Search Results (68)

Background/Objectives: The increasing volume of laboratory testing and the tightening of quality standards have rendered automation tasks in medical laboratories highly relevant. Conventional total laboratory automation (TLA) systems demonstrate high throughput; however, their economic and organizational efficiency is often constrained by their complex integration and substantial implementation costs. In this context, collaborative robots (cobots) are attracting increasing attention due to their ability to perform pre-analytical and logistical tasks in close association with laboratory personnel. The objective of the present study was the systematic integration of commercially available cobots into the pre-analytical workflow of a large centralized laboratory. Methods: The implemented system incorporated a set of specialized modules, including decapping, barcode orientation and verification, analyzer loading, aliquoting, and specimen sorting, with bidirectional integration into the Laboratory Information System (LIS). The architectural design, control algorithms, and primary effects on labor input and operational turnaround time were evaluated. Results: The results demonstrated that the implementation of cobots into laboratory processes led to an 87% reduction in labor input, a 3.4% improvement in liquid aliquoting accuracy, and an overall improvement in nominal throughput, while requiring minimal personnel training. However, human operators performed the aliquoting procedure significantly faster than cobots, with an average speed advantage of 42.5%. Conclusions: The use of collaborative robotic systems in centralized medical laboratories appears promising due to their operational efficiency and flexibility compared to conventional automation platforms and manual workflows. The effect of the use of cobots on the quality/accuracy of the tests needs to be evaluated, and perhaps a larger study of multiple laboratories needs to be conducted to confirm the results are generalizable. Full article

Circulating tumour DNA (ctDNA) assays are increasingly applied in haematological malignancies for non-invasive genotyping, quantitative response assessment, measurable residual disease (MRD) detection, and relapse surveillance, often complementing bone marrow-based testing and, in selected scenarios, potentially reducing its frequency. Yet, translating ctDNA results into comparable clinical decisions across laboratories, platforms, and time remains challenging because ctDNA measurements are influenced by the definition of the measurand (for example, variant allele fraction versus mutant molecules per mL), pre-analytical variables, end-to-end workflow losses, and lineage-specific confounders such as clonal haematopoiesis of indeterminate potential (CHIP), therapy-related clonal haematopoiesis, and compartmental disease (marrow, plasma, cerebrospinal fluid, extramedullary sites). This review proposes a harmonisation framework for haematological ctDNA based on three linked concepts—metrological traceability, which connects reported values to reference systems with stated uncertainty, commutability, which ensures that reference materials behave like patient specimens across diverse workflows and fit-for-purpose reference materials that support calibration, and quality control, external quality assessment, and cut-off setting for intended uses such as early molecular response in large B-cell lymphoma, molecular MRD in acute myeloid leukaemia, and deep response monitoring in multiple myeloma. This framework is accompanied by harmonised CHIP-aware reporting rules for settings without matched cellular DNA and practical change-control/bridging strategies to preserve clinical decision thresholds when platforms or bioinformatic pipelines evolve. Full article

The human microbiome is increasingly recognized as a key determinant of health and disease, yet methodological variability continues to limit reproducibility and clinical translation of findings. This review synthesizes current approaches in microbiome research, critically evaluating each step from sampling to sequencing and downstream bioinformatics. Pre-analytical factors such as sample type, collection method, preservation, and storage conditions profoundly affect microbial community profiles and remain a major source of bias. Nucleic acid extraction protocols and quality assessment strategies are discussed with emphasis on optimized lysis techniques, contamination controls, and DNA yield evaluation. Advances in sequencing technologies are highlighted, including 16S rRNA amplicon sequencing, shotgun metagenomics, third-generation long-read platforms, and emerging single-cell and minimal-input methods, each with specific advantages and limitations in taxonomic and functional resolution. Bioinformatics pipelines for taxonomic profiling, variant detection, phylogenetic inference, and functional annotation are compared, with attention to widely used reference databases such as RefSeq, GTDB, and SILVA. Integrative multi-omics approaches, including metatranscriptomics, metabolomics, and genome-scale metabolic modeling, are presented as powerful tools for linking microbial community structure to host physiology and disease mechanisms. Despite these advances, the lack of standardized workflows across pre-analytical, sequencing, and computational steps continues to hinder inter-study comparability and biomarker validation. This review aims to provide a methodological framework that highlights both strengths and limitations of current technologies while underlining the need for harmonized protocols to ensure reproducibility and accelerate the translation of microbiome research into clinical practice. Full article

Metabolic profiling enables comprehensive characterisation of the small molecules that are part of the biochemical composition of biological fluids. The most widely profiled biofluids include serum and plasma. Additionally synovial fluid provides a direct reflection of the metabolomic environment of joints and holds promise for biomarker discovery in arthropathies. However, the reproducibility of metabolomics data is highly sensitive to pre-analytical variation, and at the present time, standardised protocols for synovial fluid remain underdeveloped. This review aims to identify and evaluate the existing literature on effects of biofluid pre-analytical handling treatments on metabolic profiles. This review was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. A search was carried out to identify studies employing LC-MS, GC-MS, and NMR spectroscopy for the investigation of factors including sample collection variables, pre-centrifugation conditions, centrifugation parameters, post-centrifugations conditions, sample storage conditions, and freeze/thaw cycling. Best practice recommendations emerging from this review include the use of additive free serum and heparin plasma tubes, the centrifugation of samples within two hours of collection, immediate storage of samples at −80 °C, and avoidance of repeated freeze/thaw cycling. However, while pre-analytical influences have been extensively characterised for plasma and serum, evidence for synovial fluid remains limited. Overall, the findings highlight the existing recommendations for plasma and serum and demonstrate the need for standardised pre-analytical protocols and validation of quality control markers to advance synovial fluid metabolomics. Full article

Background: Whole-slide imaging and algorithmic advances have moved computational pathology from research to routine consideration. Despite notable successes, real-world deployment remains limited by generalization, validation gaps, and human-factor risks, which can be amplified in resource-constrained settings. Content/Scope: This narrative review and implementation perspective summarizes clinically proximate AI capabilities in cancer pathology, including lesion detection, metastasis triage, mitosis counting, immunomarker quantification, and prediction of selected molecular alterations from routine histology. We also summarize recurring failure modes, dataset leakage, stain/batch/site shifts, misleading explanation overlays, calibration errors, and automation bias, and distinguish applications supported by external retrospective validation, prospective reader-assistance or real-world studies, and regulatory-cleared use. We translate these evidence patterns into a practical checklist covering dataset design, external and temporal validation, robustness testing, calibration and uncertainty handling, explainability sanity checks, and workflow-safety design. Equity Focus: We propose a stepwise adoption pathway for low- and middle-income countries: prioritize narrow, high-impact use cases; match compute and storage requirements to local infrastructure; standardize pre-analytics; pool validation cohorts; and embed quality management, privacy protections, and audit trails. Conclusions: AI can already serve as a reliable second reader for selected tasks, reducing variance and freeing expert time. Safe, equitable deployment requires disciplined validation, calibrated uncertainty, and guardrails against human-factor failure. With pragmatic scoping and shared infrastructure, pathology programs can realize benefits while preserving trust and accountability. Full article

Controlling pre-analytical conditions for medical biology tests, particularly during transport, is crucial for complying with the ISO 15189 standard and ensuring high-quality medical services. The use of drones, also known as unmanned aerial vehicles, to transport clinical samples is growing in scale, but requires prior validation to verify that there is no negative impact on the test results provided to doctors. This study aimed to establish a secure, high-quality solution for transporting biological samples by drone in a coastal region of France. The 80 km routes passed over several densely populated urban areas, with take-off and landing points within hospital grounds. The analytical and clinical impact of this mode of transport was compared according to two protocols: an interventional clinical trial on 30 volunteers compared to the reference transport by car, and an observational study on samples from 126 hospitalized patients compared to no transport. The system enabled samples to be transported without damage by maintaining freezing, refrigerated, and room temperatures throughout the flight, without any significant gain in travel time. Analytical variations were observed for sodium, folate, GGT, and platelet levels, with no clinical impact on the interpretation of the results. There is a risk of time-dependent alterations of blood glucose measurements in heparin tubes, which can be corrected by using fluoride tubes. This demonstrated the feasibility and security of transporting biological samples over long distances in line with the ISO 15189 standard. Controlling transport times remains crucial to assessing the quality of analyses. It is imperative to devise contingency plans for backup solutions to ensure the continuity of transportation in the event of inclement weather. 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

Viral infections in humans and animals are increasing, and retrospective studies using formalin-fixed, paraffin-embedded (FFPE) samples reveal recurring outbreaks over past decades. However, the impact of pre-analytical factors like fixation and autolysis on immunohistochemistry (IHC) remains insufficiently understood. To examine how autolysis, fixation duration (6–72 h) and formalin concentration (2.5–25%) influence histology and IHC of canine distemper virus (CDV, Morbillivirus canis), interferon-β (IFN-β), and selected IFN-stimulated genes (ISGs), the study was conducted using an in vitro model based on persistently CDV-infected and non-infected DH82 cells (canine histiocytic sarcoma cell line). Autolysis led to a progressive loss of cell morphology, whereas formalin fixation had minimal impact. CDV nucleoprotein, ISG15, and myxovirus resistance protein (Mx) showed stable immunohistochemical signals across all fixation conditions and remained detectable after prolonged autolysis. CDV infection upregulated ISG15 and Mx. In contrast, IFN-β and phosphorylated protein kinase R (pPKR) exhibited variable staining and did not distinguish infected from non-infected samples. Overall, autolysis had a stronger negative impact on IHC signal quality than fixation parameters. Despite the limitations of the in vitro model, the robustness of CDV, ISG15, and Mx under suboptimal conditions highlights their potential utility as virus-sensing markers in FFPE material. Full article

Biobanks are essential for precision oncology, providing high-quality materials for biomedical research. Liquid biopsy has become a key tool for non-invasive detection of tumor-derived biomarkers, including circulating tumor DNA, proteins, and extracellular vesicles. However, the reliability of these assays critically depends on standardized preanalytical procedures. In this study, we evaluated the impact of two plasma isolation methods—direct centrifugation (DC) and density gradient centrifugation (DGC)—on the overall quality of breast cancer samples collected at the Bruno Boerci Biobank (Maugeri, Italy). Plasma obtained with the two methods was analyzed by spectrometry for hemolysis and lipemia, biochemical analysis for protein and lipoprotein composition, flow cytometry for cellular debris and platelet contamination. Preanalytical nonconformities due to hemolysis, icterus, and lipemia were comparable between methods. However, DGC was associated with a higher platelet contamination and reduced albumin and cholesterol levels. Inter-individual variability was preserved, supporting the robustness of patient-specific molecular signatures, despite absolute discrepancies. This study highlights the pivotal role of the isolation techniques in shaping the quality and overall composition of plasma samples. Harmonized, “fit-for-purpose” biobanking protocols are required to ensure reproducibility of downstream analyses, support biomarker discovery, and ultimately advance the identification of novel therapeutic targets in cancer. Full article

Background: Venous blood collection in pediatric patients is a critical procedure for diagnostic and monitoring purposes, yet it remains considerably more challenging than in adults. Factors such as small vein size, limited cooperation, and heightened sensitivity to pain contribute to technical difficulties and increased error rates. Objectives: This mini-review aims to provide a concise synthesis of current clinical practices and emerging technologies that support safer, more efficient venipuncture in children. Results: Key findings include the anatomical and procedural considerations relevant to pediatric venipuncture, age-specific recommendations for technique and positioning, as well as evidence-based strategies to reduce pain and anxiety. Common preanalytical errors, particularly hemolysis and insufficient sample volumes, are also addressed, along with their implications for clinical outcomes. Recent advances in medical digitalization, including the use of venous ultrasound, near-infrared projection, and transillumination, offer valuable support in overcoming procedural challenges. These technologies are not meant to replace human expertise but to complement it, improving vein visualization and increasing first-attempt success rates when integrated into a child-centered approach. Conclusions: Venous blood collection in pediatric patients requires a delicate balance between technical proficiency and human-centered care. Emphasis is placed on the importance of a child-centered approach, combining technical skill with empathy and clear communication. Enhancing the quality and safety of venous sampling in children requires not only training and standardization, but also a deeper understanding of the psychological dimensions involved in pediatric care. 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

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

Background/Objectives: Coeliac disease is an immune-mediated disorder of the gastrointestinal tract that may result in significant nutritional deficiencies. Effective management requires strict, lifelong adherence to a gluten-free diet. Both underdiagnosis and unnecessary dietary restrictions can adversely affect patients’ health and quality of life. To assess adherence to the current recommendations for the laboratory diagnosis of coeliac disease and promote evidence-based practices while reducing inter-laboratory variability, the Spanish Group on Autoimmunity of the Spanish Society of Immunology conducted a nationwide survey. Methods: A thirty-item survey was distributed to fifty autoimmune laboratories across Spain. Data were collected through a structured Excel-based questionnaire comprising multiple-choice items, which was distributed via email to the participating laboratories. It explored practices related to the diagnosis of coeliac disease in the general population and among at-risk groups as well as approaches to patient follow-up and demand management. Results: Thirty-five laboratories completed the electronic questionnaire. For the serological screening of coeliac disease, all the respondents reported using IgA anti-tissue transglutaminase (tTG-IgA) antibody testing together with total IgA measurement to assess IgA competence. However, consistent use of anti-endomysial antibody testing and HLA genotyping and adherence to pre-analytical recommendations for accurate interpretation of results were not uniform across centres. Conclusions: At the time these data were collected (the third trimester of 2021), the 2020 ESPGHAN guidelines for the diagnosis of coeliac disease in the paediatric population had not yet been fully implemented in most of the laboratories surveyed. For diagnosing adults, most laboratories adhered to local and European guidelines. Full article

The upcoming wave of personalized medicine, driven by genomic diagnostics and artificial intelligence, demands clearly defined pre-laboratory and laboratory procedures to ensure the acquisition of DNA and RNA of sufficient quantity and quality. In prostate cancer oncogenetics, diagnostic and prognostic assessments increasingly rely on personalized approaches, including Comprehensive Genomic Profiling (CGP). In this pilot study, we aimed to establish optimal pre-analytical and analytical conditions for selected genetic diagnostic methods using tissue samples acquired through multiparametric MRI-guided biopsy. Tissue specimens from thirteen patients were processed for DNA isolation, fluorescence in situ hybridization (FISH), and next-generation sequencing (NGS). Comparative analyses were performed on DNA derived from both fresh and formalin-fixed, paraffin-embedded (FFPE) samples. Sequencing quality metrics demonstrated markedly superior performance in fresh tissue compared to FFPE. These results highlight the importance of standardized tissue collection and processing protocols to enable reliable molecular diagnostics in prostate cancer. Our findings support the feasibility of integrating high-quality genomic testing into routine biopsy workflows and emphasize the need for further large-scale validation. Full article