Publications by authors named "Federico Marini"

121 Publications

Coupling high-resolution mass spectrometry and chemometrics for the structural characterization of anabolic-androgenic steroids and the early detection of unknown designer structures.

Talanta 2021 May 4;227:122173. Epub 2021 Feb 4.

Dipartimento di Chimica, "Sapienza" Università di Roma, Piazzale Aldo Moro 5, 00185, Rome, Italy.

Predictive models have been developed for the early identification of novel anabolic androgenic steroids and to obtain information on their molecular structure. To this purpose, gas-chromatographic and mass spectrometric characteristic parameters of 136 anabolic androgenic steroids have been specifically considered. Starting from Principal Component Analysis, different chemometric methods were applied, such as classification and clustering techniques, outlining a spectral and structural characterization for each steroid subclass, and considering the contribution of more than 30 variables. Mass spectrometric data on the TMS-derivatives of the target steroids were obtained by gas chromatography coupled to quadrupole-time of flight mass spectrometry using electron ionization. Steroids included in the training set were grouped in 5 subclasses according to their structural similarity, and the experimental data, processed by the chemometric models, allowed the identification of class-specific common fragments and spectral trends. The results of this study, validated on a test set of 21 steroids, have confirmed that the proposed approach allows tracing novel "designer anabolic steroids", including those previously unknown new structures that may have been designed and illicitly synthesized to be invisible to the current anti-doping tests.
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http://dx.doi.org/10.1016/j.talanta.2021.122173DOI Listing
May 2021

Application of ANOVA-simultaneous component analysis to quantify and characterise effects of age, temperature, syrup adulteration and irradiation on near-infrared (NIR) spectral data of honey.

Spectrochim Acta A Mol Biomol Spectrosc 2021 May 4;253:119546. Epub 2021 Feb 4.

Department of Food Science, Stellenbosch University, Private Bag X1, Matieland, Stellenbosch 7602, South Africa. Electronic address:

NIR spectroscopy combined with chemometric analysis has proven to be a rapid and cost-effective screening tool for the detection of syrup-adulterated honey. Processing and storage conditions which alter the chemical and physical state of honey may affect the spectra. The effects of age, storage temperature, syrup adulteration (10 and 20% w/w) and irradiation treatment on the NIR spectra of honey were investigated as a function of time with ANOVA-simultaneous component analysis (ASCA), an experimental design-focused exploratory data analysis method. The factors 'time', 'temperature' and 'adulteration' were found to have significant effects (p < 0.05), but no significant effect was observed for irradiation treatment. A significant interaction effect was found between factors 'time' and 'adulteration', with the greatest disparity between authentic and adulterated class signals found immediately after adulteration and decreasing within three months thereafter.
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http://dx.doi.org/10.1016/j.saa.2021.119546DOI Listing
May 2021

Effects of thermal treatments on durum wheat pasta flavour during production process: A modelling approach to provide added-value to pasta dried at low temperatures.

Talanta 2021 Apr 3;225:121955. Epub 2020 Dec 3.

Department of Physical and Chemical Sciences, University of L'Aquila, Via Vetoio, 67100, Coppito, L'Aquila, Italy.

Pasta is a key element of the Mediterranean Diet and it has been declared by Unesco intangible cultural heritage of humanity. Despite seems a simple food, only made of semolina and water, pasta is produced following a multi-step process that strongly affect the final product. Drying stage is the one that has the greater influence on its organoleptic/nutritional characteristics. This study aimed to analyse the flavour of pasta to test whether the different drying treatments (High Temperature-Short time or Low Temperature-Long time) have a direct impact on its composition and consequently whether they could influence the end-product quality. The headspace solid-phase microextraction was optimized using an experimental design and 52 samples were analysed by HS-SPME/GC-MS and classified by PLS-DA. The resulting classification model (validated by repeated double cross-validation and permutation tests) allowed correctly predicting more than 80% of samples, confirming that drying may have a significant impact on pasta flavour.
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http://dx.doi.org/10.1016/j.talanta.2020.121955DOI Listing
April 2021

Insulin resistance, oxidative stress and mitochondrial defects in Ts65dn mice brain: A harmful synergistic path in down syndrome.

Free Radic Biol Med 2021 Mar 29;165:152-170. Epub 2021 Jan 29.

Department of Biochemical Sciences "A. Rossi-Fanelli", Sapienza University of Rome, Piazzale A. Moro 5, 00185, Roma, Italy. Electronic address:

Dysregulation of brain insulin signaling with reduced downstream neuronal survival and plasticity mechanisms are fundamental abnormalities observed in Alzheimer disease (AD). This phenomenon, known as brain insulin resistance, is associated with poor cognitive performance and is driven by the inhibition of IRS1. Since Down syndrome (DS) and AD neuropathology share many common features, we investigated metabolic aspects of neurodegeneration in DS and whether they contribute to early onset AD in DS. We evaluated levels and activation of proteins belonging to the insulin signaling pathway (IR, IRS1, BVR-A, MAPK, PTEN, Akt, GSK3β, PKCζ, AS160, GLUT4) in the frontal cortex of Ts65dn (DS model) (n = 5-6/group) and euploid mice (n = 6/group) at different ages (1, 3, 9 and 18 months). Furthermore, we analyzed whether changes of brain insulin signaling were associated with alterations of: (i) proteins regulating brain energy metabolism (mitochondrial complexes, hexokinase-II, Sirt1); (ii) oxidative stress (OS) markers (iii) APP cleavage; and (iv) proteins mediating synaptic plasticity mechanisms (PSD95, syntaxin-1 and BDNF). Ts65dn mice showed an overall impairment of the above-mentioned pathways, mainly characterized by defects of proteins activation state. Such alterations start early in life (at 1 month, during brain maturation). In particular, accumulation of inhibited IRS1, together with the uncoupling among the proteins downstream from IRS1 (brain insulin resistance), characterize Ts65dn mice. Furthermore, reduced levels of mitochondrial complexes and Sirt1, as well as increased indices of OS also were observed. These alterations precede the accumulation of APP-C99 in Ts65dn mice. Tellingly, oxidative stress levels were negatively associated with IR, IRS1 and AS160 activation as well as mitochondrial complexes levels in Ts65dn mice, suggesting a role for oxidative stress in the observed alterations. We propose that a close link exists among brain insulin resistance, mitochondrial defects and OS that contributes to brain dysfunctions observed in DS, likely favoring the development of AD in DS.
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http://dx.doi.org/10.1016/j.freeradbiomed.2021.01.042DOI Listing
March 2021

Fourier-Transform Infrared Spectroscopy of Skeletal Muscle Tissue: Expanding Biomarkers in Primary Mitochondrial Myopathies.

Genes (Basel) 2020 Dec 19;11(12). Epub 2020 Dec 19.

Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.

Primary mitochondrial myopathies (PMM) are a group of mitochondrial disorders characterized by a predominant skeletal muscle involvement. The aim of this study was to evaluate whether the biochemical profile determined by Fourier-transform infrared (FTIR) spectroscopic technique would allow to distinguish among patients affected by progressive external ophthalmoplegia (PEO), the most common PMM presentation, oculopharyngeal muscular dystrophy (OPMD), and healthy controls. Thirty-four participants were enrolled in the study. FTIR spectroscopy was found to be a sensitive and specific diagnostic marker for PEO. In particular, FTIR spectroscopy was able to distinguish PEO patients from those affected by OPMD, even in the presence of histological findings similar to mitochondrial myopathy. At the same time, FTIR spectroscopy differentiated single mtDNA deletion and mutations in , the most common nuclear gene associated with mitochondrial diseases, with high sensitivity and specificity. In conclusion, our data suggest that FTIR spectroscopy is a valuable biodiagnostic tool for the differential diagnosis of PEO with a high ability to also distinguish between single mtDNA deletion and mutations in gene based on specific metabolic transitions.
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http://dx.doi.org/10.3390/genes11121522DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7766922PMC
December 2020

annoFuse: an R Package to annotate, prioritize, and interactively explore putative oncogenic RNA fusions.

BMC Bioinformatics 2020 Dec 14;21(1):577. Epub 2020 Dec 14.

Center for Data-Driven Discovery in Biomedicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.

Background: Gene fusion events are significant sources of somatic variation across adult and pediatric cancers and are some of the most clinically-effective therapeutic targets, yet low consensus of RNA-Seq fusion prediction algorithms makes therapeutic prioritization difficult. In addition, events such as polymerase read-throughs, mis-mapping due to gene homology, and fusions occurring in healthy normal tissue require informed filtering, making it difficult for researchers and clinicians to rapidly discern gene fusions that might be true underlying oncogenic drivers of a tumor and in some cases, appropriate targets for therapy.

Results: We developed annoFuse, an R package, and shinyFuse, a companion web application, to annotate, prioritize, and explore biologically-relevant expressed gene fusions, downstream of fusion calling. We validated annoFuse using a random cohort of TCGA RNA-Seq samples (N = 160) and achieved a 96% sensitivity for retention of high-confidence fusions (N = 603). annoFuse uses FusionAnnotator annotations to filter non-oncogenic and/or artifactual fusions. Then, fusions are prioritized if previously reported in TCGA and/or fusions containing gene partners that are known oncogenes, tumor suppressor genes, COSMIC genes, and/or transcription factors. We applied annoFuse to fusion calls from pediatric brain tumor RNA-Seq samples (N = 1028) provided as part of the Open Pediatric Brain Tumor Atlas (OpenPBTA) Project to determine recurrent fusions and recurrently-fused genes within different brain tumor histologies. annoFuse annotates protein domains using the PFAM database, assesses reciprocality, and annotates gene partners for kinase domain retention. As a standard function, reportFuse enables generation of a reproducible R Markdown report to summarize filtered fusions, visualize breakpoints and protein domains by transcript, and plot recurrent fusions within cohorts. Finally, we created shinyFuse for algorithm-agnostic interactive exploration and plotting of gene fusions.

Conclusions: annoFuse provides standardized filtering and annotation for gene fusion calls from STAR-Fusion and Arriba by merging, filtering, and prioritizing putative oncogenic fusions across large cancer datasets, as demonstrated here with data from the OpenPBTA project. We are expanding the package to be widely-applicable to other fusion algorithms and expect annoFuse to provide researchers a method for rapidly evaluating, prioritizing, and translating fusion findings in patient tumors.
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http://dx.doi.org/10.1186/s12859-020-03922-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7737294PMC
December 2020

Improved prediction of fuel properties with near-infrared spectroscopy using a complementary sequential fusion of scatter correction techniques.

Talanta 2021 Feb 24;223(Pt 1):121693. Epub 2020 Sep 24.

ITAP, INRAE, Institut Agro, University Montpellier, Montpellier, France; ChemHouse Research Group, Montpellier, France.

Near-infrared (NIR) spectroscopy of fuels can suffer from scattering effects which may mask the signals corresponding to key analytes in the spectra. Therefore, scatter correction techniques are often used prior to any modelling so to remove scattering and improve predictive performances. However, different scatter correction techniques may carry complementary information so that, if jointly used, both model stability and performances could be improved. A solution to that is the fusion of complementary information from differently scatter corrected data. In the present work, the use of a preprocessing fusion approach called sequential preprocessing through orthogonalization (SPORT) is demonstrated for predicting key quality parameters in diesel fuels. In particular, the possibility of predicting four different key properties, i.e., boiling point (°C), density (g/mL), aromatic mass (%) and viscosity (cSt), was considered. As a comparison, standard partial least-squares (PLS) regression modelling was performed on data pretreated by SNV and 2nd derivative (which is a widely used preprocessing combination). The results showed that the SPORT models, based on the fusion of scatter correction techniques, outperformed the standard PLS models in the prediction of all the four properties, suggesting that selection and use of a single scatter correction technique is often not sufficient. Up to complete bias removal with 50% reduction in prediction error was obtained. The R was increased by up to 8%. The sequential scatter fusion approach (SPORT) is not limited to NIR data but can be applied to any other spectral data where a preprocessing optimization step is required.
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http://dx.doi.org/10.1016/j.talanta.2020.121693DOI Listing
February 2021

Sequential fusion of information from two portable spectrometers for improved prediction of moisture and soluble solids content in pear fruit.

Talanta 2021 Feb 13;223(Pt 2):121733. Epub 2020 Oct 13.

Wageningen Food and Biobased Research, Bornse Weilanden 9, P.O. Box 17, 6700AA, Wageningen, the Netherlands.

Near infrared (NIR) spectroscopy allows rapid estimation of quality traits in fresh fruit. Several portable spectrometers are available in the market as a low-cost solution to perform NIR spectroscopy. However, portable spectrometers, being lower in cost than a benchtop counterpart, do not cover the complete near infrared (NIR) spectral range. Often portable sensors either use silicon-based visible and NIR detector to cover 400-1000 nm, or InGaAs-based short wave infrared (SWIR) detector covering the 900-1700 nm. However, these two spectral regions carry complementary information, since the 400-1000 nm interval captures the color and 3rd overtones of most functional group vibrations, while the 1st and the 2nd overtones of the same transitions fall in the 1000-1700 nm range. To exploit such complementarity, sequential data fusion strategies were used to fuse the data from two portable spectrometers, i.e., Felix F750 (~400-1000 nm) and the DLP NIR Scan Nano (~900-1700 nm). In particular, two different sequential fusion approaches were used, namely sequential orthogonalized partial-least squares (SO-PLS) regression and sequential orthogonalized covariate selection (SO-CovSel). SO-PLS improved the prediction of moisture content (MC) and soluble solids content (SSC) in pear fruit, leading to an accuracy which was not obtainable with models built on any of the two spectral data set individually. Instead, SO-CovSel was used to select the key wavelengths from both the spectral ranges mostly correlated to quality parameters of pear fruit. Sequential fusion of the data from the two portable spectrometers led to an improved model prediction (higher R and lower RMSEP) of MC and SSC in pear fruit: compared to the models built with the DLP NIR Scan Nano (the worst individual block) where SO-PLS showed an increase in R up to 56% and a corresponding 47% decrease in RMSEP. Differences were less pronounced to the use of Felix data alone, but still the R was increased by 2.5% and the RMSEP was reduced by 6.5%. Sequential data fusion is not limited to NIR data but it can be considered as a general tool for integrating information from multiple sensors.
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http://dx.doi.org/10.1016/j.talanta.2020.121733DOI Listing
February 2021

ideal: an R/Bioconductor package for interactive differential expression analysis.

BMC Bioinformatics 2020 Dec 9;21(1):565. Epub 2020 Dec 9.

Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Stefan-Meier-Str. 26, 79104, Freiburg, Germany.

Background: RNA sequencing (RNA-seq) is an ever increasingly popular tool for transcriptome profiling. A key point to make the best use of the available data is to provide software tools that are easy to use but still provide flexibility and transparency in the adopted methods. Despite the availability of many packages focused on detecting differential expression, a method to streamline this type of bioinformatics analysis in a comprehensive, accessible, and reproducible way is lacking.

Results: We developed the ideal software package, which serves as a web application for interactive and reproducible RNA-seq analysis, while producing a wealth of visualizations to facilitate data interpretation. ideal is implemented in R using the Shiny framework, and is fully integrated with the existing core structures of the Bioconductor project. Users can perform the essential steps of the differential expression analysis workflow in an assisted way, and generate a broad spectrum of publication-ready outputs, including diagnostic and summary visualizations in each module, all the way down to functional analysis. ideal also offers the possibility to seamlessly generate a full HTML report for storing and sharing results together with code for reproducibility.

Conclusion: ideal is distributed as an R package in the Bioconductor project ( http://bioconductor.org/packages/ideal/ ), and provides a solution for performing interactive and reproducible analyses of summarized RNA-seq expression data, empowering researchers with many different profiles (life scientists, clinicians, but also experienced bioinformaticians) to make the ideal use of the data at hand.
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http://dx.doi.org/10.1186/s12859-020-03819-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7724894PMC
December 2020

Correction: ERK3/MAPK6 is required for KRAS-mediated NSCLC tumorigenesis.

Cancer Gene Ther 2020 Nov 9. Epub 2020 Nov 9.

Cell Biology Unit, University Medical Center of the Johannes Gutenberg University Mainz, 55131, Mainz, Germany.

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http://dx.doi.org/10.1038/s41417-020-00250-zDOI Listing
November 2020

Circulating Mitochondrial-Derived Vesicles, Inflammatory Biomarkers and Amino Acids in Older Adults With Physical Frailty and Sarcopenia: A Preliminary BIOSPHERE Multi-Marker Study Using Sequential and Orthogonalized Covariance Selection - Linear Discriminant Analysis.

Front Cell Dev Biol 2020 22;8:564417. Epub 2020 Sep 22.

Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, Rome, Italy.

Physical frailty and sarcopenia (PF&S) is a prototypical geriatric condition characterized by reduced physical function and low muscle mass. The multifaceted pathophysiology of this condition recapitulates all hallmarks of aging making the identification of specific biomarkers challenging. In the present study, we explored the relationship among three processes that are thought to be involved in PF&S (i.e., systemic inflammation, amino acid dysmetabolism, and mitochondrial dysfunction). We took advantage of the well-characterized cohort of older adults recruited in the "BIOmarkers associated with Sarcopenia and Physical frailty in EldeRly pErsons" (BIOSPHERE) study to preliminarily combine in a multi-platform analytical approach inflammatory biomolecules, amino acids and derivatives, and mitochondrial-derived vesicle (MDV) cargo molecules to evaluate their performance as possible biomarkers for PF&S. Eleven older adults aged 70 years and older with PF&S and 10 non-sarcopenic non-frail controls were included in the analysis based on the availability of the three categories of biomolecules. A sequential and orthogonalized covariance selection-linear discriminant analysis (SO-CovSel-LDA) approach was used for biomarkers selection. Of the 75 analytes assayed, 16 had concentrations below the detection limit. Within the remaining 59 biomolecules, So-CovSel-LDA selected a set comprising two amino acids (phosphoethanolamine and tryptophan), two cytokines (interleukin 1 receptor antagonist and macrophage inflammatory protein 1β), and MDV-derived nicotinamide adenine dinucleotide reduced form:ubiquinone oxidoreductase subunit S3 as the best predictors for discriminating older people with and without PF&S. The evaluation of these biomarkers in larger cohorts and their changes over time or in response to interventions may unveil specific pathogenetic pathways of PF&S and identify new biological targets for drug development.
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http://dx.doi.org/10.3389/fcell.2020.564417DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536309PMC
September 2020

ERK3/MAPK6 is required for KRAS-mediated NSCLC tumorigenesis.

Cancer Gene Ther 2020 Oct 17. Epub 2020 Oct 17.

Cell Biology Unit, University Medical Center of the Johannes Gutenberg University Mainz, 55131, Mainz, Germany.

KRAS is one of the most frequently mutated oncogenes, especially in lung cancers. Targeting of KRAS directly or the downstream effector signaling machinery is of prime interest in treating lung cancers. Here, we uncover that ERK3, a ubiquitously expressed atypical MAPK, is required for KRAS-mediated NSCLC tumors. ERK3 is highly expressed in lung cancers, and oncogenic KRAS led to the activation and stabilization of the ERK3 protein. In particular, phosphorylation of serine 189 in the activation motif of ERK3 is significantly increased in lung adenocarcinomas in comparison to adjacent normal controls in patients. Loss of ERK3 prevents the anchorage-independent growth of KRAS G12C-transformed human bronchial epithelial cells. We further find that loss of ERK3 reduces the oncogenic growth of KRAS G12C-driven NSCLC tumors in vivo and that the kinase activity of ERK3 is required for KRAS-driven oncogenesis in vitro. Our results demonstrate an obligatory role for ERK3 in NSCLC tumor progression and suggest that ERK3 kinase inhibitors can be pursued for treating KRAS G12C-driven tumors.
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http://dx.doi.org/10.1038/s41417-020-00245-wDOI Listing
October 2020

Chemometric Approach to a Rapid Attenuated Total Reflection Fourier Transform Infrared Analysis of Complex Heroin-Based Mixtures.

Appl Spectrosc 2020 Nov 6:3702820969715. Epub 2020 Nov 6.

Department of Analytical Chemistry, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia.

Heroin is one of the most frequently seized drugs in Southeastern Europe. Due to the position in the Balkan route, the Republic of Serbia keeps important role in suppression of the trafficking of heroin for domestic and foreign illegal market. This research is aimed to provide a good scientific approach in the field of seized heroin analysis. Two different forms of heroin are present in the illegal market, mostly in mixtures with typical "cutting" agents: caffeine, paracetamol, and sugars. It was observed that the quantity of pure heroin in seized samples slightly increases from year to year. The aim of this study was to produce a reliable and fast procedure for classification of illicit heroin samples and determination of the concentration range of heroin in the samples. For that purpose, the attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) technique was used and combined with such chemometric methods as principal component analysis, cluster analysis, and partial least squares. Principal component analysis (PCA) as an unsupervised model was used for exploratory purposes to identify trends, similarities, and differences between samples by reducing the dimensionality of the data. The cluster classification of examined samples turned out to be extremely useful to evaluate the possibilities of the ATR FT-IR technique to classify the samples appropriately into the patterns, the constituted clusters. Additionally, partial least square was the suitable method for the purpose of determination of the heroin hydrochloride concentration range in examined samples. It is proved that the joined application of spectroscopy and chemometrics can be extremely convenient and useful for forensic and drugs control laboratories.
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http://dx.doi.org/10.1177/0003702820969715DOI Listing
November 2020

Fused Omics Data Models Reveal Gut Microbiome Signatures Specific of Inactive Stage of Juvenile Idiopathic Arthritis in Pediatric Patients.

Microorganisms 2020 Oct 6;8(10). Epub 2020 Oct 6.

Department of Laboratories, Unit of Parasitology and Area of Genetics and Rare Diseases, Unit of Human Microbiome, Bambino Gesù Children's Hospital, IRCCS, 00165 Rome, Italy.

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease in children. Herein, we evaluated the relationship between the gut microbiome (GM) and disease phenotype by an integrated omics fused approach. In a multicenter, observational cohort study, stools from Italian JIA patients were collected at baseline, active, and inactive disease stages, and their GM compared to healthy controls (CTRLs). The microbiota metabolome was analyzed to detect volatile- and non-volatile organic compounds (VOCs); the data were fused with operational taxonomic units (OTUs) from 16S RNA targeted-metagenomics and classified by chemometric models. Non-VOCs did not characterize JIA patients nor JIA activity stages compared to CTRLs. The core of VOCs, (Ethanol, Methyl-isobutyl-ketone, 2,6-Dimethyl-4-heptanone and Phenol) characterized patients at baseline and inactive disease stages, while the OTUs represented by Ruminococcaceae, Lachnospiraceae and Clostridiacea discriminated between JIA inactive stage and CTRLs. No differences were highlighted amongst JIA activity stages. Finally, the fused data discriminated inactive and baseline stages versus CTRLs, based on the contribution of the invariant core of VOCs while Ruminococcaceae concurred for the inactive stage versus CTRLs comparison. In conclusion, the GM signatures enabled to distinguish the inactive disease stage from CTRLs.
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http://dx.doi.org/10.3390/microorganisms8101540DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7650812PMC
October 2020

TREND-DB-a transcriptome-wide atlas of the dynamic landscape of alternative polyadenylation.

Nucleic Acids Res 2021 01;49(D1):D243-D253

Center for Thrombosis and Hemostasis (CTH), University Medical Center Mainz, 55131 Mainz, Germany.

Alternative polyadenylation (APA) profoundly expands the transcriptome complexity. Perturbations of APA can disrupt biological processes, ultimately resulting in devastating disorders. A major challenge in identifying mechanisms and consequences of APA (and its perturbations) lies in the complexity of RNA 3' end processing, involving poorly conserved RNA motifs and multi-component complexes consisting of far more than 50 proteins. This is further complicated in that RNA 3' end maturation is closely linked to transcription, RNA processing and even epigenetic (histone/DNA/RNA) modifications. Here, we present TREND-DB (http://shiny.imbei.uni-mainz.de:3838/trend-db), a resource cataloging the dynamic landscape of APA after depletion of >170 proteins involved in various facets of transcriptional, co- and post-transcriptional gene regulation, epigenetic modifications and further processes. TREND-DB visualizes the dynamics of transcriptome 3' end diversification (TREND) in a highly interactive manner; it provides a global APA network map and allows interrogating genes affected by specific APA-regulators and vice versa. It also permits condition-specific functional enrichment analyses of APA-affected genes, which suggest wide biological and clinical relevance across all RNAi conditions. The implementation of the UCSC Genome Browser provides additional customizable layers of gene regulation accounting for individual transcript isoforms (e.g. epigenetics, miRNA-binding sites and RNA-binding proteins). TREND-DB thereby fosters disentangling the role of APA for various biological programs, including potential disease mechanisms, and helps identify their diagnostic and therapeutic potential.
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http://dx.doi.org/10.1093/nar/gkaa722DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778938PMC
January 2021

ExploreModelMatrix: Interactive exploration for improved understanding of design matrices and linear models in R.

F1000Res 2020 4;9:512. Epub 2020 Jun 4.

Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.

Linear and generalized linear models are used extensively in many scientific fields, to model observed data and as the basis for hypothesis tests. The use of such models requires specification of a design matrix, and subsequent formulation of contrasts representing scientific hypotheses of interest. Proper execution of these steps requires a thorough understanding of the meaning of the individual coefficients, and is a frequent source of uncertainty for end users. Here, we present an R/Bioconductor package, , which enables interactive exploration of design matrices and linear model diagnostics. Given a sample data table and a desired design formula, the package displays how the model coefficients are combined to give the fitted values for each combination of predictor variables, which allows users to both extract the interpretation of each individual coefficient, and formulate desired linear contrasts. In addition, the interactive interface displays informative characteristics for the regular linear model corresponding to the provided design, such as variance inflation factors and the pseudoinverse of the design matrix. We envision the package and the built-in collection of common types of linear model designs to be useful for teaching and self-learning purposes, as well as for assisting more experienced users in the interpretation of complex model designs.
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http://dx.doi.org/10.12688/f1000research.24187.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359746PMC
March 2021

Bacterial polyphosphates interfere with the innate host defense to infection.

Nat Commun 2020 08 12;11(1):4035. Epub 2020 Aug 12.

Center for Thrombosis and Hemostasis, University Medical Center Mainz, 55131, Mainz, Germany.

Polyphosphates are linear polymers and ubiquitous metabolites. Bacterial polyphosphates are long chains of hundreds of phosphate units. Here, we report that mouse survival of peritoneal Escherichia coli sepsis is compromised by long-chain polyphosphates, and improves with bacterial polyphosphatekinase deficiency or neutralization using recombinant exopolyphosphatase. Polyphosphate activities are chain-length dependent, impair pathogen clearance, antagonize phagocyte recruitment, diminish phagocytosis and decrease production of iNOS and cytokines. Macrophages bind and internalize polyphosphates, in which their effects are independent of P2Y1 and RAGE receptors. The M1 polarization driven by E. coli derived LPS is misdirected by polyphosphates in favor of an M2 resembling phenotype. Long-chain polyphosphates modulate the expression of more than 1800 LPS/TLR4-regulated genes in macrophages. This interference includes suppression of hundreds of type I interferon-regulated genes due to lower interferon production and responsiveness, blunted STAT1 phosphorylation and reduced MHCII expression. In conclusion, prokaryotic polyphosphates disturb multiple macrophage functions for evading host immunity.
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http://dx.doi.org/10.1038/s41467-020-17639-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7423913PMC
August 2020

A Specific Urinary Amino Acid Profile Characterizes People with Kidney Stones.

Dis Markers 2020 30;2020:8848225. Epub 2020 Jun 30.

Università Cattolica del Sacro Cuore, Rome, Italy.

Background: Urolithiasis is the process of stone formation in the urinary tract. Its etiology is only partly known, and efficient therapeutic approaches are currently lacking. Metabolomics is increasingly used in biomarkers discovery for its ability to identify mediators of relevant (patho)physiological processes. Amino acids may be involved in kidney stone formation. The aim of the present study was to investigate the presence of an amino acid signature in stone former urine through a targeted metabolomic approach.

Methods: A panel of 35 amino acids and derivatives was assessed in urines from 15 stone former patients and 12 healthy subjects by UPLC-MS. Partial Least Squares Discriminant Analysis (PLS-DA) was used to define amino acid profiles of cases and controls. Our approach led to the definition of a specific amino acid fingerprint in people with kidney stones. A urinary amino acid profile of stone formers was characterized by lower levels of -aminobutyric acid, asparagine, ethanolamine, isoleucine, methionine, phenylalanine, serine, tryptophan, and valine. Metabolomic analysis may lend insights into the pathophysiology of urolithiasis and allow tracking this prevalent condition over time.
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http://dx.doi.org/10.1155/2020/8848225DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7345965PMC
June 2020

Interleukin-1 promotes autoimmune neuroinflammation by suppressing endothelial heme oxygenase-1 at the blood-brain barrier.

Acta Neuropathol 2020 10 11;140(4):549-567. Epub 2020 Jul 11.

Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.

The proinflammatory cytokine interleukin 1 (IL-1) is crucially involved in the pathogenesis of multiple sclerosis (MS) and its animal model experimental autoimmune encephalomyelitis (EAE). Herein, we studied the role of IL-1 signaling in blood-brain barrier (BBB) endothelial cells (ECs), astrocytes and microglia for EAE development, using mice with the conditional deletion of its signaling receptor IL-1R1. We found that IL-1 signaling in microglia and astrocytes is redundant for the development of EAE, whereas the IL-1R1 deletion in BBB-ECs markedly ameliorated disease severity. IL-1 signaling in BBB-ECs upregulated the expression of the adhesion molecules Vcam-1, Icam-1 and the chemokine receptor Darc, all of which have been previously shown to promote CNS-specific inflammation. In contrast, IL-1R1 signaling suppressed the expression of the stress-responsive heme catabolizing enzyme heme oxygenase-1 (HO-1) in BBB-ECs, promoting disease progression via a mechanism associated with deregulated expression of the IL-1-responsive genes Vcam1, Icam1 and Ackr1 (Darc). Mechanistically, our data emphasize a functional crosstalk of BBB-EC IL-1 signaling and HO-1, controlling the transcription of downstream proinflammatory genes promoting the pathogenesis of autoimmune neuroinflammation.
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http://dx.doi.org/10.1007/s00401-020-02187-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498485PMC
October 2020

Direct Catalytic Fuel Cell Device Coupled to Chemometric Methods to Detect Organic Compounds of Pharmaceutical and Biomedical Interest.

Sensors (Basel) 2020 Jun 27;20(13). Epub 2020 Jun 27.

Department of Electronic Engineering, University of Rome "Tor Vergata", Via Politecnico 1, 00133 Rome, Italy.

Making use of a small direct methanol fuel cell device (DMFC), used as an analytical sensor, chemometric methods, organic compounds very different from one another, can be determined qualitatively and quantitatively. In this research, the following seven different organic compounds of pharmaceutical and biomedical interest, having in common only one -OH group, were considered: chloramphenicol, imipenem, methanol, ethanol, propanol, atropine and cortisone. From a quantitative point of view, the traditional approach, involving the building of individual calibration curves, which allow the quantitative determination of the corresponding organic compounds, even if with different sensitivities, was followed. For the qualitative analysis of each compound, this approach has been much more innovative. In fact, by processing the data from each of the individual response curves, obtained through the fuel cell, using chemometric methods, it is possible to directly identify and recognize each of the seven organic compounds. Since the study is a proof of concept to show the potential of this innovative methodological approach, based on the combination of direct methanol fuel cell with advanced chemometric tools, at this stage, concentration ranges that may not be the ones found in some real situations were investigated. The three methods adopted are all explorative methods with very limited computation costs, which have different characteristics and, therefore, may provide complementary information on the analyzed data. Indeed, while PCA (principal components analysis) provides the most parsimonious summary of the variability observed in the current response matrix, the analysis of the current response behavior was performed by the "slicing" method, in order to transform the current response profiles into numerical matrices, while PARAFAC (Parallel Factor Analysis) allows to obtain a finer deconvolution of the exponential curves. On the other hand, the multiblock nature of "ComDim" (Common Components and Specific Weight Analysis) has been the basis to relate the variability observed in the current response behavior with the parameters of the linear calibrations.
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http://dx.doi.org/10.3390/s20133615DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374455PMC
June 2020

Identification of biomarkers for physical frailty and sarcopenia through a new multi-marker approach: results from the BIOSPHERE study.

Geroscience 2020 Jun 1. Epub 2020 Jun 1.

Fondazione Policlinico Universitario ''Agostino Gemelli'' IRCCS, L.go F. Vito 1, 00168, Rome, Italy.

Physical frailty and sarcopenia (PF&S) is a prototypical geriatric condition characterized by reduced physical function and low muscle mass. The aim of the present study was to provide an initial selection of biomarkers for PF&S using a novel multivariate analytic strategy. Two-hundred community-dwellers, 100 with PF&S and 100 non-physically frail, non-sarcopenic (nonPF&S) controls aged 70 and older were enrolled as part of the BIOmarkers associated with Sarcopenia and Physical frailty in EldeRly pErsons (BIOSPHERE) study. A panel of 74 serum analytes involved in inflammation, muscle growth and remodeling, neuromuscular junction damage, and amino acid metabolism was assayed. Biomarker selection was accomplished through sequential and orthogonalized covariance selection (SO-CovSel) analysis. Separate SO-CovSel models were constructed for the whole study population and for the two genders. The model with the best prediction ability obtained with the smallest number of variables was built using seven biomolecules. This model allowed correct classification of 80.6 ± 5.3% PF&S participants and 79.9 ± 5.1% nonPF&S controls. The PF&S biomarker profile was characterized by higher serum levels of asparagine, aspartic acid, and citrulline. Higher serum concentrations of platelet-derived growth factor BB, heat shock protein 72 (Hsp72), myeloperoxidase, and α-aminobutyric acid defined the profile of nonPF&S participants. Gender-specific SO-CovSel models identified a "core" biomarker profile of PF&S, characterized by higher serum levels of aspartic acid and Hsp72 and lower concentrations of macrophage inflammatory protein 1β, with peculiar signatures in men and women.SO-CovSel analysis allowed identifying a set of potential biomarkers for PF&S. The adoption of such an innovative multivariate approach could help address the complex pathophysiology of PF&S, translate biomarker discovery from bench to bedside, and unveil novel targets for interventions.
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http://dx.doi.org/10.1007/s11357-020-00197-xDOI Listing
June 2020

A novel multi-marker discovery approach identifies new serum biomarkers for Parkinson's disease in older people: an EXosomes in PArkiNson Disease (EXPAND) ancillary study.

Geroscience 2020 10 26;42(5):1323-1334. Epub 2020 May 26.

Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, Rome, Italy.

Dopaminergic nigrostriatal denervation and widespread intracellular α-synuclein accumulation are neuropathologic hallmarks of Parkinson's disease (PD). A constellation of peripheral processes, including metabolic and inflammatory changes, are thought to contribute to neurodegeneration. In the present study, we sought to obtain insight into the multifaceted pathophysiology of PD through the application of a multi-marker discovery approach. Fifty older adults aged 70+, 20 with PD and 30 age-matched controls were enrolled as part of the EXosomes in PArkiNson Disease (EXPAND) study. A panel of 68 circulating mediators of inflammation, neurogenesis and neural plasticity, and amino acid metabolism was assayed. Biomarker selection was accomplished through sequential and orthogonalized covariance selection (SO-CovSel), a multi-platform regression method developed to handle highly correlated variables organized in multi-block datasets. The SO-CovSel model with the best prediction ability using the smallest number of variables was built with seven biomolecules. The model allowed correct classification of 94.2 ± 3.1% participants with PD and 100% controls. The biomarker profile of older adults with PD was defined by higher circulating levels of interleukin (IL) 8, macrophage inflammatory protein (MIP)-1β, phosphoethanolamine, and proline, and by lower concentrations of citrulline, IL9, and MIP-1α. Our innovative approach allowed identifying and evaluating the classification performance of a set of potential biomarkers for PD in older adults. Future studies are warranted to establish whether these biomolecules could serve as biomarkers for PD as well as unveil new targets for interventions.
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http://dx.doi.org/10.1007/s11357-020-00192-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7525911PMC
October 2020

ERK3/MAPK6 controls IL-8 production and chemotaxis.

Elife 2020 04 21;9. Epub 2020 Apr 21.

Cell Biology Unit, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

ERK3 is a ubiquitously expressed member of the atypical mitogen activated protein kinases (MAPKs) and the physiological significance of its short half-life remains unclear. By employing gastrointestinal 3D organoids, we detect that ERK3 protein levels steadily decrease during epithelial differentiation. ERK3 is not required for 3D growth of human gastric epithelium. However, ERK3 is stabilized and activated in tumorigenic cells, but deteriorates over time in primary cells in response to lipopolysaccharide (LPS). ERK3 is necessary for production of several cellular factors including interleukin-8 (IL-8), in both, normal and tumorigenic cells. Particularly, ERK3 is critical for AP-1 signaling through its interaction and regulation of c-Jun protein. The secretome of ERK3-deficient cells is defective in chemotaxis of neutrophils and monocytes both in vitro and in vivo. Further, knockdown of ERK3 reduces metastatic potential of invasive breast cancer cells. We unveil an ERK3-mediated regulation of IL-8 and epithelial secretome for chemotaxis.
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http://dx.doi.org/10.7554/eLife.52511DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7192585PMC
April 2020

The "develOpment of metabolic and functional markers of Dementia IN Older people" (ODINO) Study: Rationale, Design and Methods.

J Pers Med 2020 Apr 9;10(2). Epub 2020 Apr 9.

Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, 00168 Rome, Italy.

Mild cognitive impairment (MCI), also termed mild neurocognitive disorder, includes a heterogeneous group of conditions characterized by declines in one or more cognitive domains greater than that expected during "normal" aging but not severe enough to impair functional abilities. MCI has been associated with an increased risk of developing dementia and even considered an early stage of it. Therefore, noninvasively accessible biomarkers of MCI are highly sought after for early identification of the condition. Systemic inflammation, metabolic perturbations, and declining physical performance have been described in people with MCI. However, whether biological and functional parameters differ across MCI neuropsychological subtypes is presently debated. Likewise, the predictive value of existing biomarkers toward MCI conversion into dementia is unclear. The "develOpment of metabolic and functional markers of Dementia IN Older people" (ODINO) study was conceived as a multi-dimensional investigation in which multi-marker discovery will be coupled with innovative statistical approaches to characterize patterns of systemic inflammation, metabolic perturbations, and physical performance in older adults with MCI. The ultimate aim of ODINO is to identify potential biomarkers specific for MCI subtypes and predictive of MCI conversion into Alzheimer's disease or other forms of dementia over a three-year follow-up. Here, we describe the rationale, design, and methods of ODINO.
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http://dx.doi.org/10.3390/jpm10020022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354545PMC
April 2020

Retention Modelling of Phenoxy Acid Herbicides in Reversed-Phase HPLC under Gradient Elution.

Molecules 2020 Mar 11;25(6). Epub 2020 Mar 11.

Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, Coppito, 67100 L'Aquila (AQ), Italy.

Phenoxy acid herbicides are used worldwide and are potential contaminants of drinking water. Reversed phase high-performance liquid chromatography (RP-HPLC) is commonly used to monitor phenoxy acid herbicides in water samples. RP-HPLC retention of phenoxy acids is affected by both mobile phase composition and pH, but the synergic effect of these two factors, which is also dependent on the structure and pKa of solutes, cannot be easily predicted. In this paper, to support the setup of RP-HPLC analysis of phenoxy acids under application of linear mobile phase gradients we modelled the simultaneous effect of the molecular structure and the elution conditions (pH, initial acetonitrile content in the eluent and gradient slope) on the retention of the solutes. In particular, the chromatographic conditions and the molecular descriptors collected on the analyzed compounds were used to estimate the retention factor k by Partial Least Squares (PLS) regression. Eventually, a variable selection approach, Genetic Algorithms, was used to reduce the model complexity and allow an easier interpretation. The PLS model calibrated on the retention data of 15 solutes and successively tested on three external analytes provided satisfying and reliable results.
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http://dx.doi.org/10.3390/molecules25061262DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7144001PMC
March 2020

Mitochondrial Signatures in Circulating Extracellular Vesicles of Older Adults with Parkinson's Disease: Results from the EXosomes in PArkiNson's Disease (EXPAND) Study.

J Clin Med 2020 Feb 12;9(2). Epub 2020 Feb 12.

Institute of Internal Medicine and Geriatrics, Università Cattolica del Sacro Cuore, 00168 Rome, Italy.

Systemic inflammation and mitochondrial dysfunction are involved in neurodegeneration in Parkinson's disease (PD). Extracellular vesicle (EV) trafficking may link inflammation and mitochondrial dysfunction. In the present study, circulating small EVs (sEVs) from 16 older adults with PD and 12 non-PD controls were purified and characterized. A panel of serum inflammatory biomolecules was measured by multiplex immunoassay. Protein levels of three tetraspanins (CD9, CD63, and CD81) and selected mitochondrial markers (adenosine triphosphate 5A (ATP5A), mitochondrial cytochrome C oxidase subunit I (MTCOI), nicotinamide adenine dinucleotide reduced form (NADH):ubiquinone oxidoreductase subunit B8 (NDUFB8), NADH:ubiquinone oxidoreductase subunit S3 (NDUFS3), succinate dehydrogenase complex iron sulfur subunit B (SDHB), and ubiquinol-cytochrome C reductase core protein 2 (UQCRC2)) were quantified in purified sEVs by immunoblotting. Relative to controls, PD participants showed a greater amount of circulating sEVs. Levels of CD9 and CD63 were lower in the sEV fraction of PD participants, whereas those of CD81 were similar between groups. Lower levels of ATP5A, NDUFS3, and SDHB were detected in sEVs from PD participants. No signal was retrieved for UQCRC2, MTCOI, or NDUFB8 in either participant group. To identify a molecular signature in circulating sEVs in relationship to systemic inflammation, a low level-fused (multi-platform) partial least squares discriminant analysis was applied. The model correctly classified 94.2% ± 6.1% PD participants and 66.7% ± 5.4% controls, and identified seven biomolecules as relevant (CD9, NDUFS3, C-reactive protein, fibroblast growth factor 21, interleukin 9, macrophage inflammatory protein 1β, and tumor necrosis factor alpha). In conclusion, a mitochondrial signature was identified in circulating sEVs from older adults with PD, in association with a specific inflammatory profile. In-depth characterization of sEV trafficking may allow identifying new biomarkers for PD and possible targets for personalized interventions.
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http://dx.doi.org/10.3390/jcm9020504DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7074517PMC
February 2020

Reduction of repeatability error for analysis of variance-Simultaneous Component Analysis (REP-ASCA): Application to NIR spectroscopy on coffee sample.

Anal Chim Acta 2020 Mar 16;1101:23-31. Epub 2019 Dec 16.

ITAP, Univ Montpellier, Irstea, Montpellier SupAgro, Montpellier, France.

A method to reduce repeatability error in multivariate data for Analysis of variance-Simultaneous Component Analysis (REP-ASCA) has been developed. This method proposes to adapt the acquisition protocol by adding a set containing repeated measures for describing repeatability error. Then, an orthogonal projection is performed in the row-space to reduce the repeatability error of the original dataset. Finally, ASCA is performed on the orthogonalized dataset. This method was evaluated on NIR spectral data of coffee beans. This study shows that the repeatability error due to physical variations between measurements can alter results of the analysis of variance. These effects are predominant in factors analysis and can be seen on spectra as constant or non-constant baselines. By reducing repeatability error with REP-ASCA, baselines are removed and factor analysis provides more information about chemical content of the factors of interest.
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http://dx.doi.org/10.1016/j.aca.2019.12.024DOI Listing
March 2020

Microglial A20 Protects the Brain from CD8 T-Cell-Mediated Immunopathology.

Cell Rep 2020 02;30(5):1585-1597.e6

Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg University of Mainz, 55131 Mainz, Germany. Electronic address:

Tumor-necrosis-factor-alpha-induced protein 3 (TNFAIP3), or A20, is a ubiquitin-modifying protein and negative regulator of canonical nuclear factor κB (NF-κB) signaling. Several single-nucleotide polymorphisms in TNFAIP3 are associated with autoimmune diseases, suggesting a role in tissue inflammation. While the role of A20 in peripheral immune cells has been well investigated, less is known about its role in the central nervous system (CNS). Here, we show that microglial A20 is crucial for maintaining brain homeostasis. Without microglial A20, CD8 T cells spontaneously infiltrate the CNS and acquire a viral response signature. The combination of infiltrating CD8 T cells and activated A20-deficient microglia leads to an increase in VGLUT1 terminals and frequency of spontaneous excitatory currents. Ultimately, A20-deficient microglia upregulate genes associated with the antiviral response and neurodegenerative diseases. Together, our data suggest that microglial A20 acts as a sensor for viral infection and a master regulator of CNS homeostasis.
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http://dx.doi.org/10.1016/j.celrep.2019.12.097DOI Listing
February 2020

Gut metabolomics profiling of non-small cell lung cancer (NSCLC) patients under immunotherapy treatment.

J Transl Med 2020 02 3;18(1):49. Epub 2020 Feb 3.

Department of Clinical and Molecular Medicine, Sapienza University of Rome, Rome, Italy.

Background: Despite the efficacy of immune checkpoint inhibitors (ICIs) only the 20-30% of treated patients present long term benefits. The metabolic changes occurring in the gut microbiota metabolome are herein proposed as a factor potentially influencing the response to immunotherapy.

Methods: The metabolomic profiling of gut microbiota was characterized in 11 patients affected by non-small cell lung cancer (NSCLC) treated with nivolumab in second-line treatment with anti-PD-1 nivolumab. The metabolomics analyses were performed by GC-MS/SPME and H-NMR in order to detect volatile and non-volatile metabolites. Metabolomic data were processed by statistical profiling and chemometric analyses.

Results: Four out of 11 patients (36%) presented early progression, while the remaining 7 out of 11 (64%) presented disease progression after 12 months. 2-Pentanone (ketone) and tridecane (alkane) were significantly associated with early progression, and on the contrary short chain fatty acids (SCFAs) (i.e., propionate, butyrate), lysine and nicotinic acid were significantly associated with long-term beneficial effects.

Conclusions: Our preliminary data suggest a significant role of gut microbiota metabolic pathways in affecting response to immunotherapy. The metabolic approach could be a promising strategy to contribute to the personalized management of cancer patients by the identification of microbiota-linked "indicators" of early progressor and long responder patients.
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http://dx.doi.org/10.1186/s12967-020-02231-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6998840PMC
February 2020

Identification of a Circulating Amino Acid Signature in Frail Older Persons with Type 2 Diabetes Mellitus: Results from the Metabofrail Study.

Nutrients 2020 Jan 12;12(1). Epub 2020 Jan 12.

Università Cattolica del Sacro Cuore, 00168 Rome, Italy.

Diabetes and frailty are highly prevalent conditions that impact the health status of older adults. Perturbations in protein/amino acid metabolism are associated with both functional impairment and type 2 diabetes mellitus (T2DM). In the present study, we compared the concentrations of a panel of circulating 37 amino acids and derivatives between frail/pre-frail older adults with T2DM and robust non-diabetic controls. Sixty-six functionally impaired older persons aged 70+ with T2DM and 30 age and sex-matched controls were included in the analysis. We applied a partial least squares-discriminant analysis (PLS-DA)-based analytical strategy to characterize the metabotype of study participants. The optimal complexity of the PLS-DA model was found to be two latent variables. The proportion of correct classification was 94.1 ± 1.9% for frail/pre-frail persons with T2DM and 100% for control participants. Functionally impaired older persons with T2DM showed higher levels of 3-methyl histidine, alanine, arginine, glutamic acid, ethanolamine sarcosine, and tryptophan. Control participants had higher levels of ornithine and taurine. These findings indicate that a specific profile of amino acids and derivatives characterizes pre-frail/frail older persons with T2DM. The dissection of these pathways may provide novel insights into the metabolic perturbations involved in the disabling cascade in older persons with T2DM.
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http://dx.doi.org/10.3390/nu12010199DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019630PMC
January 2020