Talanta

Cystatin-C is an important renal function biomarker, and conventional quantification requires centralized laboratory analyzers, which limits timely testing in primary care and resource-limited settings. To address this need, we developed and validated a simple, rapid, and quantitative smartphone-based (SP) lateral flow immunoassay (LFIA) for measuring serum Cystatin-C. The SP-LFIA platform consists of a colorimetric LFIA strip and a custom SP reader with uniform LED illumination and macro lens for image capture. Quantitative image analysis of the colorimetric signal is performed by a dedicated application using a pre-defined third order polynomial calibration model. Following systematic optimization, the assay demonstrated a wide quantitative range of 0.32-8.00 mg/L, with a limit of detection of 0.15 mg/L. Analytical validation conducted according to CLSI guidelines showed excellent precision, with intra- and inter-assay coefficients of variation below 10%, and no significant interference from bilirubin, triglycerides, hemoglobin, or rheumatoid factor. Accelerated stability testing confirmed robust strip performance after storage at 50 {degrees}C for 28 days. Method comparison using 100 clinical serum samples showed high agreement with a commercial PETIA reference method (R{superscript 2} = 0.993) and minimal bias. These results indicate that the developed smartphone-based LFIA provides a reliable, cost-effective, and practical tool for point-of-care Cystatin-C monitoring.

Fluorescent capillary gel electrophoresis (CGE) with sodium dodecyl sulfate (CE-SDS) provides a powerful, high-sensitivity alternative to ultraviolet (UV)-based detection for characterizing therapeutic monoclonal antibodies (mAb). Regulatory and standards organizations, such as the United States Pharmacopeia (USP), include only UV based CE-SDS methods, hindering adoption, of alternative detection methods. There is growing opportunity to expand beyond exclusively UV-based CE-SDS methods. In this study, we present a full analytical validation of a light-emitting diode (LED) fluorescence-based parallel CE-SDS method for both non-reduced and reduced analysis of therapeutic antibodies. Using the NISTmAb reference material as a model system, size heterogeneity critical quality attributes (CQAs) including monomeric purity, percent glycosylation, and percent thioether were assessed. The fluorescence method demonstrated high specificity and precision with relative standard deviation (RSD) values <1% for monomeric purity and glycosylation, and <3% for thioether), as well as robust performance across variations in injection voltage, electrophoresis voltage, labeling temperature, and Labeling Buffer concentration. Ruggedness testing across users and reagent lots confirmed reproducibility, and accuracy assessments showed strong agreement with reported values from the National Institute of Standards (NIST) and traditional UV detection measurements. Linearity studies yielded coefficient of determination (R2) values >0.995 for both non-reduced and reduced analyses. These results highlight the high sensitivity, stable baseline performance, and suitability of LED fluorescence-based parallel CE-SDS as a validated, higher-throughput alternative to traditional UV-based methods for mAb quality control (QC).

Mimiviral polymerase X, mvPolX, is a repair polymerase that is involved in base excision repair (BER) and carries out the gap-filling function in double-stranded DNA (dsDNA). We demonstrate a sensitive and sequence-specific DNA detection method using this polymerase. mvPolX begins polymerizing DNA from the 3 end of a gap, displacing the downstream nucleotides without exonuclease activity. Our detection method is built on this activity of mvPolX. We designed a probe molecule consisting of a partial dsDNA with a 3 over-hang region complementary to the target DNA to be detected. The probe has a fluorophore-quencher (FAM-BHQ1) tag to facilitate detection upon strand removal. Binding of the probe to the complementary target forms a dsDNA with a single nucleotide gap in one strand. mvPolX binds this gap region and begins polymerisation eventually displacing the quencher strand leading to an increase in fluorescence. Proof-of-concept has been established using a synthetic 19 bp target DNA sequence. The method is specific and did not show any strand displacement when a single or double mismatched nucleotide at the 3 end of the target DNA was used. To demonstrate this molecular assay, we used M13 phage as our target. Asymmetric PCR (aPCR) was used to obtain single-stranded target DNA (158 bases) from M13 genomic DNA, which was directly used in the assay as target. The combination of aPCR and mvPolX assay can detect as low as 10 copies of genomic DNA. The enzymatic reaction is fast, requiring only 15 min of incubation with mvPolX at 30 {degrees}C. We have further demonstrated the efficiency of the assay in presence of multiple non-target DNA by detecting the target DNA from M13 phage spiked lakewater samples.

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.

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.

Dengue disease exhibits diverse clinical manifestations in patients when infected by its different serotypes. Early and accurate detection of dengue virus (DENV) infections, particularly distinguishing between serotypes is crucial for effective patient management and sporadic outbreak control. Surface-Enhanced Raman Spectroscopy (SERS) offers advantages of high sensitivity, rapid acquisition, rapid analysis, minimal sample and preparation requirements. In this study, we present a simple and reproducible approach for serotype-specific detection of non-structural protein 1 (NS1) utilizing SERS on an aluminium based substrate. Leveraging specific vibrational signatures of NS1 protein from DENV serotypes, we demonstrated the potential of SERS to discriminate between NS1 proteins across DENV serotypes and also the amino acid residue variations that exist among them from different biological samples. Study demonstrates the SERS based detection of NS1 in the current in-vitro setting has sensitivity and specificity comparable to ELISA assays with limit of detection (LOD) reaching to 1ng/mL. However, the application of nanomaterials-based SERS substrate has potential to further enhance the LOD enabling detection even at lower concentrations. This approach holds promise for advancing our capacity to rapidly diagnose serotypic DENV infection in samples, studying pathogenesis and improving strategies for disease management and control.

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 [&le;]5.2%, R2 [&ge;]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 [&ge;]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.

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

Luminescence is a powerful method for detecting trace analytes and monitoring biological processes. However, most bioluminescence reagents, including luciferase and its substrates, are sensitive to temperature, limiting their useable shelf lives, and resulting in inconsistent performance. Enhancing the stability of these reagents could improve data quality, simplify workflows, and address cold chain storage issues. In this study, we demonstrate the application of the platform stabilization technology, capillary-assisted vitrification (CAV), as a tool to stabilize different luciferases and their substrates, and the application of the stabilized reagents in both in vitro and in vivo bioluminescent assays. We demonstrate that CAV-stabilized reagents can be stored and shipped ambiently, maintain consistent performance over time, and are suitable for use in cell viability quantification, tumor monitoring, in vivo imaging, microbial detection, and immunoassays. Additionally, different reagents can be co-formulated to make ready-to-use assay kits that can also be shipped and stored ambiently. Our results demonstrate that CAV stabilization is a viable alternative to traditional storage methods, with broad potential to improve bioluminescence workflows.

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.

Streptavidin-biotin, avidin-biotin interactions are classical models for protein-ligand binding, yet the energetic changes accompanying biotin binding remain poorly resolved. Using fluorescent dyes as energy sensors, we show that biotin binding produces two distinct regimes occurring in parallel as concentration of biotin increases cooperativity and conformational rearrangements, wherein cooperativity is observed via exchange broadening of fluorescence linewidth and conformational rearrangements exclusively observed in emission energy. Where the first biotin binding creates the highest contribution to the emission energy. Further analysis of tetramer-tetramer only interactions revealed extremely long ranged intermolecular interactions extending to hundreds of nm. The intermolecular interactions become negligible only at concentrations of approximately 10 nM for both streptavidin and avidin. Affinity values estimated for these diluted samples were below 1 nM.

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.

It was recently reported that Methylobacterium extorquens AM1 produces the citrate-hydroxamate siderophore N-deoxyschizokinen A, identified by LC-HRMS. Multiple properties were inconsistent with the assignment: the feature eluted far later than the other schizokinen derivatives (17 min versus 6-8 min), a reversed-phase shift larger than a single-hydroxyl difference in a molecule can explain, further its accurate mass deviated from the calculated one by 28 ppm, well outside the error on the co-analyzed standards and its diagnostic m/z 105 and 77 fragments suggest a molecule with an aromatic moiety. A replicate comparison of identical samples in plastic versus glass autosampler vials was decisive: the m/z 387 feature was reproducibly present with plastic vials and absent with glass. We therefore conclude that the reported detection of N-deoxyschizokinen A in M. extorquens AM1 is an artifact, and recommend glass-vial and solvent-blank controls, an explicit accurate-mass threshold, and narrow MS/MS isolation when assigning trace siderophore-like features from complex extracts.

Capillary electrophoresis-mass spectrometry (CE-MS) offers unique analytical advantages for polar metabolite profiling but has remained underutilized in metabolomics relative to liquid chromatography-MS (LC-MS), in part due to challenges in managing migration time drift during data analysis. Here we introduce the use of indexed migration time (iMT) for easily managing this aspect of CE-MS data for metabolomics. Migration time indexing using a panel of stable isotope-labeled (SIL) amino acid reference standards, stored as an iRT database in Skyline, outperformed both uncorrected migration time and relative migration time (RMT) correction across three independent analytical batches spanning 90 samples from four biological matrices. The indexed migration time approach achieved sub-1% relative standard deviation (RSD) in migration index across batches, compared to up to [~]15% RSD for uncorrected migration times. Additionally, we evaluate the use of single-point external calibration in Skyline for the purposes of metabolite quantification from complex matrices in order to ease the burden of translational metabolite quantification from metabolomics using high-resolution mass spectrometry (HRMS). Single-point external calibration using a biological matrix-based calibrator was benchmarked against a 13-point linear calibration curve across a panel of amino acids; above 1 M, greater than 95% of back-calculated concentrations fell within {+/-}20% of multi-point calibration. Application of the complete workflow to plasma, serum, urine, and NIST Standard Reference Material (SRM)-1950 demonstrated low inter-batch variability by principal components analysis, broad metabolite coverage across 126 quantifiable analytes, and strong quantitative concordance (Deming slope = 0.862, pseudo-R2 = 0.994, n = 64 analytes) with an independent comprehensive reference dataset for NIST SRM-1950. Together, these results establish a practical mCE-HRMS metabolomics workflow that bridges targeted and discovery metabolomics paradigms and lays the groundwork for single-point external calibration as a powerful tool for translational metabolomics.

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.

Accurate and decentralized quantification of serotonin, also known as 5-hydroxytryptamine (5-HT), in biological fluids is critically important for the diagnosis, prognosis, and therapeutic monitoring of neurological and psychiatric disorders. However, conventional analytical methods generally rely on centralized laboratory infrastructure, skilled personnel, and labor-intensive sample processing, which restrict their applicability in rapid near-patient and point-of-care settings. Herein, we report a portable molecularly imprinted polymer (MIP)-based electrochemical sensing platform for selective and on-site detection of serotonin using screen-printed carbon electrodes (SPCEs). The biomimetic recognition interface was fabricated through direct electropolymerization of a polydopamine recognition layer in the presence of serotonin as the template molecule, followed by template extraction to generate complementary recognition cavities for selective rebinding. The sensor fabrication parameters, including monomer concentration, electropolymerization cycles, template-to-monomer stoichiometry, and electrolyte pH, were systematically optimized to achieve improved sensitivity, selectivity, and signal stability. Under optimized conditions, the MIP/SPCE sensor exhibited a broad linear response from 10 pM -10 uM in phosphate buffer, with a correlation coefficient of R2 = 0.974 and an ultralow limit of detection of 0.16 pM. The analytical applicability of the platform was further validated in spiked artificial serum, where the sensor achieved an LOD of 0.12 pM, satisfactory recovery values of 88.66-96.02%, and acceptable precision with RSD values [&le;] 8.43% (n=3), confirming its reliability in a complex biological matrix. The developed sensor demonstrated excellent selectivity toward serotonin against physiologically relevant interferents, maintaining signal retention between 99% and 101%. In addition, the platform showed high operational repeatability with an RSD of 0.45%, good inter-electrode reproducibility with an RSD of 6.3%, and long-term storage stability, retaining 90-110% of its initial response over 28 days. Importantly, cross-platform validation using a smartphone-coupled potentiostat demonstrated strong analytical agreement with laboratory-grade instrumentation, as evidenced by R2 = 0.9967 and a slope of 1.023. These findings establish the proposed MIP/SPCE platform as a simple, low-cost, portable, and smartphone-compatible electrochemical device for field-deployable serotonin monitoring in clinically relevant samples.