The Quantification of Spike Proteins in the Inactivated SARS-CoV-2 Vaccines of the Prototype, Delta, and Omicron Variants by LC-MS.

Developing variant vaccines or multivalent vaccines is a feasible way to address the epidemic as the SARS-CoV-2 variants of concern (VOCs) posed an increased risk to global public health. The spike protein of the SARS-CoV-2 virus was usually used as the main antigen in many types of vaccines to produce neutralizing antibodies against the virus. However, the spike (S) proteins of different variants were only differentiated by a few amino acids, making it difficult to obtain specific antibodies that can distinguish different VOCs, thereby challenging the accurate distinction and quantification of the variants using immunological methods such as ELISA. Here, we established a method based on LC-MS to quantify the S proteins in inactivated monovalent vaccines or trivalent vaccines (prototype, Delta, and Omicron strains). By analyzing the S protein sequences of the prototype, Delta, and Omicron strains, we identified peptides that were different and specific among the three strains and synthesized them as references. The synthetic peptides were isotopically labeled as internal targets. Quantitative analysis was performed by calculating the ratio between the reference and internal target. The verification results have shown that the method we established had good specificity, accuracy, and precision. This method can not only accurately quantify the inactivated monovalent vaccine but also could be applied to each strain in inactivated trivalent SARS-CoV-2 vaccines. Hence, the LC-MS method established in this study can be applied to the quality control of monovalent and multivalent SARS-CoV-2 variation vaccines. By enabling more accurate quantification, it will help to improve the protection of the vaccine to some extent.

Simultaneous Determination of Ten Active Components From Jinhongtang Granule in Rat Plasma by LC-MS/MS and its Application to a Comparative Pharmacokinetic Study in Normal and Sepsis Rats In Vivo and In Vitro.

Jinhongtang granule (JHT) is a traditional Chinese medicine formula used for treatment of infection diseases including severe COVID-19. However, pharmacokinetics of JHT was unknown, especially in infection condition. A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed to simultaneously quantify ten active components form JHT in rat plasma. MS detection was performed by MRM scanning operating in the negative ionization mode. The method showed good linearity (r > 0.997). The accuracy, precision, matrix effect, recovery and stability were all satisfactory with current criterion. The method was successfully applied to compare the pharmacokinetic difference between normal and sepsis rats. The pharmacokinetic behaviors of analytes in sepsis rats were significantly different from those in normal rats. Cmax and AUC of rhein, emodin, aloe emodin, rhein-8-glucoside, aloe emodin 8-glucoside, protocatechuic acid, epicatechin and salidroside, were significantly increased in sepsis rats, except for 4-hydroxycinnamic acid and ferulic acid. In vitro intestinal absorption study using everted intestinal sac preparations indicated that the intestinal permeability was altered under sepsis. In conclusion, pharmacokinetic difference of JHT between normal and sepsis rats were evaluated for the first time, which provided useful information for the clinical application of JHT as an integrative therapy for severe and critical COVID-19.

Development and validation of method for analysis of favipiravir and remdesivir in volumetric absorptive microsampling with ultra high-performance liquid chromatography-tandem mass spectrophotometry.

Favipiravir and remdesivir are drugs to treat COVID-19. This study aims to find an optimum and validated method for simultaneous analysis of favipiravir and remdesivir in Volumetric Absorptive Microsampling (VAMS) by Ultra High-Performance Liquid Chromatography-Tandem Mass Spectrophotometry. The use of VAMS can be an advantage because the volume of blood is small and the sample preparation process is simple. Sample preparation was done by precipitation of protein using 500 µL of methanol. Analysis was carried out by ultra high-performance liquid chromatography-tandem mass spectrophotometry with ESI+ and MRM with m/z 157.9 > 112.92 for favipiravir, 603.09 > 200.005 for remdesivir, and at m/z 225.968 > 151.991 for acyclovir as the internal standard. The separation was carried out using an Acquity UPLC BEH C18 column (100 × 2.1 mm; 1.7 m), 0.2% formic acid-acetonitrile (50:50), flow rate was 0.15 mL/min, and column temperature was 50°C. The analytical method has been validated with the requirements issued by the Food and Drug Administration (2018) and European Medicine Agency (2011). The calibration range of favipiravir is 0.5-160 µg/mL and 0.002-8 µg/mL for remdesivir.

Determination of 25 quaternary ammonium compounds in sludge by liquid chromatography-mass spectrometry.

With the pandemic of COVID-19, the application of quaternary ammonium compounds (QACs), which can be used in SARS-CoV-2 disinfection products, has increased substantially. QACs cumulated in sewer system are ultimately deposited and enriched in sludge. QACs in the environment can adversely affect human health and the environment. In this study, a liquid chromatography-mass spectrometry method was established for the simultaneous determination of 25 QACs in sludge samples. Ultrasonic extraction and filtration of the samples was performed using a 50 mM hydrochloric acid-methanol solution. The samples were separated by liquid chromatography and detected in multiple reaction monitoring mode. The matrix effects of the sludge on the 25 QACs ranged from - 25.5% to 7.2%. All substances showed good linearity in the range of 0.5-100 ng/mL, with all determination coefficients (R2) greater than 0.999. The method detection limits (MDLs) were 9.0 ng/g for alkyltrimethylammonium chloride (ATMAC), 3.0 ng/g for benzylalkyldimethylammonium chloride (BAC), and 3.0 ng/g for dialkyldimethylammonium chloride (DADMAC). The spiked recovery rates were in the range of 74-107%, while the relative standard deviations were in the range of 0.8-20.6%. Considering its sensitivity, accuracy, and easy operation, the proposed method in this study was used to determine 22 sludge samples collected from a comprehensive wastewater treatment plant. The results showed that the concentrations of ΣATMACs, ΣBACs, and ΣDADMACs were 19.684, 3.199, and 8.344 µg/g, respectively. The main components included ATMAC-C16, ATMAC-C18, ATMAC-C20, ATMAC-C22, BAC-C12, and DADMAC-C18:C18, with concentrations exceeding 1.0 µg/g. The concentration relationships of different components in the congeners showed that some components were of similar origin.

Understanding common population markers for SARS-CoV-2 RNA normalization in wastewater - A review.

Wastewater monitoring and epidemiology have seen renewed interest during the recent COVID-19 pandemic. As a result, there is an increasing need to normalize wastewater-derived viral loads in local populations. Chemical tracers, both exogenous and endogenous compounds, have proven to be more stable and reliable for normalization than biological indicators. However, differing instrumentation and extraction methods can make it difficult to compare results. This review examines current extraction and quantification methods for ten common population indicators: creatinine, coprostanol, nicotine, cotinine, sucralose, acesulfame, androstenedione 5-hydroindoleacetic acid (5-HIAA), caffeine, and 1,7-dimethyluric acid. Some wastewater parameters such as ammonia, total nitrogen, total phosphorus, and daily flowrate were also evaluated. The analytical methods included direct injection, dilute and shoot, liquid/liquid, and solid phase extraction (SPE). Creatine, acesulfame, nicotine, 5-HIAA and androstenedione have been analysed by direct injection into LC-MS; however, most authors prefer to include SPE steps to avoid matrix effects. Both LC-MS and GC-MS have been successfully used to quantify coprostanol in wastewater, and the other selected indicators have been quantified successfully with LC-MS. Acidification to stabilize the sample before freezing to maintain the integrity of samples has been reported to be beneficial. However, there are arguments both for and against working at acidic pHs. Wastewater parameters mentioned earlier are quick and easy to quantify, but the data does not always represent the human population effectively. A preference for population indicators originating solely from humans is apparent. This review summarises methods employed for chemical indicators in wastewater, provides a basis for choosing an appropriate extraction and analysis method, and highlights the utility of accurate chemical tracer data for wastewater-based epidemiology.

Untargeted metabolomics of COVID-19 patient serum reveals potential prognostic markers of both severity and outcome.

INTRODUCTION: The diagnosis of COVID-19 is normally based on the qualitative detection of viral nucleic acid sequences. Properties of the host response are not measured but are key in determining outcome. Although metabolic profiles are well suited to capture host state, most metabolomics studies are either underpowered, measure only a restricted subset of metabolites, compare infected individuals against uninfected control cohorts that are not suitably matched, or do not provide a compact predictive model. OBJECTIVES: Here we provide a well-powered, untargeted metabolomics assessment of 120 COVID-19 patient samples acquired at hospital admission. The study aims to predict the patient's infection severity (i.e., mild or severe) and potential outcome (i.e., discharged or deceased). METHODS: High resolution untargeted UHPLC-MS/MS analysis was performed on patient serum using both positive and negative ionization modes. A subset of 20 intermediary metabolites predictive of severity or outcome were selected based on univariate statistical significance and a multiple predictor Bayesian logistic regression model was created. RESULTS: The predictors were selected for their relevant biological function and include deoxycytidine and ureidopropionate (indirectly reflecting viral load), kynurenine (reflecting host inflammatory response), and multiple short chain acylcarnitines (energy metabolism) among others. Currently, this approach predicts outcome and severity with a Monte Carlo cross validated area under the ROC curve of 0.792 (SD 0.09) and 0.793 (SD 0.08), respectively. A blind validation study on an additional 90 patients predicted outcome and severity at ROC AUC of 0.83 (CI 0.74-0.91) and 0.76 (CI 0.67-0.86). CONCLUSION: Prognostic tests based on the markers discussed in this paper could allow improvement in the planning of COVID-19 patient treatment.

Metabolites and metabolomics in COVID-19

Metabolomics is a comprehensive approach for identifying, quantifying, and characterizing entire metabolites in a biological system using a high-throughput technique. Metabolomics has great potential in discovering biochemical pathways and pathway interactions, disease diagnosis, and biomarker discovery. Viral infections induce changes in the host cell metabolism resulting in cellular reprogramming. In COVID-19, the dysregulation of host metabolites has been implemented in various aspects including diagnosis and management. This chapter summarizes various applications of metabolites and metabolomics approaches in COVID-19. © 2023 Elsevier Inc. All rights reserved.

In-silico Discovery of Fungal Metabolites Bergenin, Quercitrin and Dihy-droartemisinin as Potential Inhibitors against Main Protease of SARS-CoV-2

Background: Emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has given rise to COVID-19 pandemic, which has become a wreaking havoc worldwide. Therefore, there is an urgent need to find out novel drugs to combat SARS-CoV-2 in-fection. In this backdrop, the present study aimed to assess potent bioactive compounds from different fungi as potential inhibitors of SARS-CoV-2 main protease (Mpro) using an in-silico analysis. Method(s): High-Resolution Liquid Chromatography Mass Spectrometry analysis (HR-LCMS) was used for the bioactive profiling of ethanolic crude extract of Dictyophora indusiata, Geastrum tri-plex and Cyathus stercoreus. Of which, only bergenin (D. indusiata), quercitrin (G. triplex) and di-hydroartemisinin (C. stercoreus) were selected based on their medicinal uses, binding score and the active site covered. The 6LU7, a protein crystallographic structure of SARS-CoV-2 Mpro, was docked with bergenin, quercitrin and dihydroartemisinin using Autodock 4.2. Result(s): A total of 118 bioactive compounds were analyzed from the crude extract of used fungi and identified using HR LC/MS analysis. The binding energies obtained were-7.86,-10.29 and-7.20 kcal/mol, respectively, after docking analysis. Bergenin, quercitrin and dihydroartemisinin formed hydrogen bond, electrostatic interactions and hydrophobic interactions with foremost active site amino acids THR190, GLU166, GLN189, GLY143, HIS163, HIS164, CYS145 and PHE140. Conclusion(s): Present investigation suggests that these three compounds may be used as alternative inhibitors against SARS-CoV-2 Mpro. However, further research is necessary to assess in vitro potential of these compounds. To the best of our knowledge, the present investigation reported these three bioactive compounds of fungal origin for the first time.Copyright © 2021 Bentham Science Publishers.

Identification of phytochemical compounds of Fagopyrum dibotrys and their targets by metabolomics, network pharmacology and molecular docking studies.

Acute lung injury (ALI) is a clinically severe lung illness with high incidence rate and mortality. Especially, coronavirus disease 2019 (COVID-19) poses a serious threat to world wide governmental fitness. It has distributed to almost from corner to corner of the universe, and the situation in the prevention and control of COVID-19 remains grave. Traditional Chinese medicine plays a vital role in the precaution and therapy of sicknesses. At present, there is a lack of drugs for treating these diseases, so it is necessary to develop drugs for treating COVID-19 related ALI. Fagopyrum dibotrys (D. Don) Hara is an annual plant of the Polygonaceae family and one of the long-history used traditional medicine in China. In recent years, its rhizomes (medicinal parts) have attracted the attention of scholars at home and abroad due to their significant anti-inflammatory, antibacterial and anticancer activities. It can work on SARS-COV-2 with numerous components, targets, and pathways, and has a certain effect on coronavirus disease 2019 (COVID-19) related acute lung injury (ALI). However, there are few systematic studies on its aerial parts (including stems and leaves) and its potential therapeutic mechanism has not been studied. The phytochemical constituents of rhizome of F. dibotrys were collected using TCMSP database. And metabolites of F. dibotrys' s aerial parts were detected by metabonomics. The phytochemical targets of F. dibotrys were predicted by the PharmMapper website tool. COVID-19 and ALI-related genes were retrieved from GeneCards. Cross targets and active phytochemicals of COVID-19 and ALI related genes in F. dibotrys were enriched by gene ontology (GO) and KEGG by metscape bioinformatics tools. The interplay network entre active phytochemicals and anti COVID-19 and ALI targets was established and broke down using Cytoscape software. Discovery Studio (version 2019) was used to perform molecular docking of crux active plant chemicals with anti COVID-19 and ALI targets. We identified 1136 chemicals from the aerial parts of F. dibotrys, among which 47 were active flavonoids and phenolic chemicals. A total of 61 chemicals were searched from the rhizome of F. dibotrys, and 15 of them were active chemicals. So there are 6 commonly key active chemicals at the aerial parts and the rhizome of F. dibotrys, 89 these phytochemicals's potential targets, and 211 COVID-19 and ALI related genes. GO enrichment bespoken that F. dibotrys might be involved in influencing gene targets contained numerous biological processes, for instance, negative regulation of megakaryocyte differentiation, regulation of DNA metabolic process, which could be put down to its anti COVID-19 associated ALI effects. KEGG pathway indicated that viral carcinogenesis, spliceosome, salmonella infection, coronavirus disease - COVID-19, legionellosis and human immunodeficiency virus 1 infection pathway are the primary pathways obsessed in the anti COVID-19 associated ALI effects of F. dibotrys. Molecular docking confirmed that the 6 critical active phytochemicals of F. dibotrys, such as luteolin, (+) -epicatechin, quercetin, isorhamnetin, (+) -catechin, and (-) -catechin gallate, can combine with kernel therapeutic targets NEDD8, SRPK1, DCUN1D1, and PARP1. In vitro activity experiments showed that the total antioxidant capacity of the aerial parts and rhizomes of F. dibotrys increased with the increase of concentration in a certain range. In addition, as a whole, the antioxidant capacity of the aerial part of F. dibotrys was stronger than that of the rhizome. Our research afford cues for farther exploration of the anti COVID-19 associated ALI chemical compositions and mechanisms of F. dibotrys and afford scientific foundation for progressing modern anti COVID-19 associated ALI drugs based on phytochemicals in F. dibotrys. We also fully developed the medicinal value of F. dibotrys' s aerial parts, which can effectively avoid the waste of resources. Meanwhile, our work provides a new strategy for integrating metabonomics, network pharmacology, and molecular docking techniques which was an efficient way for recognizing effective constituents and mechanisms valid to the pharmacologic actions of traditional Chinese medicine.

Proteomic characteristics and diagnostic potential of exhaled breath particles in patients with COVID-19.

BACKGROUND: SARS-CoV-2 has been shown to predominantly infect the airways and the respiratory tract and too often have an unpredictable and different pathologic pattern compared to other respiratory diseases. Current clinical diagnostical tools in pulmonary medicine expose patients to harmful radiation, are too unspecific or even invasive. Proteomic analysis of exhaled breath particles (EBPs) in contrast, are non-invasive, sample directly from the pathological source and presents as a novel explorative and diagnostical tool. METHODS: Patients with PCR-verified COVID-19 infection (COV-POS, n = 20), and patients with respiratory symptoms but with > 2 negative polymerase chain reaction (PCR) tests (COV-NEG, n = 16) and healthy controls (HCO, n = 12) were prospectively recruited. EBPs were collected using a "particles in exhaled air" (PExA 2.0) device. Particle per exhaled volume (PEV) and size distribution profiles were compared. Proteins were analyzed using liquid chromatography-mass spectrometry. A random forest machine learning classification model was then trained and validated on EBP data achieving an accuracy of 0.92. RESULTS: Significant increases in PEV and changes in size distribution profiles of EBPs was seen in COV-POS and COV-NEG compared to healthy controls. We achieved a deep proteome profiling of EBP across the three groups with proteins involved in immune activation, acute phase response, cell adhesion, blood coagulation, and known components of the respiratory tract lining fluid, among others. We demonstrated promising results for the use of an integrated EBP biomarker panel together with particle concentration for diagnosis of COVID-19 as well as a robust method for protein identification in EBPs. CONCLUSION: Our results demonstrate the promising potential for the use of EBP fingerprints in biomarker discovery and for diagnosing pulmonary diseases, rapidly and non-invasively with minimal patient discomfort.

LC-MS/MS: A sensitive and selective analytical technique to detect COVID-19 protein biomarkers in the early disease stage.

INTRODUCTION: The COVID-19 outbreak has put enormous pressure on the scientific community to detect infection rapidly, identify the status of disease severity, and provide an immediate vaccine/drug for the treatment. Relying on immunoassay and a real-time reverse transcription polymerase chain reaction (rRT-PCR) led to many false-negative and false-positive reports. Therefore, detecting biomarkers is an alternative and reliable approach for determining the infection, its severity, and disease progression. Recent advances in liquid chromatography and mass spectrometry (LC-MS/MS) enable the protein biomarkers even at low concentrations, thus facilitating clinicians to monitor the treatment in hospitals. AREAS COVERED: This review highlights the role of LC-MS/MS in identifying protein biomarkers and discusses the clinically significant protein biomarkers such as Serum amyloid A, Interleukin-6, C-Reactive Protein, Lactate dehydrogenase, D-dimer, cardiac troponin, ferritin, Alanine transaminase, Aspartate transaminase, gelsolin and galectin-3-binding protein in COVID-19, and their analysis by LC-MS/MS in the early stage. EXPERT OPINION: Clinical doctors monitor significant biomarkers to understand, stratify, and treat patients according to disease severity. Knowledge of clinically significant COVID-19 protein biomarkers is critical not only for COVID-19 caused by the coronavirus but also to prepare us for future pandemics of other diseases in detecting by LC-MS/MS at the early stages.

Analysis of Antimicrobials in Muscle and Drinking Water in Terms of Reducing the Need of Antimicrobial Use by Increasing the Health and Welfare of Pig and Broiler.

Antimicrobial residues may pose harmful effects on the health of consumers. At the same time, an adequate quality of drinking water for animals is one of the important element to ensure animal welfare and food without antibacterials. The presented study is aimed at estimating the residue levels of antibacterial compounds, such as penicillins, cephalosporin, macrolides, tetracyclines, quinolones, sulphonamides, aminoglycosides, diaminopirymidines, pleuromutilines and lincosamides in meat and on-farm drinking water samples using liquid chromatography-tandem mass spectrometry (LC-MS/MS), as a part of a surveillance system on pig and broiler farms within the project Healthy Livestock. A total of 870 samples of muscle from pig and broiler, as well as 229 water samples were analysed for antibiotic residues. Samples were collected from farms in EU countries in two steps, before and after implementation of a tailor-made health plan. In muscle samples, the detected concentrations of doxycycline in the post-intervention step (15.9-70.8 µg/kg) were lower than concentrations in the pre-intervention step (20.6-100 µg/kg). In water samples, doxycycline in an average concentration of 119 µg/L in the pre- and 23.1 µg/L in the post-intervention step, as well as enrofloxacin at concentrations of 170 µg/L in the pre- and 1.72 µg/L in the post-intervention step were quantified. Amoxicillin was only present before intervention. The obtained results confirm the effectiveness of the intervention actions. The concentrations of antibiotics in muscles and water were lower after implementation of a health plan on the farms.

A Simultaneous Extraction/Derivatization Strategy for Quantitation of Vitamin D in Dried Blood Spots Using LC-MS/MS: Application to Biomarker Study in Subjects Tested for SARS-CoV-2.

Vitamin D plays a critical role in bone development and maintenance, and in other physiological functions. The quantitation of endogenous levels of individual vitamin D and its metabolites is crucial for assessing several disease state conditions. With cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) leading to the coronavirus disease 2019 (COVID-19) pandemic, there are several studies that have associated lower levels of serum vitamin D with severity of infection in COVID-19 patients. In this context, we have developed and validated a robust LC-MS/MS method for simultaneous quantitation of vitamin D and its metabolites in human dried blood spot (DBS) obtained from participants tested for COVID-19. The chromatographic separation for vitamin D and metabolites was performed using an ACE Excel C18 PFP column protected with a C18 guard column (Phenomenex, Torrance, CA, USA). The mobile phase consisted of formic acid in water (0.1% v/v) as mobile phase A and formic acid in methanol (0.1% v/v) as mobile phase B, operated at a flow rate of 0.5 mL/min. Analysis was performed utilizing the LC-MS/MS technique. The method was sensitive with a limit of quantification of 0.78 ng/mL for all analytes, and had a large dynamic range (200 ng/mL) with a total run time of 11 min. The inter- and intraday accuracy and precision values met the acceptance criteria per the US Food and Drug Administration guidelines. Blood concentrations of 25(OH)D3, vitamin D3, 25(OH)D2, and vitamin D2 over a range of 2-195.6, 0.5-121.5, 0.6-54.9, and 0.5-23.9 ng/mL, respectively, were quantified in 909 DBS samples. In summary, our developed LC-MS/MS method may be used for quantification of vitamin D and its metabolites in DBS, and may be applied to investigations of the emerging role of these compounds in various physiological processes.

Classification of Common Food Lipid Sources Regarding Healthiness Using Advanced Lipidomics: A Four-Arm Crossover Study.

Prospective studies have failed to establish a causal relationship between animal fat intake and cardiovascular diseases in humans. Furthermore, the metabolic effects of different dietary sources remain unknown. In this four-arm crossover study, we investigated the impact of consuming cheese, beef, and pork meat on classic and new cardiovascular risk markers (obtained from lipidomics) in the context of a healthy diet. A total of 33 young healthy volunteers (23 women/10 men) were assigned to one out of four test diets in a Latin square design. Each test diet was consumed for 14 days, with a 2-week washout. Participants received a healthy diet plus Gouda- or Goutaler-type cheeses, pork, or beef meats. Before and after each diet, fasting blood samples were withdrawn. A reduction in total cholesterol and an increase in high density lipoprotein particle size were detected after all diets. Only the pork diet upregulated plasma unsaturated fatty acids and downregulated triglycerides species. Improvements in the lipoprotein profile and upregulation of circulating plasmalogen species were also observed after the pork diet. Our study suggests that, within the context of a healthy diet rich in micronutrients and fiber, the consumption of animal products, in particular pork meat, may not induce deleterious effects, and reducing the intake of animal products should not be regarded as a way of reducing cardiovascular risk in young individuals.

t6A and ms2t6A Modified Nucleosides in Serum and Urine as Strong Candidate Biomarkers of COVID-19 Infection and Severity.

SARS-CoV-2 infection alters cellular RNA content. Cellular RNAs are chemically modified and eventually degraded, depositing modified nucleosides into extracellular fluids such as serum and urine. Here we searched for COVID-19-specific changes in modified nucleoside levels contained in serum and urine of 308 COVID-19 patients using liquid chromatography-mass spectrometry (LC-MS). We found that two modified nucleosides, N6-threonylcarbamoyladenosine (t6A) and 2-methylthio-N6-threonylcarbamoyladenosine (ms2t6A), were elevated in serum and urine of COVID-19 patients. Moreover, these levels were associated with symptom severity and decreased upon recovery from COVID-19. In addition, the elevation of similarly modified nucleosides was observed regardless of COVID-19 variants. These findings illuminate specific modified RNA nucleosides in the extracellular fluids as biomarkers for COVID-19 infection and severity.

LC-MS/MS Determination of 88 Psychotropic Drugs in 1865 Hair Samples From Addicts in Drug Abstinence.

The emergence of novel drugs and the continuous expansion of the scope of the types of drugs under control have greatly increased requests for screening of a range of drugs in hair. Here, a multi-analyte method for the detection and quantification of 88 psychotropic drugs in the hair of addicts in drug abstinence was developed and fully validated using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Hair samples (25 mg) were washed, cut into pieces, cryogenically ground, and extracted in methanol. The extracted analytes were separated on an Allure PFPP column (100×2.1 mm, 5 mm i.d., Restek, USA) and analyzed by LC-MS/MS in multiple reaction monitoring mode. The limits of detection and limits of quantification ranged from 0.1 to 20 pg/mg and 0.2 to 50 pg/mg, respectively. The intra- and inter-assay precisions (RSD) of all analysis ranged from 0.9 to 14.9% and 1.9 to 15.9%, respectively. Accuracy values were 100±20%. The extraction recovery of quality control samples ranged from 50.9% to 99.6% for all analytes. The matrix effects for all analytes ranged from 46.8% to 99.7%. The method was successfully used to analyze 1,865 hair samples from addicts in drug rehabilitation at their own communities.. Among the samples, 129 cases were positive; the majority of positive cases were from males (78.29%), 92.25% of whom were over 35 years old. Traditional drugs, like methamphetamine and opioids, accounted for most positive cases, and 27 of the abstinence cases with a use history of methamphetamine were still positive. In addition to abused drugs, like methamphetamine, morphine, and cocaine, the sedative hypnotic and psychotherapeutic drugs, including clonazepam, alprazolam, estazolam, zolpidem, and quetiapine, were detected in 26% of the hair samples, suggesting that these addicts may have insomnia and mental problems such as depression and psychosis, probably due to the long-term effects of drugs and withdrawal reactions. Three synthetic cannabinoids were also detected in 4 (2.7%) cases. A total of 37 cases were positive for methadone, tramadol, and dextromethorphan, reflecting a new trend of alternative drug use when traditional drugs were not easy to obtain during the COVID-19 outbreak.

Green adherent degradation kinetics study of Nirmatrelvir, an oral anti-COVID-19: characterization of degradation products using LC-MS with insilico toxicity profile.

The SARS-CoV-2 virus sets up a global catastrophe, and countries all around the world made significant efforts to halt the spread. Nirmatrelvir (NMV) was lately approved by the FDA as a safe and well-tolerated oral direct-acting antiviral medication for SARS-CoV-2 virus infection. Therefore, a fast completely validated stability indicating method was established-for the first time- for NMV determination. The study used NaOH, HCl, neutral, H2O2, and sunlight to test NMV stability under various stress conditions followed by kinetics degradation investigation and derivation of Arrhenius plot. The analysis was performed using Agilent Zorbax Eclipse-C18 column (5 µm, 4.6 × 250 mm) with a mobile phase consisting of acetonitrile: 50 mM ammonium acetate, pH = 5 (50:50, v/v, respectively) at a flow rate of 1.0 mL/min with 5 min run time. Diode array detector (DAD) was set at 225 nm to quantify NMV at the concentration range of 5-500 µg/mL with LOD and LOQ of 0.6 and 2 µg/mL, respectively. Method's greenness was assessed using different metrics including Analytical Eco-Scale, Greenness Assessment Procedure Index, GAPI, and Analytical Greenness, AGREE. A thorough study of stress stability revealed that NMV was more susceptible to alkaline hydrolysis compared with acid hydrolysis. In contrast, it was found that NMV remained stable when subjected to oxidative, neutral, and sun-induced degradation conditions. Moreover, acid and alkali-induced hydrolysis were found to follow pseudo first order kinetics. Consequently, the half lifetime of the studied degradation conditions at room temperature were calculated using the Arrhenius plot. The mechanism of the degradation pathways under stress circumstances was proposed using LC-MS-UV. Toxicities of the proposed degradation products were assessed using ProTox-II, along with the parent medication NMV, and were shown to be hardly hazardous.

Development and Validation of an Innovative Analytical Approach for the Quantitation of Tris(Hydroxymethyl)Aminomethane (TRIS) in Pharmaceutical Formulations by Liquid Chromatography Tandem Mass Spectrometry.

A novel COVID-19 vaccine (BriLife®) has been developed by the Israel Institute for Biological Research (IIBR) to prevent the spread of the SARS-CoV-2 virus throughout the population in Israel. One of the components in the vaccine formulation is tris(hydroxymethyl)aminomethane (tromethamine, TRIS), a buffering agent. TRIS is a commonly used excipient in various approved parenteral medicinal products, including the mRNA COVID-19 vaccines produced by Pfizer/BioNtech and Moderna. TRIS is a hydrophilic basic compound that does not contain any chromophores/fluorophores and hence cannot be retained and detected by reverse-phase liquid chromatography (RPLC)-ultraviolet (UV)/fluorescence methods. Among the few extant methods for TRIS determination, all exhibit a lack of selectivity and/or sensitivity and require laborious sample treatment. In this study, LC−mass spectrometry (MS) with its inherent selectivity and sensitivity in the multiple reaction monitoring (MRM) mode was utilized, for the first time, as an alternative method for TRIS quantitation. Extensive validation of the developed method demonstrated suitable specificity, linearity, precision, accuracy and robustness over the investigated concentration range (1.2−4.8 mg/mL). Specifically, the R2 of the standard curve was >0.999, the recovery was >92%, and the coefficient of variance (%CV) was <12% and <6% for repeatability and intermediate precision, respectively. Moreover, the method was validated in accordance with strict Good Manufacturing Practice (GMP) guidelines. The developed method provides valuable tools that pharmaceutical companies can use for TRIS quantitation in vaccines and other pharmaceutical products.

Presence and toxicity of drugs used to treat SARS-CoV-2 in Llobregat River, Catalonia, Spain.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a strain of coronavirus that causes COVID-19 (coronavirus disease 2019), the respiratory illness responsible for the on-going COVID-19 pandemic. In March 2020, it was declared global pandemic, causing millions of deaths. An evident tendency of global pharmaceutical consumption due to COVID-19 pandemic should be seen worldwide, and this increase might suppose an environmental threat. Pharmaceuticals administrated at home or in pharmacies are excreted by faeces and urine after consumption, and wastewater treatment plants (WWTPs) are not able to remove all pharmaceuticals residues that eventually will end up in the aquatic media (rivers and sea). For this reason, analytical techniques such as liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) have become prominent to identify and quantify pharmaceuticals residues in aquatic matrices. In view of the scarce data on the occurrence of pharmaceuticals used as COVID-19 treatment, the aim of the present study was to evaluate the presence of these class of pharmaceuticals in river water which were dexamethasone, prednisone, ciprofloxacin, levofloxacin, remdesivir, ritonavir, lopinavir, acetaminophen, hydroxychloroquine, chloroquine and cloperastine, their toxicity in the aquatic environment using D. magna and to perform an exhaustive risk assessment in seven points of the Llobregat river basin. Dexamethasone, cloperastine and acetaminophen were the pharmaceuticals with higher concentrations, showing mean levels between 313 and 859 ng L-1.

Comprehensive investigation of pathway enrichment methods for functional interpretation of LC-MS global metabolomics data.

BACKGROUND: Global or untargeted metabolomics is widely used to comprehensively investigate metabolic profiles under various pathophysiological conditions such as inflammations, infections, responses to exposures or interactions with microbial communities. However, biological interpretation of global metabolomics data remains a daunting task. Recent years have seen growing applications of pathway enrichment analysis based on putative annotations of liquid chromatography coupled with mass spectrometry (LC-MS) peaks for functional interpretation of LC-MS-based global metabolomics data. However, due to intricate peak-metabolite and metabolite-pathway relationships, considerable variations are observed among results obtained using different approaches. There is an urgent need to benchmark these approaches to inform the best practices. RESULTS: We have conducted a benchmark study of common peak annotation approaches and pathway enrichment methods in current metabolomics studies. Representative approaches, including three peak annotation methods and four enrichment methods, were selected and benchmarked under different scenarios. Based on the results, we have provided a set of recommendations regarding peak annotation, ranking metrics and feature selection. The overall better performance was obtained for the mummichog approach. We have observed that a ~30% annotation rate is sufficient to achieve high recall (~90% based on mummichog), and using semi-annotated data improves functional interpretation. Based on the current platforms and enrichment methods, we further propose an identifiability index to indicate the possibility of a pathway being reliably identified. Finally, we evaluated all methods using 11 COVID-19 and 8 inflammatory bowel diseases (IBD) global metabolomics datasets.