Rapid Electrochemical Impedance Detection of the Mi^a Antigen on Red Blood Cells

Abstract

The Mi^a antigen on red blood cells (RBCs) of the MNS blood group system is clinically significant in Southeast Asian populations and is associated with a risk of alloimmunization and hemolytic transfusion reactions. Conventional serological typing for Mi^a requires large reagent and sample volumes and subjective interpretation, highlighting the need for alternative analytical approaches. In this study, a novel simple electrochemical impedance spectroscopy-based immunoassay was developed for Mi^a antigen detection using a “mix-and-drop” strategy involving packed RBCs and specific anti-Mi^a antibodies on a screen-printed carbon electrode (SPCE). The analytical signal was defined as the change in charge transfer resistance (ΔR _ct) measured on an SPCE in the presence of a ferri/ferrocyanide redox probe. Key assay parameters, including the RBC:antibody volume ratio, antibody dilution, and incubation time, were systematically optimized to maximize ΔR _ct in the agglutinating and non-agglutinating samples. Under optimized conditions, Mi^a -positive agglutination samples produced a distinct and reproducible increase in impedance, attributed to the formation of hemagglutination, which impeded electron transfer at the electrode interface. The assay was evaluated using 232 clinical blood samples (122 Mi^a-positive and 110 Mi^a-negative), containing internal (70%) and external (30%) validation sets. The ΔR _ct values for Mi^a-positive and Mi^a-negative samples demonstrated significant discrimination between groups (Mann-Whitney U test, p < 0.0001). Receiver operating characteristic analysis revealed excellent diagnostic performance (p < 0.0001, AUC = 1.0), with an optimal ΔR _ct cutoff of 71.10 kΩ, yielding 100% sensitivity and specificity within the internal and external validation sets. This label-free electrochemical assay requires low volumes of reagent and sample and is a rapid and practical approach for screening for the Mi^a antigen without electrode surface modification, supporting its potential use in pre-transfusion blood testing.

1. Introduction

The MNS blood group system (International Society of Blood Transfusion; ISBT 002) is a genetically diverse and clinically significant blood group system comprising 50 recognized antigens (MNS1–MNS50), primarily encoded by the GYPA and GYPB genes. Among these, the Mi^a antigen on red blood cells (RBCs) belongs to the Miltenberger subsystem and arises from hybrid glycophorin structures formed through genetic recombination events. Although Mi^a is rare in Caucasian populations, it is markedly more prevalent in Asian populations, making it a clinically important antigen in transfusion medicine within this region.

The clinical significance of the Mi^a antigen stems from its ability to induce anti-Mi^a alloantibody production in Mi^a-negative individuals following exposure to Mi^a-positive RBCs through transfusion or pregnancy. Anti-Mi^a antibodies are predominantly IgM in nature and may occur as clinically significant IgG antibodies that react at 37 °C, causing hemolytic transfusion reactions (HTRs) and hemolytic disease of the fetus and newborn (HDFN). Epidemiological studies have reported Mi^a antigen frequencies of approximately 6.28% in Chinese blood donors from Hong Kong, approximately 4.66% in Taiwan, and up to 17.97% in northeast Thai donors, with predicted frequencies of 4.45–9.33% among Thai regional cohorts, indicating its clinical relevance in Southeast Asian transfusion medicine. − This population-specific distribution results in a disproportionately high occurrence of anti-Mi^a antibodies in Asian transfusion services, where they are among the most frequently detected clinically significant alloantibodies during pretransfusion testing.

Detection of the Mi^a antigen is currently performed using serological methods (standard tube- or column-agglutination tests). Although tube agglutination is widely used for Mi^a phenotyping in Southeast Asia because of its low cost and clear reaction. Moreover, standard tube tests require large reagent and sample volumes. Column agglutination technology is another common technique for detecting RBC antigens. However, the gel cards are expensive, and specialized equipment is needed. These limitations highlight the need for alternative analytical approaches for Mi^a phenotyping.

Electrochemical detection strategies have gained increasing attention in clinical diagnostics because of their sensitivity, low instrumentation cost, and potential for miniaturization. Electrochemical impedance spectroscopy (EIS), in particular, has emerged as a powerful label-free technique for monitoring biomolecular interactions through changes in interfacial electron-transfer properties. EIS is also well suited for monitoring RBC aggregation, as electrical signals can readily penetrate blood and biological tissues, making EIS particularly attractive for rapid point-of-care diagnostic applications. However, most reported immunoassays for blood typing rely on electrode surface modification and biomolecule immobilization, increasing assay complexity and potential variability. This highlights the need for simplified approaches that minimize the number of assay steps while maintaining sufficient diagnostic discrimination for routine transfusion medicine applications. ,

In this study, we report a novel “mix-and-drop″ EIS assay for Mi^a antigen detection directly from blood samples. The proposed method exploits solution-phase antigen–antibody interactions, allowing immunocomplex formation prior to electrochemical measurement. These complexes induce pronounced changes in the charge transfer resistance (ΔR_ct) upon contact with an unmodified electrode surface, enabling differentiation between the Mi^a-positive and -negative samples without electrode functionalization. This simplified electrochemical strategy addresses the clinically relevant need for Mi^a screening in populations where the MNS blood-group system may pose significant transfusion risk.

2. Experimental Details

2.1. Sample Collection and Ethical Considerations

Ethylenediaminetetraacetic acid (EDTA)-anticoagulated whole blood samples were collected as leftover samples from 232 individual donors (122 Mi^a-positive and 110 Mi^a-negative blood samples) at the Central Blood Bank, Faculty of Medicine, Khon Kaen University, where they had been previously used for routine diagnostic testing, which was approved by the Khon Kaen University Ethics Committee (HE694004). All leftover samples were tested and identified as Mi^a-positive and -negative samples by the standard tube test method, and no additional blood was collected from the donors.

2.2. Materials and Apparatus

All the chemicals used in this study were of analytical grade and were prepared in accordance with standard laboratory procedures. Human monoclonal anti-Mi^a antibody (IgM) was obtained from the Thai Red Cross-National Blood Service Center. Normal saline solution (NSS) was prepared from 0.9% sodium chloride (Sigma–Aldrich, USA) and used for washing steps and as a negative control solution. Screen-printed carbon electrodes (SPCEs) were obtained from Quasense (Bangkok, Thailand). EIS measurements were carried out using a PalmSens4 potentiostat (Palm Sens BV Co., Netherlands) operated using PSTrace version 5.9. EIS measurements were conducted over a frequency range of 100 kHz to 0.1 Hz, and Nyquist plots were fitted to a Randles equivalent circuit model using PSTrace software to extract R_ct values, which served as the primary analytical parameter for evaluating Mi^a antigen detection. All the experiments employed disposable SPCEs composed of a 2.5 mm diameter carbon working electrode, a carbon counter electrode, and a built-in Ag/AgCl reference electrode. The electrochemical redox probe consisted of 5 mM potassium ferri/ferrocyanide ([Fe­(CN)₆]^3–/^4–) and 0.1 M potassium chloride (KCl) prepared in NSS. NSS was used to provide an isotonic environment and prevent RBC lysis, whereas KCl served as a supporting electrolyte to increase the ionic conductivity and stabilize the electrochemical measurements.

2.3. Optimization of Analytical Parameters

The optimal condition was performed with single independent Mi^a-positive and single independent Mi^a-negative samples. The optimal measurement conditions were determined by evaluating three parameters: (1) the volume ratio between RBCs and anti-Mi^a antibody (1:2, 1:5, and 1:10), (2) the antibody dilution (undiluted, 1:2, and 1:4), and (3) the incubation time prior to impedance measurement (0, 5, 10, and 15 min). The RBCs used in this study were packed red cells collected after the removal of plasma and buffy coat. Each condition was tested in triplicate for both test and control samples. ΔR_ct was calculated according to eq :

$${\Delta R}_{ct}={\Delta R}_{ct1}-{\Delta R}_{ct0}$$ 1

where R_ct0 and R_ct1 represent the baseline and target detection values, respectively. The agglutination condition corresponded to Mi^a-positive RBCs incubated with anti-Mi^a antibody, whereas the non-agglutination controls consisted of Mi^a-positive RBCs incubated with NSS and Mi^a-negative RBCs incubated with anti-Mi^a antibody. The net signal was then calculated, as shown in eqs and , respectively.

Net signal relative to the NSS control

$$\mathrm{\Delta }{R}_{ct}^{\mathrm{net},\mathrm{NSS}}=\mathrm{\Delta }{R}_{ct}^{({Mi}^a\mathrm{‐positive\; RBCs}+\mathrm{anti‐}{Mi}^a\mathrm{antibody})}-\mathrm{\Delta }{R}_{ct}^{{(Mi}^a\mathrm{‐positive\; RBCs}+\mathrm{NSS})}$$ 2

Net signal relative to the Mi^a-negative control

$$\mathrm{\Delta }{R}_{ct}^{\mathrm{net},{Mi}^{a-}}=\mathrm{\Delta }{R}_{ct}^{{(Mi}^a\mathrm{‐positive\; RBCs}+\mathrm{anti‐}{Mi}^a\mathrm{antibody})}-\mathrm{\Delta }{R}_{ct}^{{(Mi}^a\mathrm{‐negative\; RBCs}+\mathrm{ant‐i}{Mi}^a\mathrm{antibody})}$$ 3

2.3.1. Optimization of RBC: Antibody Volume Ratio

To determine the appropriate RBC: antibody volume ratio, undiluted anti-Mi^a antibody was added to test tubes at volumes of 44 μL, 55 μL, and 60 μL, corresponding to ratios of 1:2, 1:5, and 1:10, respectively, while the same volumes of NSS were added to the negative control tubes. The RBCs used in this experiment were packed red cells collected after the removal of plasma and buffy coat. Mi^a-positive RBCs were then slowly dispensed at 22 μL (1:2), 11 μL (1:5), and 6 μL (1:10) into the antibody and NSS, respectively, while Mi^a-negative RBCs were slowly added into different antibody volume ratios. Afterward, redox solution (100 μL) was added to each tube and gently mixed by pipetting up and down, after which 166 μL of the final mixture was dispensed onto the SPCE surface for a 5 min reaction prior to EIS measurement.

2.3.2. Optimization of Antibody Dilution

To determine the appropriate antibody dilution, anti-Mi^a antibody was prepared at three dilution levels, namely, undiluted, 1:2, and 1:4, using NSS as the diluent. 55 μL of each antibody dilution was transferred into separate test tubes, while 55 μL of NSS was added to the negative control tubes. The Mi^a-positive and -negative RBCs used in this experiment were packed red cells collected after the removal of plasma and buffy coat. Subsequently, 11 μL of Mi^a-positive RBCs was added to each tube containing anti-Mi^a antibody or NSS. In parallel, 11 μL of Mi^a-negative RBCs was added to tubes containing each antibody dilution. Following incubation, 100 μL of redox solution was added to each tube and gently mixed by pipetting up and down. The final mixture (166 μL) was dispensed onto the SPCE surface. After a 5 min reaction period, EIS measurements were performed.

2.3.3. Optimization of Incubation Time

To determine the appropriate incubation time, 55 μL of anti-Mi^a antibody (1:4 dilution) was mixed with 11 μL of Mi^a-positive or Mi^a-negative RBCs, while 55 μL of NSS was mixed with 11 μL of Mi^a-positive RBCs as the negative control. Afterwards, 100 μL of redox solution was added to each tube and gently mixed by pipetting up and down. The final mixture (166 μL) was dispensed onto the SPCE surface. EIS measurements were recorded at 0, 5, 10, and 15 min to evaluate the effect of incubation time on the ΔR_ct response.

2.4. Electrochemical Measurement of the Mi^a Antigen on Red Blood Cells

The electrochemical detection strategy based on EIS in this study is as follows: antigen-antibody binding induced RBC agglutination, leading to increased steric hindrance at the electrode interface. This agglutinated layer reduced the accessibility of the redox probe to the SPCE surface, thereby impeding electron transfer and producing a measurable increase in R_ct compared with the baseline measurement, which was used as the analytical signal. Before each analytical session, a baseline EIS measurement was performed by applying 66 μL of NSS and 100 μL of redox solution to the SPCE surface to confirm electrode integrity and system stability. For antigen detection, 55 μL of anti-Mi^a antibody (1:4 diluted with NSS) was pipetted into a test tube. An 11 μL aliquot of packed RBCs was added to each tube, and 100 μL of redox solution was added to each tube and mixed well. A 166 μL aliquot of the mixture was applied to the SPCE surface, and impedance measurements were recorded immediately (0 min incubation). All tests were performed in triplicate. A schematic overview of the experimental workflow is provided in Figure .

1.

Schematic illustration of the mix-and-drop electrochemical detection strategy for the Mi^a antigen on RBCs. (a) In Mi^a-negative samples, RBCs mixed with anti-Mi^a antibody show no agglutination, whereas Mi^a-positive samples mixed with anti-Mi^a antibody exhibit antibody-mediated agglutination, followed by the addition of the redox probe, (b) an aliquot of the reaction mixture is dropped onto the SPCE, (c) EIS measurements are performed using a portable potentiostat, and (d) the impedance response is recorded and visualized on a computer interface, enabling discrimination between Mi^a-positive and -negative samples based on R_ct changes.

2.5. Clinical Sample Analysis

A total of 122 clinical samples of Mi^a-positive blood and 110 clinical samples of Mi^a-negative blood, collected packed red cells after removal of plasma and buffy coat, were analyzed under the optimized assay conditions. For antigen detection, 55 μL of anti-Mi^a antibody (1:4 dilution) was pipetted into a test tube, after which 11 μL of packed RBCs was added to each tube and mixed well. Next, 100 μL of redox solution was added to each tube. All mixtures were dropped on the SPCE surface for Mi^a detection. EIS measurements were recorded immediately (0 min incubation).

2.6. Data Analysis

The impedance data were extracted using PSTrace software. The electrochemical response was expressed as ΔR_ct, as defined in Section . Statistical analysis of the optimization experiments was performed using ordinary two-way ANOVA followed by Tukey’s multiple comparisons test. For clinical sample testing, statistical analyses were performed using IBM SPSS Statistics for Windows, Version 29.0 (IBM Corp., Armonk, NY, USA). Comparisons between the Mi^a-positive and Mi^a-negative groups were performed using the Mann–Whitney U test. To evaluate the diagnostic performance, a complete dataset of 232 clinical blood samples (122 Mi^a-positive and 110 Mi^a-negative) was used for internal validation (70%, n = 162) and an external validation set (30%, n = 70), and stratified random sampling was used to preserve the proportion of Mi^a-positive and Mi^a-negative samples. Receiver operating characteristic (ROC) curve analysis was performed using the training dataset to determine the optimal ΔR_ct cut-off value based on the maximum Youden index. The selected cut-off was subsequently applied without modifiation to the external validation dataset. Diagnostic performance was evaluated by calculating true positive (TP), false negative (FN), true negative (TN), false positive (FP), sensitivity, specificity, and overall accuracy using the tube agglutination assay as the reference standard. The area under the ROC curve (AUC) was calculated. All graphical presentations, including bar plots and ROC curves, were generated using GraphPad Prism (version 8.0.2; GraphPad Software, San Diego, CA, USA). A p value of < 0.05 was considered statistically significant.

3. Results

3.1. Parameter Optimization for Electrochemical Detection of the Mi^a Antigen

The fitted solution resistance (R_s or R1) values obtained under different optimization conditions are summarized in Table . Across all the optimization conditions, R1 remained relatively stable, whereas the charge-transfer resistance (R_ct or R2) exhibited more pronounced changes between the agglutination and non-agglutination control conditions, indicating that the observed impedance differences were primarily associated with changes in R_ct (Figure ). To enhance the discrimination capability of the impedance-based biosensor, key analytical parameters were optimized by evaluating their influence on the net impedance response obtained from two non-agglutination conditions: Mi^a-positive samples incubated with NSS and Mi^a-negative samples incubated with anti-Mi^a antibody (Figure ). As illustrated in Figure a, the RBC: antibody volume ratio significantly influenced the sensor’s performance. The 1:5 ratio was found to be optimal, providing the highest ΔR_ct of NSS and Mi^a-negative controls. At a ratio of 1:2, the low quantity of antibody led to small changes in hemagglutination in positive controls, which were small ΔR_ct . Conversely, at a 1:10 ratio, the response decreased because of insufficient RBC availability to react with the Mi^a antibodies. Statistical analysis revealed that compared with the 1:2 ratio, both the 1:5 and the 1:10 ratios resulted in significantly higher ΔR_ct values (p < 0.0001), whereas no significant difference was observed between the 1:5 and 1:10 ratios (p > 0.05). The effect of antibody dilution (Figure b) revealed that a 1:4 dilution resulted in the most ΔR_ct differentiation between agglutination and non-agglutination controls for Mi^a detection on RBCs. Undiluted and 1:2 dilutions of antibodies showed lower ΔR_ct than the 1:4 dilution did. Statistical analysis demonstrated that compared with the undiluted antibody and the 1:2 dilution (p < 0.0001), the 1:4 dilution resulted in significantly higher ΔR_ct values under both normalization methods. Interestingly, the maximum ΔR_ct response between agglutination and non-agglutination controls was observed at an incubation time of 0 min (Figure c), with a gradual decrease in the signal over time (5, 10, and 15 min). This finding indicates rapid and near-instantaneous antigen–antibody interactions at the electrode interface. Statistical analysis revealed that the ΔR_ct values obtained at 0 min were significantly higher than those at 5, 10, and 15 min (p < 0.0001), whereas no significant differences were observed among the 5, 10, and 15 min incubation periods (p > 0.05) under both conditions.

1. R1 Values under Different Optimization Conditions.

Optimization parameter	Condition	Non-agglutination control	Agglutination
RBC: antibody volume ratio	1:2	0.20 ± 0.03	0.18 ± 0.01
	1:5	0.19 ± 0.02	0.20 ± 0.03
	1:10	0.18 ± 0.01	0.18 ± 0.01
Antibody dilution	Undiluted	0.19 ± 0.01	0.19 ± 0.01
	1:2	0.20 ± 0.01	0.19 ± 0.01
	1:4	0.20 ± 0.01	0.22 ± 0.01
Incubation time	0 min	0.18 ± 0.01	0.20 ± 0.02
	5 min	0.18 ± 0.01	0.20 ± 0.02
	10 min	0.19 ± 0.01	0.20 ± 0.02
	15 min	0.19 ± 0.01	0.20 ± 0.02

2.

Optimization of analytical parameters for electrochemical detection of the Mi^a antigen on the basis of the net change in ΔR_ct responses. (a) RBC: antibody volume ratio, (b) antibody dilution, and (c) incubation time. The data are shown as the mean ± SD. Statistical analysis was performed using two-way ANOVA followed by Tukey’s multiple comparisons test. * p < 0.05, ** p < 0.01, *** p < 0.001, and ****p < 0.0001.

3.2. Electrochemical Immunodetection of the Mi^a Antigen on Red Blood Cells

The electrochemical response toward Mi^a antigen detection on RBCs was investigated using EIS, which enables sensitive monitoring of interfacial changes through variations in R_ct. The impedance data were fitted using the equivalent circuit model shown in Figure a, which consists of R1, R2, double-layer capacitance (C1), and Warburg impedance (W1), to describe interfacial electrochemical processes. Nyquist plots obtained for the bare SPCE, Mi^a-negative control and Mi^a-positive target are shown in Figure b. The bare electrode exhibited a small semicircle diameter in the Nyquist plot, indicating a low R_ct and efficient electron transfer between the redox probe and the electrode surface. After exposure to the Mi^a-negative sample, the semicircle diameter increased noticeably, reflecting partial surface blocking caused by non-specific adsorption of blood components and proteins. In contrast, the Mi^a-positive sample produced a pronounced enlargement of the semicircle, corresponding to a substantially higher R_ct. This strong impedance response is attributed to specific antigen–antibody interactions that rapidly induce RBC agglutination. The resulting RBC aggregates may increase interfacial obstruction to the redox probe and electron transfer at the electrode surface, leading to an increase in R_ct. Equivalent circuit fitting demonstrated that the electrochemical response was dominated by changes in R2 rather than R1, with R2 increasing from 61.9 ± 5.2 kΩ for Mi^a -negative samples to 121.1 ± 13.3 kΩ for Mi^a -positive samples, whereas R1 remained comparatively unchanged. The clear separation between the impedance responses of the Mi^a-positive and -negative samples demonstrates that this mix-and-drop EIS approach enables reliable discrimination of target presence without the need for electrode surface functionalization. These results confirm that antigen-antibody recognition, combined with an impedance-based readout, provides a simple, effective strategy for Mi^a antigen detection on RBCs.

3.

Electrochemical immunodetection of the Mi^a antigen by EIS. (a) Equivalent circuit model used for fitting the impedance data and (b) representative Nyquist plots obtained from three measurements of the bare SPCE (baseline), Mi^a-negative and -positive samples.

3.3. Assay Performance with Clinical Samples

The performance of the electrochemical assay for Mi^a antigen detection was evaluated using 232 independent blood samples, including 122 clinical samples of Mi^a-positive and 110 clinical samples of Mi^a-negative blood, measured under optimized conditions. The analytical response was quantified as ΔR_ct, which reflects interfacial blocking effects arising from sample–antibody interactions resulting in RBC agglutination. Accordingly, non-parametric statistical analysis was employed. As illustrated in the dot plots (Figure ), Mi^a-positive samples exhibited markedly higher ΔR_ct values than Mi^a-negative samples, with a clear separation between the two groups in the internal and external validation sets. Mann-Whitney U test confirmed a highly significant difference between the groups (p < 0.0001), indicating complete group discrimination in the internal validation set (Figure a). The median ΔR_ct was approximately 98.24 kΩ (interquartile range 85.80–110.7 kΩ, n = 85) for the Mi^a-positive samples and 48.82 kΩ (interquartile range 40.92–54.78 kΩ, n = 77) for the Mi^a-negative samples. Similarly, in the external validation set (Figure b), the median ΔR_ct was 99.11 kΩ for the Mi^a-positive group (interquartile range 90.94–108.50 kΩ, n = 37) and 44.82 kΩ for the Mi^a-negative group (interquartile range 39.33–52.98 kΩ, n = 33). The results of the Mann–Whitney U analysis likewise confirmed a highly significant difference between the groups (p < 0.0001). The strong signal separation across independent samples highlights the suitability of this strategy for practical blood group screening applications.

4.

Statistical analysis of Mi^a detection. Individual-value dot plots showing the ΔR_ct values for Mi^a-positive and Mi^a-negative blood samples in the (a) internal validation and (b) external validation datasets. Each dot represents one clinical sample, and the horizontal line indicates the median value of each group. Statistical significance was determined using the Mann-Whitney U test (p < 0.0001).

3.4. ROC Curve Analysis and Data Validation

To evaluate the diagnostic performance of the proposed assay, the complete clinical dataset was randomly divided into an internal validation set (70%, n = 162) and an external validation set (30%, n = 70) using stratified random sampling. ROC curve analysis of the internal validation dataset yielded an AUC of 1.000 (95% CI: 1.000–1.000) (Figure a), indicating excellent discrimination between Mi^a-positive and -negative samples in this study cohort. The results of the ROC analysis were statistically significant (p < 0.0001), supporting the robustness of the discrimination performance under the experimental conditions employed. Based on the maximum Youden index, an optimal ΔR_ct cut-off value of 71.10 kΩ was selected. The selected cut-off was subsequently applied without modification to the external validation dataset. ROC analysis of the external validation dataset also yielded an AUC of 1.000 (95% CI: 1.000–1.000) (Figure b), with statistically significant discrimination (p < 0.0001). These results demonstrate that the selected cut-off maintained excellent diagnostic performance when evaluated using an independent internal validation dataset.

5.

ROC curve analysis for the discrimination of Mi^a-positive samples from Mi^a-negative samples. (a) internal validation (n = 162) and (b) external validation (n = 70).

4. Discussion

This study demonstrates a rapid, label-free electrochemical strategy for Mi^a antigen detection based on solution-phase antigen–antibody recognition and impedance readout. Unlike conventional serological assays that rely on visible agglutination and operator-dependent interpretation, the proposed mix-and-drop EIS approach converts immunorecognition events into quantitative changes in R_ct, enabling objective discrimination of Mi^a status directly on RBCs.

Optimization of the analytical parameters was essential for achieving robust signal discrimination. To achieve controlled optimization, the blood sample was kept constant throughout the optimization experiments, as variations in RBC properties could independently influence the electrochemical impedance response and obscure the true effect of the analytical parameters. The RBC:antibody volume ratio strongly influenced ΔR_ct responses, reflecting the need for optimal antigen/antibody availability to enable efficient immunocomplex formation. This finding is consistent with a previous report that optimal antibody titration is required to achieve strong RBC agglutination, as imbalanced antigen-antibody ratios can reduce agglutination efficiency and consequently weaken detectable signals. Excessive Mi^a antibodies caused steric hindrance in antibody binding to the Mi^a antigen, whereas insufficient antibody levels limited antigen capture. This observation is consistent with a previous report showing that both steric crowding at high bioconjugation densities and reduced binding site availability at low densities diminish immunosensor performance. The optimal RBC: antibody volume ratio was 1:5. Similarly, moderate antibody dilution yielded superior discrimination compared with undiluted antibodies, in agreement with a prior electrochemical study showing that excessively high surface antibody densities can lead to steric obstruction and reduced recognition efficiency. In a previous electrochemical immunosensor study, moderate antibody dilutions were shown to improve analytical performance by reducing non-specific adsorption and steric effects, compared with both very high and very low antibody densities. The optimum antibody dilution was 1:4. In this study, a notable advantage of the developed platform was the near-instantaneous signal generation observed without incubation. The highest response occurred at 0 min, followed by a decrease with increasing incubation time, suggesting that the electrochemical response was associated with rapid initial specific binding transiently causes peak steric blockage. The signal (ΔR_ct ) decayed overtime (5-15 min). The proposed mechanism may be due to RBC agglutination becoming tighter and more stable. Kinetic stabilization may occur as more antibody binding sites find and lock onto adjacent RBC-surface antigens, resulting in reduced total surface area and lowered steric blockage. Zorea et al. (2020) reported that modern label-free impedance-based biosensors utilize high-affinity antibodies for point-of-care applications, as demonstrated by rapid impedance-based platforms achieving detection in less than 5 min. In contrast, conventional serological agglutination methods, such as the tube method (5–30 min) and gel column agglutination assays (15 min), require extended incubation periods to achieve visually interpretable results. The efficiency of our developed electrochemical platform highlights its rapid detection capability compared with time-consuming conventional blood typing assays.

A confirmed mechanism in this study is that compared with Mi^a-negative samples (Figure b), Mi^a-positive samples form larger antigen–antibody aggregates. Upon deposition on the SPCE surface, these aggregates generate a thicker and more heterogeneous interfacial layer that partially blocks the access of ferri/ferrocyanide redox species to the electrode surface. The resulting increase in steric hindrance and diffusion resistance contributes to the observed increase in R_ct. The ability of EIS to resolve interfacial states distinct from those of the bare electrode and non-specific adsorption to specific antigen-antibody complex formation underscores its established utility in immunosensing, as immunorecognition events are known to induce measurable increases in ΔR_ct, with larger immunocomplexes producing greater interfacial blocking and impedance contrast. For example, a label-free electrochemical immunosensor for detecting Staphylococcus aureus demonstrated that EIS provided similar strong linearity and reliable quantification comparable to differential pulse voltammetry, confirming the sensitivity of R_ct changes to specific antigen-antibody binding at the electrode interface. In this study, we developed the EIS-based Mi^a detection in contrast to many electrochemical sensing approaches that require electrode surface modification, covalent antibody immobilization, or secondary labels to amplify signal differences. − This mix-and-drop strategy (anti-Mi^a antibody and RBCs) employed here leverages solution-phase immunorecognition and the intrinsic sensitivity of EIS to generate robust impedance contrast with minimal assay complexity, highlighting the practical advantage of an impedance-based readout for rapid, high-contrast immunosensing without extensive surface engineering.

The clinical performance obtained in this study was evaluated using clinical blood samples, demonstrating reliable discrimination of Mi^a-positive and -negative samples. Completely correct discrimination of Mi^a-positive and -negative samples, confirmed by statistical analysis and ROC evaluation, indicated excellent discriminative capability within the studied cohorts. The observed AUC of 1.0 demonstrates excellent discriminative capability in internal and external validation studies. Nevertheless, these results indicate that the impedance-based signal generated by the mix-and-drop strategy provides high signal-to-background contrast and enables reliable binary discrimination of Mi^a antigen status without the need for electrode surface modification. The identified cut-off value offers a practical criterion for translating the electrochemical response into a clinically interpretable diagnostic outcome. Accordingly, the ROC results are methodologically acceptable and demonstrate that the developed electrochemical approach can generate a high-contrast analytical signal suitable for diagnostic decision-making. Because Mi^a is a cell-surface blood group antigen, the assay is intended for qualitative antigen typing rather than analyte quantification. The diagnostic performance was evaluated using authentic clinical RBC samples from different donors, which inherently reflect the biological heterogeneity of Mi^a-associated hybrid glycophorin variants on RBCs. Overall, these results highlight the potential of impedance-based mix-and-drop immunoassays as a rapid, simple, and quantitative alternative to conventional serological methods for Mi^a antigen screening. Despite the excellent performance observed in this cohort, the study is limited by its single-center nature. Future work will focus on validating the assay for more diverse populations, assessing inter-operator variability, and exploring integration into portable electrochemical platforms for rapid blood group screening.

5. Conclusion

This study demonstrates a simple electrochemical strategy for Mi^a antigen detection within the MNS blood group system using a mix-and-drop impedance approach, enabling clear discrimination between Mi^a-positive and -negative blood samples without electrode surface modification. The strong discrimination of impedance responses and robust statistical validation indicate that specific Mi^a-associated interactions can be effectively translated into a measurable electrochemical signal, even in complex clinical matrices. The key novelty of this work lies in the elimination of electrode functionalization and immobilization steps, which simplify the assay design and reduce the preparation time and rapid detection time, while maintaining high diagnostic contrast. Such developments could support practical applications in transfusion medicine, particularly for identifying clinically significant Mi^a antigen status, and can be applied for the detection of other antigens on RBCs.

All the data required to support the findings of this study are contained within the article. The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conceptualization, investigation, methodology, formal analysis, data curation, writing – original draft, O. Z.; Review & editing, N. N. S. A., T. S., K. M., K. K., P. T., and J. D.; Conceptualization, funding acquisition, methodology, formal analysis, writing – original draft, review & editing, supervision, P. M.

The Research on biosensing for Mi^a detection has received funding support from the Fundamental Fund of Khon Kaen University and the National Science, Research and Innovation Fund or NSRF, Thailand.

The study was conducted in accordance with the Declaration of Helsinki and Clinical investigation of medical devices for human subjects – Good Clinical Practice, and the protocol was reviewed and approved by the Khon Kaen University Ethics Committee (HE694004).

The authors declare no competing financial interest.