An Agile and Accurate Approach for N-Nitrosamines Detection and Quantification in Medicines by DART-MS.

N-nitrosamines (NAs) are prevalent mutagenic impurities in various consumer products. Their discovery in valsartan-containing medicines in 2018 prompted global regulatory agencies to set guidelines on their presence and permissible levels in pharmaceuticals. In order to determine the NAs content in medicines, efficient and sensitive analytical methods have been developed based on mass spectrometry techniques. Direct analysis in real time-mass spectrometry (DART-MS) has emerged as a prominent ambient ionization technique for pharmaceutical analysis due to its high-throughput capability, simplicity, and minimal sample preparation requirements. Thus, in this study DART-MS was evaluated for the screening and quantification of NAs in medicines. DART-MS analyses were conducted in positive ion mode, for both direct tablet analysis and solution analysis. The analytical performance was evaluated regarding linearity, precision, accuracy, limits of detection, and quantification. The DART-MS proved to be suitable for the determination of NAs in medicines, whether through direct tablet analysis or solution analysis. The analytical performance demonstrated linearity in the range from 1.00 to 200.00 ng mL-1, limits of quantification about 1.00 ng mL-1, precision and accuracy lower than 15%, and no significant matrix effect for six drug-related NAs. In conclusion, the DART-MS technique demonstrated to be an alternative method to determine NAs in medicines, aligning with the principles of green chemistry.

Multinational experience with next-generation sequencing: opportunity to identify transthyretin cardiac amyloidosis and Fabry disease.

Background: Sarcomeric hypertrophic cardiomyopathy (HCM) must be differentiated from phenotypically similar conditions because clinical management and prognosis may greatly differ. Patients with unexplained left ventricular hypertrophy require an early, confirmed genetic diagnosis through diagnostic or predictive genetic testing. We tested the feasibility and practicality of the application of a 17-gene next-generation sequencing (NGS) panel to detect the most common genetic causes of HCM and HCM phenocopies, including treatable phenocopies, and report detection rates. Identification of transthyretin cardiac amyloidosis (ATTR-CA) and Fabry disease (FD) is essential because of the availability of disease-specific therapy. Early initiation of these treatments may lead to better clinical outcomes. Methods: In this international, multicenter, cross-sectional pilot study, peripheral dried blood spot samples from patients of cardiology clinics with an unexplained increased left ventricular wall thickness (LVWT) of ≥13 mm in one or more left ventricular myocardial segments (measured by imaging methods) were analyzed at a central laboratory. NGS included the detection of known splice regions and flanking regions of 17 genes using the Illumina NextSeq 500 and NovaSeq 6000 sequencing systems. Results: Samples for NGS screening were collected between May 2019 and October 2020 at cardiology clinics in Colombia, Brazil, Mexico, Turkey, Israel, and Saudi Arabia. Out of 535 samples, 128 (23.9%) samples tested positive for pathogenic/likely pathogenic genetic variants associated with HCM or HCM phenocopies with double pathogenic/likely pathogenic variants detected in four samples. Among the 132 (24.7%) detected variants, 115 (21.5%) variants were associated with HCM and 17 (3.2%) variants with HCM phenocopies. Variants in MYH7 (n=60, 11.2%) and MYBPC3 (n=41, 7.7%) were the most common HCM variants. The HCM phenocopy variants included variants in the TTR (n=7, 1.3%) and GLA (n=2, 0.4%) genes. The mean (standard deviation) ages of patients with HCM or HCM phenocopy variants, including TTR and GLA variants, were 42.8 (17.9), 54.6 (17.0), and 69.0 (1.4) years, respectively. Conclusions: The overall diagnostic yield of 24.7% indicates that the screening strategy effectively identified the most common forms of HCM and HCM phenocopies among geographically dispersed patients. The results underscore the importance of including ATTR-CA (TTR variants) and FD (GLA variants), which are treatable disorders, in the differential diagnosis of patients with increased LVWT of unknown etiology.

Development of a reliable method for determination of N-nitrosamines in medicines using disposable pipette extraction and HPLC-MS analysis.

This study outlines the development and optimization of an analytical method using Disposable Pipette Extraction (DPX) followed by high performance liquid chromatography-mass spectrometry (HPLC-MS) analysis to determine NAs in medicines. HPLC-MS analysis utilized a reversed-phase and positive mode electrospray ion source. DPX parameters were optimized through univariate and multivariate analyses, including extraction phase, desorption solvent, sample pH, equilibrium time, and extraction/desorption cycles. The optimized conditions included a C18 extraction phase, methanol desorption solvent, pH at 7, an equilibrium time of 30 seconds, 2 extraction cycles, and 5 desorption cycles. Considering this method, it was possible to achieve a sample preparation step for the analysis of NAs in medicines using a minimal amount of extraction phase, sample, and desorption solvent. Furthermore, the total extraction procedure enables the extraction of NAs in around 4 minutes with NA recovery up to 98%. Analytical performance demonstrated precision and accuracy below 15% and a quantification limit of 1 ng mL-1, meeting validation requirements set by regulations worldwide. Thus, the DPX/HPLC-MS technique offers a faster and cost-effective method for analyzing NAs in medicines compared to traditional approaches. Besides, this method reduces solvent consumption and residue generation, enhancing environmental sustainability according to green chemistry principles.

Prediction of edapho-climatic parameters in the incidence of Campylobacter spp. in northwestern Mexico.

Campylobacter spp. is one of the main causes of enteric zoonotic infections worldwide. In Mexico, although a commonly detected pathogen in both children and adults, there is limited surveillance and few studies. The northern part of Mexico stands out for an unnoticed outbreak of Campylobacter jejuni due to contaminated drinking water, which caused an abrupt increase in Guillain-Barré syndrome in the local population. Although it is suggested that its distribution in nature is related to edaphic and climatic factors, this relationship is scarcely known. To understand abiotic factors driving the occurrence and prevalence of Campylobacter spp. in three municipalities from three states in northwestern Mexico (Chihuahua, Sonora, and Baja California), we used the kriging interpolation method of unsampled areas and the correspondence analysis of 23 environmental variables. Of the three municipalities evaluated, Janos in Chihuahua (CHIH), has the highest number of geographic areas classified as high and medium incidence, followed by Santa Cruz, Sonora (SON) and Mexicali, Baja California (BC). Mexicali (BC) edaphic variables limit the potential incidence of the bacterium, mainly due to the lack of soil moisture and its difficulty of surviving on dry surfaces, related to electrical conductivity and salinity. Janos (CHIH) presents limitations in terms of soil water availability, although its presence is more heterogeneous (2 to 8 months). Santa Cruz (SON) has the highest soil water availability (4 to 5 months), and presents pH, texture and low percentage of salinity conditions for the potential incidence of Campylobacter spp. Mexicali (BC) reports a temperature in the warmest month of up to 43°C, which could influence the presence of thermophilic species. The annual precipitation is another limiting factor for the potential incidence of Campylobacter spp. since it does not exceed 509.5 mm, contributing to Janos (CHIH) as the municipality with the highest potential incidence of this bacterium.

Host metabolomic responses in recurrent P. vivax malaria.

Malaria is the leading parasitic disease worldwide, with P. vivax being a major challenge for its control. Several studies have indicated metabolomics as a promising tool for combating the disease. The study evaluated plasma metabolomic profiles of patients with recurrent and non-recurrent P. vivax malaria in the Brazilian Amazon. Metabolites extracted from the plasma of P. vivax-infected patients were subjected to LC-MS analysis. Untargeted metabolomics was applied to investigate the metabolic profile of the plasma in the two groups. Overall, 51 recurrent and 59 non-recurrent patients were included in the study. Longitudinal metabolomic analysis revealed 52 and 37 significant metabolite features from the recurrent and non-recurrent participants, respectively. Recurrence was associated with disturbances in eicosanoid metabolism. Comparison between groups suggest alterations in vitamin B6 (pyridoxine) metabolism, tyrosine metabolism, 3-oxo-10-octadecatrienoate ß-oxidation, and alkaloid biosynthesis II. Integrative network analysis revealed enrichment of other metabolic pathways for the recurrent phenotype, including the butanoate metabolism, aspartate and asparagine metabolism, and N-glycan biosynthesis. The metabolites and metabolic pathways predicted in our study suggest potential biomarkers of recurrence and provide insights into targets for antimalarial development against P. vivax.

A multidisciplinary approach to analyze the antimicrobial resistance in natural ecosystems.

Antimicrobial Resistance (AMR) poses a global threat to both human health and environmental well-being. Our study delved into Costa Rican wildlife reserves, uncovering a substantial human impact on these ecosystems and underscoring the imperative to pinpoint AMR hotspots. Embracing a One Health perspective, we advocated for a comprehensive landscape analysis that intricately intertwined geographic, climatic, forest, and human factors. This study illuminated the link between laboratory results and observed patterns of antimicrobial use, thereby paving the way for sustainable solutions. Our innovative methodology involved deploying open-ended questions to explore antimicrobial usage across livestock activities, contributing to establishing a comprehensive methodology. Non-invasive sampling in wildlife emerged as a critical aspect, shedding light on areas contaminated by AMR. Feline species, positioned at the apex of the food chain, acted as sentinels for environmental health due to heightened exposure to improperly disposed waste. Regarding laboratory findings, each sample revealed the presence of at least one antimicrobial resistance gene (ARG). Notably, genes encoding resistance to tetracyclines dominated (94.9%), followed by beta-lactams (75.6%), sulfonamides (53.8%), aminoglycosides (51.3%), quinolones (44.9%), phenicols (25.6%), and macrolides (20.5%). Genes encoding polymyxins were not detected. Moreover, 66% of samples carried a multi-resistant microbiome, with 15% exhibiting resistance to three antimicrobial families and 51% to four. The absence of a correlation between forest coverage and ARG presence underscored the profound human impact on wildlife reserves, surpassing previous estimations. This environmental pressure could potentially modify microbiomes and resistomes in unknown ways. As not all antimicrobial families encoding ARGs were utilized by farmers, our next step involved evaluating other human activities to identify the primary sources of contamination. This comprehensive study contributed crucial insights into the intricate dynamics of AMR in natural ecosystems, paving the way for targeted interventions and sustainable coexistence.

Exploring salivary lipid profile changes in COVID-19 patients: Insights from mass spectrometry analysis.

The most common COVID-19 testing relies on the use of nasopharyngeal swabs. However, this sampling step is very uncomfortable and is one of the biggest challenges regarding population testing. In the present study, the use of saliva as an alternative sample for COVID-19 diagnosis was investigated. Therefore, high-resolution mass spectrometry analysis and chemometric approaches were applied to salivary lipid extracts. Two data organizations were used: classical MS data and pseudo-MS image datasets. The latter transformed MS data into pseudo-images, simplifying data interpretation. Classification models achieved high accuracy, with pseudo-MS image data performing exceptionally well. PLS-DA with OPSDA successfully separated COVID-19 and healthy groups, serving as a potential diagnostic tool. The most important lipids for COVID-19 classification were elucidated and include sphingolipids, ceramides, phospholipids, and glycerolipids. These lipids play a crucial role in viral replication and the inflammatory response. While pseudo-MS image data excelled in classification, it lacked the ability to annotate important variables, which was performed using classical MS data. These findings have the potential to improve clinical diagnosis using rapid, non-invasive testing methods and accurate high-volume results.

Molecularly imprinted polymers in online extraction liquid chromatography methods: Current advances and recent applications.

BACKGROUND: One of the primary objectives in green analytical practices is the seamless integration of extraction and separation steps, resulting in the augmentation of both analytical throughput and method performance. Consequently, the exploration of prospective sorbent materials has drawn significant attention in the scientific community, particularly concerning the potential for online procedures. Employing the optimal sorbent material within an automated analytical approach holds the promise of elevating the precision of the analytical evaluation. Molecularly imprinted polymers (MIPs) excel in specific analyte interaction within complex matrices. However, MIPs' full potential was not widely exploring especially for online analytical methodologies. RESULTS: Here is presented a comprehensive overview of the current applications of MIPs as sorbent materials within integrated and automated separation methodologies applied to diverse matrices including biological, food, and environmental samples. Notably, their primary advantage, as evidenced in the literature, lies in their exceptional selectivity for the target analyte discussed according to the adopted synthesis protocol. Furthermore, the literature discussed here illustrates the versatility of MIPs in terms of modification with one or more phases which are so-called hybrid materials, such as molecularly imprinted monoliths (MIM), the molecularly imprinted ionic liquid polymer (IL-MIP), and restricted access to molecularly imprinted polymer (RAMIP). The reported advantages enhance their applicability in integrated and automated separation procedures, especially to the column switching methods, across a broader spectrum of applications. SIGNIFICANCE: This revision aims to demonstrate the MIP's potential as a sorbent phase in integrated and automated methods, this comprehensive overview of MIP polymers in integrated and automated separation methodologies can be used as a valuable guide, inspiring new research on developing novel horizons for MIP applications to have their potential emphasized in analytical science and enhanced to the great analytical methods achievement.

Methylprednisolone therapy induces differential metabolic trajectories in severe COVID-19 patients.

IMPORTANCE: The SARS-CoV-2 virus infection in humans induces significant inflammatory and systemic reactions and complications of which corticosteroids like methylprednisolone have been recommended as treatment. Our understanding of the metabolic and metabolomic pathway dysregulations while using intravenous corticosteroids in COVID-19 is limited. This study will help enlighten the metabolic and metabolomic pathway dysregulations underlying high daily doses of intravenous methylprednisolone in COVID-19 patients compared to those receiving placebo. The information on key metabolites and pathways identified in this study together with the crosstalk with the inflammation and biochemistry components may be used, in the future, to leverage the use of methylprednisolone in any future pandemics from the coronavirus family.

Oral Squamous Cell Carcinoma Lipid Evaluation in Gingiva Tissue Stored in TRIzol via Shotgun Lipidomics and MALDI Mass Spectrometry Imaging.

Oral squamous cell carcinoma (OSCC) is the prevalent type of oral cavity cancer, requiring precise, accurate, and affordable diagnosis to identify the disease in early stages, Comprehending the differences in lipid profiles between healthy and cancerous tissues encompasses great relevance in identifying biomarker candidates and enhancing the odds of successful cancer treatment. Therefore, the present study evaluates the analytical performance of simultaneous mRNA and lipid extraction in gingiva tissue from healthy patients and patients diagnosed with OSCC preserved in TRIzol reagent. The data was analyzed by partial least-squares discriminant analysis (PLS-DA) and confirmed via matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). The lipid extraction in TRIzol solution was linear in a range from 330 to 2000 ng mL-1, r2 > 0.99, intra and interday precision and accuracy <15%, and absolute recovery values ranging from 90 to 110%. The most important lipids for tumor classification were evaluated by MALDI-MSI, revealing that the lipids responsible for distinguishing the OSCC group are more prevalent in the cancerous tissue in contrast to the healthy group. The results exhibit the possibilities to do transcriptomic and lipidomic analyses in the same sample and point out important candidates related to the presence of OSCC.

Bioanalytical LC-QTOF/MS Method for a N-phenylpiperazine Derivate (LQFM05): An Anxiolytic- and Antidepressant-like Prototype Drug Applied to Pharmacokinetic and Biodistribution Studies.

The LQFM05 is a prototype drug designed for treatment of psychiatric disorders, such as schizophrenia, exhibiting anxiolytic- and antidepressant-like (12 or 24 µmol/kg) effects in classical behavioral tests. In order to evaluate its pharmacokinetic properties, a liquid chromatography method coupled to a quadrupole time of flight mass spectrometry system (LC-QTOF/MS) was developed and fully validated for LQFM05 analysis in rat plasma and tissue samples (brain, heart, liver, and kidneys). Liquid-liquid extraction, solid phase extraction and protein precipitation were assessed as clean-up procedures for biological samples and analyte enrichment. Plasma and tissue samples underwent protein precipitation as a preliminary step, using acetonitrile. Linearity was fully demonstrated for the dynamic range (10.0 to 900.0 ng/mL), with r2 values higher than 0.99 (RSDslope ≤ 2%, Fcal < Ftab, Ccal < Ctab). Biodistribution studies in rats revealed high brain tissue concentrations (12.4 µg/g), suggesting elevated drug affinity to the main therapeutic target tissue, showing a blood partition coefficient of 1.9. Kidneys also showed great exposure and tissue affinity, suggesting a potential extrahepatic clearance. Likewise, all examined tissues exhibited satisfactory LQFMF05 distribution. The mass fragmentation spectrum indicated the presence of its main metabolite, LQFM235, yielded by high hepatic hydroxylation route, an equally bioactive derivative. Lastly, the developed LC-QTOF/MS method was shown to be sensitive (LOQ = 10 ng/mL), precise and accurate for LQFM05 determination in tissue homogenates and plasma samples.

Desorption electrospray ionization and matrix-assisted laser desorption/ionization as imaging approaches for biological samples analysis.

The imaging of biological tissues can offer valuable information about the sample composition, which improves the understanding of analyte distribution in such complex samples. Different approaches using mass spectrometry imaging (MSI), also known as imaging mass spectrometry (IMS), enabled the visualization of the distribution of numerous metabolites, drugs, lipids, and glycans in biological samples. The high sensitivity and multiple analyte evaluation/visualization in a single sample provided by MSI methods lead to various advantages and overcome drawbacks of classical microscopy techniques. In this context, the application of MSI methods, such as desorption electrospray ionization-MSI (DESI-MSI) and matrix-assisted laser desorption/ionization-MSI (MALDI-MSI), has significantly contributed to this field. This review discusses the evaluation of exogenous and endogenous molecules in biological samples using DESI and MALDI imaging. It offers rare technical insights not commonly found in the literature (scanning speed and geometric parameters), making it a comprehensive guide for applying these techniques step-by-step. Furthermore, we provide an in-depth discussion of recent research findings on using these methods to study biological tissues.

Assessing the Effectiveness of Chemical Marker Extraction from Amazonian Plant Cupuassu (Theobroma grandiflorum) by PSI-HRMS/MS and LC-HRMS/MS.

Employing a combination of liquid chromatography electrospray ionization and paper spray ionization high-resolution tandem mass spectrometry, extracts from cupuassu (Theobroma grandiflorum) pulp prepared with either water, methanol, acetonitrile or combinations thereof were subjected to metabolite fingerprinting. Among the tested extractors, 100% methanol extracted preferentially phenols and cinnamic acids derivatives, whereas acetonitrile and acetonitrile/methanol were more effective in extracting terpenoids and flavonoids, respectively. And while liquid chromatography- mass spectrometry detected twice as many metabolites as paper spray ionization tandem mass spectrometry, the latter proved its potential as a screening technique. Comprehensive structural annotation showed a high production of terpenes, mainly oleanane triterpene derivatives. of the mass spectra Further, five major metabolites with known antioxidant activity, namely catechin, citric acid, epigallocatechin-3'-glucuronide, 5,7,8-trihydroxyflavanone, and asiatic acid, were subjected to molecular docking analysis using the antioxidative enzyme peroxiredoxin 5 (PRDX5) as a model receptor. Based on its excellent docking score, a pharmacophore model of 5,7,8-trihydroxyflavanone was generated, which may help the design of new antioxidants.

Integrated Metabolic and Inflammatory Signatures Associated with Severity of, Fatality of, and Recovery from COVID-19.

Severe manifestations of coronavirus disease 2019 (COVID-19) and mortality have been associated with physiological alterations that provide insights into the pathogenesis of the disease. Moreover, factors that drive recovery from COVID-19 can be explored to identify correlates of protection. The cellular metabolism represents a potential target to improve survival upon severe disease, but the associations between the metabolism and the inflammatory response during COVID-19 are not well defined. We analyzed blood laboratorial parameters, cytokines, and metabolomes of 150 individuals with mild to severe disease, of which 33 progressed to a fatal outcome. A subset of 20 individuals was followed up after hospital discharge and recovery from acute disease. We used hierarchical community networks to integrate metabolomics profiles with cytokines and markers of inflammation, coagulation, and tissue damage. Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) promotes significant alterations in the plasma metabolome, whose activity varies according to disease severity and correlates with oxygen saturation. Differential metabolism underlying death was marked by amino acids and related metabolites, such as glutamate, glutamyl-glutamate, and oxoproline, and lipids, including progesterone, phosphocholine, and lysophosphatidylcholines (lysoPCs). Individuals who recovered from severe disease displayed persistent alterations enriched for metabolism of purines and phosphatidylinositol phosphate and glycolysis. Recovery of mild disease was associated with vitamin E metabolism. Data integration shows that the metabolic response is a hub connecting other biological features during disease and recovery. Infection by SARS-CoV-2 induces concerted activity of metabolic and inflammatory responses that depend on disease severity and collectively predict clinical outcomes of COVID-19. IMPORTANCE COVID-19 is characterized by diverse clinical outcomes that include asymptomatic to mild manifestations or severe disease and death. Infection by SARS-CoV-2 activates inflammatory and metabolic responses that drive protection or pathology. How inflammation and metabolism communicate during COVID-19 is not well defined. We used high-resolution mass spectrometry to investigate small biochemical compounds (<1,500 Da) in plasma of individuals with COVID-19 and controls. Age, sex, and comorbidities have a profound effect on the plasma metabolites of individuals with COVID-19, but we identified significant activity of pathways and metabolites related to amino acids, lipids, nucleotides, and vitamins determined by disease severity, survival outcome, and recovery. Furthermore, we identified metabolites associated with acute-phase proteins and coagulation factors, which collectively identify individuals with severe disease or individuals who died of severe COVID-19. Our study suggests that manipulating specific metabolic pathways can be explored to prevent hyperinflammation, organ dysfunction, and death.

Bisphenol determination in UHT milk and packaging by paper spray ionization mass spectrometry.

This study evaluates the use of paper spray ionization mass spectrometry (PSI-MS) for rapid determination of bisphenol A (BPA) and bisphenol S (BPS) in UHT milk and milk packaging. The packages were analyzed by cutting the cartons into triangular shapes and submitting them to PSI-MS analysis. The milk samples were subjected to a simple liquid-liquid extraction and the supernatant was deposited onto a triangular paper that was subsequently used for PSI-MS analysis. In milk, BPS and BPA levels ranged from 60.0 to 150.8 ng mL-1. The LOD and LOQ values were 1.5 and 4.8 ng mL-1 for BPA, and 4.8 and 16.0 ng mL-1 for BPS, respectively. Linearity was R2 > 0.98 for both compounds. Precision values were below 20%, and recoveries close to 100%. The PSI-MS can be used as a simple, rapid, and accurate methodology to determine bisphenols in milk and milk packaging.

LC-HRMS/MS-Based Metabolomics Approaches Applied to the Detection of Antifungal Compounds and a Metabolic Dynamic Assessment of Orchidaceae.

The liquid chromatography-mass spectrometry (LC-MS)-based metabolomics approach is a powerful technology for discovering novel biologically active molecules. In this study, we investigated the metabolic profiling of Orchidaceae species using LC-HRMS/MS data combined with chemometric methods and dereplication tools to discover antifungal compounds. We analyze twenty ethanolic plant extracts from Vanda and Cattleya (Orchidaceae) genera. Molecular networking and chemometric methods were used to discriminate ions that differentiate healthy and fungal-infected plant samples. Fifty-three metabolites were rapidly annotated through spectral library matching and in silico fragmentation tools. The metabolomic profiling showed a large production of polyphenols, including flavonoids, phenolic acids, chromones, stilbenoids, and tannins, which varied in relative abundance across species. Considering the presence and abundance of metabolites in both groups of samples, we can infer that these constituents are associated with biochemical responses to microbial attacks. In addition, we evaluated the metabolic dynamic through the synthesis of stilbenoids in fungal-infected plants. The tricin derivative flavonoid- and the loliolide terpenoidfound only in healthy plant samples, are promising antifungal metabolites. LC-HRMS/MS, combined with state-of-the-art tools, proved to be a rapid and reliable technique for fingerprinting medicinal plants and discovering new hits and leads.

ICD indication in hypertrophic cardiomyopathy: which algorithm to use?

OBJECTIVE: This study aimed to evaluate the agreement in the indication of implantable cardioverter-defibrillators in patients with Hypertrophic cardiomyopathy, as per the 2014 European Society of Cardiology and 2020 American Heart Association recommendations, and evaluate fragmented QRS as a predictor of cardiovascular outcome. METHODS: Retrospective cohort with 81 patients was evaluated between 2019 and 2021. Patients with hypertrophic cardiomyopathy ≥16 years old were included. Exclusion criteria include secondary myocardiopathy and follow-up <1 year. Kappa coefficient was used to determine the agreement. Survival and incidence curves were determined by Kaplan-Meier method. A p<0.05 was considered significant. RESULTS: The fragmented QRS was identified in 44.4% of patients. There were no differences between patients with and without fragmented QRS regarding clinical parameters, echocardiography, fibrosis, and sudden cardiac death risk. During follow-up of 4.8±3.4 years, there was no sudden cardiac death, but 20.6% patients with implantable cardioverter-defibrillator had at least one appropriate shock. Three of the seven appropriate shocks occurred in European Society of Cardiology low- to moderate-risk patients. Three shocks occurred in moderate-risk patients and four in American Heart Association high-risk patients. Overall recommendations agreement was 64% with a kappa of 0.270 (p=0.007). C-statistic showed no differences regarding the incidence of appropriate shock (p=0.644). CONCLUSION: sudden cardiac death risk stratification algorithms present discrepancies in implantable cardioverter-defibrillator indication, both with low accuracy.

ICD indication in hypertrophic cardiomyopathy: which algorithm to use?

SUMMARY OBJECTIVE: This study aimed to evaluate the agreement in the indication of implantable cardioverter-defibrillators in patients with Hypertrophic cardiomyopathy, as per the 2014 European Society of Cardiology and 2020 American Heart Association recommendations, and evaluate fragmented QRS as a predictor of cardiovascular outcome. METHODS: Retrospective cohort with 81 patients was evaluated between 2019 and 2021. Patients with hypertrophic cardiomyopathy ≥16 years old were included. Exclusion criteria include secondary myocardiopathy and follow-up <1 year. Kappa coefficient was used to determine the agreement. Survival and incidence curves were determined by Kaplan-Meier method. A p<0.05 was considered significant. RESULTS: The fragmented QRS was identified in 44.4% of patients. There were no differences between patients with and without fragmented QRS regarding clinical parameters, echocardiography, fibrosis, and sudden cardiac death risk. During follow-up of 4.8±3.4 years, there was no sudden cardiac death, but 20.6% patients with implantable cardioverter-defibrillator had at least one appropriate shock. Three of the seven appropriate shocks occurred in European Society of Cardiology low- to moderate-risk patients. Three shocks occurred in moderate-risk patients and four in American Heart Association high-risk patients. Overall recommendations agreement was 64% with a kappa of 0.270 (p=0.007). C-statistic showed no differences regarding the incidence of appropriate shock (p=0.644). CONCLUSION: sudden cardiac death risk stratification algorithms present discrepancies in implantable cardioverter-defibrillator indication, both with low accuracy.

MALDI(+) FT-ICR Mass Spectrometry (MS) Combined with Machine Learning toward Saliva-Based Diagnostic Screening for COVID-19.

Rapid identification of existing respiratory viruses in biological samples is of utmost importance in strategies to combat pandemics. Inputting MALDI FT-ICR MS (matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry) data output into machine learning algorithms could hold promise in classifying positive samples for SARS-CoV-2. This study aimed to develop a fast and effective methodology to perform saliva-based screening of patients with suspected COVID-19, using the MALDI FT-ICR MS technique with a support vector machine (SVM). In the method optimization, the best sample preparation was obtained with the digestion of saliva in 10 µL of trypsin for 2 h and the MALDI analysis, which presented a satisfactory resolution for the analysis with 1 M. SVM models were created with data from the analysis of 97 samples that were designated as SARS-CoV-2 positives versus 52 negatives, confirmed by RT-PCR tests. SVM1 and SVM2 models showed the best results. The calibration group obtained 100% accuracy, and the test group 95.6% (SVM1) and 86.7% (SVM2). SVM1 selected 780 variables and has a false negative rate (FNR) of 0%, while SVM2 selected only two variables with a FNR of 3%. The proposed methodology suggests a promising tool to aid screening for COVID-19.

Electromembrane Extraction of Naphthenic Acids in Produced Water Followed by Ultra-High-Resolution Mass Spectrometry Analysis.

Naphthenic acids comprise one of the most toxic compounds of the produced water released from offshore oil platforms. Therefore, developing and applying faster, simpler, and more efficient analytical methods for analyzing naphthenic acids are urgently needed. Electromembrane extraction (EME) uses the electrokinetic migration of target ions through a porous membrane. Herein, the EME method was applied to extract naphthenic acids from produced water. The EME method was optimized, and the optimal conditions encompassed decanol as the organic solvent, the sample with pH 10.0, 5 min of extraction at 200 V, and the ratio 4:1 (borate buffer/matrix, v/v). Electrochemical impedance spectroscopy confirmed charged species' migration from produced water through the EME. Subsequently, all extracts were analyzed by ultra-high-resolution mass spectrometry. The EME efficiency was assessed by comparing the extraction results to the liquid-liquid extraction (LLE) method results. Analytical results showed good linearity for both solvent and matrix curves (R2 > 0.98). Low detection limits ranged from 0.10 to 0.13 µg mL-1 and quantification limits from 0.36 to 0.45 µg mL-1. Precision and accuracy values ranged from -13.3% to 16.5%. These values fit the proposed method, demonstrating that the EME was more efficient than LLE in naphthenic acid extraction. The EME method preferably extracted aromatic compounds with double-bond equivalence from 6 to 8. The EME coupled with ultra-high-resolution mass spectrometry was demonstrated as a promising analytical approach to naphthenic acid extraction as an efficient and more environmentally friendly alternative to conventional extraction methods.