Eleonora Nicolai

Background and Aims: Herpes simplex virus type 1 (HSV‐1) is highly prevalent worldwide, making accurate serological testing essential for both clinical diagnosis and epidemiological surveillance. Automated chemiluminescent immunoassays (CLIAs) offer operational advantages over enzyme‐linked immunosorbent assays (ELISAs); however, their diagnostic performance relative to Western blot (WB) confirmation in high‐prevalence settings remains insufficiently characterized. The comparative diagnostic accuracy of CLIA‐ and ELISA‐based assays for HSV‐1 IgG detection, when benchmarked against a WB reference standard in endemic populations, remains unclear. This study aimed to evaluate HSV‐1 IgG seroprevalence and diagnostic performance of one CLIA and two ELISA platforms using Western blot as the reference method. Methods: Four hundred archived serum samples from adult male craft and manual workers in Qatar were tested using the Mindray CL‐900i CLIA, HerpeSelect ELISA, NovaLisa ELISA, and Euroimmun Western blot. Seroprevalence, diagnostic accuracy, and interassay agreement were assessed using WB as the reference standard, with equivocal and indeterminate results excluded from analysis. Results: HSV‐1 IgG seroprevalence estimates were comparable across assays: HerpeSelect 72.5% (290/400), Mindray 70.3% (281/400), NovaLisa 66.3% (265/400), and Western blot 57.8% (231/400), with no statistically significant differences (all p > 0.05). The Mindray CLIA demonstrated the highest diagnostic performance (sensitivity 95.7%, specificity 88.9%, accuracy 93.4%) and strong agreement with Western blot ( κ = 0.85). HerpeSelect showed substantial agreement ( κ = 0.81), while NovaLisa exhibited lower specificity. Conclusion: CLIA‐ and ELISA‐based assays produced comparable HSV‐1 seroprevalence estimates in this high‐prevalence population; however, diagnostic accuracy varied across platforms. The CLIA platform demonstrated the strongest agreement with Western blot, supporting its use in high‐throughput settings, while confirmatory testing remains important to minimize misclassification.

Serum immunofixation electrophoresis (IFE) is the reference method for identifying and characterizing monoclonal immunoglobulins in plasma cell dyscrasias; however, its interpretation remains time-consuming, operator-dependent, and subject to inter-observer variability. This study evaluated a deep learning-based decision-support system (ImmunoGUI) for automated IFE interpretation intended to support the laboratory reporting workflow. A dual-stage framework was developed to isolate electrophoretic regions of interest and automatically generate standardized textual reports, paired with visual attention maps for diagnostic explainability. The system was evaluated on real-patient datasets across six canonical intact monoclonal immunoglobulin classes (IgGκ, IgGλ, IgAκ, IgAλ, IgMκ, and IgMλ). Models were trained using combinations of real-patient and synthetic IFE images and evaluated on independent real-patient test cohorts. The first-stage model achieved 89.5% overall binary accuracy, with 91% sensitivity and 88% specificity. The second-stage structured reporting model achieved a Top-1 diagnostic accuracy of 79.4%, reaching 95.5% Top-3 accuracy when evaluated as a decision-support hypothesis ranker. Visual attention maps reliably highlighted target monoclonal bands, providing intuitive spatial explainability to support clinical review. ImmunoGUI offers a practical, computationally lightweight decision-support tool to semi-automated IFE reporting. Although further validation on larger multicentre datasets will be required before routine clinical implementation, the system has the potential to help in reducing manual reporting workload and enhancing standardization in routine IFE screening under expert human oversight.

Background: Vitamin D is a key regulator of skeletal homeostasis, and hypovitaminosis D is highly prevalent among postmenopausal women, who are at increased risk of osteoporosis, sarcopenia, and related complications. Accurate assessment of serum 25-hydroxyvitamin D [25(OH)D] is therefore essential. However, substantial variability exists among analytical methods, particularly between automated chemiluminescent immunoassays (CLIA) and liquid chromatography–tandem mass spectrometry (LC-MS/MS), the latter considered the reference technique. This study aimed to compare four analytical methods, three CLIA platforms, and LC-MS/MS for measuring circulating 25(OH)D levels in a cohort of menopausal and postmenopausal women. Methods: A total of 425 serum samples from menopausal and postmenopausal women representing the real-world distribution of vitamin D levels in this population were analyzed using three automated CLIA systems and LC-MS/MS. Method comparison, agreement, precision through quality control assessment, total error, and sigma were evaluated. Results: The evaluated CLIA platforms (Abbott, Snibe, and Siemens) showed strong correlation with LC-MS/MS, with r = 0.919, r = 0.978, and r = 0.879. Furthermore, all assays showed excellent precision (CV < 5%), with good-to-acceptable total error (TE) and Sigma-metric performance. Conclusions: In conclusion, these findings demonstrate that while CLIA platforms offer a reliable and precise alternative for routine clinical use, these findings underscore the importance of method selection and result interpretation in the clinical assessment of vitamin D status in postmenopausal women. Furthermore, it highlights the ongoing need to minimize inter-assay variability and ensure consistent vitamin D assessment.

Microplastics (MPs) have become a widespread environmental contaminant, raising concern due to their persistence, capacity to transport pollutants, and potential risks to ecosystems and human health. Their increasing global production, prolonged degradation, and ubiquity in aquatic environments underscore the need for improved monitoring and mitigation strategies. Current findings indicate widespread MP contamination, including within the human body, emphasizing significant ecological and health concerns. This review examines the definition, sources, environmental transport mechanisms, associated risks, and current detection methods for MPs in natural and engineered water systems. The methods discussed encompass a broad range of analytical and sensing technologies used to identify, characterize, and quantify MPs across diverse environmental matrices. The review highlights that no single technique is sufficient for comprehensive MP analysis; instead, the combination of multiple methods enhances sensitivity, specificity, and reliability. Progress in automated sample preparation, advanced sensing platforms and standardized methodologies is key to improving detection efficiency and comparability across different studies. In particular, the extensive body of scientific literature underscores the imperative for standardized and harmonized protocols regarding data collection and analysis, as well as homogeneous limits of detection and units of measurement. Reducing MP pollution will require interdisciplinary collaboration, regulatory action, and increased public awareness to protect environmental integrity and human health.

Microplastics (MPs) have become a widespread environmental contaminant, raising concern due to their persistence, capacity to transport pollutants, and potential risks to ecosystems and human health. Their increasing global production, prolonged degra-dation, and ubiquity in aquatic environments underscore the need for improved strategies for monitoring and mitigation. This review examines the definition, sources, environmental transport mechanisms, associated risks, and current detection methods for MPs in natural and engineered water systems. The methods discussed encompass a broad range of analytical and sensing technologies used to identify, characterize, and quantify MPs across diverse environmental matrices. The review highlights that no single technique is sufficient for comprehensive MP analysis; instead, the combination of multiple methods enhances sensitivity, specificity, and reliability. Current findings indicate widespread MP contamination, including within the human body, emphasizing significant ecological and health concerns. Progress in automated sample preparation, standardized protocols, and advanced sensing platforms is key to improving detection efficiency and comparability across different studies. Overall, the evidence presented supports the need for strengthened monitoring, continued technological innovation, and coordinated mitigation policies. Reducing MP pollution will require interdisciplinary collaboration, regulatory action, and increased public awareness to protect environ-mental integrity and human health.

Background: 25-Hydroxy vitamin D [25(OH)D] is the circulating form of vitamin D. Its deficiency is a major global health concern, affecting over one billion people. Beyond its role in bone health, low vitamin D levels have been implicated in a wide range of chronic and inflammatory diseases, including diabetes, chronic kidney disease, and cancer. While immunoassays are widely used in routine testing, liquid chromatography–tandem mass spectrometry (LC-MS/MS) remains the reference method for its superior accuracy. This study aimed to evaluate the analytical performance of the Autobio 25(OH)D chemiluminescence assay (Autobio Diagnostics, Zhengzhou, China) compared with LC-MS/MS (Chromsystems Instruments & Chemicals GmbH, Gräfelfing, Germany) and the Siemens chemiluminescent microparticle immunoassay (Siemens HealthCare, Erlangen, Germany). Additionally, the influence of age and sex on 25(OH)D concentrations was examined to explore potential demographic and pathophysiological variations. Methods: 200 residual serum samples were analyzed to compare all three methods. Precision and linearity were verified. Statistical analysis was performed. Results: The Autobio assay showed good correlation with LC-MS/MS (R² = 0.953; p < 0.001), with acceptable bias and precision (CV < 10%) and confirmed linearity. Age- and sex-related differences were observed, indicating demographic influences on vitamin D status. Conclusions: Accurate and accessible laboratory testing for 25(OH)D is therefore essential for both disease prevention and clinical management. The Autobio 25(OH)D assay demonstrated strong correlation with LC-MS/MS and high analytical reliability. Its good performance makes it a valuable tool for routine assessment of 25(OH)D and for supporting the early detection or monitoring of hypovitaminosis D in clinical practice.

Background: Urine microbial analysis is a frequently requested test that is often associated with contamination during specimen collection or storage, which leads to false-positive diagnoses and delayed reporting. In the era of digitalization, machine learning (ML) can serve as a valuable tool to support clinical decision-making. Methods: This study investigates the application of a simple artificial neural network (ANN) to pre-identify negative and contaminated (false-positive) specimens. An ML model was developed using 8181 urine samples, including cytology, dipstick tests, and culture results. The dataset was randomly split 2:1 for training and testing a multilayer perceptron (MLP). Input variables with a normalized importance below 0.2 were excluded. Results: The final model used only microbial and either urine color or urobilinogen pigment analysis as inputs; other physical, chemical, and cellular parameters were omitted. The frequency of positive and negative specimens for bacteria was 6.9% and 89.6%, respectively. Contaminated specimens represented 3.5% of cases and were predominantly misclassified as negative by the MLP. Thus, the negative predictive value (NPV) was 96.5% and the positive predictive value (PPV) was 87.2%, leading to 0.82% of the cultures being unnecessary microbial cultures (UMC). Conclusions: These results suggest that the MLP is reliable for screening out negative specimens but less effective at identifying positive ones. In conclusion, ANN models can effectively support the screening of negative urine samples, detect clinically significant bacteriuria, and potentially reduce unnecessary cultures. Incorporating morphological information data could further improve the accuracy of our model and minimize false negatives.

Background: International guidelines recommend the use of high-sensitivity cardiac troponin (hs-cTn) I and T methods for the detection of myocardial injury as a pre-requisite for the diagnosis of acute myocardial infarction (AMI) in patients admitted to the emergency department. Recently, Mindray (Mindray Bio-Medical Electronics Co., Ltd., Shenzhen, China) has introduced a new chemiluminescence immunoassay (CLIA) for the detection of the cTn complex. The present study aims to verify and validate the hs-cTnI Mindray assay on the new automated CL2600i analyzer compared to the routine Alinity-i series instrument by Abbott (Abbott, Chicago, IL, USA). Methods: This study evaluated linearity, precision through the 5 × 5 protocol, methodological comparison on plasma and serum matrices, hs-cTnI 99th percentile imprecision, and the hs-cTnI detection rate in a healthy population. Results: The results obtained proved that the performance of the Mindray hs-cTnI test on the CL2600i platform was closely comparable to the Abbott Alinity-i system (plasma R²: 0.974; serum R²: 0.995). The CVs were consistently low, and no significant differences were reported. Excellent analytical performance, with high sensitivity, was also observed in the healthy population (overall detection rate: 79%), as well as good linearity within the measuring range (R²: 0.994). Conclusions: The Mindray hs-cTnI test confirms its robustness and utility in routine practice as an advanced assay. The new technology, with more sensitive detection methods, may improve the accuracy and reliability of cardiac biomarker testing, ultimately leading to better outcomes in the management of patients with AMI and other cardiac conditions.

Sepsis is a life-threatening condition, and clinicians should diagnose it as soon as possible to enable rapid intervention. The study aims to validate the AIA-360 Presepsin (PSEP) test for its use in determination in the diagnosis of septic patients after admission to emergency departments (ED). A total of 97 blood samples were collected from patients at the ED and from blood donors of Tor Vergata Hospital. Here, 15 samples were obtained from patients with a confirmed diagnosis of sepsis, and 44 samples with non-septic inflammatory condition. A control group of 38 samples from healthy subjects was also included. The non-septic inflammatory condition group and the confirmed sepsis group had a median of 874.40 pg/mL and 1467.10 pg/mL, respectively, while the control group showed a PSEP median value of 473.90 pg/mL, thus showing a significant statistical difference among all groups. The ROC curves highlighted a good sensitivity (93.33%) and specificity (76.19%) for PSEP values, suggesting the best cut-off point of 890 pg/mL. (p-value < 0.001; Mann–Whitney test). The PSEP test can improve and speed up the diagnosis of sepsis after admission to the ED with respect to other biomarkers, mainly due to its early kinetics.