Clinica Chimica Acta最新文献

Chronic kidney disease (CKD) is a prevalent health condition characterized by gradual kidney function loss. Early detection is crucial for the effective management and treatment of CKD. A promising biomarker for various diseases, including chronic kidney disease, is microRNAs (miRNAs), which are becoming increasingly important due to their stability and differential expression in various disease-related states, including CKD. Recent developments in microRNA biosensors have made it possible to detect miRNAs associated with CKD in a sensitive and specific manner. This review article discusses the current state of microRNA biosensors for detecting CKD and highlights their potential applications in clinical settings. Various microRNA biosensors, including electrochemical, optical, and nanomaterial-based sensors, are explored for their ability to detect specific miRNAs linked to CKD progression. The advantages and limitations of these biosensors are evaluated, focusing on factors such as sensitivity, specificity, and ease of use. Overall, microRNA biosensors are promising diagnostic tools for early detection of CKD. However, challenges such as standardizing protocols, validating in large cohorts, and translating to clinical practice remain to be addressed. Future research efforts should aim to overcome these limitations to fully realize the potential of microRNA biosensors in improving the diagnosis and management of CKD.

Over 1400 variants of hemoglobin (Hb) have been identified and characterized with phenotypes ranging from clinically silent to severe clinical manifestations in carriers. Different analytical methods have been established to detect Hb variants. Here, we report the first pediatric case of hemoglobin I-High Wycombe [β59(E3) Lys → Glu] variant found in an infant of Mexican-American descent. The patient is thriving and has no clinical complication due to this hemoglobinopathy. In this case, globin chain analysis and peptide mapping by reversed phase high-performance liquid chromatography revealed the presence of hemoglobin I-High Wycombe which can easily be reported incorrectly as beta thalassemia trait.

Electrochemical biosensors have revolutionized the detection of biomarkers related to depression and the quantification of antidepressant drugs. These biosensors leverage nanomaterials and advanced assay designs to achieve high sensitivity and selectivity for clinically relevant analytes. Key neurotransmitters implicated in depression, such as serotonin, dopamine, and glutamate, can be accurately measured via biosensors, providing insights into the effects of antidepressant treatments on neurotransmission. Biosensors can also detect biomarkers of inflammation, oxidative stress, and neuronal health that are altered in depression. Real-time biosensing techniques such as fast-scan cyclic voltammetry enable monitoring of dynamic neurotransmitter changes during depressive episodes and pharmacological interventions. Advancements incorporating graphene, gold nanoparticles, and other nanomaterials have enhanced biosensor performance, enabling the detection of low biomarker concentrations. Closed-loop biosensing systems hold promise for precision medicine by automating antidepressant dosage adjustments on the basis of neurotransmitter levels. A wide range of depression biomarkers, including apolipoprotein A4, heat shock protein 70, brain-derived neurotrophic factor, microRNAs, proteins, and combinatorial biomarker panels, have been detected via sophisticated biosensor platforms. Emerging biosensors show selectivity for antidepressant drugs such as serotonin-norepinephrine reuptake inhibitors, tricyclic antidepressants, and selective serotonin reuptake inhibitors in biological samples. This review emphasizes the transformative potential of electrochemical biosensors in combating depression. By facilitating earlier and more accurate diagnoses, these biosensors can revolutionize patient care and enhance treatment outcomes.

Mycobacterium species cause several vital human diseases, including tuberculosis and non-tuberculous mycobacterial infections, which are treated with different drug regimens Therefore, accurate and rapid diagnosis is essential for effective treatment and controlling the spread of these pathogens. This study aims to develop an isothermal method combining RPA and CRISPR-Cas12a techniques, named as MyTRACK, to detect and differentiate major clinical mycobacteria at the species level. The assay has no cross-reactivity with limit of detection of 1 to 100 copies/reaction for various targeted mycobacteria. The results demonstrated 100 % specificity and 92.59 % to 100 % sensitivity in clinical isolates and were consistent with the culture technique with LPA for clinical samples. The MyTRACK assay is an effective, portable, rapid, and accurate screening method for mycobacterial detection and identification, especially in low-resource clinical settings.

T2DM detection methods are commonly used in teens and adults but are generally unsuitable to unborn fetuses in the context of non-invasive prenatal testing (NIPT). Biophysical and biochemical tests for fetuses are often invasive, carry risks, and have low sensitivity and specificity, with no direct method available to diagnose T2DM in utero. In contrast, cell-free DNA (cfDNA) is known have high sensitivity (93-98 %) and specificity (94-100 %) for cancer detection and fetal genetic disorders (trisomy 21, 8, and 13) making it applicable for fetal epigenetic and genetic analysis, including T2DM early detection. However, no study has explored its use for this purpose. Our review focuses on the potential of IGFBP methylation levels in cfDNA as biomarkers for NIPT of T2DM. Placental global hypomethylation in GDM may predict T2DM during the prenatal period, and a similar pattern potentially be detected in cfDNA. Targeted genes reliable for NIPT, such as IGFBPs are needed because their significant role in T2DM and GDM. Among these, IGFBP-1 and IGFBP-2 have shown potential as predictive genes, exhibiting hypermethylation in placental tissue from GDM cases. This hypermethylation reduces their expression and the formation of the IGF-1-IGFBP complex, leading to increased levels of free IGF-1, which is associated with T2DM in the fetus. Hypermethylation regions have longer fragment sizes in cfDNA, thus in T2DM cases, hypermethylation of IGFBP-1 and IGFBP-2 from fetus results in longer cfDNA fragments. Therefore, analyzing the methylation levels and fragment sizes of IGFBP-1 or IGFBP-2 cfDNA could be a promising biomarker for identifying fetal T2DM risk non-invasively.

Psoriatic arthritis (PsA), a chronic autoimmune disease of unclear aetiology, is associated with dysregulated angiogenesis due to the proliferation, migration, and differentiation of endothelial cells. Vascular endothelial growth factor (VEGF) plays a key role such that PsA patients exhibit skin and joint symptoms, e.g., pain and stiffness, with morphologic alterations in blood vessels. To more fully examine this phenomenon, a systematic review and meta-analysis compliant with the PRISMA guidelines (PROSPERO CRD42024572653) was conducted using subgroup and meta-regression analyses. Secondary analyses on disease activity and response to treatment were also included. In the twelve selected studies, VEGF was significantly higher in PsA vs healthy controls (SMD = 0.544, 95 % CI 0.253-0.835;p < 0.001) with moderate heterogeneity across studies. Subgroup analysis revealed that the SMD in prospectively conducted studies was significantly higher vs those conducted retrospectively (p = 0.005). Furthermore, methotrexate or sulfasalazine treatment did not affect VEGF which remained significantly higher than controls. Moreover, VEGF was lower in those with inactive disease and in those receiving disease modifying agents in pre-post studies. These findings suggest that VEGF is a promising candidate biomarker in PsA and worthy of further prospective studies to investigate its utility in monitoring disease progress and response to treatment.

Since Candida albicans, a type of fungus, causes severe infections that pose a significant threat to human health, its rapid detection is critical in clinical antifungal therapy. Traditional fungal diagnostic approaches are largely based on the culture method. This method is time-consuming and laborious, taking about 48-72 h, and cannot identify emerging species, making it unsuitable for critically ill patients with bloodstream infections, sepsis, and so on. Other antigen or nucleic acid amplification-based methods were also found to be unsuitable for Point-of-Care Testing (POCT) diagnosis due to various limitations. Therefore, establishing a new approach for the rapid diagnosis of Candida spp is imperative. Herein, we proposed a novel diagnostic method for invasive fungi detection. Specifically, we created a new CRISPR diagnostic platform for Candida albicans-specific Internal Transcriptional Spacer 2 (ITS2) gene by combining the DNase cleavage activity of Cas12a with Recombinase Polymerase Amplification (RPA). Furthermore, to achieve rapid on-site detection under low-resource conditions, we used a transverse lateral flow strip with a single target to visualize the Cas12a single enzyme digestion product. We designated the platform as a rapid molecular detection tool that integrates RPA and the CRISPR-Cas12a technology. The entire platform can accurately identify Candida albicans within 50 minwhile remaining unaffected by other fungi or bacteria. Furthermore, the detection limit of the platform could reach 10² CFU/ml. Moreover, this approach offers additional benefits, including easy operation, low set-up cost, and broad applicability for Candida albicans detection across medical institutions at all levels, especially in township health centers in resource-poor regions.

The establishment of reference systems for the standardization of hemoglobin A₂ (HbA₂) and fetal hemoglobin (HbF), both critical for improving diagnostic accuracy in conditions such as β-thalassemia and sickle cell disease, are described. Efforts were led by the IFCC and other groups to address and reduce the variability in laboratory measurements of these hemoglobins. This document outlines the production of certified reference materials (CRMs) for HbA₂ and the development of a reference measurement procedure using isotope dilution mass spectrometry. Similarly, standardizing HbF is essential for supporting diagnostic and therapeutic strategies, particularly in managing sickle cell disease. HbF levels can predict disease outcomes and guide treatment plans. Significant challenges remain in achieving consistent measurement across laboratories, and the process for standardization for this minor hemoglobin has just begun. We are confident that the implementation of these reference systems will provide improved accuracy and traceability in the future.

Background: The question of whether to treat patients with chronic hepatitis B (CHB) during the immune tolerance (IT) period is a matter of ongoing debate, as it is difficult to discern different levels of liver disease severity. We created and assessed a novel diagnostic model for identifying significant liver tissue damage in individuals with CHB in IT phase.

Methods: From November 2018 to December 2022, a cross-sectional study of 311 patients with chronic hepatitis B virus infection (HBV DNA > 30 IU/mL) at Ningbo No. 2 Hospital, Ningbo, China, who underwent liver biopsy, including 44 patients in IT phase. Utilizing univariate regression analyses and logistics analysis, and model was developed and validated to predict the severity of hepatic inflammatory and fibrosis in CHB patients and in IT phase.

Results: Chitinase 3-like Protein (CHI3L1), albumin (ALB), alanine transaminase (ALT) / aspartate aminotransferase (AST) were identified as independent predictors of liver lesion severity in CHB patients with IT. The three were combined to build the model (named as CAA index), which demonstrated good performance. The CAA index achieved an area under the receiver operating characteristic curve (AUC) of 0.916 (95 % CI, 0.820-1.000) and AUC of validation group was 0.875 (95 % CI, 0.683-1.000).

Conclusions: CHI3L1 serves as an independent measure of liver fibrosis and inflammation in CHB. This diagnostic model has some value in assessing the severity of the patient's liver lesion severity and may be a reliable non-invasive diagnostic model helping determine whether treatment is necessary among CHB patients in IT phase.

Background: Biopsy is the gold standard method for diagnosing liver fibrosis. FibroScan is a non-invasive method of diagnosing liver fibrosis, but it still faces some limitations. This study aimed to establish a nomogram model and identify patients at high risk of advanced liver fibrosis associated with hepatitis B infection.

Methods: Data were collected from 375 patients with hepatitis B who underwent liver biopsy. Patients were divided randomly into the training (n = 263) and validation sets (n = 112). Their demographic and clinical characteristics were analyzed using the least absolute shrinkage and selection operator regression (LASSO). A nomogram model was established to predict the fibrosis stage, and its performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) and was compared with other recognized models.

Results: In total, 209 patients with non-advanced fibrosis (S0-1) and 166 patients with advanced fibrosis (S ≥ 2) were included. Hyaluronic acid (HA), laminin, total cholesterol (TC), platelet, and age were entered into the nomogram model based on the LASSO analysis. The nomogram model for predicting advanced fibrosis exhibited a relatively high AUC in the training set. Compared with FIB4 and APRI, the nomogram model showed a better agreement between the actual status and predicted status based on the calibration curve. The nomogram model showed an AUC similar to FibroScan in the validation cohort, and showed high clinical net benefits in the training and validation sets.

Conclusion: Our nomogram model can help identify patients with hepatitis B and advanced liver fibrosis.