The chemical complexity of medicinal plants poses a significant challenge for metabolomic profiling and chemotaxonomic discrimination. In this study, we applied an integrated pipeline combining Global Natural Products Social Molecular Networking (GNPS) platform with SIRIUS-based in silico annotation to systematically profile and compare the metabolomes of three medicinal Polygonaceae plants: Rheum palmatum, Polygonum cuspidatum, and Polygonum multiflorum. Beyond routine library matching, we implemented a data-mining strategy combining spectral networking and in silico structure annotation to extract characteristic MS/MS fragmentation features with chemotaxonomic relevance. Our results reveal distinct metabolic fingerprints among the three species and demonstrate that this integrated approach provides an efficient platform for comparative phytochemical studies, supporting chemotaxonomic classification and quality control of medicinal plants.
Triazine herbicides are widely used in agricultural production. However, their environmental persistence and mobility pose potential threats to ecological safety and human health. Herein, a novel analytical method integrating stir bar sorptive extraction (SBSE) with airflow-assisted thermal desorption dielectric barrier discharge ionization mass spectrometry (AFA-TD-DBDI-MS), an ambient ionization mass spectrometry (AMS), was developed for the sensitive determination of triazine herbicides. A hydroxyl-functionalized covalent organic framework (COF-HF) was synthesized and used to fabricate COF-HF-coated stir bars via physical adhesion. The as-prepared stir bars exhibited outstanding extraction performance toward triazine herbicides, and the underlying adsorption mechanism was systematically investigated. The established COF-HF-based SBSE-AFA-TD-DBDI-MS method demonstrated good linearity (R² ≥ 0.9957), satisfactory recoveries (91.31%-98.81%), good repeatability (RSD ≤ 8.49%), and low limits of detection (0.0061-0.0312 ng/mL). This study provides a rapid and efficient strategy for monitoring trace triazine pollutants in environmental water and serum matrices.
Plants of the genus Curcuma are vital medicinal resources; however, their highly similar chemical profiles and morphological features present substantial challenges for accurate species authentication. Here, we established a comprehensive analytical strategy for the precise differentiation of eight medicinal Curcuma species and one counterfeit by integrating untargeted gas chromatography-mass spectrometry (GC-MS) profiling with rapid in situ portable mass spectrometry (PMS) and machine learning. GC-MS analysis tentatively identified ten predominant volatile components, whose potential biological targets and signaling pathways were elucidated via network pharmacology. Chemometric analysis of GC-MS metabolic profiles further enabled the screening of core differential markers driving species discrimination. For rapid on-site detection, in situ PMS fingerprints were acquired and processed using a characteristic ion-based binarization strategy following base peak normalization. When coupled with advanced machine learning algorithms, particularly Ensemble and Efficient Linear classifiers, the system achieved 100% classification accuracy with high computational efficiency. Together, this dual-platform approach provides an effective, and broadly applicable method for quality control and rapid authentication of multi-origin traditional medicines.
In this study, we developed a systematic validation framework for non-targeted analysis (NTA) and applied it to complementary analytical workflows using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) and liquid chromatography-trapped ion mobility spectrometry-quadrupole time-of-flight mass spectrometry (LC-TIMS-QTOFMS) for broad profiling of cigarette mainstream smoke constituents. The validation framework evaluated instrumental detection and annotation performance, method-specific library-search thresholds, the accuracy of semi-quantitative concentration estimates, repeatability and intermediate precision, and analytical coverage across two GC × GC-TOFMS methods and three LC-TIMS-QTOFMS methods. An operational reporting threshold of 100 ng per cigarette was selected as the lowest evaluated level at which the mean true-positive rate across the analytical methods was at least 90% and no individual method showed a true-positive rate below 80%. The method-specific library-similarity-score thresholds used to define high-confidence annotations ranged from 700 to 800. For the GC × GC-TOFMS methods, the accuracy of semi-quantitative concentration estimates for the quality control (QC) compounds ranged from 41% to 128%. In the LC-TIMS-QTOFMS methods, the initial semi-quantitative concentration estimates showed substantial compound-dependent positive bias; application of predicted relative response factors reduced this bias, although the accuracy of the adjusted semi-quantitative estimates still ranged from 67% to 428%. The coefficients of variation for repeatability and intermediate precision were below 30% for all evaluated QC compounds across all analytical methods. The summed semi-quantitative concentration estimates obtained using the NTA workflows, together with separately determined amounts of major constituents, including nicotine, water, propylene glycol, glycerin, and triacetin, represented 39.6 mg/cig. This amount corresponded to an apparent mass ratio of 91.0% relative to the gravimetrically determined total particulate matter (TPM) yield. The annotated constituents also demonstrated broad and complementary chemical space coverage in terms of molecular weight and calculated log P. Application of the evaluated workflows to mainstream smoke from the Kentucky reference cigarette (1R6F) resulted in 3590 reported analytical features after consolidation of duplicate "Confirmed" identifications across analytical methods. These results demonstrate that the proposed framework provides a systematic basis for evaluating and further developing NTA workflows for cigarette smoke and other complex chemical mixtures.
Autographa californica multiple nucleopolyhedrovirus, known as Baculovirus, is a widely used platform for producing therapeutic proteins and viral vectors. The purity and infectious activity of Baculovirus stocks determine the quality and productivity of recombinant products produced through this system. Current purification strategies suffer from major limitations: centrifugation lacks productivity and scalability; ion-exchange chromatography affords limited selectivity and purity; and the only commercial affinity resin requires harsh elution conditions that significantly reduce functional product recovery. To overcome these limitations, this study introduces the first peptide affinity ligands targeting the baculoviral envelope glycoprotein GP64 for the purification of active Baculovirus particles. We implemented a combinatorial selection workflow based on dual-fluorescence screening of solid-phase peptide libraries to identify 12-mer sequences that bind GP64 and elute Baculovirus under mild conditions (pH 8.5). As the selected ligands are enriched in histidine and tyrosine residues, product release is effected by the combined modulation of pH and ionic strength. Eight candidate peptides (SB1-SB8) were evaluated on Toyopearl and POROS chromatographic resins, demonstrating that matrix chemistry, pore size, and ligand density govern purification performance. The lead peptide SB4 conjugated to POROS resin at ∼10 µmol/mL achieved 81% recovery of infectious virions (transducing units), robust host cell protein reduction (LRV 1.65), and a dynamic binding capacity (DBC10%) of 1.9 × 1010 vg/mL resin. Transmission electron microscopy and multi-angle light scattering confirmed the integrity of purified particles (200 × 50 nm rods with intact nucleocapsids), compared to BacuClear eluates that showed collapsed morphology. The SB4-POROS resin demonstrated storage stability and ∼80% retention of binding capacity over ten purification–regeneration cycles with caustic cleaning. Integration into a three-step downstream process (clarification, affinity capture, and polishing) raised product purity 1,528-fold, from 6.22 × 106 to 9.50 × 109 viral genomes per µg of HCP, while reducing the total HCP burden 1,698-fold, at a cumulative transducing-unit yield of ∼69% relative to the feedstock, establishing SB4-POROS as a promising technology with a favorable projected cost structure for Baculovirus purification.
Solid-phase extraction (SPE) constitutes one of the most common techniques for cleanup of sample extracts in analytical chemistry. Traditionally, SPE cleanup involves 100-1000 mg of one sorbent phase housed in cartridges placed onto vacuum manifolds for manual performance of several steps. However, this format has several drawbacks regarding convenience, versatility, speed, cost, labor, and performance, among other facets. To overcome several of these limitations, dispersive (d)-SPE has become more commonly applied in which extracts are simply mixed with sorbents in a versatile, quick, easy, and cheap approach that often yields high recoveries of analytes. The main disadvantage of d-SPE, however, is that quality of cleanup is often sacrificed for its other benefits. Over time, other commercial SPE approaches and formats have become available, such as mini-column SPE (or µ-SPE) using either a robotic or centrifugal platform to avoid the inconveniences of traditional SPE with a vacuum manifold. In this way, the conveniences of d-SPE can be merged with the better cleanup of columnar SPE. In Part I of this study, a new commercial centrifugal mini-SPE product using different spin rates was compared with d-SPE in a SpinFiltr format. QECh*All (formerly known as QuEChERSER) extracts of 9 commodities (apple, orange, kale, grains, catfish, egg, infant formula, cashew, and coffee) were cleaned up at the same time using both techniques with the same sorbents from the same source with equivalent sample/sorbent ratios. Low-pressure gas chromatography - high-resolution mass spectrometry with orbital ion trap detection (LPGC-orbitrap) was used for analysis of 47 pesticides and environmental contaminants with LogP ranging from -1 to 8. Practical aspects, degree of cleanup, and analytical performance were compared. Centrifugal mini-SPE using 16-177 rcf was found to remove up to 99% of the fatty acids, cholesterol, phytosterols, and other matrix components from the extracts for the same or better sample throughput, cost, and ease compared to d-SPE. It also provided better and more consistent analyte recoveries, especially for the complex fatty matrices, except coffee which required more extensive cleanup than achieved by either approach.
An emulsive liquid‑liquid microextraction (ELLME) technique based on deep eutectic solvents (DES) was developed for the extraction of three sulfonamide antibiotics (SAs) in canine and feline urine, followed by their determination using high‑performance liquid chromatography (HPLC) with a diode array detector (DAD). The DES synthesized from thymol and hexanoic acid was used as an extractant to form an emulsion with water for the efficient extraction of SAs. Without using auxiliary instruments or chemical reagents, the emulsion undergoes spontaneous demulsification upon static standing. No auxiliary equipment, such as vortex mixers, ultrasonic baths, or centrifuges, is required for sample pretreatment. This simplifies operational procedures and shortens the extraction time. The linear range is 0.005-0.5 mg L-1, with detection and quantitation limits of 0.002 and 0.005 mg L-1, respectively. The extraction recovery ranges from 85.3 % to 97.2 %, with a relative standard deviation <2.7 %. Seven evaluation tools were employed to assess the greenness and practical applicability of the analytical procedure. This simple and eco-friendly DES-ELLME-HPLC-DAD method provides a novel and reliable technical strategy for rapid screening and accurate quantification of veterinary drugs in urine samples.
The ion transport mechanism is a key factor influencing the analytical properties of detectors used in ion mobility spectrometry. In this study, the transport properties of hydrated chloride, bromide, and iodide ions were investigated using drift tube ion mobility spectrometer (DT IMS) and differential mobility spectrometer (DMS) under controlled humidity and temperature conditions. The objective of this work was to compare the effects of temperature and electric field strength on the transport properties of hydrated halide ions. DT IMS measurements were performed in nitrogen at atmospheric pressure over the temperature range of 318-363 K and water vapor concentrations up to approximately 1000 ppm. For all halide ions, increasing humidity resulted in systematic decreases in reduced mobility, whereas increasing temperature promoted declustering and increased mobility. DMS measurements revealed positive field-dependent mobility behavior for all hydrated halide ions. Increasing electric field strength causes declustering, leading to mobility changes analogous to those observed in DT IMS with increasing temperature. The results indicate that the commonly used concept of effective temperature does not adequately describe the transport of hydrated ions in DT IMS and DMS, where clustering and declustering processes modify the composition of the ion population. Comparison of DT IMS and DMS data indicates that a more appropriate description can be obtained using the concept of an equivalent temperature defined by the degree of ion hydration. Because hydration equilibria depend on water vapor concentration, the equivalent temperature is also humidity-dependent and cannot be represented by a single universal value.
Glyphosate, a widely used herbicide in agricultural and forestry settings, raises significant concerns regarding potential occupational exposure. However, comprehensive exposure assessment integrating biological and environmental monitoring remains limited, partly due to the lack of analytical workflows capable of supporting multiple sample matrices on a single platform. Here, we developed and validated a high-throughput derivatization-free LC-MS/MS workflow for the determination of glyphosate and aminomethylphosphonic acid (AMPA) in urine, surface wipes, patches and breath zone air monitoring samples collected using Occupational Safety and Health Administration (OSHA) versatile sampler (OVS) tubes. The workflow combines selective solid-phase extraction (SPE) using AFFINIMIP molecularly imprinted polymer cartridges for urine with a simplified universal aqueous extraction workflow for environmental matrices, enabling efficient analysis of diverse matrices using a single analytical platform. Chromatographic separation was achieved on a mixed-mode Obelisc N column within 6 minutes, with the in-sample addition of 0.1 mmol L-1 methylenediphosphonic acid (MA) significantly improved peak shape and sensitivity. The method demonstrated excellent specificity, accuracy and precision across all matrices. The limits of detection (LODs) for glyphosate and AMPA were 0.1 and 0.2 ng mL-1 in urine, respectively; and 1.6 ng in surface wipes and patches, and 0.4 ng in OVS air samples for both analytes. The method was successfully applied to 1121 biological and environmental samples collected from forestry workers in Australia, confirming its suitability for real-world exposure assessment. By integrating biomonitoring and environmental monitoring within a single analytical platform, this approach provides a practical and high-throughput tool for comprehensive assessment of occupational glyphosate exposure.
A novel, and efficient spin-assisted dispersive micro-solid phase extraction (SA-DµSPE) method coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed for quantifying trace levels of organophosphorus pesticide (OPP) residues in plant-based milk alternatives (PBMAs). To fabricate the extraction sorbent, silica-coated magnetite nanoparticles were incorporated into a copper-based metal-organic gel (MOG) network, followed by freeze-drying, yielding a porous magnetic aerogel with excellent adsorption properties. A custom-built electrical device was employed to promote sorbent dispersion and expedite its magnetic separation. Adsorption and desorption parameters were optimized using a rotatable central composite design (RCCD) and one-variable-at-a-time (OVAT) approach. Matrix effect (ME%) values ranged from 15.0% to 34.9%; therefore, a matrix-matched calibration method was employed for OPP quantification. Under the optimal conditions, calibration curves in various matrices were linear within the range of 0.05-200.0 ng mL-1, with coefficients of determination (R²) ≥ 0.9978. Limits of detection (LODs) and quantification (LOQs) ranged from 0.03 to 0.08 ng mL-1 and 0.05 to 0.25 ng mL⁻¹, respectively. Preconcentration factors (PFs) were calculated in the range of 16.3 to 24.3 for different matrices, corresponding to absolute extraction recoveries (ER%) between 40.8% and 60.8%. The method provided relative recoveries (RR%s) of 90.0%-111.3% and relative standard deviations (RSD%) of 3.5-6.8% for the determination of OPPs in almond, soy, and hazelnut milks. The newly prepared aerogel combined with LC-MS/MS provided efficient retention of the target analytes, which, together with the other analytical figures of merit, confirms the proposed method as a suitable alternative for OPP determination in PBMAs.
Radioactive 195Au is useful for the long-term biodistribution tracking of gold nanoparticles in cancer diagnostics and therapeutics. This study develops a highly selective separation method for 195Au produced via the charged particle irradiation of a Pt target using UTEVA resin column chromatography and elucidates the underlying separation mechanism. To optimize the chromatographic conditions, batch experiments were performed with the UTEVA resin in HCl and HNO3 media using tracer amounts of 195Au and macro amounts of Pt. 195Au exhibited high distribution coefficients in HCl, whereas Pt showed negligible adsorption. In HNO3 media, the distribution coefficients of 195Au decreased with increasing acid concentration. Subsequent two-step column chromatography using the UTEVA resin achieved a chemical yield of 91.6% and a decontamination factor of 4.6 × 103 for Pt. To understand this selectivity, density functional theory (DFT) calculations were performed on the interactions between the anionic chloride complexes of Au, Pt, and Ir (a by-product of the nuclear reaction) and the protonated phosphonate cation. The calculations revealed that the Gibbs free energy change for ion-pair formation follows the order of Au < Ir < Pt, suggesting that anionic chloride complexes of Au readily form ion-pair complexes and are extracted. This extraction of Au is driven by a lower dehydration energy and reduced steric hindrance of [AuCl4]- compared to the highly charged and octahedral [PtCl6]2- and [IrCl6]2- ions. This study demonstrates that the UTEVA resin is highly effective for the separation and purification of 195Au from irradiated Pt targets. The purified 195Au obtained by this method can be utilized in future research on Au nanoparticles.
