SLAS Technology

In vitro cytotoxicity assessments frequently rely on staining-based methods that indirectly estimate viable cell numbers indirectly. A major limitation of many such techniques is their endpoint nature, requiring cell lysis or irreversible processing that precludes longitudinal monitoring of cellular responses following treatment. An ideal assay for evaluating cell viability and proliferation should be simple, rapid, cost-effective, reproducible, and highly sensitive, while also enabling accurate quantification with minimal interference from test compounds. The resazurin reduction assay satisfies these criteria, offering a sensitive and economical alternative to conventional tetrazolium-based methods. Although both assay types depend on the metabolic reduction of a dye by viable cells, they differ mechanistically. Tetrazolium salts (e.g., MTT) are reduced by cellular dehydrogenases to insoluble formazan crystals that require solubilization before to detection. In contrast, resazurin--a cell-permeable, non-fluorescent blue dye--is reduced to resorufin, a highly fluorescent compound detectable without additional processing steps. This property renders the resazurin assay broadly applicable to viability testing in eukaryotic cells cultured in both 2D and 3D formats, as well as in bacterial systems. Here, we present a streamlined, universal protocol for implementing the resazurin reduction assay across diverse experimental models, emphasizing its practicality, reproducibility, and adaptability for real-time viability monitoring. Key featuresO_LIReal-time, non-destructive monitoring: Enables longitudinal studies by allowing repeated measurements of the same samples over hours without toxicity or disruption. C_LIO_LIStreamlined workflow: A simple "add-incubate-read" protocol eliminates the need for cell lysis, washing, or extraction, saving time and reducing variability. C_LIO_LIBroad sample compatibility: Versatile and reliable for use with 2D monolayers, 3D spheroids, organoids, and bacterial cultures. C_LIO_LIHigh sensitivity: Fluorescent detection of resorufin provides exceptional sensitivity, enabling accurate quantification of even small viable cell populations. C_LIO_LILow background and minimal interference: A clean fluorescent readout reduces the risk of signal artifacts, offering a more reliable alternative to traditional colorimetric assays. C_LIO_LICost-effective and accessible: Utilizes standard laboratory plate readers and commercially available reagents, making it an economical choice for any lab. C_LIO_LIScalable for high-throughput screening: Easily adaptable to various plate formats, supporting both small-scale experiments and large-scale automated screening applications. C_LI Graphical overview O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/718248v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@82bcecorg.highwire.dtl.DTLVardef@14164aforg.highwire.dtl.DTLVardef@395118org.highwire.dtl.DTLVardef@fb1349_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundHigh-content assays (HCAs) have problems distinguishing biologically significant effects from the incidental effects of non-repeatable technical factors. Non-repeatable results are attributed to variations in the cell culture environment and the numerous, heterogeneous descriptors evaluated. The aim here was to determine whether preprocessing operations impacted the reproducibility of class assignments of experimental data. MethodsBatch effects that could affect reproducibility, i.e., signal/noise ratio, instrumental conditions, and segmentation, were controlled variables. The remaining batch effects, variations in materials, personnel, and culture environment could not be controlled. Descriptors values were measured directly from images. Exploratory factor analysis was used to solve the identifiable and interpretable feature, factor 4. In each of five trials, one sample was treated with the same chemical mixture (EXP) and another with the solvent vehicle alone (CON). ResultsRepeated CON and EXP samples showed significant differences among factor 4 means in data regularized within each trial. The mean of Trial 3 CON differed significantly from all other CON samples. These differences disappeared upon regularization to comprehensive databases. Among repeated EXPs, the Trial 2 mean differed from three other EXPs, but regularization to comprehensive databases had little effect. However, classification patterns were unchanged after regularization to any comprehensive database derived by the same protocol. After regularization to datasets derived by two different protocols, the classification pattern differed but only reflected elevation of differences that had been marginal to statistical significance. Outlier removal was deleterious. Even with the most sparing definition of outliers, over 3% of a single samples contents were removed from most trials. Elimination based on the overall within-trial distributions caused type I and type II errors. ConclusionsNon-repeatable factor 4 means in repeated trials had negligible influence on classification outcomes, so repeatability may not be a good indicator of assay quality. Irreducible batch effects, combined with small sample sizes and skewed distributions of descriptors values, may account for non-repeatability. As the current results are based on real-world data, they suggest that non-repeatability is an uncorrectable feature of these assays. Classification patterns are not affected by several irreducible technical factors, namely materials, personnel, and non-repeatable environmental variables.

With the introduction of dedicated nanoscale flow cytometers, the need for suitable compensation beads has emerged. Here, we present a rapid and cost-effective method to generate [~]100 nm antibody-binding compensation beads compatible with a wide range of antibody species for use in nanoscale flow cytometry. This approach may provide a practical interim solution until commercial alternatives become available.

1.Adipocyte size is an independent predictor of several metabolic disorders, including type 2 diabetes, liver and cardiovascular diseases. However, technical limitations due to the fragile nature of mature adipocytes have restricted the functional analyses of size-separated adipocytes using conventional methods. Therefore, we have developed a microfluidic device, based on deterministic lateral displacement, for sorting intact, mature adipocytes. Cell-size distribution was determined from time-lapse recordings inside the device, in separate outlets, and by Coulter counter analysis of the collected cell fractions. This approach allowed size-separation with minimal size-overlap with mean diameters of (small fraction) 47 {micro}m and (large fraction) 82 {micro}m based on Coulter counter measurements. Viability of the separated cells was verified by insulin stimulation and western blotting of key insulin signaling proteins. The sample recovery, comparing input versus output material, was relatively high, 42% for the large fraction with a purity of 93%. We demonstrate that microfluidics is a suitable approach to overcome the limitations of sorting mature adipocytes according to size. Together, the high recovery rate, high throughput capacity, accurate separation and the fact that the cells maintained hormonal response after sorting provides compelling evidence of the strength and usability of the microfluidic approach for exploring adipocyte function in relation to size.

Transcriptional bursts regulate gene expression by altering burst size or burst frequency. Here, we present a protocol that integrates fixed-cell smFISH and live-cell single-molecule imaging to analyze estrogen-responsive transcriptional bursting of the TFF1 gene in human breast cancer cell lines. This workflow enables measurement of burst size, burst initiation, and active allele frequency to determine how endocrine disruptor chemicals modulate transcriptional bursting dynamics. For complete details on the use and execution of this protocol, please refer to Day, Yasar et al.1

Traditional clonogenic assays remain central to evaluating the self-renewal capacity of tumor cells. However, the assay relies on subjective endpoint measurements, is restricted to two-dimensional monolayer growth, and lacks the single cell resolution required to resolve heterogeneous expansion behaviors. We describe a high-density microwell array-based platform for quantitative assessment of single cell clonogenic growth outcomes, defined by cell count distributions spanning non-dividing, slow-dividing, and fast-dividing three-dimensional colony forming phenotypes. This approach links initial single-cell occupancy to defined growth outcomes across thousands of indexed microwells per well. The platform integrates high-density, low-adhesion microwell arrays within industry standard device plate formats and an automated image analysis pipeline incorporating machine learning, enabling parallel quantification of spatially indexed founder-derived microwells using widely accessible automated imaging systems. The assay was implemented in both 4-well and 96-well plate formats to evaluate reproducibility and scalability across different plate configurations. Using three glioblastoma cell lines as model systems, we demonstrate reproducible single founder occupancy and consistent clonal growth outcome distributions across replicate formats. This integrated microscale assay platform enables systematic quantitative characterization of clonogenic expansion capacity at single cell resolution and is compatible with applications in cancer biology, therapeutic testing, and functional single cell phenotyping. By resolving single-cell persistence, limited expansion and high expansion outcomes within a scalable high-density format, this approach expands the analytical resolution of single cell clonogenic profiling beyond traditional binary colony scoring.

Accurate quantification of fungi is important for a myriad of applications but remains challenging. Previously, we demonstrated that an approach called the adenine-HPLC method can quantify bacteria, including those with aggregating properties that are difficult to quantify using conventional methods, by measuring cellular adenine derived from DNA and converting the adenine amount to genome copy number, without being influenced by cell morphology. However, in this study, when this adenine-HPLC method was applied to the quantification of budding yeast as a model fungus, accurate measurement proved impossible. This limitation was attributed to adenine release from other adenine-containing biomolecules, such as RNA and ATP, and we therefore developed a method that suppresses adenine release from these molecules. This method involves reducing the temperature of the acid treatment and prewashing the cells before acid treatment. In addition, we incorporated a process that corrects for the naturally occurring free adenine level as background during total adenine measurement. The improved adenine-HPLC method based on these modifications enables accurate quantification of budding yeast using genomic DNA content in whole cells as the quantification unit.

Manual colony counting remains the rate-limiting, operator-dependent step in culture-based food microbiology quality control (QC). Automated colony analysis using machine learning (ML) offers the potential to standardise, accelerate, and improve the traceability of this process. However, systematic multi-method validation data for AI-based platforms against recognised international standards remain scarce. We conducted a prospective, multi-study validation of the Reshape Smart Incubator which is an automated imaging and ML-based colony analysis system, across eight ISO microbiological reference methods. In total, 887 plates were analysed, spanning qualitative (presence/absence) detection of Listeria spp. (ISO 11290-1) and Salmonella spp. (ISO 6579), and quantitative enumeration of total viable count (ISO 4833), Bacillus cereus (ISO 7932), Enterobacteriaceae (ISO 21528), coagulase-positive Staphylococci (ISO 6888), yeasts and moulds (ISO 21527), and lactic acid bacteria (ISO 15214). Automated results were benchmarked against the consensus of three or more trained technicians. The platform achieved 100% agreement with manual assessment for all both qualitative detection methods (ISO 11290-1, ISO 6579) with zero false positives and zero false negatives. For quantitative enumeration, agreement ranged from 92.97% (ISO 15214, n=122, using ISO-aligned {+/-}10%/>30 CFU thresholds) to 98.46% (ISO 21528, n=130). Where discrepancies occurred, they largely coincided with plates showing high inter-technician variability. Precision testing demonstrated a coefficient of variation of 5.88% and a mean standard deviation of 0.44 CFU for low-count plates. This study presents a comprehensive multi-ISO validation of an AI-based colony analysis system to date. The AI models demonstrated performance comparable to or exceeding that of trained human technicians across a broad range of microbiological targets, agar types, and colony morphologies, thereby supporting their use as a validated and traceable alternative to manual plate reading in accredited food microbiology quality control laboratories.

In this paper, we aim to present a new intravital cells visualization method, which is based on use of a dye called ABDS ("A Beautiful dye for staining"), which can be prepared using a marker pen and is useful for eukaryotic cell research. Using a wide range of instruments, including optical measurements, microscopy studies and wet biology techniques, we have shown that ABDS is close by properties to Rhodamine 6G dye (R6G), which is well known as endoplasmic reticulum stainer. However, by the careful examination of the ABDS and R6G images (ABDS/R6G), we have proved for the first time that these dyes also stain the cytoplasmic membranes. The significant contrast between ABDS/R6G signal from cell membrane and endoplasmic reticulum allows them to be distinguished in the fluorescence photographs. Other important properties of ABDS are its availability, simplicity in manufacturing, safety for living cells in vitro, and bright stable fluorescence, which in contrast to commercial dye like DiBAC allows us to study cells in space and time with high detalization. The paper includes a method for preparing ABDS, a data set with its characteristics, comparison with other commercial dyes, as well as examples of ABDS usage in cells research. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=198 SRC="FIGDIR/small/717455v1_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@f1ceacorg.highwire.dtl.DTLVardef@137abd2org.highwire.dtl.DTLVardef@1f19efcorg.highwire.dtl.DTLVardef@1fcbc9e_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA protocol for high-resolution vital staining of the cells using an inexpensive dye based on permanent marker ink is proposed. C_LIO_LIThe absorption, emission and Raman spectra of the proposed dye are presented, and a direct comparison with commercial dyes Rhodamine 6G, DiBAC and Deep Red Cell Mask dye is made. C_LIO_LIThe main characteristics of the proposed dye are low toxicity, long-term fluorescence, and the ability to separately stain the endoplasmic reticulum and cytoplasmic membrane. C_LIO_LIThe ability of the Rhodamine 6G dye to stain cell membranes also has been proved. C_LI

Aroma perception during food consumption results from the combined effects of food composition, oral processing (such as chewing and saliva action), the release and transport of volatile compounds toward the olfactory epithelium, followed by cognitive integration in the brain. Recent advances in real-time analytical techniques, particularly Proton Transfer Reaction-Time-of-Flight Mass Spectrometry (PTR-ToF-MS), enable in vivo monitoring of aroma release with high temporal resolution and have become widely used for analyzing the composition of exhaled air. However, the interpretation of aroma release kinetics remains challenging due to substantial intra- and inter-individual variability caused by differences in physiology, anatomy, oral behavior, and respiratory patterns. In this context, the present study was designed to quantify aroma release associated with different food oral processing (FOP) mechanisms, such as chewing and swallowing, using simple model matrices containing a single aroma compound, and to document inter- and intra-individual variability among subjects. Real-time PTR-MS measurements were combined with self-reported oral events and simultaneous respiratory monitoring to analyze aroma release from aqueous solutions and gummy discs flavored with isoamyl acetate. The results showed that inter-individual variability was higher than intra-individual variability and allowed its quantification in aroma release. Significant differences in aroma release kinetics were observed depending on FOP protocols. The importance of considering swallowing events when analyzing aroma release data was also highlighted.

IntroductionAccurate in silico evaluation of primers and probes is essential for the rational design of molecular multi-parameter assays. We present Assay-BLAST v2 to automate and simplify this process for extensive assay designs. ResultsA newly integrated strand and proximity check enables precise validation of corresponding oligonucleotides, ensuring correct orientation and spacing for efficient amplification. Based on predicted oligonucleotide interactions, Assay-BLAST v2 estimates amplification outcomes, offering a computational benchmark for downstream wet-lab validation and performance correlation. Additionally, the updated software integrates an adaptive BLAST parameter optimization that dynamically scales with database size, thereby improving both analytical sensitivity and computational performance. These improvements are supported by a comparative evaluation against the previous version of AssayBLAST. ConclusionsCollectively, these enhancements streamline the assay development workflow, reduce costs associated with suboptimal primer and probe synthesis, and increase the robustness and reliability of molecular diagnostics and research applications.

Colorimetric loop-mediated isothermal amplification (LAMP) on microfluidic paper-based analytical devices (PADs) offers a low-cost, disposable, and equipment-free alternative to liquid LAMP assays. However, amplification on PADs is consistently slower, by 5-46%, than reactions in tubes. To identify the origin of this delay, we evaluated heat transfer, diffusion in porous cellulose, and nonspecific adsorption of LAMP components across both high- and low-copy input regimes. Our results show that once thermal equilibrium is reached, reduced effective diffusion is the dominant contributor to the kinetic lag at low copy numbers, whereas nonspecific adsorption becomes the primary barrier at higher template concentrations. Pre-coating the paper with bovine serum albumin (BSA) mitigates adsorption. It narrows the tube-to-paper gap, thereby accelerating amplification of the SARS-CoV-2 ORF7ab synthetic gene by an average of 6 minutes, from 1E3 to 1E5 copies per reaction. These findings provide a mechanistic basis for the copy-number-dependent behavior of PAD LAMP and offer simple, low-cost strategies to improve the speed and reliability of PAD nucleic acid assays.

Maintaining precise isothermal conditions in portable nucleic acid amplification tests (NAATs) is critical for reproducible results but remains challenging with conventional single-sided thin-film heaters, which exhibit temperature gradients and strong dependence on ambient conditions. To close this gap, we engineered ThermiQuant VitroMini, a dual-sided heater design that achieves volumetric-level temperature uniformity using thin-film heaters while preserving optical transparency for real-time colorimetric loop-mediated isothermal amplification (LAMP) analysis on microfluidic paper-based analytical devices ({micro}PADs). The device integrates two independently regulated indium tin oxide (ITO) heaters (8 {Omega} each) controlled by independent proportional-integral-derivative (PID) algorithms. Heaters were evaluated under controlled ambient environments of 4 {degrees}C (refrigerated), 23 {degrees}C (room temperature), and 50 {degrees}C (oven). Analytical tests were performed using a colorimetric LAMP assay targeting the SARS-CoV-2 orf7ab gene on {micro}PADs preloaded with dried LAMP reagents, with time-lapse images (30 seconds interval) analyzed via Amplimetrics software. VitroMini maintained 65 {+/-} 0.5 {degrees}C across 4 to 50 {degrees}C ambient conditions and achieved a limit of detection of 50 copies/reaction (6.7 copies/{micro}L), with quantification times (Tq) linearly correlated with log10 DNA concentration. Dual-sided heating eliminated temperature bias, condensation artifacts, and ambient-dependent variability while preserving optical transparency for real-time LAMP quantification. ThermiQuant VitroMini bridges the gap between benchtop volumetric heaters and portable diagnostic devices, offering a compact, low-power, and field-deployable platform for decentralized molecular diagnostics and One Health applications.

Antimicrobial resistance (AMR) is a growing global threat to human health, and rapid methods for characterising emerging antimicrobial resistance genes (ARGs) are needed. Here, we develop a semi-automated workflow using cell-free gene expression (CFE) systems to measure the activity of two ARGs encoded on plasmid DNA that produce rifampicin-inactivating and gentamicin-inactivating enzymes. We validated the use of a small benchtop Myra liquid handling system compared to manual pipetting, with no statistical differences observed. After optimising the pre-incubation time of ARGs and dispensing protocol, expression of aac(3)-IIa increased the half-maximal inhibition concentration (IC50) of gentamicin by over 150-fold, while arr-3 increased the IC50 of rifampicin by approximately 20-fold compared to controls. Future work could extend this platform to characterise novel ARGs identified through genomic surveillance or rapidly profile activity of new or derivative antibiotics. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/720151v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1a61fe3org.highwire.dtl.DTLVardef@1778eadorg.highwire.dtl.DTLVardef@380be4org.highwire.dtl.DTLVardef@194bb63_HPS_FORMAT_FIGEXP M_FIG C_FIG

Digital PCR (dPCR) is a powerful technology for absolute quantification of nucleic acids, valued for its accuracy, sensitivity, and repeatability. Yet, the commercialization of different instruments with proprietary software has introduced challenges to data analysis, interoperability, and comparability. Therefore, we present the Digital PCR Data Essentials Standard (DDES) - a lightweight, human- and machine-readable, and cross-platform data standard developed in collaboration with the dPCR community. The standard consists of three file types designed to enable both manual inspection and automated analysis: (i) a main file summarizing experiment and reaction-level (meta-)data; (ii) an assay file describing targets and detection chemistry, and (iii) intensity files capturing partition-level raw fluorescence data per reaction. DDES supports a wide range of current dPCR applications, including singleplex and multiplex assays, endpoint and real-time readouts, and will be curated to implement future dPCR developments. By harmonizing the data structure, DDES lays out the foundation for FAIR dPCR data practices and supports improved software compatibility, collaborative and reproducible research, and future dPCR data repositories.

Biocompatible fluorosurfactants are essential for many droplet microfluidic workflows but are often obtained from commercial sources because published syntheses of perfluoropolyether (PFPE)-based surfactants typically require acid chloride intermediates and chemistry-oriented purification methods. These requirements can limit access for biology and clinical laboratories seeking low-cost or customizable surfactant systems. Here we describe a practical method for preparing functional PFPE-based fluorosurfactant materials by direct carbodiimide coupling of functionalized PFPE carboxylic acids(Krytox 157 FSH) to amine-containing head groups under laboratory-accessible conditions. Using this approach, we prepared a PFPE-polyethylene-glycol (PFPE-PEG) material from Jeffamine ED900 and a PFPE-Tris material from Tris base. Because these products were not fully structurally characterized, we present them as functional reaction products and evaluate them by use in biomicrofluidic workflows rather than by definitive compositional assignment. PFPE-Tris was useful for generating relatively uniform small droplets, whereas the PFPE-PEG preparation supported a broader range of biological applications. These materials were used in genomic library screening for {beta}-glucosidase activity, thermocycling-associated droplet workflows, and protein crystallization experiments. In addition, the PFPE-PEG preparation improved emulsion behavior in many protein crystallization screens that were unstable with a commercial droplet oil used in our laboratory. This method reduces the practical barrier to in-house fluorosurfactant preparation and allows biology-focused laboratories to explore head-group chemistry, oil composition, and operating conditions without complete reliance on commercial reagents. The results support this workflow as a useful entry point for biomicrofluidics laboratories, while also highlighting the need for careful interpretation of thermocycled droplet assays and for future analytical characterization of the resulting materials. Significance statementDroplet microfluidics relies on fluorosurfactants that are often costly and difficult to synthesize outside of chemistry-focused settings. We describe a simple, biology-laboratory-compatible approach for generating functional perfluoropolyether-based fluorosurfactant materials using direct carbodiimide coupling and straightforward cleanup. The resulting materials supported multiple biomicrofluidic workflows in our laboratory, including enzymatic screening and protein crystallization, and provide a practical route for groups seeking lower-cost and more customizable surfactant systems.

Cultivated meat production requires robust and validated analytical methods for comprehensive characterization. While transcriptomics-based approaches establish the foundational profile of molecular analysis, proteomics provides additional resolution that further enhances scientific certainty in both product development and safety characterization. However, the industry adoption of proteomics is currently hindered by technical complexity and a critical lack of analytical standardization, which leads to significant workflow-dependent variations in proteome coverage. To address this gap, we investigated the influence of key workflow steps (digestion, cleanup, LC-MS conditions) on the proteome profile of cultivated duck biomass. We compared five bottom-up sample preparation protocols - two traditional in-solution options (urea and SDC-based protocols), two device-based approaches (PreOmics iST and EasyPep kits), and an innovative protocol (SPEED), and demonstrated that device-based protocols offered the highest peptide yield and proteome coverage. However, optimization allowed cost-effective in-solution methods to achieve comparable performance. Specifically, an optimal digestion time of 3 hours at 37{degrees}C and the use of polymer-based desalting columns significantly enhanced protein identification ([~]4500 - 5000 IDs). Moreover, data independent acquisition (DIA) provided deeper proteome coverage than data dependent acquisition (DDA) with higher precision ([~]6500 vs 5000 IDs). The validated Standard Operating Procedures presented here establish a standardized framework for bulk bottom-up proteomics in cultivated meat, facilitating the generation of reliable and comparable data required for robust multi-omics characterization. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/713501v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@5b61b8org.highwire.dtl.DTLVardef@16c7e65org.highwire.dtl.DTLVardef@1de21d2org.highwire.dtl.DTLVardef@7e984a_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIComplexity and non-standardization limit MS-proteomics use in cultivated meat (CM). C_LIO_LICM protein profile varies with sample prep, LC-MS, and data processing pipeline. C_LIO_LIDevice-based and optimized cost-effective protocols offer a high proteome coverage. C_LIO_LIProteomics can complement transcriptomics for a comprehensive CM characterization. C_LIO_LIProposed standardized methods ensure reliable data for future regulatory submissions. C_LI

The development of chemiluminescent immunoassays (CLIAs) is a complex and iterative process that relies on costly laboratory infrastructure, limiting its accessibility and application across healthcare settings and disease areas. Here, we detail the CLIA Mobile Development Kit (CLIAMDK) a modular, mobile, and inexpensive platform to assess image sensors, smartphones and data processing workflows for CLIA development. For its demonstration, we developed two CLIAs targeting renin and aldosterone, key biomarkers for diagnosing primary aldosteronism. The results from our performance study, including 50 patient samples, demonstrate the potential of our platform in a real-world scenario. We found that the performance of our mobile reader platform is comparable to that of a state-of-the-art plate reader, with a Lower Limit-of-Detection (LLoD) approaching 41 femtomolar. We envision that our platform will help accelerate CLIA development, make it more accessible, and lay the foundations for novel, distributed, yet highly sensitive diagnostic tests.

Subtyping of ketoacidosis, a metabolic state characterized by blood acidification due to various causes, remains challenging in forensic casework. Postmortem omics samples paired with machine learning offers an independent tool to address this challenge. However, such data, especially related to real forensic cases, are rare. In Sweden, high-resolution mass spectrometry data routinely collected in forensic toxicology, can be leveraged for metabolomic analysis. Here, we integrate postmortem metabolomics and machine learning models to detect and subtype ketoacidosis-related deaths using real forensic cases in Sweden. From femoral blood samples of 109 alcoholic ketoacidosis cases, 220 diabetic ketoacidosis cases, 140 hypothermia cases, and 1,229 controls (hanging cases), we developed and tested three machine learning models, which achieved over 90% accuracy in ketoacidosis detection and over 80% in subtyping. Validation with independent cohorts (21 starvation cases, 29 alcoholic controls, and 40 diabetic controls) confirmed robustness with over 80% of starvation cases classified as ketoacidosis-related. Feature clustering highlighted metabolites such as cortisol to be important for subtyping. In summary, our findings demonstrate that combining machine learning with postmortem metabolomics enables accurate detection and subtyping of ketoacidosis-related deaths, which is useful for forensic casework.

Industrializing cultivated meat requires cell lines with high proliferative capacity, genetic stability, and suspension adaptability. We present a comprehensive multi-omics framework, integrating genomics, transcriptomics, and proteomics, to characterize a commercial duck Embryonic Stem Cell (dESC) line. Our analysis demonstrates continuous proliferation in protein-free suspension media while maintaining a stable genome and a functional conserved transcriptome. Broad-scale transcriptomics confirms the absence of hazardous pathway activation, and targeted assays verify sustained pluripotency marker expression during scale-up. Compositional analysis reveals a low-fat biomass containing all nine essential amino acids with an amino acid profile comparable to conventional duck meat. Furthermore, proteomic profiling demonstrates inter-batch reproducibility and protein distributions comparable to duck breast and liver. This study provides the first detailed molecular characterization of a commercial cultivated meat cell line, establishing a reference for the stability and safety assessment of future cultivated meat cell lines.