Quantification of paracetamol and 5-oxoproline in serum by capillary electrophoresis: Implication for clinical toxicology

Novel COVID-19 biomarkers identified through multi-omics data analysis: N-acetyl-4-O-acetylneuraminic acid, N-acetyl-L-alanine, N-acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate

This study aims to apply machine learning models to identify new biomarkers associated with the early diagnosis and prognosis of SARS-CoV-2 infection.Plasma and serum samples from COVID-19 patients (mild, moderate, and severe), patients with other pneumonia (but with negative COVID-19 RT-PCR), and healthy volunteers (control) from hospitals in four different countries (China, Spain, France, and Italy) were analyzed by GC-MS, LC-MS, and NMR. Machine learning models (PCA and PLS-DA) were developed to predict the diagnosis and prognosis of COVID-19 and identify biomarkers associated with these outcomes.A total of 1410 patient samples were analyzed. The PLS-DA model presented a diagnostic and prognostic accuracy of around 95% of all analyzed data. A total of 23 biomarkers (e.g., spermidine, taurine, L-aspartic, L-glutamic, L-phenylalanine and xanthine, ornithine, and ribothimidine) have been identified as being associated with the diagnosis and prognosis of COVID-19. Additionally, we also identified for the first time five new biomarkers (N-Acetyl-4-O-acetylneuraminic acid, N-Acetyl-L-Alanine, N-Acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate) that are also associated with the severity and diagnosis of COVID-19. These five new biomarkers were elevated in severe COVID-19 patients compared to patients with mild disease or healthy volunteers.The PLS-DA model was able to predict the diagnosis and prognosis of COVID-19 around 95%. Additionally, our investigation pinpointed five novel potential biomarkers linked to the diagnosis and prognosis of COVID-19: N-Acetyl-4-O-acetylneuraminic acid, N-Acetyl-L-Alanine, N-Acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate. These biomarkers exhibited heightened levels in severe COVID-19 patients compared to those with mild COVID-19 or healthy volunteers.

Ambient ionisation mass spectrometry for drug and toxin analysis: A review of the recent literature

Ambient ionisation mass spectrometry (AIMS) is a form of mass spectrometry whereby analyte ionisation occurs outside of a vacuum source under ambient conditions. This enables the direct analysis of samples in their native state, with little or no sample preparation and without chromatographic separation. The removal of these steps facilitates a much faster analytical process, enabling the direct analysis of samples within minutes if not seconds. Consequently, AIMS has gained rapid popularity across a diverse range of applications, in particular the analysis of drugs and toxins. Numerous fields rely upon mass spectrometry for the detection and identification of drugs, including clinical diagnostics, forensic chemistry, and food safety. However, all of these fields are hindered by the time-consuming and laboratory-confined nature of traditional techniques. As such, the potential for AIMS to resolve these challenges has resulted in a growing interest in ambient ionisation for drug and toxin analysis. Since the early 2000s, forensic science, diagnostic testing, anti-doping, pharmaceuticals, environmental analysis and food safety have all seen a marked increase in AIMS applications, foreshadowing a new future for drug testing. In this review, some of the most promising AIMS techniques for drug analysis will be discussed, alongside different applications of AIMS published over a 5-year period, to provide a summary of the recent research activity for ambient ionisation for drug and toxin analysis.

A bibliometric analysis of graphene in acetaminophen detection: Current status, development, and future directions

Acetaminophen is a widely used analgesic throughout the world. Detection of acetaminophen has particular value in pharmacy and clinics. Electrochemical sensors assembled with advanced materials are an effective method for the rapid detection of acetaminophen. Graphene-based carbon nanomaterials have been extensively investigated for potential analytical applications in the last decade. In this article, we selected papers containing both graphene and acetaminophen. Bibliometrics was used to analyze the relationships and trends among these papers. The results show that the topic has grown at a high rate since 2009. Among them, the detection of acetaminophen by an electrochemical sensor based on graphene is the most important direction. Graphene has moved from being a primary sensing material to a substrate for immobilization of other active ingredients. In addition, the degradation of acetaminophen using graphene-modified electrodes is also an important direction. We analyzed the research history and current status of this topic through bibliometrics. Authors, institutions, countries, and key literature were discussed. We also proposed perspectives for this topic.

Metabolomics analysis identifies glutamic acid and cystine imbalances in COVID-19 patients without comorbid conditions. Implications on redox homeostasis and COVID-19 pathophysiology

It is well known that the presence of comorbidities and age-related health issues may hide biochemical and metabolic features triggered by SARS-CoV-2 infection and other diseases associated to hypoxia, as they are by themselves chronic inflammatory conditions that may potentially disturb metabolic homeostasis and thereby negatively impact on COVID-19 progression. To unveil the metabolic abnormalities inherent to hypoxemia caused by COVID-19, we here applied gas chromatography coupled to mass spectrometry to analyze the main metabolic changes exhibited by a population of male patients less than 50 years of age with mild/moderate and severe COVID-19 without pre-existing comorbidities known to predispose to life-threatening complications from this infection. Several differences in serum levels of particular metabolites between normal controls and patients with COVID-19 as well as between mild/moderate and severe COVID-19 were identified. These included increased glutamic acid and reduced glutamine, cystine, threonic acid, and proline levels. In particular, using the entire metabolomic fingerprint obtained, we observed that glutamine/glutamate metabolism was associated with disease severity as patients in the severe COVID-19 group presented the lowest and higher serum levels of these amino acids, respectively. These data highlight the hypoxia-derived metabolic alterations provoked by SARS-CoV-2 infection in the absence of pre-existing co-morbidities as well as the value of amino acid metabolism in determining reactive oxygen species recycling pathways, which when impaired may lead to increased oxidation of proteins and cell damage. They also provide insights on new supportive therapies for COVID-19 and other disorders that involve altered redox homeostasis and lower oxygen levels that may lead to better outcomes of disease severity.

High humidity aggravates the severity of arthritis in collagen-induced arthritis mice by upregulating xylitol and L-pyroglutamic acid

Background

Humidity was an unfavorable factor for patients with rheumatoid arthritis (RA). RA disease activity was severe in high humidity conditions. However, there is no evidence to demonstrate the effects of humidity on arthritis in the animal experiments and explore its relevant mechanism.

Methods

Using the DBA/1 mice, this study addressed the effects of a high humidity (80 ± 5%) on arthritis in collagen-induced arthritis (CIA) mice. Then, this study used the gas chromatography-mass spectrometer (GC-MS) to explore alterations in serum metabolome caused by the high humidity. Furthermore, xylitol and L-pyroglutamic acid, which were both significantly upregulated by the high humidity, were selected to further study their effects on arthritis in the CIA mice.

Results

The high humidity (80 ± 5%) could aggravate arthritis variables including increasing arthritis score and swelling, serum autoantibodies (anti-COII and anti-CCP), and proinflammatory cytokines (IL-6, IL-17A, and G-CSF). In addition, the high humidity could cause significant alterations in serum metabolome in the CIA mice. Xylitol and L-pyroglutamic acid were the representative serum metabolites that were significantly upregulated by the high humidity. Further experiments demonstrated that the supplementation of 0.4 mg/mL xylitol in drinking water after inducing the CIA model and 2.0 mg/mL in drinking water before inducing the CIA model could both aggravate arthritis in the CIA mice.

Conclusions

These data demonstrated that high humidity was not beneficial for arthritis development and its mechanism might be associated with xylitol and L-pyroglutamic acid.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-021-02681-x.

Selective Electrochemical Sensing Platform Based on the Synergy between Carbon Black and Single-Crystalline Bismuth Sulfide for Rapid Analysis of Antipyretic Drugs

Nanomaterials are of significant interest in acetaminophen (APAP) detection in pharmaceutical samples. Herein, a carbon black/single-crystalline rodlike bismuth sulfide (CB/Bi₂S₃) composite prepared by an ultrasonic method is reported and utilized for the rapid analysis of APAP. The highly oriented edge reactive sites of the CB/Bi₂S₃ composite promoted synergy and good electrochemical sensing performance with a fast electron transfer rate and low overpotential (0.35 V). Therefore, a CB/Bi₂S₃ composite-modified glassy carbon electrode (GCE) was applied to the selective determination of APAP by the voltammetric technique. The CB/Bi₂S₃ composite-modified electrode showed the lowest limit of detection of APAP (1.9 nM) with excellent sensitivity. The proposed CB/Bi₂S₃/GCE platform exhibited high selectivity, excellent stability (87.15%), and reproducibility. Also, the CB/Bi₂S₃/GCE sensor was then successfully used to analyze an APAP pharmaceutical sample and exhibited satisfactory outcomes. Therefore, the CB/Bi₂S₃-modified GCE sensor platform would be a low-cost and robust GCE electrode material for APAP detection.

Ratiometric electrochemical sensing based on Mo2C for detection of acetaminophen

In this work, MoO2 nanoparticles were synthesized and annealed to form Mo2C nanoparticles. This is the first report of a ratiometric electrochemical sensor (R-ECS) for the detection of acetaminophen (AP), in which Mo2C is used as the sensing agent and ferrocene (FC) is used as an internal reference. FC (100 μM) is added directly to the electrolyte solution for convenient operation. The synthesized materials were fully characterized with respect to composition, morphology and electrochemical performance. The oxidation peak potentials of FC (0.196 V) and AP (0.364 V) can be completely separated by the Mo2C modified glassy carbon electrode, and their ratiometric signals are used for the quantification of AP. It was found that the oxidation peak currents of AP at separated potentials on Mo2C/GCE are linear with concentration in the range of 0.5-600 μM, and the detection limit is 0.029 μM (S/N = 3). Mo2C/GCE exhibited decent repeatability, reproducibility, stability, and selectivity. The sensor was then applied to measure AP in tap water and river water.

Causal relationships between genetically determined metabolites and human intelligence: a Mendelian randomization study

Intelligence predicts important life and health outcomes, but the biological mechanisms underlying differences in intelligence are not yet understood. The use of genetically determined metabotypes (GDMs) to understand the role of genetic and environmental factors, and their interactions, in human complex traits has been recently proposed. However, this strategy has not been applied to human intelligence. Here we implemented a two-sample Mendelian randomization (MR) analysis using GDMs to assess the causal relationships between genetically determined metabolites and human intelligence. The standard inverse-variance weighted (IVW) method was used for the primary MR analysis and three additional MR methods (MR-Egger, weighted median, and MR-PRESSO) were used for sensitivity analyses. Using 25 genetic variants as instrumental variables (IVs), our study found that 5-oxoproline was associated with better performance in human intelligence tests (P_IVW = 9.25 × 10^-5). The causal relationship was robust when sensitivity analyses were applied (P_MR-Egger = 0.0001, P_{Weighted median} = 6.29 × 10^-6, P_MR-PRESSO = 0.0007), and repeated analysis yielded consistent result (P_IVW = 0.0087). Similarly, also dihomo-linoleate (20:2n6) and p-acetamidophenylglucuronide showed robust association with intelligence. Our study provides novel insight by integrating genomics and metabolomics to estimate causal effects of genetically determined metabolites on human intelligence, which help to understanding of the biological mechanisms related to human intelligence.

Comparative Electroanalytical Studies of Graphite Flake and Multilayer Graphene Paste Electrodes

In this paper, the fabrication, surface characterisation and electrochemical properties of graphite flake (GFPE) and multilayer graphene (MLGPE) paste electrodes are described. The Raman investigations and scanning electron microscopy were used to analyze and compare structure of both carbon materials. The electroanalytical performance of both electrodes was examined and compared on the basis of the square-wave and cyclic voltammetric behavior of acetaminophen and model redox systems. Results of those studies revealed that GFPE has a larger electroactive surface area and better conductive properties, whilst MLGPE demonstrate better analytical characteristic in case of acetaminophen (AC) determination. AC determination was developed using square wave voltammetry (SWV) and square wave stripping voltammetry (SWSV). For both working electrodes, the process of accumulation enabled us to obtain an extended linear range and to lower the detection limit. In pharmaceutical formulations, AC was determined with good recovery.

Causal effects of serum metabolites on amyotrophic lateral sclerosis: A Mendelian randomization study

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder that is affected by both genetic and environmental factors. Nowadays, OMIC technologies, such as genomics and metabolomics, are providing a systematic readout of genetic structures and physiological states for understanding human diseases. However, the comprehensive analysis of cross-omics is often lacking. Here, we conducted a Mendelian randomization analysis to provide a comprehensive analysis of metabolomics and genomics to estimate the causal relationships between non-targeted human serum metabolites and the development of ALS. Using genetic variants as predictors, our study detected 18 metabolites that might have causal effects on the development of ALS, including a group of gamma-glutamyl amino acids. Our findings suggested that glutathione metabolism dysfunction might be involved in the pathogenesis of ALS. Furthermore, our study provides a novel method to understand the pathogenesis of human diseases and develop therapeutic strategies for diseases by combining metabolomics with genomics.

Simultaneous electrochemical detection of levodapa, paracetamol and l-tyrosine based on multi-walled carbon nanotubes

A novel electrochemical sensor for the simultaneous detection of levodopa, paracetamol and l-tyrosine was developed based on multi-walled carbon nanotubes. The sensor has the merits of wide linear range, good selectivity and good reproducibility.

Capillary electrophoresis for the investigation of two novel aminoalkanol derivatives of 1,7-diethyl-8,9-diphenyl-4-azatricyclo[5.2.1.02,6] dec-8-ene-3,5,10-trione as potential anticancer drugs in water solution and serum

A simple, rapid, capillary zone electrophoresis method was developed and validated for the analysis of two novel aminoalkanol derivatives (I) and (II) of 1,7-diethyl-8,9-diphenyl-4-azatricyclo[5.2.1.0^2,6 ]dec-8-ene-3,5,10-trione, which were found in earlier studies as potential anticancer drugs. Samples were analyzed to demonstrate the specificity and stability indicating ability of the developed method. The samples were extracted using n-hexane-ethyl acetate mixture in the ratio of 90:10. Electrophoretic separation was performed on a eCAP fused silica capillary (37 cm length, 50 µm inside diameter) with a 50 mM tetraborate buffer as a background electrolyte adjusted to pH = 2.5. The separation time of (I) and (II) was achieved within 7 min. In addition, analysis of the two compounds in the serum was conducted. Limits of detection of (I) and (II) by UV absorbance at 200 nm were achieved in the range of 87.4-92.1 ng/mL. The sufficient recovery was observed in the range of 90.3-99.8%. The quantification limits for the compounds (I) and (II) were in the range of 279.71-291.03 ng/mL, respectively. The method has been successfully applied to the analysis of compounds (I) and (II) in serum samples.

5-Oxoproline concentrations in acute acetaminophen overdose

Introduction: Several reports describe high anion gap metabolic acidosis with 5-oxoproline (5-OP) after acetaminophen exposure, including therapeutic use of acetaminophen. The mechanism may involve disordered glutathione metabolism. It is unknown whether acute acetaminophen overdose consistently causes elevations in 5-oxoproline concentration.Methods: We enrolled 23 consecutive adult and adolescent patients with measureable plasma APAP after acute APAP overdose. We used plasma left over in the laboratory after blood tests obtained in clinical care of the patients. We measured plasma [5-OP] by GC/MS. We compared the [5-OP] to laboratory results obtained in the care of these patients to search for correlations. The study had IRB approval.Results: Eighteen patients had non-detectable or normal (<100 μmol/L) 5-oxoproline concentrations. Six more patients had concentrations between 100 μmol/L and 300 μmol/L. There was no significant correlation of 5-OP with APAP, AST, ALT, creatinine, anion gap, INR, or total bilirubin.Discussion: Limitations of the study include small sample size and treatment with IV N-acetylcysteine for all patients with APAP concentrations above the 150 line of the Rumack Matthew nomogram or with hepatotoxicity. We believe that inherited enzyme deficiencies more likely explain cases of 5-oxoprolinemia.Conclusion: Acetaminophen overdose generally results in normal 5-oxoproline concentrations with some patients having slightly elevated 5-oxoproline concentrations.