decomposition, breaking into the Au12 fragment and L–Au–Cl (L = NHCMe or PMe3) complexes eventually. The optical and electronic properties of these two clusters change significantly due to ligand alteration. Furthermore, we have designed a novel [Au13(NHCMe)­(PMe3)8Cl3]2+ cluster coprotected by NHC and phosphine ligands, displaying higher thermal stability than the homoligand protected [Au13(NHCMe)9Cl3]2+ and [Au13(PMe3)9Cl3]2+. Our hypothetical species are an interesting model for nanostructured materials, facilitating the experimental exploration of cluster synthesis and catalytic applications

Periodic Patterning on Carbon Nanotubes: Supercritical CO₂-Induced Polyethylene Epitaxy

Periodic Patterning on Carbon Nanotubes:  Supercritical CO2-Induced Polyethylene Epitax

Fabrication of Free-Standing Hierarchical Carbon Nanofiber/Graphene Oxide/Polyaniline Films for Supercapacitors

A hierarchical high-performance electrode with nanoacanthine-style polyaniline (PANI) deposited onto a carbon nanofiber/graphene oxide (CNF/GO) template was successfully prepared via an in situ polymerization process. The morphology analysis shows that introducing one-dimensional (1D) CNF could significantly decrease/inhibit the staking of laminated GO to form an open-porous CNF/GO architecture. Followed with in situ facial deposition of PANI, the as-synthesized PANI modified CNF/GO exhibits three-dimensional (3D) hierarchical layered nanoarchitecture, which favors the diffusion of the electrolyte ions into the inner region of active materials. The hierarchical free-standing electrodes were directly fabricated into sandwich structured supercapacitors using 1 M H₂SO₄ as the electrolyte showing a significant specific capacitance of 450.2 F/g at the voltage scan rate of 10 mV/s. The electrochemical properties of the hierarchical structure can be further improved by a reduction procedure of GO before the deposition of PANI

Modification of Carbon Nanotubes: Water-Soluble Polymers Nanocrystal Wrapping to Periodic Patterning with Assistance of Supercritical CO₂

Modification of Carbon Nanotubes: Water-Soluble Polymers Nanocrystal Wrapping to Periodic Patterning with Assistance of Supercritical CO2</sub

Table3_Prioritization of Diagnostic and Prognostic Biomarkers for Lupus Nephritis Based on Integrated Bioinformatics Analyses.DOCX

Lupus nephritis (LN) is an important driver of end-stage renal disease (ESRD). However, few biomarkers are available for evaluating the diagnosis and prognosis of LN. For this study, we downloaded microarray data of multiple LN expression profiles from the GEO database. We used the WGCNA and R limma packages to identify LN hub genes and differentially-expressed genes (DEGs). We identified nine co-DEGs in the intersection with LN-related genes from the Genecards database. We found DEGs that are primarily associated with immune-related functions and pathways (including with the complement pathway, primary immunodeficiency markers, and MHC-like protein complexes) through our comprehensive GSEA, GO, and KEGG enrichment analyses. We used other LN and SLE validation datasets and discovered six explicitly expressed co-DEGs: HLA-DMA, HLA-DPA1, HLA-DPB1, HLA-DRA, IL10RA, and IRF8 in the LN set; ROC and Precision-Recall curve analyses revealed that these six genes have a good diagnostic efficacy. The correlation analysis with prognostic data from the Nephroseq database indicates that the differential expression of these co-DEGs is associated with a low glomerular filtration rate in that cohort. Additionally, we used a single-cell LN database of immune cells (for the first time) and discovered these co-DEGs to be predominantly distributed in different types of macrophages and B cells. In conclusion, by integrating multiple approaches for DEGs discovery, we identified six valuable biomarkers that are strongly correlated with the diagnosis and prognosis of LN. These markers can help clarify the pathogenesis and improve the clinical management of LN.</p

DataSheet1_Prioritization of Diagnostic and Prognostic Biomarkers for Lupus Nephritis Based on Integrated Bioinformatics Analyses.ZIP

Lupus nephritis (LN) is an important driver of end-stage renal disease (ESRD). However, few biomarkers are available for evaluating the diagnosis and prognosis of LN. For this study, we downloaded microarray data of multiple LN expression profiles from the GEO database. We used the WGCNA and R limma packages to identify LN hub genes and differentially-expressed genes (DEGs). We identified nine co-DEGs in the intersection with LN-related genes from the Genecards database. We found DEGs that are primarily associated with immune-related functions and pathways (including with the complement pathway, primary immunodeficiency markers, and MHC-like protein complexes) through our comprehensive GSEA, GO, and KEGG enrichment analyses. We used other LN and SLE validation datasets and discovered six explicitly expressed co-DEGs: HLA-DMA, HLA-DPA1, HLA-DPB1, HLA-DRA, IL10RA, and IRF8 in the LN set; ROC and Precision-Recall curve analyses revealed that these six genes have a good diagnostic efficacy. The correlation analysis with prognostic data from the Nephroseq database indicates that the differential expression of these co-DEGs is associated with a low glomerular filtration rate in that cohort. Additionally, we used a single-cell LN database of immune cells (for the first time) and discovered these co-DEGs to be predominantly distributed in different types of macrophages and B cells. In conclusion, by integrating multiple approaches for DEGs discovery, we identified six valuable biomarkers that are strongly correlated with the diagnosis and prognosis of LN. These markers can help clarify the pathogenesis and improve the clinical management of LN.</p

Table2_Prioritization of Diagnostic and Prognostic Biomarkers for Lupus Nephritis Based on Integrated Bioinformatics Analyses.XLSX

Lupus nephritis (LN) is an important driver of end-stage renal disease (ESRD). However, few biomarkers are available for evaluating the diagnosis and prognosis of LN. For this study, we downloaded microarray data of multiple LN expression profiles from the GEO database. We used the WGCNA and R limma packages to identify LN hub genes and differentially-expressed genes (DEGs). We identified nine co-DEGs in the intersection with LN-related genes from the Genecards database. We found DEGs that are primarily associated with immune-related functions and pathways (including with the complement pathway, primary immunodeficiency markers, and MHC-like protein complexes) through our comprehensive GSEA, GO, and KEGG enrichment analyses. We used other LN and SLE validation datasets and discovered six explicitly expressed co-DEGs: HLA-DMA, HLA-DPA1, HLA-DPB1, HLA-DRA, IL10RA, and IRF8 in the LN set; ROC and Precision-Recall curve analyses revealed that these six genes have a good diagnostic efficacy. The correlation analysis with prognostic data from the Nephroseq database indicates that the differential expression of these co-DEGs is associated with a low glomerular filtration rate in that cohort. Additionally, we used a single-cell LN database of immune cells (for the first time) and discovered these co-DEGs to be predominantly distributed in different types of macrophages and B cells. In conclusion, by integrating multiple approaches for DEGs discovery, we identified six valuable biomarkers that are strongly correlated with the diagnosis and prognosis of LN. These markers can help clarify the pathogenesis and improve the clinical management of LN.</p

Data for: Locate vaccination stations with travel distance, operational costs and work schedule considered

The data file includes full data used in the case study of the paper

Table1_Prioritization of Diagnostic and Prognostic Biomarkers for Lupus Nephritis Based on Integrated Bioinformatics Analyses.XLSX

Lupus nephritis (LN) is an important driver of end-stage renal disease (ESRD). However, few biomarkers are available for evaluating the diagnosis and prognosis of LN. For this study, we downloaded microarray data of multiple LN expression profiles from the GEO database. We used the WGCNA and R limma packages to identify LN hub genes and differentially-expressed genes (DEGs). We identified nine co-DEGs in the intersection with LN-related genes from the Genecards database. We found DEGs that are primarily associated with immune-related functions and pathways (including with the complement pathway, primary immunodeficiency markers, and MHC-like protein complexes) through our comprehensive GSEA, GO, and KEGG enrichment analyses. We used other LN and SLE validation datasets and discovered six explicitly expressed co-DEGs: HLA-DMA, HLA-DPA1, HLA-DPB1, HLA-DRA, IL10RA, and IRF8 in the LN set; ROC and Precision-Recall curve analyses revealed that these six genes have a good diagnostic efficacy. The correlation analysis with prognostic data from the Nephroseq database indicates that the differential expression of these co-DEGs is associated with a low glomerular filtration rate in that cohort. Additionally, we used a single-cell LN database of immune cells (for the first time) and discovered these co-DEGs to be predominantly distributed in different types of macrophages and B cells. In conclusion, by integrating multiple approaches for DEGs discovery, we identified six valuable biomarkers that are strongly correlated with the diagnosis and prognosis of LN. These markers can help clarify the pathogenesis and improve the clinical management of LN.</p