Identification of necroptosis-related diagnostic biomarkers in coronary heart disease.

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.

Effective enrichment of trace exosomes for the label-free SERS detection via low-cost thermophoretic profiling.

Exosome-based liquid biopsies possess great potential in monitoring cancer development However, current exosome detection biosensors require large exosome volumes, showing the weak detection sensitivity. Besides, these methods pay little attention to in situ analysis of exosomes, hence limiting the provision of more accurate clinically-relevant information. Herein, we develop an innovative label-free biosensor combining the low-cost thermophoretic enrichment method with the surface-enhanced Raman spectroscopy (SERS) detection. Based on the thermophoretic enrichment strategy, exosomes and gold nanoparticles can be enriched together into a small area with a scale of 500 µm within 10 min. The Raman signals of various exosomes derived from normal, cancerous cell lines and human serum are dynamically monitored in situ, with the limit of detection of 102-103 particles per microliter, presenting higher sensitivity compared with the similar label-free SERS detection. The spectral data set of different exosomes is applied to train for multivariate classification of cell types and to estimate how the normal exosome data resemble cancer cell exosome. The reliable classification and identification of different exosomes can be realized. The current biosensor is convenient, low-cost and requires small exosome volumes (∼3 µL), and if validated in larger cohorts may contribute to the tumor prediction and diagnosis.

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

Background: Heart 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. Methods: The 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. Results: We 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. Conclusion: Our 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.

Prediction of diagnostic gene biomarkers for hypertrophic cardiomyopathy by integrated machine learning.

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.

Identification of Immuno-Inflammation-Related Biomarkers for Acute Myocardial Infarction Based on Bioinformatics.

Purpose: Previous studies have confirmed that inflammation and immunity are involved in the pathogenesis of acute myocardial infarction (AMI). However, only few related genes are identified as biomarkers for the diagnosis and treatment of AMI. Patients and Methods: GSE48060 and GSE60993 datasets were retrieved from Gene Expression Omnibus. The differentially expressed immuno-inflammation-related genes (DEIIRGs) were obtained from GSE48060, and the biomarkers for AMI were screened and validated using the "Neuralnet" package and GSE60993 dataset. Further, the biomarker-based nomogram was constructed, and miRNAs, transcription factors (TFs), and potential drugs targeting the biomarkers were explored. Furthermore, immune infiltration analysis was analyzed in AMI. Finally, the biomarkers were verified by assessing their mRNA levels using real-time quantitative PCR (RT-qPCR). Results: First, eight biomarkers were screened via bioinformatics, and the artificial neural network model indicated a higher prediction accuracy for AMI even in the validation dataset. Nomogram had accurate forecasting ability for AMI as well. The TFs GTF2I, PHOX2B, RUNX1, and FOS targeting hsa-miR-1297 could regulate the expressions of ADM and CBLB, and RORA could effectively interact with melatonin and citalopram. RT-qPCR results for ADM, PI3, MMP9, NRG1 and CBLB were consistent with those of bioinformatic analysis. Conclusion: In conclusion, eight key immuno-inflammation-related genes, namely, SH2D1B, ADM, PI3, MMP9, NRG1, CBLB, RORA, and FASLG, may serve as the potential biomarkers for AMI, in which the downregulation of CBLB and upregulation of ADM, PI3, and NRG1 in AMI was detected for the first time, providing a new strategy for the diagnosis and treatment of AMI.

Exploration of the shared gene signatures and molecular mechanisms between atherosclerosis and rheumatoid arthritis via multi-microarray data analyses.

Background: Accumulating evidence indicates the inflammatory state of rheumatoid arthritis (RA) predisposes to the acceleration of atherosclerosis (AS). Nevertheless, the potential mechanisms of accelerating AS in RA have not been fully elucidated. Our current study was to probe the problem via multi-microarray data analyses. Methods: The transcriptional profiling of synovial tissues from RA (GSE55235 and GSE55457) and that of atherosclerotic plaques from AS (GSE28829 and GSE41571) were downloaded from the Gene Expression Omnibus database. Bioinformatics analyses procedures included identifying common differentially expressed genes (DEGs), constructing protein-protein interaction network, key modules analysis and identifying hub genes, validating hub genes by using external datasets (GSE77298 and GSE163154), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, constructing transcription factor (TF)-miRNA coregulatory network and exploiting candidate drugs targeting hub genes. Results: A total of 67 common DEGs were identified for downstream analyses. GO and KEGG analyses of these genes expounded a critical role of inflammatory mediators and reactions in the comorbidities. Sixteen hub genes were identified, and their functional analyses further highlighted a complicated inflammatory micro-environment and signaling pathways involving RA and AS. Six TFs and four miRNAs interacted with hub genes, and the candidate drugs targeting them were simvastatin, 5-azacytidine, bisindolylmaleimide, retinoic acid, and verteporfin, etc. Conclusions: Our comprehensive bioinformatics analyses provided a novel view regarding the potential pathogenesis of AS in RA. Furthermore, exploitation of candidate drugs might hold great promise in the future fight against the comorbidities.

TIPE2 protects cardiomyocytes from ischemia-reperfusion-induced apoptosis by decreasing cell autophagy via the mTORC1 signaling pathway.

In cardiac ischemia-reperfusion (I/R), autophagy of hyperactivated cardiomyocytes degrades normal proteins and organelles, destroys cells and causes irreversible cell death. The present study aimed to determine the molecular mechanism through which TNF-α-induced protein 8-like protein 2 (TIPE2) regulates cardiomyocyte apoptosis via autophagy in I/R. The results revealed that the number of apoptotic cells and the protein expression levels of TIPE2 in the heart tissue of I/R model mice were significantly increased. In vitro, the overexpression of TIPE2 decreased oxygen glucose deprivation (OGD)-induced autophagy, apoptosis and activation of the mTOR complex 1 (mTORC1) signaling pathway in H9c2 cells. Treatment with the mTORC1 inhibitor not only inhibited the TIPE2-activated mTORC1 signaling pathway, but also increased OGD-induced autophagy and apoptosis of H9c2 cells. In conclusion, the results of the present study revealed that TIPE2 may protect cardiomyocytes from I/R-induced apoptosis by decreasing cell autophagy via the mTORC1 signaling pathway.

Remote Raman Detection of Trace Explosives by Laser Beam Focusing and Plasmonic Spray Enhancement Methods.

Remote Raman spectroscopy is a technique that can detect and identify different target molecules through Raman vibrational modes from a remote distance. However, the current remote Raman technique is restricted by poor detection sensitivity, and it is still extremely challenging for trace explosive detection. Here, in order to achieve trace explosive detection from a remote distance, we innovatively propose two enhanced Raman spectroscopy methods by using a plasmonic spray and a laser beam focusing/Raman signal collecting instrument. In brief, a facile convex lens can converge the laser beam and collect Raman scattering signals, and a plasmonic spray can be used for surface-enhanced Raman scattering. Under the combination of the above enhancement methods, we achieve remote Raman detection of a variety of trace explosives with a concentration of ∼1 µg/cm2 from a distance of 30 m. These novel methods demonstrate a simple approach that significantly improves the capability of remote detection of trace chemicals for further applications.

Casted MoS2 nanostructures and their Raman properties.

Two-dimensional (2D) transition metal dichalcogenides (TMDCs) have been widely investigated for optoelectronic applications. Here, by employing the nanocasting method, molybdenum disulfide (MoS2) nanostructures, including supercrystals, nanoparticles and nanowires, are synthesized with curved features by changing the precursor concentration and template types. The Raman properties of different MoS2 nanostructures are investigated by varying the laser power under both resonant and non-resonant excitations. The defect disorder induced LA(M) mode and other silent Raman modes in planar 2D materials are clearly observed under the resonant excitation. We believe that the varying optical properties of TMDC nanostructures will greatly broaden the optoelectronic applications of 2D materials.

The Key Genes Underlying Pathophysiology Correlation Between the Acute Myocardial Infarction and COVID-19.

Introduction: Accumulating evidences disclose that COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has a marked effect on acute myocardial infarction (AMI). Nevertheless, the underlying pathophysiology correlation between the AMI and COVID-19 remains vague. Materials and Methods: Bioinformatics analyses of the altered transcriptional profiling of peripheral blood mononuclear cells (PBMCs) in patients with AMI and COVID-19 were implemented, including identification of differentially expressed genes and common genes between AMI and COVID-19, protein-protein interactions, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses, TF-genes and miRNA coregulatory networks, to explore their biological functions and potential roles in the pathogenesis of COVID-19-related AMI. Conclusion: Our bioinformatic analyses of gene expression profiling of PBMCs in patients with AMI and COVID-19 provide us with a unique view regarding underlying pathophysiology correlation between the two vital diseases.

Ultra-rapid and highly efficient enrichment of organic pollutants via magnetic mesoporous nanosponge for ultrasensitive nanosensors.

Currently, owing to the single-molecule-level sensitivity and highly informative spectroscopic characteristics, surface-enhanced Raman scattering (SERS) is regarded as the most direct and effective detection technique. However, SERS still faces several challenges in its practical applications, such as the complex matrix interferences, and low sensitivity to the molecules of intrinsic small cross-sections or weak affinity to the surface of metals. Here, we show an enrichment-typed sensing strategy with both excellent selectivity and ultrahigh detection sensitivity based on a powerful porous composite material, called mesoporous nanosponge. The nanosponge consists of porous ß-cyclodextrin polymers immobilized with magnetic NPs, demonstrating remarkable capability of effective and fast removal of organic micropollutants, e.g., ~90% removal efficiency within ~1 min, and an enrichment factor up to ~103. By means of this current enrichment strategy, the limit of detection for typical organic pollutants can be significantly improved by 2~3 orders of magnitude. Consequently, the current enrichment strategy is proved to be applicable in a variety of fields for portable and fast detection, such as Raman and fluorescent sensing.

Switchable Binding Energy of Ionic Compounds and Application in Customizable Ligand Exchange for Colloid Nanocrystals.

The ability to engineer the surface ligands or adsorbed molecules on colloid nanocrystals (NCs) is important for various applications, as the physical and chemical properties are strongly affected by the surface chemistry. Here, we develop a facile and generalized ionic compound-mediated ligand-exchange strategy based on density functional theory calculations, in which the ionic compounds possess switchable bonding energy when they transfer between the ionized state and the non-ionized state, hence catalyzing the ligand-exchange process. By using an organic acid as the intermediate ligand, ligands such as oleylamine, butylamine, polyvinylpyrrolidone, and poly(vinyl alcohol) can be freely exchanged on the surface of Au NCs. Benefiting from this unique ligand-exchange strategy, the ligands with strong bonding energy can be replaced by weak ones, which is hard to realize in traditional ligand-exchange processes. The ionic compound-mediated ligand exchange is further utilized to improve the catalytic properties of Au NCs, facilitate the loading of nanoparticles on substrates, and tailor the growth of colloid NCs. These results indicate that the mechanism of switchable bonding energy can be significantly expanded to manipulate the surface property and functionalization of NCs that have applications in a wide range of chemical and biomedical fields.

Solution-Based SERS Detection of Weak Surficial Affinity Molecules Using Cysteamine-Modified Au Bipyramids.

To achieve ultrasensitive detection of trace targets through solution-based surface-enhanced Raman spectroscopy (SERS), direct adsorption of the target molecules on a SERS-active surface is vital. In this work, cetyltrimethylammonium bromide (CTAB)-capped gold nano-bipyramids (Au BPs) with different aspect ratios (ARs) are prepared and the surface is successfully modified by a simple ligand exchange method. Cysteamine-capped gold nano-bipyramids (cyst-Au BPs) are obtained by means of replacement of CTAB by cysteamine using Au-S covalent bonding and applied in the solution-based SERS detection of different pigment molecules, which always have weak affinity to the gold surface. The hydrogen bonding between the pigment molecule and cysteamine causes the aggregation of Au BPs to generate local electromagnetic field enhancement. The influence of the AR and concentration of Au BPs on SERS properties is investigated. The SERS detection of weak-affinity molecules to an extremely low limit shows that the cyst-Au BPs are highly sensitive compared to CTAB-capped Au BPs. The limit of detection (LOD) of allura red as low as 0.1 ppb and that of sunset yellow as low as 1 ppb show that the proposed strategy has many advantages due to its simplicity and fast and rapid detection for the sensitivity analysis of weak-affinity molecules.

Clinical value of serum Ape1/Ref-1 combined with TGF-ß1 monitoring in predicting the occurrence of radiation pneumonitis (RP) in non-small cell lung cancer patients.

BACKGROUND: The aim of the present study was to explore the predictive value of serum apurinic/apyrimidinic endonuclease 1/redox factor-1 (Ape1/Ref-1) combined with transforming growth factor ß1 (TGF-ß1) levels in the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLS). METHODS: Eighty-one patients with NSCLS who were admitted from August 2017 to July 2019 were enrolled in the present study. All patients were treated with concurrent radiotherapy and chemotherapy. Serum Ape1/Ref-1 and TGF-ß1 levels were measured before treatment and 12 weeks after treatment. Patients with radiation-induced lung injury were assessed and divided into the RP group (lung injury ≥2) and non-RP (NRP) group (grade <2). The levels of serum Ape1/Ref-1 and TGF-ß1 before and after treatment between the 2 groups were compared. The relationship between clinical characteristics, serum Ape1/Ref-1, TGF-ß1 levels, and the occurrence of RP were then analyzed, and the relationship between serum Ape1/Ref-1, TGF-ß1 levels, and their predictive value for the occurrence of RP was also assessed. RESULTS: The incidence of RP in 81 patients was 30.86%. After treatment, the serum Ape1/Ref-1 and TGF-ß1 levels of the 2 groups were significantly higher than those before treatment (P<0.05). Furthermore, after treatment, the levels of serum Ape1/Ref-1 and TGF-ß1 in the RP group were significantly higher than those of the NRP group (P<0.05). Multivariate logistic regression analysis showed that V20, Ape1/Ref-1, and TGF-ß1 were associated with the occurrence of RP (P<0.05). The levels of serum Ape1/Ref-1 were positively correlated with TGF-ß1 (r=0.734, P<0.05). Finally, the area under the curve of RP occurrence, which was predicted by the levels of serum Ape1/Ref-1, TGF-ß1, and the combination of both were 0.779, 0.69, and 0.842, respectively. CONCLUSIONS: The occurrence of RP in NSCLS patients is closely related to the levels of serum Ape1/Ref-1 and TGF-ß1, and the combination of both has important predictive values for the occurrence of RP.

Rosmarinic acid ameliorated cardiac dysfunction and mitochondrial injury in diabetic cardiomyopathy mice via activation of the SIRT1/PGC-1α pathway.

Mitochondrial injury plays an essential role in the pathogenesis of diabetic cardiomyopathy (DCM). Previous studies demonstrated that rosmarinic acid (RA) treatment prevented high glucose-induced mitochondrial injury in vitro. However, whether RA can ameliorate cardiac function by preventing mitochondrial injury in DCM is unknown. The SIRT1/PGC-1α pathway has emerged as an important regulator of metabolic control and other mitochondrial functions. The present study was undertaken to determine the effects of RA on mitochondrial and cardiac function in DCM as well as the involvement of the SIRT1/PGC-1α pathway. Our results revealed that RA improved cardiac systolic and diastolic function and prevented mitochondrial injury in DCM, as shown by the reduced blood glucose and lipid levels, increased mitochondrial membrane potential levels, improved adenosine triphosphate synthesis, and inhibited apoptosis (P < 0.05). Moreover, RA upregulated the expression of SIRT1 and PGC-1α in DCM mice and high glucose-treated H9c2 cardiomyocytes (P < 0.05). Further mechanistic studies in H9c2 cardiomyocytes revealed that suppression of SIRT1 by Sh-SIRT1 counteracted the effects of RA on high glucose-induced abnormal metabolism of glucose and lipids, oxidative stress and apoptosis (P < 0.05). Taken together, these data indicate that RA prevented mitochondrial injury and cardiac dysfunction in DCM mice, and the SIRT1/PGC-1α pathway mediated the protective effects of RA.

Micro-area investigation on electrochemical performance improvement with Co and Mn doping in PbO2 electrode materials.

PbO2-Co3O4-MnO2 electrodes, used in the electrowinning industry and in the degradation of organic pollutants, have demonstrated an elevated performance through macroscopic electrochemical measurements. However, few reports have investigated localized electrochemical performance, which plays an indispensable role in determining the essential reasons for the improvement of the modified material. In this study, the causes of the increase in electrochemical reactivity are unveiled from a micro perspective through scanning electrochemical microscopy (SECM), X-ray diffraction (XRD), Raman microscopy (Raman), and X-ray photoelectronic energy spectroscopy (XPS). The results show that the increase of electrochemical reactivity of the modified electrodes results from two factors: transformation of the microstructure and change in the intrinsic physicochemical properties. Constant-height scanning maps indicate that the electrochemical reactivity of the modified electrodes is higher than that of the PbO2 electrode on the whole and high-reactivity areas are orderly distributed, coinciding with the observations from SEM and XRD. Thus, one of the reasons for the improvement of the modified electrode performance is the refinement of the microscopic morphology. The other reason is the surge of the oxygen vacancy concentration on the surface of the coating, which is supported by XRD, Raman and XPS. This finding is detected by the probe approach curve (PAC), which can quantitatively characterize the electrochemical reactivity of a substrate. Heterogeneous charge transfer rate constants of the modified electrode are 4-5 times higher than that of the traditional PbO2 electrode. This research offers some insight into the electrochemical reactivity of modified PbO2 electrodes from a micro perspective.

[Rosmarinic acid inhibits high glucose-induced cardiomyocyte hypertrophy by activating Parkin-mediated mitophagy].

OBJECTIVE: To evaluate the effect of rosmarinic acid (RA) on mitophagy and hypertrophy of cardiomyocytes exposed to high glucose (HG). METHODS: Rat cardiomyocytes (H9c2) exposed to HG (25 mmol/L) were treated with 50 µmol/L RA or with both RA treatment and Parkin siRNA transfection, with the cells cultured in normal glucose (5.5 mmol/L) and HG as the controls. The expressions of PINK1, Parkin and LC3II/LC3I in the cells were detected by Western blotting. The formation of mitochondrial autophagosomes was observed by transmission electron microscope. Flow cytometry was employed to detect the level of reactive oxygen species (ROS) and apoptotic rate of the cells. The activities of respiratory chain complex enzymes were measured by spectrophotometry. Fluorescence enzyme labeling and 3H-leucine labeling were used for determining the level of membrane potential and protein synthesis rate, respectively. The cell surface area was observed by light microscopy. RESULTS: RA treatment significantly increased the expression levels of PINK1, Parkin and LC3-II/I (P < 0.05), promoted the formation of mitochondrail autophagosome, inhibited the production of reactive oxygen species (P < 0.05), restored the activities of mitochondrial respiratory chain complex enzymes and mitochondrial membrane potential (P < 0.05), inhibited apoptosis (P < 0.05), and reduced the cell surface area and protein synthesis rate of H9c2 cells induced by HG exposure (P < 0.05). The protective effects of RA against HG-induced oxidative stress and cardiomyocyte hypertrophy was obviously blocked by inhibition of mitophagy mediated by transfection with Parkin siRNA (P < 0.05). CONCLUSIONS: RA can protect rat cardiomyocytes against oxidative stress injury and cardiomyocyte hypertrophy induced by HG by activating Parkin-mediated mitophagy.

Facile Surface Modification of Mesoporous Au Nanoparticles for Highly Sensitive SERS Detection.

The stability, dispersity, and surface chemical properties of colloidal nanoparticles are crucial for the reliable and desired chemical sensing in various applications. Here, we report an effective strategy to engineer the surface properties of mesoporous Au nanoparticles (meso-Au NPs) via PVP ligand modification, template removal, and surface purification. Monodispersed 3D meso-Au NPs with well-defined sizes and shapes were obtained using a general soft-enveloping strategy. During surface modification, the addition of PVP ligands and the concentration of HF solutions play key roles in the stability, shape, and size distributions of ordered Au networks. In order to obtain an improved sensing performance, the morphologies of meso-Au NPs were optimized with smaller mesopore size, and NaBH4 solution was used to efficiently remove the adsorbed PVP ligands. Due to the characteristics of high-density porosities and large surface area, the purified meso-Au NPs could be a kind of promising plasmonic-enhanced nanomaterial and provide abundant "hot spots." Combined with the enrichment effect using a slippery liquid-infused porous surface, the lowest detection limits of crystal violet molecule could be down to 0.1 pM, demonstrating an excellent SERS sensitivity. Moreover, a realistic illegal drug containing aspirin could be sensitively detected with a limit of 2.8 × 10-6 M, showing great potential for practical molecular sensing and applications.

Ratiometric Sensing of Polycyclic Aromatic Hydrocarbons Using Capturing Ligand Functionalized Mesoporous Au Nanoparticles as a Surface-Enhanced Raman Scattering Substrate.

The absorption behavior between plasmonic nanostructures and a target molecule plays key roles in effective surface-enhanced Raman scattering (SERS) detection. However, for analytes with low surface affinity to the metallic surface, e.g., polycyclic aromatic hydrocarbons (PAHs), it remains challenging to observe the enhanced Raman signal. In this work, we reported a ratiometric SERS strategy for sensitive PAH detection through the surface functionalization of 3D ordered mesoporous Au nanoparticles (meso-Au NPs). By employing mono-6-thio-ß-cyclodextrin (HS-ß-CD) as capture ligands, the hydrophobic molecules, e.g., anthracene, could be effectively absorbed on the meso-Au NP surface via a host-guest interaction. Besides, a hydrophobic slippery surface is used as a concentrator to deliver and enrich the Au/analyte droplets into a small area. Consequently, the detection limits of anthracene and naphthalene are down to 1 and 10 ppb. The improved SERS enhancement is mainly ascribed to the host-guest effect of HS-ß-CD ligands, large surface area and high-density of sub-10 nm mesopores of Au networks, as well as the enrichment effect of hydrophobic slippery surface. Moreover, the HS-ß-CD (480 cm-1 band) could serve as an internal standard, leading to the ratiometric determination of anthracene ranging from 1 ppm to 1 ppb. The proposed surface modification strategy in combination with the hydrophobic slippery surface shows great potential for active capture and trace detection of persistent organic pollutants in real-world SERS applications.

Shape-Controlled Hierarchical Flowerlike Au Nanostructure Microarrays by Electrochemical Growth for Surface-Enhanced Raman Spectroscopy Application.

How to fabricate Au nanostructures conveniently on microstructured/nanostructured arrays surface with low cost has become a crucial and urgent challenge. In this study, we demonstrate hierarchical flowerlike Au nanostructures with rich nanothorns (HF-AuNTs) through one-step electrochemical deposition. The morphology of the HF-AuNTs is easily manipulated by controlling the applied potential or precursor solution concentration of electrodeposition. The as-prepared HF-AuNTs possessing unique local morphology of thin petals and dense thorns are further applied in the Si micropit arrays to acquire HF-AuNTs microarrays. As an initial detection, these HF-AuNTs microarrays exhibit a fascinating surface-enhanced Raman spectroscopy consistency (relative standard deviation is 7.17%) and sensitivity with the limitation of crystal violet reaching to 10-10 M, and Rhodamine 6G reaching to 10-11 M. The HF-AuNTs microarrays with well-defined shape and elaborate structure may be applicated in SERS substrates, superhydrophobic materials, and so on.