Talanta

Non-small-cell lung cancer (NSCLC) diagnosis is challenged owing to the need for reliable, non-invasive biomarkers. Circulating cell-free microRNAs (ccf-miRNAs) are promising candidates, but their low levels and short sequences in blood complicate detection. In this study, a novel nano-hybrid fluorescent array was developed to enable rapid and sensitive identification of NSCLC-related ccf-miRNAs. The array consists of poly(T)-modified fluorescent nano-polystyrene beads for capturing target miRNAs, and fluorophore-labeled, sequence-specific locked nucleic acid (LNA) probes for their detection. This design forms a sandwich structure with the target miRNA. Nano cytometry and fluorescence microscopy assessed both the capture and specificity of detection. The assay was tested on plasma samples for miR-16-5p and U6, evaluating selectivity, sensitivity, and reproducibility. The results showed that the poly(T)-modified beads efficiently captured the target miRNAs, and the LNA probes accurately distinguished the sequences. The assay enabled direct detection of miR-16-5p and U6 from plasma without amplification, demonstrating high selectivity, sensitivity, and reproducibility. Combining enrichment with nano-polystyrene beads and sequence-specific LNA probes addressed the main challenges of ccf-miRNA detection, namely their low abundance and short sequence length. As ccf-miRNAs are linked to NSCLC progression, this method could assist in early diagnosis, disease monitoring, and assessment of treatment response. The target-independent nature of the poly(T) capture layer allows for easy calibration to new miRNAs by changing the LNA probes, rendering it suitable for multiplex detection in clinical settings. However, further preclinical and clinical studies are needed before adoption in routine practice. This nano-hybrid fluorescent array presents a rapid and reliable approach for detecting low-abundance ccf-miRNAs in plasma. Its encouraging performance and flexible design show potential for future application in NSCLC diagnosis and monitoring, subject to additional confirmation.

Perovskite quantum dots (PQDs) are exceptionally promising next-generation optical materials for bioimaging applications. This paper presents an optical PQDs nanocomposite method to identify bacterial species associated with breast cancer, employing a LSTM deep learning model. The results indicate that the developed PQD-based nano-sensor offers impressive sensitivity, selectivity, and practical application. The four bacterial species identified in the study, Pseudomonas aeruginosa, Vibrio parvula, Acinetobacter baumannii, and Streptococcus vestibularis, were considered the most relevant indicators of breast cancer. With rapid detection, an intuitive design, and improved reliability, the PQD sensor could be an excellent breast cancer diagnostic tool for a point-of-care application. Furthermore, it has the potential to be integrated into healthcare systems, specifically in resource-limited settings, thereby improving the accessibility and efficiency of early breast cancer detection.

In the enzymatic toolbox of depollution, hydrolytic dehalogenases are of particular interest for the bioremediation of organohalogenated compounds. To better identify and characterize these enzymes, it is important to develop appropriate sensing methods. Fluorescent probes for dehalogenase detection have been developed in the past years, however, to this date none were available for application using the common FITC parameters (i.e. excitation laser at 488 nm). To address this limitation, we herein report a new fluorescent probe, COU4-Cl, excitable in the violet (405 nm) and blue (488 nm) wavelengths adapted for the detection and characterization of haloalkane dehalogenases. Its applicability is discussed and evaluated in comparison to the previously described COU2-Cl probe only excitable in the violet (405 nm). This study shows the advantages and complementarity of the two probes, and further demonstrate their application for the discrimination of dehalogenase activity in whole cell assays.

Integrating spatial metabolomics and spatial proteomics on the same tissue section remains challenging because matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and laser capture microdissection (LCM)-based proteomics impose different requirements on sample slides. Here, we developed and systematically evaluated a conductive indium tin oxide-coated polyethylene terephthalate (ITO-PET) slide that enables sequential MALDI-MSI and LCM-liquid chromatography-mass spectrometry (LCM-LC-MS) analysis of the same tissue section. Using mouse brain tissue as a model, ITO-PET provided MALDI-MSI performance closely comparable to conventional ITO-glass, including spectral concordance (Pearson correlation, R = 0.90), ion detection coverage, metabolite annotation, signal intensity distribution, and preservation of spatial molecular patterns. Following MALDI-MSI, the ITO-PET slide enabled cutting-mode LCM and yielded proteomic signal intensities and numbers of identified protein groups comparable to those obtained with conventional PEN-glass slides. Across different tissue sampling areas, proteomic signal intensity distributions, precursor ion counts, and protein group identifications remained broadly comparable before and after MALDI-MSI, with substantial overlap in identified protein groups. Similar patterns were observed in mouse kidney, lung, spleen, and liver tissues, further supporting the applicability of the workflow across different tissue types. By combining the electrical conductivity required for MALDI-MSI with the mechanical properties required for LCM cutting, the ITO-PET slide addresses a major material incompatibility between the two analytical modalities and enables sequential spatial metabolomic and proteomic analysis from the same tissue section. This workflow provides a practical analytical platform for obtaining complementary molecular information from spatially limited biological specimens.

To explore adapting qPCR systems for end-point nucleic acid quantification using dyes such as SYTO-9, we quantified serial dilutions of DNA and RNA standards in the range of 0.75 - 200 ng/{micro}l on 384-well qPCR devices. SYTO-9 fluorescence was successfully measured using standard SYBR Green settings. Blank-subtracted relative SYTO-9 signal showed a logarithmic dependence on DNA/RNA concentration (R2 > 0.95). Measurements were highly stable with different incubation times, temperatures of up to 95{degrees}C, and photobleaching. The described approach is a valuable QC option for high-throughput DNA/RNA isolations and could be adapted to additional fluorometric assays beyond nucleic acids.

High dietary fructose consumption is a major contributor to the development of obesity and related cardiometabolic diseases, highlighting the need for accurate assessment of fructose metabolism in humans. Stable isotope tracer approaches, such as 13C6-fructose, require highly sensitive and specific analytical methods to quantify both concentrations and isotopic enrichments. In this study, we developed and validated a robust gas chromatography-triple quadrupole mass spectrometry (GC-QQQ)-based method for the simultaneous measurement of unlabeled and 13C6-fructose in human plasma. The method employs oximation and per-acetate derivatization, and demonstrates high specificity and accuracy. Intra- and inter-assay precision were below 10%, with no detectable carry-over, and a lower limit of quantification (LLOQ) of 0.1 nmol/mL for concentration and 0.02 molar percent excess (MPE%) for enrichment and no interference from glucose. We further compared data acquisition using multiple reaction monitoring (MRM) and selected ion monitoring (SIM). MRM showed superior performance at the low concentrations and enrichment levels characteristic of clinical plasma samples, resulting in improved sensitivity and lower LLOQs compared to SIM. Overall, this validated method provides a sensitive and reliable approach for fructose tracer studies in humans. Its application will facilitate robust investigations into fructose metabolism, and its role in metabolic dysregulation and obesity-related disease.

Dried blood spot (DBS) sampling is becoming a popular alternative to traditional blood sampling approaches, offering advantages such as convenience of collection, transportation, and storage, as well as lower biohazard risk. N-glycosylation, a major post-translational modification of proteins associated with numerous biological and pathological functions, is one area of interest for DBS analysis. In this study, we utilize a protocol for N-glycosylation profiling of DBS by ultra-high-performance liquid chromatography based on hydrophilic interactions and fluorescence detection (HILIC-UHPLC-FLR). The protocol includes DBS cutting, protein extraction and enzymatic digestion, labeling with 2-aminobenzamide, followed by cleanup and HILIC-UHPLC-FLR measurement. We compare DBS with plasma and demonstrate the stability of DBS N-glycosylation profile when DBS are prepared from fresh blood, frozen whole blood, or a combination of separated frozen blood cells and corresponding frozen plasma. Additionally, we compared DBS N-glycans from pre- and diabetic subjects. Fucosylation, bisection, and galactosylation showed a statistically non-significant increasing trend in diabetes, whereas sialylation showed a statistically non-significant decreasing trend in diabetes. The main advantage of this method is the ability to repurpose samples, which were initially not intended for biomarker N-glycan analysis, such as frozen whole blood. Additionally, DBS N-glycan profiling is the easier, cheapest and the least invasive approach to conventional plasma in pre-diabetes and diabetes patients' diagnostics and monitoring.

mRNA vaccines constitute a promising new platform for infectious disease prevention, having demonstrated their efficacy in response to the COVID-19 pandemic. While mRNA attributes such as purity, integrity, 5'-capping, polyA tail length, and nucleobase lipidation are critical to vaccine efficacy, another key attribute of any vaccine mRNA is its translatability - that is, how much antigen protein is produced by ribosomal translation. To assess mRNA translatability, cell-free translation (CFT) can be employed. Advantages of CFT include its rapid readout (~5 hours), minimal sample consumption, and measurement of antigen translation directly from mRNA, thereby eliminating any variability associated with cell transfection efficiency. This is in contrast to cell-based methods, which require larger amounts of mRNA material and formulation in lipid nanoparticles or lipofectamine to facilitate cell transfection. When developing a CFT method to assay mRNA translatability, one key consideration is which CFT system to use as there are several commercially available systems from a variety of different organisms and cell types. Presented here is the evaluation of three eukaryotic CFT systems - wheat germ extract (WGE), rabbit reticulocyte lysate (RRL), and HeLa cell lysate (HCL) - for the purpose of developing an analytical method to assay the translatability of mRNA. The dynamic range, linear range, sensitivity to thermal stress, and sensitivity to potential impurities (e.g., EDTA, double-stranded RNA) were determined for each system. Although HCL translated less protein than either WGE or RRL systems, it showed several advantages, notably a larger linear range and greater sensitivity to mRNA thermal stress and dsRNA impurities. Therefore, while it is still worthwhile to screen different CFT systems, the results presented here suggest that HCL should be strongly considered when developing an analytical method to assay translatability for mRNA vaccines.

The binding affinities of a chimeric analog of a riboflavin derivative linked to biotin, (6- (7,8-dimethyl-2,4-dioxo-3,4-dihydrobenzo[g]pteridin-10(2H)-yl)hexyl 5-((3aS,4S,6aR)-2- oxohexahydro-1H-thieno[3,4-d]imidazol-4-yl)pentanoate), referred to as C6-Rf-biotin-tag, to the riboflavin binding retain or streptavidin are in the M range, 1.29 {+/-} 0.277 and 3.00 {+/-} 0.459, respectively. These values suggest that C6-Rf-biotin-tag has potential applications in diagnostic assay and labelling target flavin binding proteins. The C6-Rf-biotin-tag which was characterized with respect to physical and biochemical properties retains UV/Vis spectroscopic and fluorescence behavior similar to riboflavin.

Multimodal imaging workflows increasingly require multiple analytical techniques to be applied to the same tissue section to improve spatial co-registration and molecular interpretation. Polyethylene naphthalate (PEN) membrane substrates are attractive for this purpose because of their low thickness and compatibility with downstream modalities, but their use for matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI MSI) remains challenging due to low conductivity, reduced ion yield and susceptibility to laser-induced damage. In this study, MALDI MSI conditions for small-molecule analysis on PEN substrates were systematically optimised using bovine brain homogenate and mouse brain tissue using a TimsTOF flex MALDI-2 platform. Matrix selection, laser energy, pixel size (5 and 20 m), ionisation mode and PEN type were evaluated to identify acquisition conditions that balanced signal intensity with spectral quality and preservation of sample and membrane integrity. Among the matrices tested, 1,5-diaminonaphthalene (DAN) resulted in the best overall performance, providing higher ion intensities, less damage to the PEN substrates and a broader usable laser energy range than the other matrices tested. Different PEN substrate formats were also compared, showing distinct trade-offs between analytical performance and practical suitability for multimodal analysis. Under the tested conditions, glass-supported PEN (gPEN) provided the most practical overall compromise, while frame-supported PEN was not suitable for routine analysis on the instrument configuration used. Application of the optimised method to mouse brain tissue confirmed that spatially resolved metabolite imaging on PEN substrates is feasible and can support same-section multimodal workflows.

BACKGROUND: Circulating lipoprotein measures such as low-density lipoprotein (LDL) cholesterol and apolipoprotein B are causal biomarkers of cardiovascular risk. These can be quantified quickly and accurately by nuclear magnetic resonance (NMR) spectroscopy, but clinical translation has been slow. We investigated easy-to-operate and affordable benchtop NMR technology as a new means to quantify lipoprotein biomarkers in point-of-care settings. METHODS: Serum samples from 336 individuals were analysed with a benchtop NMR spectrometer operating at 80 MHz and a high-field NMR spectrometer operating at 600 MHz. Glucose, apolipoprotein A-I, apolipoprotein B, total triglycerides, total cholesterol, LDL cholesterol and high-density cholesterol were determined by standard biochemistry. Corresponding NMR-based measures were quantified by linear regression. The 80 MHz dataset included experiments with different scan settings to optimize measurement time (1,987 spectra in total). RESULTS: We identified 32 scans (2 min 8 s) as the minimum runtime for lipoprotein quantification. Total triglycerides and glucose were quantified with the highest accuracy (CV [≤]5.2%, R2 [≥]95%), while LDL cholesterol was more challenging (CV = 10.1%, R2 = 72%) and apolipoprotein B in between (CV = 7.4%, R2 = 74%). Epidemiological correlations between biochemistry assays and sex, obesity, glycemia and blood pressure were reproduced by the corresponding benchtop assays (P [≥]0.11 for difference). CONCLUSIONS: We developed a new lipoprotein quantification method and demonstrated its feasibility for standard lipoprotein analytics. The portability and cost-effectiveness of benchtop NMR make it an appealing choice for research and clinical settings where rapid and robust results on site are an advantage.

Central carbon metabolism coordinates energy production and carbon skeleton allocation across photosynthetic and heterotrophic organisms. Here, we established an optimized targeted metabolomics workflow for Chlamydomonas reinhardtii and Arabidopsis thaliana using a single-run HILIC-MS/MS assay with alternating positive and negative ionization. Our method provides robust multi-class coverage across 21 amino acids, 11 carboxylic acids, 4 sugars, 3 adenine nucleotides, 2 nucleotide sugars, 18 phosphorylated compounds in CCM, and Acetyl-CoA in a 20-minute run using both ESI modes. An optimal concentration of medronic acid with a BEH Amide column at high pH prevented metal adsorption, and low quantification limits (10 to 50 nM) for labile intermediates such as PEP, ATP and RUBP were achieved. Retention time variations remained below 1.3%, and over 90% of analytes showed high linearity (R2 > 0.990) across dynamic ranges spanning two to three orders of magnitude (typically 0.01-0.5 uM up to 15-20 uM). For sample preparation, glass-fiber filters (GF/C) outperformed nitrocellulose for harvesting C. reinhardtii. For A. thaliana, it was proved that no further grinding with micro pestle and extended cooling were necessary. A two-phase chloroform/methanol/water extraction was essential, as a single-phase extraction co-extracted green chlorophyll, which heavily suppressed phosphorylated signals. In Arabidopsis, glutamate, fumaric acid and citric acid were the dominant primary pools, indicating the importance of dilution and column washing for preventing carryover, and sensitive intermediates were reliably quantified at physiological levels. Together, this unified analytical and extraction strategy enables robust, artifact-free, high-throughput profiling of central metabolism in photosynthetic organisms.

Analytical technologies that can provide quick, precise, and continuous information regarding process performance are necessary for the development of biopharmaceutical manufacturing. Conventional bioprocess monitoring is largely dependent on laboratory-based data and offline sampling, which can restrict process management and cause delays in decision-making. This study develops a machine learning-enabled Raman spectroscopy framework for Process Analytical Technology (PAT) and Real-Time Release Testing (RTRT) applications in bioprocess manufacturing. Five predictive modeling techniques--Partial Least Squares (PLS) regression, Support Vector Regression (SVR), Random Forest, Extreme Gradient Boosting (XGBoost), and Neural Networks--were used to analyze Raman spectral data from an Escherichia coli fermentation dataset. The models were assessed using the coefficient of determination (R{superscript 2}), root mean square error (RMSE), and mean absolute error (MAE) to predict two crucial fermentation parameters: the concentrations of glucose and acetate. The superior performance of PLS regression for glucose prediction and the improved prediction accuracy of XGBoost for acetate concentration demonstrated the importance of selecting modeling techniques based on biological complexity. Explainable artificial intelligence using SHAP analysis was incorporated to improve model transparency by identifying Raman spectral regions contributing to predictions. The suggested architecture shows how Raman spectroscopy and machine learning can be combined to assist automated process monitoring, enhance process comprehension, and hasten the implementation of real-time quality judgments in next-generation biomanufacturing. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/740653v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@6a460aorg.highwire.dtl.DTLVardef@11c68e5org.highwire.dtl.DTLVardef@2acf7aorg.highwire.dtl.DTLVardef@9b890a_HPS_FORMAT_FIGEXP M_FIG C_FIG Overall workflow of the Raman spectroscopy-based machine learning framework for PAT and RTRT implementation. Raman spectra collected from E. coli fermentation were preprocessed and analyzed using multiple machine learning algorithms for the prediction of glucose and acetate concentrations. Model performance evaluation and SHAP-based explainable AI analysis enabled the identification of important spectral features for real-time bioprocess monitoring. HighlightsO_LIDeveloped a Raman spectroscopy-based machine learning framework for real-time monitoring of critical bioprocess parameters. C_LIO_LICompared traditional chemometric modeling (PLS regression) with advanced machine learning approaches, including SVR, Random Forest, XGBoost, and neural networks. C_LIO_LIShowed that the biochemical target affects the models performance, with XGBoost improving acetate prediction and PLS offering better glucose prediction. C_LIO_LIIntegrated explainable artificial intelligence to identify Raman spectral regions contributing to bioprocess predictions. C_LIO_LIEstablished a pathway toward interpretable Raman-based Process Analytical Technology (PAT) and Real-Time Release Testing (RTRT) implementation. C_LI

The formation of magnesium pyrophosphate (Mg2P2O7) in nucleic acid amplification and cell-free transcription systems has attracted considerable attention, since Mg2P2O7 serves as a reliable indicator of reaction efficiency. However, real-time monitoring of Mg2P2O7 remains challenging, relying largely on time-consuming analytical techniques or end-point detection methods. Here, we report a Mg2P2O7-driven co-aggregation mechanism involving glutathione-capped gold nanoclusters (GSH-AuNCs) that induces fluorescence enhancement, enabling real-time crystal formation monitoring. The mechanism was first investigated in simplified mixtures containing pyrophosphate (P2O74-) and magnesium (Mg2+) ions. Real-time fluorescence profiles revealed that the GSH-AuNCs/Mg2P2O7 co-aggregation can be correlated with crystal formation/growth/solubilization and solution turbidity, while distinct kinetic patterns can be indicative of the crystal size at the end of the reaction. As a next level of complexity, we examined the effects of common components in an enzymatic amplification reaction, i.e., dithiothreitol (DTT), ammonium sulfate ((NH4)2SO4), deoxynucleotides (dNTPs) and Bst polymerase, on Mg2P2O7 formation through real-time GSH-AuNCs fluorescence variations. Guided by the above results, we studied and selected the experimental parameters for the design of an optimized qualitative (end-point) or quantitative (real-time) genetic test. Finally, the loop-mediated isothermal amplification (LAMP) was used as a platform to demonstrate the quantification of Influenza A RNA within the range of 102-108 copies/reaction. The resulting one-tube, contamination-free assay was shown to have a response time of <25 min even in a crude saliva sample. Beyond diagnostics, this crystallization-activated fluorescence strategy may also support real-time investigation of Mg2P2O7 formation in other biotechnological processes, including in vitro transcription and Mg2P2O7-bioorganic composites synthesis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/744482v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@96dd88org.highwire.dtl.DTLVardef@aa122dorg.highwire.dtl.DTLVardef@18f4abforg.highwire.dtl.DTLVardef@745f1e_HPS_FORMAT_FIGEXP M_FIG C_FIG

Paper-based colorimetric sensors offer a low-cost and accessible platform for point-of-care (POC) analysis, but enzyme activity loss during coating and drying can weaken analytical signals and require high enzyme loadings or complex immobilization procedures. Although surfactants are widely used to improve wettability in paper-based assays, their potential contribution to colorimetric performance beyond these effects remains unclear. Here, we investigated surfactant-assisted colorimetric signal enhancement in a glucose assay implemented on a 96-puddle paper plate (96-PPP) and identified Tween 20 as the most effective surfactant. Its effect on detection performance became more pronounced as glucose oxidase (GOx) loading decreased; at 0.1 mg/mL GOx, Tween 20 lowered the limit of detection (LoD) from 0.113 to 0.034 mg/mL (approximately 3.3-fold) over a working range of 0-5 mg/mL, despite no statistically significant change in the measured contact angle at this loading. Tween 20 had no appreciable effect on the reaction in solution but preserved 95% of the apparent reaction rate constant after drying, compared with 11% without it, and atomic force microscopy (AFM) revealed a more dispersed dried enzyme morphology on mica. Tween 20-containing sensors also showed slower signal decay during repeated wetting-drying cycles and thermal stress, retained 77% (vs 26%) of the response at 400 mM NaCl, and exhibited within-PPP and between-batch coefficients of variation (CVs) below 10% (vs 12.3-19.5%), while maintaining glucose selectivity over potentially interfering molecules. These results indicate that Tween 20 enhances paper-based glucose sensing beyond wettability, in part by retaining enzyme cascade activity during drying, although the contributions of the individual enzymes and the underlying mechanism remain to be established.

ShortThe SwissProt database contains a stable 20,418 human protein-coding genes and 42,541 human protein sequences. Ribo-Seq suggests about 7,000 additional, non-canonical Open Reading Frames (ORFs) are present in humans, though only a few of them are confirmed by Mass Spectrometry (MS). Detecting these proteins requires extensive database searches, increasing computational load and inflating False Discovery Rates (FDR). Using the ionbot search engine with the OpenProt database allows for reliable detection of non-canonical proteins while controlling FDR. Ionbot surpasses the Trans-Proteomics Pipeline (TPP) in reproducibility, identifying more peptides and proteins supported by multiple spectra. In addition, open modification searches yield better PSMs compared to closed searches. This work highlights the importance of employing cutting-edge search engines in non-canonical protein research, as well as the value of open modification search in correcting errors in non-canonical protein detection. LongO_ST_ABSBackgroundC_ST_ABSThe SwissProt database reports a quite stable 20,418 human protein-coding genes and 42,541 human protein sequences, figures that have remained stable. New techniques like Ribo-Seq indicate that approximately 7,000 additional, non-canonical Open Reading Frames (ORFs) are translated in humans, few of which have been confirmed by Mass Spectrometry (MS). Detecting these non-canonical proteins requires comprehensive database searches, which increase computational load and False Discovery Rate (FDR). Here, we use the open search engine ionbot in combination with the OpenProt proteogenomics database to reproducibly detect non-canonical proteins while maintaining a well-controlled FDR. ResultsCompared to the current gold standard, the Trans-Proteomics Pipeline (TPP), ionbot shows higher reproducibility, with a higher number of peptides and proteins supported by multiple spectra, and across multiple samples. We observe that PSMs from the open modification search against OpenProt have higher fragment ion intensity correlation compared to PSMs obtained from the closed search, or by only searching canonical proteins. ConclusionsIn this work, we show the potential for open modification searching to correct potential mistakes in non-canonical proteins detection by preventing modified canonical peptides or variants from being incorrectly identified as non-canonical peptides. We also highlight the importance of assessing the FDR of non-canonical identifications separately from canonical ones, as global FDR calculations are biased by the scarcity of non-canonical identifications in each dataset.

Significance: Fluorescence imaging remains largely qualitative and device-specific, limiting reproducibility and intersystem comparisons. SI-traceable radiometric characterization requires calibrated sources suitable for transferring known radiance to imaging systems. Aim: Establish and evaluate a compact, calibrated solid-state radiometric emitter target (RET) for SI-traceable radiance transfer, and assess methods for evaluating radiance invariance, imager responsivity, and extension of radiance transfer to digitally defined regions of interest (ROIs). Approach: The radiance invariance of an LED-based RET was evaluated by measuring its radiance across varying source-to-aperture distances and collection apertures. A previously described radiance-transfer formalism based on calibrated source radiance and collection geometry was implemented to determine imager responsivity (R{lambda}), which was evaluated across varying working distances and lens apertures. Grubbs and MAD outlier tests and one-way ANOVA were used to assess radiance and responsivity invariance. Finally, responsivity obtained using digitally defined ROIs was compared with matched physical apertures to assess ROI-based radiance transfer. Results: The measured RET radiance remained invariant across the tested source-to-aperture distances and collection apertures, with no significant differences observed across distance (p = 0.88) or aperture (p = 0.15). Imager responsivity remained stable across working distances for both tested lens configurations (p = 0.48 and p > 0.99). Responsivity was also invariant across lens apertures, except for deviations at f/11 that were consistent with practical aperture tolerances. Digitally defined ROIs reproduced responsivity values obtained using matched physical apertures, demonstrating that the radiance-transfer approach can be extended to image-defined regions. Conclusions: The presented methods provide an approach for evaluating compact LED-based sources for invariant-radiance emission and suitability for SI-traceable radiance transfer. The characterized RET supported stable imager responsivity across changes in imaging geometry and extension to digitally defined ROIs. These methods can be adapted to other LED-based sources, with further angular characterization and uncertainty analysis needed to establish broader applicability.

Antimicrobial resistance (AMR) represents a major global health threat, with plasmid-borne mcr genes driving colistin resistance and exposing critical gaps in One-Health surveillance across human, animal, and environmental reservoirs. The most prevalent variant, mcr-1, remains difficult to monitor in resource-limited settings due to the lack of rapid, affordable, and field-deployable molecular tools. Here, we developed C12amcr, an integrated molecular toolbox that combines pre-amplification PCR with a fluorescent CRISPR-Cas12a assay targeting a conserved region of mcr-1 and a custom low-cost, hand-held 3D-printed portable fluorometer. Under optimized conditions, the assay achieved a limit of detection of 630 cells/mL. In poultry feces spiked with mcr-1-positive E. coli, C12amcr detected as few as 1,800 cells/mL. When tested on 22 community-derived E. coli isolates, the assay showed 100% concordance with both next-generation sequencing for mcr-1 detection and phenotypic colistin susceptibility testing by broth microdilution. The accompanying portable fluorometer performed equivalently to a laboratory microplate reader while enabling fully decentralized workflows compatible with portable PCR platforms. By integrating locally produced molecular reagents, straightforward protocols, and an accessible field-ready fluorescence reader, C12amcr overcomes key barriers to decentralized AMR surveillance and provides a practical, scalable solution for One-Health monitoring in resource-limited settings.

Antisense oligonucleotides (ASO) are nucleotide polymers that hybridize to sense strands and have been successful in treating a variety of diseases. A wide range of strategies have been investigated to optimize and develop ASO for clinical studies. A key objective for this study was to provide an overview of the range of detailed data that get be obtained and provide an updated method review on how to design surface plasmon resonance (SPR) kinetic experiments for DNA oligonucleotide hybridization studies that can also be applied to other ASO including peptide nucleic acids (PNA). We describe many lessons learned from published literature and provide a state-of-the-art strategy and methods for generating not only kinetic but also thermodynamic characterizations of oligonucleotide hybridization. In this study we have performed an SPR kinetic and thermodynamic analysis for the hybridization of HIF1 antisense DNA strands to its immobilized Intron2-Exon3 splice site sense DNA strand to provide insight, in general, on the optimal length and insight into optimal design of DNA ASOs. We provide a process on how to design experiments to: 1.) obtain oligonucleotide-length dependent kinetics, 2.) analyze reactions to obtain association and dissociation rate kinetics (ka, kd), assess if hybridization follows a 2-state model and to obtain kinetic dissociation constants (Kd), 3.) perform temperature-dependent hybridization kinetics to obtain thermodynamic values ({Delta}H{degrees}, {Delta}S{degrees} and {Delta}G{degrees}) that can give insight into the molecular interactions driving hybridization, 4.) compare experimental thermodynamic values to values derived from nearest-neighbor prediction models to identify atypical reactions and importantly 5.) enable calculations to predict oligomer hybridization affinity at the physiological 37 {degrees}C temperature to asses if the design of the oligomer will have the required cellular activity for a therapeutic effect. The strategy and results presented throughout the paper are compared to previous SPR reports and suggestions made to optimize kinetic studies.

The effect of microcurrents on facultative microbial pathogens remains controversial. Solid cultures in Sabouraud Glucose Agar of the ubiquitous mold Aspergillus fumigatus were repeatedly treated with a commercially available device performing wireless conductive microelectrostimulation by 3.5 A microcurrent routed by spraying negatively charged air particles onto solid cultures in modified petri dishes. The treated cultures displayed increased growth compared to standard ones, but only as a function of mycelial density and total surface; the radial growth rate of the mycelium remained unaltered. The increased growth was positively related to the duration of the treatment. At the same time, secondary development (new mycelial loci within the dish) was greatly upheld due to treatment, as the spraying created microairstreams dislocating the fungal spores. These results imply perplexed kinetics of mycelial growth both with and without treatment, since the folding of the mycelial mat is observed regularly. Both the fungus response to the ES and the possible revision of growth kinetics create prospects for biotechnological and bioremediation applications but also imply biomedical considerations, regarding infection dynamics of mycelial fungi and their in situ resistance to immune responses and treatment.