Clinica Chimica Acta最新文献

{"title":"Immature platelet fraction in cardiology","authors":"Zhao Cao ,&nbsp;Hamed Soleimani Samarkhazan","doi":"10.1016/j.cca.2025.120600","DOIUrl":"10.1016/j.cca.2025.120600","url":null,"abstract":"<div><div>Cardiovascular diseases (CVDs) remain a leading global cause of mortality, necessitating biomarkers that enhance risk stratification and therapeutic personalization. The Immature Platelet Fraction (IPF), representing young, RNA-rich platelets (also known as reticulated platelets, RP) released from bone marrow, has emerged as a dynamic biomarker linking platelet turnover to cardiovascular pathophysiology. Clinically, elevated IPF is associated with adverse outcomes in acute coronary syndromes (ACS), myocardial infarction, and post-cardiac surgery, particularly when measured 24–72 hours after the event or post-operatively. It correlates with infarct size, recurrent thrombosis, and major adverse cardiovascular events (MACE), though its predictive value is inconsistent at the initial clinical encounter. Its rise reflects compensatory thrombopoiesis in hypercoagulable states like diabetes, COVID-19, and malignancy. IPF also informs antiplatelet therapy, high IPF correlates with clopidogrel resistance but not ticagrelor, guiding agent selection and dual antiplatelet therapy (DAPT) duration. Despite standardization challenges across measurement platforms (flow cytometry vs. automated analyzers), IPF outperforms mean platelet volume (MPV) in tracking platelet activity. Future directions include point-of-care IPF devices, multi-marker panels, and novel therapies targeting thrombopoiesis. Integrating IPF into clinical practice promises refined risk assessment, personalized treatment, and improved prognostic precision in cardiology, bridging translational innovation to patient care. This review synthesizes current evidence on IPF’s role in CVDs, highlighting its molecular characteristics, elevated prothrombotic mediators (e.g., thromboxane A₂, P-selectin), heightened reactivity, and rapid response to inflammatory stimuli.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"579 ","pages":"Article 120600"},"PeriodicalIF":2.9,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145058318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An approach for the calculation of preliminary measurement uncertainty values in clincial routine laboratories using verification data","authors":"Simon Michaelis ,&nbsp;Laura Binder ,&nbsp;Christopher Schneider ,&nbsp;Wolfgang J. Schnedl ,&nbsp;Andreas Baranyi ,&nbsp;Dietmar Enko","doi":"10.1016/j.cca.2025.120605","DOIUrl":"10.1016/j.cca.2025.120605","url":null,"abstract":"<div><h3>Background</h3><div>The measurement uncertainty is an essential measure of quality in clinical routine laboratories. Its estimation is mandatory for the ISO 15189 accreditation. However, there is no in consensus on how to establish the MU. The study aimed to evaluate a procedure for calculating a preliminary MU based on already existing verification data and results from external quality assessment (EQA) schemes.</div></div><div><h3>Methods</h3><div>Expanded measurement uncertainty (U) was calculated for 29 measurands using two different data sets applying the Nordtest protocol. One U was determined with internal quality control (IQC) data from one year (60 measurements/level; two levels) and six EQA-samples (MU_IQC-scheme), the second U was performed with verification data according to the CLSI EP15-A3 guideline (25 measurements/level, 5x5-scheme; two levels) and four EQA samples (MU_Verification-scheme). The difference between MU_IQC and MU_Verification (ΔU) was calculated. MU_IQC and MU_Verification were compared to published acceptance criteria (Rili-BAEK and Westgard).</div></div><div><h3>Results</h3><div>For most measurands, U was higher for MU_IQC (range 2.2 %–20.9 %) compared with MU_Verification (range 2.2 %–13.0 %). The ΔU ranged between −1.8 %–13.8 %. Five measurands showed a ΔU of &gt; 5 %, while seven measurands showed a higher U for MU_Verification (ΔU-range −1.8 %–−0.8 %). For all measurands, the U for MU_IQC and MU_Verification were within the Rili-BAEK and Westgard acceptance criteria.</div></div><div><h3>Conclusion</h3><div>The use of verification data may serve as a suitable approach for the estimation of preliminary MU values in clinical routine laboratories.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"579 ","pages":"Article 120605"},"PeriodicalIF":2.9,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Serum miRNA panel for prostate cancer diagnosis","authors":"Xu-Xiao Guo,&nbsp;Shu-Mei Bai","doi":"10.1016/j.cca.2025.120601","DOIUrl":"10.1016/j.cca.2025.120601","url":null,"abstract":"","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"579 ","pages":"Article 120601"},"PeriodicalIF":2.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lipoprotein(a) in neoplastic transformation","authors":"Dan-Qi Han ,&nbsp;Tian-Yi Ma ,&nbsp;Duo-Hong Wu ,&nbsp;Shi-Juan Lu ,&nbsp;Jiang-Hua Zhong ,&nbsp;Jian-Jun Li","doi":"10.1016/j.cca.2025.120581","DOIUrl":"10.1016/j.cca.2025.120581","url":null,"abstract":"<div><div>Cardiovascular diseases and cancer are top global causes of death, sharing risk factors and treatment strategies. Although dyslipidemia is linked to both, its exact roles are unclear. Recent studies suggest a potential association between plasma lipoprotein(a) levels and cancer risk. This review compiles the latest on lipoprotein(a)’s relation to several cancers and explores potential underlying mechanisms, aiming to deepen understanding of its role in cancer.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"579 ","pages":"Article 120581"},"PeriodicalIF":2.9,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145029045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wilms’ tumor 1 in urinary exosomes as a non-invasive biomarker for diabetic nephropathy","authors":"Anuradha Kalani ,&nbsp;Shatakshi Chaturvedi ,&nbsp;Pankaj Chaturvedi","doi":"10.1016/j.cca.2025.120599","DOIUrl":"10.1016/j.cca.2025.120599","url":null,"abstract":"<div><div>Diabetic nephropathy (DN) is a major cause of end-stage renal disease, with podocyte injury representing an early pathogenic event. Conventional biomarkers such as albuminuria and eGFR identify renal damage only at advanced stages, limiting opportunities for timely intervention. Wilms’ Tumor 1 (WT1), a podocyte-specific transcription factor, has emerged as a sensitive marker of early glomerular stress. Earlier studies show that urinary exosomal WT1 was detected in 33 of 48 type 1 diabetic patients but only in 1 of 25 healthy controls. WT1 levels correlated positively with albumin-to-creatinine ratio (r = 0.89, p &lt; 0.001), and inversely with eGFR (r = –0.62, p &lt; 0.001). Moreover, WT1 predicted reduced renal function (eGFR &lt; 60 ml/min/1.73 m²) with high accuracy (AUC = 0.92). Animal studies further demonstrated that exosomal WT1 rises before albuminuria and declines with therapy. These findings position urinary exosomal WT1 as a non-invasive, podocyte-specific biomarker for early detection and monitoring of DN.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"579 ","pages":"Article 120599"},"PeriodicalIF":2.9,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145029035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of serum Ninj1 as a potential biomarker for predicting severity in patients with COVID-19","authors":"Hua Sun ,&nbsp;Ling Yan ,&nbsp;Hong Chen,&nbsp;Ding Wang,&nbsp;Chenfan Niu,&nbsp;Siyang Wen,&nbsp;Qin Hu","doi":"10.1016/j.cca.2025.120591","DOIUrl":"10.1016/j.cca.2025.120591","url":null,"abstract":"<div><div>Infection with SARS-CoV-2 elevates the expression of cytokines, resulting in a cytokine storm that serves as the primary factor for severe illness and mortality; however, effective markers for predicting disease severity and preventing are lacking. Thus, we investigated the association between serum levels of nerve injury-induced protein 1 (Ninj1), a mediator of plasma membrane rupture, and the extent of lung damage in COVID-19 patients was examined to anticipate the severity of SARS-CoV-2 infection. This study included 62 healthy participants and 264 patients with COVID-19. The serum levels of Ninj1, cytokines (interleukin (IL)- 1β, IL-2, IL-6, IL-8, IL-10, interferon-γ (IFN-γ), and tumor necrosis factor-alpha (TNF-α)), and inflammatory markers (C-reactive protein (CRP), procalcitonin (PCT), ferritin, and lactate dehydrogenase (LDH)) were measured and correlated with disease severity using Pearson’s correlation test. Our tests revealed that elevated levels of Ninj1, IL-6, PCT, and LDH were observed in individuals suffering from COVID-19, and these concentrations were linked to the severity of the illness. Analysis of correlation indicated that Ninj1 levels were related to the concentrations of these biomarkers. Additionally, Ninj1 expression exhibited a correlation with the viral load of SARS-CoV-2. Circulating Ninj1 levels showed good predictive potential for respiratory failure and prognosis. Finally, we found that SARS-CoV-2 infection increases serum Ninj1 levels, which are correlated with disease severity. Ninj1 could serve as a serum biomarker for forecasting the severity of COVID-19.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"579 ","pages":"Article 120591"},"PeriodicalIF":2.9,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145013973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population-adjusted cut-off: A new approach for enhancing the diagnostic efficacy of hematological discrimination formulae for screening β-Thalassemia trait","authors":"Isuru Aravinda ,&nbsp;Shashini Dharmasiri ,&nbsp;Chathurika Sewwandi ,&nbsp;Sinthu Karunaithas ,&nbsp;Sonali Goonetilleke ,&nbsp;Karunaithas Rasaratnam","doi":"10.1016/j.cca.2025.120592","DOIUrl":"10.1016/j.cca.2025.120592","url":null,"abstract":"<div><div>Screening for β-thalassemia trait (βTT) is crucial for preventing β-thalassemia major in offspring. Although hematological discrimination formulae (HDF), developed using complete blood count parameters, are cost-effective tools for screening βTT, their performance varies across different populations. This study evaluated the performance of 32 HDF for screening βTT in the Sri Lankan population. Data were retrieved from laboratory databases and categorized into confirmed βTT and non-βTT groups based on high-performance liquid chromatography results. The βTT screening performance of the HDF was assessed using accuracy measurements, the receiver operating characteristic (ROC) curve, and Youden’s index (YI). Furthermore, a population-adjusted cut-off was determined using the Index of Union (IU) method to optimize the predictive accuracy of HDF in screening βTT. Bordbar demonstrated excellent predictive performance in males (AUC = 0.908; YI = 0.815), while Shine &amp; Lal, Kerman-I, Nishad, Sehgal, Bordbar, and Roth demonstrated high discriminative ability in females (AUC &gt; 0.833; YI &gt; 0.666). Applying a population-adjusted cut-off improved the βTT screening potential of Shine &amp; Lal, Kerman-I, Nishad, Bordbar, and Roth in males (AUC &gt; 0.911; YI &gt; 0.822) and enhanced the performance of Kerman-II in females (AUC &gt; 0.861; YI &gt; 0.722). Notably, Shine &amp; Lal (AUC = 0.937; YI &gt; 0.873) and Nishad (AUC = 0.897; YI &gt; 0.794) demonstrated the best performance for males and females, respectively, when a population-adjusted cut-off was applied for screening βTT. In conclusion, determining a population-adjusted cut-off is a new initiative to enhance the βTT screening performance of HDF across different populations.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"579 ","pages":"Article 120592"},"PeriodicalIF":2.9,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Residual disease in NPM1-mutated acute myeloid leukemia","authors":"Pejman Hamedi-Asl ,&nbsp;Amineh Hosseinkhani ,&nbsp;Nafiseh Sanei-Ataabadi ,&nbsp;Anahita Ranjbar ,&nbsp;Horsa Sadat Seyedebrahimi ,&nbsp;Taraneh Hoseinnezhad ,&nbsp;Paria Zahedi ,&nbsp;Davod Jafari ,&nbsp;Majid Safa","doi":"10.1016/j.cca.2025.120586","DOIUrl":"10.1016/j.cca.2025.120586","url":null,"abstract":"<div><div>Acute myeloid leukemia (AML) represents a genetically heterogeneous malignancy, with mutations in the nucleophosmin-1 (NPM1) gene identified as the most prevalent and clinically significant molecular biomarkers. These mutations play a crucial pivotal role in the realms of diagnosis, prognosis, and therapeutic decision-making. Although an ideal measurable residual disease (MRD) test has yet to be developed, there is increasing acknowledgment of the significance of advanced molecular methodologies for monitoring MRD in NPM1-mutated (<em>NPM1^mut</em>) AML. This underscores the necessity to customize strategies according to individual mutation profiles and clinical scenarios. Techniques such as quantitative PCR (qPCR), next-generation sequencing (NGS), and Droplet Digital PCR (ddPCR) are evaluated for their sensitivity and specificity in the detection of MRD. Concurrently, innovative approaches, including CRISPR-Cas9 and single-cell sequencing, are particularly instrumental in elucidating complex diseases like AML, where conventional methods frequently fall short in identifying clonal diversity and MRD. Furthermore, the incorporation of artificial intelligence (AI) is emphasized for its potential to enhance diagnostic accuracy, enhance prognostic modeling, and streamline personalized treatment planning. Despite its considerable potential, only a limited number of AI and machine learning (ML) tools have been fully integrated into clinical practice. This limited adoption is primarily due to challenges related to data quality, equity, the need for advanced infrastructure, and the establishment of robust evaluation metrics. While AI offers significant promise in the field of MRD in <em>NPM1^mut</em> AML, its widespread use remains constrained by critical issues, including algorithmic bias, data integrity concerns, and the lack of regulatory frameworks and safety standards capable of keeping pace with rapid technological advancements. This review elucidates the dynamic landscape of MRD monitoring and rigorously assesses the challenges inherent in contemporary molecular techniques such as qPCR, in addition to interdisciplinary technologies—including single-cell sequencing, CRISPR-based methodologies, and AI-driven analyses—focusing on the implementation of these technologies and their implications for improving clinical decision-making in <em>NPM1^mut</em> AML.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"579 ","pages":"Article 120586"},"PeriodicalIF":2.9,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144996985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Glucose metabolism in anterior pituitary adenomas","authors":"Valeria Hernández-Brito ,&nbsp;Stephanie Lemoni Casco-Morales ,&nbsp;Andrés Vega-Rosas","doi":"10.1016/j.cca.2025.120587","DOIUrl":"10.1016/j.cca.2025.120587","url":null,"abstract":"<div><div>Glucose metabolism alterations are frequently observed in patients with secretory pituitary adenomas. The most commonly secreted hormones in these tumors include prolactin, growth hormone (GH), adrenocorticotropic hormone (ACTH), and thyroid-stimulating hormone (TSH), all of which can disrupt glucose homeostasis through distinct pathophysiological mechanisms. Prolactin stimulates pancreatic β-cell proliferation, enhances insulin gene transcription, increases intracellular insulin content, and augments glucose-induced insulin secretion. GH promotes lipolysis and hepatic glucose production while impairing peripheral glucose uptake, contributing to insulin resistance. ACTH, via excess glucocorticoids, reduces GLUT-4 translocation, enhances gluconeogenesis and proteolysis, and inhibits glycogen synthesis. Excessive TSH leads to increased T3 and T4 production, which in turn stimulate glucose uptake in muscle and enhance both glycolysis and gluconeogenesis. This review summarizes the current understanding of how hormone hypersecretion in pituitary adenomas contributes to glucose metabolism dysregulation.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"578 ","pages":"Article 120587"},"PeriodicalIF":2.9,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assay-specific machine-learning models converting insulin to C-peptide or C-peptide index and C-peptide to HOMA2-IR: Single-center retrospective observational study","authors":"Yuichiro Iwamoto,&nbsp;Tomohiko Kimura,&nbsp;Toshitomo Sugisaki,&nbsp;Kazunori Dan,&nbsp;Hideyuki Iwamoto,&nbsp;Junpei Sanada,&nbsp;Yoshiro Fushimi,&nbsp;Masashi Shimoda,&nbsp;Shuhei Nakanishi,&nbsp;Tomoatsu Mune,&nbsp;Kohei Kaku,&nbsp;Hideaki Kaneto","doi":"10.1016/j.cca.2025.120585","DOIUrl":"10.1016/j.cca.2025.120585","url":null,"abstract":"<div><h3>Background</h3><div>In this study, we employed machine learning to develop a conversion method for comparing immunoreactive insulin (IRI) and C-peptide immunoreactivity (CPR), which are indicators of endogenous insulin secretion capacity, using a standardized approach.</div></div><div><h3>Methods</h3><div>This is a single-center retrospective observational study of 449 patients with type 2 diabetes (T2D) who were hospitalized at our hospital and 63 patients with T2D who were treated as outpatients, focusing on patients in whom IRI and CPR were measured simultaneously.</div></div><div><h3>Results</h3><div>The gradient boosting decision tree (GBDT) model constructed for hospitalized patients used seven features, including IRI, and showed an accuracy of R² = 0.641 and MSE = 0.247 ng/mL after applying a nonlinear transformation to the CPR index (CPI). The correlation coefficient between actual CPI and predicted CPI was r = 0.943. The accuracy of the GBDT model, which nonlinearly transforms HOMA2-IR using seven features, including CPR, was R² = 0.615 and MSE = 0.268. The correlation coefficient between the actual HOMA2-IR and the predicted HOMA2-IR was r = 0.943. When the model was applied to outpatients, CPI and HOMA2-IR were significantly correlated with actual values (r = 0.820 and r = 0.812, respectively).</div></div><div><h3>Conclusions</h3><div>If either IRI or CPR is measured, it will be possible to evaluate endogenous insulin secretion capacity and insulin resistance using the same standards, and it is expected to be used as an auxiliary indicator in future clinical research and when integrating data from multiple institutions.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"578 ","pages":"Article 120585"},"PeriodicalIF":2.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144988149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}