Clinical Chemistry and Laboratory Medicine (CCLM)

Current clinical management of multiple myeloma (MM) relies on bone marrow (BM) biopsies for minimal residual disease (MRD) assessment. While BM biopsies are the gold standard, their invasive nature and potential to miss extramedullary or patchy disease necessitate sensitive, non-invasive liquid biopsy platforms. In this study, we evaluated the analytical performance of the CellSearch CMMC assay to determine its utility for deep-MRD monitoring. Using a standard 4 mL whole blood input, the assay achieves a WBC-normalized sensitivity of 2.45 x 10-7, supported by a limit of quantitation of 5 cells per run. Given this high analytical sensitivity, the assay provides a robust negative predictive value, rendering false-negative findings highly unlikely in populations with detectable peripheral disease. These findings characterize the CellSearch CMMC assay as a highly sensitive, analytically validated platform for non-invasive deep-MRD level longitudinal surveillance monitoring. When integrated into a clinical workflow that accounts for its specificity profile, the platform offers a patient-friendly complement to serial BM biopsies, with the potential to reduce their frequency in appropriate clinical contexts.

AimsTo evaluate the association between platelet indices and platelet count severity in patients with primary immune thrombocytopenia during routine post-treatment follow-up. MethodsThis retrospective observational study included patients with primary immune thrombocytopenia followed at a single tertiary care center between 2011 and 2025. Demographic and laboratory data were obtained from medical records. Platelet count severity was categorized as less than 30 x 10^9/L, 30 to 100 x 10^9/L, and greater than 100 x 10^9/L. Platelet indices, including mean platelet volume (MPV) and platelet distribution width (PDW), were analyzed using the most recent complete blood count obtained during routine follow-up after treatment initiation. Continuous variables were summarized as median and interquartile range. Comparisons across platelet count categories were performed using the Kruskal-Wallis test with post hoc Mann-Whitney U testing. Correlation analysis and simple linear regression were also conducted. ResultsA total of 243 patients were identified, of whom 232 met the inclusion criteria. Platelet distribution width differed significantly across platelet count severity categories (Kruskal-Wallis p < 0.001) and demonstrated a strong inverse association with platelet count. Mean platelet volume also showed a statistically significant difference across platelet count groups (Kruskal-Wallis p = 0.007), although the association was weaker and less consistent compared with PDW. Regression analysis confirmed a significant association between platelet count and PDW. ConclusionPlatelet distribution width is more closely associated with platelet count severity than mean platelet volume in patients with primary immune thrombocytopenia during routine post-treatment follow-up. PDW may represent a useful adjunctive laboratory parameter when interpreted alongside platelet count in routine clinical practice.

BackgroundThere is a need for synthetic peptide-based serologic assays that exploit avidity to replace whole antigens while enabling low-cost diagnostics in resource-limited settings. ObjectiveTo evaluate the diagnostic accuracy of a polymeric peptide-based ELISA leveraging avidity to enhance signal. MethodA 15-member SARS-CoV-2 peptide library corresponding to multiple epitope clusters and proteins was screened by indirect ELISA using pooled sera from RT-PCR-confirmed COVID-19 patients to identify peptides with possible diagnostic utility. The identified lead candidate, S559, possessed terminal cysteine-substitution to allow disulfide polymerization, and the resulting avidity gain was evaluated by comparing the apparent dissociation constant (KDapp) before and after depolymerization with N-acetylcysteine. The performance of an optimized ELISA using S559 was evaluated on 1,222 prospectively collected COVID-19 serum samples and 218 biobanked pre-COVID control serum samples. ResultsPolymeric S559 with a KDapp of 29.26 nM-1was demonstrated to have a 218% avidity gain relative to the completely depolymerized form. At pre-defined thresholds, the optimized S559 ELISA has a sensitivity and specificity of 83.39% (95%CI: 81.18% and 85.43%) and 96.79% (95%CI: 93.50% and 98.70%), respectively. At post hoc thresholds determined by Youden index, sensitivity and specificity reached 95.01 (95% CI: 93.63% - 96.16%) and 100.00% (95% CI: 98.32% - 100.00%), respectively. ConclusionHomomultivalent epitope presentation using polymeric S559 allows a highly specific immunoassay using human sera that may have important value in detecting antibodies, whether for diagnosing infection, confirming vaccination status or conducting surveillance.

Bacterial and Viral infections have identical symptoms, making it difficult to diagnose based on visible symptoms. This results in the overprescription of antibiotics, even in cases of viral infections, to avoid missing bacterial infections that could progress into a more severe condition and/or sepsis. This diagnostic gap contributes to the overuse of antimicrobials. To address the issue, a deployable diagnostic test has been developed and evaluated that can help differentiate between bacterial and viral infections. The approach is centred on three crucial biological markers: CD64 expression on leukocytes to detect bacterial infections, CD169 expression on leukocytes to detect viral infections and total leukocyte count as a general health indicator of the patient. ABxSure comprises a cartridge for sample processing, a device with in-built pneumatics, and an optical reader for quantifying biomarkers from blood. The ABxSure performance was tested and compared with a commercial plate reader and flow cytometer, yielding a promising correlation of 0.89. This comprehensive test will potentially provide clinicians with valuable information for effective and timely treatment.

Background: External Quality Assurance (EQA) is an essential component of modern laboratory medicine. Current scientific evidence on EQA focuses primarily on the analyses carried out by EQA providers while relatively little research has been conducted in individual clinical laboratories. Methods: In this retrospective single-center observational study in a clinical laboratory, EQA results were analyzed over a period of four years (2021-2024). The evaluation was based on EQA action reports documented in the institutes internal quality management system. Deviations were classified according to department, type of discrepancy, root cause category (analytical, preanalytical, systemic, unidentifiable), and measures taken. Results: A total of 7226 EQA participations were evaluated during the observation period. The overall error rate remained consistently low, ranging between 0.8% and 1.6%, with no significant change over time (p = 0.87). Most deviations occurred in the departments of clinical chemistry and immuno/autoimmune diagnostics (p < 0.001). These were predominantly quantitative discrepancies (false low/false negative or false high/false positive). Root cause analysis showed a clear dominance of analytical causes (p < 0.001), while preanalytical and systemic causes were identified less frequently. In most cases, corrective measures, such as re-analyses, recalibrations, process adjustments, or staff training, were implemented promptly. Hard structural measures, such as changing methods or discontinuing tests, were rarely necessary. Conclusion: In a clinical laboratory, EQA is an important tool for structured error analysis and continuous quality improvement. Consistent processing of deviating EQA results goes hand in hand with stable analytical performance and a low error rate.

IntroductionAnaemia is one of the most prevalent global public health challenges, particularly among women of reproductive age and children. According to the World Health Organization, anaemia is defined as a hemoglobin concentration below 13.0 g/dL in adult men, 12.0 g/dL in non-pregnant women, and 11.0 g/dL in pregnant women. Hemoglobin measurement therefore plays a critical role in diagnosis, classification, and monitoring of anaemia at both clinical and public health levels. Hemoglobin estimation allows early identification and intervention in at-risk populations. MethodologyA cross-sectional study was conducted at Aniniwaa Medical Centre, Kumasi, involving 100 participants who visited the laboratory for a complete blood count. Venous blood samples were collected aseptically into EDTA tubes and analysed first with the fully automated analyser, followed by the two Hb meters. Data were analysed using Chi-square tests, Bland-Altman plots, and descriptive statistics. ResultsResults showed that the prevalence of anaemia varied across methods: 28% by the analyser, 60% by Urit, and 64% by Mission. Both meters demonstrated 100% sensitivity but lower specificities (55.6% for Urit and 50.0% for Mission). Bland-Altman analysis indicated negative biases (Urit = -1.665 g/dL; Mission = -1.55 g/dL), suggesting both underestimated hemoglobin values compared to the reference. ConclusionThe study revealed that while Hb meters offer convenience and portability for field screening, the fully automated analyser remains more accurate and reliable for diagnosing anaemia in clinical settings.

Waldenstrom macroglobulinemia (WM) is a rare indolent neoplasm characterized by presence of more than 10% lymphoid cells in BM that exhibit plasmacytoid or plasma cell differentiation that secretes an IgM monoclonal protein. This is a retrospective analysis of 89 patients of WM that describes the clinical and laboratory characteristics, treatment patterns and outcome of patients of WM. The median age of the entire cophort was 66 years with male predominance (67.4%). Most common presentations were symptoms pertaining to anemia (77.5%) and constitutional symptoms (33.7%). Median bone marrow lymphoplasmacytic cells were 41%. Positivity for MYD88 and CXCR4 mutations were seen in 81.8% and 2.4% cases. BR was the most common regimen used (52.8%). Overall response rates were seen at 87.8%. Median overall survival, progression free survival and time to next treatment is 8.49 years, 2.15 years and 3.88 years. BR regimen was associated with highest event free survival.

ObjectivePost-thrombotic syndrome (PTS), a common complication of deep vein thrombosis, lacks objective diagnostic biomarkers and its molecular mechanisms remain poorly understood. This study aimed to identify plasma biomarkers and clarify pathways using integrated multi-omics and machine learning. MethodsProteomic and metabolomic profiling of 75 PTS patients and 75 controls was performed. Differential expression analysis, pathway enrichment, and protein-metabolite network analysis were conducted. A multi-algorithm machine learning with 8 feature selection methods prioritized biomarkers. Validations and 14 models were assessed. Results1,104 proteins and 1,891 metabolites were differentially expressed. Citrate cycle and unsaturated fatty acid biosynthesis were enriched. Three proteins, namely DIP2B, KNG1, and SUCLG2, were consistently selected as core biomarkers. All of these proteins were significantly downregulated in PTS and externally validated. A random forest model utilizing these proteins achieved an accuracy of 97.7% in independent testing, with SUCLG2 being the most influential predictor. ConclusionThis study identifies a novel three - protein biomarker panel for the diagnosis of PTS and reveals an immunometabolic axis in the pathogenesis of PTS, which links inflammatory regulation with mitochondrial energy metabolism. These findings provide valuable insights into the development of diagnostic tools and targeted therapeutic approaches.

Background: To investigate the safety and efficacy of CTguided lung nodule localization needles for the preoperative localization of small pulmonary nodules. Methods: A retrospective study was conducted on 102 patients with a total of 113 small pulmonary nodules who underwent preoperative localization at Jinan Fourth People's Hospital from January 2024 to December 2025. Nodule diameter and depth, localization time, the number of pleural punctures, the localization success rate, and postoperative complications (hook dislodgement, hemorrhage, and pneumothorax) were recorded. All patients underwent video assisted thoracoscopic surgery (VATS) after localization. Results: The mean nodule diameter was 0.97{+/-}0.36 cm, the mean depth was 1.26{+/-}0.48 cm, and the mean localization time was 9.8{+/-}3.65 minutes. The hook dislodgement rate was 0.98% (1/102), the intrapulmonary hemorrhage rate was 14.71% (15/102), and the pneumothorax rate was 16.67% (17/102). All pulmonary nodules were successfully resected by VATS at 73.82{+/-}13.83 minutes after localization, and no severe complications occurred. Conclusions: The use of a CTguided lung nodule localization needle for the preoperative localization of small pulmonary nodules decreases the time needed for intraoperative nodule detection and operation time. This strategy is a simple, safe, and accurate preoperative localization method that is worthy of increased clinical use.

Introduction The complete blood count with differential (CBD) is one of the most commonly performed blood tests worldwide, used in nearly all areas of medicine. Although modern CBD analyzers generate flow cytometry based single cell measurements,the resultant CBD markers are limited to coarse summary features, such as total cell counts and average cell sizes. This means, the markers cannotdetect subtle cell population shifts that may signal early stage pathogenesis. To test this, we evaluate whether AI based analysis of the raw single cell data underlying the CBD can be used to develop novel, clinically prognostic biomarkers, across patient settings. Method We developed two complementary methods for biomarker discovery using CBD tests and evaluated them with longitudinal data from an academic medical center. To create interpretable biomarkers, we clustered cells into physiologically meaningful subpopulations and performed robust statistical summarization. In tandem, self supervised autoencoders were developed to extract novel nonlinear markers. We evaluated the utility of these clustering (CLS) and autoencoder (AE) markers for patient prognostication across a range of outcomes (mortality, inpatient admission, and future disease development). Results Our study included 242,623 CBD samples from 127,545 patients. Both clustering and embedding approaches successfully generated hundreds of new clinical biomarkers. Many biomarkers showed strong prognostic associations for all cause mortality, inpatient admission, and development of anemia, cancer, or cardiovascular disease, with associations remaining significant after adjustment for demographics and clinical CBD markers. A large subset of these prognostic markers also showed high novelty, having low correlations to existing CBD markers, while also exhibiting significant correlations with broader physiologic signals, such as inflammatory, hormonal, infectious, and coagulopathic markers. Conclusion Collectively, these results demonstrate how modern AI techniques can allow for deeper phenotyping of routine clinical blood counts, generating novel biomarkers that capture more subtle physiologic signals than what are currently clinically utilized.

Purpose: To compare hypopyon detection using anterior segment optical coherence tomography (ASOCT) versus slit lamp examination (SLE) in microbial keratitis, and to evaluate intra-and inter-grader agreement for ASOCT hypopyon measurement. Methods: Two masked graders independently evaluated ASOCT images for hypopyon presence or absence in eyes with microbial keratitis, with disagreements resolved by consensus. A subset of hypopyon eyes underwent triplicate height measurement using two methods (endothelial length, vertical height). Cohen's kappa, intraclass correlation coefficients (ICC), sensitivity, and specificity were calculated comparing diagnostic performance of ASOCT versus SLE. Results: Inter-grader agreement for hypopyon detection on ASOCT was excellent (k=0.94; 95% CI 0.84-1.00) and intra-grader agreement was excellent (k=0.89-1.00). ASOCT detected hypopyon in 67.1% of eyes versus 57.0% by SLE (sensitivity 83.0%, specificity 96.2% using ASOCT as reference). Intra-grader reproducibility was excellent for both endothelial length and vertical height measurements (ICC 0.977-0.996). Inter-grader agreement was good for endothelial length (ICC 0.831) and vertical height (ICC 0.827), though a statistically significant inter-grader bias was identified for vertical height only (Wilcoxon p=0.008). Conclusions: ASOCT detected hypopyon with greater sensitivity than SLE and demonstrated excellent intra-grader and good inter-grader measurement reproducibility. Endothelial length showed slightly superior inter-grader concordance to vertical height measurement.

iii.Background and ObjectivesThe "Pan-European Transfusion Research InfrAstructure" (PETRA) project was established to advance the use of donor, blood product, and patient datasets in Europe, aiming to benefit both patient and donor health. Here, the initial PETRA objective was to describe the landscape of existing donor and blood establishment (BE) databases. Materials and MethodsAn online survey was circulated to the European Blood Alliances BE members. The survey collected information on the feasibility of accessing donor data, and challenges and possibilities for linking these datasets with information on the associated blood products and transfusion recipients, and donors own health records. ResultsSeventeen BEs across 16 countries completed the survey. The majority could, in principle, link their donor data to product data (13 BEs (76%)) and recipient data (10 BEs (59%)), for research purposes. However, capabilities were limited and in only 29% of the BEs was the donor to recipients linkage an automated process. BEs reported significant challenges to achieve full vein-to-vein linkage, including legal constraints and lack of consent (11 BEs) and resources (10-14 BEs). IT and data issues as well as lack of knowledge and training were cited as obstacles by a minority of BEs. ConclusionWhilst the survey results suggest considerable interest in developing linkages between blood donors, their products, and recipients, many challenges remain due to a variety of obstacles. First steps in working towards a PETRA may be assistance to navigate legal frameworks as well as investing in resources and quality and harmonisation of data collections. iv. HighlightsO_LI17 blood establishments (BEs) in 16 countries responded to a survey on obstacles and opportunities for achieving vein-to-vein datasets. C_LIO_LIIn 59% of the BEs donor-to-recipient links can be established for research improving transfusion outcomes, but only in 29% this is an automated process. C_LIO_LIIn order to work towards a "Pan-European Transfusion Research InfrAstructure" (PETRA), legal frameworks, adequate donor consent and (financial and human) resources are the most common obstacles that require addressing. C_LI

Anemia, particularly iron-deficiency anemia, is a critical global health concern, with a high prevalence among children under six years of age. Early and non-invasive detection can significantly improve health outcomes. This study proposes a computer vision and machine learning framework for anemia screening and hemoglobin (Hb) level prediction using palmar images from pediatric subjects. The region of interest (palm) was segmented using a U-Net model, achieving a Dice coefficient of 0.96. Images were processed across RGB, CIELab, and HSV color spaces to extract key color features, including red fraction, erythema index, and normalized a-component. For anemia classification, multiple machine learning models were evaluated, with Logistic Regression, Gradient Boosting, and a custom Convolutional Neural Network (CNN) achieving the highest test accuracies of approximately 94.5% and 95.53%, respectively. For hemoglobin regression, a Random Forest model in the CIELab color space achieved a coefficient of determination (R2) of 0.95. The Pearson correlation coefficient in the Lab color space was 0.98 for the Random Forest algorithm and 0.94 for the Linear Regression algorithm. The analysis, supported by SHAP values, identified red-related color features as the most significant predictors. The model demonstrated robust performance across different skin tones, with particularly high accuracy (R2 = 0.9926) in darker-skinned individuals, who constituted the majority of the studied Iranian population. The results confirm that pallor analysis of palmar images using artificial intelligence techniques offers a reliable, non-invasive, and effective tool for pediatric anemia screening and hemoglobin estimation, with strong potential for point-of-care applications.

Purpose To evaluate associations between optical coherence tomography angiography (OCT-A) metrics and diabetic retinopathy (DR) and compare their discrimination against conventional clinical risk factors. Methods In this cross-sectional study, 108 adult eyes (right eye if both eligible) with diabetes were recruited from tertiary ophthalmology/optometry clinics. DR was clinically graded using ETDRS categories and dichotomised as no DR vs >= mild NPDR (primary outcome). Macular 6x6 mm OCT-A (Zeiss AngioPlex) was acquired; scans with signal strength >7 and without major artefact were included. Quantitative metrics from the superficial capillary plexus included vessel density (VD) and perfusion density (PD) (central/inner/outer/full regions); structural OCT measures and FAZ parameters were secondary. Associations with >= mild NPDR were assessed using multivariable logistic regression adjusted for age, sex, HbA1c, and diabetes duration. Discrimination was evaluated with ROC curves/AUC (95% CI) and DeLong comparisons of AUCs. Results DR was present in 63% of eyes. DR was associated with lower VD (central, inner, outer, full) and lower PD (central, inner, full) (all p<=0.04). After adjustment, central VD (OR 0.82, 95% CI 0.68-0.98) and central PD (OR 0.92, 95% CI 0.86-0.99) remained independently associated with DR. The OCT-A model outperformed the clinical model (AUC 0.73 vs 0.60); the combined model yielded AUC 0.76. Conclusion VD and PD from the superficial plexus are independently associated with DR and show superior discrimination versus conventional clinical factors alone, supporting OCT-A as an adjunct for earlier DR detection.

The development of chemiluminescent immunoassays (CLIAs) is a complex and iterative process that relies on costly laboratory infrastructure, limiting its accessibility and application across healthcare settings and disease areas. Here, we detail the CLIA Mobile Development Kit (CLIAMDK) a modular, mobile, and inexpensive platform to assess image sensors, smartphones and data processing workflows for CLIA development. For its demonstration, we developed two CLIAs targeting renin and aldosterone, key biomarkers for diagnosing primary aldosteronism. The results from our performance study, including 50 patient samples, demonstrate the potential of our platform in a real-world scenario. We found that the performance of our mobile reader platform is comparable to that of a state-of-the-art plate reader, with a Lower Limit-of-Detection (LLoD) approaching 41 femtomolar. We envision that our platform will help accelerate CLIA development, make it more accessible, and lay the foundations for novel, distributed, yet highly sensitive diagnostic tests.

The 2024 dengue epidemic in Brazil-the largest arboviral emergency in the country's history-exposed critical gaps in the reliability of molecular diagnostics across its national public health laboratory network. Quality control (QC) of RT-qPCR assays performed by geographically dispersed Central Public Health Laboratories (LACENs) is essential to ensure the accuracy of epidemiological surveillance and clinical management. We conducted a multicenter QC evaluation of 3,192 complete RT-qPCR runs (19,152 datapoints) for dengue virus serotypes 1-4 (DENV1-4), Zika virus (ZIKV), and Chikungunya virus (CHIKV) across 15 LACENs over one epidemic year. An automated R-based bioinformatic pipeline applied hierarchical clustering (AGNES and DIANA), principal component analysis (PCA), linear and quadratic discriminant analysis (LDA/QDA), Shewhart and XmR control charts, process capability analysis, ANOVA, Baker's gamma permutation testing, and PVClust bootstrap clustering to positive-control cycle threshold (CT) value datasets. Median CT values for DENV4 positive controls ranged from 26.3 to 30.5 across laboratories, representing an approximately 16-fold difference in measured RNA quantity. PCA explained 54.1%-100% of total variance on PC1 across viral targets. Baker's gamma permutation tests confirmed significant concordance between AGNES and DIANA hierarchies across all six viral targets. LDA achieved 37.7% and QDA 49.1% cross-validated accuracy in laboratory-of-origin classification. PVClust bootstrap clustering identified DENV2+DENV4 (approximately unbiased probability, AU = 90) as the most analytically coherent serotype pair. ANOVA confirmed significant operator effects on ZIKV CT values (F = 8.799, df = 23), with regression coefficients for specific operators reaching beta; = +4.01 cycles-equivalent to an approximately 16-fold inferred difference in RNA quantity. Extreme outlier CT values signaled data integrity failures requiring immediate corrective action. The integrated multivariate QC framework substantially outperformed univariate Westgard-rule monitoring. Operator-specific CT deviations of up to four cycles carry direct consequences for clinical classification of borderline specimens. The automated R-based pipeline is operationally feasible in low-resource public health networks and provides a replicable model for arboviral diagnostic QC governance during epidemic emergencies.

Latent tuberculosis infection (LTBI) remains a significant barrier to global TB control and elimination efforts. The QuantiFERON-TB Gold (QFT) assay is commonly used for the diagnosis of LTBI. However, blood collected in QFT tubes is seldom utilized for molecular and genetic analysis due to the presence of heparin and a dense gel barrier that hinders efficient DNA extraction. To address this limitation, we aimed to develop a method for directly isolating high-quality DNA from blood in QFT tubes, eliminating the need for additional blood sampling and enabling their use in both diagnostic and molecular workflows. In this study, DNA was extracted from blood in EDTA and QFT tubes using a hybrid approach that combined manual lysis with three commercial kits: Thermo Scientific GeneJET, QIAamp DNA Blood Kit, and FavorPrep Blood Genomic DNA Extraction Kit. DNA concentration and purity were measured with a Multiskan SkyHigh Microplate Spectrophotometer, while integrity was assessed through agarose gel electrophoresis. Two nucleic acid amplification techniques (NAATs), ARMS-PCR and whole exome sequencing (WES) were performed to validate applicability of extracted DNA for molecular biology applications. We did not find any differences in the quantity, quality, or application of PCR or sequencing for DNA extracted from EDTA or QFT tubes. The extracted DNA from both EDTA and QFT tubes exhibited A260/280 ratios of 1.7-1.9 and concentrations ranging from 4.9 to 118.5 {micro}g/mL, indicating an adequate yield and purity. Intact genomic DNA and PCR product bands on agarose gel indicated suitability for downstream applications. Additionally, WES produced 6.47-8.71 GB of data per sample, with 42.8-57.7 M reads and GC content between 49.29% and 52.54%. Sequencing metrics were consistently strong, with Q20 values exceeding 98.6% and Q30 values above 95%. Our study presents an optimized and reproducible protocol for extracting high-quality DNA from QFT tubes, producing DNA suitable for both PCR and sequencing technologies. This protocol provides a cost-effective and practical strategy to integrate LTBI diagnosis with genomic research, particularly beneficial in resource-limited settings. This study introduces a novel analytical workflow applicable to diagnostic laboratory settings, enabling the integration of routine LTBI immunodiagnostic testing with downstream genomic analysis. The approach supports improved utilization of clinical specimens in laboratory medicine and may facilitate future biomarker and precision diagnostics research.

BackgroundSickle Cell Anaemia (SCA), a genetic blood disorder caused by a single mutation in the beta globin gene, displays a highly variable clinical course. Hydroxyurea (HU), an effective treatment, has an unclear mechanism of action. Plasma proteins can act as biomarkers for understanding disease states and response to HU treatment in SCA patients. MethodsPlasma proteome profiling of 31 healthy individuals and 76 SCA patients, including those with and without HU treatment, was performed using a high-performance liquid chromatography system and Orbitrap mass spectrometer. Statistical analysis was performed to identify differentially abundant proteins (DAPs) between SCA patients and healthy controls. Subgroup analyses were performed to look at the impact of HU treatment on plasma proteome. ResultsOur analysis yielded 43 DAPs in the plasma of SCA patients. Global correlation and protein-protein network analysis revealed that these proteins are part of a robust interaction network. Proteins showing higher abundance (LBP, ORM1 and TFRC) were primarily associated with immune response whereas those with reduced abundance (FBLN1 and F13B) were linked to blood coagulation and proteolysis. Differential abundance of several proteins such as CD14, FCN3, LFALS3BP, LAP and TGFBI was observed in either male or female patients indicating influence of gender. Importantly, HU treatment was associated with elevated levels of haptoglobin (HP) and hemopexin (HPX), key proteins involved in free hemoglobin scavenging. Notably, DAPs such as F10, LPA, and FCN3 overlapped with proteins previously reported to be differentially abundant in beta-thalassemia patients. Moreover, multiple proteins, including APOL1, AZGP1, FBLN1, GPLD1, HPX, LGALS3BP, and TFRC correlated with clinical parameters, such as blood transfusion frequency and, vaso-occlusive crisis, and WBC and platelet counts. ConclusionsThis study identifies novel differentially abundant plasma proteins in SCA, expanding the current repertoire of disease-associated biomarkers and proteins modulated by hydroxyurea therapy. The observed overlap with beta-thalassemia associated signatures reinforces shared pathophysiological mechanisms between these hemoglobinopathies. Several of these proteins show significant correlations with key clinical parameters and disease complications, offering insights into disease mechanisms and potential utility in disease management. Collectively, these findings provide a strong foundation for translational validation in larger, independent cohorts.

BackgroundSevere Fever with Thrombocytopenia Syndrome (SFTS) is an acute infectious disease with high mortality. This study aimed to develop a quantitative scoring system for grading SFTS severity using dynamic clinical data. MethodsA retrospective study included 547 confirmed SFTS patients from two hospitals. Clinical data were collected over a 14-day course (divided into four phases). Patients were grouped into survivors (n=451) and non-survivors (n=96). Statistical analyses, including Kaplan-Meier curves and log-rank tests, were performed. An external validation cohort of 44 new patients was used to validate the scoring system via C-statistic, calibration curves, and decision curve analysis (DCA). ResultsOf 547 patients, 96 (17.55%) were non-survivors. Multivariate logistic regression identified six independent prognostic factors across phases: age, platelet (PLT), aspartate aminotransferase (AST), and creatinine (Cr) (days 5-7); age, red blood cell distribution width (RDW), Cr, and lactate dehydrogenase (LDH) (days 8-10); Cr and LDH (days 11-14). A scoring system (0-11 points) was developed, stratifying patients into low (0-3), intermediate (4-7), and high (8-11) risk groups, with adverse outcome rates of 1.04%, 22.92%, and 76.04%, respectively. Kaplan-Meier curves showed significant prognostic differences (log-rank P<0.001). External validation (44 cases) confirmed excellent performance: AUC 0.810-0.952, good calibration (Hosmer-Lemeshow P>0.05), and net clinical benefit (DCA Eavg 0.068-0.098, Emax 0.422-0.559). ConclusionA dynamic SFTS severity scoring system was developed and validated. Internal and external validation confirmed its reliability and clinical utility, providing a simple, practical tool for timely assessment and early intervention.

PurposeTo evaluate the diagnostic performance of anterior segment optical coherence tomography (ASOCT) compared to slit lamp examination for identification of corneal perforation in microbial keratitis, and to assess ASOCT grading reproducibility. MethodsWe conducted a diagnostic concordance study of 150 eyes with microbial keratitis at a tertiary eye hospital in India. Two masked graders independently evaluated ASOCT scans for perforation, with disagreements resolved by consensus. We calculated Cohens kappa for inter-grader concordance and intra-grader repeatability. Sensitivity and specificity of slit lamp examination were calculated using ASOCT as the reference standard. Logistic regression identified factors associated with disagreement between modalities. ResultsInter-grader agreement for ASOCT was near-perfect ({kappa}=0.98; 95% CI, 0.92-1.00). ASOCT identified perforation in 24 eyes (16.0%) compared to 12 eyes (8.0%) by slit lamp examination. Using ASOCT as reference, slit lamp examination demonstrated 33.3% sensitivity (95% CI, 14.9-52.2%) and 96.8% specificity (95% CI, 93.4-99.2%). Odds of disagreement were significantly higher for eyes with stromal thinning (OR=8.19; 95% CI, 2.27-29.54), mid-stromal involvement (OR=4.44; 95% CI, 1.08-18.30), and infection within 2mm of the limbus (OR=8.81; 95% CI, 1.77-43.80). ConclusionsASOCT enables highly reproducible perforation grading and detects substantially more perforations than slit lamp examination, particularly in severe disease. These findings support ASOCT as an objective tool for clinical assessment and outcome ascertainment in microbial keratitis.