Development of dual quantum dots-based fluorescence-linked immunosorbent assay for simultaneous detection on inflammation biomarkers

Development of dual quantum dots-based fluorescence-linked immunosorbent assay for simultaneous detection on inflammation biomarkers

Sensors & Actuators: B. Chemical 301 (2019) 127118 Contents lists available at ScienceDirect Sensors and Actuators B: Chemical journal homepage: www...

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Sensors & Actuators: B. Chemical 301 (2019) 127118

Contents lists available at ScienceDirect

Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb

Development of dual quantum dots-based fluorescence-linked immunosorbent assay for simultaneous detection on inflammation biomarkers ⁎

T



Yanbing Lva, Fangfang Wangb, Ning Lib, Ruili Wub, , Jinjie Lib, Huaibin Shenb, Lin Song Lib, , ⁎ Fang Guoa, a b

School of Chemistry, Liaoning University, Shenyang, 110036, China Key Lab for Special Functional Materials of Ministry of Education, School of Materials Science and Engineering, Henan University, Kaifeng, 475004, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Quantum dots Quantum dot-based fluorescence-linked immunosorbent assay Simultaneous detection Inflammation biomarkers

Simultaneous detections of different but clinically relevant biomarkers are of extremely importance in biomedicine. Due to their unique photophysical properties, quantum dots (QDs) are ideally suited for highly sensitive multiplexed determination. Herein, a dual quantum dots-based fluorescence-linked immunosorbent assay (dQDs-FLISA) for simultaneous and quantitative detection of inflammation biomarkers (i.e. serum amyloid A (SAA) and C-reactive protein (CRP)) has been established. After being coated by amphiphilic oligomers (polymaleic acid n-hexadecanol ester, PMAH), the red-QD and green-QD with high quantum yields were used as fluorescence probes to couple SAA and CRP antibodies, respectively. Cross-reactivity among the SAA and CRP’s antibodies and antigens have been carefully examined by interference experiments, and it was successfully avoided by the specific probe adding sequence. Therefore, the assay provided a broad linear analytical range, including SAA quantitative range of 10–1,000 ng mL−1 with linear correlation (R2) of 0.992, and CRP quantitative range of 10–1,000 ng mL−1 with R2 of 0.998. The limit of detections (LODs) for SAA and CRP using dQDsFLISA were 2.39 ng mL−1 and 6.37 ng mL−1, respectively. The accuracy of the assay has been confirmed with recoveries of 92.13%–101.85%. More importantly, the assay results showed good specificity, the QD-antibody probe could couple corresponding antigen (CRP or SAA) high-efficiently and it could be out of interference of other antigens and substances in serum. Given its good performance, the proposed dQDs-FLISA method offers great potential for simultaneous and quantitative detection of other biomarkers in in vitro diagnostic (IVD).

1. Introduction Accurate and sensitive detection has an increasing demand in biomedicine, especially, for various biomolecules (including biomarkers, aptamer, and proteins) recently [1–3]. Among them, how to efficiently apply biomarkers into quantitative assay is of great significance in clinical diagnosis [4]. To date, many immunoassay methods have been developed, including enzyme-linked immunosorbent assay (ELISA) [5,6], chemiluminescence immunoassay [7,8], fluorescence immunoassay [9,10], lateral flow test strip [11,12], electrochemistry [13,14], and surface plasmon resonance [15,16], etc. Even though with high sensitivity, broad detection range, and high-throughput, most of these methods have only been used to detect one kind of biomarker independently, i.e. one reaction unit responses for one type of biomarker only [17,18]. These one-biomarker based methods have already



been used in clinical diagnostic practically, but it can barely meet the clinical basic demand. The use of one single biomarker as indicator is not always precise for clinical diagnosis because it is not completely sensitive and specific. Thus, the use of different but clinically relevant multiple biomarkers can increase the accuracy of diagnosis for many diseases [19,20]. In some case, certain disease may have different “window periods”, such as acute myocardial injury (AMI) may have several different indexes related to certain incidence cycle [21]. The use of multiple biomarkers is a “must-have” approach to diagnose pathogenesis stages promptly, which is also extremely important to guide further treatment or therapy. The development of simultaneous multiplexed assays may challenge, but this will deliver promising accuracy and lead us toward extensive applications in biomedical diagnosis [22]. With promising photophysical and photochemical properties, semiconductor quantum dots (QDs) have been widely used in

Corresponding authors. E-mail addresses: [email protected] (R. Wu), [email protected] (L.S. Li), [email protected] (F. Guo).

https://doi.org/10.1016/j.snb.2019.127118 Received 18 July 2019; Received in revised form 5 September 2019; Accepted 9 September 2019 Available online 11 September 2019 0925-4005/ © 2019 Elsevier B.V. All rights reserved.

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single well of the microplate. Then, target antigens in serum sample were added in the well and they could be captured. After adding redQD-SAA antibody and green-QD-CRP antibody in turn, both inflammation biomarkers (CRP and SAA) have been captured in the well due to the antibody-antigen-antibody sandwich structure. The concentration difference of two biomarkers can be detected respectively according to the changes of photoluminescence (PL) intensity of labeled red-QD and green-QD. Most importantly, this method can indeed provide accurate analysis for both biomarkers in a sample well simultaneously.

biosensors [23], cancer cell targeting [24], photoelectrochemical sensors [25], in vivo imaging [26,27], and in vitro diagnostic (IVD) [28]. In particular, QDs have a huge potential to be used as ideal fluorescence probe for highly sensitive, simultaneous, and multiplexed assay because one excitation band can excite many kinds of QDs with different emissions [29]. Recently, QD-based fluorescence immunoassay to detect various biomarkers [30], proteins [31], small molecules [32], and antibiotic residues [33] have been reported. A qualitative detection of β-human chorionic gonadotrophin (β-HCG) and α-fetal protein (AFP) in the microporous nylon membrane using red-QD and green-QD has been reported by our group before [34]. In addition, we also used a quantum dot-based lateral flow immunoassay system (QD-LFIAS) to simultaneously detect both influenza A virus subtypes H5 and H9 [35]. However, these methods can only achieve qualitative simultaneous detection, and the reproducibility needs to be further improved. Mattoussi et al. first brought the concept to achieve multiplexed toxin analysis from a single sample in a single well with four colors of QDs [36]. Subsequently, simultaneous detections in a single well for series of toxins with multi-color of QD-based competition methods have been reported [37–39]. To promote the development of IVD, it has an urgent demand to have a dual or multi-QDs based accurate quantitative method for simultaneously detection of multiple biomarkers. The trend of development in biomedicine is the possibility to detect a single sample at extremely low concentration and volume in simultaneous and multiplexed assays [40,41]. Semiconductor QDs can answer this requirement by realizing the simultaneous detection of different biomarkers. In this paper, we want to demonstrate a dual quantum dots-based fluorescence-linked immunosorbent assay (dQDsFLISA) method. Inflammation biomarkers are generally as important indicator in many diseases, for example, the low level of C-reactive protein (CRP) can predict pathogenesis of cardiovascular events [42–44], and serum amyloid A (SAA) increases sharply in the early stages of acute bacterial infection [45–47], etc. Rapid and accurate assays of various inflammation biomarkers are crucial to the clinical estimate of bacterial and viral infection, which thereby can reduce the abuse of antibiotics [48,49]. Therefore, a method to simultaneously detect different inflammation biomarkers (such as CRP and SAA) is of great significance, it will be conducive to a more accurate clinical diagnosis. A schematic representation of the dQDs-FLISA method is presented in Scheme 1. First, the coating antibodies were bounded on a

2. Experimental section 2.1. Reagents and instruments The details for reagents and instruments and the other preparation processes were shown in supplementary information.

2.2. Fabrication of dQDs-FLISA The SAA and CRP monoclonal antibodies were diluted in 50 mM carbonate-bicarbonate buffer (pH 9.6) with the concentration ratio of 1:1. Subsequently, the mixture was immobilized on a standard 96-well microplate in 100 μL per well and incubated for 24 h at 4 °C. To remove excess coating antibodies, the microplate was washed three times by washing buffer (10 mM PBS containing 0.05% Tween-20, PBST). The excess binding sites were blocked with BSA (0.5 wt%) in 10 mM PBS (pH = 7.4) by incubating overnight at 4 °C. The microplate was dried in a constant temperature and humidity chamber for 24 h, and then stored at 4 °C until use. Subsequently, the different concentrations of mixture CRP and SAA antigens (10-1,000 ng mL−1) were captured by the antibodies immobilized on the microplate, respectively. The red-QD-SAA antibody and green-QD-CRP antibody probes were then added separately and incubating in turn for 30 min at 37 °C. Finally, the PL intensity for both emission peaks on the microplate increased gradually with the increase of antigen’s concentration, which could be read by using the SpectraMax i3 Multi-Mode microplate reader (Scheme 1).

Scheme 1. A schematic illustration of dQDs-FLISA procedure. 2

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Fig. 1. TEM images of the hydrophobic CdSe/ZnS QDs (red-QD, PL = 613 nm) and ZnCdSeS/ZnS QDs (green-QD, PL = 511 nm) in n-hexane (a) (c) and corresponding aqueous QDs in water (b) (d). Inset: size distribution data.

3. Results and discussion

were completely transferred from the organic phase to the aqueous phase, and both hydrophobic QDs and aqueous QDs were clear and transparent. The red-QD could show narrower full width at half maximum (FWHM) of 37 nm (Fig. 2(a)), and there was no change in PL peak shape and peak position of red-QD after it was transferred into aqueous solution. Besides, comparing with hydrophobic QDs, the PL intensity of aqueous red-QD just slightly decreased. However, there were some centrifugal loss for the preparation of aqueous green-QD due to its small size. In Fig. 2(b), the aqueous green-QD still kept high PL QY, which basically met the needs of follow-up experiment. In addition, the FWHM of green-QD was 24 nm, and the PL peak position was unchanged from the PL spectra of the hydrophobic QDs and the aqueous QDs. The above results indicate that the aqueous red-QD and green-QD have been successfully prepared, which is ready for the further biological application. In order to demonstrate the stability of the aqueous QDs, the changes of PL intensities in different physiological environmental conditions were carefully tracked (Fig. 3). As shown in Fig. 3(a), the PL intensity of red-QD in acidic-to-alkaline pH environments kept good stability at a range of pH 3–12 (PL intensity > 80%). However, the PL intensity of green-QD was weaker than that of red-QD. The overall PL

3.1. Characterization of QDs and aqueous QDs According to the strategy developed by our group, the hydrophobic ZnCdSeS/ZnS QDs (green-QD, PL = 511 nm) and CdSe/ZnS QDs (redQD, PL = 613 nm) were synthesized first. This high-quality red-QD and green-QD showed high photoluminescent quantum yield (PL QY) of 92% and 86%, respectively. Then, the corresponding aqueous QDs with good biocompatibility were prepared by coating with amphiphilic oligomers (PMAH). The red-QD presented monodisperse in n-hexane, which appeared dispersion with an average size of 13.1 ± 1.5 nm (the size distribution was calculated by statistics of 100 dots) in Fig. 1(a). After coating PMAH, an average size of the aqueous red-QD increased to 14.7 ± 1.6 nm, and the PL QY still maintained almost the same. As shown in Fig. 1(c), the typical transmission electron microscopy (TEM) image of high-quality hydrophobic green-QD was collected, and the mean diameter of green-QD was 10.0 ± 1.5 nm with highly monodisperse. And the size of aqueous green-QD increased to 10.9 ± 1.3 nm after coating amphiphilic polymer (PMAH). The Fig. 2 clearly showed that hydrophobic red-QD and green-QD 3

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Fig. 2. Photoluminescence spectra of hydrophobic CdSe/ZnS QDs (solid line) and corresponding aqueous QDs (dot line) (a), inset: photographs of hydrophobic CdSe/ZnS QDs (right) and corresponding aqueous QDs (left) (upper phase is H2O; bottom phase is CHCl3) under room light (upper) and 365 nm ultraviolet light (under). Photoluminescence spectra of hydrophobic ZnCdSeS/ZnS QDs (solid line) and corresponding aqueous QDs (dot line) (b), inset: photographs of hydrophobic ZnCdSeS/ ZnS QDs (right) and corresponding aqueous QDs (left) (upper phase is H2O; bottom phase is CHCl3) under room light (upper) and 365 nm ultraviolet light (under).

3.2. Characterization of QD-antibody

intensities were stable between pH = 2 and pH = 13. The result from thermal stability test was shown in Fig. 3(b), the PL intensity decreased with the increase of temperature, and it could still keep 63.1% (red-QD) and 47.5% (green-QD) of the original PL intensity when the aqueous QDs were heated to 100 °C. Although, the PL intensity of green-QD occurred a larger decline at high temperature, the PL intensity also recovered when the temperature was restored to 25 °C. The photostability test was carried out by illuminating the QD solution with a 365 nm ultraviolet lamp. As shown in Fig. 3(c), the PL intensity of redQD and green-QD still remained 60% after 7 days of continuous illumination. The Fig. 3(d) showed that the PL intensity of red-QD kept 72.8% and green-QD kept 52.3% in 60 °C storage for seven days. The above results prove that both red-QD and green-QD have relatively good photostability and thermal stability in harsh conditions, which can meet the requirements for accurate quantitative and simultaneous detection of multiple biomarkers.

In this assay, the red-QD conjugated SAA antibody and green-QD conjugated CRP antibody were prepared, and then the PL spectra, dynamic light scattering (DLS) and zeta potential of QDs and QD-antibody were characterized in Fig. 4. As shown in Fig. 4(a), the PL spectra redQD-SAA showed that the PL peaks kept symmetrical and had almost no changed on peak position and peak shape, and the PL intensity maintained above 83% of the red-QD PL intensity after coupling SAA antibody. Both red-QD and red-QD-SAA had a narrow and uniform size distribution (Fig. 4(b)), and the hydrodynamic size of QDs increased from 47.8 to 78.1 nm after the conjugation with SAA antibody. In Fig. 4(c), the zeta potential of red-QD changed from -48.5 to -34.2 mV before and after coupling SAA antibody, which still located the stable range for stabilized colloids (> +30 mV or < −30 mV). Besides, the PL intensity of green-QD-CRP kept 70% PL intensity of green-QD-CRP kept 70% of that of the green-QD in Fig. 3(d), due to the centrifuge

Fig. 3. The pH stability (a), thermal stability (b), and photostability (c) of red-QD and green-QD, the PL intensity of red-QD and green-QD versus storage time in 60 °C (d). 4

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Fig. 4. Photoluminescence spectra (a), dynamic light scattering (b), zeta potential (c) of the aqueous red-QD (solid line) and QD-SAA antibody (dash line). Photoluminescence spectra (d), dynamic light scattering (e), zeta potential (f) of the aqueous green-QD (soild line) and QD-CRP antibody (dash line).

green-QD-CRP antibody probe had basically not affected the result, and the PL intensity increased with the increase of CRP antigen concentration. However, the combination of SAA antigen-antibody system was influenced greatly by different adding sequence of red-QD-SAA antibody probe. As shown in Fig. 5(b), the SAA antigen could be combined better to SAA antibody only when the red-QD-SAA antibody probe was preferentially added into the mixture of SAA and CRP antigens. It was supposed that the specific binding capacity of CRP antigenantibody was stronger than of SAA system, so the SAA antibody-antigen-antibody need to be preferentially combined by firstly adding redQD-SAA antibody. In this assay, the adding sequence of probe was adopted with first adding red-QD-SAA antibody and then adding greenQD-CRP antibody.

separation of the coupling process. Whereafter, the hydrodynamic size of the aqueous green-QD was increased from 45.6 nm to 74.5 nm after coupling CRP antibody in Fig. 4(e). As shown in Fig. 4(f), the zeta potential of green-QD showed a surface charge of -48.2 mV, suggesting both green-QD and green-QD-CRP antibodies were stabilized colloids (zeta potential under −30 mV). Besides, Fourier transform infrared (FTIR) spectroscopy was applied to validate the coupling results in Fig. S1. Take the red-QD coupled SAA antibody as an example, the appearance of the 1552 cm−1 was attributed to the new formation of amido bond (C-N-H flexural vibration) of red-QD-SAA antibody. A bond at 1079 cm−1 for red-QD-SAA antibody was affirmed to the C − N stretching vibration mode. This result indicated that an amido bond was formed after the reaction of carboxyl group on aqueous red-QDs and amino group on antibody. In a word, the QD-antibodies had been successfully prepared, which would be used as fluorescent probes for quantitative detection of CRP and SAA biomarkers.

3.5. Interference experiment of dQDs-FLISA In order to verify whether there was interference between the SAA and CRP systems, the following experiment was conducted under the above optimized experimental conditions and operating sequence. In assay for CRP, a series of concentration of CRP antigens (10–1,000 ng mL−1) were tested at the concentrations of 0, 50, 200, and 800 ng mL−1 of SAA under the optimal probe adding sequence the red-QD-SAA antibody and green-QD-CRP antibody probes were added separately. As shown in Fig. 6(a–d), different concentrations of SAA antigens did not affect the determination of CRP, and the PL intensity of CRP system (green line) increased linearly with the increase of CRP antigen concentrations. Similarly, for SAA assay, at different concentrations of CRP antigens (0, 50, 200, and 800 ng mL−1), the PL intensity of SAA system presented a gradually increasing trend (red line) with the concentrations of SAA antigens increased in Fig. 6(e–h). In general, the detection of CRP and SAA system had not been influenced each other, which laid a foundation for the following simultaneous and quantitative detection of the two type biomarkers.

3.3. Optimization of dQDs-FLISA We optimized the concentrations of coating antibody and the QDantibody probe of SAA and CRP using QD-FLISA method (Supporting Information, Table S1 and Table S2). For SAA or CRP immunoassay, the obvious increase of PL intensity was obtained when the concentration of coating antibody was 5 μg mL−1 and the diluted ratios of QD-antibody probe was 1:100 (SAA assay) or 1:10 (CRP assay). The screening of SAA antigen dilution was preceded in Fig. S2, 10% human serum of PBS buffer as the antigen dilution. Then, the screening of red-QD-SAA antibody probe and green-QD-CRP antibody probe dilution buffer were carried out, separately. According to Figs. S3 and S5, the 0.5 wt% BSA of PBS buffer as the probe dilution buffer was selected. In addition, CRP and SAA antigens were detected separately by QD-FLISA method and good linear results were obtained in Figs. S4 and S6. 3.4. Effect of probe adding sequence

3.6. Standard curve of dQDs-FLISA In order to avoid cross-reactivity between antibodies and antigens, the adding sequence of probes was examined and the interesting experimental results were obtained. As shown in Fig. 5, three adding probes sequence were provided after the mixture of SAA and CRP antigens incubated completely. For CRP assay, the adding sequence of the

Adapting the above optimal experimental conditions and operating sequence, we carried out the dQDs-FLISA method to simultaneously detect CRP and SAA antigens with different concentrations. As shown in Fig. 7(a), the standard curve for the dQDs-FLISA method was obtained 5

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Fig. 5. The different adding sequence of probes: mix red-QD-SAA antibody and green-QD-CRP antibody (a); first adding red-QD-SAA antibody and then adding greenQD-CRP antibody (b); first adding green-QD-CRP antibody and then adding red-QD-SAA antibody (c).

with the increase of CRP or SAA antigens concentration (10-1,000 ng mL−1), and were linearly responded to antigens concentration (R2 > 0.99), which could still meet the quantitative determination after exchange the red-green QDs. The result showed that the method had a certain universality for the detection of both inflammation biomarkers. Recovery experiment of SAA and CRP antigens were conducted to evaluate the accuracy of this dQDs-FLISA method by addition different concentrations of SAA and CRP antigens in human negative serum. Five concentrations of SAA and CRP antigens with high, medium and low concentration (25–750 ng mL−1) were selected for the assay respectively. As shown in Table 1, the recovery rates of CRP samples ranged from 92.4% to 101.7% with a coefficient of variance (CV) of 3.9%–13.1%, and results for the SAA samples ranged from 92.1% to 101.9% with CV less than 15%. The CV of recovery assay using dQDsFLISA method was acceptable, which indicated that this method had good reliability for detection of inflammation biomarkers (CRP and SAA). Subsequently, the good specificity of the dQDs-FLISA method was evaluated. Five interference factors (10 μg mL−1 PCT, 10 μg mL−1 Lcystenine, 10 μg mL−1 DL-homocystenine, 10 μg mL−1 GSH, and 10 μg mL−1 ALP) and 100 ng mL−1 CRP and SAA antigens were carried

by plotting the PL intensity against the CRP samples concentration (101,000 ng mL−1), which the best linear fit was Y = 6709 + 151 X with R2 = 0.998 (n = 3). The results shown in Fig. 7(b) demonstrated that the quantitative detection of SAA antigens with the calibration curve was Y = 4.38 + 0.5 X, R2 = 0.992 (n = 3). The limit of detections (LODs) was an important evaluation parameter for the sensitivity of this detection method. Generally speaking, the LODs was calculated as three times the standard deviation (SD) of ten times black wells (the negative control samples) to the slope of the min-concentration calibration plot (LODs = 3 SD/slope) [50]. In the dQDs-FLISA method, the LODs of redQD-SAA was 2.39 ng mL-1 and the LODs of green-QD-CRP was 6.37 ng mL-1. As a result, a broad detection range and high sensitivity were obtained, which met the needs of clinical for the detection of CRP and SAA antigens. Therefore, this approach can be further developed to detect other dual or even multiple biomarkers at the same time in one sample-well. Such dQDs-FLISA method indeed have great advantages in IVD to simultaneously detect dual or multi-biomarkers. To verify the universality of the method, we interchanged the redgreen QDs detection system. The green-QD could conjugated SAA antibody to detect SAA antigen, and the red-QD conjugated CRP antibody to detect CRP antigen. As shown in Fig. 8, the PL intensity increased 6

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Fig. 6. Interference experiment: (a–d) a series of concentration CRP antigens were detected at different concentration of SAA (0 ng mL−1, 50 ng mL−1, 200 ng mL−1, and 800 ng mL−1); (e–f) a series of concentration SAA antigens were detected at different concentration of CRP (0 ng mL−1, 50 ng mL−1, 200 ng mL−1, and 800 ng mL−1). The SAA system was red line and the CRP system was green line.

7

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Fig. 7. The standard curve of green-QD detection CRP antigens (a), the standard curve of red-QD detection SAA antigens, photoluminescence spectra from dQDsFLISA for determination of CRP and SAA antigens (c) (n = 3).

out in following assay. As shown in Fig. 9(a), after adding green-QDCRP antibody probe, the other substances (the concentration was 100 times for the CRP concentration) could not interfere the detection of CRP antigen. Compared the PL intensity of SAA system, the influences on the detected PL intensity of interference factors almost were negligible after adding red-QD-SAA antibody probe in Fig. 9(b). Thus, the proposed dQDs-FLISA method possessed of good selectivity without apparent interference from nonspecific adsorption of other antigens.

Table 1 Recoveries of different concentrations of CRP and SAA antigens in human negative serum.

CRP

4. Conclusion SAA

In the process of any immunoassay, cross-reactivity between antibodies and antigens can be problematic and needs to be carefully avoided [36]. In order to produce a reliable assay, we have found a new protocol to optimize assay conditions and antibody reagents as follows: First, the two types of coating antibodies bound on the microplate with the concentration ratio of 1:1. Then, the target antigens from the sample were loaded and captured. The red-QD-SAA antibody was added first with priority binding, and then followed by green-QD-CRP antibody. Finally, an accurate result was obtained with both CRP and SAA antibodies coating in a single well simultaneously. We indeed achieved to report two types of biomarkers in one reaction unit. The result

Sample number

Experimental value (ng mL−1)

Spiked value (ng mL−1)

Recovery (%)

RSD (%)

1 2 3 4 5 1 2 3 4 5

711.11 501.55 254.25 93.21 23.09 705.56 509.25 230.33 101.07 23.97

750 500 250 100 25 750 500 250 100 25

94.81 100.3 101.7 93.21 92.39 94.07 101.85 92.13 101.07 95.87

7.54 3.97 5.49 10.43 13.05 5.2 7.33 12.95 10.54 10.29

showed good reproducibility, high-sensitivity, and high specificity. The detection of two types of biomarkers was conducted by dual QDs with different emission wavelengths, giving rise to good monochromaticity, under the same excitation wavelength in one sample-well on microplate. Combining these advantages of QDs-FLISA method, we have been prepared an approach in dual or multi-simultaneous determination of

Fig. 8. The standard curve of green-QD detection SAA antigens (a), the standard curve of red-QD detection CRP antigens, photoluminescence spectra from dQDsFLISA for determination of CRP and SAA antigens (c) (n = 3). 8

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Fig. 9. Cross-reaction and specificity of dQDs-FLISA method.

different biomarkers. Furthermore, this proposed dQDs-FLISA method has immense potential for the development of simultaneous and accuracy determination in biomedicines, food safety, and environmental monitoring.

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Yanbing Lv obtained her M.Sc. degree in 2017 at Key Lab for Special Functional Materials of Ministry of Education, and School of Materials Science and Engineering, Henan University, Kaifeng, 475004, China. She is working toward her Ph.D. in Prof. Fang Guo group at School of Chemistry, Liaoning University, Shenyang, 110036, China. Her research interests include immunoassay, biological labeling, and nanomaterials.

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Fangfang Wang obtained her M.Sc. degree in 2018 at Key Lab for Special Functional Materials of Ministry of Education, and School of Materials Science and Engineering, Henan University, Kaifeng, 475004, China. She is working toward her Ph.D. in Prof. Wenyu Ji group at College of Physics of Jilin University, Changchun, 130021, China. Her research interests include colloidal semiconductor quantum dots and quantum dot-based light emitting diodes. Ning Li obtained his M.Sc. degree in 2015 at Key Lab for Special Functional Materials of Ministry of Education, and School of Materials Science and Engineering, Henan University, Kaifeng, 475004, China. He is working toward his Ph.D. in Prof. Lin Song Li group at Key Lab for Special Functional Materials of Ministry of Education, and School of Materials Science and Engineering, Henan University, Kaifeng, 475004, China. His research interests include quantum dot synthesis and its surface modification. Ruili Wu received her Ph.D. degrees in 2018 at Key Lab for Special Functional Materials of Ministry of Education, and School of Materials Science and Engineering, Henan University, Kaifeng, 475004, China. Her is working in Prof. Lin Song Li group at Key Lab for Special Functional Materials of Ministry of Education, and School of Materials Science and Engineering, Henan University, Kaifeng, 475004, China. Her research interests include aqueous phase quantum dot, immunoassay and biological labeling. Jinjie Li obtained her M.Sc. degree in 2014 at Key Lab for Special Functional Materials of Ministry of Education, and School of Materials Science and Engineering, Henan University, Kaifeng, 475004, China. She is working toward her Ph.D. in Prof. Xia Chen group at National & Local United Engineering Laboratory for Chinese Herbal Medicine Breeding and Cultivation, School of Life Sciences, Jilin University, Changchun, 130021, China. Her research interests include quantum dot modification, aqueous phase quantum dot, and nanobeads. Huaibing Shen received his Ph.D. degrees in Biochemistry from Jilin University in 2011. He is a professor at Key Lab for Special Functional Materials of Ministry of Education, and School of Materials Science and Engineering, Henan University, Kaifeng, 475004, China. His research interests include colloidal semiconductor quantum dots, biological labeling and quantum dot-based light emitting diodes. Lin Song Li obtained his Ph.D. degrees in Physical Chemistry from Jilin University in 1997. He is a professor at Key Lab for Special Functional Materials of Ministry of Education, and School of Materials Science and Engineering, Henan University, Kaifeng, 475004, China. His main reach fields are colloidal semiconductor quantum dots, quantum dot-based light emitting diodes, and biological labeling. Fang Guo received her Ph.D. degrees in 2007 at School of Chemistry, Cardiff University, Wales, UK. She is a professor at School of Chemistry, Liaoning University, Shenyang, 110036, China. Her research interests include supramolecular and crystal materials.

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