The coronavirus disease 2019 (Covid-19), which caused respiratory problems in many patients worldwide, led to more than 5 million deaths by the end of 2021. Experienced symptoms vary from mild to severe illness. Understanding the infection severity to reach a better prognosis could be useful to the clinics, and one study area to fulfill one piece of this biological puzzle is metabolomics. The metabolite profile and/or levels being monitored can help predict phenotype properties. Therefore, this study evaluated plasma metabolomes of 110 individual samples, 57 from control patients and 53 from recent positive cases of Covid-19 (IgM 98% reagent), representing mild to severe symptoms, before any clinical intervention. Polar metabolites from plasma samples were analyzed by quantitative 1 H NMR. Glycerol, 3-aminoisobutyrate, formate, and glucuronate levels showed alterations in Covid-19 patients compared to those in the control group (Tukey’s HSD p -value cutoff = 0.05), affecting the lactate, phenylalanine, tyrosine, and tryptophan biosynthesis and d -glutamine, d -glutamate, and glycerolipid metabolisms. These metabolic alterations show that SARS-CoV-2 infection led to disturbance in the energetic system, supporting the viral replication and corroborating with the severe clinical conditions of patients. Six polar metabolites (glycerol, acetate, 3-aminoisobutyrate, formate, glucuronate, and lactate) were revealed by PLS-DA and predicted by ROC curves and ANOVA to be potential prognostic metabolite panels for Covid-19 and considered clinically relevant for predicting infection severity due to their straight roles in the lipid and energy metabolism. Thus, metabolomics from samples of Covid-19 patients is a powerful tool for a better understanding of the disease mechanism of action and metabolic consequences of the infection in the human body and may corroborate allowing clinicians to intervene quickly according to the needs of Covid-19 patients.

Current methods employed for the analysis of the chemical composition of solid matrices (such as plant, animal, or human tissues; soil; etc.) often require many sample treatment steps, including an extraction step with exclusively dedicated solvents. This work describes an optimized analytical setup in which the extraction of a solid sample is directly coupled to its analysis by high-performance liquid chromatography. This approach avoids (i) the use of pumps and valves other than those comprising the HPLC instrument, (ii) the use of solvents other than those of the mobile phase, and (iii) the need to stop the mobile phase flow at any time during the full analytical procedure. The compatibility of this approach with the direct analysis of fresh tissues (leaves, stems, and seeds of four plant species with dissimilar chemical compositions) was successfully demonstrated, leading to the elimination of sample preparation steps such as drying, grinding, concentration, dilution, and filtration, among others. This work describes a new, simple, and efficient green approach to minimize or eliminate sample treatment procedures. It could be easily applied for quality control of plant materials and their derived products through chromatographic fingerprints and for untargeted metabolomic investigations of solid matrices, among other applications.

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E-cadherin immunoexpression patterns help us to characterise gastric carcinoma histotypes. The presence or absence of membranous staining is the most valuable criterion in evaluating E-cadherin expression. Mixed tumours show a characteristic E-cadherin cytoplasmic expression in gastric carcinomas.

Cancer cells have differential metabolic dependencies compared to their nonmalignant counterparts. However, few metabolism-targeting compounds have been successful in clinical trials. Here, we investigated the metabolic vulnerabilities of triple-negative breast cancer (TNBC), particularly those metabolic perturbations that increased mitochondrial apoptotic priming and sensitivity to BH3 mimetics (drugs that antagonize antiapoptotic proteins). We used high-throughput dynamic BH3 profiling (HT-DBP) to screen a library of metabolism-perturbing small molecules, which revealed inhibitors of the enzyme nicotinamide phosphoribosyltransferase (NAMPT) as top candidates. In some TNBC cells but not in nonmalignant cells, NAMPT inhibitors increased overall apoptotic priming and induced dependencies on specific antiapoptotic BCL-2 family members. Treatment of TNBC cells with NAMPT inhibitors sensitized them to subsequent treatment with BH3 mimetics. The combination of a NAMPT inhibitor (FK866) and an MCL-1 antagonist (S63845) reduced tumor growth in a TNBC patient–derived xenograft model in vivo. We found that NAMPT inhibition reduced NAD+ concentrations below a critical threshold that resulted in depletion of adenine, which was the metabolic trigger that primed TNBC cells for apoptosis. These findings demonstrate a close interaction between metabolic and mitochondrial apoptotic signaling pathways and reveal that exploitation of a tumor-specific metabolic vulnerability can sensitize some TNBC to BH3 mimetics.

Metabolomics uses several analytical tools to identify the chemical diversity of metabolites present in organisms. These metabolites are low molecular weight molecules (<1500 Da) classified as a final or intermediary product of metabolic processes. The application of this omics technology has become prominent in inferring physiological conditions through reporting on the phenotypic state; therefore, the introduction of metabolomics into clinical studies has been growing in recent years due to its efficiency in discriminating pathophysiological states. Regarding endocrine diseases, there is a great interest in verifying comprehensive and individualized physiological scenarios, in particular for growth hormone deficiency (GHD). The current GHD diagnostic tests are laborious and invasive and there is no exam with ideal reproducibility and sensitivity for diagnosis neither standard GH cutoff point. Therefore, this review was focussed on articles that applied metabolomics in the search for new biomarkers for GHD. The present work shows that the applications of metabolomics in GHD are still limited, since the little complementarily of analytical techniques, a low number of samples, GHD combined to other deficiencies, and idiopathic diagnosis shows a lack of progress. The results of the research are relevant and similar; however, their results do not provide an application for clinical practice due to the lack of multidisciplinary actions that would be needed to mediate the translation of the knowledge produced in the laboratory, if transferred to the medical setting.

Indocyanine green (ICG) is the only near-infrared (NIR) dye approved for clinical use. Despite its versatility in photonic applications and potential for photothermal therapy, its photobleaching hinders its application. Here we discovered a nanostructure of dimeric ICG (Nano-dICG) generated by using ICG to stabilize nanoemulsions, after which ICG enabled complete dimerization on the nanoemulsion shell, followed by J-aggregation of ICG-dimer, resulting in a narrow, red-shifted (780 nm!894 nm) and intense ( � 2-fold) absorbance. Compared to ICG, Nano-dICG demonstrated superior photothermal conversion (2-fold higher), significantly reduced photodegradation (À 9.6 % vs. À 46.3 %), and undiminished photothermal effect (7 vs. 2 cycles) under repeated irradiations, in addition to excellent colloidal and structural stabilities. Following intravenous injection, Nano-dICG enabled real-time tracking of its delivery to mouse tumors within 24 h by photoacoustic imaging at NIR wavelength (890 nm) distinct from the endogenous signal to guide effective photothermal therapy. The unprecedented finding of nanostructure-driven ICG dimerization leads to an ultrastable phototheranostic platform.

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