English

• Carcinoembryonic antigen, signal amplification, ternary transition metal sulfides photoelectrochemical (PEC) immunoassay has gained significant attention due to its unique characteristics, such as high sensitivity, minimal background interference, and unambiguous input-output signal separation [1-5], which has been widely applied in the fields including ecological evaluation [6], food safety [7] and biological monitoring [8]. Despite some advances in recent years, design of stable photoelectrodes, innovative signal transduction mechanisms, and high-sensitivity detection protocols still remain ongoing goals [9-11]. Photoelectrically active materials are regarded as the cores of PEC sensing systems because their biocompatibility ensures the biorecognition on the surfaces [12]. Furthermore, the effective strategies of signal amplification can transform the biorecognition events into the detectable signals, thus improving the sensitivity of PEC assays [13, 14]. To this end, there is an urgent requirement to explore new photoactive materials with high electron transfer energy efficiency and new strategies for the signal amplification [15, 16].

  Transition metal sulfides have attracted a lot of attention in the field of PEC sensors, because of their exceptional optical and electrical characteristics [17, 18]. Among them, ternary transition metal sulfides are considered as a prospective class of semiconductor materials due to their unique advantages such as large specific surface area and narrow band gap, which exhibit excellent photoelectric properties and good structural stability [19, 20]. Favorably, Zn_xCd_1-xS ternary solid solution introduces ZnS into the CdS lattice, combining the advantages of ZnS and CdS. Simultaneously, its band gap positions, which impact the photoelectric reactivity, are readily manipulated by varying the value of x [21, 22]. Nevertheless, the quick electron-hole complexation rate of the single ZnCdS semiconductor severely restrict photovoltaic conversion efficiency. A number of methods, such as elemental doping, morphological control, and heterostructures, have been put forth to address these issues [23-27]. CuS is an important p-type semiconductor with narrow band gap and exemplary optical properties [28-30]. The incorporation of CuS into ZnCdS extends the light absorption range from UV to visible and near-infrared light, thereby increasing the light absorption rate, effectively promoting photogenerated electron/hole separation, and prolonging charge lifetime [31].

  Liposome-mediated PEC immunoassays integrate the PEC biosensing with the functionalized liposomes to achieve signal amplification strategies by exerting synergistic effects, showing creative value with great future benefits and development potential [32-34]. The excellent modifiability and maneuverability exhibited by liposome-assisted bioanalysis in amplifying the photocurrent response is attributed to their suitable biocompatibility and functionalized surfaces. Among the design strategies for the functionalized of liposome surfaces, antibodies are of great interest owing to their capacity to bind specifically to antigens and endogenous immune receptors and play a vital part in the application of liposomes in bio-immune sensing analysis [35-37]. In this procedure, the functionalized liposomes serve as bio-signal amplification components by hydrolyzing in particular circumstances to release a great number of encapsulating small-molecules, which in turn boost the signal intensity of the assay. For example, our group designed a PEC immunosensing platform based on a high-entropy effect (ZnCdFeMnCu)_xS photoactive material and dopamine-loaded liposomes as signal amplifiers, thereby enabling ultrasensitive detection of prostate-specific antigen [38]. Gao et al. constructed a liposome-mediated PEC immunoassay that loaded alkaline phosphatase onto liposomes and generated ZnInS/SnS₂ heterojunctions in situ, which were enzymatically degraded to generate H₂S for extremely accurate detection of heart-type fatty acid binding protein [39]. Therefore, our work was motivated by using liposomes as signal-amplifying carriers for the sensitive detection of CEA in the immunoassays.

  Herein, we developed a liposome-mediated signal-off PEC immunosensing platform to accomplish extremely accurate detection of CEA. As illustrated in Scheme 1, the process primarily included immunological response, liposome capture, and dopamine release. The synthesized CuS/ZnCdS composites modified F-doped tin oxide (FTO) electrode was acted as photoelectric signal sensing element to detect the photocurrent. Monoclonal antibody (mAb₁) was capable of specifically recognizing CEA and serves as an immunoreactive site in 96-well plates. The dopamine-loaded liposomes (DLL) was modified on a polyclonal antibody (pAb₂) to serve as the detection antibody. In the presence of the target CEA, an immune complex was formed on 96-well plates via the traditionally sandwiched immunological response. The dopamine produced from liposome cleavage was diffused in the solution upon the addition of Triton X-100, which reduced the photocurrent and permits sensitive detection of CEA. This study advances the development of PEC biosensors, which are expected to be more widely used in the future to detect other disease markers.

  Scheme 1

  

  Scheme 1.  Schematic representation of CuS/ZnCdS composites-based PEC immunoassay using dopamine-loaded liposomes (CEA: carcinoembryonic antigen; mAb₁: anti-CEA capture antibody; pAb₂: anti-CEA secondary antibody; DLL: dopamine-loaded liposomes).

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  To evaluate the morphological composition and the microstructure of the as-prepared materials, using transmission electron microscopy (TEM), and high-resolution TEM (HRTEM) to analyze the samples. According to the TEM image of CuS/ZnCdS composites (Fig. 1A), the CuS was evenly distributed on the surface of the ZnCdS. The HRTEM images (Figs. 1B and C) showed that the CuS/ZnCdS composites had lattice distances of 0.32 nm and 0.189 nm, respectively. These correspond to the (002) facet of ZnCdS and the (102) facet of CuS. The uniform distribution of the Cu, Zn, Cd, and S elements in CuS/ZnCdS composites was demonstrated by the element mapping patterns (Fig. 1D). Then, X-ray powder diffraction (XRD) was used to analyze crystal structure of the composites. As shown in Fig. 1E, the three diffraction peaks of the ZnCdS were observed at 27.08°, 44.83°, and 53.43°, which could be correlated with the (002), (110), and (112) diffraction crystal planes of ZnCdS (JCPDS No. 40–0836). The three diffraction peaks of CuS were observed at 31.82°, 35.06°, and 47.99°, corresponding to the (103), (104), and (110) diffraction crystal planes of CuS (JCPDS No. 79–2321). The diffraction peaks of the prepared precursor materials are clearly discernible, thereby attesting to their high degree of crystallinity. In the case of the CuS/ZnCdS composites, the peaks observed in the spectra are those of the precursor material binding, and the absence of any additional impurity peaks, further indicating that CuS/ZnCdS composites was successfully fabricated.

  Figure 1

  

  Figure 1.  (A) TEM image and (B, C) HRTEM images of CuS/ZnCdS composites. (D) Elemental maps showing the distribution of Cu, Zn, Cd, and S in CuS/ZnCdS composites. (E) XRD patterns of CuS, ZnCdS and CuS/ZnCdS composites.

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  The utilization of proper signal amplification procedures, and the exploration of outstanding performance photoactive materials, was key to the development of efficient and sensitive PEC immunoassay analytical methods. For the designed PEC sensor, the ability of CuS/ZnCdS composites to produce a photocurrent signaling effect on dopamine is also crucial for the success of the experiment. In response to this question, the photocurrent measurements on CuS, ZnCdS, and CuS/ZnCdS composites were carried out to confirm the PEC capabilities of the prepared composites (Fig. 2A). The photocurrent response of the CuS/ZnCdS composites was greatly enhanced under irradiation compared with the two precursors. This evidence demonstrated that the CuS/ZnCdS composites was capable of efficiently segregating the photogenerated carriers, thereby enhancing the photocurrent responsiveness. The photocurrents of CuS/ZnCdS composites were found to be significantly attenuated by the addition of dopamine. This indicated that dopamine could act as a hole-trapping agent and achieve the effect of reducing photocurrents by depleting photogenerated holes.

  Figure 2

  

  Figure 2.  (A) Photocurrent responses of (a) CuS, (b) ZnCdS, (c, d) CuS/ZnCdS composites before and after adding dopamine. (B) UV–vis diffuse spectra, (C) XPS valence spectra, and (D) TEM image of dopamine-loaded liposomes.

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  To determine the energy band relationships of the CuS/ZnCdS composites, as presented in Fig. 2B, the optical characteristics of our composites were investigated through UV–vis diffuse reflectance spectroscopy, the light absorption intensity of the composites was further enhanced compared with ZnCdS, indicating that the CuS/ZnCdS composites exhibit a broad spectral response and could be validly used in the area of PEC. The band gap energies of pure CuS, ZnCdS, and CuS/ZnCdS composites were determined using the Tauc plot. Fig. S2 (Supporting information) illustrates that the band gap values (E_g) of the pure CuS and ZnCdS were approximately 1.46 eV and 2.45 eV, respectively. In comparison with ZnCdS, the E_g of the CuS/ZnCdS composites was gradually reduced due to the addition of CuS, which was attributed to the tight interface interaction between CuS and ZnCdS affecting the electronic properties of ZnCdS. While exposed to visible light, electrons were able to move more easily from the valence band to the conduction band owing to the narrower forbidden bandwidth, thus producing more photocurrent. To ascertain the energy band structure (Fig. 2C), the valence band potential (E_VB-XPS) of CuS and ZnCdS was obtained by the VB-XPS method. The valence band potentials (E_VB-XPS) of CuS and ZnCdS were calculated to be 1.28 eV and 1.62 eV, respectively. To further ascertain the precise band structure, the E_{VB, NHE} of the correspondent standard hydrogen electrode may be computed as follows: E_{VB, NHE} = φ + E_VB-XPS - 4.44 eV, and the value of the work function of the instrument (φ) was defined as 4.60 eV [40]. Therefore, the E_{VB, NHE} of CuS, and ZnCdS were calculated to be 1.44 eV and 1.78 eV. Afterward, utilizing the formula E_CB = E_VB - E_g, the conduction band potentials (E_CB) of CuS and ZnCdS were computed to be −0.67 eV and −0.02 eV, respectively. As depicted in Fig. S3 (Supporting information), the E_{OX, NHE} of dopamine was found to be 1.193 V by cyclic voltammogram measurements, which was lower than the values of E_{VB, NHE} for ZnCdS, and CuS, verifying that the oxidation potential of the dopamine molecule could be matched with CuS/ZnCdS composites. It is shown that holes on the VB of both ZnCdS and CuS could oxidize dopamine, thereby reducing the photocurrent (Fig. S5 in Supporting information).

  Due to good photocurrent response of CuS/ZnCdS composites to dopamine, dopamine was used as a signal tag loaded in liposomes to amplify the signal. The DLL were characterized by dynamic light scattering (DLS) and TEM. The DLL exhibited an average diameter of around 250 nm and a polydispersity index (PDI) of 0.251 as determined by DLS (Fig. 2D, inset). The TEM plot presented in Fig. 2D shows that the DLL were quasi-spherical in shape, measuring around 130 ± 10 nm in diameter and possessed an entire capsule wall, confirming the success of establishing a standard liposome vesicle structure.

  Based on the successful synthesis of DLL, we performed a feasibility analysis of PEC immunoassay in this study (Fig. S4 in Supporting information). Firstly, we conducted photocurrent tests on blank FTO substrates as control experiments with negligible photocurrent response values (curve a). Then, for the immunoassay, the experiment was divided into two cases in the presence or absence of CEA, and the consistent procedure was repeated for the assay. The photocurrent signals were significantly different between curve b (without CEA) and curve c (with 5.0 ng/mL CEA). When the target CEA was present, DLL were confined in 96-well microplates to undergo a conventional sandwich immunoreaction to form an immune compound. Triton X-100 was subsequently incorporated to lyse the liposome, releasing dopamine that was then distributed throughout the solution to lower the photocurrent and enable CEA-sensitive detection. Therefore, the addition of the target CEA to the system enabled a quantitative analysis process in the form of attenuation of the photocurrent.

  The performance and sensitivity of the CuS/ZnCdS composites-based PEC immunosensing platform was investigated using standard samples with different concentrations of CEA. As illustrated in Fig. 3A, the photocurrent response value exhibited a decreasing trend with increasing CEA concentration. In the meantime, there was an ideal linear relationship between the photocurrent signal recorded by the PEC immunoassay platform and the CEA concentration within the logarithmic range of 0.1–50 ng/mL. The equation for the linear regression equation was I (µA) = 0.235 × logC_CEA - 1.031 (ng/mL, R² = 0.996, n = 7) (Fig. 3B). The limit of detection (LOD) for CEA was calculated to 31.6 pg/mL (S/N = 3), which was compared with other similar strategies (Table S1 in supporting information). Since the normal threshold of human serum CEA concentration in clinical testing was 5.0 ng/mL [41], the PEC immunoassay could meet the requirements of practical applications.

  Figure 3

  

  Figure 3.  (A) Monitoring photocurrent intensity of gradient concentrations (0, 0.1, 0.3, 1, 2, 5, 15, 25, 50 ng/mL) of CEA based on the PEC immunoassay. (B) Linear relationship between photocurrent intensity and logarithm of CEA concentration. (C) Stability of the PEC immunoassay platform for the detection of 0.3 ng/mL CEA. (D) Corresponding selectivity of the constructed PEC immunoassay for 50 ng/mL of CEA by comparing with interfering proteins added at 5 µg/mL level. The error bars indicate the standard deviations obtained from three measurements.

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  The applicability of a PEC immunosensing platform to actual clinical diagnostics depends on the stability and specificity of the platform. In this case, the photocurrent response was evaluated experimentally over the course of eight on/off cycles, and the relative standard deviation was calculated to be 7.79% (Fig. 3C). The photocurrent levels were found to have stabilized relatively throughout the cycle, with no discernible changes. To further investigate the selectivity of the developed PEC immunoassay, other interfering biological proteins such as bovine serum albumin (BSA), alpha-fetoprotein (AFP), and prostate specific antigen (PSA) that may be present in the serum samples were selected for interference experiments. As illustrated in Fig. 3D, the CEA detector exhibited lower photocurrent values than other interfering biological proteins., regardless of whether it was used alone or in combination with the target detector. These results indicated that the PEC immunoassay had good selectivity in detecting target CEA.

  To determine the accuray of CuS/ZnCdS composites-based PEC immunoassay for analysis of real samples, the commercial CEA ELISA kit was used as a reference to examine six human serum samples from Fujian Cancer Hospital. Prior to measurement, these serum specimens were initially centrifuged for 5 min at 5000 g to remove the possible precipitates, and then determined by using commercialized human CEA ELISA kit and PEC immunoassay, respectively. Table 1 shows that the designed platform was evaluated using t-test, and the calculated the experimental values (t_exp) were all lower than the critical value (t_crit) of 2.78 (t_{crit, [0.05, 4]} = 2.78), proving that a notable absence of discernible variation was observed between the two assays. Hence, the developed PEC immunoassay was highly reliable and could be utilized as a substitute methodology in the clinical detection of CEA.

  Table 1

  

  Table 1.  Comparison of the analytical results between the PEC immunoassay and the commercial CEA ELISA kit in human serum samples.

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  Sample No.	Method accuracy [Conc.: mean ± SD (RSD), ng/mL, n = 3]		texp
  	PEC immunoassay	CEA ELISA
  1	1.82 ± 0.12 (6.59%)	1.58 ± 0.15 (9.49%)	2.16
  2	21.84 ± 2.05 (9.38%)	23.72 ± 2.34 (9.87%)	1.05
  3	12.62 ± 1.21 (9.59%)	13.48 ± 1.16 (8.61%)	0.88
  4	19.54 ± 0.97 (4.96%)	20.26 ± 0.76 (3.75%)	1.01
  5	5.93 ± 0.54 (9.11%)	5.61 ± 0.47 (8.38%)	0.77
  6	0.79 ± 0.06 (7.59%)	0.88 ± 0.07 (7.95%)	1.69

  In summary, an innovative PEC immunosensing platform was established for the sensitive detection of CEA, on the basis of good photocurrents of CuS/ZnCdS photoactive materials and by a dopamine-loaded liposomal photo-induced reaction system to amplify the photocurrent signals. The experimental results demonstrated that the as-obtained PEC sensor exhibited efficient photocathodic responses and superior analytical performance for CEA with good stability and high selectivity. Compared to previous studies, the liposomal PEC immunoassay offers specific benefits and tantalizing potential, opening new perspectives for highly sensitive PEC bioassays.

  Ethical statement

  All experiments were performed in accordance with the Guidelines of Fuzhou University (China), and approved by the Ethics Committee at Fuzhou University (China). Informed consents were obtained from human participants of this study.

  Declaration of competing interest

  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.

  CRediT authorship contribution statement

  Shuo Tian: Writing – original draft, Methodology, Investigation, Conceptualization. Shuyun Chen: Visualization, Software, Formal analysis, Data curation. Yunsen Wang: Writing – original draft, Visualization, Investigation, Formal analysis. Dianping Tang: Writing – review & editing, Supervision, Project administration, Funding acquisition.

  Acknowledgment

  Authors acknowledge the financial support from the National Natural Science Foundation of China (Nos. 22274022 and 21874022).

  Supplementary materials

  Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.cclet.2024.110418.

  
  
• 1. [1]

     Z. Hu, Y. Xu, H. Wang, G. Fan, X. Luo, Chin. Chem. Lett. 33 (2022) 4750–4755.

  2. [2]

     Y. Chen, Y. Jia, X. Zhu, et al., ACS Sens. 9 (2024) 2429–2439. doi: 10.1021/acssensors.4c00108

  3. [3]

     F. Chen, X. Fu, X. Yu, et al., Anal. Chem. 95 (2023) 9052–9059. doi: 10.1021/acs.analchem.3c01401

  4. [4]

     H. Wang, L. Guo, Q. Du, et al., Anal. Chem. 96 (2024) 581–589. doi: 10.1021/acs.analchem.3c04931

  5. [5]

     P. Yan, Y. Jin, L. Xu, et al., Biosens. Bioelectron. 206 (2022) 114144.

  6. [6]

     L. Li, J. Chen, C. Xiao, et al., Chin. Chem. Lett. 34 (2023) 107904.

  7. [7]

     M. Sobiech, P. Luliński, P. Wieczorek, M. Marć, TrAC Trends Anal. Chem. 142 (2021) 116306.

  8. [8]

     L. Tao, Y. Kong, Y. Xiang, et al., Chin. Chem. Lett. 34 (2023) 107481.

  9. [9]

     X. Ye, X. Wang, Y. Kong, et al., Angew. Chem. Int. Ed. 60 (2021) 11774–11778. doi: 10.1002/anie.202101468

  10. [10]

      Y. Gao, Z. Yu, L. Huang, et al., Anal. Chem. 95 (2023) 9130–9137. doi: 10.1021/acs.analchem.3c01690

  11. [11]

      R. Zeng, W. Wang, G. Cai, et al., Nano Energy 74 (2020) 104931.

  12. [12]

      Q. Zhou, D. Tang, TrAC Trends Anal. Chem. 124 (2020) 115814.

  13. [13]

      A. Victorious, S. Saha, R. Pandey, L. Soleymani, Angew. Chem. Int. Ed. 60 (2021) 7316–7322. doi: 10.1002/anie.202014329

  14. [14]

      L. Kong, S. Lv, Z. Qiao, et al., Biosens. Bioelectron. 207 (2022) 114188.

  15. [15]

      Q. Zeng, Q. Wei, J. Luo, et al., Chin. Chem. Lett. 33 (2022) 2954–2958.

  16. [16]

      X. Wan, D. Tang, H. Wang, X. Wang, D. Tang, Sens. Actuators B 412 (2024) 135798.

  17. [17]

      H. Wang, C. Li, J. Zhang, et al., Adv. Funct. Mater. 34 (2024) 2315917.

  18. [18]

      Y. Lei, L. Zhang, W. Xu, et al., Nano Res. 15 (2022) 6054–6061. doi: 10.1007/s12274-022-4304-8

  19. [19]

      W. Li, J. Li, Z. Liu, et al., Rare Metals 43 (2024) 533–542. doi: 10.1007/s12598-023-02419-5

  20. [20]

      X. Zhang, G. Yang, C. Han, et al., Colloid. Surface A 664 (2023) 131184.

  21. [21]

      X. Zhou, J. Wu, Y. Xiao, et al., Sep. Purif. Technol. 311 (2023) 123243.

  22. [22]

      R. Zeng, T. Liu, M. Qiu, et al., J. Am. Chem. Soc. 146 (2024) 9721–9727. doi: 10.1021/jacs.3c13827

  23. [23]

      B. Diroll, B. Guzelturk, H. Po, et al., Chem. Rev. 123 (2023) 3543–3624. doi: 10.1021/acs.chemrev.2c00436

  24. [24]

      J. Kosco, S. Gonzalez-Carrero, C. Howells, et al., Nat. Energy 7 (2022) 340–351. doi: 10.1038/s41560-022-00990-2

  25. [25]

      M. Sawatzki-Park, S. Wang, H. Kleemann, K. Leo, Chem. Rev. 123 (2023) 8232–8250. doi: 10.1021/acs.chemrev.2c00844

  26. [26]

      Y. Zhou, S. Lv, X. Wang, L. Kong, S. Bi, Anal. Chem. 94 (2022) 14492–14501. doi: 10.1021/acs.analchem.2c03885

  27. [27]

      Y. Chen, D. Deng, P. Yan, et al., Sens. Actuators B 395 (2023) 134501.

  28. [28]

      Q. Zhang, A. Mirzaei, Y. Wang, et al., Appl. Catal. B Environ. 317 (2022) 121792.

  29. [29]

      Q. Chen, M. Zhang, J. Li, et al., Chem. Eng. J. 389 (2020) 124476.

  30. [30]

      H. Wang, G. Yang, S. Wu, et al., Sci. Total Environ. 784 (2021) 147221.

  31. [31]

      Q. Mao, J. Chen, H. Chen, et al., J. Mater. Chem. A 7 (2019) 8472–8484. doi: 10.1039/c8ta12526k

  32. [32]

      F. Chen, D. Han, H. Chen, Anal. Chem. 92 (2020) 8450–8458. doi: 10.1021/acs.analchem.0c01162

  33. [33]

      H. Zheng, Z. Wang, G. Luo, et al., Sens. Actuators B 411 (2024) 135744.

  34. [34]

      M. Zhou, H. Huang, X. Zhao, et al., Anal. Chem. 94 (2022) 13913–13920. doi: 10.1021/acs.analchem.2c02827

  35. [35]

      C. Wang, X. Lan, L. Zhu, et al., Small 20 (2024) 2309031.

  36. [36]

      C. Tzror-Azankot, O. Betzer, T. Sadan, et al., ACS Nano 15 (2021) 1301–1309. doi: 10.1021/acsnano.0c08530

  37. [37]

      D. Blanken, D. Foschepoth, A. Serrão, C. Danelon, Nat. Commun. 11 (2020) 4317.

  38. [38]

      X. Wan, R. Zeng, X. Wang, et al., Biosens. Bioelectron. 237 (2023) 115535.

  39. [39]

      Y. Gao, Y. Zeng, X. Liu, D. Tang, Anal. Chem. 94 (2022) 4859–4865. doi: 10.1021/acs.analchem.2c00283

  40. [40]

      X. Li, B. Kang, F. Dong, et al., Nano Energy 81 (2021) 105671.

  41. [41]

      V. Singh, S. Kumar, S. Pandey, et al., Biosens. Bioelectron. 105 (2018) 173–181.

• 

  Scheme 1  Schematic representation of CuS/ZnCdS composites-based PEC immunoassay using dopamine-loaded liposomes (CEA: carcinoembryonic antigen; mAb₁: anti-CEA capture antibody; pAb₂: anti-CEA secondary antibody; DLL: dopamine-loaded liposomes).

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  Figure 1  (A) TEM image and (B, C) HRTEM images of CuS/ZnCdS composites. (D) Elemental maps showing the distribution of Cu, Zn, Cd, and S in CuS/ZnCdS composites. (E) XRD patterns of CuS, ZnCdS and CuS/ZnCdS composites.

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  Figure 2  (A) Photocurrent responses of (a) CuS, (b) ZnCdS, (c, d) CuS/ZnCdS composites before and after adding dopamine. (B) UV–vis diffuse spectra, (C) XPS valence spectra, and (D) TEM image of dopamine-loaded liposomes.

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  Figure 3  (A) Monitoring photocurrent intensity of gradient concentrations (0, 0.1, 0.3, 1, 2, 5, 15, 25, 50 ng/mL) of CEA based on the PEC immunoassay. (B) Linear relationship between photocurrent intensity and logarithm of CEA concentration. (C) Stability of the PEC immunoassay platform for the detection of 0.3 ng/mL CEA. (D) Corresponding selectivity of the constructed PEC immunoassay for 50 ng/mL of CEA by comparing with interfering proteins added at 5 µg/mL level. The error bars indicate the standard deviations obtained from three measurements.

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  Table 1.  Comparison of the analytical results between the PEC immunoassay and the commercial CEA ELISA kit in human serum samples.

  Sample No.	Method accuracy [Conc.: mean ± SD (RSD), ng/mL, n = 3]		texp
  	PEC immunoassay	CEA ELISA
  1	1.82 ± 0.12 (6.59%)	1.58 ± 0.15 (9.49%)	2.16
  2	21.84 ± 2.05 (9.38%)	23.72 ± 2.34 (9.87%)	1.05
  3	12.62 ± 1.21 (9.59%)	13.48 ± 1.16 (8.61%)	0.88
  4	19.54 ± 0.97 (4.96%)	20.26 ± 0.76 (3.75%)	1.01
  5	5.93 ± 0.54 (9.11%)	5.61 ± 0.47 (8.38%)	0.77
  6	0.79 ± 0.06 (7.59%)	0.88 ± 0.07 (7.95%)	1.69

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