Skip to main content
NCBI home page
Poultry Science logoLink to Poultry Science
. 2025 Feb 18;104(4):104924. doi: 10.1016/j.psj.2025.104924

Development of a graphene oxide multilayer quantum dot-based immunochromatographic strip for the ultrasensitive detection of H7 subtype avian influenza viruses

Jiamin Fu a, Ping Wang a, Han Wu a, Fan Yang b, Linfang Cheng a, Fumin Liu a, Hangping Yao a, Nanping Wu a, Lihua Xu c, Haibo Wu a,⁎
PMCID: PMC11904543  PMID: 39985899

Abstract

Since March 2013, the H7N9 subtype of avian influenza virus (AIV) has become an important zoonotic infectious disease, garnering significant global attention because of its potential to affect human health. Establishing a rapid, effective, and sensitive method to detect H7 subtype AIVs is crucial for disease control. In this study, we developed a graphene oxide multilayer quantum dot-based immunochromatographic strip for the ultrasensitive detection of H7 subtype AIVs. The method demonstrated excellent sensitivity, with a limit of detection of 0.063 hemagglutinin units and 0.016 ng/ml for the hemagglutinin protein. The method exhibited remarkable specificity, with no reaction with other subtypes of influenza A virus andno cross-reactivity with other types of avian virus. Additionally, this method exhibited excellent reproducibility, with both inter-group and intra-group variations remaining below 10 %. Preliminary testing on avian clinical samples showed impressive consistency, underscoring the method's reliability. These initial results suggest that this detection approach has significant potential for widespread use in analyzing avian clinical samples, indicating substantial promise for its future application in various diagnostic settings.

Keywords: H7 subtype influenza virus, Immunochromatographic strip, Graphene oxide, Quantum dot, Ultrasensitive detection

Introduction

In March 2013, the world's first case of novel reassortant H7N9 influenza was discovered in humans in eastern China (Chen et al., 2013). Since then, H7N9 has become an important zoonotic infectious disease, attracting significant global attention because of its potential infect humans (Shi, et al., 2023). In January 2017, the China CDC reported the identification of a highly pathogenic H7N9 virus strain that was found in both humans and poultry in Guangdong, presenting a serious threat to poultry health. Despite the extensive vaccination efforts aimed at H7N9 in poultry, new genetic variants of the virus are continually emerging. This persistent evolution of the virus continues to pose a risk to the health of both animals and humans (Chen, et al., 2022; Yin, et al., 2021). As of August 2, 2024, there have been 1,568 laboratory-confirmed cases of H7N9 avian influenza reported globally among humans. Among these cases, tragically, 616 individuals have died, leading to a high mortality rate of 39 %.

Considering the extensive prevalence of H7N9 avian influenza viruses (AIVs) among different poultry species, it is important to establish detection methods that are both rapid and highly accurate to identify these viruses. Currently, the methods to detect H7N9 AIV mainly include virus isolation, loop-mediated isothermalamplification, colloidal gold methods, and polymerase chain reaction (PCR) (Chen, et al., 2008; Payungporn, et al., 2006; Yu, et al., 2018). Virus isolation is a time-consuming process, making it unsuitable for rapid diagnosis. By contrast, PCR methods show high sensitivity and specificity, allowing for the detection of the virus at the early stages and providing accurate results even at low viral loads.PCR has several limitations, including a high dependency on specialized equipment and trained personnel, which restrict its use in resource-constrained settings, such as point-of-care environments. Additionally, PCR typically involves a prolonged turnaround time, often exceeding 2 h for thermal cycling and analysis, making it less suitable for rapid point-of-care testing (POCT)(Craw and Balachandran, 2012; Yang, et al., 2022). Additionally, its sensitivity can be affected by inhibitors in complex sample matrices, limiting its applicability in POCT (Niemz, et al., 2011).Each of these methods has limitations in practical clinical applications.

A lateral flow immunoassay (LFA) is widely regarded as one of the most practical and feasible methods for POCT. Its applications range from medical diagnostics, such as pregnancy tests and disease detection, to environmental monitoring and food safety testing. Despite its advantages, LFA might have limited sensitivity and specificity compared with other methods. Usually, the detection limit of colloidal gold is higher than 1ng/ml.The colloidal gold method is easy to operate and has a short detection time, ranging from 20 min to 30 min, making it better suited for POCT;however, it has lower sensitivity and might result in false negatives (Quesada-González and Merkoçi, 2015; Vemula, et al., 2016).

The increased attention focused on quantum dots (QDs) highlights the expanding role and significance of QDs in advancing the capabilities and effectiveness of immunoassays (Li, et al., 2019a; Chan and Nie, 1998; Wen, et al., 2016). There is an increasing demand for highly accurate and sensitive detection results, especially in the realm of identifying various viruses, biomolecules, bacteria, and toxins (Li, et al., 2020; Lifen, et al., 2016; Rong, et al., 2019; Zhenli, et al., 2016).Therefore, there has been a notable rise in the focus on immunoassay applications. This emerging trend highlights the urgent necessity for the swift and accurate extraction of comprehensive biological information from individual samples, even when these samples are available in very low concentrations or minimal volumes (Zongwen and Niko, 2012). Consequently, optical biosensors that utilize QDs have demonstrated significant potential. This is attributed to the distinct photophysical properties of QDs, which render them especially effective for tasks requiring highly sensitive detection (Niko, 2011). The data suggest that QDs could play a pivotal role in advancing onsite diagnostic procedures, offering significant advantages in terms of accuracy and efficiency. Their application in real-world, on-site testing scenarios appears highly feasible and could lead to notable improvements in rapid diagnostic capabilities.

Graphene holds significant potential in LFAs because of its unique properties. Its large surface area allows for efficient conjugation with antibodies and other biomolecules, thereby enhancing the sensitivity and specificity of the assays (Lin, et al., 2022; Wang, et al., 2023; Zhu, et al., 2020). This versatility not only enhances the overall efficiency of immunoassays, but also opens up new avenues for multiplexing, allowing researchers and clinicians to simultaneously detect multiple pathogens.

Recently, our research team developed of a range of monoclonal antibodies (mAbs) specifically targeting the hemagglutinin (HA) protein of the H7N9 AIV, and these antibodies have proven to be highly valuable in the immunological detection of the H7N9 virus, with effective applications in techniques such as enzyme-linked immunosorbent assay (ELISA) and colloidal gold methods (Yang, et al., 2020a, 2021, 2020b). In this study, we employed previously obtained mAbs 1H10 and 2D1 to develop a rapid detection method forH7N9 AIV, based on a QD and graphene approach. This method demonstrated excellent sensitivity, with a limit of detection (LOD) reaching 0.063 hemagglutinin unit (HAU) and 0.016ng/ml for the HA protein. Additionally, the method exhibited remarkable specificity, showing no reaction with other subtypes of influenza A viruses and no cross-reaction with other pathogens of avian viruses. This high degree of specificity ensures that the detection is both accurate and reliable, highlighting the method's potential application in various diagnostic scenarios.

Materials and methods

Viruses

A comprehensive overview of the viruses utilized in this study is provided in Table 1. Our team previously isolated viral strains from H7N9-infected patients in Zhejiang and Guangdong. Specifically, A/Zhejiang/DTID-ZJU01/2013 and A/Guangdong/HP001/2017 were the identified strains. These isolates were carefully selected to ensure a comprehensive analysis of the H7N9 virus, reflecting the geographical and temporal diversity of infections (Wu, et al., 2020). Various subtypes of avian influenza viruses, including H1N2, H2N8, H3N2, H4N6, H5N6, H6N1, H7N3, H7N7, H9N2, H10N2, and H11N9, as well as other avian viruses such as avian paramyxovirus-4 (APMV-4, ZJ-1), infectious bronchitis virus (IBV, H120), infectious bursal disease virus (IBDV, NF8), and Newcastle disease virus (NDV, La Sota) were isolated from poultry. These viruses are preserved in our laboratory's −80°C freezer to maintain their stability and viability for ongoing and future research. The animal experiments conducted with these mice received approval from the Animal Care and Use Committee of the First Affiliated Hospital, School of Medicine, Zhejiang University (No.2019-39). The researchers conducted experiments involving highly pathogenic AIVs with strict adherence to the requirements specified in the biosafety management manual, which were carried out within the confines of biosafety level 3 laboratories.

Table 1.

Respiratory viruses mentioned in the study.

Virus strains QDFM- LFA strip Reference
real-time RT-PCRa
A/duck/Zhejiang/D1/2013(H1N2) - 21.29
A/duck/Zhejiang/6D10/2013(H2N8) - 26.11
A/duck/Zhejiang/4613/2013(H3N2) - 27.74
A/duck/Zhejiang/409/2013(H4N6) - 24.64
A/duck/Zhejiang/6D2/2013 (H5N6) - 20.84
A/chicken/Zhejiang/1664/2017(H6N1) - 26.15
A/duck/Zhejiang/DK10/2013(H7N3) + 23.76
A/chicken/Zhejiang/92752/2015(H7N3) + 25.84
A/chicken/Jiangxi/C25/2014(H7N7) + 26.87
A/chicken/Zhejiang/DTID-ZJU01/2013(H7N9) + 24.62
A/chicken/DTID-ZJU01/2013(H7N9) + 22.58
A/chicken/Zhejiang/1026105/2015(H7N9) + 29.84
A/chicken/Zhejiang/1128/2023(H7N9) + 28.26
A/Guangdong/HP001/2017(H7N9) + 25.18
A/chicken/Zhejiang/329/2011(H9N2) - 24.10
A/duck/Zhejiang/6D20/2013(H10N2) - 22.12
A/duck/Zhejiang/71750/2013(H11N9) - 19.62
Infectious bronchitis virus (IBV, H120) - ND
Newcastle disease virus (NDV, La Sota) - ND
Infectious bursal disease virus (IBDV, NF8) - ND
Avian paramyxovirus-4 (APMV-4, ZJ-1) - ND
Open in a new tab

Note:aThe results were obtained using a commercial real-time reverse transcription (RT)-PCR kit to detect influenza A viruses (Liferiver, Shanghai, China). bND, Not detected.

Preparation of immune-GO-TQD-probe

Initially, 2 ml of monolayer graphene oxide(GO, XFNANO, Suzhou, China) nanosheets (1 mg/ml) were sonicated for 10 min and centrifuged at 12000 rpm for 15 min. The pellet, containing the desired size fraction of GO nanosheets, was collected and resuspended in 20 ml of deionized water. To take advantage of the electrostatic adsorption between GO and polyethyleneimine (PEI, Sigma-Aldrich, Saint Louis, MO), the GO solution was mixed with 1 ml of PEI, sonicated for 20 min, and centrifuged at 12000 rpm for 15 min to obtain GO-PEI sheets. Subsequently, the GO-PEI sheets were resuspended in 20 ml of deionized water added with 20 μl of QDs (Q2650, Jiayuan, Wuhan, China). The mixture was subsequently subjected to sonication for 50 min, ensuring thorough dispersion and mixing of the components. Subsequently, the mixture was centrifuged at10,000 rpm for 15 min, which was crucial to separate the components based on their densities, allowed us to isolate the desired GO-QD nanofilms effectively. The GO-QD nanofilms were thoroughly washed twice using deionized water and resuspended in 30 ml of deionized water. The following process was repeated twice: first, the GO surface was coated with an additional layer of QD using PEI, resulting in the formation of GO-double QD nanofilms (GO-DQD); and second, two additional layers of QD were applied to create GO-triple QD (GO-TQD) nanofilms. The obtained GO-TQD nanofilms were each resuspended in 10 ml of anhydrous ethanol.

The GO-TQD nanofilms were centrifuged at 8000 rpm for 10 min and resuspended in 10 ml of 100 mM 4-Morpholineethanesulfonic acid (Sigma-Aldrich). To this suspension, 100 μl of 19 mg/mL 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride (Thermo Fisher Scientific, Rochford, USA) and 200 μl of 21 mg/mL N-hydroxysuccinimide (Sigma-Aldrich, Saint Louis, MO, USA) were added. The mixture was subjected to ultrasound treatment for 20 min to ensure thorough mixing and activation of the carboxyl groups, followed by centrifugationat 8000 rpm for 10 min. The GO-TQD nanofilms were resuspended in 5 ml of PBST (PBS containing 1 % Tween) and then mixed with 0.2 mg of the mAb 2D1. This mixture was incubated at room temperature on a horizontal shaker for 90 min to ensure proper interaction and binding. Next, 5 ml of PBST supplemented with 10 % BSA (Sangon Biotechnology, Shanghai, China) was added and incubated at room temperature for 60 min. Next, the mixture was centrifuged at 8000 rpm for 10 min and washed twice with PBST. Finally, the immuno-GO-TQD-probes were resuspended in 1 ml of PBST.

Preparation of the GO-TQD LFA strip

The goat anti-mouse IgG (Solarbio, Beijing, China) and mAb 1H10 were diluted to concentrations of 1 mg/ml and 2 mg/ml, respectively, using PBS and PBST. These solutions were then evenly sprayed onto the nitrocellulose membrane (Unisart, Sartorius, Göttingen, Germany) using a BioDot XYZ distribution platform (Jinbiao Biotechnology, Shanghai, China) to generate the Control line (C) and Test line (T). The immuno-GO-TQD-probe was evenly sprayed onto the conjugate pad (Jiening Biotechnology, Shanghai, China) using the BioDot XYZ distribution platform. The GO-TQD LFA strips were meticulously assembled onto a polyvinyl chloride board, which included the sample pad, conjugate pad, nitrocellulose membrane, and absorbent pad. Once the assembly was complete, the strips were precisely cut into uniform 3.5 mm wide bands. This cutting process was carried out using an automatic cutter (Jinbiao Biotechnology), ensuring consistent and accurate dimensions for each strip. When the sample interacts with the T line or C line, a black line becomes visible to the naked eye under natural light conditions. Simultaneously, we are able to visually observe the fluorescent bands under 365 nm ultraviolet light. Additionally, we measured the fluorescence intensity employing a fluorescent test strip scanner (Hemai Technology, Suzhou, China), Fig. 1.

Fig. 1.

Fig. 1

Open in a new tab

Schematic of (A) the fabrication of GO-TQD nanoprobe and (B) GO-TQD LFA for the direct analysis of H7AIVs. AIV, avian influenza virus; GO, graphene oxide; QD, quantum dot; DQD, double quantum dot; TQD, triple quantum dot; PEI, polyethyleneimine; LFA, lateral flow immunoassay; mAb, monoclonal antibody; UV, ultraviolet; EDC, 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride; NHS, N-hydroxysuccinimide; PVC, polyvinyl chloride.

Sensitivity, specificity, and reproducibility of the H7GO-TQD LFA strip

The procedure to test the sensitivity of the GO-TQD LFA strip was as follows: H7 allantoic fluid, which has a concentration range varying from 26 to 2−6 HAU, along with H7 purified HA protein, which ranged in concentration from 128 to 0.004 ng/ml, were two-fold serially diluted. These diluted samples are then resuspended in a running buffer composed of PBS, 1 % Tween, and 10 % fetal bovine serum. Subsequently, these prepared solutions are applied to the sample pad of the GO-TQD LFA strip to detect its sensitivity. To assess its specificity, different virus samples listed in Table 1 were tested using the GO-TQDLFA strip. The H7 purified HA protein was diluted using running buffer to create solutions with a high concentration (64 ng/ml), moderate concentration (4 ng/ml), and low concentration (0.25 ng/ml). These different concentrations were then added to the strip, and each concentration was tested independently seven times. This series of tests was conducted to evaluate the repeatability and consistency of the GO-TQD LFA strip.

Detection of real poultry and human samples

To assess the detection capability of the GO-TQD LFA strip for clinical samples, we conducted a comprehensive evaluation involving 150 avian samples, which included 20 throat swabs and 130 fecal samples collected from poultry in Zhejiang Province, Eastern China, from June 2018 to December 2023. Among them, 10 samples were H7 positive, as confirmed by PCR testing (Yang, et al., 2022). Additionally, 62 human throat swab samples were collected, which were identified as positive by PCR. These included 12 samples of influenza B, 15 samples of H3N2 influenza, 15 samples of H 1N1 influenza, and 20 samples of COVID-19 (Yang, et al., 2022). Meanwhile, we prepared nine H7-spiked samples (throat swabs) to rigorously access the clinical performance of the GO-TQD method.

Results

Characteristics of mAbs

In our previous research, a series of mAbs against the H7N9 virus HA protein were successfully developed using hybridoma technology and ELISA. For the subsequent study of the GO-TQD strips, we specifically chose two mAbs, named 2D1 and 1H10.The characteristics of these two mAbs are provided in Table S1. The isotypes of mAb 2D1 and 1H10 are IgG2a and IgG2b, respectively. Both antibodies exhibit strong reactivity specifically against the H7N9 virus, and do not no cross-react with other influenza virus subtypes, such as H1 and H3.The two mAbs bind to different locations on the HA protein of A/Zhejiang/DTID-ZJU01/2013 (H7N9). Specifically, mAb 1H10 interacts with R148 M, while mAb 2D1 targets E124V.

LOD of the GO-TQD LFA strip

To explore the capability of the GO-TQD LFA strip to detect the H7 subtype influenza virus, we conducted tests using three replicate samples. These samples consisted of H7 allantoic fluid and purified HA protein at concentrations ranging from 26 to 2−6 HAU and from 128 to 0.002 ng/ml, respectively. As shown in Fig. 2, the fluorescence intensity detected on the test line exhibited a direct correlation with the concentration of the virus present. As the virus concentration increased, a corresponding rise in fluorescence intensity was observed. This relationship is crucial to accurately quantify viral loads, enabling more effective assessment and interpretation of the test results. Our findings revealed that the fluorescence signal generated by the GO-TQD LFA strip, which was designed to detect H7 purified HA protein, remained observable to the naked eye even at a concentration of 0.032 ng/ml. At the same time, the fluorescence test strip scanner was capable of detecting this fluorescence signal at 0.016 ng/ml, providing a fluorescence intensity value of approximately 436. However, the LOD values for the QD, GO-QD, and GO-DQD to detect the H7 HA protein were 0.25, 0.125, and 0.032 ng/ml, respectively (Fig. 2A).When we compared the performance of QDs with that of GO-TQDs, we found that the LOD for the GO-TQDs to detect the H7 HA protein improved significantly, showing an increase of nearly 16-fold. Additionally, we observed that at identical concentrations of allantoic fluid and HA protein, the GO-TQD, GO-DQD, and GO-QD LFA strips produced significantly stronger fluorescence signals at the T line compared with those on conventional QD strips. Our findings suggested that the fluorescence signal produced by the GO-TQD LFA strip, which is used to detect H7 allantoic fluid, remains visible to the naked eye even at a concentration of 2−4 HAU. The LOD values for QD, GO-QD, and GO-DQD were 2°, 2−1 and 2−3 HAU, respectively. However, when employing a fluorescence test strip scanner, we were able to detect significantly lower titers of the H7 virus at the T line of the GO-TQD LFA strip, achieving a sensitivity of2−4 HAU (Fig. 2B). In a similar manner, compared with QD, the LOD of GO-TQD to detect H7 allantoic fluid increased by nearly 16-fold. In addition, we utilized three different H7 subtype AIVs, specifically H7N3, H7N7, and H7N9, along with one H10N5 virus, which served as a negative control. This approach was undertaken to thoroughly evaluate the sensitivity of the AC-ELISA reaction. The findings from the AC-ELISA demonstrated that the LOD to accurately identify H7 viruses was 2−2 HAU. Moreover, we observed positive results at 3.9 ng/ml, which further indicated that the LOD for the H7 HA protein within the AC-ELISA framework was 3.9 ng/ml (Yang, et al., 2021). The LOD for H7 determined using AC-ELISA was 243 times higher than that of the GO-TQD strip. This enhancement demonstrated the superior sensitivity of the GO-TQDs in this specific application.

Fig. 2.

Fig. 2

Open in a new tab

Images and corresponding fluorescence intensities of QD, GO-QD, GO-DQD, and the GO-TQD LFA strip to detecting allantoic fluid and purified HA protein of H7 AIV. (A) Serial dilutions of purified H7N9 HA protein ranging from 128 to 0.002 ng/ml were used to determine the limit of detection of the QD, GO-QD, GO-DQD, and GO-TQD LFA. Fluorescence intensity scans at different concentrations of purified H7N9 HA protein measured by the fluorescence test strip scanner. (B) Serial dilutions of H7 AIV ranging from 2−6 to 26 HAU were used to determine the limit of detection of the QD, GO-QD, GO-DQD, and the GO-TQD LFA strip. Fluorescence intensity scans at different concentrations of allantoic fluid of H7 AIV measured by the fluorescence test strip scanner. GO, graphene oxide; QD, quantum dot; DQD, double quantum dot; TQD, triple quantum dot; LFA, lateral flow immunoassay; HA, hemagglutinin; AIV, avian influenza virus; HAU, hemagglutinin unit. The red triangle represents the lowest detectable value.

Specificity of the GO-TQD strip

To access the specificity of the GO-TQD LFA strip, we tested a range of non-H7 subtype influenza viruses, including H1N2, H2N8, H3N2, H4N6, H5N6, H6N1, H9N2, H10N2, and H11N9. Furthermore, we expanded our assessment to incorporate various strains of avian viruses. Among them, we included the common NDV, IBV, IBDV and APMV-4. A phylogenetic tree of the HA genes of representative H7 influenza viruses is shown in Fig. 3.The results revealed that the GO-TQD LFA strip specifically reacts only with H7 AIVs, including H7N3, H7N7, and H7N9 (Fig. 4). Importantly, it did not demonstrate any cross-reactivity with other subtypes of influenza A viruses or with any of the other tested viruses. The absence of any interference significantly guarantees that the results obtained are both accurate and reliable to diagnose infection with the intended target virus. Our findings strongly indicated that the GO-TQD strip exhibits high specificity to detect H7 subtype AIVs. This specificity is crucial to ensure a precise diagnosis and to enhance the overall reliability of the test process.

Fig. 3.

Fig. 3

Open in a new tab

Phylogenetic tree of HA genes of representative H7 subtype influenza viruses, which was generated in the MEGA11 software using the maximum likelihood method. Black dots indicate the H7 subtype influenza viruses mentioned in this study.

Fig. 4.

Fig. 4

Open in a new tab

Cross-reactivity tests of influenza A viruses (including H1N2, H2N8, H3N2, H4N6, H5N6, H6N1, H7N3, H7N7, H7N9, H9N2, H10N2, and H11N9) and other avian viruses (including infectious bronchitis virus (IBV), Newcastle disease virus (NDV), infectious bursal disease virus (IBDV) and avian paramyxovirus-4 (APMV-4)). The red triangle represents a positive result.

Reproducibility of the GO-TQD strip

The reproducibility of the GO-TQD strip was evaluated by detecting absorbance from four replicates across different titers of H7N9 purified HA protein (64, 4, and 0.25 ng/ml). The signals produced by the four replicates of the three different concentrations of H7 purified HA protein were detected to test the reproducibility of the GO-TQD strip (Fig. 5). The values of the relative standard deviation (RSD) were all below 10 % (Table 2). This finding indicated that the GO-TQD strip demonstrated high reproducibility.

Fig. 5.

Fig. 5

Open in a new tab

Reproducibility testing of the GO-TQD LFA strip. Different concentrations of H7 HA protein (64, 4 and 0.25 ng/ml) were used to assess the reproducibility of the GO-TQD LFA strips and to measure the corresponding fluorescence intensity. GO-TQD LFA, graphene oxide-triple quantum dot-lateral flow immunoassay; HA, hemagglutinin; a.u., average fluorescence intensity.

Table 2.

Reproducibility the GO-TQD LFA strip.

HA protein concentrations
(ng/ml)		 Average fluorescence intensity (a.u.) Std. dev RSD/%
(n = 4)
64 51340 4794 9.33
4 21157 1061 5.01
0.25 4466 267.4 5.99
Open in a new tab

Note: GO-TQD LFA, graphene oxide-triple quantum dot-lateral flow immunoassay; HA, hemagglutinin; RSD, relative standard deviation.

Detection of real biological samples

Among the 150 avian samples tested, 10 samples were H7 positive, as confirmed by PCR. Additionally, the 62 human throat swab samples, identified as positive by PCR, included 12 samples of influenza B, 15 samples of H3N2 influenza, 15 samples of H 1N1 influenza, and 20 samples of COVID-19. Meanwhile, there were nine H7-spiked samples. The accuracy of the GO-TQD method was thoroughly assessed by comparing its results to those obtained from a real-time PCR assay, which served as the reference method for evaluation. This comparison aimed to determine how well the GO-TQD method performed in relation to the established real-time PCR technique. As detailed in Table 3, both methods yielded identical results, demonstrating 100 % concordance. This indicated that the GO-TQD strip performed reliably across diverse sample types without interference, achieving high sensitivity and specificity.

Table 3.

Sample tests using the GO-TQD LFA strip or real-time PCR.

Samples Number GO-TQD LFA
result (P/N)		 real-time PCR
result (P/N)
Avian samples Throat swabs 20 10/140 10/140
Fecalswabs 130
Human samples Throat swabs 62 0/62 0/62
H7-spikedsamples Throat swabs 9 9/0 9/0
Open in a new tab

Note:GO-TQD LFA, graphene oxide-triple quantum dot-lateral flow immunoassay; P/N, number of positives/ number of negatives.

Discussion

The rapid clinical detection of influenza viruses has been a significant focus of research within the field of disease prevention and control. Numerous related studies have been conducted, highlighting the importance and urgency of developing effective diagnostic methods. In our earlier research, we successfully developed two monoclonal antibodies, designated as 2D5 and 2F5, specifically targeting the H7N9 subtype AIVs (Fan, et al., 2020).We proceeded to create a colloidal gold test strip designed for the rapid detection of H7 subtype AIVs, which possessed an LOD of 2 HAU or 102.5550 % tissue culture infectious dose for H7 subtype AIVs. Subsequently, we developed an AC-ELISA utilizing these antibodies, which had an LOD for the H7 HA protein reaching as low as 3.9 ng/ml and 0.25 HAU for H7 viruses (Yang, et al., 2021). These methods demonstrated excellent specificity and reproducibility. While these advances have enhanced our capacity to detect AIVs, they have certain deficiencies. The colloidal gold method suffers from low sensitivity, which can compromise its effectiveness in various applications. Similarly, although the AC-ELISA shows promise, its LOD still requires improvement, and the overall process can be quite intricate and labor-intensive. Additionally, multiplex real-time reverse transcription-PCR requires skilled personnel who have undergone formal training, along with specialized laboratory equipment to ensure accurate and reliable results (Yang, et al., 2022). Addressing these challenges is essential to further advance our detection capabilities for AIVs.

Recently, QDs have emerged as a promising material in LFAs, enhancing the sensitivity and specificity of these diagnostic tests. Their unique optical properties, including size-tunable fluorescence and broad absorption spectra, allow for multiplexing, enabling the simultaneous detection of multiple targets in a single assay. One of the key advantages of using QDs in LFAs is their high photo stability, which ensures consistent signal intensity over time, thereby improving the reliability of the results. Additionally, QDs exhibit brighter fluorescence compared with that of traditional dyes, allowing for the detection of lower concentrations of analytes. This increased sensitivity is particularly valuable in applications where early detection is crucial. Furthermore, the ability to modify the surface of QDs facilitates the conjugation of various biomolecules, enhancing their functionalization for specific assays (Lu, et al., 2019). Overall, the integration of QDs into LFAs represents a significant advance, providing rapid, accurate, and highly sensitive diagnostic capabilities. In recent years, scholars worldwide have conducted a series of studies on pathogen detection based on QDs (Duracova, et al., 2018; Li et al., 2019b). Compared with conventional detection techniques, this new approach offers a simpler operational procedure, delivers more consistent and reliable results, and is more appropriately designed for on-site detection (Wang, et al., 2019).

A novel composite nanomaterial made from silica and QDs was developed, which exhibited excellent stability and superior fluorescence signals, and enabled the rapid detection of SARS-CoV-2 antigens within 15 min, with a detection limit reaching as low as 5 pg/ml. The remarkable stability and high-quality fluorescence of this new nanomaterial make it highly effective for quick and sensitive detection, significantly enhancing the efficiency and accuracy of SARS-CoV-2 antigen testing (Wang, et al., 2021). Other researchers have successfully integrated graphene with QDs to create an ultrasensitive immunochromatographic test strip featuring QDs to the H 1N1 virus. This innovative test strip provides enhanced fluorescence sensitivity that is nearly 500 times greater and offers a tenfold improvement in visual detection capabilities (Cheng, et al., 2023). Additionally, the LOD for the detection of H1, H5, and H9 subtype viruses using QD-based immunochromatography technology were 0.0005 HAU, 0.016 HAU, and 0.25 HAU, respectively. When QDs were combined with magnetic beads, their ability to detect H5 was greatly enhanced, achieving an LOD 0.1 ng of viral RNA. Compared with traditional detection technologies, QD-based detection methods show significantly improved sensitivity, comparable to that of PCR (Seder, et al., 2022; Wu, et al., 2016; Zhang, et al., 2010). Researchers also developed a specialized probe that utilizes graphene QDs, specifically engineered for the detection of HBV-DNA. The results of that study demonstrated that this innovative probe exhibited exceptional sensitivity, with an LOD reaching as low as 1 nM (Xiang, et al., 2018). The above results indicated that the combination of QDs with other chemical materials as new fluorescent dyes for the rapid and accurate pathogen detection has promising clinical application prospects.

In this study, we successfully developed a GO-TQD LFA strip specifically designed to detectH7 AIVs. This innovative approach involves wrapping three layers of QDs onto the surface of GO nanosheets using PEI. This method significantly enhanced the fluorescence signal, providing a substantial increase in sensitivity. Furthermore, the incorporation of these QDs created abundant surface sites for antibody binding. The GO-TQD LFA strip can rapidly analyze samples and produce reliable results via a simple 365 nm fluorescence device within 15 min. The LOD of GO-TQD LFA strip to detect H7 subtype AIV was 0.063 HAU per 80 μl sample, with a corresponding LOD for the HA protein of H7 AIV at 0.016 ng/ml. In addition, the GO-TQD LFA strip showed lower detection limits than the GO-QD and GO-DQD LFA strips. Compared with that of AC-ELISA, its sensitivity improved by nearly 243-fold. Furthermore, the GO-TQD LFA method demonstrated both high specificity and excellent reproducibility, ensuring reliable and accurate results. The tests on clinical samples showed highly consistency between GO-TQD LFA and real-time PCR. Film-like magnetic quantum dot (QD) films offer rapid separation and signal amplification but require complex synthesis and external magnetic field control (Wang, et al., 2019). In contrast, our design simplifies the fabrication process through a one-step self-assembly method while maintaining comparable magnetic responsiveness. Similarly, surface-enhanced Raman scattering (SERS) nanofilms based on graphene oxide (GO) or MoS2 substrates exhibit ultra-high sensitivity, but their performance is often hindered by poor reproducibility due to uneven "hot spot" distribution (Achadu, et al., 2021; Pan, et al., 2022). To address this, our material integrates a uniform plasmonic nanostructure, ensuring consistent SERS enhancement. Additionally, 3D nanozyme films, which mimic natural enzymes for catalytic signal amplification, typically suffer from low catalytic stability under harsh conditions (Wang, et al., 2024). Our approach combines nanozyme activity with a protective polymer matrix, significantly enhancing durability without compromising catalytic efficiency. Thus, the GO-TQD LFA showed an acceptable performance, with the advantages of speed and accuracy, providing new options for POCT for viral diagnosis. Our method offers a cost-effective solution for point-of-care testing (POCT), utilizing low-cost materials such as paper-based substrates or polymer membranes, which are commonly used in commercial lateral flow assays (LFAs) due to their affordability (Yetisen, et al., 2013). This makes our approach economically viable for mass production, comparable to colloidal gold-based LFAs (Foubert, et al., 2017). In terms of equipment, we intentionally minimize the reliance on specialized instruments, allowing signal readout with portable UV lamps or smartphone-based fluorescence detectors (Bermejo-Pelaez, et al., 2024; Li, et al., 2022). This is in line with the growing trend of decentralized diagnostics, where smartphone-integrated devices are becoming increasingly common for field applications (de Araujo, et al., 2024). Furthermore, the scalability and compatibility of our fabrication process with existing LFA roll-to-roll production lines, combined with high-reproducibility techniques such as inkjet printing or robotic dispensing for probe deposition, ensures the feasibility of large-scale manufacturing (Carota, et al., 2024).We look forward to large-scale commercial application in the near future.

Disclosures

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This study was supported by Grants from the National Science Foundation of the People's Republic of China (32273092), Zhejiang Provincial Natural Science Foundation of China (LY24H190001 and QN25H190012), the Fundamental Research Funds for the Central Universities (2022ZFJH003) and National Key R&D Program of China (2024YFC2309903).

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.psj.2025.104924.

Appendix. Supplementary materials

mmc1.docx (13.1KB, docx)

References

  1. Achadu O.J., Abe F.., Li T.-C., Khoris I.M., Lee D., Lee J., Suzuki T., Park E.Y. Molybdenum trioxide quantum dot-encapsulated nanogels for virus detection by surface-enhanced raman scattering on a 2D substrate. ACS. Appl. Mater. Interfaces. 2021;13:27836–27844. doi: 10.1021/acsami.1c04793. [DOI] [PubMed] [Google Scholar]
  2. Bermejo-Pelaez D., Alastruey-Izquierdo A., Medina N., Capellan-Martin D., Bonilla O., Luengo-Oroz M., Rodriguez-Tudela J.L. Artificial intelligence-driven mobile interpretation of a semi-quantitative cryptococcal antigen lateral flow assay. IMa Fungus. 2024;15:27. doi: 10.1186/s43008-024-00158-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Carota A.G., Bonini A.., Urban M., Poma N., Vivaldi F.M., Tavanti A., Rossetti M., Rosati G., Merkoci A., Di Francesco F. Low-cost inkjet-printed nanostructured biosensor based on CRISPR/Cas12a system for pathogen detection. Biosens. Bioelectron. 2024;258 doi: 10.1016/j.bios.2024.116340. [DOI] [PubMed] [Google Scholar]
  4. Chan W.C., Nie S. Quantum dot bioconjugates for ultrasensitive nonisotopic detection. Science. 1998;281:2016–2018. doi: 10.1126/science.281.5385.2016. [DOI] [PubMed] [Google Scholar]
  5. Chen H.T., Zhang J.., Sun D.H., Ma L.N., Liu X.T., Cai X.P., Liu Y.S. Development of reverse transcription loop-mediated isothermal amplification for rapid detection of H9 avian influenza virus. J. Virol. Methods. 2008;151:200–203. doi: 10.1016/j.jviromet.2008.05.009. [DOI] [PubMed] [Google Scholar]
  6. Chen J., Liu Z., Li K., Li X., Xu L., Zhang M., Wu Y., Liu T., Wang X., Xie S., Xin A., Liao M., Jia W. Emergence of novel avian origin H7N9 viruses after introduction of H7-Re3 and rLN79 vaccine strains to China. Transbound. Emerg. Dis. 2022;69:213–220. doi: 10.1111/tbed.14401. [DOI] [PubMed] [Google Scholar]
  7. Chen Y., Liang W., Yang S., Wu N., Gao H., Sheng J., Yao H., Wo J., Fang Q., Cui D., Li Y., Yao X., Zhang Y., Wu H., Zheng S., Diao H., Xia S., Zhang Y., Chan K.H., Tsoi H.W., Teng J.L., Song W., Wang P., Lau S.Y., Zheng M., Chan J.F., To K.K., Chen H., Li L., Yuen K.Y. Human infections with the emerging avian influenza A H7N9 virus from wet market poultry: clinical analysis and characterisation of viral genome. Lancet. 2013;381:1916–1925. doi: 10.1016/S0140-6736(13)60903-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Cheng X., Yang X., Tu Z., Rong Z., Wang C., Wang S. Graphene oxide-based colorimetric/fluorescence dual-mode immunochromatography assay for simultaneous ultrasensitive detection of respiratory virus and bacteria in complex samples. J. Hazard. Mater. 2023;459 doi: 10.1016/j.jhazmat.2023.132192. [DOI] [PubMed] [Google Scholar]
  9. Craw P., Balachandran W. Isothermal nucleic acid amplification technologies for point-of-care diagnostics: a critical review. Lab. Chip. 2012;12:2469–2486. doi: 10.1039/c2lc40100b. [DOI] [PubMed] [Google Scholar]
  10. de Araujo W.R., Lukas H.., Torres M.D.T., Gao W., de la Fuente-Nunez C. Low-cost biosensor technologies for rapid detection of COVID-19 and future pandemics. ACS. Nano. 2024;18:1757–1777. doi: 10.1021/acsnano.3c01629. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Duracova M., Klimentova J., Fucikova A., Dresler J. Proteomic methods of detection and quantification of protein toxins. Toxins. (Basel) 2018;10:99. doi: 10.3390/toxins10030099. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Fan Y., Yixin X., Bin C., Liyan W., Fumin L., Hangping Y., Nanping W., Haibo W. Development of a colloidal gold-based immunochromatographic strip test using two monoclonal antibodies to detect H7N9 avian influenza virus. Virus. Genes. 2020;56:396–400. doi: 10.1007/s11262-020-01742-8. [DOI] [PubMed] [Google Scholar]
  13. Foubert A., Beloglazova N.V., De Saeger S. Comparative study of colloidal gold and quantum dots as labels for multiplex screening tests for multi-mycotoxin detection. Anal. Chim. Acta. 2017;955:48–57. doi: 10.1016/j.aca.2016.11.042. [DOI] [PubMed] [Google Scholar]
  14. Li J., Liu B., Tang X., Wu Z., Lu J., Liang C., Hou S., Zhang L., Li T., Zhao W., Fu Y., Ke Y., Li C. Development of a smartphone-based quantum dot lateral flow immunoassay strip for ultrasensitive detection of anti-SARS-CoV-2 IgG and neutralizing antibodies. Int. J. Infect. Dis. 2022;121:58–65. doi: 10.1016/j.ijid.2022.04.042. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Li X., Fengchun H., Li H., Gaozhe C., Lingyan Z., Yanbin L., Jianhan L. A sensitive immunoassay for simultaneous detection of foodborne pathogens using MnO(2) nanoflowers-assisted loading and release of quantum dots. Food Chem. 2020;322:126719. doi: 10.1016/j.foodchem.2020.126719. [DOI] [PubMed] [Google Scholar]
  16. Li X., Lin Q., Song J., Shen H., Zhang H., Li L.S., Li X., Du Z. Quantum-dot light-emitting diodes for outdoor displays with high stability at high brightness. Adv. Opt. Mater. 2019;8 doi: 10.1002/adom.201901145. [DOI] [Google Scholar]
  17. Li X., Wang J., Yi C., Jiang L., Wu J., Chen X., Shen X., Sun Y., Lei H. A smartphone-based quantitative detection device integrated with latex microsphere immunochromatography for on-site detection of zearalenone in cereals and feed. Sensor Actuat. B. 2019;290:170–179. doi: 10.1016/j.snb.2019.03.108. [DOI] [Google Scholar]
  18. Lifen L., Simin W., Fengxiang J., Hongbo Z., Chunping J., Gang L., Hui C., Qinghui J., Jianlong Z. Bead-based microarray immunoassay for lung cancer biomarkers using quantum dots as labels. Biosens. Bioelectron. 2016;80:300–306. doi: 10.1016/j.bios.2016.01.084. [DOI] [PubMed] [Google Scholar]
  19. Lin C., Liang S., Peng L.L., Li Y., Huang Z., Long N.V., Luo X., Liu J., Li Z., Li, Yang Y. Visualized SERS imaging of single molecule by Ag/black phosphorus nanosheets. Nanomicro Lett. 2022;14:75. doi: 10.1007/s40820-022-00803-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Lu H., Li W., Dong H., Wei M. Graphene quantum dots for optical bioimaging. Small. 2019;15 doi: 10.1002/smll.201902136. [DOI] [PubMed] [Google Scholar]
  21. Niemz A., Ferguson T.M., Boyle D.S. Point-of-care nucleic acid testing for infectious diseases. Trends Biotechnol. 2011;29:240–250. doi: 10.1016/j.tibtech.2011.01.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Niko H. Biofunctional quantum dots: controlled conjugation for multiplexed biosensors. ACS. Nano. 2011;5:5286–5290. doi: 10.1021/nn2023123. [DOI] [PubMed] [Google Scholar]
  23. Pan H., Dong Y., Gong L., Zhai J., Song C., Ge Z., Su Y., Zhu D., Chao J., Su S., Wang L., Wan Y., Fan C. Sensing gastric cancer exosomes with MoS2-based SERS aptasensor. Biosensors Bioelectr. 2022;215:114553. doi: 10.1016/j.bios.2022.114553. [DOI] [PubMed] [Google Scholar]
  24. Payungporn S., Chutinimitkul S., Chaisingh A., Damrongwantanapokin S., Buranathai C., Amonsin A., Theamboonlers A., Poovorawan Y. Single step multiplex real-time RT-PCR for H5N1 influenza A virus detection. J. Virol. Methods. 2006;131:143–147. doi: 10.1016/j.jviromet.2005.08.004. [DOI] [PubMed] [Google Scholar]
  25. Quesada-González D., Merkoçi A. Nanoparticle-based lateral flow biosensors. Biosensor Bioelectr. 2015;73:47–63. doi: 10.1016/j.bios.2015.05.050. [DOI] [PubMed] [Google Scholar]
  26. Rong M., Yang X., Huang L., Chi S., Zhou Y., Shen Y., Chen B., Deng X., Liu Z.Q. Hydrogen peroxide-assisted ultrasonic synthesis of BCNO QDs for anthrax biomarker detection. ACS. Appl. Mater. Interfaces. 2019;11:2336–2343. doi: 10.1021/acsami.8b21786. [DOI] [PubMed] [Google Scholar]
  27. Seder I., Jo A., Jun B.H., Kim S.J. Movable layer device for rapid detection of influenza a H1N1 virus using highly bright multi-quantum dot-embedded particles and magnetic beads. Nanomaterials. (Basel) 2022;12:284. doi: 10.3390/nano12020284. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Shi J., Zeng X., Cui P., Yan C., Chen H. Alarming situation of emerging H5 and H7 avian influenza and effective control strategies. Emerg. Microbes. Infect. 2023;12 doi: 10.1080/22221751.2022.2155072. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Vemula S.V., Zhao J.., Liu J., Wang X., Biswas S., Hewlett I. Current approaches for diagnosis of influenza virus infections in humans. Viruses. 2016;8:96. doi: 10.3390/v8040096. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Wang C., Shen W., Li Z., Xia X., Li J., Xu C., Zheng S., Gu B. 3D Film-like nanozyme with a synergistic amplification effect for the ultrasensitive immunochromatographic detection of Respiratory viruses. ACS. Nano. 2024;18:25865–25879. doi: 10.1021/acsnano.4c09513. [DOI] [PubMed] [Google Scholar]
  31. Wang C., Xiao R., Wang S., Yang X., Bai Z., Li X., Rong Z., Shen B., Wang S. Magnetic quantum dot based lateral flow assay biosensor for multiplex and sensitive detection of protein toxins in food samples. Biosensors Bioelectr. 2019;146:111754. doi: 10.1016/j.bios.2019.111754. [DOI] [PubMed] [Google Scholar]
  32. Wang C., Yang X., Zheng S., Cheng X., Xiao R., Li Q., Wang W., Liu X., Wang S. Development of an ultrasensitive fluorescent immunochromatographic assay based on multilayer quantum dot nanobead for simultaneous detection of SARS-CoV-2 antigen and influenza A virus. Sens. Actuators. B Chem. 2021;345 doi: 10.1016/j.snb.2021.130372. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Wang W., Yang X., Rong Z., Tu Z., Zhang X., Gu B., Wang C., Wang S. Introduction of graphene oxide-supported multilayer-quantum dots nanofilm into multiplex lateral flow immunoassay: a rapid and ultrasensitive point-of-care testing technique for multiple respiratory viruses. Nano Res. 2023;16:3063–3073. doi: 10.1007/s12274-022-5043-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Wen C.Y., Xie H..Y., Zhang Z.L., Wu L.L., Hu J., Tang M., Wu M., Pang D.W. Fluorescent/magnetic micro/nano-spheres based on quantum dots and/or magnetic nanoparticles: preparation, properties, and their applications in cancer studies. Nanoscale. 2016;8:12406–12429. doi: 10.1039/c5nr08534a. [DOI] [PubMed] [Google Scholar]
  35. Wu F., Yuan H., Zhou C., Mao M., Liu Q., Shen H., Cen Y., Qin Z., Ma L., Li L.S. Multiplexed detection of influenza A virus subtype H5 and H9 via quantum dot-based immunoassay. Biosens. Bioelectron. 2016;77:464–470. doi: 10.1016/j.bios.2015.10.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Wu X.X., Zhao L..Z., Tang S.J., Weng T.H., Wu W.G., Yao S.H., Wu H.B., Cheng L.F., Wang J., Hu F.Y., Wu N.P., Yao H.P., Zhang F.C., Li L.J. Novel pathogenic characteristics of highly pathogenic avian influenza virus H7N9: viraemia and extrapulmonary infection. Emerg. Microbes. Infect. 2020;9:962–975. doi: 10.1080/22221751.2020.1754135. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Xiang Q., Huang J., Huang H., Mao W., Ye Z. A label-free electrochemical platform for the highly sensitive detection of hepatitis B virus DNA using graphene quantum dots. RSC. Adv. 2018;8:1820–1825. doi: 10.1039/c7ra11945c. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Yang F., Dong D., Wu D., Zhu L., Liu F., Yao H., Wu N., Ye C., Wu H. A multiplex real-time RT-PCR method for detecting H5, H7 and H9 subtype avian influenza viruses in field and clinical samples. Virus. Res. 2022;309 doi: 10.1016/j.virusres.2021.198669. [DOI] [PubMed] [Google Scholar]
  39. Yang F., Xiao Y., Chen B., Wang L., Liu F., Yao H., Wu N., Wu H. Development of a colloidal gold-based immunochromatographic strip test using two monoclonal antibodies to detect H7N9 avian influenza virus. Virus. Genes. 2020;56:396–400. doi: 10.1007/s11262-020-01742-8. [DOI] [PubMed] [Google Scholar]
  40. Yang F., Xiao Y., Liu F., Yao H., Wu N., Wu H. Development of a monoclonal antibody-based antigen capture enzyme-linked immunosorbent assay for detection of H7N9 subtype avian influenza virus. J. Med. Virol. 2021;93:3939–3943. doi: 10.1002/jmv.26292. [DOI] [PubMed] [Google Scholar]
  41. Yang F., Xiao Y., Lu R., Chen B., Liu F., Wang L., Yao H., Wu N., Wu H. Generation of neutralizing and non-neutralizing monoclonal antibodies against H7N9 influenza virus. Emerg. Microbes. Infect. 2020;9:664–675. doi: 10.1080/22221751.2020.1742076. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Yetisen A.K., Akram M..S., Lowe C.R. Paper-based microfluidic point-of-care diagnostic devices. Lab. Chip. 2013;13:2210–2251. doi: 10.1039/c3lc50169h. [DOI] [PubMed] [Google Scholar]
  43. Yin X., Deng G., Zeng X., Cui P., Hou Y., Liu Y., Fang J., Pan S., Wang D., Chen X., Zhang Y., Wang X., Tian G., Li Y., Chen Y., Liu L., Suzuki Y., Guan Y., Li C., Shi J., Chen H. Genetic and biological properties of H7N9 avian influenza viruses detected after application of the H7N9 poultry vaccine in China. PLoS. Pathog. 2021;17 doi: 10.1371/journal.ppat.1009561. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Yu X., Wei L., Chen H., Niu X., Dou Y., Yang J., Wang Z., Tang Y., Diao Y. Development of colloidal gold-based immunochromatographic assay for rapid detection of goose parvovirus. Front. Microbiol. 2018;9:953. doi: 10.3389/fmicb.2018.00953. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Zhang W., Wu D., Wei J., Xiao G. A new method for the detection of the H5 influenza virus by magnetic beads capturing quantum dot fluorescent signals. Biotechnol. Lett. 2010;32:1933–1937. doi: 10.1007/s10529-010-0379-5. [DOI] [PubMed] [Google Scholar]
  46. Zhenli Q., Jian S., Yu H., Zhenzhen L., Kangyao Z., Shuzhen L., Dianping T. CdTe/CdSe quantum dot-based fluorescent aptasensor with hemin/G-quadruplex DNzyme for sensitive detection of lysozyme using rolling circle amplification and strand hybridization. Biosens. Bioelectron. 2016;87:18–24. doi: 10.1016/j.bios.2016.08.003. [DOI] [PubMed] [Google Scholar]
  47. Zhu X., Zhang Y., Liu M., Liu Y. 2D titanium carbide MXenes as emerging optical biosensing platforms. Biosens. Bioelectron. 2020;171 doi: 10.1016/j.bios.2020.112730. [DOI] [PubMed] [Google Scholar]
  48. Zongwen J., Niko H. Semiconductor quantum dots for in vitro diagnostics and cellular imaging. Trends Biotechnol. 2012;30:394–403. doi: 10.1016/j.tibtech.2012.04.005. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

mmc1.docx (13.1KB, docx)

Articles from Poultry Science are provided here courtesy of Elsevier

RESOURCES