Search Results (327)

Background and Objectives: Ixekizumab is a human monoclonal antibody targeting interleukin-17A, approved for the treatment of moderate-to-severe plaque psoriasis. Given its demonstrated efficacy and safety in clinical trials, this study aimed to evaluate the real-world drug survival of Ixekizumab and identify clinical predictors of treatment discontinuation. Materials and Methods: A retrospective, observational, hospital-based study was conducted in the Department of Dermatology at the Central University Hospital of Asturias (HUCA). Patients with moderate-to-severe plaque psoriasis who initiated treatment with Ixekizumab (Taltz^®) between 8 June 2017 and 10 October 2024, were included. Demographic data, comorbidities, age at disease onset, family history, PASI score, and previous treatments were recorded. Drug survival was assessed using Kaplan–Meier survival curves and the log-rank test. Predictors of discontinuation were analyzed using univariate and multivariate Cox proportional hazards models. Results: A total of 103 patients (55.3% women) were included. Drug survival rates were 85% at one year, 73% at two years, and 61% at four years, with a mean treatment duration of 52.5 months (95% CI: 46.01–58.99). Multivariate analysis showed that patients under the age of 65 had a significantly higher risk of treatment discontinuation (hazard ratio: 1.813; p < 0.05). The most common reason for discontinuation was secondary treatment failure (45.16%). Ixekizumab demonstrated sustained drug survival in a real-world setting, with rates falling within the mid-to-upper range reported in the literature. Older age (>65 years) was associated with greater treatment persistence, highlighting a potential influence of age on long-term therapeutic adherence. Full article

YKL-40 is a glycoprotein that may be present at elevated levels in many cancers and neurodegenerative diseases. It has been investigated in numerous studies as a potential biomarker for several conditions, including Alzheimer’s Disease (AD). In this study, a biosensor with Surface Plasmon Resonance imaging (SPRi) detection, sensitive to YKL-40, was constructed for the detection of this analyte in the blood plasma of AD patients. Extensive validation of the biosensor was performed. This included the determination of analytical parameters such as the biosensor’s response characteristics, detection and quantification limits, precision, accuracy, repeatability, selectivity, stability, and performance in natural samples. Validation parameters were primarily tested using standard solutions, while natural samples were employed to evaluate repeatability, stability, and assay accuracy in three groups of samples from different patients. A YKL-40-specific antibody was used as the receptor layer, immobilized on a gold plate using the EDC/NHS protocol on thiol 11-MUA. The biosensor exhibited a wide operating range (1–200 ng/mL), a low detection limit (LOD) of 2 pg/mL, and a quantification limit (LOQ) of 7 pg/mL. High precision and accuracy were confirmed by the calculated standard deviations (SD) and coefficients of variation (CV), which ranged from 0.0009 to 7.02 ng/mL and from 0.12% to 9.24%, respectively. The sensor also demonstrated good repeatability (CV = 4.995%) and was capable of detecting the analyte of interest in complex biological matrices. Its applicability was confirmed in a study using plasma from AD patients and two selected control groups: plasma from smokers and patients with prostatitis. This allowed the assessment of YKL-40 levels across different groups. The results were consistent with literature values, and statistical analysis confirmed the significance of concentration differences between groups. Furthermore, ROC curve analysis confirmed the diagnostic usefulness of the constructed YKL-40 test in the context of Alzheimer’s disease. Full article

Background/Objectives: The development of anti-drug antibodies (ADA) significantly diminishes the clinical efficacy of infliximab (IFX) in Crohn’s disease (CD). This study aimed to develop and validate an interpretable machine learning (ML) framework for predicting ADA risk during IFX induction therapy using multidimensional clinical and laboratory data. Methods: We conducted a retrospective analysis of 606 CD patients who initiated IFX induction between January 2023 and August 2024 at the Sixth Affiliated Hospital of Sun Yat-sen University. Predictor selection was performed through univariate analysis and least absolute shrinkage and selection operator (LASSO) regression, with significant features further evaluated via multivariate logistic regression. Seven ML models were developed and evaluated mainly based on area under the curve (AUC), F1 score, and Brier score. Model interpretability was enhanced using SHapley Additive exPlanations (SHAP). Results: Among the 606 CD patients, 145 (23.93%) developed ADA during IFX induction. Independent predictors included serum trough levels of IFX (TLI), erythrocyte sedimentation rate (ESR), history of delayed treatment, prior exposure to anti-TNF agents, and concomitant use of immunosuppressants (IMM). The XGBoost algorithm outperformed others, with an AUC of 0.899, accuracy of 0.851, F1 score of 0.640, and Brier score of 0.102 in validation. SHAP analysis identified TLI and ESR as the most influential predictors, with history of delayed treatment and prior exposure to anti-TNF agents showing moderate impact, while concomitant use of IMM was associated with a protective effect. Conclusions: We developed an interpretable ML model that effectively predicts ADA formation in CD patients undergoing IFX induction therapy, facilitating early risk stratification and personalized treatment planning. This approach integrates advanced analytics with clinical practice to support precision medicine in CD management. Full article

Background/Objectives: Mesalazine agents are essential drugs for treating ulcerative colitis (UC). Biomarkers that can differentiate mesalazine intolerance from exacerbated UC are needed because of the similarity of their symptoms and increasing prevalence of mesalazine intolerance. The study aim was to assess the usefulness of proteinase 3 antineutrophil cytoplasmic antibody (PR3-ANCA) to identify mesalazine intolerance in patients with UC. Methods: In this single-center retrospective study, patients with UC in whom serum PR3-ANCA was measured were included, and the serum levels were compared between the mesalazine-intolerant and -tolerant patient groups. The predictability of the marker to discriminate between these patients was analyzed. Results: Among 406 patients with UC with measured serum PR3-ANCA levels, 68 (17%) had mesalazine intolerance. The PR3-ANCA levels were significantly higher in the intolerance group than in the tolerance group [4.5 U/mL (0.8–26.2 U/mL) vs. 1.5 U/mL (0.0–8.5 U/mL), p = 0.001]. The area under the curve of the receiver operating characteristic curve analysis of the predictability of PR3-ANCA in differentiating mesalazine-intolerant patients from clinically active patients with UC was 0.755 (95% confidence interval: 0.634–0.876, cutoff value: 15.05 U/mL; sensitivity: 0.625, specificity: 0.813). Multivariate logistic regression analysis using various clinical factors revealed that serum PR3-ANCA > 15.0 U/mL was an independent risk factor of mesalazine intolerance (odds ratio: 8.25, 95% confidence interval: 2.52–27.02, p < 0.001). Conclusions: Serum PR3-ANCA could be a useful marker to identify mesalazine-intolerant patients with UC. Full article

Background/Objectives: Streptococcus suis (SS), an important zoonotic pathogen, has caused significant economic losses to the global pig industry. Existing commercial vaccines for SS mainly provide effective protection against a single serotype. Due to the existence of many serotypes and their robust immune evasion capabilities, the development of multi-component subunit vaccines or multi-epitope vaccines that provide effective cross-protection against different strains of SS is a key focus of current research. Methods: We applied two-dimensional electrophoresis (2-DE) and immunoblotting to screen for candidate immunogens among the immunogenic cell wall proteins of SS. BALB/c mice were immunized intradermally with a multi-component, multi-epitope vaccine. The vaccine’s safety and immunogenicity were assessed via clinical monitoring, antibody titer detection, cytokine assays, and survival curve analyses. Results: In this study, eight immunogenic cell wall proteins (GH25, Pk, PdhA, Ldh, ExoA, Pgk, MalX, and Dnak) were successfully identified using MALDI-TOF-MS, all of which could induce high IgG antibody titers. Based on the conservation and immunoprotection demonstrated by these eight protective antigenic proteins, PdhA, Ldh, and MalX were screened to construct a multi-component subunit vaccine as a candidate vaccine for providing cross-protection against SS isolates of multiple serotypes. Challenge studies showed that mice immunized with the multi-component subunit vaccine (PdhA, Ldh, and MalX) were protected against challenges with the SS2 virulent strain ZY05719 (62.5% protection) and the SSChz virulent strain CZ130302 (75% protection). Subsequently, we utilized immunoinformatics techniques to design a novel multi-epitope vaccine (MVPLM) derived from the immunogenic proteins PdhA, Ldh, and MalX. However, challenge tests revealed that the MVPLM offered limited protection against SS. Conclusions: These data demonstrate that a multi-component subunit vaccine composed of PdhA, Ldh, and MalX proteins shows promise as a candidate universal vaccine against multiple SS serotypes. Full article

Background/Objectives: Differentiating Type 1 from Type 2 diabetes mellitus (T1DM vs. T2DM) remains clinically challenging, especially in early-onset cases with overlapping features. This study assessed the diagnostic utility of diabetes-related autoantibodies in an Omani cohort and evaluated their predictive performance using machine learning. Methods: Clinical and laboratory data from 448 patients (aged ≥ 2 years) in Al Batinah North, Oman, were retrospectively analyzed. We assessed autoantibody positivity (anti-GAD, anti-islet, anti-TPO, anti-tissue), age, sex, and HbA1c. Receiver operating characteristic (ROC) curves and a neural network model were used to evaluate diagnostic accuracy. Results: Anti-GAD and anti-islet antibodies were significantly more prevalent in T1DM (69.0% and 64.1%) than T2DM (7.4% and 3.8%; p < 0.0001). HbA1c was elevated in both subtypes but lacked discriminatory specificity. Nearly half (48.5%) of T1DM patients showed multiple antibody positivity, especially in younger age groups. Anti-TPO and anti-tissue antibodies were more frequently detected in T1DM, suggesting broader autoimmunity. ROC analysis showed strong predictive value for anti-islet (AUC = 0.835) and anti-GAD (AUC = 0.827). Neural network modeling identified anti-GAD, anti-islet, and age as the most informative predictors, achieving over 92% classification accuracy. Importantly, antibody positivity in a subset of insulin-treated T2DM patients suggested potential latent autoimmune diabetes (LADA) misclassification. Conclusions: This is the first study in Oman to combine autoantibody screening with AI-based modeling to refine diabetes classification. Our findings highlight the value of immunological profiling in early diagnosis, uncover possible misclassification, and support AI integration to guide individualized management. Full article

The associations between sialylated anti-cyclic citrullinated peptide (anti-CCP) antibodies bearing α-2,6-sialic acid (SIA), ST6Gal1 and Neu1 enzymes, and clinical disease activity measures such as disease activity score 28 (DAS28), the Simplified Disease Activity Index (SDAI), and Clinical Disease Activity Index (CDAI) are unknown in rheumatoid arthritis (RA). To address this gap, this study included 97 patients with RA evaluated at baseline (month 0) and at 6 and 12 months. At each visit, blood cells were analyzed for B-cell ST6Gal1 and Neu1 expressions, and plasma samples were assessed for ST6Gal1 and Neu1 levels. The erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), monocyte chemotactic protein-1 (MCP-1), and IgG anti-CCP with its α-2,6-SIA modification were measured. Disease activity measures, namely DAS28-ESR, DAS28-CRP, DAS28-MCP-1, SDAI, and CDAI, were calculated. Correlations and Receiver Operating Characteristics among ST6Gal, Neu1, SIA/anti-CCP ratios, and disease activity measures were assessed. Multivariate regression analyses were performed to reveal confounding factors in such correlations. The total SIA content of anti-CCP antibodies was inversely correlated with B-cell Neu1 levels (ρ = −0.317 with p = 0.013. Plasma (free-form) Neu1 levels were inversely correlated with SIA/IgG anti-CCP ratios (ρ = −0.361, p = 0.001) in the DAS28-MCP-1 < 2.2 (remission) subgroup. No such correlation was observed for the DAS28-ESR, DAS28-CRP, SDAI, or CDAI subgroups. B-cell ST6Gal1 levels correlated inversely with SDAI ≤ 11 and DAS28-MCP-1 ≤ 3.6 combined remission and low-disease-activity subgroups (ρ = −0.315 with p = 0.001 and ρ = −0.237 with p = 0.008, respectively). The same was observed for B-cell ST6Gal1/Neu1 ratios correlating with the SDAI ≤ 11 subgroup (ρ = −0.261, p = 0.009). Nevertheless, B-cell ST6Gal1/Neu1 ratios against SDAI ≤ 11 and DAS28-MCP-1 ≤ 3.6 subgroups produced significant area-under-curve (AUC) values of 0.616 and 0.600, respectively (asymptotic p-Values 0.004 and 0.018, respectively). Through multivariate regression analyses, we found that biologics (a confounding factor) interfered with p-Values related to the B-cell ST6Gal1 enzyme but did not interfere with p-Values related to the pure B-cell Neu1 enzyme. In addition, disease duration interfered with p-Values related to the pure Neu1 enzyme on B-cells or in plasma. Moreover, plasma ST6Gal1/Neu1 ratios against the DAS28-MCP-1 < 2.2 remission subgroup produced an AUC of 0.628 and asymptotic p = 0.003. Therefore, it is suggested that B-cell ST6Gal1/Neu1 ratios can be used as clinical indicators for the combined remission and low-disease-activity subgroup of SDAI and DAS28-MCP-1 formulae. Plasma ST6Gal1/Neu1 ratios are also good indicators of DAS28-MCP-1 remission. Full article

Glial fibrillary acidic protein (GFAP) has been shown to be a reliable biomarker for detecting neurological disorders. Recently, we developed the Lumipulse G GFAP plasma assay, which is a commercially available tool. Compared to existing assays, the LUMIPLSE G platform offers the high-throughput, rapid, and fully automated quantification of biomarkers, enabling more standardized and accessible clinical study. In this study, we evaluated this assay using cerebrospinal fluid (CSF) samples. Assessing GFAP in CSF may provide more direct insights into central nervous system pathology than plasma and could improve the characterization of Alzheimer’s disease (AD) stages and support treatment monitoring. The LUMIPULSE G system is a chemiluminescent enzyme immunoassay (CLEIA) platform equipped with full automation, utilizing specialized cartridges to process samples within 30 min. The assay, which employs a pair of proprietary monoclonal antibodies targeting GFAP, was evaluated for clinical performance using 30 CSF samples from patients diagnosed with AD, patients with mild cognitive impairment (MCI), and cognitively unimpaired (CU) individuals, with 10 samples from each group. In addition, levels of β-amyloid 1–40 (Aβ40), β-amyloid 1–42 (Aβ42), and pTau181 were simultaneously measured. The Lumipulse G GFAP assay significantly differentiated (p < 0.05) between the amyloid accumulation and non-amyloid accumulation groups, as classified based on the CSF Aβ test. Furthermore, GFAP showed a moderate correlation with pTau181 (r = 0.588), as determined based on Spearman’s rank correlation coefficient. Moreover, receiver operating characteristic (ROC) analysis was performed to determine the performance of GFAP in distinguishing amyloid-positive and amyloid-negative subjects, with an area under the curve (AUC) of 0.72 (0.50–0.93). When stratified by CSF pTau181 positivity, GFAP demonstrated an improved diagnostic accuracy, achieving an AUC of 0.86 (95% CI: 0.68–1.00). This study demonstrates that the Lumipulse G GFAP assay, when applied to CSF samples, has the potential to differentiate AD from non-AD cases, particularly suggesting its utility in detecting tau-related pathology. While GFAP has previously been established as a biomarker for AD, our findings highlight that combining GFAP with other biomarkers such as Aβ40, Aβ42, and pTau181 may enhance the understanding of AD pathogenesis, disease staging, and possibly treatment responses. These findings suggest that GFAP may serve as a complementary biomarker reflecting astroglial reactivity associated with tau positivity, alongside established biomarkers such as Aβ40, Aβ42, and pTau181. However, since GFAP levels may also be elevated in other neurological disorders beyond AD, further investigation into these conditions is required. Full article

Background: Dengue infection is a spreading vector borne disease with most severe infection-related fatalities occurring in adults. This study was conducted to explore prognostic indicators of dengue infection severity. Methods: This study included patients aged over 15 years who were diagnosed with dengue viral infection. Data were collected from nine hospitals across all regions of Thailand between January 2019 and December 2022. Diagnosis of dengue infection was confirmed by a positive result for the NS-1 antigen via RT–PCR, IgM antibody, or IgG antibody tests. Data including gender, age, BMI, underlying disease, clinical characteristics and laboratory findings were collected. Multivariable logistic regression with backward elimination was used to identify a set of prognostic factors. Results: The prognostic indicators of severe dengue were age < 55 years (OR = 6.13, p = 0.054), severe bleeding (bleeding from the gastrointestinal tract, hematemesis, melena, menorrhagia, or hematuria) (OR = 20.75, p < 0.001), pleural effusion (OR = 10.23, p < 0.001), and platelet ≤ 100,000 (/µL) (OR = 3.62, p = 0.035). These predictors were able to accurately estimate the severity of dengue infection with an area under the receiver operating curve (AuROC) of 0.836. Conclusions: The proposed four prognostic factors can be applied to predict severe dengue infections. These findings may inform the development of a risk scoring system to forecast severe dengue infection, early detection, and appropriate treatment during sickness. Full article

Lyme borreliosis (LB) is a tick-borne infection of global relevance that remains underrecognized, hindering effective surveillance and diagnosis. This lack of awareness and the limited specificity and low antibody titters of current serological assays underscore the need for improved diagnostic tools. Here, we investigated the molecular fine specificity of IgM antibody responses to five proteins of Borrelia burgdorferi. Materials and Methods: We employed peptide arrays on cellulose support (SPOT synthesis) to screen IgM epitopes and assess cross-reactivity through databank searches and Enzyme-Linked Immunosorbent Assay (ELISA). Validation was performed using ELISA and Receiver Operating Characteristic (ROC) curve analysis. Results: We identified ten IgM epitopes, of which four were classified as specific. The ELISA peptide assay demonstrated a sensitivity of ≥87.3%, specificity of ≥56.2%, and accuracy of ≥66.6%. A bi-specific peptide was subsequently synthesized and evaluated by ELISA using a panel of patient sera representing different pathologies. This result showed a sensitivity of 85.0% and a specificity of 100.0%, with significant differences in cross-reactivity between the leptospirosis and syphilis groups. Conclusions: These findings indicate that the identified peptide combinations could facilitate the development of new, highly specific serodiagnostic assays, thereby enhancing public health initiatives and epidemiological studies. Full article

Canine visceral leishmaniasis (CVL) is a major zoonosis that poses a growing challenge to public health services, as successful disease management requires sensitive, specific, and rapid diagnostic methods capable of identifying infected animals even at a subclinical level. The objective of this study was to evaluate the performance of the recombinant chimeric protein rMELEISH3 as an antigen in ELISA assays for the robust diagnosis of CVL. The protein was expressed in a bacterial system, purified by affinity chromatography, and evaluated through a series of serological assays using serum samples from dogs infected with Leishmania infantum. ROC curve analysis revealed a diagnostic sensitivity of 96.4%, a specificity of 100%, and an area under the curve of 0.996, indicating excellent discriminatory power. Furthermore, rMELEISH3 was recognized by antibodies present in the serum of dogs with low parasite loads, reinforcing the diagnostic potential of the assay in asymptomatic cases. It is concluded that the use of the recombinant antigen rMELEISH3 could significantly contribute to the improvement of CVL surveillance and control programs in endemic areas of Brazil and other countries, by offering a safe, reproducible and effective alternative to the methods currently recommended for the serological diagnosis of the disease. Full article

Background: Autoimmune liver diseases (ALDs) are a diverse group of chronic inflammatory disorders. Individuals with a history of one autoimmune disease (AD) are at a substantially increased risk of developing additional autoimmune conditions. Polyautoimmunity has increasingly been recognized as a factor associated with a more complex disease course and poorer long-term outcomes. Methods: This retrospective, cross-sectional observational study reviewed medical records of patients diagnosed with ALDs who had been admitted to the gastroenterology clinic. Results: A total of 457 patients with ALDs were included. Polyautoimmunity was present in 194 patients (42.5%), and multiple autoimmune syndrome (MAS) was diagnosed in 26 of these patients (5.7%). Serological comparisons revealed that antinuclear antibody (ANA) positivity was significantly more common in the polyautoimmunity group. Only 22.2% of the patients with polyautoimmunity were ANA-negative, compared with 52.9% in those without. An ROC curve analysis was conducted to assess the predictive value of clinical and laboratory variables for polyautoimmunity. Among all the tested parameters, ANA positivity (>+2) had the strongest predictive value (AUC: 0.724). A disease duration longer than 6.5 years followed, with a moderate discriminative capacity (AUC: 0.677). Additionally, lower albumin levels (<3.0 g/dL) and elevated erythrocyte sedimentation rates (ESRs) (>29.5 mm/h) were significantly associated with polyautoimmunity. Conclusions: In our cohort, 42.5% of patients had at least one additional autoimmune disorder, highlighting the need for a systemic and comprehensive approach to patient care. Simple and accessible markers—such as ANA titers, disease duration, albumin levels, and ESRs—may help to identify patients at greater risk. Full article

Background/Objectives: Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy; however, reliable biomarkers of therapeutic efficacy remain limited. We investigated the clinical utility of plasma WFDC2 levels in patients receiving anti-PD-1 antibody treatment. Methods: Twenty-one patients with non-small cell lung, gastric, or bladder cancer received nivolumab or pembrolizumab. Plasma WFDC2 concentrations were measured by ELISA before ICI treatment (pre-ICI) and after two and four treatment cycles. Associations between WFDC2 expression changes and overall survival (OS), progression-free survival (PFS), and tumor progression were assessed. ROC curve analyses compared the predictive performance of WFDC2, soluble PD-L1 (sPD-L1), soluble PD-1 (sPD-1), and their combinations, with the area under the curve (AUC) evaluating predictive accuracy. Results: Levels of WFDC2 pre-ICI and those after two cycles were significantly higher than levels in healthy donors. However, no significant differences in WFDC2 levels were found between the time points during treatment. Greater increases in WFDC2 levels were significantly correlated with shorter OS (p = 0.002), shorter PFS (p = 0.037), and tumor progression (p = 0.003). ROC analysis revealed that WFDC2 achieved a higher AUC (0.700) than sPD-L1 (0.538) or sPD-1 (0.650). Combining biomarkers improved the predictive accuracy, with sPD-L1 plus WFDC2 showing the highest AUC (0.825). Conclusions: Serial increases in plasma WFDC2 are associated with poor clinical outcomes, highlighting its potential as a biomarker. Baseline plasma WFDC2 outperformed sPD-L1 and sPD-1 diagnostically. These findings should be interpreted as exploratory and hypothesis-generating, requiring confirmation in larger, tumor-specific cohorts with multivariate adjustment. WFDC2 represents a promising minimally invasive biomarker for the early identification of patients unlikely to benefit from ICI therapy. Full article

Background: Hemodialysis patients, due to impaired kidney function and compromised immune responses, face increased risks from SARS-CoV-2. Anti-nucleocapsid IgG (anti-IgG N) antibodies are a commonly used marker to assess prior infection in the general population; however, their efficacy for hemodialysis patients remains unclear. Methods: A retrospective study of 361 hemodialysis patients evaluated anti-IgG N antibodies for detecting prior SARS-CoV-2 infection. Antibody levels were measured using a chemiluminescence immunoassay (CLIA) over the four time points. Boxplots illustrated antibody distribution across sampling stages and infection status. Logistic regression and receiver operating characteristic (ROC) curve analysis determined diagnostic accuracy, sensitivity, specificity, and optimal cutoff values. Results: Among the 361 hemodialysis patients, 36 (10.0%) had SARS-CoV-2 infection. Sex distribution showed a trend toward significance (p = 0.05). Boxplot analysis showed that anti-IgG N levels remained low in non-infected patients but increased in infected patients, peaking at the third sampling. Anti-IgG N demonstrated high diagnostic accuracy (AUC: 0.973–0.865) but declined over time (p = 0.00525). The optimal cutoff at C1 was 0.01 AU/mL (sensitivity 1.00, specificity 0.94). Adjusted models had lower predictive value. Conclusions: Anti-IgG N antibodies showed high diagnostic accuracy for detecting prior SARS-CoV-2 infection in hemodialysis patients, though performance declined over time. These findings highlight the need for tailored diagnostic strategies in this vulnerable population. Full article

(1) Background: The ongoing global health threat posed by SARS-CoV-2 requires reliable and accessible diagnostic tools, especially in resource-limited settings where RT-qPCR may be impractical. This study describes the development and validation of two enzyme-linked immunosorbent assays (ELISA) designed to detect anti-SARS-CoV-2 IgG antibodies employing recombinant S1 and S2 spike protein subunits. (2) Methods: The assays were optimized and validated using serum samples from 354 RT-qPCR-confirmed hospitalized patients and 337 pre-pandemic blood donors. (3) Results: The S1-based ELISA achieved a 52.8% sensitivity and a specificity of 93.5%, with an area under the ROC curve (AUC) of 71.6%. In contrast, the S2-based ELISA demonstrated superior diagnostic performance, with a sensitivity of 63.7%, a specificity of 99.7%, and an AUC of 83.1%. Cross-reactivity analysis using sera from individuals with unrelated infectious diseases confirmed the high specificity of the S2-ELISA. Time-stratified analysis revealed that sensitivity increased with time, peaking between 15 and 21 days post-symptom onset. Compared to commercial serological assays, the S2-ELISA demonstrated comparable or improved performance, particularly in specificity and diagnostic odds ratio. (4) Conclusions: The S2-ELISA offers a robust, highly specific, and operationally simple tool for serological detection of SARS-CoV-2 infection. Its strong diagnostic performance and accessibility make it well-suited for implementation in diverse epidemiological settings, particularly where molecular testing is limited. The development of affordable, validated serological assays such as this is critical for strengthening surveillance, understanding transmission dynamics, and informing public health responses. Full article