Clinica Chimica Acta最新文献

The emergence of multidrug-resistant (MDR), extensively drug-resistant (XDR), and pandrug-resistant (PDR) bacteria poses a significant threat to global public health, complicating the management of infectious diseases and increasing morbidity and mortality rates. Rapid and sensitive detection of these resistant pathogens is crucial for effective treatment and infection control. This manuscript provides a comprehensive overview of various biosensor technologies developed for the rapid identification and quantification of MDR and XDR bacteria. We discuss the principles of operation, sensitivity, specificity, and practical applications of different biosensing platforms, including electrochemical, optical, and piezoelectric sensors. Additionally, we explore recent advancements in nanomaterials and microfluidics that enhance biosensor performance and enable point-of-care testing. The manuscript also addresses the challenges faced in the implementation of these technologies in clinical settings, such as regulatory hurdles and the need for standardization. A systematic literature review was conducted to identify relevant studies. Databases utilized include PubMed and Scopus, covering the time frame from 2015 to 2024. The literature screening criteria focused on the inclusion of only clinically validated studies to ensure the reliability and applicability of the findings. By highlighting the potential of biosensors to revolutionize the detection of drug-resistant bacteria, this work aims to inform researchers, clinicians, and policymakers about the critical role of innovative diagnostic tools in combating antibiotic resistance and improving patient outcomes.

Background: Chromosome abnormalities are a leading cause of conception failure and pregnancy loss. While traditional cytogenetics technologies like karyotyping have been helpful in identifying structural variations (SVs), they face challenges in detecting complex rearrangements and cryptic structures. In this study, we developed a new method called chromosome conformation based karyotyping (C-MoKa) to comprehensively detect different types of chromosomal abnormalities in patients with conception failure and pregnancy loss.

Methods: A total of 70 clinical samples exhibiting known results of SVs, mosaic aneuploidies, copy number variations （CNVs） and uniparental disomy (UPD) were included in our cohort and underwent C-MoKa analysis. The results obtained from different techniques, including karyotyping, CNV-seq, and CMA were compared and analyzed.

Results: Distinct chromosomal conformation patterns of various variations were observed and analyzed in clinical samples. Our C-MoKa method not only validated all the findings of karyotyping, CNV-seq and CMA, but also provided more detailed results. It demonstrated superior fragment resolution (<500 Kb) and more precise breakpoints (>100 kb). Moreover, C-MoKa showed higher sensitivity in decoding intricate rearrangements in a single test.

Conclusions: Our results highlight the potential utility of C-MoKa in precisely unraveling SVs, mosaic aneuploidies, CNVs, and UPD in clinical settings, which can significantly impact further clinical decision-making.

Introduction: To perform simulation studies on patient-based real-time quality control (PBRTQC) for aspartate aminotransferase (AST), iron (Fe), potassium (K), and thyrotropin (thyroid stimulating hormone, TSH) analytes, focusing on optimizing systematic error detection while minimizing data loss.

Methods: Clinical laboratory data for the four analytes were analyzed using various truncation methods. Among these methods, truncation limits corresponding to fixed percentiles (e.g., 1st-99th percentiles), reference change value based on between-individual biological variation (RCVg), and truncation limits derived from ± 3 standard deviations from the mean were included. These exclusion methods were applied using trimming or winsorization techniques, and transformation methods (logarithmic, square root, and Yeo-Johnson transformations) were employed to fit the data to a normal or near-normal distribution. Moving average techniques, such as exponentially weighted moving average (EWMA), were used with various block sizes to evaluate systematic error detection performance.

Results: Truncation based on RCVg improved performance for analytes with lower individuality indices-AST, potassium, and TSH-by enabling faster error detection. In contrast, methods either without truncation or with winsorization applied proved to be more effective for Fe. Among the moving average methods, EWMA with smaller block sizes (20 and 30) generally showed superior performance by detecting systematic errors more quickly.

Conclusion: RCVg-based truncation improves error detection for analytes with low individuality when combined with PBRTQC methods like EWMA, minimizing data loss. Tailored strategies considering analyte-specific individuality and distribution are essential for optimal error monitoring, warranting further validation in diverse clinical settings.

Background: To explore the underlying causes of significant fluctuations in creatinine levels within three days due to transient and severe uric acid elevation, and to provide evidence for the interpretation of abnormal test results and clinical diagnosis and management.

Methods: The issues were resolved by retesting the samples, comparing results across different detection platforms, and analyzing the reaction curve. We comprehensively reviewed patients' general conditions, imaging examinations, and treatments. Additionally, we compared pre- and post-admission changes in laboratory indices and performed an extensive literature search for comprehensive analysis.

Results: At the patient's first visit, the levels of uric acid (UA), creatinine (CR), and urea (UREA) were measured at 891 umol/L, 211 umol/L, and 7.8 mmol/L, respectively using a Roche full-automatic biochemical analyzer and its corresponding reagents. Subsequent testing yielded 917 umol/L, 211 umol/L, and 8.3 mmol/L for UA, CR, and UREA. After retesting with the Beckman automatic biochemical analyzer and its corresponding reagents, the results for UA, CR, and UREA were 1013 umol/L, 221 umol/L, and 7.75 mmol/L, respectively. The results of the two detection systems were in agreement. A supplementary measurement of Cystatin C (CYSC) at 1.69 mg/L indicates renal dysfunction, consistent with the observed increase in CR levels and ruling out false elevation due to assay-related issues. At 48 h post-admission, untreated, the levels of blood UA, CR, and UREA decreased to 567umol/L, 77umol/L, and 5.1 mmol/L, respectively. Through literature review and analysis, it was determined that the transient abnormal increase in the patient's creatinine level may be attributed to a substantial accumulation of uric acid crystals obstructing the renal tubules, leading to an impediment in renal tubular excretion which subsequently resolves spontaneously.

Conclusion: Severe hyperuricemia may result in a transient increase in blood CR levels and could potentially lead to the development of acute uric acid nephropathy. When a clinical laboratory encounters test results inconsistent with the clinical manifestations, it is essential to not only address any potential detection issues but also proactively investigate the underlying reasons for abnormal test results through comprehensive literature reviews and other rigorous methodologies.

Background: An important aspect of the shift towards dried blood spots (DBS) as a sample matrix for laboratory measurements, is the availability of robust liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods that can reliably quantify analyte concentrations in DBS. The development and validation of these LC-MS/MS methods, however, concerns an extensive process, for which large amounts of DBS samples are required. DBS are usually obtained from capillary blood samples, but they can also be prepared from venous (residual) blood samples, which are widely available in clinical laboratories. Therefore, we aimed to determine whether DBS prepared from (residual) venous blood samples, collected in EDTA blood tubes, can be used for future development and validation of LC-MS/MS methods to quantify steroid hormones in DBS.

Methods: Capillary DBS and venous blood samples (EDTA tube and tube without additives) were collected from twenty healthy volunteers (12F/8M). From both venous blood samples, DBS were prepared volumetrically. Samples were analyzed using in-house developed LC-MS/MS methods for testosterone, androstenedione, 17-hydroxyprogesterone (17-OHP), cortisol, cortisone, corticosterone, and for dehydroepiandrosterone sulfate (DHEA-S).

Results: DBS made from venous blood collected in EDTA tubes compared with capillary blood showed a correlation coefficient of ≥ 0.89 for all steroid hormones except corticosterone (0.67). DBS made from venous blood collected in tubes without additives showed a strong correlation with both DBS made from venous blood collected in EDTA tubes (≥0.97 for all steroid hormones) and capillary DBS (>0.90) except corticosterone (0.64).

Conclusion: DBS prepared from (residual) venous blood collected in EDTA blood tubes can be used for future development and validation of LC-MS/MS methods to quantify steroid hormones, except for corticosterone, in capillary DBS.

Early detection and management of cardiovascular diseases (CVDs) are crucial for patient survival and long-term health. CVD biomarkers such as cardiac Troponin-I (cTnI), N-terminal pro-brain natriuretic peptide (NT-proBNP), creatine kinase MB (CK-MB), Galectin-3 (Gal-3), etc are released into the circulation following heart muscle injury, ie, acute myocardial infarction (AMI). Biosensor technology including the use of nanoparticles can be designed to target specific biomarkers associated with CVD, enabling early detection and more rapid intervention to decrease morbidity and mortality. To date, with the combination of developed nanoparticles, several optical and electrochemical-based biosensors have successfully been used detection of CVD biomarkers. Nanomaterials, when introduced as the modifiers of sensor surfaces like electrodes and gold chips, can result in the more comprehensive and more effective immobilization of capture molecules, ie, antibodies, aptamers and other ligands, due to their large surface area. In recent years, inorganic nanoparticles have regularly been used in the production of biosensors mostly due to their excellent response intensification, adaptable functionalization chemistry, shape control, good biocompatibility, and great stability. In this review, we discuss the application of different kinds of nanoparticles for the sensitive and specific detection of CVD biomarkers.

Background: Pyridoxine-dependent epilepsy (PDE) is a rare inborn error of lysine metabolism. To date, diagnosis of PDE relies on the quantification of α-AminoAdipic SemiAldehyde (α- AASA), Piperideine-6-Carboxylate (P6C) and Pipecolic acid (PA) in urine or plasma from patients with overt symptoms. However, these biomarkers are not specific, and their biochemical analysis is challenged by their instability and technical limitations. We set-up and validated a method for the quantification of two new biomarkers of PDE (2S,6S- and 2S,6R-oxopropylpiperidine-2-carboxylic acid, 2-OPP, and 6-oxopiperidine2-carboxylic acid, 6-oxoPIP) on human urine and plasma by LC-MS/MS, to overcome the diagnostic and technical challenges of old biomarkers.

Methods: We analysed urine and plasma samples by LC-MS/MS, and validated the method in both biological matrices.

Results: We performed the biomarkers extraction from a 10 µL aliquot of urine or plasma in around 15 min using water 100 % for urine, and a solution of water/methanol 50 % for plasma, respectively. The analytical method was validated and gave good linearity (r² > 0.999) in the range 0-15 µmol/L for 2-OPP and 0-25 µmol/L for 6-oxoPIP. In both matrices, the biomarkers were stable at different storage temperatures tested.

Conclusions: We set-up and validated a reliable method and confirmed its clinical applicability on real samples from PDE patients. This method could be used as routine test for the diagnosis and monitoring of PDE.

MicroRNAs (miRNAs), a class of endogenous small RNAs with lengths of approximately 19-24 nucleotides, play important regulatory roles in cells. In recent years, miR-363 has emerged as a prominent member of the miR-92a family, participating in various biological functions, including cellular proliferation, cycle, migration, and apoptosis. In particular, miR-363 plays a critical role in acute kidney injury, renal fibrosis, and diabetic nephropathy and can serve as a biomarker for the diagnosis of renal cell carcinoma. Ongoing research is exploring its potential as a biomarker of other kidney diseases. This review focuses on the role of miR-363 in kidney diseases, elucidating its regulatory mechanisms and exploring its possible value as a biomarker of kidney diseases.

Sjogren's disease (SjD) in children is a rare chronic autoimmune disease not fully recognized due to clinical manifestations different from adults. As such, new objective indicators are needed to supplement existing markers and assist in diagnosis. This review summarizes pathogenesis of SjD in children, current diagnostic criteria and research progress in laboratory diagnosis including serologic testing, saliva and tear analysis, histopathological examination as well as emerging markers of interest.

Celiac disease (CeD) is an autoimmune disorder triggered by sensitivity to gluten, a protein complex found in wheat, barley, and rye. Gliadins, a component of gluten, are proteins that trigger an immune response in individuals with CeD, primarily affecting the small intestine's inner lining. Despite a 1-1.5% prevalence, only 24% of cases are diagnosed due to non-specific symptoms. Screening is advised for high-risk groups, including first-degree relatives and type 1 diabetes patients. The accurate diagnosis of this condition and the assessment of the patient's response to the current treatment - a lifelong gluten-free diet - necessitate using dependable, swift, sensitive, specific, uncomplicated, and affordable analytical methods. Detecting CeD biomarkers in whole blood, serum, or plasma provides a non-invasive approach that serves as an ideal initial diagnostic step. Biosensors offer a novel and alternative way for CeD detection, began emerging in 2007, and hold promise for clinical and point-of-care applications. This review explores the use of biomarker-based diagnostic approaches for CeD, with a focus on biosensors. It delves into the progress of biosensors for CeD diagnosis, identifying trends and challenges in this evolving field. Key biomarkers are highlighted, offering insights into the evolving landscape of biosensors in CeD detection.