Analytical Issues Research Articles

2D geochemical imaging of biogenic marine carbonates using LA-TOF-ICP-MS at 1 and 2 μm pixel resolution

Many applications at the forefront of the study of the chemical composition of marine carbonates require in-situ micro-scale geochemical imaging. Such analyses are, however, challenging, requiring analytical techniques that are either expensive with limited accessibility (e.g. synchrotron X-Ray spectroscopy and secondary ion mass spectrometry), or time-consuming and able to only analyse a limited range of elements (e.g. electron microprobe). Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) as a tool for generating 2D images has grown in popularity, yet many analytical issues remain when generating high-spatial resolution geochemical images using this approach. Here we employ the imageGEO193 (ESL) fast wash-out laser ablation system coupled to the Nu Instruments Vitesse Time-of-Flight (TOF) ICP mass spectrometer, with its near-full mass spectra capabilities, to generate 2D geochemical images of a range of biogenic carbonates at ≤2 μm pixel resolution (pixel widths of either 1 or 2 μm) and at an unprecedented speed (200 pixels/s). We demonstrate sensitivity of ∼100 cps/μg g−1 at low mass rising to ∼1000 cps/μg g−1 at high mass based on analyses of reference materials JCp-1 (carbonate) and NIST SRM612 (silicate) with 1 μm wide square laser beams, and accuracy of ±7 % for elements present at concentrations >0.5 μg g−1 based on analyses of carbonate reference material JCt-1. By applying our quantitative method to a range of biogenic carbonates (coral skeletons, coralline algae, foraminifera), we demonstrate that considerable but coherent micron-scale compositional variability is the norm for nearly all quantified elements, including: Mg, Sr, Ba and U. This approach therefore has great potential to provide valuable insights into biomineralisation mechanisms and “vital effects”, ultimately facilitating more robust reconstructions of past environments.

B-108 Delta Check Performance Assessment by Using Real-WorldData at the Temple University Health System​

Abstract Background Delta check is a post-analytic tool focusing on pre-analytical, analytical and post-analytical errors. It can be sensitive in detecting isolated errors affecting a single patient, as opposed to moving patient averages, which is another QC tool for detecting errors that affect a cohort/population of patients. As a computer-based system on selected tests, delta checks are to detect excessive changes from prior value in the patient test result and to detect possible specimen errors such as misidentified or compromised samples before results are reported. It may also play a role in detecting examination(analytical) issues and clinically significant results. If delta checks exceed established limits, the result is flagged. There is a common agreement that measurands with low indices of individuality (<0.6) make good candidates for the identification of cases of sample misidentification than higher indices of individuality (>1.4). CLSI EP33 Use of Delta Checks in the Medical Laboratory guidelines recommends that laboratories assess the validity of current delta check parameters by reviewing retrospective data on flagged results to determine if errors are being identified efficiently. At Temple University Health System, delta check limits were established historically by using published data, however, its performance characteristics have not been verified previously. Verification of clinical performance of predefined delta check limits can be performed either through mathematical calculations or via clinical audits. Clinical audits are achieved by documenting the follow-up actions and outcomes of the samples flagged by a delta check rule(s). It has been suggested that this should be performed using a protocolized follow-up procedure to ensure uniformity in the investigation and management. Corey M. et al. shared an excel template, a mathematical model that can be adopted easily by replacing the example data with retrospectively extracted data and modifying the parameters to suit their laboratory’s requirements. Methods We collected up to 30,000 data points for each 12 measurand in the clinical chemistry lab retrospectively. By using the excel template, clinical sensitivity and clinical specificity has been calculated. Furthermore, we created ROC curves and evaluated them using the (YI) Youden Index and AUC (Area Under the Curve). Results In general, YI values were found to be very low, less than 0.6. Highest YI was used to establish new delta check limits for each analyte; only the current creatinine delta check limit was found as effective, and no change required. 11 out of 12 measurand were required a revision of delta check limits and were proposed to replace with lower delta checks. AUC values were found between 0.56-0.794. Na showed the highest AUC, which correlates its low individuality index (0.5) and its effects on effectiveness of the delta check system. Conclusions It is of vital importance to establish a solid follow-up evaluation for delta check alerts and distinguish between integrity issues and clinically significant changes. Conclusively, this endeavor can develop into extensive information for the application, evaluation, and follow-up of delta checks whilst improving diagnostic accuracy and quality assurance.

A-196 Using Aggregated Proficiency Testing Results to Identify Systematic Error

Abstract Background Proficiency testing (PT) should identify systematic errors, which are likely to recur. The Clinical Laboratory Improvement Amendments of 1988 (CLIA) acceptance limits (ALs) include 3SD and concentration limits. We investigated the ability of PT to detect systematic error, especially as affected by the AL type. Methods Ungradable, duplicate, and irregular scores were removed from 2008 to 2018 CLIA laboratory PT results. For analytes that had at least 200 events and at least 200 participating laboratories, we calculated the overall sample miss rate, the unsatisfactory event rate, i.e., less than 80, and event rates for Score 100 to 0. We used paired t-tests and the Wilcoxon Signed-Rank test to compare miss rates and unsatisfactory event rates between short- and long-term participants. We used the binomial distribution to model the expected event scores under the assumption that all errors may be independent (random); see Figure. For each analyte and each of the possible PT scores, we compared observed event scores with their expected values as a ratio. Results 40,596 laboratories produced 15,140,128 event scores for 75 analytes. The distribution of event scores was over-weighted with higher-order event errors (Score 0 - Score 60) compared to the predicted distribution. Miss rates and unsatisfactory rates were significantly higher for short-term laboratories. Plotting the log ratio of observed versus expected rates for event scores showed that the degree of systematic effect increased progressively for each analyte. The magnitude of the effect was less for 3SD ALs. Conclusions In an event, PT errors are often dependent. Concentration and 3SD ALs were similarly sensitive to detect systematic error; both were more sensitive than ALs for qualitative or dilution assays. Expressing systematic error using PT data could help to identify remediable analytical issues.

“Green mathematical approaches in fluorescence spectroscopy for quality control and clinical studies”

In the past decade, significant advancements have been made in mathematical spectral approaches for estimating binary and ternary drug combinations in raw materials and dosage forms. These approaches established on mathematical spectral manipulations of mixture analytes, without the need for separation techniques.The idea of using mathematical spectral approaches in fluorescence spectroscopy was resolving analytical issues and reach to biological concentrations thus, Ratio subtraction (RD) and ratio subtraction coupled with constant multiplication (RS-CM) have been proposed in fluorescence spectroscopy to evaluate the content uniformity of Flunarizine dihydrochloride (FLZ) and Propranolol hydrochloride (PRO) combination in raw materials, tablets, and spiked biological fluids (blood-urine). These approaches have demonstrated the ability to overcome the quantitative analytical challenges posed by the high native fluorescence intensity of the major component (PRO) at λex = 286/λem = 341 nm and the low native fluorescence intensity of the minor component (FLZ) at λex = 254/λem = 311 nm. The linearity range for (PRO) was found to be 25–500 ng/mL, and for (FLZ), it was 50–500 ng/mL. However, the spectrum addition technique was required to estimate (FLZ) in mixtures with concentrations less than 300 ng/mL.The overall validity of the proposed approaches was confirmed through adherence to ICH guidelines, and no statistical variation was observed in comparison to official studies. Additionally, the greenness and whiteness of the proposed approaches were evaluated using the Analytical greenness metric (AGREE), Green Solvents Selecting Tool (GSST), and Red-Green-Blue (RGB) algorithm.

Chromatographic Comparison of Commercially Available Columns for Liquid Chromatography in Polar Pesticide Detection and Quantification Using a Score-Based Methodology.

The detection and quantification of polar pesticides in liquid chromatography coupled with mass spectrometry present significant analytical challenges. This study compares the performance of three LC columns (Hypercarb™, Raptor Polar X™, and Anionic Polar Pesticide™) in separating and quantifying eleven polar pesticides in chicken eggs using a score-based methodology. Analytes include glyphosate, its metabolites, and other high-polarity pesticides like Ethephon, Glufosinate, and Fosetyl aluminum, included in the EU's official control plan. Polar pesticides, characterized by high polarity and hydrophilicity, lead to analytical issues such as poor retention and unconventional peak shapes with traditional reversed-phase methods. Their weak interaction with hydrophobic stationary phases complicates separation, necessitating specific stationary phases to enhance retention and selectivity. This study evaluates these columns' efficacy in complex matrices like chicken eggs and other food samples. Chromatographic separation was performed using a UPLC system coupled with a Q-TOF mass spectrometer; extraction and purification involved freeze-out, centrifugation, and filtration steps. The study highlights the critical role of column selection in achieving accurate and reliable separation and quantification of highly polar analytes in matrices of animal origin, offering in the meantime an easy-to-apply methodology of selection for the right determination of the best chromatographic column for different purposes.

Graph contrastive learning as a versatile foundation for advanced scRNA-seq data analysis.

Single-cell RNA sequencing (scRNA-seq) offers unprecedented insights into transcriptome-wide gene expression at the single-cell level. Cell clustering has been long established in the analysis of scRNA-seq data to identify the groups of cells with similar expression profiles. However, cell clustering is technically challenging, as raw scRNA-seq data have various analytical issues, including high dimensionality and dropout values. Existing research has developed deep learning models, such as graph machine learning models and contrastive learning-based models, for cell clustering using scRNA-seq data and has summarized the unsupervised learning of cell clustering into a human-interpretable format. While advances in cell clustering have been profound, we are no closer to finding a simple yet effective framework for learning high-quality representations necessary for robust clustering. In this study, we propose scSimGCL, a novel framework based on the graph contrastive learning paradigm for self-supervised pretraining of graph neural networks. This framework facilitates the generation of high-quality representations crucial for cell clustering. Our scSimGCL incorporates cell-cell graph structure and contrastive learning to enhance the performance of cell clustering. Extensive experimental results on simulated and real scRNA-seq datasets suggest the superiority of the proposed scSimGCL. Moreover, clustering assignment analysis confirms the general applicability of scSimGCL, including state-of-the-art clustering algorithms. Further, ablation study and hyperparameter analysis suggest the efficacy of our network architecture with the robustness of decisions in the self-supervised learning setting. The proposed scSimGCL can serve as a robust framework for practitioners developing tools for cell clustering. The source code of scSimGCL is publicly available at https://github.com/zhangzh1328/scSimGCL.

Vitamin D assay and supplementation: still debatable issues.

Over the last decades, in addition to the improvement of pathophysiological knowledge regarding the role and mechanisms of action of vitamin D, there hasbeen a progressive advancement in analytical technologies for its measurement, as well as in methodological standardization. A significant number of scientific works, meta-analyses, and guidelines have been published on the importance of vitamin D and the need for supplementation in deficient individuals. However, it appears necessary to clarify the fundamental elements related to the measurement of vitamin D (both at the strictly analytical and post-analytical levels) and the scientific evidence related to the efficacy/safety of supplementation. In particular, there isa need to discuss current recommended levels for deficiency, insufficiency and possible toxicity in the light of evidence from standardization projects. Additionally, given the important interrelations between vitamin D, parathyroid hormone (PTH), and fibroblast growth factor-23 (FGF23), the analytical issues and clinical utility of these biomarkers will be discussed.

PARAFAC under non-negativity constraint is adapted to recover the underlying Beer-Lambert law of the excitation-emission fluorescence matrix measurements acquired from analyte-triggered semiconductor QDs photoluminescence modulation. When and why?

BackgroundAnalyte-triggered semiconductor quantum dots (QDs) modulation in the presence of non-consistently responsive fluorescent species represents a challenging analytical issue in concrete multi-way data handling. QDs with heterogeneous sizes and/or uneven distribution of functional moieties on their surfaces exhibit significant fluctuations in the fluorescent response components, known as chemical rank, across different excitation/emission modes. This phenomenon may lead to a substantial deviation from the proportionality prescribed by Beer-Lambert law. Nonetheless, even in the presence of such deviation, a multi-way model may be successfully selected after determining a proper chemical rank in a QDs system. ResultsWe show that in a valid PARAllel FACtor (PARAFAC) model under properly determined chemical rank, meaningfully resolved pure spectral profiles can be reached for each fluorescent responsive constituent in the original excitation-emission fluorescence matrix (EEFM) measurements. This was thoroughly illustrated by applying PARAFAC trilinear decomposition of a three-way data array of two distinct datasets acquired from semiconductor QDs sensing systems with low-rank trilinear assumption. The first dataset, presented here for the first time, comprises EEFM measurements of the ligand-driven quenching of thiomalic acid (TMA)-capped AgInS2 (AIS) QDs by vomitoxin. The second dataset, employed for illustrative purposes, comprises EEFM measurements of the quenching, via cation bridging, of glutathione (GSH)-capped CdTe QDs by Pb(II). The results of this study enabled the determination of vomitoxin at a ppb level in real samples of fish feeds, showcasing the efficacy of the PARAFAC model in resolving spectral signatures (loadings) and pure concentration profiles (scores). SignificancePARAFAC under a properly examined chemical rank can be easily adapted for retrieval the underlying Beer-Lambert law of the original EEFM measurements with a low-rank trilinear structure through the chemically meaningful information either when (i) no deviation of Beer-Lambert law was observed as deeply discussed in connection with the dataset acquired from vomitoxin-driven molecular sensing through TMA-capped AIS QDs, or when (ii) substantial deviations of the Beer-Lambert law are evident, as discussed in connection with the dataset collected from sensing ionic species through Pb(II) bridging of GSH-capped CdTe QDs.

Resolving unsolved whole-genome sequencing data in paediatric neurological disorders: a cohort study

ObjectiveTo resolve unsolved whole-genome sequencing (WGS) data in individuals with paediatric neurological disorders.DesignA cohort study method using updated bioinformatic tools, new analysis targets, clinical information and literature databases was employed...

Symposium 1: Analyzing Special Needs Support through Networks and Learning Analytics in Primary Education

In this short paper, analytical issues of networked learning are related to special needs support and learning analytics research in primary education. Very brief suggestions for these analytical issues are discussed for the networked learning research field to continue to expand upon. In part, the discussion is intended to form the underpinnings of a work-in-progress research project with cross-disciplinary networked connections across multiple universities. Currently, teachers are faced with an expansion of their professional role that may be too economically demanding, which may result in consequences that is not beneficial for children with special needs. Researchers that aim to study inclusive education face the challenge to represent findings in a way that does not increase workload for teachers in primary education. Any failings in this regard may strengthen the intertwining of educational results and economical interest, which to a large extent could be considered as opposed to networked learning theory, dualistically separated from pedagogical concerns. The inclusive goal of addressing diversity for children with special needs may be promoted by providing an educational setting with networked connections that enhances variation to modes of behavior, by addressing specific and contextual strengths and challenges of students appropriately. With learning analytics, specific and contextual strengths and challenges of students might be easier to highlight with new database schemas, algorithms, and user interfaces to represent networked data. Radical behaviorist methodology may further emphasize specific contextual findings from primary education through strictly defined events of behavior, which may be of interest to the networked learning research community to further expand upon. Thus, this paper proposes suggestions for networked learning research of primary education, with approaches commonly implemented in special education, such as radical behaviorist methodology. The suggestions are based on networked consequences from three social dimensions: political, economic, and technology-developmental. 1 The political dimension is discussed through the notion of inclusive education for children with special needs and its current state, 2 the economic dimension is discussed through the 21st century role expansion of teachers, 3 the technology-developmental dimension is discussed through learning analytic research and its connection to bodily and biological associations. This dimension is especially noteworthy, as learning analytics is currently underutilized in primary education research as opposed to common higher education research.

Neutral Emden–Fowler Differential Equation of Second Order: Oscillation Criteria of Coles Type

In this work, we study the asymptotic and oscillatory behavior of solutions to the second-order general neutral Emden–Fowler differential equation (avηxvz′v)′ + qvFxgv = 0, where v≥v0 and the corresponding function z = x + px∘h. Besides the importance of equations of the neutral type, studying the qualitative behavior of solutions to these equations is rich in analytical points and interesting issues. We begin by finding the monotonic features of positive solutions. The new properties contribute to obtaining new and improved relationships between x and z for use in studying oscillatory behavior. We present new conditions that exclude the existence of positive solutions to the examined equation, and then we establish oscillation criteria through the symmetry property between non-oscillatory solutions. We use the generalized Riccati substitution method, which enables us to apply the results to a larger area than the special cases of the considered equation. The new results essentially improve and extend previous results in the literature. We support this claim by applying the results to an example and comparing them with previous findings. Moreover, the reduction of our results to Euler’s differential equation introduces the well-known sharp oscillation criterion.

The performance of quantitative D-dimer assays in Chinese clinical laboratories by analyzing data from National External quality Assessment Scheme

Background and aimsTo investigate performance of D-dimer assays in China and address analytical quality issues. Materials and methodsD-dimer assays data were collected from China National External Quality Assessment Scheme (China NEQAS) from 2014 to 2022. We analyzed reagents, assay results, reporting unit and cutoffs in 2022 China NEQAS. Interlaboratory coefficient variations (CVs) and influence of modified/unmodified test systems on CVs were investigated over 9 years. ResultsThere were 82 reagent brands in China NEQAS, but 55 reagent instructions did not indicate expression unit (DDU or FEU). Up to 7-fold of the ratio of max-to-min mean results was shown among different assays with same unit on the same sample. A prevalence of FEU (63.4%) over DDU (17.1%) was observed. Although 669 laboratories (37.9%) among 1766 laboratories used reagents without VTE exclusion claim, they also reported cutoffs. The CVs of only two assays were decreasing over years. CVs of modified test systems were higher than those of unmodified systems before improvement. ConclusionsExpression unit should be required to label in package inserts by regulatory authority. Laboratory professionals should follow instructions for use and prefer unmodified test systems for clinical safely application. Harmonization of reporting units through collaborative efforts is the promising step.

Detection of fibrous microplastics and natural microfibers in fish species (Engraulis encrasicolus, Mullus barbatus and Merluccius merluccius) for human consumption from the Tyrrhenian sea

The occurrence of natural/artificial and synthetic microfibers was assessed in three commercial fish species (Engraulis encrasicolus, Mullus barbatus, Merluccius merluccius) from the Tyrrhenian Sea sold for human consumption. The gastrointestinal tracts of n. 150 samples were analyzed, the isolated microfibers were classified applying a morphological approach, based on the analysis of their morphological features, coupled with the identification of the chemical composition of a subsample of microfibers. All the species contained microfibers at levels ranging from 0 to 49 items/individual and the number of ingested microfibers significantly differed between pelagic and demersal fishes. The evaluation of fiber morphologies highlighted that natural/artificial microfibers were the most numerous among the isolated microfibers, while the dominant colors were blue, black, and clear in all the species. Chemical characterization confirmed the morphological identification and indicated cellulose and polyester as the most common polymer types. Considering the analytical issues that may affect the evaluation of microfiber pollution, the results pointed out the importance of an accurate morphological approach that allows the distinction between different fiber types, before the spectroscopic analyses. Moreover, the implementation of fast and accessible methods to identify microfibers in fish species intended for human consumption will be beneficial also to make an adequate risk assessment to consumer health.

Small patients, big challenges: navigating the complex world of pediatric reference intervals

Abstract With about 60%-70% of medical decisions based on laboratory investigations, modern medicine is increasingly more reliant on laboratory medicine. Pediatric healthcare particularly depends on laboratory testing, with reference intervals (RIs) serving as critical tools for accurate result interpretation. However, establishing pediatric RIs poses distinctive challenges due to developmental, growth, nutritional, and disease-related variations across age groups, along with technical, ethical, and logistical challenges. Despite these limitations, there are several ongoing initiatives for developing pediatric RIs globally, underscoring the importance of developing accurate pediatric RIs. This review outlines the particularities of pediatric laboratory medicine and the specific challenges in establishing pediatric RIs, highlighting the recent initiatives in this area. It also addresses biological and analytical variability issues and explores future perspectives aimed at enhancing diagnostic accuracy and elevating patient care standards.

Metrology of Platinum Nanozymes: Mechanistic Insights and Analytical Issues (Adv. Funct. Mater. 24/2024)

Metrology of Platinum Nanozymes: Mechanistic Insights and Analytical Issues (Adv. Funct. Mater. 24/2024)

Free scalar field theory on a Sobolev space over a bounded interval

This paper discusses several functional analytic issues relevant for field theories in the context of the Hamiltonian formulation for a free, massless, scalar field defined on a closed interval of the real line. The fields that we use belong to a Sobolev space with a scalar product. As we show this choice is useful because it leads to an explicit representation of the points in the fibers of the phase space (the cotangent bundle of the configuration space). The dynamical role of the boundary of the spatial manifold where the fields are defined is analyzed.

AUTOMATION IN ANALYTICAL CHEMISTRY: THE ROLE OF AI IN CHROMATOGRAPHY

Artificial Intelligence (AI) has facilitated significant breakthroughs in drug discovery, the design of materials, and organic synthesis. The advancements in the latter group are especially remarkable due to the abilities of the latest computational methods (molecular design algorithms) that enable the exploration of extensive chemical spaces and enhance research in fields such as predicting molecule properties, designing molecules, retrosynthesis, predicting reaction conditions, and predicting reaction outcomes. A literary review was conducted following PRISMA guidelines. This study aimed to review existing data on the application of AI in separation chromatography. The evolution and utilization of AI in the pharmaceutical industry and its future aspects were articulated in this study. The utilization of AI can completely transform the field of chromatography analysis by facilitating expedited, more precise, and more effective data processing. By automating chromatography analysis, AI can enhance efficiency and minimize the potential for human mistakes. This advancement enables scientists to dedicate their efforts towards addressing intricate and demanding analytical issues. With the evolution of technology and the increasing adoption, we can anticipate more progress in chromatography analysis and analytical chemistry.

Laser-induced breakdown spectroscopy analysis of tourmaline: protocols, procedures, and predicaments

Abstract. Laser-induced breakdown spectroscopy (LIBS) is an appropriate choice of analytical tool for analysis of complex minerals because it is rapid, requires little sample preparation, and acquires major and trace element compositional information on all naturally occurring elements at concentrations above their intrinsic levels of detection for the specific analyte material. Tourmaline, a complex borosilicate mineral supergroup, was chosen as a test mineral due to the complexity of its major and minor element composition. Four analytical issues were investigated during project development: (1) the spacing between analytical laser shots to avoid analysis of the recast from previous laser ablations, (2) the efficacy of using a cleaning shot prior to data acquisition, (3) the number of ablations required to collect an average spectrum that is representative of the tourmaline sample, and (4) the effect of spectrometer drift on principal component analysis (PCA) when using the entire LIBS spectra to model the compositional variations within the sample suite. The minimum spacing between locations of analysis was determined to be 800 µm for the analytical conditions used in this study by examining spectra acquired in a 2×2 grid across a quartz–tourmaline boundary. At a spacing of 100 µm, twice the diameter of the laser beam, the intensity of the boron I peaks at 249.68 and 249.77 nm was very low in the first location (quartz) but quite high in the fourth location (quartz) due to deposition of tourmaline-composition recast by laser shots in the second and third locations (both on tourmaline). Increasing the distance between locations to 800 µm ensured that the area analyzed largely avoided the recast layer from previous ablations. Given that the distribution of recast was taken into account, no cleaning shots were collected. PCA score plots calculated using successively larger numbers of spectra from the same sample show that a total of 64 spots, or 16 2×2 grids, are needed to acquire a representative average analysis of tourmaline. Spectrometer drift was recognized in PCA loading plots by a characteristic splitting of element peaks; half the peak indicates positive loading and the other half of the peak indicates negative loading. Drift correction was aligned by placing the Ca II peak at 393.34 nm in the 393.398 bin; this correction eliminated split peaks in loading plots. The resolution of these issues yielded LIBS spectra suitable for multivariate statistical analysis that can be applied to understanding geologic processes. These results contribute to the application of rapid LIBS analysis of complex geomaterials.

Technical Advances in Circulating Cell-Free DNA Detection and Analysis for Personalized Medicine in Patients' Care.

Circulating cell-free DNA (cfDNA) refers to small fragments of DNA molecules released after programmed cell death and necrosis in several body fluids such as blood, saliva, urine, and cerebrospinal fluid. The discovery of cfDNA has revolutionized the field of non-invasive diagnostics in the oncologic field, in prenatal testing, and in organ transplantation. Despite the potential of cfDNA and the solid results published in the recent literature, several challenges remain, represented by a low abundance, a need for highly sensitive assays, and analytical issues. In this review, the main technical advances in cfDNA analysis are presented and discussed, with a comprehensive examination of the current available methodologies applied in each field. Considering the potential advantages of cfDNA, this biomarker is increasing its consensus among clinicians, as it allows us to monitor patients' conditions in an easy and non-invasive way, offering a more personalized care. Nevertheless, cfDNA analysis is still considered a diagnostic marker to be further validated, and very few centers are implementing its analysis in routine diagnostics. As technical improvements are enhancing the performances of cfDNA analysis, its application will transversally improve patients' quality of life.

Retention in care of infants diagnosed with HIV at birth: Beyond the diagnostic strategy.

Birth HIV point-of-care (POC) tests curtail analytical testing issues and expedite diagnosis, potentially allowing for earlier mother-infant pair engagement and improved outcomes. Many children are lost post antiretroviral therapy (ART) initiation within the first 6 months of follow-up. We compared 6-month retention in care, HIV viral load (VL) suppression and mortality among infants diagnosed with HIV at birth, using laboratory-based versus POC HIV PCR testing. From 2018 to 2019, infants exposed to HIV underwent birth HIV PCR POC testing at Kalafong Provincial Tertiary Hospital in Tshwane District. Their outcomes were compared to a historical control born between 2014 and 2016, who exclusively underwent laboratory-based HIV PCR testing. Both groups received comparable HIV care following national guidelines. Fifty-seven infants were studied (POC: 27; Control: 30). The POC turnaround time was significantly shorter (POC: 15.5 h [IQR: 4.3-24.7], Control: 68.3 h [IQR 46.0-93.9]; p = < 0.0001). Both populations had the same elapsed time from HIV diagnosis to ART initiation (median: 13 days, POC: IQR 8-21 days; Control: IQR 9-36 days). Six infants were never initiated (POC: 2 [7%]; Control: 4 [13%]). At 6 months, overall care retention was 72% (41/57), higher among the Control group (Control 23/30, 77%; POC: 18/27, 67%). HIV viral suppression at 6 months was higher among the POC group (POC: 14/18, 78%; Control: 9/19, 47%, p = 0.09). No deaths were reported. Poor care retention at 6 months post ART initiation is concerning. Initial mother-infant visits should be effectively utilised to assess and manage potential risk factors for loss of follow-up. This study highlights the ongoing need to find workable solutions to improve retention in care, thereby ensuring the benefits of expedited HIV diagnosis and ART initiation.