Liquid Chromatography-high Resolution Research Articles

Alpibectir: Early Qualitative and Quantitative Metabolic Profiling from a First-Time-in-Human Study by Combining 19F-NMR (Nuclear Magnetic Resonance), 1H-NMR, and High-Resolution Mass Spectrometric Analyses.

Alpibectir (also known as BVL-GSK098 and GSK3729098) is a new chemical entity (NCE) with a novel mechanism for the treatment of tuberculosis. The disposition of alpibectir was determined in subjects from a first-time-in-human trial after a single oral dose of 40 mg and after 7 days repeat dosing at 30 mg. Here we present a combined approach of 19F-NMR (nuclear magnetic resonance), 1H-NMR, and high-resolution mass spectrometry (HRMS) to confidently determine the human metabolic fate of alpibectir. Utilizing multiple sites of fluorination in the molecule, it was possible to fractionate human urine and plasma to confidently detect and quantify the metabolite responses using 19F-NMR. Qualitative detection and structural characterization of F-containing NMR fractions were performed using complementary high-resolution ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) analyses to further add confidence to the metabolite responses in these fractions. Subsequent 1H-NMR then provided unequivocal standard-free structural confirmation for key metabolites, which would not be possible with conventional radioactivity detection and LC-MS/MS techniques. Alpibectir was shown to undergo extensive hydrolysis of the central amide moiety, where the resultant N-dealkylated amine and trifluorobutyric acid products were detected initially by unbiased 19F-NMR detection along with major downstream biotransformations to form a carbamoyl glucuronide conjugate and trifluoroacetic acid, respectively. Parallel UHPLC-MS/MS analyses provided confirmatory or additional structural characterization only where relevant. These concerted data allowed for the qualitative metabolic profile and quantitative determination of drug-related material (DRM) in urine and plasma, along with the percentage of dose excreted in urine, to be reported in a comprehensive, efficient, and data-led manner. SIGNIFICANCE STATEMENT: Combining the selectivity of 19F-NMR (nuclear magnetic resonance) for unfractionated samples as first-intent, data-led sample fractionation prior to 19F-NMR and structure-rich 1H-NMR detection, along with the sensitivity of high-resolution ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS), a novel alternative for time-efficient detection and quantification of drug-related material (DRM) in human without use of radiolabeled drug is reported. This allowed more complete data rationalization of human metabolism, permitting early risk assessment and progression of the development of antitubercular agent, alpibectir.

Revealing mechanism of phenol-amine reaction to form humus in compost based on high-resolution liquid chromatography mass spectrometry and spectroscopy

Humus is the stable form of carbon storage in straw compost. The phenol-amine reaction is a pathway for humus formation in straw compost. In this study, two reaction systems, GP group (pyrogallol and glycine) and GCP group (catechol, pyrogallol, and glycine), were constructed in a simulated composting environment and revealed the molecular binding mechanism of the phenol-amine reaction through spectroscopy and mass spectrometry. The results showed that phenolic self-polymerization was faster than phenol-amine reaction. Therefore, the aromatization degree of GP was 27.14 % higher than that of GCP. The phenol-amine reaction first produced fulvic acid, and then formed humus units rich in active functional group structures (i.e., phenolic hydroxyl and carboxyl groups). These units further captured small molecule compounds to form humic acid eventually. This study would provide theoretical support for exploring the humus formation process and the promotion of straw humification by adding phenol or amino acids to compost.

Metabolite profiling of chemically modified oligonucleotides in rat liver homogenates using hydrophilic interaction liquid chromatography-high resolution mass spectrometry

Chemically modified oligonucleotide is a rapidly emerging field of biotherapeutics. The evaluation of the metabolic stability of therapeutic oligonucleotides is critical. The current methods are limited to the ion-pairing reversed phase chromatographic techniques. Due to complex chemical modifications of therapeutic oligonucleotides and diverse structural changes in their metabolites, comprehensive metabolite profiling is still challenging. Therefore, an alternative analytical method for the metabolism study of oligonucleotides is urgently needed. In this study, a novel hydrophilic interaction liquid chromatography-high resolution mass spectrometry (HILIC-HRMS) method was developed and applied to the metabolism study of two chemically modified oligonucleotides, i.e., N11-GalNAc (phosphorothioate, 2′-F, 2′-OMe, and 3′-GalNAc) and N9 (phosphorothioate, 2′-F), in rat liver homogenates. Highly broad retention of metabolites on the HILIC column was achieved, with truncated metabolite having a single nucleotide being detected. A stepped normalized collisional energy (NCE) in HRMS led to characteristic c/y, d/y, and b/y fragment ion series, and diagnostic fragment ions for linker and GalNAc, which covered the whole sequence of oligonucleotides. A total number of twenty-seven and twenty-nine metabolites were identified in rat liver homogenates for N11-GalNAc and N9, respectively, by using the isotopic envelope of the precursor ion and stepped NCE-based sequence mapping data. The time-dependent production of metabolites was observed. The UCU sequence with the uniform 2′-F modification on ribose was identified as the major metabolic site for N11-GalNAc, and the phosphodiester bonds between nucleosides involving unmodified uracil were identified as the metabolic soft sites for N9. The developed HILIC-HRMS method provided a high coverage of various oligonucleotide metabolites. Characteristic fragment ions enable sequence mapping and therefore unambiguous metabolite identifications. This approach can be broadly applicable to the metabolism study of chemically modified oligonucleotides and the identification of their metabolic soft sites.

Identification of Secondary Metabolites from Actinomycetes Isolated from the Hilly Region of Nepal

Actinomycetes are a unique class of Gram-positive bacteria with a fungus-like filamentous mycelium. They are often called ‘antibiotics factories’ because they can produce many potent secondary metabolites. At present, multidrug-resistant (MDR) pathogens are the main problem for humans and animals and to overcome this problem, more potent antibiotics are urgently required. Fortunately, Nepal has great geographical and climatic diversity serving as a home for various actinomycetes. This study identified several actinomycetes using morphological and biochemical assays from seven soil samples collected from different elevations in Nepal. The primary objective of this study was to screen the potent metabolites-producing actinomycetes. For this purpose, antimicrobial assays of seven isolates were carried out against Escherichia coli ATCC 25922, Salmonella typhi ATCC 14028, Shigella sonnei ATCC 25931, and Staphylococcus aureus ATCC 43300. The sample BT36 demonstrated the highest zone of inhibition against the tested microorganisms among others. Similarly, minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of all isolates were carried out. Among them, the MIC of samples BT36, PT7, and AB1 were found to be 1.952 mg/mL, 0.012 mg/mL, and 0.029 mg/mL, respectively. Ethyl acetate extracts of resulting potent isolates PT7 and AB1 were subjected to mass spectrometric analysis. A total of 22 bioactive compounds were annotated from liquid chromatography-high resolution mass spectroscopy (LC-HRMS), including epopromycin A, myxopyronin B, gilvocarcin HE, and okilactomycin A. It is concluded that this study will be useful in setting up a strategy to isolate useful secondary metabolites from soil microbes from the hilly region of Nepal.

Identification of major degradation products of Clorsulon drug substance including its degradation pathways by high resolution mass spectrometry and NMR

Clorsulon is an effective anthelmintic drug substance extensively used in the treatment of parasitic infestations in both cattle and sheep. An in-depth investigation of Clorsulon’s degradation products (DPs) was carried out through forced degradation study to comprehend its degradation path. A total of eight degradation products were separated under various stress degradation conditions. Structural elucidation of these DPs was conducted using ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS), and their fragmentation patterns were compared to that of the parent compound. Adequate amount of DP-4 was isolated and purified by semi-preparative high-performance liquid chromatography (HPLC) methods. Subsequently, it was examined in detail using both 1D and 2D NMR (nuclear magnetic resonance spectroscopy). Most probable mechanistic pathways for the formation of degradation products under various stress degradation conditions were proposed to better understand the degradation profile. Based on the results of the stress study, Clorsulon drug substance was found to be unstable under photolytic and oxidative conditions. Understanding Clorsulon's degradation pathway is essential for determining shelf-life prediction of the finished product, safety and efficacy assurance, and guiding the development of stable, high-quality formulations.

Abstract PO4-07-02: Development of an Artificial Intelligence-based breast cancer detection model using Plasma Lipidomic Signature

Abstract Background: Mammography is the current diagnostic standard for breast cancer screening and monitoring. However, accessibility challenges, accuracy issues and patient discomfort all contribute to reduced patient compliance and utilization, resulting in a need for more effective diagnostic tools. An artificial intelligence (AI)-based lipidomic blood test may add significant value to early breast cancer detection rate and improve outcomes for patients. We have previously reported a series of lipidomic studies (n=793) and derived a lipid signature from plasma-enriched extracellular vesicles (EVs) that effectively distinguished people with localized breast cancer from cancer-free controls. Here we report the development of a breast cancer detection AI model from lipidomic data assessed directly using plasma samples. Methods: Lipids in both EVs and plasma collected from fasted breast cancer and control blood samples (n=256) were extracted and analysed by liquid chromatography-high resolution mass spectrometry (LC-HRAM-MS). Over 400 manually curated lipids were quantified. A bootstrapped analysis using Boruta, a robust and statistically rigorous feature selection algorithm based on random forest feature importance, was employed to identify cancer discriminatory lipid signatures in EV and plasma lipidomes consistently selected across 2000 bootstrap samples. The resulting lipid signature was then used to train an ensemble of 18 distinct machine learning models for cancer status prediction using a majority vote to aggregate the individual predictions. Model performance and variability were assessed over 2000 iterations of leave-group-out cross-validation (LGOCV) using an 80/20 train-test split. Average patient-level predictions across LGOCV iterations were recorded for both EV-and plasma-derived models and the two modalities were compared using an exact paired samples test (McNemar’s test). Results: Both the EV- and plasma-derived lipid signatures performed well in distinguishing breast cancer samples from controls. The development of a bioinformatics AI pipeline enabled the creation of a robust ensemble model achieving an F1 score of 0.89 in plasma with LGOCV. The final plasma ensemble predictive performance of 86.1% (±4.5%) in accuracy, 91.4% (±5.4%) in sensitivity, and 78.7% (±8.6%) specificity was achieved, which is comparable to that of EV (accuracy: 86.1±4.4%, sensitivity: 90.4±5.3%, specificity: 80.2±8.7%). Paired samples analysis using McNemar’s test indicated no significant differences between models trained on EV- and plasma-derived lipid signatures in either the sensitivity (p=0.65), specificity (p=0.49), or accuracy (p=0.42). Conclusion: The initial study demonstrated the high performance of a plasma-enriched extracellular vesicle-derived lipid biomarker signature for early breast cancer detection. Direct assessment of the lipidomic signature from plasma showed promise in simplifying the test. Assessing plasma directly offered advantages in terms of scalability, higher throughput, and ease of implementation. Further verification of the lipid signature in an upcoming study involving 500 plasma samples is planned. Ongoing studies will further optimize the plasma lipidomic signature and strengthen our AI pipeline. These findings support the potential clinical application of AI-based lipidomic profiling as a blood-based screening tool for breast cancer detection. Citation Format: Ameline Lim, Cheka Kehelpannala, Fatemeh Vafaee, Forrest Koch, Dana Pascovici, Desmond Li, Kerry Heffernan, Gillian Lamoury, Amani Batarseh, Bruce Mann. Development of an Artificial Intelligence-based breast cancer detection model using Plasma Lipidomic Signature [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-07-02.

Untargeted metabolomics using liquid chromatography-high resolution mass spectrometry and chemometrics for analysis of non-halal meats adulteration in beef meat.

The adulteration of raw beef (BMr) with dog meat (DMr) and pork (PMr) becomes a serious problem because it is associated with halal status, quality, and safety of meats. This research aimed to develop an effective authentication method to detect non-halal meats (dog meat and pork) in beef using metabolomics approach. Liquid chromatography-high resolution mass spectrometry (LC-HRMS) using untargeted approach combined with chemometrics was applied for analysis non-halal meats in BMr. The untargeted metabolomics approach successfully identified various metabolites in BMr DMr, PMr, and their mixtures. The discrimination and classification between authentic BMr and those adulterated with DMr and PMr were successfully determined using partial least square-discriminant analysis (PLS-DA) with high accuracy. All BMr samples containing non-halal meats could be differentiated from authentic BMr. A number of discriminating metabolites with potential as biomarkers to discriminate BMr in the mixtures with DMr and PMr could be identified from the analysis of variable importance for projection value. Partial least square (PLS) and orthogonal PLS (OPLS) regression using discriminating metabolites showed high accuracy (R2>0.990) and high precision (both RMSEC and RMSEE <5%) in predicting the concentration of DMr and PMr present in beef indicating that the discriminating metabolites were good predictors. The developed untargeted LC-HRMS metabolomics and chemometrics successfully identified non-halal meats adulteration (DMr and PMr) in beef with high sensitivity up to 0.1% (w/w). A combination of LC-HRMS untargeted metabolomic and chemometrics promises to be an effective analytical technique for halal authenticity testing of meats. This method could be further standardized and proposed as a method for halal authentication of meats.

The screening method for 39 phytotoxins and mycotoxins in blood and urine with liquid chromatography-high resolution mass spectrometry

BackgroundPoisonings caused by plant toxins and mycotoxins occur frequently, which do great harm to human health and social public health safety. When a poisoning incident occurs, biological samples are commonly be used to conduct the detection of toxic substances and their metabolites for targeted clinical treatment and incident analysis. ObjectiveTo establish an efficient and accurate analysis method of 39 phytotoxins and mycotoxins in blood and urine by high performance liquid chromatography quadrupole tandem orbitrap mass spectrometry (HPLC-Orbitrap MS). MethodAfter 3 mL of methanol being added to 1 mL blood and urine respectively for extraction and protein precipitation, the supernatant was injected into HPLC-Orbitrap MS for analysis. The phytotoxins and mycotoxins were separated by Hypersil GOLD PFP column with gradient elution using methanol-5 mmol/L ammonium acetate as mobile phase. The data were collected in ESI positive ion mode using Full MS/dd-MS2 for mass spectrometry detection. ResultThe mass database of 39 phytotoxins and mycotoxins was developed, and accurate qualitative analysis can be obtained by matching with the database using the proposed identification criteria. Limit of detections (LODs) were 1.34 × 10−4 ∼ 1.92 ng/mL and 1.92 × 10−4 ∼ 9.80 ng/mL for blood and urine samples, respectively. Limits of quantification (LOQ) of toxins in blood and urine ranged from 4.47 × 10−4 ∼ 6.32 ng/mL and 6.39 × 10−4 ∼ 32.67 ng/mL, respectively. Intra-day relative standard deviations (RSDs) were 0.79 % ∼ 10.90 %, and inter-day RSDs were 1.08 % ∼ 18.93 %. The recoveries can reach 90 % ∼ 110 % with matrix matching calibration curves. ConclusionThe established method is simple and rapid to operate, which can complete the sample analysis within 30 min, providing technical support for clinical poisoning treatment and public health poisoning analysis.

The Metabolic and Lipidomic Fingerprint of Torin1 Exposure in Mouse Embryonic Fibroblasts Using Untargeted Metabolomics.

Torin1, a selective kinase inhibitor targeting the mammalian target of rapamycin (mTOR), remains widely used in autophagy research due to its potent autophagy-inducing abilities, regardless of its unspecific properties. Recognizing the impact of mTOR inhibition on metabolism, our objective was to develop a reliable and thorough untargeted metabolomics workflow to study torin1-induced metabolic changes in mouse embryonic fibroblast (MEF) cells. Crucially, our quality assurance and quality control (QA/QC) protocols were designed to increase confidence in the reported findings by reducing the likelihood of false positives, including a validation experiment replicating all experimental steps from sample preparation to data analysis. This study investigated the metabolic fingerprint of torin1 exposure by using liquid chromatography-high resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics platforms. Our workflow identified 67 altered metabolites after torin1 exposure, combining univariate and multivariate statistics and the implementation of a validation experiment. In particular, intracellular ceramides, diglycerides, phosphatidylcholines, phosphatidylethanolamines, glutathione, and 5'-methylthioadenosine were downregulated. Lyso-phosphatidylcholines, lyso-phosphatidylethanolamines, glycerophosphocholine, triglycerides, inosine, and hypoxanthine were upregulated. Further biochemical pathway analyses provided deeper insights into the reported changes. Ultimately, our study provides a valuable workflow that can be implemented for future investigations into the effects of other compounds, including more specific autophagy modulators.

A suspect screening strategy with automated data processing tools for the comprehensive detection of emerging chemical hazards in food

In a rapidly evolving agri-food landscape fraught with unforeseen chemical risks, the establishment of proactive analytical strategies become paramount to safeguard food safety and public health. Leveraging ultra-high-performance liquid chromatography high resolution tandem mass spectrometry (UHPLC-HRMS/MS), this study presents a comprehensive suspect screening strategy which was designed for the efficient detection of emerging contaminants in food. Employing a generic extraction protocol and an extensive suspect list, the strategy was implemented on representative food samples fortified at parts per billion (ppb) level. A notable range of the observed True Positive Rates (TPR) spanning 84%–100% underscores the strategy's robustness and versatility in accurately identifying a wide array of compounds in complex food matrices. Moreover, the integration of a python-powered graphical user interface (GUI) plays a pivotal role in automating data processing steps, streamlining data and facilitating data prioritisation through the application of a metabolomics-inspired approach. This enhancement significantly elevates the strategy's efficiency for high throughput analyses, thus reflecting a more agile approach in addressing emerging hazards.

Impact of four different extraction methods and three different reconstitution solvents on the untargeted metabolomics analysis of human and rat urine samples

Unsuitable sample preparation may result in loss of important analytes and consequently affect the outcome of untargeted metabolomics. Due to species differences, different sample preparations may be required within the same biological matrix.The study aimed to compare the in-house sample preparation method for urine with methods from literature and to investigate the transferability of sample preparation from human urine to rat urine. A total of 12 different conditions for protein precipitation were tested, combining four different extraction solvents and three different reconstitution solvents using an untargeted liquid-chromatography high resolution mass spectrometry (LC-HRMS) metabolomics analysis. Evaluation was done based on the impact on feature count, their detectability, as well as the reproducibility of selected compounds.Results showed that a combination of methanol as extraction and acetonitrile/water (75/25) as reconstitution solvent provided improved results at least regarding the total feature count. Additionally, it was found that a higher amount of methanol was most suitable for extraction of rat urine among the tested conditions. In comparison, human urine requires significantly less volume of extraction solvent.Overall, it is recommended to systematically optimize both, the extraction method, and the reconstitution solvent for the used biofluid and the individual analytical settings.

Improved analysis of grape seed extract by liquid chromatography–high resolution mass spectrometry (LC-HRMS) reveals that proanthocyanidin-protein interaction mechanisms in cream depend on degree of polymerization

This study aimed to comprehensively characterize chemical profiles of proanthocyanidins (PACs) from grape seed extract (GSE), examine their interactions with proteins in a cream system, and define the mechanisms mediating PAC-protein interactions. GSE PACs were fractionated and characterized by thiolysis followed by liquid chromatography–high resolution mass spectrometry (LC-HRMS) analysis. New PACs with a degree of polymerization (DP) up to 16 were identified by improved HRMS data processing methods. In the model cream system, high-DP PACs exhibited greater precipitation capacity and protein binding than low-DP PACs. Low-DP PACs primarily engaged in hydrogen bonding, while high-DP PACs predominantly utilized multiple hydrophobic interaction sites to form cream protein aggregates. Furthermore, particle size and viscosity measurement of cream revealed a progressively DP-dependent increase in aggregated fat globules and cream viscosity. These findings enhanced our understanding of PACs’ structural intricacies and highlighted their functional role as PAC-rich natural ingredients in creating structured cream systems.

Deciphering the chemical constituents of Phlomis monocephala extracts using UHPLC-HRMS and their antioxidant, neuroprotective, antidiabetic and toxic potentials

In the current study, five different extracts (n-hexane, ethyl acetate, dichloromethane, ethanol, and water) of Phlomis monocephala were analyzed for the first time by ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) to identify their phenolic compounds. The extracts were also evaluated for their non-enzyme antioxidant activities using a variety of methods, including DPPH and, ABTS•+ scavenging activities, reduction of ferric (Fe3+), and cupric ions (Cu2+), metal chelating (MCA) activities, and phosphomolybdenum (PBD). Additionally, the extracts were assessed for their in vitro enzyme inhibition potential (acetylcholinesterase (AChE)/butyrylcholinesterase (BChE), α-amylase, α-glucosidase, and tyrosinase). Furthermore, cell viability was evaluated on HepG2 (human hepatocellular carcinoma), S17 cells (murine bone marrow stromal) and RAW (murine macrophages). UHPLC-HRMS allowed for the identification of 115 compounds from different chemical groups including flavonoids, iridoid glycosides, phenylethanoid glycosides and others. Most of the extracts had strong antioxidant potential and were rich in phenolic compounds. Ethanol and water extracts appear as the most promising antioxidant extracts providing the highest values followed by ethyl acetate by all the methodologies employed in this study. Furthermore, all the extracts, except the aqueous extract, inhibited all the enzymes significantly. Surprisingly, the aqueous extract did not show a prominent inhibition (low or no inhibition) against these enzymes. Hexane, ethyl acetate, and dichloromethane exhibited extremely significant cytotoxic effects against all cell lines at a higher concentration. The HepG2 cells demonstrated lower sensitivity to the extracts than RAW and S17 cells. In conclusion, P. monocephala can be considered as a valuable ingredient for the production of functional applications including nutraceuticals.

LC-MS/MS-QTOF Screening and Identification of Phenolic compounds from Ethyl Acetate Fraction of Madhuca longifolia Leaves

Natural products, particularly those derived from plants and microbes, offer an endless supply of unique compounds that can be converted into new pharmaceuticals. Due to their potential health benefits, bioactive components from herbs, particularly phenolics, have recently attracted a lot of interest. One of the multi-use forest tree species, Madhuca longifoliaJ. Koenig. (mahua), is found throughout much of South Asia and offers locals a source of food, fuel, fodder, and other non-timber forest products (NTFPs) in addition to timber. Almost all of this tree's components exhibit its therapeutic qualities.Mahua's phytochemical analysis reveals that it contains high levels of vitamins, alkaloids, sugar, glycosides, proteins, steroids, tannins, flavonoids, saponins, terpenoids, and phenolic compounds. These compounds are responsible for a variety of pharmacological properties, including anti-inflammatory, antioxidant, analgesic, antihyperglycemic, spasmolytic, hepatoprotective, anticonvulsant, anticancer, results of the High-Resolution Liquid Chromatography Mass Spectroscopy (HR-LCMS) analysis showed that plant extracts included a number of pharmaceutically significant chemicals. By comparing the weights and fragmentation patterns of the twenty-four (24) phenolic compounds in this work with those of published libraries, the LC-MS/MS method was used to screen and confirm them. The findings of this research support the usage of this plant as a source of bioactives and the beneficial effects of these compounds on human health.

Proteomics Analysis of the Polyomavirus DNA Replication Initiation Complex Reveals Novel Functional Phosphorylated Residues and Associated Proteins.

Polyomavirus (PyV) Large T-antigen (LT) is the major viral regulatory protein that targets numerous cellular pathways for cellular transformation and viral replication. LT directly recruits the cellular replication factors involved in initiation of viral DNA replication through mutual interactions between LT, DNA polymerase alpha-primase (Polprim), and single-stranded DNA binding complex, (RPA). Activities and interactions of these complexes are known to be modulated by post-translational modifications; however, high-sensitivity proteomic analyses of the PTMs and proteins associated have been lacking. High-resolution liquid chromatography tandem mass spectrometry (LC-MS/MS) of the immunoprecipitated factors (IPMS) identified 479 novel phosphorylated amino acid residues (PAARs) on the three factors; the function of one has been validated. IPMS revealed 374, 453, and 183 novel proteins associated with the three, respectively. A significant transcription-related process network identified by Gene Ontology (GO) enrichment analysis was unique to LT. Although unidentified by IPMS, the ETS protooncogene 1, transcription factor (ETS1) was significantly overconnected to our dataset indicating its involvement in PyV processes. This result was validated by demonstrating that ETS1 coimmunoprecipitates with LT. Identification of a novel PAAR that regulates PyV replication and LT's association with the protooncogenic Ets1 transcription factor demonstrates the value of these results for studies in PyV biology.

A Reliable Quantification of Cholesterol and 25-Hydroxycholesterol in Liposomal Adjuvant Formulation by Liquid Chromatography High-Resolution Tandem Mass Spectrometry.

Cholesterol, as one of the major components of liposomes, plays a critical role in modulating membrane bilayer permeability, fluidity, and structural stability. Controlling these quality attributes is essential to maintaining the efficacy and fitness of the liposomes in various applications. However, during the manufacture and storage of liposomes, cholesterol has a propensity to undergo oxidative degradation. Hence, an analytical tool that is capable of determining not only the identity and quantity of cholesterol but also its associated degradants is a prerequisite to effective process control and product quality and safety assessments. In this view, a new liquid chromatography electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) method with parallel reaction monitoring (PRM) was developed and qualified to accurately quantify cholesterol and monitor the formation of 25-hydroxycholesterol degradant in liposomal drug formulations without the use of an isotopic internal standard (IS). The method was qualified according to the FDA Quality Guidance for Industry: Q2(R1). Study results showed that the method presents good specificity for cholesterol and 25-hydroxycholesterol detection in the liposomal matrix, good sensitivity characterized by LOD/LOQ in the nanomolar range, and accuracy within the range of 80 to 120%. The described method enables accurate evaluation of in-process and product release samples of Army Liposome Formulation with QS21 (ALFQ).

Japanese Planocerid Flatworms: Difference in Composition of Tetrodotoxin and Its Analogs and the Effects of Ingestion by Toxin-Bearing Fishes in the Ryukyu Islands, Japan

Tetrodotoxin (TTX), known as pufferfish toxin, is a potent neurotoxin blocking sodium channels in muscle and nerve tissues. TTX has been detected in various taxa other than pufferfish, including marine polyclad flatworms, suggesting that pufferfish toxin accumulates in fish bodies via food webs. The composition of TTX and its analogs in the flatworm Planocera multitentaculata was identical to those in wild grass puffer Takifugu alboplumbeus. Previously, Planocera sp. from Okinawa Island, Japan, were reported to possess high level of TTX, but no information was available on TTX analogs in this species. Here we identified TTX and analogs in the planocerid flatworm using high-resolution liquid chromatography–mass spectrometry, and compared the composition of TTX and analogs with those of another toxic and non-toxic planocerid species. We show that the composition of TTX and several analogs, such as 5,6,11-trideoxyTTX, dideoxyTTXs, deoxyTTXs, and 11-norTTX-6(S)-ol, of Planocera sp. was identical to those of toxic species, but not to its non-toxic counterpart. The difference in the toxin composition was reflected in the phylogenetic relationship based on the mitochondrial genome sequence. A toxification experiment using predatory fish and egg plates of P. multitentaculata demonstrated that the composition of TTX and analogs in wild T. alboplumbeus juveniles was reproduced in artificially toxified pufferfish. Additionally, feeding on the flatworm egg plates enhanced the signal intensities of all TTX compounds in Chelonodon patoca and that of deoxyTTXs in Yongeichthys criniger.

Biomarker profiling in plants to distinguish between exposure to chlorine gas and bleach using LC-HRMS/MS and chemometrics

Since its first employment in World War I, chlorine gas has often been used as chemical warfare agent. Unfortunately, after suspected release, it is difficult to prove the use of chlorine as a chemical weapon and unambiguous verification is still challenging. Furthermore, similar evidence can be found for exposure to chlorine gas and other, less harmful chlorinating agents. Therefore, the current study aims to use untargeted high resolution mass spectrometric analysis of chlorinated biomarkers together with machine learning techniques to be able to differentiate between exposure of plants to various chlorinating agents. Green spire (Euonymus japonicus), stinging nettle (Urtica dioica), and feathergrass (Stipa tenuifolia) were exposed to 1000 and 7500 ppm chlorine gas and household bleach, pool bleach, and concentrated sodium hypochlorite. After sample preparation and digestion, the samples were analyzed by liquid chromatography high resolution tandem mass spectrometry (LC-HRMS/MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS). More than 150 chlorinated compounds including plant fatty acids, proteins, and DNA adducts were tentatively identified. Principal component analysis (PCA) and linear discriminant analysis (LDA) showed clear discrimination between chlorine gas and bleach exposure and grouping of the samples according to chlorine concentration and type of bleach. The identity of a set of novel biomarkers was confirmed using commercially available or synthetic reference standards. Chlorodopamine, dichlorodopamine, and trichlorodopamine were identified as specific markers for chlorine gas exposure. Fenclonine (Cl-Phe), 3-chlorotyrosine (Cl-Tyr), 3,5-dichlorotyrosine (di-Cl-Tyr), and 5-chlorocytosine (Cl-Cyt) were more abundantly present in plants after chlorine contact. In contrast, the DNA adduct 2-amino-6-chloropurine (Cl-Ade) was identified in both types of samples at a similar level. None of these chlorinated biomarkers were observed in untreated samples. The DNA adducts Cl-Cyt and Cl-Ade could clearly be identified even three months after the actual exposure. This study demonstrates the feasibility of forensic biomarker profiling in plants to distinguish between exposure to chlorine gas and bleach.

Identification of hot spots and co-occurrence patterns of activities on thyroid hormone receptor and transthyretin binding in passive samplers from Czech surface waters

One of the less studied in vitro biological activities in the aquatic environment are thyroid hormone receptor beta (TRβ)-mediated agonistic and antagonistic activities and transthyretin (TTR) binding activity. They were measured mostly using active sampling methods, but rarely found. It is unclear if these activities co-occur, and the drivers of the (anti-)TRβ activity are mostly unknown. Therefore, the main aim of the study was to determine (anti-)TRβ activities as well as transthyretin (TTR) binding activity in passive samplers from Czech surface waters in combination with the search for the effect drivers based on liquid chromatography-high resolution mass spectrometry (LC-HRMS) analysis by applying suspect screening. Passive samplers (polar organic chemical integrative samplers, POCIS) were deployed at twenty-one sites (all ends of watersheds and other important sites in Elbe River) in the Czech rivers. The (anti-)TRβ and TTR binding activity were measured using (anti-)TRβ-CALUX and TTR-TRβ-CALUX bioassays. Anti-TRβ activity was found at eight sites, and TTR binding activity co-occurred there at six of these sites. The co-occurrence of TRβ-mediated antagonistic activity and TTR binding indicate that they may have common effect drivers. No sample exhibited TRβ agonistic activity. The extract from the site Bílina River, the most burdened with anti-TRβ activity, was further successfully fractionated, and this activity was revealed in the fraction, where mid-polar compounds prevailed. However, the suspect LC-HRMS analysis did not reveal the chemical effect drivers. Our results showed that anti-TRβ activity can be found in surface waters by employing passive sampling and frequently co-occurs with TTR binding activity. Overall, the fractionation procedure and non-target data acquisition used in this study can serve as a basis for searching the effect drivers in future research.

Wound healing potential of Cystoseira/mesenchymal stem cells in immunosuppressed rats supported by overwhelming immuno-inflammatory crosstalk.

Wound healing, one of the most intricate and dynamic processes of the body, maintains skin integrity following trauma. One of the main issues that still exists is impaired wound healing, particularly for immunosuppressed patients. Recently, natural products from marine environments have been employed in wound-repairing activities. This work investigates the mesenchymal stem cells in the combined capacity of the bone marrow (BMMSC) for wound healing and Cystoseira sp. Algae extract in immunosuppressed rats. High-resolution liquid chromatography / MS investigation of Cystoseira extract revealed the prevalence of fatty acids that have wound-soothing potential. From constructed PPI network for wound healing and further analysis through molecular docking and molecular dynamics (MD) simulation experiments suggested that cystalgerone metabolite may be responsible for the wound healing-promoting effect of Cystoseira extract. According to the CD marker characterization of the BMMSC, 98.21% of them expressed CD90, and 97.1% expressed CD105. Sixteen d after immunity suppression (by 40 mg/kg hydrocortisone daily), an incision was made in the dorsal skin of the rat. The treatments were applied for 16 d and samples were taken from the tested groups on the 8th, 14th, and 16th days. The BMMSCs / Cystoseira group showed significantly improved wound closure, thickness, density of new layers, and skin elasticity than the control group (p < 0.001). The BMMSCs / Cystoseira combination significantly reduced the oxidative indicators, pro-inflammatory cytokines, and immune markers, according to the RT-PCR gene expression study. In order to delve deeper into the complex interconnections among wound healing-related biological targets and pinpoint key factors in this complex process, we engaged in network pharmacology and computational research. Subsequently, we conducted a comprehensive computational analysis, including reverse docking, free energy (ΔG) computation, and molecular dynamics simulations, on the molecular structures of the annotated compounds. The purpose of this investigation was to identify potential new targets for these chemicals as well as any potential interactions they may have with different signaling pathways related to the wound healing process. Our research indicates that the primary compounds of Cystoseira holds potential wound healing therapeutic activity. Although more safety testing and clinical studies are required, the combination has great potential for regenerative medicine and could be a revolutionary advance in the healing of the wounds of immunosuppressed patients.