BACKGROUND: Compound annotation is always a challenging step in metabolomics studies. The molecular networking strategy has been developed recently to organize the relationship between compounds as a network based on their tandem mass (MS2) spectra similarity, which can be used to improve compound annotation in metabolomics analysis.
OBJECTIVE: This study used Bupleuri Radix from different geographic areas to evaluate the performance of molecular networking strategy for compound annotation in liquid chromatography-mass spectrometry (LC-MS)-based metabolomics.
METHODS: The Bupleuri Radix extract was analyzed by LC-quadrupole time-of-flight MS under MSe acquisition mode. After raw data preprocessing, the resulting dataset was used for statistical analysis, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The chemical makers related to the sample growth place were selected using variable importance in projection (VIP) > 2, fold change (FC) > 2, and p < 0.05. The molecular networking analysis was applied to conduct the compound annotation.
RESULTS: The score plots of PCA showed that the samples were classified into two clusters depending on their growth place. Then, the PLS-DA model was constructed to explore the chemical changes of the samples further. Sixteen compounds were selected as chemical makers and tentatively annotated by the feature-based molecular networking (FBMN) analysis.
CONCLUSIONS: The results showed that the molecular networking method fully exploits the MS information and is a promising tool for facilitating compound annotation in metabolomics studies. However, the software used for feature extraction influenced the results of library searching and molecular network construction, which need to be taken into account in future studies.

OBJECTIVE: The aim of this study was to explore the potential to profile and distinguish varying clinical severity grades of MIH, compared to normal enamel, using proteomics.
METHODS: Liquid chromatography-mass spectrometry analyses were conducted on enamel samples of extracted teeth, from 11 children and adolescents, spanning an age range of 6-18 years. Enamel powder samples were collected from extracted, third molars (n = 3) and first permanent molars diagnosed with MIH (n = 8). The MIH tooth samples were categorized into subgroups based on clinical severity grade. The data were statistically analyzed using ANOVA and Welch\'s t test.
RESULTS: Teeth affected by MIH exhibited a diverse array of proteins, each with different functions related to dental enamel, distinguishing them from their normal enamel counterparts. The application of microdissection combined with LC-MS techniques has revealed the potential to discern unique proteomic profiles among MIH-affected teeth, characterized by varying clinical severity grades. Both analyzed MIH groups displayed consistent trends in the presentation of biological processes, including underabundance of proteins primarily associated with cell organization and biogenesis. Furthermore, proteins linked to cell death were overabundant in both MIH groups.
CONCLUSIONS: Proteomics enabled the detection and differentiation of various proteins across different clinical severity grades of MIH.

Hypoxic-ischemic encephalopathy (HIE) is one of the most common causes of childhood disability. Hypothermic therapy is currently the only approved neuroprotective approach. However, early diagnosis of HIE can be challenging, especially in the first hours after birth when the decision to use hypothermic therapy is critical. Distinguishing HIE from other neonatal conditions, such as sepsis, becomes a significant problem in diagnosis. This study explored the utility of a metabolomic-based approach employing the NeoBase 2 MSMS kit to diagnose HIE using dry blood stains in a Rice-Vannucci model of HIE in rats. We evaluated the diagnostic fidelity of this approach in a range between 3 and 6 h after the onset of HIE, including in the context of systemic inflammation and concomitant hypothermic therapy. Discriminant analysis revealed several metabolite patterns associated with HIE. A logistic regression model using glycine levels achieved high diagnostic fidelity with areas under the receiver operating characteristic curve of 0.94 at 3 h and 0.96 at 6 h after the onset of HIE. In addition, orthogonal partial least squares discriminant analysis, which included five metabolites, achieved 100% sensitivity and 80% specificity within 3 h of HIE. These results highlight the significant potential of the NeoBase 2 MSMS kit for the early diagnosis of HIE and could improve patient management and outcomes in this serious illness.

A priori estimation of analyte response is crucial for the efficient development of liquid chromatography-electrospray ionization/mass spectrometry (LC-ESI/MS) methods, but remains a demanding task given the lack of knowledge about the factors affecting the experimental outcome. In this research, we address the challenge of discovering the interactive relationship between signal response and structural properties, method parameters and solvent-related descriptors throughout an approach featuring quantitative structure-property relationship (QSPR) and design of experiments (DoE). To systematically investigate the experimental domain within which QSPR prediction should be undertaken, we varied LC and instrumental factors according to the Box-Behnken DoE scheme. Seven compounds, including aripiprazole and its impurities, were subjected to 57 different experimental conditions, resulting in 399 LC-ESI/MS data endpoints. To obtain a more standard distribution of the measured response, the peak areas were log-transformed before modeling. QSPR predictions were made using features selected by Genetic Algorithm (GA) and providing Gradient Boosted Trees (GBT) with training data. Proposed model showed satisfactory performance on test data with a RMSEP of 1.57 % and a of 96.48 %. This is the first QSPR study in LC-ESI/MS that provided a holistic overview of the analyte\'s response behavior across the experimental and chemical space. Since intramolecular electronic effects and molecular size were given great importance, the GA-GBT model improved the understanding of signal response generation of model compounds. It also highlighted the need to fine-tune the parameters affecting desolvation and droplet charging efficiency.

High-throughput metabolomics has enabled the development of large-scale cohort studies. Long-term studies require multiple batch-based measurements, which require sophisticated quality control (QC) to eliminate unexpected bias to obtain biologically meaningful quantified metabolomic profiles. Liquid chromatography-mass spectrometry was used to analyze 10,833 samples in 279 batch measurements. The quantified profile included 147 lipids including acylcarnitine, fatty acids, glucosylceramide, lactosylceramide, lysophosphatidic acid, and progesterone. Each batch included 40 samples, and 5 QC samples were measured for 10 samples of each. The quantified data from the QC samples were used to normalize the quantified profiles of the sample data. The intra- and inter-batch median coefficients of variation (CV) among the 147 lipids were 44.3% and 20.8%, respectively. After normalization, the CV values decreased by 42.0% and 14.7%, respectively. The effect of this normalization on the subsequent analyses was also evaluated. The demonstrated analyses will contribute to obtaining unbiased, quantified data for large-scale metabolomics.

UNASSIGNED: Carvacrol is an essential oil extracted from oregano which can be used as a natural additive in poultry litter and could have a positive impact not only on production rates but also on the quality of poultry meat. The aim of this study was to evaluate the effect of the addition of carvacrol to litter on weight gain and the occurrence of residues in chicken tissues.
UNASSIGNED: One-day-old Ross 308 chicks were used for the study and were randomly divided into two experimental groups. For 42 days, one group was kept in a room with litter enriched with carvacrol and the second group was kept in a room with litter without carvacrol. After 42 days, the birds were sacrificed and necropsied. Carvacrol content was determined in homogenised organ tissue samples by liquid chromatography-mass spectrometry.
UNASSIGNED: Weekly weighing results showed that exposure to carvacrol in litter had no impact on chicken body weight. The analysis of plasma, muscle, liver and lung tissue after 42 days\' exposure clearly indicated that there were residues of carvacrol in the analysed matrices.
UNASSIGNED: Exposure of chickens to carvacrol left residues but did not affect body weight.

BACKGROUND: Rectal cancer is one of the most lethal of gastrointestinal malignancies. Metabonomics has gradually developed as a convenient, inexpensive and non-destructive technique for the study of cancers.
METHODS: A total of 150 tissue samples from 25 rectal cancer patients were analyzed by liquid chromatography-mass spectrometry (LC-MS), and 6 tissue samples were collected from each patient (group 1: tumor; group 2: 0.5 cm from tumor; group 3:1 cm from tumor; group 4:2 cm from tumor; group 5:3 cm from tumor and group 6:5 cm from tumor). The differential metabolites of tumor tissues and 5 cm from the tumor (normal tissues) were first selected. The differential metabolites between tumor tissues and normal tissues were regrouped by hierarchical clustering analysis, and further selected by discriminant analysis according to the regrouping of clustering results. The potential safe margin of clinical T(cT)1,cT2 stage rectal cancer and cT3,cT4 stage rectal cancer at the metabolomic level was further identified by observing the changes in the level of differential metabolites within the samples from group 1 to group 6.
RESULTS: We found 22 specific metabolites to distinguish tumor tissue and normal tissue. The most significant changes in metabolite levels were observed at 0.5 cm (cT1, cT2) and 2.0 cm (cT3, cT4) from the tumor, while the changes in the tissues afterwards showed a stable trend.
CONCLUSIONS: There are differential metabolites between tumor tissues and normal tissues in rectal cancer. Based on our limited sample size, the safe distal incision margin for rectal cancer surgery in metabolites may be 0.5 cm in patients with cT1 and cT2 stage rectal cancer and 2.0 cm in patients with cT3 and cT4 stage rectal cancer.

The increased production and use of nanopesticides will increase the likelihood of their exposure to humans and the environment. In order to properly evaluate their risk, it will be necessary to rigorously quantify their concentrations in major environmental compartments including water, soil and food. Due to major differences in the characteristics of their formulation, it is unclear whether analytical techniques that have been developed for conventional pesticides will allow quantification of the nano-forms. Therefore, it is necessary to develop and validate analytical techniques for the quantification of nanopesticides in foods and the environment. The goal of this study was to validate a method for analyzing the active ingredients of two pesticides with different physicochemical properties: azoxystrobin (AZOX, a fungicide, log Kow 3.7) and bifenthrin (BFT, an insecticide, log Kow 6.6) that were applied to agricultural soils, either as a conventional formulation or encapsulated in nanoparticles (either Allosperse® or porous hollow nSiO2). Pesticide-free strawberry plants (Fragaria × ananassa) and three different agricultural soils were spiked with the active ingredients (azoxystrobin and bifenthrin), in either conventional or nano formulations. A modified QuEChERS approach was used to extract the pesticides from the strawberry plants (roots, leaves and fruits) and a solvent extraction (1:2 acetonitrile) was employed for the soils. Samples were analyzed by liquid chromatography-hybrid quadrupole time-of-flight mass spectrometry in order to determine method detection limits, recoveries, precision and matrix effects for both the \"conventional\" and nanoencapsulated pesticides. Results for the modified method indicated good recoveries and precision for the analysis of the nanoencapsulated pesticides from strawberries and agricultural soils, with recoveries ranging from 85 to 127% (AZOX) and 68-138% (BFT). The results indicated that the presence of the nanoencapsulants had significant effects on the efficiency of extraction and the quantification of the active ingredients. The modified analytical methods were successfully used to measure strawberry and soil samples from a field experiment, providing the means to explore the fate of nanoencapsulated pesticides in food and environmental matrices.

BACKGROUND: People who inject drugs (PWID) have a high risk of premature death due to fatal overdoses. Newly emerged fentanyls, much more potent than heroin and other opioids, may increase this risk further. Therefore, precise information on injected drugs is critical to improving prevention strategies.
OBJECTIVE: This study aimed to analyse drug residues in used injection equipment in order to determine drug and drug combinations and compare and complement findings with self-reported information.
METHODS: Used syringes and needles (n=766) were collected at the supervised drug consumption facilities, the needle exchange service and two low-threshold health services for problem drug users in Oslo, Norway. The material was collected every third month from June 2019 to June 2020 and analysed for 64 substances using highly specific analytical methods (ultra-high performance liquid chromatography tandem mass spectrometry). Additionally, a street-recruited sample of PWID was interviewed from 2017 to 2019 regarding their drug injection habits (n=572).
RESULTS: Heroin (65.5%) or amphetamines (59.8%), often in combination (30.5%), were commonly detected in drug residues. Other opioids, stimulants or benzodiazepines were rarely detected (6.1%). Fentanyl was detected in only one syringe. Heroin was the most reported drug (77.6% during the past four weeks, 48.3% daily/almost daily), followed by amphetamines (57.5% during the past four weeks, 23.1% daily or almost daily). Injection of methadone, buprenorphine and dissolved tablets was self-reported more frequently than determined in drug residue findings.
CONCLUSIONS: Analysis of the injection equipment proved useful as a non-invasive, rapid and accurate means to obtain detailed information on injected drugs in Oslo and supplement traditional PWID survey information.

Oxygen deficiency in cells, tissues, and organs can not only prevent the proper development of biological functions but it can also lead to several diseases and disorders. In this sense, the kidney deserves special attention since hypoxia can be considered an important factor in the pathophysiology of both acute kidney injury and chronic kidney disease. To provide better knowledge to unveil the molecular mechanisms involved, new studies are necessary. In this sense, this work aims to study, for the first time, an in vitro model of hypoxia-induced metabolic alterations in human proximal tubular HK-2 cells because renal proximal tubules are particularly susceptible to hypoxia. Different groups of cells, cultivated under control and hypoxia conditions at 0.5, 5, 24, and 48 h, were investigated using untargeted metabolomic approaches based on reversed-phase liquid chromatography-mass spectrometry. Both intracellular and extracellular fluids were studied to obtain a large metabolite coverage. On the other hand, multivariate and univariate analyses were carried out to find the differences among the cell groups and to select the most relevant variables. The molecular features identified as affected metabolites were mainly amino acids and Amadori compounds. Insights about their biological relevance are also provided.