Enzyme-activatable charge transfer in gold nanoclusters.

Surface-protecting ligands, as a major component of metal nanoclusters (MNCs), can dominate molecular characteristics, performance behaviors, and biological properties of MNCs, which brings diversity and flexibility to the nanoclusters and largely promotes their applications in optics, electricity, magnetism, catalysis, biology, and other fields. We report herein the design of a new kind of water-soluble luminescent gold nanoclusters (AuNCs) for enzyme-activatable charge transfer (CT) based on the ligand engineering of AuNCs with 6-mercaptopurine ribonucleoside (MPR). This elaborately designed cluster, Au5(MPR)2, can form a stable intramolecular CT state after light excitation, and exhibits long-lived color-tunable phosphorescence. After the cleavage by purine nucleoside phosphorylase (PNP), the CT triplet state can be easily directed to a low-lying energy level, leading to a bathochromic shift of the emission band accompanied by weaker and shorter-lived luminescence. Remarkably, these ligand-engineered AuNCs show high affinity towards PNP as well as decent performance for analyzing and visualizing enzyme activity and related drugs. The work of this paper provides a good example for diversifying physicochemical properties and application scenarios of MNCs by rational ligand engineering, which will facilitate future interest and new strategies to precisely engineer solution-based nanocluster materials.

Unraveling a Concerted Proton-Coupled Electron Transfer Pathway in Atomically Precise Gold Nanoclusters.

Metal nanoclusters (MNCs) represent a promising class of materials for catalytic carbon dioxide and proton reduction as well as dihydrogen oxidation. In such reactions, multiple proton-coupled electron transfer (PCET) processes are typically involved, and the current understanding of PCET mechanisms in MNCs has primarily focused on the sequential transfer mode. However, a concerted transfer pathway, i.e., concerted electron-proton transfer (CEPT), despite its potential for a higher catalytic rate and lower reaction barrier, still lacks comprehensive elucidation. Herein, we introduce an experimental paradigm to test the feasibility of the CEPT process in MNCs, by employing Au18(SR)14 (SR denotes thiolate ligand), Au22(SR)18, and Au25(SR)18- as model clusters. Detailed investigations indicate that the photoinduced PCET reactions in the designed system proceed via an CEPT pathway. Furthermore, the rate constants of gold nanoclusters (AuNCs) have been found to be correlated with both the size of the cluster and the flexibility of the Au-S framework. This newly identified PCET behavior in AuNCs is prominently different from that observed in semiconductor quantum dots and plasmonic metal nanoparticles. Our findings are of crucial importance for unveiling the catalytic mechanisms of quantum-confined metal nanomaterials and for the future rational design of more efficient catalysts.

Reciprocal expression of MADS-box genes and DNA methylation reconfiguration initiate bisexual cones in spruce.

The naturally occurring bisexual cone of gymnosperms has long been considered a possible intermediate stage in the origin of flowers, but the mechanisms governing bisexual cone formation remain largely elusive. Here, we employed transcriptomic and DNA methylomic analyses, together with hormone measurement, to investigate the molecular mechanisms underlying bisexual cone development in the conifer Picea crassifolia. Our study reveals a "bisexual" expression profile in bisexual cones, especially in expression patterns of B-class, C-class and LEAFY genes, supporting the out of male model. GGM7 could be essential for initiating bisexual cones. DNA methylation reconfiguration in bisexual cones affects the expression of key genes in cone development, including PcDAL12, PcDAL10, PcNEEDLY, and PcHDG5. Auxin likely plays an important role in the development of female structures of bisexual cones. This study unveils the potential mechanisms responsible for bisexual cone formation in conifers and may shed light on the evolution of bisexuality.

6-Aza-2-Thiothymine-Capped Gold Nanoclusters as Robust Antimicrobial Nanoagents for Eradicating Multidrug-Resistant Escherichia coli Infection.

Multidrug-resistant bacterial infections, especially those caused by multidrug-resistant Escherichia coli (E. coli) bacteria, are an ever-growing threat because of the shrinking arsenal of efficacious antibiotics. Therefore, it is urgently needed to develop a kind of novel, long-term antibacterial agent effectively overcome resistant bacteria. Herein, we present a novel designed antibacterial agent-6-Aza-2-thiothymine-capped gold nanoclusters (ATT-AuNCs), which show excellent antibacterial activity against multidrug-resistant E. coli bacteria. The prepared AuNCs could permeabilize into the bacterial cell membrane via binding with a bivalent cation (e.g., Ca2+), followed by the generation of reactive oxygen species (e.g., •OH and •O2-), ultimately resulting in protein leakage from compromised cell membranes, inducing DNA damage and upregulating pro-oxidative genes intracellular. The AuNCs also speed up the wound healing process without noticeable hemolytic activity or cytotoxicity to erythrocytes and mammalian tissue. Altogether, the results indicate the great promise of ATT-AuNCs for treating multidrug-resistant E. coli bacterial infection.

Promoting the healing of methicillin-resistant Staphylococcus aureus-infected wound by a multi-target antimicrobial AIEgen of 6-Aza-2-thiothymine-decorated gold nanoclusters.

The use of conventional antibiotic therapies is in question owing to the emergence of drug-resistant pathogenic bacteria. Therefore, novel, highly efficient antibacterial agents to effectively overcome resistant bacteria are urgently needed. Accordingly, in this work, we described a novel class luminogen of 6-Aza-2-thiothymine-decorated gold nanoclusters (ATT-AuNCs) with aggregation-induced emission property that possessed potent antimicrobial activity against methicillin-resistant Staphylococcus aureus (MRSA). Scanning electron microscopy was performed to investigate the interactions between ATT-AuNCs and MRSA. In addition, ATT-AuNCs exhibited excellent ROS generation efficiency and could effectively ablate MRSA via their internalization to the cells. Finally, tandem mass tag-labeling proteome analysis was carried out to investigate the differential expression proteins in MRSA strains. The results suggested that ATT-AuNCs killed MRSA cells through altering the expression of multiple target proteins involved in DNA replication, aminoacyl-tRNA synthesis, peptidoglycan and arginine biosynthesis metabolism. Parallel reaction monitoring technique was further used for the validation of these proteome results. ATT-AuNCs could also be served as a wound-healing agent and accelerate the healing process. Overall, we proposed ATT-AuNCs could serve as a robust antimicrobial aggregation-induced emission luminogen (AIEgen) that shows the ability to alter the activities of multiple targets for the elimination of drug-resistant bacteria.

Multi-excitation wavelength of gold nanocluster-based fluorescence sensor array for sulfonamides discrimination.

Sulfonamides (SAs) are widely used in many fields because of their advantages, including low price, wide antibacterial spectrum, and high stability. However, their accumulation in the human body leads to a variety of serious diseases. Therefore, it is necessary to design a convenient, effective, and sensitive method to detect SAs. Moreover, the fluorescence excitation spectrum has rich information characteristics, especially for the interaction between fluorophore and quencher via various mechanisms. However, the excitation wavelength-guided sensor array construction does not draw proper attention. To address these issues, we used BSA-AuNCs as a single probe to construct a sensor array for the detection of five SAs. The selected SAs showed different quenching effects on the fluorescence intensities of BSA-AuNCs. The changes in the fluorescence intensity at different excitation wavelengths (λ = 230, 250, and 280 nm) have been applied to construct our sensor array and address the distinguishability between the selected SAs. With helping of pattern recognition methods, five different SAs have been identified at three different concentrations. Additionally, qualitative analysis at different moral ratios and quantitative analysis at nanogram concentrations have been considered. Moreover, the proposed sensor array was successfully used to distinguish between different SAs in commercial milk with an accuracy of 100 %. This study provides a simple and powerful approach to SAs detection. Also, it shows a broad application prospect in the field of food and drug monitoring.

Feature Selection Assists BLSTM for the Ultrasensitive Detection of Bioflavonoids in Different Biological Matrices Based on the 3D Fluorescence Spectra of Gold Nanoclusters.

Rapid and on-site qualitative and quantitative analysis of small molecules (including bioflavonoids) in biofluids are of great importance in biomedical applications. Herein, we have developed two deep learning models based on the 3D fluorescence spectra of gold nanoclusters as a single probe for rapid qualitative and quantitative analysis of eight bioflavonoids in serum. The results proved the efficiency and stability of the random forest-bidirectional long short-term memory (RF-BLSTM) model, which was used only with the most important features after deleting the unimportant features that might hinder the performance of the model in identifying the selected bioflavonoids in serum at very low concentrations. The optimized model achieves excellent overall accuracy (98-100%) in the qualitative analysis of the selected bioflavonoids. Next, the optimized model was transferred to quantify the selected bioflavonoids in serum at nanoscale concentrations. The transferred model achieved excellent accuracy, and the overall determination coefficient (R2) value range was 99-100%. Furthermore, the optimized model achieved excellent accuracies in other applications, including multiplex detection in serum and model applicability in urine. Also, LOD in serum at nanoscale concentration was considered. Therefore, this approach opens the window for qualitative and quantitative analysis of small molecules in biofluids at nanoscale concentrations, which may help in the rapid inclusion of sensor arrays in biomedical and other applications.

Highly Efficient Luminescence from Charge-Transfer Gold Nanoclusters Enabled by Lewis Acid.

Understanding the complicated intramolecular charge transfer (ICT) behaviors of nanomaterials is crucial to the development of high-quality nanoluminophores for various applications. However, the ICT process in molecule-like metal nanoclusters has been rarely explored. Herein, a proton binding-induced enhanced ICT state is discovered in 6-aza-2-thiothymine-protected gold nanoclusters (ATT-AuNCs). Such an excited-state electron transfer process gives rise to the weakened and red-shifted photoluminescence of these nanoclusters. By the joint use of this newfound ICT mechanism and a restriction of intramolecular motion (RIM) strategy, a red shift in the emission maxima of 30 nm with 27.5-fold higher fluorescence quantum efficiency is achieved after introducing rare-earth scandium ion (Sc3+) into ATT-AuNCs. Furthermore, it is found that upon the addition of Sc3+, the photoinduced electron transfer (PET) rate from ATT-AuNCs to minocycline is largely accelerated by forming a donor-bridge-acceptor structure. This paper offers a simple method to modulate the luminescent properties of metal nanoclusters for the rational design of next-generation sensing platforms.

Machine learning-based sensor array: full and reduced fluorescence data for versatile analyte detection based on gold nanocluster as a single probe.

Different acquisition data approaches have been used to fetch the fluorescence spectra. However, the comparison between them is rare. Also, the extendability of a sensor array, which can work with heavy metal ions and other types of analytes, is scarce. In this study, we used first- and second-order fluorescent data generated by 6-Aza-2-thiothymine-gold nanocluster (ATT-AuNCs) as a single probe along with machine learning to distinguish between a group of heavy metal ions. Moreover, the dimensionality reduction was carried out for the different acquisition data approaches. In our case, the accuracy of different machine learning algorithms using first-order data outperforms the second-order data before and after the dimensionality reduction. For proving the extendibility of this approach, four anions were used as an example. As expected, the same finding has been found. Furthermore, random forest (RF) showed more stable and accurate results than other models. Also, linear discriminant analysis (LDA) gave acceptable accuracy in the analysis of the high-dimensionality data. Accordingly, using LDA in high-dimensionality data (the first- and second-order data) analysis was highlighted for discrimination between the selected heavy metal ions in different concentrations and in different molar ratios, as well as in real samples. Also, the same method was applied for the anion's discrimination, and LDA gave an excellent separation ability. Moreover, LDA was able to differentiate between all the selected analytes with excellent separation ability. Additionally, the quantitative detection was considered using a wide concentration range of Cd2+, and the LOD was 60.40 nM. Therefore, we believe that our approach opens new avenues for linking analytical chemistry, especially sensor array chemistry, with machine learning.

A Comprehensive Evolutionary Study of Chloroplast RNA Editing in Gymnosperms: A Novel Type of G-to-A RNA Editing Is Common in Gymnosperms.

Although more than 9100 plant plastomes have been sequenced, RNA editing sites of the whole plastome have been experimentally verified in only approximately 21 species, which seriously hampers the comprehensive evolutionary study of chloroplast RNA editing. We investigated the evolutionary pattern of chloroplast RNA editing sites in 19 species from all 13 families of gymnosperms based on a combination of genomic and transcriptomic data. We found that the chloroplast C-to-U RNA editing sites of gymnosperms shared many common characteristics with those of other land plants, but also exhibited many unique characteristics. In contrast to that noted in angiosperms, the density of RNA editing sites in ndh genes was not the highest in the sampled gymnosperms, and both loss and gain events at editing sites occurred frequently during the evolution of gymnosperms. In addition, GC content and plastomic size were positively correlated with the number of chloroplast RNA editing sites in gymnosperms, suggesting that the increase in GC content could provide more materials for RNA editing and facilitate the evolution of RNA editing in land plants or vice versa. Interestingly, novel G-to-A RNA editing events were commonly found in all sampled gymnosperm species, and G-to-A RNA editing exhibits many different characteristics from C-to-U RNA editing in gymnosperms. This study revealed a comprehensive evolutionary scenario for chloroplast RNA editing sites in gymnosperms, and reported that a novel type of G-to-A RNA editing is prevalent in gymnosperms.

Deep Learning-Based Sensor Array: 3D Fluorescence Spectra of Gold Nanoclusters for Qualitative and Quantitative Analysis of Vitamin B6 Derivatives.

Vitamin B6 derivatives (VB6Ds) are of great importance for all living organisms to complete their physiological processes. However, their excess in the body can cause serious problems. What is more, the qualitative and quantitative analysis of different VB6Ds may present significant challenges due to the high similarity of their chemical structures. Also, the transfer of deep learning model from one task to a similar task needs to be present more in the fluorescence-based biosensor. Therefore, to address these problems, two deep learning models based on the intrinsic fingerprint of 3D fluorescence spectra have been developed to identify five VB6Ds. The accuracy ranges of a deep neural network (DNN) and a convolutional neural network (CNN) were 94.44-97.77% and 97.77-100%, respectively. After that, the developed models were transferred for quantitative analysis of the selected VB6Ds at a broad concentration range (1-100 µM). The determination coefficient (R2) values of the test set for DNN and CNN were 93.28 and 97.01%, respectively, which also represents the outperformance of CNN over DNN. Therefore, our approach opens new avenues for qualitative and quantitative sensing of small molecules, which will enrich fields related to deep learning, analytical chemistry, and especially sensor array chemistry.

Gold Nanocluster-Based Fluorometric Banoxantrone Assay Enabled by Photoinduced Electron Transfer.

Monitoring the blood concentration of banoxantrone (AQ4N) is important to evaluate the therapeutic efficacy and side effects of this new anticancer prodrug during its clinical applications. Herein, we report a fluorescence method for AQ4N detection through the modulation of the molecule-like photoinduced electron transfer (PET) behavior of gold nanoclusters (AuNCs). AQ4N can electrostatically bind to the surface of carboxylated chitosan (CC) and dithiothreitol (DTT) co-stabilized AuNCs and quench their fluorescence via a Coulomb interaction-accelerated PET process. Under optimized experimental conditions, the linear range of AQ4N is from 25 to 200 nM and the limit of detection is as low as 5 nM. In addition, this assay is confirmed to be reliable based on its successful use in AQ4N determination in mouse plasma samples. This work offers an effective strategy for AQ4N sensing based on fluorescent AuNCs and widens the application of AuNCs in clinical diagnosis and pharmaceutical analysis.

Antenna effect of pyridoxal phosphate on the fluorescence of mitoxantrone-silicon nanoparticles and its application in alkaline phosphatase assay.

As a kind of sensing and imaging fluorescent probe with the merit of low toxicity, good stability, and environment-friendly, silicon nanoparticles (SiNPs) are currently attracting extensive research. In this work, we obtained mitoxantrone-SiNPs (MXT-SiNPs) with green emission by one-pot synthesis under mild temperature condition. The antenna based on pyridoxal phosphate (PLP) was designed for light-harvesting to enhance the luminescence of MXT-SiNPs and to establish a novel sensing strategy for alkaline phosphatase (ALP). PLP transfers the absorbed photon energy to MXT-SiNPs by forming Schiff base. When PLP is dephosphorized by ALP, the released free hydroxyl group reacts with aldehyde group to form internal hemiacetal, which leads to the failure of Schiff base formation. Based on the relationship between antenna formation ability and PLP hydrolysis degree, the activity of ALP can be measured. A good linear relationship was obtained from 0.2 to 3.0 U/L, with a limit of detection of 0.06 U/L. Furthermore, the sensing platform was successfully used to detect ALP in human serum with recovery of 97.6-106.2%. The rational design of antenna elements for fluorescent nanomaterials can not only provide a new pathway to manipulate the luminescence, but also provide a new direction for fluorescence sensing strategy.

Immunofluorescent-aggregation assay based on anti-Salmonella typhimurium IgG-AuNCs, for rapid detection of Salmonella typhimurium.

Sensitive and rapid detection of pathogenic bacteria plays an important role in avoiding food poisoning. However, the practical application value of conventional assays for detection of foodborne bacteria, are limited by major drawbacks; these include the laboriousness of pure culture preparation, complexity of DNA extraction for polymerase chain reaction, and low sensitivity of enzyme-linked immunosorbent assay. Herein, we designed a non-complex strategy for the sensitive, quantitative, and rapid detection of Salmonella typhimurium with high specificity, using an anti-Salmonella typhimurium IgG-AuNC-based immunofluorescent-aggregation assay. Salmonella typhimurium was agglutinated with fluorescent anti-Salmonella typhimurium IgG-AuNC on a glass slide, and observed using a fluorescence microscope with photoexcitation and photoemission at 560 nm and 620 nm, respectively. Under optimized reaction conditions, the AuNC-based immunofluorescent-aggregation assay had a determination range between 7.0 × 103 and 3.0 × 108 CFU/mL, a limit of detection of 1.0 × 103 CFU/mL and an assay response time of 3 min. The technique delivered good results in assessing real samples.

Bell-Shaped Electron Transfer Kinetics in Gold Nanoclusters.

Although metal nanoclusters (MNCs) have shown great promise for the further development of photochemical techniques to be applied in diverse areas (e.g., photoelectronic devices, photochemical sensors, photocatalysts, and energy storage and conversion systems), the fundamental problem of their electron transfer behavior still remains unsolved. Herein, a driving force-dependent photoinduced electron transfer process of gold nanoclusters (AuNCs) is clarified for the first time from a rational-designed opposite-charged system. It was found that the electron transfer dynamic of carboxylated chitosan and dithiothreitol-commodified AuNCs (CC/DTT-AuNCs) can be satisfactorily described by the Marcus electron transfer theory. This proved model was applied to estimate the ultrafast charge separation process between CC/DTT-AuNCs and mitoxantrone, which was confirmed by fluorescence quenching and femtosecond transient absorption spectroscopy measurements. We envision that this work will open a new door for understanding the electron transfer behavior of MNCs and facilitate the design of advanced optoelectronic devices.

Detection of tetanus toxoid with fluorescent tetanus human IgG-AuNC-based immunochromatography test strip.

Assays for detecting tetanus toxoid are of great significance to be applied in the research of the safety testing of tetanus vaccine. Currently, guinea pigs or mice are usually used to evaluate the toxicity in these assays. Herein, a facile and quick biomineralization process was carried out to generate tetanus human immunoglobulin G (Tet-IgG)-functionalized Au nanoclusters (Tet-IgG-AuNCs). The obtained Tet-IgG-AuNCs exhibited strong red emission with a photoluminescence quantum yield of 13%. Based on surface plasmon resonance measurements, the apparent dissociation constant of the Tet-IgG-AuNC-tetanus toxoid complexes was measured to be 2.27 × 10-8 M. A facile detection approach was developed using a fluorescent Tet-IgG-AuNC-based immunochromatography test strip. By utilizing the high-brightness fluorescent Tet-IgG-AuNCs, this immunosensor showed favorable sensitivity with a detection limit at the level of 0.03 µg/mL. Further results demonstrated that this assay can reliably detect tetanus toxoid and therefore might provide a novel method to replace animal tests for the quantification of tetanus toxicity. Moreover, the antibody-AuNC-based immunochromatography test strip platform serves as a promising candidate to develop new approaches for detecting targeted antigens and biological events of interest.

Rare-Earth Eu3+/Gold Nanocluster Ensemble-Based Fluorescent Photoinduced Electron Transfer Sensor for Biomarker Dipicolinic Acid Detection.

The use of metal ions to bridge the fluorescent materials to target analytes has been demonstrated to be a promising way to sensor design. Herein, the effect of rare-earth ions on the fluorescence of l-methionine-stabilized gold nanoclusters (Met-AuNCs) was investigated. It was found that europium (Eu3+) can significantly suppress the emission of Met-AuNCs, while other rare-earth ions showed a negligible impact. The mechanism on the observed fluorescence quenching of Met-AuNCs triggered by Eu3+ was systematically explored, with results revealing the dominant role of photoinduced electron transfer (PET). Eu3+ can bind to the surface of Met-AuNCs by the coordination effect and accepts the electron from the excited Met-AuNCs, which results in Met-AuNC fluorescence suppression. After introducing dipicolinic acid (DPA), an excellent biomarker for spore-forming pathogens, Eu3+ was removed from the surface of Met-AuNCs owing to the higher binding affinity between Eu3+ and DPA. Consequently, an immediate fluorescence recovery occurred when DPA was present in the system. Based on the Met-AuNC/Eu3+ ensemble, we then established a simple and sensitive fluorescence strategy for turn-on determination of biomarker DPA, with a linear range of 0.2-4 µM and a low limit of detection of 110 nM. The feasibility of the proposed method was further validated by the quantitative detection of DPA in the soil samples. We believe that this study would significantly facilitate the construction of metal-ion-mediated PET sensors for the measurement of various interested analytes by applying fluorescent AuNCs as detection probes.

Single gold nanocluster probe-based fluorescent sensor array for heavy metal ion discrimination.

There is a continuing high demand to design effective sensors for the determination of heavy metal ions (HMIs) since they are hazardous to both human health and the environment. In this study, we reported a facile fluorescent sensor array for rapid discrimination of HMIs based on a single gold nanocluster (AuNC) probe. This AuNC probe was prepared by using 2-mercapto-1-methylimidazole (MMI) as a ligand and polyvinypyrrolidone (PVP) as a dispersing agent. The fluorescence emission of PVP/MMI-AuNC was observed to be closely related to the pH value of the aqueous solution, which displays yellow (λmax = 512 nm) and red (λmax = 700 nm) fluorescence at pH 12.0 and 6.0, respectively. Further experiments indicated that different HMIs can produce differential effects on the photoluminescence of PVP/MMI-AuNC and thus generate distinct fluorescent responses at 512 and 700 nm. On the basis of this phenomenon, a fluorescent sensor array based on the PVP/MMI-AuNC was then built by simply changing pH value in the sensor element. A total of seven HMIs had their unique response patterns and were successfully distinguished by hierarchical cluster analysis and linear discriminant analysis both in buffer solution and spiked water samples, achieving 100% identification accuracy. This study provides a simple and powerful fingerprinting sensing platform for multiple HMIs, showing broad application prospects in the field of environmental monitoring.

Solid-state thiolate-stabilized copper nanoclusters with ultrahigh photoluminescence quantum yield for white light-emitting devices.

As a new emerging candidate for solid-state phosphors, copper nanoclusters (CuNCs) have gained tremendous interest in the field of white light-emitting devices (WLEDs). However, their further applications are impeded by the low photoluminescence quantum yield (PLQY) and poor emission color tunability of CuNCs. This work demonstrates the synthesis of cyan and orange emitting CuNCs, and their combination as color conversion phosphors in WLEDs. The cyan and orange emitting CuNCs were prepared employing 2-mercapto-1-methylimidazole (MMI) and N-acetyl-l-cysteine (NAC), respectively, as stabilizing-cum-reducing agents. The dispersions of MMI-CuNCs and NAC-CuNCs are weakly emissive. However, after processing into powders, they both possess ultrahigh PLQYs (45.2% for MMI-CuNCs, and 64.6% for NAC-CuNCs) owing to the effect of aggregation-induced emission (AIE). All-CuNC based WLEDs are then designed and developed using powdered MMI-CuNC and NAC-CuNC samples on commercially available 365 nm GaN LED chips. They display acceptable white light characteristics with a Commission Internationale de l'Eclairage coordinate value and color rendering index of (0.26, 0.30) and 83, respectively. We believe that these cost-effective and eco-friendly CuNCs with interesting AIE properties will vigorously promote the development of high-quality WLEDs for commercial applications.

Gold nanoclusters/graphene quantum dots complex-based dual-emitting ratiometric fluorescence probe for the determination of glucose.

Herein, we report the design of a single-excitation/double-emission ratiometric fluorescence nanosensor for the determination of glucose. The sensing system combines glucose oxidation catalyzed by glucose oxidase, Fenton chemistry, Fe3+-sensitive fluorescent gold nanoclusters (AuNCs), and Fe3+-inert fluorescent graphene quantum dots (GQDs). We used orange-fluorescent AuNCs co-modified with bovine serum albumin and 3-mercaptopropionic acid as the indicator probe, and GQDs with the same excitation wavelength as the BSA/MPA-AuNCs, but with different emission wavelength, as the reference probe. The fluorescence intensity-ratio between 420 nm and 575 nm (F420/F575) was used to quantitatively determine glucose with a low detection limit of 0.18 µM, and the nanosensor was successfully used to detect glucose in human serum. This ratiometric fluorescence sensing system, based on AuNCs and GQDs, ensures sensitive and convenient determination of glucose, and has broad application prospects for biomedical-analysis applications.