Search Results (87)

Hepatitis B virus (HBV) pregenomic RNA (pgRNA), transcribed directly from nuclear covalently closed circular DNA (cccDNA), is an essential component in viral replication. The synthesis and encapsidation of pgRNA depend significantly on the transcriptional activity of cccDNA, making serum pgRNA a recently recognized non-invasive biomarker for evaluating cccDNA activity. However, its clinical application is limited by factors including preanalytical variables, methodological inconsistencies in detection, and a lack of standardization in quantification. This review provides an overview of the biological origins of pgRNA and its critical role in the HBV replication cycle, highlighting the stability challenges encountered during the collection, processing, and storage of plasma/serum samples. Furthermore, it analyzes recent significant advancements in pgRNA detection technologies, encompassing modified reverse transcription quantitative polymerase chain reaction (RT-qPCR), nucleocapsid-captured methodologies, automated testing platforms, multiplex digital PCR, isothermal amplification, and clustered regularly interspaced short palindromic repeats-based assays. A comparison of these technologies revealed that discrepancies in pgRNA quantification arise primarily from variations in sample processing and measurement systems, rather than from inherent biological limitations. Therefore, establishing standardized sample handling procedures, harmonized detection methods, and unified measurement systems is imperative before pgRNA can be reliably applied to monitor treatment, guide cessation decisions, or evaluate cure in chronic hepatitis B. Full article

Background: Accurate microbiological diagnosis of bone and joint infections (BJIs) is frequently hampered by low bacterial load, biofilm formation, and suboptimal tissue processing. This study evaluated the diagnostic performance of mechanical bead-milling using the Ultra-Turrax^® Tube Drive system compared with standard vortex homogenization. Methods: In a prospective cohort of 116 patients undergoing surgery for suspected BJIs, 540 intraoperative samples were processed using both methods. Culture and 16S rRNA PCR results were analyzed using classical and Bayesian statistical approaches. Diagnostic performance was assessed globally and across specimen types and anatomical sites. Results: Ultra-Turrax^® significantly improved sensitivity across all sample types (87.1% vs. 75.2%, p < 0.0001), while maintaining comparable specificity (>99%). Culture positivity increased by 17%, with the greatest gains observed in bone samples and hip prosthesis infections. Quantitative cultures demonstrated a 1.5–2 log₁₀ CFU/mL increase in bacterial yield. In culture-negative specimens, 16S rRNA PCR detection doubled with Ultra-Turrax^® processing (26% vs. 13%, p = 0.04). No increase in contamination was observed. Time to positivity was similar between methods, although Ultra-Turrax^® provided earlier results in 17% of cases. Bayesian modeling confirmed superior sensitivity (posterior probability > 0.995). Conclusions: Ultra-Turrax^® bead-milling markedly enhances microbiological detection in BJIs, particularly in low-biomass and bone-derived specimens. Its simplicity, reproducibility, and compatibility with routine workflows support its integration into diagnostic pathways. This pre-analytical optimization may improve etiological identification and guide more targeted antimicrobial therapy. Full article

Vaginal microbiome composition has been linked to risk of preterm birth (PTB), a persistent global health challenge. 16S rRNA microbial profiling has identified specific vaginal community state types (CSTs) that have been associated with PTB risk. Diagnostic profiling requires standardised pre-analytical protocols. We evaluated two storage methods and validated a curated, vagina-specific 16S rRNA gene database (VagDB) to enhance annotation. Paired Copan FLOQ swabs from 22 women at high PTB risk were processed for either (a) dry/immediate freezing or (b) Amies-stabilisation/refrigeration. Amplicon sequence variants were generated via 16S rRNA gene (V4) PCR and Illumina sequencing. We assessed diversity, composition, and community state type (CST) allocation. Amies-stabilised samples yielded significantly higher DNA (p = 0.003), but this did not alter species richness, evenness, or community structure. VagDB enhanced species-level resolution. PCoA showed robust clustering by participant and CST (p < 0.001), irrespective of storage; CST concordance exceeded 90%. Routinely collected vaginal swabs in stabilisation medium with an 8–72 h refrigeration window yield reliable data, supporting the integration of vaginal microbiome profiling into clinical PTB risk assessment. Full article

Background/Objectives: Combining Whole Slide Imaging (WSI) and Artificial Intelligence (AI) in digital pathology (DP) is accelerating the field of diagnostic pathology by improving analysis metrics accuracy, reproducibility, and speed. AI applications in pathology include automated image capture, assessment and analysis, risk stratification, and prognostic prediction. This integration introduces significant challenges, including data quality, high computational demands, the ability to generalize across different settings, and a range of ethical considerations. This review provides an end-to-end roadmap covering WSI acquisition, preprocessing, and deep learning (DL) channels through tumor recognition, biomarker prediction, and evolving computational methods such as original models and combined learning, highlighting the specific challenges and opportunities of WSI-attached AI in pathology. Methods: This review provides a WSI-centric analysis that examines AI and DL applications specifically as they overlap with the acquisition, processing, and computational analysis of WSI. Therefore, this review aims to comprehensively examine the challenges and pitfalls associated with the use of WSI in AI-Based Digital Pathology. Results: Pre-analytical factors like how the tissue is prepared, staining, and scanning artifacts affect AI and contain possible post-analytical barriers such as the range of colors used, color standardization, and algorithm transparency. Furthermore, there may be bias found in the training datasets that can blur the ethical and legal boundaries alongside regulatory uncertainty. Conclusions: Even though there is an array of challenges, AI applied in DP can enhance the accuracy of medical diagnosis, encourage workflow efficiency, facilitate cross-collaboration for pediatric research, and enable research into rare diseases. Further development on the topic needs to focus on defining standard operating procedures and guidelines alongside dependable datasets through teamwork from various scientific fields. Full article

Food allergies represent a growing public health concern, requiring analytical methods capable of detecting trace levels of allergenic ingredients in increasingly complex and processed food matrices. In recent years, nucleic acid-based electrochemical sensors have emerged as a powerful alternative to protein-targeting assays, offering improved stability and sequence specificity, as well as compatibility with portable, low-cost sensing platforms. This review provides a comprehensive overview of nucleic acid-based sensing strategies developed for detecting either allergen proteins or nucleic acids related to allergenic species. Particular attention is given to the methodological approaches implemented, which for DNA detection include sandwich-type designs and DNA switches, while for protein detection rely on aptamer-based assays in a labelled or label-free setup. The review also discusses the impact of pre-analytical steps, such as nucleic acid extraction and PCR-based amplification, on assay reproducibility, cost and applicability at the point of need. Although significant improvements in analytical performance have been achieved, challenges remain in terms of simplifying workflows, standardizing methods, validating them on a large scale, and developing continuous monitoring schemes for timely intervention. The review highlights emerging opportunities, including multiplexed detection platforms, robust extraction protocols, and the harmonization of allergen thresholds, which are key to supporting the practical implementation of nucleic acid-based sensors. Full article

Background/Objectives: The limited specificity of prostate-specific antigen (PSA) drives unnecessary biopsies in prostate cancer (PCa). Urinary extracellular vesicles (uEVs) provide a non-invasive reservoir of tumor-derived nucleic acids and proteins. Aptamers selected by SELEX enable highly specific capture, and artificial intelligence (AI) can accelerate their optimization. This systematic review evaluated AI-assisted SELEX for urine-derived and exosome-enriched aptamer panels in PCa detection. Methods: Systematic searches of PubMed, Scopus, and Web of Science (1 January 2010–24 August 2025; no language restrictions) followed PRISMA 2020 and PRISMA-S. The protocol is registered on OSF (osf.io/b2y7u). After deduplication, 1348 records were screened; 129 studies met the eligibility criteria, including 34 (26.4%) integrating AI within SELEX or downstream refinement. Inclusion required at least one quantitative metric (dissociation constant K_d, SELEX cycles, limit of detection [LoD], sensitivity, specificity, or AUC). Risk of bias was appraised with QUADAS-2 (diagnostic accuracy studies) and PROBAST (prediction/machine learning models). Results: AI-assisted SELEX workflows reduced laboratory enrichment cycles from conventional 12–15 to 5–7 (≈40–55% relative reduction) and reported K_d values spanning low picomolar to upper nanomolar ranges; heterogeneity and inconsistent comparators precluded pooled estimates. Multiplex urinary panels (e.g., PCA3, TMPRSS2:ERG, miR-21, miR-375, EN2) yielded single-study AUCs between 0.70 and 0.92 with sensitivities up to 95% and specificities up to 88%; incomplete 2 × 2 contingency reporting prevented bivariate meta-analysis. LoD reporting was sparse and non-standardized despite several ultralow claims (attomolar to low femtomolar) on nanomaterial-enhanced platforms. Pre-analytical variability and absent threshold prespecification contributed to high or unclear risk (QUADAS-2). PROBAST frequently indicated high risk in participants and analysis domains. Across the included studies, lower K_d and reduced LoD improved analytical detectability; however, clinical specificity and AUC were predominantly shaped by pre-analytical control (matrix; post-DRE vs. spontaneous urine) and prespecified thresholds, so engineering gains did not consistently translate into higher diagnostic accuracy. Conclusions: AI-assisted SELEX is a promising strategy for accelerating high-affinity aptamer discovery and assembling multiplex urinary panels for PCa, but current evidence is early phase, heterogeneous, and largely single-center. Priorities include standardized uEV processing, complete 2 × 2 diagnostic reporting, multicenter external validation, calibration and decision impact analyses, and harmonized LoD and K_d reporting frameworks. Full article

Background: Quantitative urine culture (CFU/mL) remains the reference standard for diagnosing urinary tract infections (UTIs) but is limited by delayed turnaround times and sensitivity to pre-analytic factors. Multiplex PCR panels offer rapid detection; however, standardized mappings between molecular signals and viable bacterial burdens are insufficiently defined. We used the multicenter NCT06996301 paired dataset to evaluate the analytical validity (AV), clinical validity (CV), and pre-analytic robustness of ΔCt (Ct_target − IC_Ct) as a semi-quantitative indicator of bacterial load. Methods: We analyzed 1027 paired PCR and quantitative urine culture specimens from six sites. The primary molecular predictor was ΔCt (Ct_target − IC_Ct). Species-level Spearman and Pearson correlations, species-specific linear mixed-effects calibration models (log₁₀CFU ~ ΔCt + (1|site)), and ROC analyses were performed for the taxa meeting pre-specified sample thresholds. A pooled multilevel model assessed the collection method and time-to-processing (hours) effects (log₁₀CFU ~ ΔCt × collection_method + ΔCt × time_to_processing_h + (1|site) + (1|run)). AV was assessed via reproducibility, internal control normalization, and site run variance. CV was assessed by ΔCt calibration and discrimination. Clinical utility (CU) was contextualized using outcomes from the parent randomized trial. Results: PCR positivity exceeded culture positivity across all sites (PCR ~82–88% vs. culture ~66–70%); this excess likely reflects a combination of molecular detection of non-viable DNA, detection of fastidious taxa less readily recovered by culture, and pre-analytic effects. For six common uropathogens (n = 90 pairs/species), ΔCt correlated strongly with log₁₀CFU (Spearman ρ = −0.64 to −0.75; Pearson r = −0.75 to −0.83). Species-specific mixed models yielded slopes of −0.746 to −0.922 log₁₀CFU per ΔCt unit (all p < 0.001), indicating that each 1 unit ΔCt change corresponds to a ~5.6–8.4-fold CFU difference. ROC AUCs for ΔCt discrimination were 0.78–0.84 (interpreted as good discrimination, i.e., ΔCt meaningfully improves the clinician’s probability estimate of a high CFU but does not perfectly classify every specimen). The collection method (catheter vs. clean-catch) did not materially modify the ΔCt→CFU relationship, whereas the processing delay was associated with reduced recovered CFU (~0.048 log₁₀CFU lost per hour) and a significant ΔCt × time interaction, consistent with time-dependent viability loss driving the PCR⁺/culture⁻ discordance. Conclusions: ΔCt from the DOC Lab UTM 2.0 panel shows a reproducible, analytically valid semi-quantitative measure of urinary bacterial load. Laboratories can derive assay- and workflow-specific ΔCt cut points for semi-quantitative reporting, but thresholds must be validated prospectively and paired with operational controls for specimen handling. Full article

Proteins are essential biological macromolecules that play key regulatory roles in all biological processes. Abnormalities in these processes are often reflected in proteins, manifesting as changes in their structure, sequence, folding state, stoichiometry, or spatial and temporal distribution. Proteins serve as biological targets for drugs and other therapeutics and can also function as therapeutic agents to restore normal biological functions by treating diseases. Hence, it is essential to study native protein species, their modifications, higher-order structures, and complexes, which can be extremely difficult due to the challenges in preserving their native conditions and the instrumental capability required for such analysis. High-resolution mass spectrometry (HRMS) instruments provide advanced technical capabilities to study intact protein species from their gas phase ions after the protein solution is sprayed into the mass spectrometers. However, there are debates about the gas-phase protein structures obtained through mass spectrometry and the resemblance to their biological native state. This review discusses various techniques for isolating, separating, and enriching intact protein species for their native mass spectrometry (nMS) analysis. Emerging technologies, such as automated sample preparation, ion mobility spectrometry, and ambient surface mass spectrometry, are briefly discussed. This review aims to serve as a general guideline for beginners, primarily focusing on the preanalytical strategies and critical instrument parameters for nMS analysis of intact proteins, proteoforms, protein complexes, and higher-order structures. Full article

Background/Objectives: Pre-analytical variation is a major challenge in metabolomics, yet most stability studies have focused on healthy volunteers and have overlooked the impact of disease and medication. To address this gap, we conducted a pilot study in systemic lupus erythematosus (SLE) to assess serum metabolite stability under delayed centrifugation. Methods: Peripheral blood from 10 SLE patients and 5 healthy controls (HC) was stored at room temperature for 1–24 h before processing and analyzed by untargeted LC-MS-based metabolomics. This design enabled direct evaluation of the effect of pre-analytical delay within the context of clinical heterogeneity. Results: Principal component trajectories showed reproducible temporal shifts in HC but dispersed patterns in SLE, indicating disease- and treatment-related influences. Linear mixed-effects models identified metabolites with condition-specific kinetics, including glucose, choline, glycerophosphocholine, and pyroglutamic acid. Mycophenolate intake was further associated with distinct AMP dynamics. Conclusions: These findings demonstrate that both disease state and medication reshape apparent metabolite stability, highlighting the need for strictly controlled sample handling and well-characterized clinical cohorts in metabolomics studies. Full article

Exosomes, which are extracellular vesicles measuring 30–150 nm, are becoming a promising new target from cellular debris classification to a recognized biomarker with the potential to transform diagnostics. They have a fundamental role in intercellular communication, with selective molecular cargo that can reflect the pathophysiological state of parent cells. Exosomes are particularly advantageous for non-invasive liquid biopsies, as they provide continuous monitoring of disease progression or response to treatment. We detail the most recent diagnostic proteins, nucleic acids, and lipids in the context of different diseases. Here, we show the potential of exosomes as non-invasive biomarkers across diverse diseases, which may transcend the sensitivity of conventional biomarkers. The potential of exosome-based liquid biopsies to transform clinical laboratory practice will be determined by their ability to overcome challenges. Limitations comprise preanalytical variability, absence of standardized protocols, and heterogeneity in exosome isolation, which limit their diagnostic potential. The implementation is limited by isolation and analytical processes; however, many advanced platforms may offer multiplexed detection, which is accelerating their implementation process in clinical laboratories. Finally, we provide an overview of the clinical applications and preclinical advancements of exosomes to provide a perspective on the significance of exosomes for their use in biomarker study, as well as therapeutic monitoring in different diseases. Future initiatives must emphasize coordinated validation, economical scalability, and incorporation into clinical workflows to fulfill the potential of exosomes as advanced diagnostics. Full article

Background/Objectives: Urinary angiotensin-converting enzyme (uACE) activity has long been regarded as a promising biomarker for kidney and cardiovascular diseases; however, its clinical applicability has been limited by the presence of endogenous urinary inhibitors and technically demanding assay protocols. We aimed to establish a fast and reproducible method for measuring uACE activity to identify the inhibitory compounds responsible for previous assay failures and to define practical preanalytical conditions suitable for routine laboratory implementation. Methods: A fluorescence-based kinetic assay was optimized for urine samples. Endogenous inhibitors were isolated by membrane filtration and chemically characterized, while the effect of sample dilution was evaluated as a simplified alternative for eliminating inhibitory interference. We assessed the stability of ACE activity under various storage conditions to support reliable measurement. Results: Urea (IC₅₀ = 1.18 M), uric acid (IC₅₀ = 3.61 × 10⁻³ M), and urobilinogen (IC₅₀ = 2.98 × 10⁻⁴ M) were identified as the principal reversible inhibitors, jointly accounting for up to 90% suppression of uACE activity. Their inhibitory effect was effectively eliminated by a 128-fold dilution. ACE activity remained stable for 24 h at 25 °C but was completely lost after freezing. A strong positive correlation between uACE activity and creatinine concentration (r = 0.76, p < 0.0001) justified normalization. ACE activity-to-creatinine ratio turned out to be significantly lower in ACE inhibitor-treated patients than in untreated controls (6.49 vs. 36.69 U/mol, p < 0.0001). Conclusions: Our findings demonstrate that accurate measurement of uACE activity is feasible using a rapid dilution-based protocol. The normalized ACE activity can serve as a practical biomarker for detecting pharmacological ACE inhibition and monitoring therapy adherence in cardiovascular care and may also provide insight into renal pathophysiology such as tubular injury or local RAAS-related processes. Full article

Quality assurance in a clinical laboratory is essential to ensure reliable, accurate and precise laboratory test results all the time. A hemostasis laboratory is an important part of a clinical laboratory setting in a hospital or a healthcare center, and clinical laboratory tests play a crucial role in diagnosis and management of conditions related to bleeding or clotting of diseased individuals. This review discusses all aspects of coagulation laboratory testing from pre-analytical, analytical, and post-analytical variables as part of daily quality assurance processes undertaken as well as the quality management process of assay validation and implementation in a laboratory prior to patient testing. The internal and external quality processes that drive a hemostasis laboratory will be discussed that shows a rigorous process in assurance of testing that is reliable and accurate every time, at all times. Full article

Background: Bradykinin (BK) is an inflammatory mediator. The degradation of labeled synthetic BK in biofluids can be used to report on the activity of angiotensin-converting enzyme (ACE) and basic carboxypeptidases N and CBP2, for which the neuropeptide is a substrate. Clinical studies have shown significant changes in the serum activity of these enzymes in patients with inflammatory diseases. Methods: Here, we investigated variation in the cleavage of dabsylated synthetic BK (DBK) in serum and the formation of the major enzymatic fragments using a thin-layer chromatography-based neuropeptide reporter assay (NRA) in a large cohort of healthy volunteers from the international human Personal Omics Profiling consortium based at Stanford University. Results: Four major outcomes were reported. First, a set of NRA reference data for the healthy population was delivered, which is important for future investigations of patient sera. Second, it was shown that the measured serum degradation capacity for DBK was significantly higher in males than in females. There was no significant correlation of the NRA results with ethnicity, body mass index or overnight fasting. Third, a batch effect was noted among sampling sites (HUPO conferences). Thus, we used subcohorts rather than the entire collection for data mining. Fourth, as the low-cost and robust NRA is sensitive to enzyme activity, it provides such a necessary quick test to eliminate degraded and/or otherwise questionable samples. Conclusions: The results reiterate the critical importance of a high level of standardization in pre-analytical sample collection and processing—most notably, sample quality should be evaluated before conducting any large and expensive omics analyses. Full article

Background: Cell-free DNA (cfDNA) has become a cornerstone of liquid biopsy applications, offering promise for early disease detection and monitoring. However, its widespread clinical adoption is limited by variability in pre-analytical processing, especially during isolation. Current extraction methods face challenges in yield, purity, and reproducibility. Methods: We developed and optimized SafeCAP 2.0, a novel magnetic bead-based cfDNA extraction kit, focusing on efficient recovery, minimal genomic DNA contamination, and PCR compatibility. Optimization involved systematic evaluation of magnetic bead chemistry, buffer composition, and reagent volumes. Performance was benchmarked against a commercial reference kit (Apostle MiniMax) using spiked oligonucleotides and plasma from patients with stage IV NSCLC. Results: The optimized protocol demonstrated superior recovery with a limit of detection (LoD) as low as 0.3 pg/µL and a limit of quantification (LoQ) of 1 pg/μL with no detectable PCR inhibition. In comparative studies, SafeCAP 2.0 showed equivalent or improved performance over the commercial kit. Clinical validation using 47 patient plasma samples confirmed robust cfDNA recovery and fragment integrity. Conclusions: SafeCAP 2.0 offers a cost-effective, high-performance solution for cfDNA extraction in both research and clinical workflows. Its design and validation address key pre-analytical barriers, supporting integration into routine diagnostics and precision medicine platforms. Full article

Circulating cell-free DNA (cfDNA) is an important biomarker for various cancer types, enabling a non-invasive testing approach. However, pre-analytical variables, including sample collection, tube type, processing conditions, and extraction methods, can significantly impact the yield, integrity, and overall quality of cfDNA. This study presents a comprehensive analytical validation of a magnetic bead-based, high-throughput cfDNA extraction system, with a focus on assessing its efficiency, reproducibility, and compatibility with downstream molecular applications. The validation was performed using a range of sample types: synthetic cfDNA spiked into DNA-free plasma, multi-analyte ctDNA plasma controls, Seraseq ctDNA reference material in a plasma-like matrix, extraction specificity controls, residual clinical specimen from patients, and samples from healthy individuals stored at room temperature or 4 °C for up to 48 h to assess stability. Extracted cfDNA was analyzed for concentration, percentage, and fragment size, using the Agilent TapeStation. Variant detection was evaluated using a next-generation sequencing (NGS) assay on the Seraseq ctDNA reference material. The results demonstrated high cfDNA recovery rates, consistent fragment size distribution (predominantly mononucleosomal and dinucleosomal), minimal genomic DNA (gDNA) contamination, and strong concordance between detected and expected variants in reference materials. The workflow also showed robust performance under different study parameters, variable sample conditions, including sample stability and integrity. Together, these findings confirm the efficiency and reliability of the evaluated cfDNA extraction system and underscore the importance of standardized pre-analytical workflows for the successful implementation of liquid biopsy for early cancer detection, therapeutic monitoring, and improved patient outcomes. Full article