Prior knowledge-guided multilevel graph neural network for tumor risk prediction and interpretation via multi-omics data integration.

The interrelation and complementary nature of multi-omics data can provide valuable insights into the intricate molecular mechanisms underlying diseases. However, challenges such as limited sample size, high data dimensionality and differences in omics modalities pose significant obstacles to fully harnessing the potential of these data. The prior knowledge such as gene regulatory network and pathway information harbors useful gene-gene interaction and gene functional module information. To effectively integrate multi-omics data and make full use of the prior knowledge, here, we propose a Multilevel-graph neural network (GNN): a hierarchically designed deep learning algorithm that sequentially leverages multi-omics data, gene regulatory networks and pathway information to extract features and enhance accuracy in predicting survival risk. Our method achieved better accuracy compared with existing methods. Furthermore, key factors nonlinearly associated with the tumor pathogenesis are prioritized by employing two interpretation algorithms (i.e. GNN-Explainer and IGscore) for neural networks, at gene and pathway level, respectively. The top genes and pathways exhibit strong associations with disease in survival analyses, many of which such as SEC61G and CYP27B1 are previously reported in the literature.

[Dynamic trajectory and cell communication of different cell clusters in malignant progression of glioblastoma].

OBJECTIVE: To delve deeply into the dynamic trajectories of cell subpopulations and the communication network among immune cell subgroups during the malignant progression of glioblastoma (GBM), and to endeavor to unearth key risk biomarkers in the GBM malignancy progression, so as to provide a more profound understanding for the treatment and prognosis of this disease by integrating transcriptomic data and clinical information of the GBM patients. METHODS: Utilizing single-cell sequencing data analysis, we constructed a cell subgroup atlas during the malignant progression of GBM. The Monocle2 tool was employed to build dynamic progression trajectories of the tumor cell subgroups in GBM. Through gene enrichment analysis, we explored the biological processes enriched in genes that significantly changed with the malignancy progression of GBM tumor cell subpopulations. CellChat was used to identify the communication network between the different immune cell subgroups. Survival analysis helped in identifying risk molecular markers that impacted the patient prognosis during the malignant progression of GBM. This method ological approach offered a comprehensive and detailed examination of the cellular and molecular dynamics within GBM, providing a robust framework for understanding the disease' s progression and potential therapeutic targets. RESULTS: The analysis of single-cell sequencing data identified 6 different cell types, including lymphocytes, pericytes, oligodendrocytes, macrophages, glioma cells, and microglia. The 27 151 cells in the single-cell dataset included 3 881 cells from the patients with low-grade glioma (LGG), 10 166 cells from the patients with newly diagnosed GBM, and 13 104 cells from the patients with recurrent glioma (rGBM). The pseudo-time analysis of the glioma cell subgroups indicated significant cellular heterogeneity during malignant progression. The cell interaction analysis of immune cell subgroups revealed the communication network among the different immune subgroups in GBM malignancy, identifying 22 biologically significant ligand-receptor pairs across 12 key biological pathways. Survival analysis had identified 8 genes related to the prognosis of the GBM patients, among which SERPINE1, COL6A1, SPP1, LTF, C1S, AEBP1, and SAA1L were high-risk genes in the GBM patients, and ABCC8 was low-risk genes in the GBM patients. These findings not only provided new theoretical bases for the treatment of GBM, but also offered fresh insights for the prognosis assessment and treatment decision-making for the GBM patients. CONCLUSION: This research comprehensively and profoundly reveals the dynamic changes in glioma cell subpopulations and the communication patterns among the immune cell subgroups during the malignant progression of GBM. These findings are of significant importance for understanding the complex biological processes of GBM, providing crucial new insights for precision medicine and treatment decisions in GBM. Through these studies, we hope to provide more effective treatment options and more accurate prognostic assessments for the patients with GBM.

Pan-cancer analysis of the DNA methylation patterns of long non-coding RNA.

Long non-coding RNA (lncRNA) regulated by abnormal DNA methylation (ADM-lncRNA) emerges as a biomarker for cancer diagnosis and treatment. This study comprehensively described the methylation patterns of lncRNA in pan-cancer using the cancer data set in The Cancer Genome Atlas (TCGA). Based on the cancer heterogeneity of ADM-lncRNA in pan-cancer, we constructed a co-expression network of pan-cancer ADM-lncRNA (pADM-lncRNA) in 10 cancers, highlighting the combined action mode of abnormal DNA methylation, and indicating the internal connection among different cancers. Functional analysis revealed the pan-carcinogenic pathway of pADM-lncRNA and suggested potential factors for cancer heterogeneity and tumor immune microenvironment changes. Survival analysis showed the potential of pADM-lncRNA-mRNA co-expression pair as cancer biomarkers. Revealing the action mode of lncRNA and DNA methylation in cancer may help understand the key molecular mechanisms of cell carcinogenesis.

The regulatory pattern of target gene expression by aberrant enhancer methylation in glioblastoma.

BACKGROUND: Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor with grim prognosis. Aberrant DNA methylation is an epigenetic mechanism that promotes GBM carcinogenesis, while the function of DNA methylation at enhancer regions in GBM remains poorly described. RESULTS: We integrated multi-omics data to identify differential methylation enhancer region (DMER)-genes and revealed global enhancer hypomethylation in GBM. In addition, a DMER-mediated target genes regulatory network and functional enrichment analysis of target genes that might be regulated by hypomethylation enhancer regions showed that aberrant enhancer regions could contribute to tumorigenesis and progression in GBM. Further, we identified 22 modules in which lncRNAs and mRNAs synergistically competed with each other. Finally, through the construction of drug-target association networks, our study identified potential small-molecule drugs for GBM treatment. CONCLUSIONS: Our study provides novel insights for understanding the regulation of aberrant enhancer region methylation and developing methylation-based biomarkers for the diagnosis and treatment of GBM.

Author Correction: Eliminating dissolution of platinum-based electrocatalysts at the atomic scale.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Eliminating dissolution of platinum-based electrocatalysts at the atomic scale.

A remaining challenge for the deployment of proton-exchange membrane fuel cells is the limited durability of platinum (Pt) nanoscale materials that operate at high voltages during the cathodic oxygen reduction reaction. In this work, atomic-scale insight into well-defined single-crystalline, thin-film and nanoscale surfaces exposed Pt dissolution trends that governed the design and synthesis of durable materials. A newly defined metric, intrinsic dissolution, is essential to understanding the correlation between the measured Pt loss, surface structure, size and ratio of Pt nanoparticles in a carbon (C) support. It was found that the utilization of a gold (Au) underlayer promotes ordering of Pt surface atoms towards a (111) structure, whereas Au on the surface selectively protects low-coordinated Pt sites. This mitigation strategy was applied towards 3 nm Pt3Au/C nanoparticles and resulted in the elimination of Pt dissolution in the liquid electrolyte, which included a 30-fold durability improvement versus 3 nm Pt/C over an extended potential range up to 1.2 V.

Pharmacokinetics and tissue distribution study of hupehenenine in rats: A novel isosteroid alkaloid isolated from Bulbus Hupehensis Fritillariae.

Hupehenenine is a novel isosteroid alkaloid that was first isolated from Bulbus Hupehensis Fritillariae. The inhibitory proliferation effect of hupehenenine and its three related alkaloid derivatives, including o-caproyl-hupehenenine, o-(2-furanoyl)-hupehenenine, and Δ5(6) -isopeimine on human lung cancer cell line, human chronic myeloid leukemia cell line, and human thyroid duct cancer cell line in vitro, has been identified. This study first developed a sensitive HPLC-MS/MS method for the simultaneous quantification of hupehenenine and three alkaloid derivatives in rat plasma and tissues. The developed method was validated, and it was linear over the concentration range of 1-800 ng/mL for all analytes with R2 ≥ 0.9939 and 0.9972, respectively, in rat plasma and rat liver homogenate. The lower limit of quantitation was 1 ng/mL for all analytes. The intra-day and inter-day precision and accuracy were satisfactory. This validated method was successfully applied to investigate the pharmacokinetics and tissue distribution of hupehenenine in rats. In pharmacokinetic study, the maximum plasma concentration of rats exists gender difference. Tissue distribution study showed that hupehenenine has good affinity for multiple tissues but is unable to cross the blood-brain barrier. These results may provide a useful reference for further research of hupehenenine and its three related alkaloid derivatives.

Control of Architecture in Rhombic Dodecahedral Pt-Ni Nanoframe Electrocatalysts.

Platinum-based alloys are known to demonstrate advanced properties in electrochemical reactions that are relevant for proton exchange membrane fuel cells and electrolyzers. Further development of Pt alloy electrocatalysts relies on the design of architectures with highly active surfaces and optimized utilization of the expensive element, Pt. Here, we show that the three-dimensional Pt anisotropy of Pt-Ni rhombic dodecahedra can be tuned by controlling the ratio between Pt and Ni precursors such that either a completely hollow nanoframe or a new architecture, the excavated nanoframe, can be obtained. The excavated nanoframe showed ∼10 times higher specific and ∼6 times higher mass activity for the oxygen reduction reaction than Pt/C, and twice the mass activity of the hollow nanoframe. The high activity is attributed to enhanced Ni content in the near-surface region and the extended two-dimensional sheet structure within the nanoframe that minimizes the number of buried Pt sites.

High-Performance Rh2P Electrocatalyst for Efficient Water Splitting.

The search for active, stable, and cost-efficient electrocatalysts for hydrogen production via water splitting could make a substantial impact on energy technologies that do not rely on fossil fuels. Here we report the synthesis of rhodium phosphide electrocatalyst with low metal loading in the form of nanocubes (NCs) dispersed in high-surface-area carbon (Rh2P/C) by a facile solvo-thermal approach. The Rh2P/C NCs exhibit remarkable performance for hydrogen evolution reaction and oxygen evolution reaction compared to Rh/C and Pt/C catalysts. The atomic structure of the Rh2P NCs was directly observed by annular dark-field scanning transmission electron microscopy, which revealed a phosphorus-rich outermost atomic layer. Combined experimental and computational studies suggest that surface phosphorus plays a crucial role in determining the robust catalyst properties.

Porous Matrix Stiffness Modulates Response to Targeted Therapy in Breast Carcinoma.

Porous matrix stiffness modulates response to targeted therapy. Poroelastic behavior within porous matrix may modulate the molecule events in cell-matrix and cell-cell interaction like the complex formation of human epidermal growth factor receptor-2 (HER2)-Src-α6ß4 integrin, influencing the targeted therapy with lapatinib.

Multimetallic core/interlayer/shell nanostructures as advanced electrocatalysts.

The fine balance between activity and durability is crucial for the development of high performance electrocatalysts. The importance of atomic structure and compositional gradients is a guiding principle in exploiting the knowledge from well-defined materials in the design of novel class of core-shell electrocatalysts comprising Ni core, Au interlayer, and PtNi shell (Ni@Au@PtNi). This multimetallic system is found to have the optimal balance of activity and durability due to the synergy between the stabilizing effect of subsurface Au and modified electronic structure of surface Pt through interaction with subsurface Ni atoms. The electrocatalysts with Ni@Au@PtNi core-interlayer-shell structure exhibit high intrinsic and mass activities as well as superior durability for the oxygen reduction reaction with less than 10% activity loss after 10,000 potential cycles between 0.6 and 1.1 V vs the reversible hydrogen electrode.

Identification and Functional Analysis of MicroRNAs in Mice following Focal Cerebral Ischemia Injury.

Numerous studies have demonstrated that genes, RNAs, and proteins are involved in the occurrence and development of stroke. In addition, previous studies concluded that microRNAs (miRNAs or miRs) are closely related to the pathological process of ischemic and hypoxic disease. Therefore, the aims of this study were to quantify the altered expression levels of miRNAs in the infarct region 6 h after middle cerebral artery occlusion (MCAO)-induced focal cerebral ischemia in mice using a large-scale miRNAs microarray. Firstly, MCAO-induced cerebral ischemic injuries were investigated by observing the changes of neurological deficits, infarct volume and edema ratio. One hundred and eighteen differentially expressed miRNAs were identified in the infarct region of mice following the MCAOs compared with sham group (p<0.05 was considered as significant). Among these 118 significantly expressed microRNAs, we found that 12 miRNAs were up-regulated with fold changes lager than two, and 18 miRNAs were down-regulated with fold changes less than 0.5 in the infarct region of mice following the 6 h MCAOs, compared with the sham group. Then, these 30 miRNAs with expression in fold change larger than two or less than 0.5 was predicted, and the functions of the target genes of 30 miRNAs were analyzed using a bioinformatics method. Finally, the miRNA-gene network was established and the functional miRNA-mRNA pairs were identified, which provided insight into the roles of the specific miRNAs that regulated specified genes in the ischemic injuries. The miRNAs identified in this study may represent effective therapeutic targets for stroke, and further study of the role of these targets may increase our understanding of the mechanisms underlying ischemic injuries.

IGF-1 alleviates NMDA-induced excitotoxicity in cultured hippocampal neurons against autophagy via the NR2B/PI3K-AKT-mTOR pathway.

Insulin-like growth factor-1 (IGF-1) is a brain-specific multifunctional protein involved in neuronal polarity and axonal guidance. Mature IGF-1 triggers three enzymes, mitogen-activated protein kinase (MAPK), phosphatidylinositol 3-kinase (PI3K), and phosphoinositide phospholipase C-γ (PLC-γ), which are its predominant downstream regulators. The PI3K-AKT signaling pathway is upstream of the mammalian target of rapamycin (mTOR), which is of great importance in the induction of autophagy. However, whether the neuroprotective effect of IGF-1 against excitotoxicity is mediated by autophagy through the PI3K/AKT/mTOR pathway remains to be elucidated. The induction of autophagy following NMDA treatment was determined by microtubule-associated protein light chain 3 (LC3) conversion and the result of this autophagy was assessed by monitoring the cleavage of caspase 3 in cultured hippocampal neurons. Cell viability was determined using MTT and LDH assay, and PI-staining was used to estimate the fate of autophagy and the protective effect of IGF-1. In addition, IGF-1 was found to decrease autophagy induced by NMDA using transmission electron microscopy and MDC staining. The protective effect of IGF-1 against autophagy was accompanied with up-regulation of phospho-AKT (p-AKT) and phospho-mTOR (p-mTOR), which was blocked by the inhibitor of PI3K. At the same time, the activation of NR2B resulting in the down-regulation of p-AKT and p-mTOR was blocked by IGF-1. Together, these data suggest that NMDA induces the autophagy, followed by apoptosis in cultured hippocampal neurons, and that IGF-1 can block this effect via inhibition of NR2B receptors and activation of the PI3K-AKT-mTOR pathway.

Core/shell Au/CuPt nanoparticles and their dual electrocatalysis for both reduction and oxidation reactions.

We report a facile synthesis of monodisperse core/shell 5/1.5 nm Au/CuPt nanoparticles by coreduction of platinum acetylacetonate and copper acetylacetonate in the presence of 5 nm Au nanoparticles. The CuPt alloy effect and core/shell interactions make these Au/CuPt nanoparticles a promising catalyst for both oxygen reduction reaction and methanol oxidation reaction in 0.1 M HClO4 solution. Their specific (mass) reduction and oxidation activities reach 2.72 mA/cm(2) (1500 mA/mg Pt) at 0.9 V and 0.755 mA/cm(2) (441 mA/mg Pt) at 0.8 V (vs reversible hydrogen electrode), respectively. Our studies show that the existence of the Au nanoparticle core not only minimizes the Pt usage but also improves the stability of the Au/CuPt catalyst for fuel cell reactions. The results suggest that the core/shell design is indeed effective for optimizing nanoparticle catalysis. The same concept may be extended to other multimetallic nanoparticle systems, making it possible to tune nanoparticle catalysis for many different chemical reactions.

Rapid detection of phenytoin sodium by partial-least squares and linear regression models combined with surface-enhanced Raman spectroscopy.

Surface-enhanced Raman spectroscopy (SERS) for quantitative analysis is challenging owing to the unstable enhanced effect. However, it can be improved by combining it with chemometrics. In this study, we established a quantitative analysis method for phenytoin sodium (PS) based on partial least-squares (PLS) and linear regression (LR) models combined with SERS. Gold nanoparticles (AuNPs) were optimally enhanced substrates for PS. 180 PS samples in the concentration range of 0.98 - 980 µg mL-1 were used to establish a quantitative prediction model by PLS regression, and an accurate and robust prediction was achieved. Furthermore, we found that SERS peak intensity showed a good linear correlation with the concentration of PS in the concentration range of 1 - 80 µg mL -1. After using P-mercaptobenzoic acid as an internal standard, the accuracy and precision of the LR model were significantly improved compared with that of the model without an internal standard. In general, PLS chemometrics and LR model with internal standard which were combined with SERS in this paper provide new possible analytical methods for analytes to develop a rapid and sensitive quantitative analysis method.

Identification of differentially expressed microRNAs and their PKC-isoform specific gene network prediction during hypoxic pre-conditioning and focal cerebral ischemia of mice.

We previously reported the involvement of conventional protein kinase C (cPKC) ßII, γ, novel PKC (nPKC) ε and their interacting proteins in hypoxic pre-conditioning (HPC)-induced neuroprotection. In this study, the large-scale miRNA microarrays and bioinformatics analysis were used to determine the differentially expressed miRNAs and their PKC-isoform specific gene network in mouse brain after HPC and 6 h middle cerebral artery occlusion (MCAO). We found 4 up-regulated and 13 down-regulated miRNAs in the cortex of HPC mice, 26 increased and 39 decreased gene expressions of miRNAs in the peri-infarct region of 6 h MCAO mice, and 11 up-regulated and 22 down-regulated miRNAs in the peri-infarct region of HPC and 6 h MCAO mice. Based on Diff Score, 19 differentially expressed miRNAs were identified in HPC and 6 h MCAO mouse brain. Then the miRNA-gene-network of 19 specified miRNAs target genes of cPKCßII, γ and nPKCε-interacting protein was predicted by using bioinformatics analysis of genome databases. Furthermore, the down-regulated miR-615-3p during HPC had a detrimental effect on the oxygen-glucose deprivation (OGD)-induced N2A cell injury. These results suggested that the identified 19 miRNAs, notably miR-615-3p, might target these genes of cPKCßII, γ and nPKCε-interacting proteins involved in HPC-induced neuroprotection.

Surfactant-induced postsynthetic modulation of Pd nanoparticle crystallinity.

Modulation of Pd nanoparticle (NP) crystallinity is achieved by switching the surfactants of different binding strengths. Pd NPs synthesized in the presence of weak binding surfactants such as oleylamine possess polyhedral shapes and a polycrystalline nature. When oleylamine is substituted by trioctylphosphine, a much stronger binding surfactant, the particles become spherical and their crystallinity decreases significantly. Moreover, the Pd NPs reconvert their polycrystalline structure when the surfactant is switched back to oleylamine. Through control experiments and molecular dynamics simulation, we propose that this unusual nanocrystallinity transition induced by surfactant exchange was resulted from a counterbalance between the surfactant binding energy and the nanocrystal adhesive energy. The findings represent a novel postsynthetic approach to tailoring the structure and corresponding functional performance of nanomaterials.

Regulatory pattern of abnormal promoter CpG island methylation in the glioblastoma multiforme classification.

Glioblastoma (GBM) is characterized by extensive genetic and phenotypic heterogeneity. However, it remains unexplored primarily how CpG island methylation abnormalities in promoter mediate glioblastoma typing. First, we presented a multi-omics scale map between glioblastoma sample clusters constructed based on promoter CpG island (PCGI) methylation-driven genes, using datasets including methylation profiles, expression profiles, and single-cell sequencing data from multiple highly annotated public clinical cohorts. Second, we identified differences in the tumor microenvironment between the two glioblastoma sample clusters and resolved key signaling pathways between cell clusters at the single-cell level based on comprehensive comparative analyses to investigate the reasons for survival differences between two of these clusters. Finally, we developed a diagnostic map and a prediction model for glioblastoma, and compared theoretical differences of drug sensitivity between two glioblastoma sample clusters. In summary, this study established a classification system for dissecting promoter CpG island methylation heterogeneity in glioblastoma and provides a new perspective for the diagnosis and treatment of glioblastoma.

Design and synthesis of bimetallic electrocatalyst with multilayered Pt-skin surfaces.

Advancement in heterogeneous catalysis relies on the capability of altering material structures at the nanoscale, and that is particularly important for the development of highly active electrocatalysts with uncompromised durability. Here, we report the design and synthesis of a Pt-bimetallic catalyst with multilayered Pt-skin surface, which shows superior electrocatalytic performance for the oxygen reduction reaction (ORR). This novel structure was first established on thin film extended surfaces with tailored composition profiles and then implemented in nanocatalysts by organic solution synthesis. Electrochemical studies for the ORR demonstrated that after prolonged exposure to reaction conditions, the Pt-bimetallic catalyst with multilayered Pt-skin surface exhibited an improvement factor of more than 1 order of magnitude in activity versus conventional Pt catalysts. The substantially enhanced catalytic activity and durability indicate great potential for improving the material properties by fine-tuning of the nanoscale architecture.

Engineered Thin Diffusion Layers for Anion-Exchange Membrane Electrolyzer Cells with Outstanding Performance.

Anion-exchange membrane electrolyzer cells (AEMECs) are one of the most promising technologies for carbon-neutral hydrogen production. Over the past few years, the performance and durability of AEMECs have substantially improved. Herein, we report an engineered liquid/gas diffusion layer (LGDL) with tunable pore morphologies that enables the high performance of AEMECs. The comparison with a commercial titanium foam in the electrolyzer indicated that the engineered LGDL with thin-flat and straight-pore structures significantly improved the interfacial contacts, mass transport, and activation of more reaction sites, leading to outstanding performance. We obtained a current density of 2.0 A/cm2 at 1.80 V with an efficiency of up to 81.9% at 60 °C under 0.1 M NaOH-fed conditions. The as-achieved high performance in this study provides insight to design advanced LGDLs for the production of low-cost and high-efficiency AEMECs.