The Analyst

Carbapenemases are major drivers of carbapenem resistance in Gram-negative bacteria and pose a critical threat to last-line antibiotic therapy. Rapid identification of carbapenemase classes is essential for appropriate treatment and epidemiological surveillance; however, current functional methods lack class-level resolution and may yield false-negative results for OXA-48-like enzymes. In this study, we developed and validated an assay based on liquid chromatography-mass spectrometry with trapped ion mobility spectrometry-time-of-flight [LC-MS (timsTOF)] for simultaneous detection and class-level differentiation of five clinically relevant carbapenemases (KPC, NDM, VIM, IMP, and OXA-48-like). The method employs three carbapenem substrates (meropenem, imipenem, and ertapenem). A total of 55 clinical isolates were analyzed using a standardized 2-hour incubation protocol, with a total analysis time of 7 min per sample. Ion mobility enabled unambiguous identification of the OXA-48-specific meropenem-derived {beta}-lactone based on its distinct collisional cross-section (185 [A]{superscript 2} vs. 191 [A]{superscript 2} for intact meropenem), despite identical mass and nearly identical retention time. This marker was detected in all OXA-48-like producers and was absent in all other groups. In contrast, imipenem and ertapenem did not provide comparable discrimination, highlighting the central role of meropenem. Distinct hydrolysis profiles enabled class-level differentiation supported by multivariate analysis. LC-MS (timsTOF) thus enables rapid, sensitive, and specific functional detection of carbapenemases within a single workflow. The ion mobility dimension is critical for accurate identification of OXA-48-like enzymes and supports the potential implementation of this approach in routine clinical microbiology laboratories. ImportanceThis study introduces an ion mobility-enabled LC-MS (timsTOF) approach for functional detection and class-level differentiation of clinically relevant carbapenemases within a single analytical workflow. By leveraging collisional cross-section measurements, the method enables reliable identification of OXA-48-like carbapenemase through detection of a meropenem-derived {beta}-lactone that is indistinguishable by mass alone. This directly addresses a major diagnostic limitation of conventional activity-based assays, which may yield false-negative results for OXA-48-like enzymes. The approach further demonstrates the potential of integrating ion mobility into routine clinical mass spectrometry to enhance specificity beyond traditional mass and retention time measurements. These findings support the development of next-generation diagnostic strategies capable of detecting both known and emerging resistance mechanisms without reliance on predefined targets.

ObjectiveA catheter-free, non-radiolabeled method that permits in vivo measurement of tissue-specific glucose uptake does not exist. To address this gap, we sought to develop and validate a new, higher throughput mass spectrometry (MS)-based method that combines an injection of insulin with a non-radiolabeled glucose tracer, 2-fluoro-2-deoxyglucose (2FDG), to determine insulin-stimulated tissue-specific glucose clearance in conscious, unrestrained mice. MethodsInjections of saline or insulin with 2FDG were coupled with LC-Q Exactive Hybrid Quadrupole-Orbitrap (LC) MS-based measures of plasma 2FDG and tissue (2-fluoro-2-deoxyglucose-6-phosphate) 2FDGP to determine glucose clearance in mice under several different conditions. ResultsThe newly developed method was first applied to a dose response experiment in mice. Next, the ability of this method to quantify changes in glucose clearance in response to an insulin stimulus was assessed, and glucose clearance was compared between chow and high fat fed mice. Results from these studies showed that insulin-stimulated skeletal muscle and heart glucose clearance can be estimated following a bolus injection of tracer, and these fluxes are blunted in diet-induced obese mice. The broad applicability of this approach was then demonstrated by assessing glucose clearance in a mouse model with anticipated changes in insulin-stimulated skeletal muscle glucose metabolism. ConclusionsThe results validated a new LC-MS method to quantify insulin-stimulated tissue-specific glucose clearance in vivo without the use of catheters or radiolabeled tracers. The method offers great potential because it is designed for application to pre-clinical studies seeking high throughput tests and/or assays that can be coupled with discovery technologies such as genomics, proteomics and metabolomics. HIGHLIGHTSO_LIIn vivo glucose clearance can be estimated by a new non-radiolabeled method. C_LIO_LIThe plasma tracer to tracee ratio is required to determine tissue tracer phosphorylation. C_LIO_LIMeasures of plasma glucose and tracer kinetics are critical for data interpretation. C_LIO_LIThe new method can be combined with omics technologies such as metabolomics. C_LI

IntroductionRetinoids are bioactive vitamin A derivatives that regulate cellular differentiation and gene expression, yet their reliable quantification remains challenging due to low abundance, structural isomerism, and sensitivity to ionization conditions while handling. ObjectivesIn this study, we performed a systematic optimization of liquid chromatography-mass spectrometry (LC-MS)-based detection of retinoids across tissues and biofluids. MethodsChromatographic separation, adduct formation, ionization parameters, fragmentation behavior, and extraction procedures were evaluated in an integrated workflow. ResultsChromatographic conditions influenced not only retention time but also the ionic species detected, affecting precursor selection for MS{superscript 2} analysis. Retinoids exhibited compound-dependent responses to electrospray ionization and collision energy, requiring tailored acquisition parameters. Extraction experiments demonstrated differential recovery among retinoid classes and revealed matrix-dependent behavior, indicating that protocols used for tissues cannot be directly transferred to low-abundance biofluids. Using optimized conditions, retinoids were detected in mouse cerebrospinal fluid (CSF) at concentrations approaching the analytical detection limit, where MS{superscript 2} confirmation was necessary for reliable identification. ConclusionTogether, our results provide a framework for reproducible retinoid profiling across biological matrices and enables comparative studies of retinoid biology in low-volume and low-abundance biofluids.

BackgroundDNA polymerase activity assays are required for enzyme quality control in biotechnology and diagnostics, but standard methods rely on specialist reagents, radioactivity and other hazardous materials, or real-time PCR instruments that are not widely accessible in resource-limited settings. This constrains local production of high quality, validated reagents and increases dependence on imported enzymes. MethodsBased on experiences derived from partnerships with scientists in several low and middle-income countries (LMICs) and stakeholder consultations, we adapted a commercial EvaGreen-based fluorometric DNA polymerase activity assay for isothermal operation using minimal equipment. Assay conditions were optimized using Design of Experiments (DOE) methodology, varying temperature, reaction volume, and MgCl2 concentration. To address reagent cost and supply-chain constraints, we developed detailed protocols for in-house synthesis of the off-patent AOAO-12 DNA dye (sold commercially as EvaGreen) and generation of single-stranded DNA templates via asymmetric PCR. ResultsOptimized isothermal assay conditions (40{degrees}C, 7.75 mM MgCl2) reliably quantified activity across multiple DNA polymerase families. In-house synthesized AOAO-12 dye exhibited comparable DNA-binding performance to commercial alternatives (R{superscript 2} = 0.95), reducing costs by more than an order of magnitude when normalized to working concentrations, enabling assay costs of approximately {pound}0.001 per reaction. The assay is effective across multiple polymerases (Bst-LF, OpenVent, Taq, Q5) and is compatible with both plate readers and qByte, a low-cost, open-source fluorometric device. ConclusionsThis stakeholder-informed assay provides an accessible, cost-effective solution for DNA polymerase quality control in resource-limited settings. The combination of optimized commercial protocols and in-house reagent synthesis offers flexibility for different resource contexts, potentially improving access to molecular biology tools globally.

Extracellular vesicles (EVs) are lipid spheres released from cells. Research utilizing EVs has met several hurdles owing to the small size of the majority of EVs and other nanoparticles (<150 nm) and the lack of detection technologies capable of providing high-throughput single particle measurements at this scale. The use of high-throughput single particle measurements is critical for the assessment of EV heterogeneity and abundance which are features often used to assess the development of isolation protocols or particle characterization. The Coulter principle, known in the field as resistive pulse sensing (RPS), has been used for several decades to size and count cells. More recently, this technology has evolved to accommodate nanoparticle analysis. In the last decade a platform utilizing microfluidic resistive pulse sensing (MRPS) has been demonstrated for nanoparticles, offering ergonomic characterization of nanoparticles along with utilizing open format data. To date, assessment of MRPS accuracy and reporting standards have not been assessed. With the aim of increasing data accuracy, ergonomics, and reporting transparency, we developed a microfluidic resistive pulse sensing post-acquisition analysis software (RPSPASS) application for automated cohort calibration, population gating, statistical output, QC plot generation, alternative data file outputs, and standardized reporting templates.

MicroRNAs (miRNAs) are ultra-short RNA molecules characterized by high sequence homology, frequent post-transcriptional modifications, and typically low abundance, particularly in circulating biofluids. These inherent biological features present substantial technical challenges for RT-qPCR- based quantification. Consequently, the development of miRNA RT-qPCR assays has required architectural adaptations at the reverse transcription (RT) stage to generate extended cDNA templates, thereby enabling effective downstream quantitative PCR amplification. One widely adopted approach involves the enzymatic addition of a poly(A) tail to the 3' end of miRNAs, followed by poly(T)-primed universal reverse transcription, which has gained broad acceptance due to its perceived sensitivity and simplified workflow. However, independent experimental evidence indicates that this architecture does not consistently provide the level of specificity required for reliable single-nucleotide (SN) discrimination, particularly when quantifying low-abundance circulating miRNA targets, as demonstrated in our previous study. An alternative strategy relies on miRNA-specific reverse transcription using stem-loop priming has been equally well accepted. When generically generated, this approach offers certain improved specificity, but its performance in resolving single-nucleotide differences remains limited. In this article, we employed precision engineering to maximize specificity for both reverse transcription and qPCR steps. By tailoring both primer design and reaction architecture to the specific sequence features of each miRNA, we enable robust single nucleotide discrimination among these ultra-short targets. Prototype of ten different miRNova assays quantifying miRNAs whose sequences are differed in various configurations were tested on synthetic miRNA targets. For miRNova assay validation, saliva samples were elite rugby players submitted to small RNA extraction, then RT-qPCR. Spike-in of synthetic targets was applied for each quantification point to characterized the sensitivity, specificity and accuracy of the assays. Comparative analysis was performed between miRNova and two commercially available kits on the same sample set. The obtained results show a superior performance of miRNova assays allowing for sensitive and accurate quantification of miRNAs in saliva samples. Altogether, this results in modular, reproducible assays optimized for low-abundance miRNA detection in challenging biofluids, including saliva, positioning the platform beyond existing sensitivity-focused solutions toward true diagnostic-grade specificity.

Peptide-level analyses are becoming increasingly popular in mass spectrometry-based proteomics and are being applied, for example, in immunopeptidomics, structural proteomics, and analyses of post-translational modifications. In such analyses, peptides that are not biologically meaningful but instead arise as artifacts prior to mass spectrometry analysis pose the risk of data misinterpretation. Here, we describe an approach based on retention time analysis and precise chromatographic peak matching to identify peptides generated by in-source fragmentation (ISF), which occurs between chromatographic separation of peptide mixtures and the first mass filter of a tandem mass spectrometer (MS). To understand the prevalence and properties of ISF, we generated 13 proteomics datasets and analyzed them along with additional 25 previously published datasets spanning a broad range of sample types, MS, and proteomics approaches including classical bottom-up proteomics, immunopeptidomics, structural proteomics, and phosphoproteomics. We found that, in typical trypsin-digested samples on average 1 % of fully-tryptic peptides and 22 % of semi-tryptic peptides originated from ISF. However, we observed large variations between datasets, and in-source fragments exceeded, in some cases, a third of the total peptide identifications. The extent of ISF was dependent on the peptide sequence, the instrument, method parameters, and sample complexity. Although ISF did not impair relative quantification across samples, it generated peptides that could be misinterpreted qualitatively, inflated peptide identifications, and comprised up to 37 percent of peptides shorter than 9 amino acids in immunopeptidomics datasets. We propose that, for peptide-centric applications, our open-source ISF detection approach be used to re-annotate peptides generated by ISF and remove them to avoid misinterpretation of data. ISF is an increasing concern with improving mass spectrometers, as they enable detection of an ever-increasing number of m/z features, including low abundance features like ISF products. Our work thus addresses a growing issue in proteomics and presents solutions to mitigate the impact of in-source fragment peptides. In the future, improved feature detection algorithms may enable elucidation of new ISF patterns affecting side chains that have been missed so far, which could contribute to explaining the vast space of as-yet unannotated proteomics data.

Background: Mucopolysaccharidosis type IIIA (MPS IIIA; Sanfilippo syndrome) is a fatal neurodegenerative lysosomal storage disorder caused by impaired degradation of heparan sulfate (HS). Despite rapid advances in gene and enzyme therapies, there remains a critical need for an analytically validated, quantitative biomarker that accurately reflects central nervous system (CNS) substrate burden. Such biomarker would be a valuable tool in assessing disease progression and monitoring therapeutic efficacy. Objective: This study describes the method development, fit for purpose validation, and preliminary clinical application of a quantitative liquid chromatography-mass spectrometry (LC-MS/MS) assay for the HS-derived disaccharide N-sulfoglucosamine-glucuronic acid (GlcNS-GlcUA) in human cerebrospinal fluid (CSF), a critical biomarker for diagnosis, disease monitoring, and regulatory evaluation of emerging MPS IIIA therapies. Methods: A structurally defined GlcNS-GlcUA reference standard and its [13C6]-labeled internal standard were used in a derivatization and detection workflow employing 1-phenyl-3-methyl-5-pyrazolone labeling, and LC-MS/MS. Results: The method exhibited acceptable linearity across 0.005-0.500 nmol/mL (r[&ge;]0.9976), with intra- and inter-assay imprecision [&le;]3.5%CV and accuracy within 95%-110% of nominal concentrations. No matrix or hemolysis interference or carryover was observed, and the analyte remained stable during freeze-thaw storage conditions. Application of the method to 12 CSF samples from patients with MPS IIIA demonstrated quantifiable GlcNS-GlcUA levels ranging from 0.0054 to 0.106 nmol/mL, confirming suitability for clinical and regulatory use. Comparison of the MPS IIIA sample results between the development laboratory and the contract research organization laboratory support robust inter-lab assay transfer. Conclusions: This validated LC-MS/MS method establishes a regulatory-grade quantitative assay for measurement of CSF HS in MPS IIIA. Its high analytical sensitivity and reproducibility enable reliable assessment of CNS substrate reduction and pharmacodynamic response, supporting biomarker-driven therapeutic development and accelerated approval pathways for neuronopathic mucopolysaccharidoses.

Global quantification of DNA cytosine modifications, including 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC), is important for understanding cancer biology, though established methods require multi-step workflows and costly instrumentation. Here we show that attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy combined with regression modelling enables rapid, label-free, and non-destructive quantification of both modifications from DNA samples. Using Adenomatous Polyposis Coli (APC) promoter DNA standards spanning 0-100% modification, we identified modification-sensitive spectral features and observed that 5-hmC produces greater spectral changes than 5-mC. A univariate peak-ratio approach yielded strong linearity for both modifications (R2 = 0.97), while partial least squares regression (PLSR) improved quantification accuracy to R2 = 0.99 (RMSE = 2.6%) for 5-hmC and R2 = 0.97 (RMSE = 5.7%) for 5-mC. In composite mixtures containing all three cytosine states, 5-hmC remained highly quantifiable (R2 = 0.97; RMSE = 5.1%), while 5-mC accuracy decreased (R2 = 0.90; RMSE = 9.6%), consistent with the greater spectral distinctiveness secondary to the hydroxymethyl group. Transferability was assessed using circulating tumour DNA (ctDNA), short cell-free DNA fragments shed from tumour cells into the bloodstream, comprising multiplexed reference material spanning seven genomic regions and a polydisperse fragment-length distribution (155-220 bp). After domain adaptation between synthetic and ctDNA spectra, we obtained a quantitative methylation calibration with R2 = 0.98 and RMSE = 5.2% under cross-validation. These results support ATR-FTIR spectroscopy as a viable platform for global cytosine modification quantification and establish proof-of-concept applicability to ctDNA analysis.

Tumour biomarkers such as CA125, CA15-3, CA19-9, AFP and CEA are routinely used in the oncology clinic to diagnose cancer, monitor response to therapy, and detect relapse. However, their quantification depends on immunoassay-based methods that are time-consuming, reagent-dependent, and poorly suited to resource-limited settings. Here, we present a machine learning-assisted ATR-FTIR spectroscopy approach for label-free tumour biomarker analysis to enable simple and rapid quantification at the bedside. Using principal component analysis (PCA), we first demonstrate that these five clinically relevant biomarkers are spectrally separable, with the protein-associated region (1200-1700 cm-1) providing the greatest discriminative information. We then develop partial least squares regression (PLSR) models to quantify CA125 in phosphate-buffered saline (R2 = 0.95) and in human serum across a clinically relevant concentration range, achieving reliable predictions at and above the clinical decision threshold of 35 U/mL. A semi-quantitative classification model further demonstrated robust identification of elevated CA125, with a macro-average sensitivity of 0.86 and specificity of 0.92. These results support ATR-FTIR spectroscopy as a rapid, reagent-free platform for cancer biomarker monitoring, with potential utility in resource-limited settings. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/714840v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1be9c03org.highwire.dtl.DTLVardef@f49e5eorg.highwire.dtl.DTLVardef@1c93e39org.highwire.dtl.DTLVardef@1141e6f_HPS_FORMAT_FIGEXP M_FIG C_FIG

Rapid quantification of sulfur-containing amino acids, particularly cysteine, in legumes is critical for assessing nutritional quality, supporting breeding program screening, and ensuring consistency in quality control processes. However, conventional methods, such as high-performance liquid chromatography (HPLC), are time-consuming and resource-intensive for high-throughput applications. This study evaluated artificial intelligence models for predicting cysteine concentration from surface-enhanced Raman spectroscopy (SERS) spectra of pea extracts. SERS spectra were acquired from 20 cultivars grown at three geographically distinct locations, with HPLC-measured cysteine concentrations as a ground truth reference. Linear regression, partial least squares regression, support vector regression, random forest regression, and a one-dimensional convolutional neural network (1D-CNN) were compared using within-cultivar splits and leave-one-cultivar-out (LOCO) evaluation. The 1D-CNN achieved RMSE 0.008 g/100 g within cultivars and maintained performance under LOCO, while other models showed limited generalization. Shapley Additive Explanations highlighted informative bands in the 630-760 cm-1 range, and noise modeling optimized scan-count selection.

Accelerating the development of enzymatic degradation of polyesters such as poly(ethylene terephthalate) (PET) and poly(butylene terephthalate) (PBT) requires a rapid and parallelizable detection method. We developed a protein-based biosensor for the fast and accurate quantification of the PET and PBT degradation product, terephthalate (TPA), which we named TPAsense. Engineering TPAsense required overcoming low thermal stability and aggregation of the initial construct by introducing stabilizing mutations without disrupting the binding affinity to TPA. The sensor performance was validated by screening for the PBT degrading activity of a Leaf-branch Compost Cutinase (LCC) mutant library and comparing with liquid chromatography data. TPAsense detects nanomolar concentrations of TPA enabling shorter incubation times for screening workflows. In addition, a comparative analysis of PETase and PBTase kinetics was performed with TPAsense. Finally, we demonstrated the detection of PET microplastic in samples from a wastewater treatment plant by combining the biosensor and a PETase. TPAsense offers a platform to accelerate PETase and PBTase development for plastic waste recycling and detection of microplastic in the environment.

The ability to detect host cell factors during Staphylococcus aureus infection in vitro by immunofluorescence microscopy is severely hampered by staphylococcal protein A (SpA), a cell wall-anchored protein that binds the fragment crystallizable (Fc) region of immunoglobulins. This interaction generates strong nonspecific fluorescent signals on the bacterial surface, complicating data interpretation and limiting the accuracy of quantitative image analysis. Several measures have been put forward to overcome this obstacle, most importantly the pre-incubation with an anti-SpA antibody (SpA) and the use of human serum (HS) as blocking agent and antibody diluent. To highlight this feature to general fluorescence microscopy users, we here systematically evaluated these two strategies. Using S. aureus coated on coverslips and S. aureus-infected A549 cells, we highlight the efficiencies of both approaches to markedly reduce nonspecific fluorescence, with HS treatment yielding the most profound suppression. Notably, HS, containing high levels of human immunoglobulins, offered a robust, cost-effective and broadly applicable solution for minimizing SpA-driven artifacts, thereby improving immunofluorescence microscopy in S. aureus infection models in vitro.

Ancient human dental calculus is one of the richest archives of archaeological biomolecular information, providing direct evidence of diet, oral health, and the oral microbiome. Proteomic analyses of this biological matrix have so far focused mainly on oral microbes and dietary proteins, with milk proteins such as beta-lactoglobulin (BLG) providing the largest corpus of proteomic evidence. Despite the close relation between the various stages of dental calculus formation and mineralization with the dental enamel surface, proteins from the dental enamel matrix have not previously been reported outside of dental enamel tissue. Here we reanalysed 498 ancient dental calculus proteomes from 14 published studies (n=434 individuals) reporting the presence of BLG, spanning from the Neolithic to the Victorian Era and applying different protein extraction protocols (FASP, GASP, SP3 and in-solution digestion). Dental enamel matrix proteins were identified in ten studies (n=37 individuals), with amelogenin being the most frequently detected. Enamel peptides occurred more often in studies that applied SP3, although amelogenin was successfully identified through both SP3 and FASP. Structural proteins, including enamelin, ameloblastin, and MMP20, were also identified. The detection of AMELX and AMELY peptide sequences provided new insights into cases where the sex was previously undetermined. These findings establish dental enamel proteins as a new category of biomolecules detected in dental calculus, broadening its application beyond diet and microbiome studies to possible sex estimation. HighlightsO_LIDental calculus entraps oral microbes along with endogenous and exogenous particles during formation and mineralization C_LIO_LIWe conduct reanalysis of 14 published ancient dental calculus studies (n = 434 individuals) spanning the Neolithic to Victorian Era C_LIO_LIDental enamel proteins AMELX, AMELY, AMBN, COL17A1, ENAM and MMP20 are identified in ancient human dental calculus C_LIO_LIAmelogenin was the most frequently detected enamel protein C_LIO_LIWe expand dental calculus palaeoproteomics beyond diet and oral microbiome to potentially include sex estimation C_LI

A recent clinical study tested the effects of two different monoclonal antibodies (mAbs) (siltuximab, anti-IL6; tocilizumab, anti-IL6R) on the fate and function of T-cells in people with type 1 diabetes. While both mAbs affect the response of T-cells to stimulation, they have very different, sometimes opposing mechanisms. Here, we use mass-spectrometry based proteomics to analyze longitudinal serum samples (baseline and two weeks post-treatment) from 20 clinical trial participants to examine the effects of siltuximab and tocilizumab on extracellular vesicles. To accomplish this, serum samples were enriched for extracellular vesicles with Mag-Net and analyzed by LC-MS/MS to identify significantly differentially abundant protein groups and pathways. Proteome analysis confirmed highly reproducible measurements across multiple draw dates. In total, we quantified >3300 protein groups of which 46 protein groups had significantly altered abundance after mAb treatment. Tocilizumab altered pathways associated with proteostasis (neddylation) and pre-notch transcription and translation. Siltuximab altered FCGR activation pathway members. In addition, quantitation of the monoclonal antibody therapies themselves enabled the measurement of the correlation between drug amounts and impacted proteins. Taken together, this work demonstrates the utility of the Mag-Net method to evaluate the impacts of therapeutic interventions on serum extracellular vesicles.

Over the past decades, the frequency of viral outbreaks has increased substantially worldwide, driven in part by global travel and resulting in millions of deaths each year. This trend underscores the urgent need for rapid, simple, and accessible diagnostic tools for infectious disease detection. Here, we present a nanofluidic digital chip (Nano-dChip) for point-of-care viral RNA detection that delivers results within 30 minutes at a cost of less than $0.50 per chip. The Nano-dChip employs reverse transcription loop-mediated isothermal amplification (RT-LAMP) for highly sensitive and specific target amplification. Reaction reagents are compartmentalized into numerous nanofluidic reservoirs, enabling highly quantitative detection while minimizing contamination risks. Using a single chip, we successfully detect both SARS-CoV-2 and Influenza H3 RNA with a detection limit of 10 fM, demonstrating the Nano-dChips potential as a rapid, low-cost, and scalable diagnostic platform for timely outbreak control.

Semi-permeable capsules (SPCs) create enclosed porous microenvironments, diffusible to only small proteins and macromolecules. This presents a powerful tool for single cell observation, isolation, and sequencing. However, their range of use for sustaining viable microbial eukaryotes is largely unexplored. Single-cell eukaryotes are often understudied, with a wealth of unknown lifecycles, culturing methods and inter-microbial interactions, which are difficult to visualize. Here, we show that eukaryotes from eight different supergroups can be captured and propagated in SPCs. Encapsulation allowed observations of cell stages, motility and growth in a traceable and parallelized manner.

IntroductionDiagnostics have become the fundamental backbone of HIV prevention, treatment and long-term retention in care, and are critical to achieving the 95-95-95 UNAIDS targets. To effectively reach underserved and remote populations, diagnostic technologies must be cost-effective, robust, user-friendly and suitable for settings with limited infrastructure. Among available testing modalities, rapid diagnostic tests (RDTs) play a central role in expanding HIV testing coverage. Earlier generations of RDTs were limited by their inability to detect acute HIV, with limited ability to detect p24 antigen (Ag), an early marker of HIV infection, which is expected to shorten the diagnostic window to two-to-three weeks. The introduction of fourth-generation RDTs, which detects both chronic and acute HIV infection through p24 Ag detection, was designed to ensure that the traditional diagnostic window of two-to-three months is shortened to approximately two-to-three weeks. However, integrating these assays into existing testing algorithms requires clear evidence that they meet high standards of quality and performance. This systematic review aims to assess the performance of WHO-prequalified fourth-generation Ag/Ab RDTs. MethodsWe performed a systematic search across six databases to identify studies evaluating Ag/Ab RDTs against laboratory reference standards in individuals aged 12 years and older, spanning 1 January 2010 to 31 December 2025. Outcomes were limited to measures of diagnostic accuracy. A meta-analysis focusing exclusively on WHO-prequalified fourth-generation RDTs was performed using a bivariate random-effect model. Results1,932 records were screened, of which 31 diagnostic accuracy studies from 19 countries were included. 15 studies used US-only approved products, 12 used WHO-prequalified products and four used commercially discontinued products. The pooled sensitivity of WHO-prequalified Ag/Ab RDTs for acute HIV infection (AHI) was 94% (95% CI: 86%-99%). An RNA threshold of [&ge;] 1,000,000 copies/mL was used as a proxy for high viraemia and used as a cut-off for the following analyses. The cut-off based analysis is considered more suited to decision-making, as it focuses on cases most likely to be associated with higher viraemia and greater potential for detection during the p24 Ag window. When using enzyme immunoassay (EIA) as the reference standard, the pooled p24 Ag sensitivity was 76% (95% CI: 62%-88%), and the pooled p24 Ag sensitivity when using nucleic acid amplification test (NAAT) as the reference standard was 75% (95% CI: 41%-97%). In the general population, the pooled sensitivity for p24 antigen detection was 77% (95% CI: 60%-92%). Amongst risk populations, only three studies had available raw data, and the pooled sensitivity was 62% (95% CI: 10%-97%). In plasma and serum specimens, pooled p24 Ag sensitivity was 74% (95% CI: 57%-88). DiscussionCollectively, these findings indicate that WHO-prequalified fourth-generation Ag/Ab RDTs can function as a scalable frontline screening tool, particularly in low- and middle-income countries, while offering incremental holistic detection through p24 Ag. Their effective deployment, however, depends on maintaining standard algorithm safeguards, including repeat testing and targeted laboratory referral when acute infection is suspected. ConclusionsResults from this meta-analysis support the use of WHO-prequalified fourth-generation Ag/Ab RDTs for general population screening. From a programmatic perspective, the added value of WHO-prequalified fourth-generation RDTs lies in their ability to combine rapid, decentralized access to testing, with incremental yet impactful improvements in holistic detection.

Backscattered electron scanning electron microscopy (BSE-SEM) provides compositional image contrast but has found limited application to biological samples due to the low atomic number difference between constituent elements, the thickness of the surrounding environment, and the need for complex sample preparation. Here, we demonstrate the use of room temperature liquid phase BSE-SEM (LPBSEM) for imaging Bacillus subtilis spores encapsulated in graphene liquid cells, preserving native hydration and reducing the thickness of the sample environment. This approach eliminates the need for staining and enables high-contrast visualisation of subcellular structures. Distinct structural layers within B. subtilis spores have been observed with a contrast similar to conventional thin-section transmission electron microscopy but without the need for sample preparation that potentially compromises sample integrity. We further investigate the influence of beam energy on the interaction volume depth and image contrast and propose optimal conditions for subsurface visualisation. Monte Carlo simulations have been used to validate our experimental observations and provide a quantitative framework for understanding BSE generation from hydrated, low atomic number specimens.

Background: Host genetics alone explains limited susceptibility to tuberculosis (TB), particularly in people with HIV (PWH). Protein quantitative trait loci (pQTLs), genetic variants that regulate plasma protein levels, may bridge genetic and immunological mechanisms underlying TB progression. Methods: We conducted cis-pQTL mapping in 60 PWH who progressed to active TB and 194 matched controls from the Swiss HIV Cohort Study. Plasma proteomes were quantified via high-resolution mass spectrometry (dia-PASEF), and genotype-protein associations were analyzed separately in TB and control groups. Results: TB progressors harbored 26 cis-pQTLs linked to 12 proteins uniquely enriched in immune pathways (antigen presentation, complement activation, phagocytosis, and T-cell regulation). Controls showed 107 cis-pQTLs linked to 14 targets. Gene Ontology enrichment revealed 46 immune biological processes in TB versus only 1 in controls, with HLA-C, C4B, and CHIT1 as key TB-specific proteins. Conclusions: Integrating proteomics with genomics suggests differential regulation of immune proteins associated with TB progression in PWH. hese genetically anchored protein candidates support follow-up studies and future biomarker evaluation for TB risk prediction.