HT SpaceM: A high-throughput and reproducible method for small-molecule single-cell metabolomics.

Single-cell metabolomics (SCM) promises to reveal metabolism in its complexity and heterogeneity, yet current methods struggle with detecting small-molecule metabolites, throughput, and reproducibility. Addressing these gaps, we developed HT SpaceM, a high-throughput SCM method combining cell preparation on custom glass slides, small-molecule matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (MS), and batch processing. We propose a unified framework covering quality control, characterization, structural validation, and differential and functional analyses.

Metabolomics-based liquid biopsy reflects molecular alterations induced by meningioma.

Meningiomas (MGMs) account for around 36% of all primary central nervous system tumors. Currently, imaging techniques are the primary method for detecting the presence of MGM, even when it recurs. This study aimed to identify plasma metabolites related to the presence of MGM, searching for a simpler approach to detect molecular alterations in the blood linked to MGM.

Antioxidant, antimicrobial and healing properties of an extract from coffee pulp for the development of a phytocosmetic.

Consumer demand for natural, chemical-free products has grown. Food industry residues, like coffee pulp, rich in caffeine, chlorogenic acid and phenolic compounds, offer potential for pharmaceutical and cosmetic applications due to their antioxidant, anti-inflammatory, and antibacterial properties. Therefore, the objective of this work was to develop a phytocosmetic only with natural products containing coffee pulp extract as active pharmaceutical ingredient with antioxidant, antimicrobial and healing activity.

Metabolomics in chronic hepatitis C: Decoding fibrosis grading and underlying pathways.

Background: Chronic Hepatitis C (CHC) affects 71 million people globally and leads to liver issues such as fibrosis, cirrhosis, cancer, and death. A better understanding and prognosis of liver involvement are vital to reduce morbidity and mortality. The accurate identification of the fibrosis stage is crucial for making treatment decisions and predicting outcomes.

Comparing plasma and skin imprint metabolic profiles in COVID-19 diagnosis and severity assessment.

As SARS-CoV-2 continues to produce new variants, the demand for diagnostics and a better understanding of COVID-19 remain key topics in healthcare. Skin manifestations have been widely reported in cases of COVID-19, but the mechanisms and markers of these symptoms are poorly described. In this cross-sectional study, 101 patients (64 COVID-19 positive patients and 37 controls) were enrolled between April and June 2020, during the first wave of COVID-19, in São Paulo, Brazil.

Metabolomics Approach Reveals Important Glioblastoma Plasma Biomarkers for Tumor Biology.

Glioblastoma (GB) is the most aggressive and frequent primary malignant tumor of the central nervous system and is associated with poor overall survival even after treatment. To better understand tumor biochemical alterations and broaden the potential targets of GB, this study aimed to evaluate differential plasma biomarkers between GB patients and healthy individuals using metabolomics analysis. Plasma samples from both groups were analyzed via untargeted metabolomics using direct injection with an electrospray ionization source and an LTQ mass spectrometer.

Exogenous succinate impacts mouse brown adipose tissue mitochondrial proteome and potentiates body mass reduction induced by liraglutide.

Obesity is one of the leading noncommunicable diseases in the world. Despite intense efforts to develop strategies to prevent and treat obesity, its prevalence continues to rise worldwide. A recent study has shown that the tricarboxylic acid intermediate succinate increases body energy expenditure by promoting brown adipose tissue thermogenesis through the activation of uncoupling protein-1; this has generated interest surrounding its potential usefulness as an approach to treat obesity.

Differential Plasma Metabolites between High- and Low-Grade Meningioma Cases.

Meningiomas (MGMs) are currently classified into grades I, II, and III. High-grade tumors are correlated with decreased survival rates and increased recurrence rates. The current grading classification is based on histological criteria and determined only after surgical tumor sampling.

Increasing quantitation in spatial single-cell metabolomics by using fluorescence as ground truth.

Imaging mass spectrometry (MS) is becoming increasingly applied for single-cell analyses. Multiple methods for imaging MS-based single-cell metabolomics were proposed, including our recent method SpaceM. An important step in imaging MS-based single-cell metabolomics is the assignment of MS intensities from individual pixels to single cells.

Unraveling the Metabolic Alterations Induced by Zika Infection in Prostate Epithelial (PNT1a) and Adenocarcinoma (PC-3) Cell Lines.

The outbreak of Zika virus infection in 2016 led to the identification of its presence in several types of biofluids, including semen. Later discoveries associated Zika infection with sexual transmission and persistent replication in cells of the male reproductive tract. Prostate epithelial and carcinoma cells are favorable to virus replication, with studies pointing to transcriptomics alterations of immune and inflammation genes upon persistence.

Tomato classification using mass spectrometry-machine learning technique: A food safety-enhancing platform.

Food safety and quality assessment mechanisms are unmet needs that industries and countries have been continuously facing in recent years. Our study aimed at developing a platform using Machine Learning algorithms to analyze Mass Spectrometry data for classification of tomatoes on organic and non-organic. Tomato samples were analyzed using silica gel plates and direct-infusion electrospray-ionization mass spectrometry technique.

Metabolomic Profiling of Plasma Reveals Differential Disease Severity Markers in COVID-19 Patients.

The severity, disabilities, and lethality caused by the coronavirus 2019 (COVID-19) disease have dumbfounded the entire world on an unprecedented scale. The multifactorial aspect of the infection has generated interest in understanding the clinical history of COVID-19, particularly the classification of severity and early prediction on prognosis. Metabolomics is a powerful tool for identifying metabolite signatures when profiling parasitic, metabolic, and microbial diseases.

Molecular signatures associated with diuron exposure on rat urothelial mitochondria.

Diuron, 3-(3,4-dichlorophenyl)-1,1-dimethylurea, is a worldwide used herbicide whose biotransformation gives rise to the metabolites, 3-(3,4-dichlorophenyl)-1-methylurea (DCPMU) and 3,4-dichloroaniline (DCA). Previous studies indicate that diuron and/or its metabolites are toxic to the bladder urothelium of the Wistar rats where, under certain conditions of exposure, they may induce successively urothelial cell degeneration, necrosis, hyperplasia and eventually tumors. The hypothesis was raised that the molecular initiating event (MIE) of this Adverse Outcome Pathway is the mitochondrial toxicity of those compounds.

Metabolic alterations in Strongyloidiasis stool samples unveil potential biomarkers of infection.

Strongyloidiasis, a parasitosis caused by Strongyloides stercoralis in humans, is a very prevalent infection in tropical or subtropical areas. Gaps on public health strategies corroborates to the high global incidence of strongyloidiasis especially due to challenges involved on its diagnosis. Based on the lack of a gold-standard diagnostic tool, we aimed to present a metabolomic study for the assessment of stool metabolic alterations.

Effect of in vitro digestion on the bioaccessibility and bioactivity of phenolic compounds in fractions of Eugenia pyriformis fruit.

Uvaia is a Brazilian fruit species that has great economic and nutritional potential, in addition to being a good source of compounds of biological interest. In this study, we evaluated for the first time the influence of in vitro gastrointestinal digestion on the bioaccessibility and bioactivity of phenolic compounds from two fractions of uvaia (edible and seed). It was observed that the content of total phenolic compounds was about 3 times higher in the seed (undigested extract), but reduced significantly after intestinal digestion (-50.

Metabolic shift of chronic myeloid leukemia patients under imatinib-pioglitazone regimen and discontinuation.

The Estudo de Descontinuação de Imatinibe após Pioglitazona (EDI-PIO) is a single-center, longitudinal, prospective, phase 2, non-randomized, open, clinical trial (NCT02852486, August 2, 2016 retrospectively registered) for the discontinuation of imatinib after concomitant use of pioglitazone, being the first of its kind in a Brazilian population with chronic myeloid leukemia. Due to remaining of leukemic quiescent cells that are not affected by tyrosine kinase inhibitors, it has been suggested the use of pioglitazone, a PPARγ agonist, together with imatinib as a strategy for the maintenance of deep molecular response. The clinical benefit to this association is still controversial, and the metabolic alteration along this process remains unclear.

Evaluation of antioxidant capacity, fatty acid profile, and bioactive compounds from buritirana (Mauritiella armata Mart.) oil: A little-explored native Brazilian fruit.

Buritirana (Mauritiella armata Mart.) is a fruit species native to the Amazon and Cerrado region, belonging to the Arecaceae family. It has high nutritional and functional potential, yet little explored.

Chemical characterization of Eugenia stipitata: A native fruit from the Amazon rich in nutrients and source of bioactive compounds.

Eugenia stipitata is a fruit native to the Brazilian Amazonian region, belonging to the Myrtaceae family whose chemical composition has been little evidenced. In this study, we evaluated for the first time the nutritional composition, bioactive compounds and antioxidant properties of two fractions of this fruit. It was observed that the edible fraction had a higher content of minerals such as K, Ca and Mg (827.

Covid-19 Automated Diagnosis and Risk Assessment through Metabolomics and Machine Learning.

COVID-19 is still placing a heavy health and financial burden worldwide. Impairment in patient screening and risk management plays a fundamental role on how governments and authorities are directing resources, planning reopening, as well as sanitary countermeasures, especially in regions where poverty is a major component in the equation. An efficient diagnostic method must be highly accurate, while having a cost-effective profile.

Distribution of nutrients and functional potential in fractions of Eugenia pyriformis: An underutilized native Brazilian fruit.

Uvaia is a Brazilian native species whose fruit has few studies on the nutritional composition and antioxidant properties. In this study, we evaluated for the first time the proximate composition, mineral content, carbohydrate profile, identification of organic compounds, and determination of antioxidant properties in two fractions of this fruit (edible fraction and seed). Edible fraction showed the highest content of ash, lipids, proteins, total fibers, minerals mainly K and Mg (1557.

Influence of high-intensity ultrasound on color, chemical composition and antioxidant properties of araçá-boi pulp.

In this study, we evaluated the influence of the ultrasound application on five levels of energy density (1000; 3000; 5000 and 7000 J g) compared to two pasteurization techniques (70 °C/5 min and 94 °C/0.5 min) on color parameters, polyphenoloxidase activity, chemical composition, and antioxidant properties of araçá-boi pulp. Ultrasound caused changes in the parameters brightness/darkness, hue angle, and total color difference, but did not change chroma, yellowness/blueness, color index, and yellow index.

Does leukotriene F4 play a major role in the infection mechanism of Candida sp.?

Candidiasis is the most common fungal infection affecting hospitalized patients, especially immunocompromised and critical patients. Limitations regarding the assertive diagnosis of both Candidemia and Candidiasis not only impairs the introduction of effective treatments but also lays a heavy financial burden over the health system. Furthermore, it is still challenging to ascertain whether diagnostic methods are accurate and whether treatment is effective for patients with Candidemia.

Metabolomics and Machine Learning Approaches Combined in Pursuit for More Accurate Paracoccidioidomycosis Diagnoses.

Brazil and many other Latin American countries are areas of endemicity for different neglected diseases, and the fungal infection paracoccidioidomycosis (PCM) is one of them. Among the clinical manifestations, pneumopathy associated with skin and mucosal lesions is the most frequent. PCM definitive diagnosis depends on yeast microscopic visualization and immunological tests, but both present ambiguous results and difficulty in differentiating PCM from other fungal infections.

Combining Machine Learning and Metabolomics to Identify Weight Gain Biomarkers.

Weight gain is a metabolic disorder that often culminates in the development of obesity and other comorbidities such as diabetes. Obesity is characterized by the development of a chronic, subclinical systemic inflammation, and is regarded as a remarkably important factor that contributes to the development of such comorbidities. Therefore, laboratory methods that allow the identification of subjects at higher risk for severe weight-associated morbidity are of utter importance, considering the health, and safety of populations.