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Background Ethylene (C 2 H 4 ) is a gaseous phytohormone that regulates various plant physiological processes and mediates the responses of the plants to various environmental stresses. 1-Aminocyclopropane-1-carboxylic acid (ACC) is the direct precursor of the phytohormone ethylene, and is also considered as a plant growth regulator. Accurate quantification of ACC is critically important in investigating its function. However, it remains challenging to accurately quantify ACC in plant tissues because it is a small, electroneutral molecule with very low concentrations. Methods An easy, cost-saving, and highly efficient quantitative method for ACC in plant tissues was set up by liquid-liquid micro-extraction (LLME) purification with green solvent ethyl-acetate, and the precise control of the mobile phase entering into the mass spectrometer combined with the ultra-high performance liquid chromatography electrospray ionization-triple quadrupole mass spectrometer (UHPLC-ESI-MS/MS). Results The contents of ACC in 10 mg of different fresh fruits were detected. The established method had limit of detection (LOD) (2.5 pg), matrix effect (ME) (92.6%), good precision (3.54%), recovery rate (95.82%), and a good linear relationship within the range of 0.5 to 1500 ng.mL −1 (R 2  = 0.9998). Conclusion We have developed an easy, sensitive, and cost-saving quantitative method for ACC in plant tissues without derivatization which is useful for the precise quantification of ACC in plant tissues.

Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping clinical symptoms with tuberculosis (TB), leading to inappropriate treatment. Herein, we employed noninvasive metabolic phenotyping coupled with comprehensive statistical modeling to discover potential biomarkers for the differential diagnosis of NTM infection versus TB. Urine samples from 19 NTM and 35 TB patients were collected, and untargeted metabolomics was performed using rapid liquid chromatography-mass spectrometry. The urine metabolome was analyzed using a combination of univariate and multivariate statistical approaches, incorporating machine learning. Univariate analysis revealed significant alterations in amino acids, especially tryptophan metabolism, in NTM infection compared to TB. Specifically, NTM infection was associated with upregulated levels of methionine but downregulated levels of glutarate, valine, 3-hydroxyanthranilate, and tryptophan. Five machine learning models were used to classify NTM and TB. Notably, the random forest model demonstrated excellent performance [area under the receiver operating characteristic (ROC) curve greater than 0.8] in distinguishing NTM from TB. Six potential biomarkers for NTM infection diagnosis, including methionine, valine, glutarate, 3-hydroxyanthranilate, corticosterone, and indole-3-carboxyaldehyde, were revealed from univariate ROC analysis and machine learning models. Altogether, our study suggested new noninvasive biomarkers and laid a foundation for applying machine learning to NTM differential diagnosis.

Following the passage of the Agriculture Improvement Act of 2018, demand for accurate cannabinoid quantification in hemp flowers has increased to ensure regulatory compliance. Liquid chromatography–tandem mass spectrometry (LC–MS/MS) using a triple-quadrupole mass spectrometer provides high sensitivity and selectivity and is well suited for this purpose; however, a review of the literature indicates that many published LC–MS/MS methods target only a limited number of cannabinoids, and reliable differentiation of structural isomers remains challenging. In this study, an LC–MS/MS method was developed for the simultaneous quantification of eighteen cannabinoids in hemp flowers. Baseline chromatographic separation of structural isomers enabled reliable differentiation of compounds with highly similar fragmentation patterns and allowed the use of the most sensitive multiple reaction monitoring (MRM) transitions for quantification. Both positive and negative ionization modes were employed to achieve optimal sensitivity using dynamic polarity switching within a single analytical run. Following validation in accordance with ISO/IEC 17025, the method was applied to a proficiency test hemp sample and six commercial hemp samples, demonstrating excellent time efficiency (11 min for 18 cannabinoids) and an exceptionally wide calibration range (8–5000 ng/mL, corresponding to 0.032–20% (w/w) for all cannabinoids).

Blueberries ( Vaccinium species) are an economically important fruit crop rich in bioactive compounds like polyphenols and flavonoids. Interestingly, some blueberry cultivars also produce monotropein, which has bioactive properties, including anti-inflammatory and neuroprotective effects. However, methods to quantify monotropein in blueberries have not been optimized. To address this gap, an optimized analytical method for monotropein extraction and quantification using ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) was developed. Different extraction strategies were compared, including variations in temperature, time, and ultrasonication treatments. Optimal extraction was achieved by heating samples to 60 °C for 15 mins in methanol. The method had high percent recovery and good repeatability. This protocol was then applied to 28 blueberry cultivars, 14 of which had not been previously analyzed for monotropein. Monotropein ranged from 0–1807 ng/mg dry weight. The developed method provides a robust tool that can be applied to future evaluations of monotropein in diverse blueberry cultivars.

This study aimed to establish a fast and efficient method for the determination of N-nitrosamines (NAs) in meat products by integrating two sample preparation techniques—QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) and FaPEx (Fast Pesticide Extraction)—with liquid chromatography–tandem mass spectrometry (LC–MS/MS). Chromatographic separation was performed on a Poroshell 120 Phenyl Hexyl column using a gradient elution of acetonitrile and 0.01% formic acid at a flow rate of 0.3 mL/min and a column temperature of 25 °C. Under these conditions, nine NAs and one internal standard were completely separated within 11 min with selective reaction monitoring mode (SRM) for detection. Samples were first extracted with QuEChERS powder using acetonitrile containing 0.1% formic acid, followed by purification with a FaPEx-Chl cartridge. This combined approach demonstrated superior performance compared with traditional solvent extraction or QuEChERS extraction alone. The recoveries of the developed method ranged from 76% to 111% and 52% to 103% at spiking levels of 50 ng/g and 20 ng/g, respectively. The limits of detection (LOD) and quantification (LOQ) were 0.002–0.3 ng/g and 0.006–1.00 ng/g, respectively. The inter-day and intra-day precisions (RSD%) ranged from 2.7% to 17% and 2.9% to 17%, respectively. These results indicate that the proposed method is among the most time-efficient and effective analytical approaches currently available for the determination of NAs in meat products.

In forensic toxicology, the rapid and reliable detection of emerging synthetic opioids and hallucinogens is crucial for case investigations and public health monitoring. This work describes the development, optimization and validation of a simple, fast and sensitive methodology for the simultaneous analysis of 6 new synthetic opioids (carfentanil, fentanyl, isotonitazene, metonitazene, norfentanyl, and sufentanil) and 2 hallucinogens (lysergide [LSD] and mescaline), together with the main LSD metabolite 2-oxo-3-hydroxy-lysergide [LSD-OH], in whole blood samples by liquid chromatography coupled to tandem mass spectrometry. Under optimized experimental conditions, linearity was verified between 0.1 and 20 ng/mL for all analytes except mescaline (2.5–500 ng/mL), with r2 > 0.99 for 1/x weighting, and no significant carryover or matrix effects were observed. Good precision (% RSD < 13 %) and trueness (% Bias within ± 20 %) values were achieved. The estimated limit of quantification (LOQ) was 0.1 ng/mL for all compounds except mescaline (2.5 ng/mL). Authentic forensic samples were also analyzed, and positive samples for fentanyl, norfentanyl, and sufentanil were identified. The proposed methodology allows the simultaneous analysis of compounds from different families of psychoactive substances, in both postmortem and in vivo samples, using only 50 µL of whole blood. The demonstrated speed, simplicity, and effectiveness make it particularly advantageous for routine implementation in forensic toxicology laboratories. [Display omitted] •First known UHPLC-MS/MS method for nitazenes and hallucinogens analysis.•Validation of fast method for in vivo and postmortem whole blood samples analysis.•Low sample volume required is advantageous for forensic toxicology laboratories.•Sensitive and extensive linear range for a broad spectrum of concentrations.•Applied to suspected intoxication cases and feasible to routine forensic work.

Abstract Context Adiponectin is a potent uterine tocolytic that decreases with gestational age, suggesting it could be a maternal metabolic quiescence factor. Maternal stress can influence preterm birth risk, and adiponectin levels may be stress responsive. Objective We characterized associations between adiponectin and glucocorticoids with preterm birth and modeled their predictive utility. We hypothesized maternal plasma adiponectin and cortisol are inversely related and lower adiponectin and higher cortisol associate with preterm birth. Methods We performed a nested case–control study using biobanked fasting maternal plasma. We included low-risk singleton pregnancies, and matched 1:3 (16 preterm, 46 term). We quantified high molecular weight (HMW), low molecular weight (LMW), and total adiponectin using an enzyme-linked immunosorbent assay. We validated a high-performance liquid chromatography-tandem mass spectrometry serum assay for use in plasma, to simultaneously measure cortisol, cortisone, and 5 related steroid hormones. We used linear/logistic regression to compare group means and machine learning for predictive modeling. Results The preterm group had lower mean LMW adiponectin (3.07 μg/mL vs 3.81 μg/mL at 15 weeks (w) 0 days (d), P = .045) and higher mean cortisone (34.4 ng/mL vs 29.0 ng/mL at 15w0d, P = .031). The preterm group had lower cortisol to cortisone and lower LMW adiponectin to cortisol ratios. We found HMW adiponectin, cortisol to cortisone ratio, cortisone, maternal height, age, and prepregnancy body mass index most strongly predicted preterm birth (area under the receiver operator curve = 0.8167). In secondary analyses, we assessed biomarker associations with maternal self-reported psychosocial stress. Lower perceived stress was associated with a steeper change in cortisone in the term group. Conclusion Overall, metabolic and stress biomarkers are associated with preterm birth in this healthy cohort. We identify a possible mechanistic link between maternal stress and metabolism for pregnancy maintenance.

As rapidly developing consumer products, cosmetics confront challenges regarding safety, especially hazardous ingredients, like sex hormones. Prolonged exposure to trace sex hormones in cosmetics can inflict immeasurable damage to human health. To accurately detect the trace amounts of sex hormones in cosmetics, a reliable method was developed and validated using ultra-high performance liquid chromatography–mass spectrometry (UHPLC-MS/MS) with magnetic solid-phase extraction (MSPE) and isotope-labeled internal standards (IL-ISs). The conditions of sample pretreatment, chromatography, and mass parameters were systemically investigated. In the MSPE procedure, the commercial Fe3O4@HLB magnetic material was employed for sample pretreatment, which was beneficial for operation, as well as sample purification and analyte enrichment. The utilization of IL-ISs compensated for potential matrix effects and losses during sample preparation, thereby improving precision and accuracy. Based on the proposed MSPE technology, UHPLC-MS/MS can address the qualitative and quantitative analysis needs for target analytes in complex cosmetic matrices. At three fortification levels, recoveries were in the range of 71.7–116.2%, with a relative standard deviation (RSD) ranging from 1.6% to 8.3%. Furthermore, based on the method proposed here, a total of 116 batches of cosmetics were analyzed, and trace progestins and estrogens were discovered in 10 samples. The MSPE method, coupled with UHPLC-MS/MS using IL-ISs, was convenient, efficient, and feasible for detecting trace amounts of sex hormones in cosmetics. The method scored 0.66 (out of 1) on the AGREE metric, confirming its green profile. Based on the detected concentrations, a preliminary safety evaluation was performed to assess the potential health risks of residual progesterone in hair loss prevention cosmetics by calculating the margin of safety (MoS).

Detecting and quantifying disinfection by-products (DBPs), especially brominated species (Br-DBPs), is analytically challenging, often necessitating multiple techniques and specific standards for each target. This complexity hinders comprehensive assessment. To overcome these limitations, we present a powerful, integrated approach combining liquid chromatography with inductively coupled plasma mass spectrometry (LC-ICP-MS) and high-resolution mass spectrometry (LC-HRMS). This method enables rapid, non-targeted group screening of Br-DBPs: LC-ICP-MS selectively identifies bromine-containing compounds, while LC-HRMS provides tentative structural identification. Crucially, this synergistic combination allows for the quantification of any Br-DBP without requiring individual reference standards. This study successfully demonstrates the application of this combined LC-ICP-MS and LC-HRMS strategy for the non-targeted detection, identification, and subsequent quantification of Br-DBPs in real drinking water samples, offering a significant advancement for DBP monitoring and risk assessment.