Parylenes are a family of polymers derived from poly(p-xylylene). The most commonly used member of this family is parylene C, which contains one chlorine substituent per monomer unit. It is used as a passivation layer in bioanalytical devices, among other applications. However, parylene C is chemically inert. This limits its use in bioanalytical applications and other fields that require chemical functionalization of the surface. Therefore, various methods have been developed to functionalize parylene C surfaces. Other approaches have aimed to develop parylenes with other moieties that are easier to functionalize. Depending on their functional group, parylenes have different characteristics, fields of application, and adjustment possibilities. In this work, four groups of parylenes are discussed: (1) parylene C and parylene N (poly(p-xylylene)) as the most common representatives of this polymer family, (2) heat-resistant parylenes, which include fluorinated parylenes, (3) parylenes with functional groups for protein coupling, such as amino groups and formyl groups, and (4) parylenes with moieties for click chemistry, allowing for a wide variety of functionalization and application. Applications include cell culture, biosensors, immunoassays, and enzyme assays, among others. A comparison of the performance of the respective parylenes is made, if possible, with regard to a specific analytical task. Though many tasks have been accomplished with available parylenes, limitations regarding functional groups, including the ability to undergo functionalization, still exist. This paves the way for new parylenes or new methods of surface modification that have not yet been widely adopted and are ready to be investigated.
Invasive pulmonary mucormycosis caused by Rhizopus microsporus is often fatal, yet analytical tools to monitor fungal burden and host responses in vivo remain limited. We developed a multimodal infection metallomics workflow combining ⁶⁸Ga-desferrioxamine B PET/CT, high-resolution MALDI mass spectrometry imaging (MALDI-MSI), and targeted LC-MS to map fungal siderophore production and host tissue remodeling in a neutropenic rat model and in human samples. ⁶⁸Ga-desferrioxamine B was rapidly taken up by R. microsporus in vitro and accumulated in infected lungs in vivo. MALDI-MSI visualized rhizoferrin (m/z 435.1259, [M-H]⁻) and homorhizoferrin (m/z 449.1420, [M-H]⁻) confined to hyphal foci and absent from control lungs, whereas heme b was depleted and spatially segregated. Neutrophil α-defensins (RatNP-2/3/4) increased 14-60-fold and formed halos around lesions, showing an inverse trend with siderophore abundance. Lipid MSI revealed remodeling of anionic surfactant lipids, with depletion of short-chain phosphatidylglycerols and phosphatidic acid-derived species and accumulation of long-chain polyunsaturated phosphatidylglycerols and phosphatidylinositols in infected regions. Targeted LC-MS of serial urine showed that rhizoferrin and homorhizoferrin emerged by day 2, peaked on day 4 (37.2 and 15.0 µg/mL), and declined with immune reconstitution; rhizoferrin was also detected in bronchoalveolar lavage from a patient with mucormycosis. Analytically, the workflow links radiotracer uptake, high-mass-accuracy spatial ion mapping of peptides with lipids, and matrix-matched urinary LC-MS quantitation within the same infection model. This integrated platform enables spatially resolved mechanistic readouts and supports non-invasive metallophore-based diagnostics of invasive mucormycosis.
Lipidomics, as a crucial branch of metabolomics, is dedicated to systematically analyzing the composition, structure, function, and dynamic changes of lipids in organisms, playing a pivotal role in elucidating disease mechanisms and discovering biomarkers. Conventional lipidomics methods based on liquid chromatography-mass spectrometry (LC-MS) require tissue homogenization, which obscures the spatial distribution of lipids and precludes the analysis of their heterogeneity within complex tissue microenvironments. In recent years, the development of spatial omics technologies such as mass spectrometry imaging (MSI) and laser capture microdissection (LCM) has provided powerful tools for the in situ and visual investigation of lipid spatial distribution. This paper systematically reviews the main analytical strategies in lipidomics, focusing on the technical principles, advances, and recent applications of spatial multi-omics integration. It further discusses the challenges faced by spatial lipidomics in terms of quantitative accuracy, isomer identification, and spatial localization precision, and provides an outlook on future technological developments. Spatial lipidomics breaks through the bottleneck of losing spatial information in traditional methods, and opens up a new path for further exploration of disease mechanisms and the discovery of new biomarkers in the spatial dimension.
p-Benzoquinone (PBQ), as a key toxic derivative of benzene, is widely present in industrial wastewater and the production and manufacturing of daily chemicals. Long-term exposure poses a serious health threat, making the development of rapid and sensitive on-site detection technologies highly significant. Electrochemical methods, due to their simple operation, high sensitivity, and ease of miniaturization, are an ideal approach for detecting PBQ. Co-MOF-74 is extensively used in the electrochemical field because of its structural stability, tunable metal nodes, and large surface area, but its low conductivity limits further applications. In this study, Co-MOF-74 was rapidly synthesized using dielectric barrier discharge (DBD) microplasma technology, and then the large π-conjugated organic ligand HATP was introduced for ligand engineering to successfully prepare Co-MOF-74-HATP. This synthesis strategy is not only efficient, but also the introduction of HATP effectively regulates the material's electronic structure, significantly enhancing its conductivity and electrocatalytic activity. The electrochemical sensor employs chronoamperometric detection at -0.15 V (vs. Ag/AgCl) and exhibits excellent performance for PBQ, featuring two wide linear ranges (17-1602 µM and 1602-5602 µM) with corresponding sensitivities of 1440 µA·mM-1·cm-2 and 497.8 µA·mM-1·cm-2, a low limit of detection (LOD) of 3.43 µM (S/N = 3), and good reproducibility (RSD < 3.0%). It was successfully applied to the detection of PBQ in actual water samples with recoveries ranging from 90.5% to 102.32%. This work expands the synthesis of ligand-functionalized MOFs through DBD microplasma technology and applies them to the electrochemical detection of PBQ in water samples.
This study introduces the first reported stepwise fluorimetric strategy for the sensitive and rapid determination of the ultra-short-acting β₁-blocker, landiolol hydrochloride. Initially, an environmentally benign method was developed by exploiting the drug's native fluorescence in water (λex/λem = 217/298 nm). While this cost-effective approach successfully utilized water as a green solvent, it demonstrated limited LOD of 32.57 ng/mL. To enhance fluorescence performance, various organic solvents were investigated, with acetonitrile providing the highest signal at λex/λem = 222/300 nm and improving the LOD to 16.31 ng/mL. To enable ultra-trace clinical monitoring, a third "turn-on" method was developed using silver nanoparticles (AgNPs). By measuring fluorescence enhancement at λex/λem = 260/524.6 nm upon interaction with landiolol, this platform amplifies the signal, achieving an outstanding LOD of 3.10 ng/mL. AgNPs were prepared using a green synthesis approach employing Aloe vera extract as a natural reducing and stabilizing agent in an aqueous medium avoiding using hazardous chemicals. Water was used throughout both nanoparticle preparation and the AgNP-enhanced determination, reinforcing the eco-friendly profile of the method. Unlike native fluorescence, the AgNP-assisted method enhances sensitivity through nanoparticle-mediated surface passivation, with a possible auxiliary contribution from resonance energy transfer (RET)-like processes. Selectivity is improved through preferential adsorption of landiolol on the AgNP surface and a large Stokes shift that minimizes interference from UV-absorbing matrix components. The resulting enhanced sensitivity and reduced matrix interference make this method a powerful tool for ultra-trace, selective, and sustainable determination of landiolol in pharmaceutical formulations and human plasma, demonstrating its suitability for routine quality control and bioanalytical applications.
Almonds and hazelnuts are widely consumed tree nuts; nevertheless, they are recognized by the U.S. Food and Drug Administration (FDA) and regulatory agencies in other countries as potential allergens requiring clear labeling on foods. While detecting these allergens during food production is essential, protein-based assays currently used to identify cross contact during food manufacturing often have variable results due to food processing effects, matrix interference, or antibody specificity. To address these challenges, the National Institute of Standards and Technology (NIST) Reference Materials (RMs) 8404 Almond Nut Flour for Allergen Detection and 8405 Hazelnut Flour for Allergen Detection were developed to harmonize detection methods. In this work, Dumas total protein assay and liquid chromatography-tandem mass spectrometry (LC-MS/MS) were used to characterize the protein composition of the NIST RMs along with other sources of nut flours. The RMs were next evaluated using commercial enzyme-linked immunosorbent assays (ELISAs) to assess their utility in standardizing the detection and quantification of total protein from almond and hazelnut flours. From these experiments, flours processed with different manufacturing methods were found to have similar recoveries for each ELISA only when quantifying total protein rather than total nut mass. Additionally, NIST RMs 8404 and 8405 were used to improve the reproducibility of protein recovery across commercial almond and hazelnut ELISA kits. These findings provide a framework for reporting ELISA results and using RMs to facilitate more reliable and standardized allergen risk management.
Alternative matrices are increasingly used in postmortem toxicology when conventional specimens such as femoral blood are unavailable. However, quantitative multi-matrix methods covering a wide range of tissues remain limited. This study describes the development and fit-for-purpose validation of a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for quantification of 20 forensically relevant drugs in human and porcine postmortem matrices. Analytes and internal standards were extracted by methanol-based protein precipitation, followed by reversed-phase chromatography gradient separation and quantitation using a linear ion trap consisting of a quadrupole mass filter. A solvent calibration curve was used to analyze all matrices in a single analytical run. Validation was performed according to a modified fit-for-purpose approach focusing on accuracy, precision, selectivity, carry-over, matrix effect, dilution feasibility, and stability. Acceptance criteria were fulfilled for 89.3% of analyte-matrix combinations under standard criteria and 96.7% after predefined fit-for-purpose adjustments. Porcine matrices showed analytical performance comparable to human tissues, supporting their use as surrogate matrices for method development and validation. The developed LC-MS/MS method enables quantification of drugs across a broad range of alternative postmortem matrices using a single extraction and calibration approach. The method is intended for fast, reliable, and resource-efficient multi-matrix studies rather than absolute quantification in individual matrices and provides a practical tool for the investigation of postmortem redistribution processes.
Originally developed for small molecules in the late 1970s and early 1980s, isotope dilution mass spectrometry (IDMS) also has become the "go to" method of quantification for those wishing to characterize the mass fraction or amount of substance content of proteins in matrix-based certified reference materials (CRMs). While instrumental factors can impact the accuracy of IDMS methods, the use of double IDMS, higher order approaches, and "exact matching" have done a lot to improve the accuracy of the results. This review shows the development of IDMS for the quantification of proteins from being a method only used for value assignment of primary calibrators using isotope-labelled peptides as internal standards to a method for quantification of proteins in complex biological matrices such as serum and blood using isotope-labelled recombinant intact proteins as internal standards. It will discuss the challenges and limitations of currently used organic IDMS peptide-based approaches regarding the definition of the measurands, equilibration of sample and internal standard, digestion efficiency, and stability and suitability of the internal standards. This paper reviews the steps taken to assess the accuracy of the peptide- and protein-based IDMS methods used for the characterization of CRMs and the requirement to ensure comparability in laboratory diagnostics down to the patient level. Furthermore, it will give an outlook on future challenges, such as including structural and protein activity information in the results.
Protein glycosylation is a major post-translational modification that regulates tumor initiation and progression; however, its dynamic modeling during multistep evolution of lung adenocarcinoma (LUAD) remains poorly understood, particularly in clinically archived tissues. Here, we established an integrated multi-omics workflow combining global proteomes, N-glycans, and site-specific intact N-glycopeptides to comprehensively characterize glycosylation in formalin-fixed paraffin-embedded (FFPE) specimens spanning four pathological stages of LUAD progression: inflammatory nodules (IN), atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), and invasive adenocarcinoma (IAC). Using optimized protein extraction, hydrophilic interaction liquid chromatography (HILIC)-based glycopeptide enrichment, and high-resolution LC-MS/MS, we achieved large-scale identification of proteins, N-glycans, and intact glycopeptides from archival clinical samples. Integrated analyses revealed progressive remodeling of site-specific N-glycosylation during malignant transformation, characterized by increased glycan branching, fucosylation, and sialylation during the transition from premalignant lesions to invasive cancer. Sialylated glycans reached their highest abundance in the premalignant AAH stage, whereas highly branched and fucosylated complex N-glycans predominated in invasive adenocarcinoma, indicating stage-dependent glycan remodeling throughout disease progression. Functional enrichment analyses linked these glycosylation alterations to extracellular matrix organization, neutrophil degranulation, and immune-associated pathways, while representative glycoproteins, including CEACAM6 and FGB, exhibited coordinated changes in protein abundance and site-specific glycoform micro-heterogeneity across pathological stages. Collectively, this study demonstrates the feasibility of deep glycoproteomic profiling using archived FFPE tissues and provides a comprehensive molecular atlas of glycosylation remodeling during LUAD progression. These findings establish a valuable resource for elucidating disease mechanisms and identifying stage-specific glycosylation biomarkers and potential glycan-targeted therapeutic candidates for early lung adenocarcinoma.
Currently, several SERS methodologies are focused on quantitative goals, and, as they move toward becoming a suitable analytical alternative, their main drawback remains the low reproducibility of SERS signals. As a result, strategies to circumvent this are highly desirable, but given the number of experimental variables that affect reproducibility, the task can sometimes be endless. Here, we selected a series of C5-substituted uracil derivatives (5-fluoro-, 5-chloro-, and 5-bromouracil) adsorbed on silver nanoparticles. These compounds are of analytical and pharmacological interest due to their role as biomarkers, pharmaceuticals, or environmental pollutants. They are expected to be found at very low levels in bioanalytical matrices; thus, to reach low limits of detection, they were paired with adenine, which has a well-known high affinity for silver nanoparticles. Considering the complexity of these pairs and the experimental variables that affect SERS reproducibility, a two-stage strategy was adopted to select the best experimental conditions and minimize the standard deviation (STD) of the signals from the three base pairs. This included a variable screening procedure followed by an optimization stage. After optimization, the STD values decreased by 100-, 300-, and 1000-fold for 5-fluorouracil, 5-bromo, and 5-chlorouracil, respectively. The validation experiments yielded STD values at the same order of magnitude as those achieved under the optimized conditions, indicating that our approach can be applied to improve signal reproducibility. In perspective, this strategy can be easily adapted to other SERS-based systems, especially for analytical purposes.
Steroid hormones play crucial regulatory roles in human growth, development, reproduction, and the maintenance of internal environmental homeostasis. Because the concentrations of most hormones in the body are extremely low and their chemical properties vary widely, developing an accurate and sensitive quantitative method has become a primary objective in clinical diagnostics. In this study, an isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS) method was developed and validated for the simultaneous quantification of 22 steroid hormones in human serum. To enhance extraction and purification efficiency, a protein precipitation-solid-phase extraction (PP-SPE) approach was employed, forming a "dual purification" strategy. The limits of quantification for progesterone, cortisol, dihydrotestosterone, and dehydroepiandrosterone sulfate were 0.05, 0.50, 0.05, and 1.00 ng/mL, respectively, representing an improvement over previously reported values obtained using similar sample pretreatment methods. Method validation results demonstrated strong linearity for all 22 steroid hormones (R2 > 0.98). Accuracy ranged from 86.9% to 119.5%, intra-day precision was below 9.7%, inter-day precision was below 12.0%, and the matrix effect was controlled within 80.3%-118.1%. These findings indicate that the method is accurate, reliable, and suitable for analyzing multiple components in complex serum matrices. Twenty real serum samples were analyzed to evaluate the clinical applicability of the method. The results demonstrated that this method can be used clinically to monitor steroid hormone levels, assist in diagnosing and treating endocrine disorders, and provide a diagnostic basis for adrenal diseases. It holds significant reference value for clinical laboratory testing.
Amino acid metabolism disorders have strong links to various kidney diseases, and the kidney is essential for maintaining systemic amino acid homeostasis. Given the lack of obvious clinical symptoms in the early stages of kidney disease, searching for reliable metabolic biomarkers is essential for early diagnosis. Endogenous AAs are widely present in human biological matrices, making it difficult to obtain analyte-free blank matrices for method validation. This poses challenges in the preparation of calibration standards, leading to uncertainty and reduced consistency in the results. This study aimed to develop a rapid hydrophilic interaction liquid chromatographic method coupled with tandem mass spectrometry. It could analyze 47 amino acids and related compounds, present in various biological matrices (human plasma, urine, and cyst fluids). The calibration curves were constructed by stripping each matrix to obtain a surrogate matrix. The slopes of the different calibration curves were systematically evaluated and the analytical results were compared with results obtained through the method of standard addition. The calibration curves established using both the standard addition method and the matrix stripping method were parallel, hence matrix stripping effectively mitigates matrix effects under a variety of matrix conditions, thereby assuring the accuracy and reliability of quantitative analysis results. To further investigate the applicability of this method to large-scale sample analysis, the analysis of plasma samples and urine samples obtained from patients with two types of kidney disease was performed.
In 2024, the US Centers for Disease Control and Prevention (CDC) and National Institute of Standards and Technology (NIST) initiated an interagency collaboration to bolster preparedness in the event of a pandemic scenario due to high pathogenicity avian influenza A(H5N1) clade 2.3.4.4b viruses that had been circulating in North America since 2021. Multiple spillover events into mammalian species, including an outbreak among dairy cattle and a surge in human cases, spurred the development of RNA reference materials to assist with new diagnostics development and validation. With input from CDC on sequences, NIST generated three synthetic RNA materials of A(H5N1) hemagglutinin, neuraminidase, and matrix proteins 1 and 2 gene segments. Here, we describe the development and characterization of these reference materials utilizing droplet digital reverse transcription polymerase chain reaction. Through this collaboration, we were able to rapidly provide quantified, homogeneous, stable, and epidemiologically relevant RNA reference materials to the public to aid new assay development and validation.
Direct analysis of raw matrices by Direct Analysis in Real Time mass spectrometry (DART-MS) remains limited by logistical and operational challenges, including complex handling and positioning, risks of sample degradation, and contamination of the analytical instrument. The Permeably Enclosed Raw Matrices (PERM) approach, introduced here, provides a standardized and instrument-safe strategy in which samples are confined within a semipermeable enclosure, enabling practical and reproducible analysis while preventing particulate release and moderating thermal exposure. The method was evaluated using six chemically and physically diverse matrices of forensic, toxicological, and food relevance: seized tablets, seized powders, roasted coffee, human hair, plant material, and spiked whole human blood. Across all samples, PERM-DART-HRMS delivered S/N ratios spanning four orders of magnitude (4-44 k). The approach enabled the identification of both major and low-abundance constituents - including MDMA, MDA, diazepam, lorazepam, 3-MMC, 25I-NBOMe, N-MEC, caffeine, endogenous lipids such as cholesterol, and sesquiterpenes such as dehydrocostus lactone - without extraction, solubilization, or chromatographic separation. Comparative analysis against conventional DART-HRMS workflows demonstrated effective prevention of instrumental contamination and markedly improved operational reliability and efficiency. Altogether, PERM-DART-MS provides a unified, preparation-free platform for rapid chemical screening, offering a practical and reliable alternative for multidisciplinary applications in forensic, toxicological, and food science contexts.
In gas measurements, there is inherent competition between sensors and analytical systems, often made difficult by a lack of understanding of approaches and constraints from both sides. This leads to controversies, sometimes simple to avoid or defuse, but sometimes leading to harsh discussions and resentment of "wrong" concepts from the respective other side. Meanwhile, collaboration between disciplines is often a key to scientific and, in the long term, economic and societal success. This is especially true today, when digitization is the pervasive topic in our society and where "sensors act as a bridge between biology and digitization." This article addresses this conflict for the field of high-performance gas measurement systems, where the two worlds of low-cost sensor systems on the one hand and high-performance analytical instruments on the other are still often at odds.
Mescaline and lysergic acid diethylamide (LSD) are strong psychedelics that significantly compromise social safety and public health. Satisfying the rapid detection requirements for public security drug enforcement is challenging because of the high costs and long durations associated with gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). To address these challenges, this study established an immunochromatographic method for the simultaneous detection of mescaline and LSD in hair based on time-resolved fluorescent microspheres. By optimizing key parameters such as the type and pH of the activation buffer, the pH of the labeling buffer, the concentrations of the detection lines (T1/T2) and the control line (C line), and the antibody labeling amount, under optimal conditions, the detection limits of this method for mescaline and LSD were 16.5 pg/mg and 12.5 pg/mg, respectively. The recovery rate ranged from 94.98 to 109.83%, and the coefficient of variation ranged from 2.24 to 8.48%, indicating excellent sensitivity, specificity, and accuracy. The detection results of real samples were essentially consistent with those of LC-MS/MS. Consequently, this method allows preliminary testing of hair samples in forensic labs, providing an efficient, reliable prescreening tool before LC-MS/MS confirmation.
Retinol-binding protein 4 (RBP4) is a key transporter of all-trans-retinol (vitamin A), circulating in blood as either holo-RBP4 (retinol-bound) or apo-RBP4 (retinol-free). Dysregulated RBP4 levels, particularly an imbalance between apo- and holo-RBP4, have been implicated in a range of metabolic and cardiovascular diseases. Current detection methods such as ELISA and Western blot lack the specificity to distinguish these two forms. Here, we present an aptamer-based biosensing strategy that overcomes this limitation by using selected single aptamer sequences for the precise and selective quantification of apo- and holo-RBP4 on graphene field-effect transistor (gFET) sensors. The specific contribution to this study is the identification of individual apo- and holo-RBP4-binding aptamers from previously enriched polyclonal libraries, their computational evaluation by molecular docking and molecular dynamics simulations, as well as their implementation as isoform-selective recognition elements on gFET sensors. The polyclonal aptamer libraries previously were generated using FluMag-SELEX (FluMag- Systematic Evolution of Ligands by Exponential Enrichment) that are specific to each RBP4 conformer. Next-generation sequencing and bioinformatic enrichment analyses identified two highly specific and high-affinity aptamers, which were further characterized via computational modelling, including molecular docking and molecular dynamics simulations. This structural approach elucidated the conformer-specific binding mechanisms, demonstrating aptamers' capacity to differentiate subtle protein conformational changes. The selected aptamers were immobilized on gFET devices, enabling label-free, real-time detection with picomolar sensitivity-a 100-fold improvement over the original libraries. Increased aptamer density on the sensor surface further enhanced signal sensitivity by an order of magnitude. These findings validate the use of aptamers as high-performance biorecognition elements in biosensors, offering a path toward precise RBP4 isoform monitoring.
Cannabis legalization has created regulated markets requiring residual pesticide testing to protect public health. Regulatory programs establish action limits governing product release and enforcement, necessitating accurate quantification in analytically challenging matrices. Compliance is further complicated by the need to quantify dozens of compounds with widely varying physicochemical properties, often requiring multiple assays per product. Validated multiplex methods in representative matrices are therefore critical for defensible quantification at regulatory thresholds. We developed and validated a multiplex liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous quantification of 64 pesticides in cannabis-derived hemp oil, employing external calibration with 58 stable isotope-labeled internal standards (SIL-IS) and 4 surrogate internal standards (IS) across 8.4 units of LogP. Validation followed Clinical & Laboratory Standards Institute (CLSI) guidelines (C62-A, EP05-A3, EP29-A) and Food and Drug Administration (FDA) guidance. All 64 pesticides demonstrated linear calibration (R2 ≥ 0.995), with accuracy of 80.0-120.0% (mean recovery = 101.9%) and precision of ≤ 15% coefficient of variation (%CV, mean %CV = 2.7%). Analytical measurement ranges extended to 20,000 parts per billion (ppb) for 62 components. Expanded measurement uncertainty ranged from ±2.3% to ±14.6% and remained ≤15% at 100 ppb for 57 of 64 pesticides. Systematic benchmarking of surrogate IS suitability across all analyte-IS pairings showed that performance correlated with chromatographic and physicochemical similarity, enabling identification of optimal surrogates and analytes requiring matched SIL-IS. This study illustrates an isotope-dilution approach for multiplexed pesticide quantification with structured uncertainty characterization to support accurate and defensible regulatory determinations at regulatory thresholds for cannabis.
Accurate in-line monitoring of particle size and solid concentration in turbid, multiphase systems remains a significant challenge in pharmaceutical manufacturing. Most particle measurement techniques are developed for off-line analysis, while recent in-line methods mainly rely on imaging and chord length distribution (CLD) measurement. Complementing these approaches, the spatially and angularly resolved diffuse reflectance measurement (SAR-DRM) system serves as a process analytical technology analyzer, capturing detailed, configuration-dependent spectral responses of particle suspensions. This study systematically evaluates SAR-DRM's effectiveness in analyzing a wide range of particle diameters (≤90-800 µm) and concentrations (1-10 wt%) for polystyrene suspensions. The visible-NIR and NIR measurements from its multiple spatial-angular fiber configurations are further analyzed to assess their potential in complementing other in-line techniques, improving interpretability and analytical performance. The results show that combining specific SAR-DRM configurations through data augmentation markedly enhances model performance compared to individual configurations or co-adding methods, reducing error by over 50% in some cases. Moreover, data fusion of SAR-DRM with CLD measurements yields the most accurate models, particularly for mid-sized particles, decreasing the prediction error to 10-12 µm. The study highlights SAR-DRM as a promising process analytical technology analyzer for particulate process monitoring, paving the way for advanced hybrid modelling in pharmaceutical and chemical manufacturing. It also underscores the complementary sensing capabilities of SAR-DRM and CLD measurements, providing a robust multisensory platform for real-time, quantitative analysis in complex, high-turbidity systems.
Ciguatera poisoning (CP) is the most prevalent marine toxin illness globally and disproportionately affects tropical and subtropical regions that rely on fish as a major food source. It is a global concern due to fish importation, tourism in endemic regions, and changes to ocean temperatures leading to the spread of the causative microorganisms into non-endemic regions. CP is caused by the consumption of fish contaminated with ciguatoxins, a class of lipophilic, ladder-framed polyether marine toxins that cause a combination of gastrointestinal, neurological, and cardiovascular symptoms. A major constraint in ciguatoxin analysis is the lack of reference materials (RMs), especially for Caribbean ciguatoxins. Caribbean ciguatoxin-5 (C-CTX5) was isolated from Gambierdiscus silvae and quantitated by qNMR. The purified C-CTX5 was accurately diluted and used to prepare a small batch calibration solution RM at a concentration of 0.5 µg/mL. The solution was shown to be homogeneous and demonstrated good stability over 28 days at temperatures up to 23 °C. A matrix reference material was prepared using fish tissue (Sphyraena barracuda) naturally incurred with C-CTX1, with concentrations estimated using the C-CTX5 calibration solution. The fish matrix RM was homogeneous, and C-CTX1 remained stable at temperatures up to 4 °C for 28 days. At temperatures above 4 °C, a time-dependent decrease in measured C-CTX1 concentration was observed. Addition of antibiotics and an antioxidant stabilizer was shown to improve both the stability of the fish matrix and measured C-CTX1 content. These successful feasibility studies establish processes for the development of large-scale C-CTX reference materials, which are essential to ensure accurate measurements for both research and regulatory frameworks.