Construction and validation of a TAMRGs prognostic signature for gliomas by integrated analysis of scRNA and bulk RNA sequencing data.

BACKGROUND: This study aimed to construct and validate a prognostic model based on tumor associated macrophage-related genes (TAMRGs) by integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) data. METHODS: The scRNA-seq data of three inhouse glioma tissues were used to identify the tumor-associated macrophages (TAMs) marker genes, the DEGs from the The Cancer Genome Atlas (TCGA) - Genotype-Tissue Expression (GTEx) dataset were used to further select TAMs marker genes. Subsequently, a TAMRG-score was constructed by Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis in the TCGA dataset and validated in the Chinese Glioma Genome Atlas (CGGA) dataset. RESULTS: We identified 186 TAMs marker genes, and a total of 6 optimal prognostic genes including CKS2, LITAF, CTSB, TWISTNB, PPIF and G0S2 were selected to construct a TAMRG-score. The high TAMRG-score was significantly associated with worse prognosis (log-rank test, P<0.001). Moreover, the TAMRG-score outperformed the other three models with AUC of 0.808. Immune cell infiltration, TME scores, immune checkpoints, TMB and drug susceptibility were significantly different between TAMRG-score groups. In addition, a nomogram were constructed by combing the TAMRG-score and clinical information (Age, Grade, IDH mutation and 1p19q codeletion) to predict the survival of glioma patients with AUC of 0.909 for 1-year survival. CONCLUSION: The high TAMRG-score group was associated with a poor prognosis. A nomogram by incorporating TMARG-score could precisely predict glioma survival, and provide evidence for personalized treatment of glioma.

A Statistical Route to Robust SERS Quantitation Beyond the Single-Molecule Level.

Single-molecule surface-enhanced Raman spectroscopy (SM-SERS) holds great potential to revolutionize ultratrace quantitative analysis. However, achieving quantitative SM-SERS is challenging because of strong intensity fluctuation and blinking characteristics. In this study, we reveal the relation P = 1 - e-α between the statistical SERS probability P and the microscopic average molecule number α in SERS spectra, which lays the physical foundation for a statistical route to implement SM-SERS quantitation. Utilizing SERS probability calibration, we achieve quantitative SERS analysis with batch-to-batch robustness, extremely wide detection range of concentration covering 9 orders of magnitude, and ultralow detection limit far below the single-molecule level. These results indicate the physical feasibility of robust SERS quantitation through statistical route and certainly open a new avenue for implementing SERS as a practical analysis tool in various application scenarios.

Localized surface plasmon resonance (LSPR) excitation on single silver nanoring with nanoscale surface roughness.

With the expansion of the application of high-sensitivity Surface-enhanced Raman scattering (SERS) technique, micro SERS-active substrates with rich optical properties and high-level functions are desired. In this study, silver nanorings with nanoscale surface roughness were fabricated as a new type of enclosed quasi-2D micro-SERS-active substrate. Highly-crystalline spherical and hemispherical silver nanoprotrusions were densely and uniformly distributed over the entire surface of the nanorings. The SERS signals were significantly enhanced on the roughened silver nanorings which were mainly derived from the maximal localized surface plasmon resonance (LSPR) points at the junctions between adjacent coupled nanoprotrusions on the roughened nanorings. The mapping image shows a uniform and intense LSPR enhancement over the nanorings, owing to the uniform and dense distribution of silver nanoprotrusions and the resulting uniform distribution of maximal LSPR points on the roughened nanorings. The dark-field spectra further indicated that the single roughened silver nanoring had significant LSPR enhancement, a wide LSPR frequency-range response, and adaptability for SERS enhancement. Notably, both the measured and simulated results demonstrate that the maximal LSPR enhancement at the junctions between the nanoprotrusions, which are distributed on the inner surface of the silver nanoring, is higher than that on the outer surface because of the plasmon-focusing effect of the enclosed silver nanoring, which leads to the lateral asymmetrical distribution of LSPR intensity, indicating more LSPR and SERS features. These results indicate that single roughened silver nanorings exhibit excellent performance as a new type of enclosed quasi-2D silver nanoring micro-SERS-active substrate, microzone LSPR catalysis, and micro/nanodevices.

Characterization of the m6A/m1A/m5C/m7G-related regulators on the prognosis and immune microenvironment of glioma by integrated analysis of scRNA-seq and bulk RNA-seq data.

BACKGROUND: Proliferation, metabolism, tumor occurrence and development in gliomas are greatly influenced by RNA modifications. However, no research has integrated the four RNA methylation regulators of m6A, m1A, m5C and m7G in gliomas to analyze their relationship with glioma prognosis and intratumoral heterogeneity. METHODS: Based on three in-house single-cell RNA-sequencing (scRNA-seq) data, the glioma heterogeneity and characteristics of m6A/m1A/m5C/m7G-related regulators were elucidated. Based on publicly available bulk RNA-sequencing (RNA-seq) data, a risk-score system for predicting the overall survival (OS) for gliomas was established by three machine learning methods and multivariate Cox regression analysis, and validated in an independent cohort. RESULTS: Seven cell types were identified in gliomas by three scRNA-seq data, and 22 m6A/m1A/m5C/m7G-related regulators among the marker genes of different cell subtypes were discovered. Three m6A/m1A/m5C/m7G-related regulators were selected to construct prognostic risk-score model, including EIFA, NSUN6 and TET1. The high-risk patients showed higher immune checkpoint expression, higher tumor microenvironment scores, as well as higher tumor mutation burden and poorer prognosis compared with low-risk patients. Additionally, the area under the curve values of the risk score and nomogram were 0.833 and 0.922 for 3 year survival and 0.759 and 0.885 for 5 year survival for gliomas. EIF3A was significantly highly expressed in glioma tissues in our in-house RNA-sequencing data (p < 0.05). CONCLUSION: These findings may contribute to further understanding of the role of m6A/m1A/m5C/m7G-related regulators in gliomas, and provide novel and reliable biomarkers for gliomas prognosis and treatment.

Development and validation of cuproptosis molecular subtype-related signature for predicting immune prognostic characterization in gliomas.

PURPOSE: Cuproptosis, a novel programmed cell death, plays an important role in glioma growth, angiogenesis, and immune response. Nonetheless, the role of cuproptosis-related genes (CRGs) in the prognosis and tumor microenvironment (TME) of gliomas remains unknown. METHODS: By non-negative matrix factorization consensus clustering, 1286 glioma patients were classified based on the mRNA expression levels of 27 CRGs and investigated the association of immune infiltration and clinical characteristics with cuproptosis subtypes. A CRG-score system was constructed using LASSO and multivariate Cox regression methods and validated in independent cohorts to predict the prognosis of glioma patients. RESULTS: Glioma patients were divided into two cuproptosis subtypes. Cluster C2 was enriched in immune-related pathways, had higher macrophage M2, neutrophils, and CD8 + T cells, and poorer prognosis compared with cluster C1 which was enriched in metabolism-related pathways. We further constructed and validated the ten-gene CRG risk scores. Glioma patients in the high CRG-score group had higher tumor mutation burden, higher TME scores, and poorer prognoses compared with the low CRG-score group. Additionally, the AUC value of the CRG-score was 0.778 in predicting the prognosis of gliomas. WHO grading, IDH mutation, 1p/19q codeletion, and MGMT methylation were significant differences between high and low CRG-score groups. CONCLUSION: This study demonstrated that CRG-score was related to immune cell infiltration and could accurately predict gliomas' prognosis. Our findings may provide a novel understanding of the potential role of cuproptosis molecular pattern and TME in the immune response and prognosis of glioma patients.

Single-cell RNA-Seq and bulk RNA-Seq reveal reliable diagnostic and prognostic biomarkers for CRC.

PURPOSE: The potential role of epithelium-specific genes through the adenoma-carcinoma sequence in the development of colorectal cancer (CRC) remains unknown. Therefore, we integrated single-cell RNA sequencing and bulk RNA sequencing data to select diagnosis and prognosis biomarkers for CRC. METHODS: The CRC scRNA-seq dataset was used to describe the cellular landscape of normal intestinal mucosa, adenoma and CRC and to further select epithelium-specific clusters. Differentially expressed genes (DEGs) of epithelium-specific clusters were identified between intestinal lesion and normal mucosa in the scRNA-seq data throughout the adenoma-carcinoma sequence. Diagnostic biomarkers and prognostic biomarker (the risk score) for CRC were selected in the bulk RNA-seq dataset based on DEGs shared by the adenoma epithelium-specific cluster and the CRC epithelium-specific cluster (shared-DEGs). RESULTS: Among the 1063 shared-DEGs, we selected 38 gene expression biomarkers and 3 methylation biomarkers that had promising diagnostic power in plasma. Multivariate Cox regression identified  174 shared-DEGs as prognostic genes for CRC. We combined 1000 times LASSO-Cox regression and two-way stepwise regression to select 10 prognostic shared-DEGs to construct the risk score in the CRC meta-dataset. In the external validation dataset, the 1- and 5-year AUCs of the risk score were higher than those of stage, the pyroptosis-related genes (PRG) score and the cuproptosis-related genes (CRG) score. In addition, the risk score was closely associated with the immune infiltration of CRC. CONCLUSION: The combined analysis of the scRNA-seq dataset and the bulk RNA-seq dataset in this study provides reliable biomarkers for the diagnosis and prognosis of CRC.

A robust SERS calibration using a pseudo-internal intensity reference.

Surface-enhanced Raman scattering (SERS) with high molecular sensitivity and specificity is a powerful nondestructive analytical tool. Since its discovery, SERS measurements have suffered from the vulnerability of calibration curve, which makes quantification analysis a great challenge. In this work, we report a robust calibration method by introducing a referenced measurement as the intensity standard. This intensity reference not only has the advantages of the internal standard method such as reflecting the SERS substrate enhancement, but also avoids the introduction of competing adsorption between target molecules and the internal standard. Based on the normalized calibration curve, the magnitude of the R6G concentration can be well evaluated from 10-7 M to 10-12 M. Furthermore, we demonstrate that this pseudo-internal standard method can also work well using a different type of molecule as the reference. This SERS calibration method would be beneficial for the development of quantitative SERS analysis.

Independent and interactive effect of sedentary time and physical activity on risk of all-cause mortality: A prospective cohort study.

OBJECTIVES: Sedentary behavior (SB) and physical inactivity have been associated with an increased risk of all-cause mortality. Evidence in China is scarce, and it is unclear whether physical activity (PA) attenuates or even eliminates the harmful effects of prolonged SB in the Chinese population. METHODS: We conducted a prospective cohort study of 17 084 Chinese adults. PA and sitting time (ST) were assessed using the IPAQ. Cox proportional hazards models were used to estimate the risk of PA and ST with all-cause mortality. Interaction plots were used to visualize the interaction effects. RESULTS: During a median follow-up of 6.01 years, a total of 1106 deaths occurred. PA level was inversely associated with the incidence of all-cause mortality, while ST showed a detrimental association (all ptrend < 0.05). In the stratified analysis, ST was associated with all-cause mortality in the low PA, while the association was attenuated in the moderate PA group: the HRs (95% CI) comparing ST of 4-8, 8-11, and ≥11 to <4 h/day were 1.15 (0.73-1.81), 1.55 (0.92-2.59), and 2.70 (1.52-4.80), respectively. In the high PA group, no significant association was found across all ST levels. In the joint analysis, compared with the high PA and ST <4 h/day, the harmful effect was found only in the combined low PA and moderate PA groups with ST ≥11 h/day (HR:2.71, 95% CI:1.69-4.35). In addition, a significant interaction association was found. CONCLUSION: Our study, based on a prospective cohort, suggests that the detrimental effect of ST on all-cause mortality is attenuated or eliminated by high PA levels in the Chinese population.

Single-model multi-tasks deep learning network for recognition and quantitation of surface-enhanced Raman spectroscopy.

Surface-enhanced Raman scattering (SERS) spectroscopy analysis has long been the central task of nanoscience and nanotechnology to realize the ultrasensitive recognition/quantitation applications. Recently, the blooming of artificial intelligence algorithms provides an edge tool to revolutionize the spectroscopy analysis, especially for multiple substances analysis and large-scale data handling. In this study, a single-model multi-tasks deep learning network is proposed to simultaneously achieve the qualitative recognition and quantitative analysis of SERS spectroscopy. The SERS spectra of two kinds of hypoglycemic drugs (PHE, ROS) and the corresponding mixtures are collected, respectively, with the concentration grade from 10-4 M to 10-8 M. Based on the SERS spectroscopy dataset, the loss functions and hyperparameters of the multi-tasks classifications model are optimized, and the recognition accuracies are tested by simulation experiments. It is demonstrated that the accuracy rates of qualitative and quantitative analysis can reach up to 99.0% and 98.4%, respectively. Moreover, the practical feasibility of this multi-tasks model is demonstrated by using it to achieve qualitative and quantitative analysis of PHE and ROS in complex serum matrix. Overall, this single-model multi-tasks deep learning network shows significant potential for the recognition and quantitation of SERS spectroscopy, which provides the algorithmic and experimental basis for large-scale and multiple substances SERS spectra analysis.

Correlations between incident and emission polarization in nanowire-particle coupled junctions.

Plasmonic nanostructures with subwavelength confinement are of great importance for the development of integrated nanophotonic circuits and devices. Here, we experimentally investigate how the polarization of the emitted light from nanowire-particle junction relies on the incident polarization. We demonstrate that the correlations can be effectively modulated by the particle position relative to the wire. By varying the wire-particle gap with only several nanometers, the nanowire-particle junction can be changed from polarization maintainer to rotator. Then, by moving the particle along the wire within half of the surface plasmon polariton (SPP) beat, the polarization behaviors can be tuned from positive to negative correlation. The mechanism can be well understood by the hybridization of wire-particle coupled mode and propagating SPP modes, which is verified by finite-difference time-domain simulations. These findings would provide a new degree of freedom for manipulating light polarization at the nanometer scale and additional flexibility for constructing nanophotonic devices.

Molecular Subtypes Based on Cuproptosis-Related Genes and Tumor Microenvironment Infiltration Characterization in Colorectal Cancer.

Recent studies have demonstrated the biological significance of cuproptosis modification, a newly discovered programmed cell death, in tumor progression. Nonetheless, the potential role of cuproptosis-related genes (CRGs) in the immune landscape and tumor microenvironment (TME) formation of colorectal cancer (CRC) remains unknown. We comprehensively assessed cuproptosis modification patterns of 1339 CRC samples based on 27 CRGs and systematically analyzed the correlation of these patterns with TME. The CRG-score was constructed to quantify cuproptosis characteristics by LASSO and multivariate Cox regression methods, and its predictive capability was validated in an independent cohort. We identified three distinct cuproptosis modification patterns in CRC. The TME immune cell infiltration demonstrated immune heterogeneity among these three subtypes. Enrichment for multiple metabolism signatures was pronounced in cluster A. Cluster C was significantly correlated with the signaling pathways of immune activation-related, resulting in poor prognoses. Cluster B with mixed features possibly represents a transition phenotype or intratumoral heterogeneity. Then, based on constructed eight-gene CRG-score, we found that the signature could predict the disease-free survival of CRC patients, and the low CRG-score was related to increased neoantigen load, immunity activation, and microsatellite instability-high (MSI-H). Additionally, we observed significant correlations of the CRG-score with the cancer stem cell index and chemotherapeutic drug susceptibility. This study demonstrated that cuproptosis was correlated with tumor progression, prognosis, and TME. Our findings may improve the understanding of CRGs in TME infiltration characterization of CRC patients and contribute to guiding more effective clinical therapeutic strategies.

Evolution of the Colocasiomyia gigantea Species Group (Diptera: Drosophilidae): Phylogeny, Biogeography and Shift of Host Use.

The gigantea species group of the genus Colocasiomyia de Meijere (Diptera: Drosophilidae) is among the four aroid-breeding species groups in this genus; however, it differs from the remaining three groups in the host use: all the flies in this group use plants from the subfamily Monsteroideae instead of from the subfamily Aroideae. So far, we have not resolved the phylogenetic relationship within this group, making it difficult to trace its geographical origin, pattern of species diversification and history of host plant use. In this study, we reconstructed the phylogenetic relationships within the C. gigantea group using DNA sequences of eight (two mitochondrial and six nuclear) gene markers, and we inferred the ancestral areas and host plants of the group based on the resulting phylogeny. According to the results, the C. gigantea group may have diverged from its sister group (i.e., the C. cristata group) through vicariance between the northeastern Oriental region and Sundaland + Wallacea, and the subsequent diversification of the C. gigantea group occurred mostly in the northeastern Oriental region, although an Oriental-to-Sundaland dispersal was followed by vicariance between these two areas, which finally gave rise to the C. gigantea-C. scindapsae lineage in the latter area. We inferred the most likely ancestral host plant of the C. gigantea group to be of the genus Rhaphidophora Hassk, with possible subsequent shifts to Scindapsus Schott and/or Epipremnum Schott plants. We discuss the potential for the egg filaments in the C. gigantea group to be used as a model system for comparative studies in pollination mutualism and developmental genetics concerning tubulogenesis.

DNA methylation-based patterns for early diagnostic prediction and prognostic evaluation in colorectal cancer patients with high tumor mutation burden.

Background: Immune checkpoint inhibitor (ICI) therapy has proven to be a promising treatment for colorectal cancer (CRC). We aim to investigate the relationship between DNA methylation and tumor mutation burden (TMB) by integrating genomic and epigenetic profiles to precisely identify clinical benefit populations and to evaluate the effect of ICI therapy. Methods: A total of 536 CRC tissues from the Cancer Genome Atlas (TCGA) with mutation data were collected and subjected to calculate TMB. 80 CRC patients with high TMB and paired normal tissues were selected as training sets and developed the diagnostic and prognostic methylation models, respectively. In the validation set, the diagnostic model was validated in our in-house 47 CRC tissues and 122 CRC tissues from the Gene Expression Omnibus (GEO) datasets, respectively. And a total of 38 CRC tissues with high TMB from the COLONOMICS dataset verified the prognostic model. Results: A positive correlation between differential methylation positions and TMB level was observed in TCGA CRC cohort (r=0.45). The diagnostic score that consisted of methylation levels of four genes (ADHFE1, DOK6, GPR75, and MAP3K14-AS1) showed high diagnostic performance in the discovery (AUC=1.000) and two independent validation (AUC=0.946, AUC=0.857) datasets. Additionally, these four genes showed significant positive correlations with NK cells. The prognostic score containing three genes (POU3F3, SYN2, and TMEM178A) had significantly poorer survival in the high-risk TMB samples than those in the low-risk TMB samples (P=0.016). CRC patients with low-risk scores combined with TMB levels represent a favorable survival. Conclusions: By integrating analyses of methylation and mutation data, it is suggested that DNA methylation patterns combined with TMB serve as a novel potential biomarker for early screening in more high-TMB populations and for evaluating the prognostic effect of CRC patients with ICI therapy.

In Situ Microfluidic SERS Chip for Ultrasensitive Hg2+ Sensing Based on I--Functionalized Silver Aggregates.

Mercury(II) ions are causing serious environmental pollution and health damage. Developing a simple, rapid, and sensitive sensor for Hg2+ detection is of great significance. Herein, we demonstrate an I--functionalized surface-enhanced Raman scattering (SERS) substrate for rapid and sensitive Hg2+ sensing on a highly integrated microfluidic platform. Based on the combination reaction between I- and Hg2+, the Hg2+ sensing is achieved via the SERS intensity "turn-off" strategy, where HgI2 precipitation is formed on an SERS substrate interface, dissociating the Raman reporters that coadsorbed with I-. Owing to the strong binding constant between I- and Hg2+, our I--functionalized substrate demonstrates a very fast sensing response (∼150 s). Through reliable in situ SERS detection, a robust calibration curve between the "turn-off" signal and "lgC" is obtained in a broad concentration range of 10-9 to 10-13 M. Additionally, the detectable Hg2+ concentration can be as low as 1 fM. The good selectivity toward Hg2+ is also verified by testing about a dozen common metal ions in water, such as K+, Na+, Ca2+, Mg2+, and so forth. Furthermore, we apply the SERS sensor for real tap and lake water sample detection, and good recoveries of 113, 97, and 107% are obtained. With its advantages of high integration, simple preparation, fast response, high sensitivity, and reliability, the proposed I--functionalized SERS sensor microfluidic chip can be a promising platform for real-time and on-site Hg2+ detection in natural water.

Three-dimensional porous SERS powder for sensitive liquid and gas detections fabricated by engineering dense "hot spots" on silica aerogel.

A three-dimensional porous SERS powder material, Ag nanoparticles-engineered-silica aerogel, was developed. Utilizing an in situ chemical reduction strategy, Ag nanoparticles were densely assembled on porous aerogel structures, thus forming three-dimensional "hot spots" distribution with intrinsic large specific surface area and high porosity. These features can effectively enrich the analytes on the metal surface and provide huge near field enhancement. Highly sensitive and homogeneous SERS detections were achieved not only on the conventional liquid analytes but also on gas with the enhancement factor up to ∼108 and relative standard deviation as small as ∼13%. Robust calibration curves were obtained from the SERS data, which demonstrates the potential for the quantification analysis. Moreover, the powder shows extraordinary SERS stability than the conventional Ag nanostructures, which makes long term storage and convenient usage feasible. With all of these advantages, the porous SERS powder material can be extended to on-site SERS "nose" applications such as liquid and gas detections for chemical analysis, environmental monitoring, and anti-terrorism.

Fabrication of a Hierarchical Ni(OH)2 @Ni3 S2 /Ni Foam Electrode from a Prussian Blue Analogue-Based Composite with Enhanced Electrochemical Capacitive and Electrocatalytic Properties.

Developing high-efficiency, cost-effective, and durable electrodes is significant for electrochemical capacitors and electrocatalysis. Herein, a 3D bifunctional electrode consisting of nickel hydroxide nanosheets@nickel sulfide nanocubes arrays on Ni foam (Ni(OH)2 @Ni3 S2 /NF) obtained from a Prussian blue analogue-based precursor is reported. The 3D higher-order porous structure and synergistic effect of different compositions endow the electrode with large specific surface area, facile ion/electron transport path, and improved conductivity. As a result, the Ni(OH)2 @Ni3 S2 /NF electrode exhibits a high specific capacity of 211 mA h g-1 at a current density of 1 A g-1 and 73 % capacity retention after 5000 cycles at 5 A g-1 . Moreover, the Ni(OH)2 @Ni3 S2 /NF electrode has superior electrocatalytic activity for the hydrogen evolution reaction with low overpotentials of 140 and 210 mV at current densities of 10 and 100 mA cm-2 , respectively. The synthetic strategy for the unique higher-order porous structure can be extended to fabricate other composite materials for energy storage and conversion.

Controlling the Morphologies of Silver Aggregates by Laser-Induced Synthesis for Optimal SERS Detection.

Controlling the synthesis of metallic nanostructures for high quality surface-enhanced Raman scattering (SERS) materials has long been a central task of nanoscience and nanotechnology. In this work, silver aggregates with different surface morphologies were controllably synthesized on a glass-solution interface via a facile laser-induced reduction method. By correlating the surface morphologies with their SERS abilities, optimal parameters (laser power and irradiation time) for SERS aggregates synthesis were obtained. Importantly, the characteristics for largest near-field enhancement were identified, which are closely packed nanorice and flake structures with abundant surface roughness. These can generate numerous hot spots with huge enhancement in nanogaps and rough surface. These results provide an understanding of the correlation between morphologies and SERS performance, and could be helpful for developing optimal and applicable SERS materials.

Plasmonic polarization beam splitting based on single silver nanowire.

Plasmonic waveguides have been indispensable "building-blocks" to construct functional elements for future integrated nano-photonic devices and circuits. In this paper, we demonstrate that a thick silver nanowire with well-defined end facets can provide multiple outcoupling channels, and the controllable beam splitting is realized. The propagating surface plasmons emission at nanowire end are split into two parts: I1 and I2, with the polarizations nearly perpendicular to the respective emitting facets. By changing incident polarization, the splitting ratio (I1/I2) can be tuned in the range of 1.52~0.36. Electromagnetic simulations indicate that polarization beam splitting mechanisms in this single thick nanowire are the interference of propagating surface plasmon modes and the superposition of excited dipoles at the nanowire end. These findings would deepen the understanding of manipulation of surface plasmons propagation/emission, and advance the development of plasmonic waveguide-based nano-photonic devices.

Silver nano-needles: focused optical field induced solution synthesis and application in remote-excitation nanofocusing SERS.

Tapered metallic nanostructures that harbor surface plasmons are highly interesting for nanophotonic applications because of their waveguiding and field-focusing properties. Here, we developed a focused optical field induced solution synthesis for unique crystallized silver nano-needles. Under the focused laser spot, inhomogeneous Ag monomer concentration is created, which triggers the uniaxial growth of silver nanostructures along the radial direction with decreasing rate, forming nano-needle structures. These nano-needles are several micrometers long, with diameter attenuating from hundreds to tens of nanometers, and terminated by a sharp apex only a few nanometers in diameter. Moreover, nano-needles with atomically smooth surfaces show excellent performance for plasmonic waveguiding and unique near-field compression abilities. This nano-needle structure can be used for effective remote-excitation detection/sensing. We also demonstrate the assembling and picking up of nano-needles, which indicate potential applications in intracellular endoscopy, high resolution scanning tips, on-chip nanophotonic devices, etc.

In Situ Two-Step Photoreduced SERS Materials for On-Chip Single-Molecule Spectroscopy with High Reproducibility.

A method is developed to synthesize surface-enhanced Raman scattering (SERS) materials capable of single-molecule detection, integrated with a microfluidic system. Using a focused laser, silver nanoparticle aggregates as SERS monitors are fabricated in a microfluidic channel through photochemical reduction. After washing out the monitor, the aggregates are irradiated again by the same laser. This key step leads to full reduction of the residual reactants, which generates numerous small silver nanoparticles on the former nanoaggregates. Consequently, the enhancement ability of the SERS monitor is greatly boosted due to the emergence of new "hot spots." At the same time, the influence of the notorious "memory effect" in microfluidics is substantially suppressed due to the depletion of surface residues. Taking these advantages, two-step photoreduced SERS materials are able to detect different types of molecules with the concentration down to 10-13 m. Based on a well-accepted bianalyte approach, it is proved that the detection limit reaches the single-molecule level. From a practical point of view, the detection reproducibility at different probing concentrations is also investigated. It is found that the effective single-molecule SERS measurements can be raised up to ≈50%. This microfluidic SERS with high reproducibility and ultrasensitivity will find promising applications in on-chip single-molecule spectroscopy.