136 research outputs found
Menadione-induced oxidative stress re-shapes the oxylipin profile of Aspergillus flavus and its lifestyle
Aspergillus flavus is an efficient producer of mycotoxins, particularly aflatoxin B1, probably the most hepatocarcinogenic naturally-occurring compound. Although the inducing agents of toxin synthesis are not unanimously identified, there is evidence that oxidative stress is one of the main actors in play. In our study, we use menadione, a quinone extensively implemented in studies on ROS response in animal cells, for causing stress to A. flavus. For uncovering the molecular determinants that drive A. flavus in challenging oxidative stress conditions, we have evaluated a wide spectrum of several different parameters, ranging from metabolic (ROS and oxylipin profile) to transcriptional analysis (RNA-seq). There emerges a scenario in which A. flavus activates several metabolic processes under oxidative stress conditions for limiting the ROS-associated detrimental effects, as well as for triggering adaptive and escape strategies
PARAMETRIC PARADIGMA: EXCEPTIONAL COFFERED CEILING ARCHITECTURE VS HBIM
The scientific community is confirming the advantages of using BIM in the processes of conservation, management, and
intervention over architectural-historical heritage. However, many difficulties remain in the transcription process of
elements of the built environment, especially when the objective of the model is to support decision-making processes in
restoration operations. Even for apparently simple elements, the procedures are not trivial; the need to define the most
adequate operational strategies remains. In the context of this study, a possible approach concerning the documentation
of a coffered ceiling has been proposed, a case study which takes into consideration the need to discretize information (to
make it effective, transmissible, and understandable) and the potential offered by the combined use of further software
automatization
Overcome Chemoresistance: Biophysical and Structural Analysis of Synthetic FHIT-Derived Peptides
The fragile histidine triad (FHIT) protein is a member of the large and ubiquitous histidine
triad (HIT) family of proteins. On the basis of genetic evidence, it has been postulated that
the FHIT protein may function as tumor suppressor, implying a role for the FHIT protein in
carcinogenesis. Recently, Gaudio et al. reported that FHIT binds and delocalizes annexin
A4 (ANXA4) from plasma membrane to cytosol in paclitaxel-resistant lung cancer cells,
thus restoring their chemosensitivity to the drug. They also identified the smallest protein
sequence of the FHIT still interacting with ANXA4, ranging fromposition 7 to 13: QHLIKPS.
This short sequence of FHIT protein was not only able to bind ANXA4 but also to hold its
target in the cytosol during paclitaxel treatment, thus avoiding ANXA4 translocation to the
inner side of the cell membrane. Starting from these results, to obtain much information
about structure requirements involved in the interaction of the peptide mentioned above,
we synthetized a panel of seven peptides through an Ala-scan approach. In detail, to study
the binding of FHIT derived peptides with ANXA4, we applied a combination of different
biophysical techniques such as differential scanning fluorimetry (DSF), surface plasmon
resonance (SPR), and microscale thermophoresis (MST). Circular dichroism (CD) and
nuclear magnetic resonance (NMR) were used to determine the conformational structure
of the lead peptide (7–13) and peptides generated from ala-scan technique. The
application of different biophysical and structural techniques, integrated by a
preliminary biological evaluation, allowed us to build a solid structure activity
relationship on the synthesized peptides
Decipher non-canonical SPAST splicing mutations with the help of functional assays in patients affected by spastic paraplegia 4 (SPG4)
Flowchart showing the molecular approach used to decipher the non-canonical splicing mutations
Impairment of T cell development and acute inflammatory response in HIV-1 Tat transgenic mice
Immune activation and chronic inflammation are hallmark features of HIV infection causing T-cell depletion and cellular immune dysfunction in AIDS. Here, we addressed the issue whether HIV-1 Tat could affect T cell development and acute inflammatory response by generating a transgenic mouse expressing Tat in lymphoid tissue. Tat-Tg mice showed thymus atrophy and the maturation block from DN4 to DP thymic subpopulations, resulting in CD4(+) and CD8(+) T cells depletion in peripheral blood. In Tat-positive thymus, we observed the increased p65/NF-κB activity and deregulated expression of cytokines/chemokines and microRNA-181a-1, which are involved in T-lymphopoiesis. Upon LPS intraperitoneal injection, Tat-Tg mice developed an abnormal acute inflammatory response, which was characterized by enhanced lethality and production of inflammatory cytokines. Based on these findings, Tat-Tg mouse could represent an animal model for testing adjunctive therapies of HIV-1-associated inflammation and immune deregulation
Tracking the evolution of epialleles during neural differentiation and brain development: D- aspartate oxidase as a model gene
Efficacy and safety of tocilizumab in patients with polyarticular-course juvenile idiopathic arthritis: Results from a phase 3, randomised, double-blind withdrawal trial
A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease
Background: Mechanisms of myocardial ischemia in obstructive and non-obstructive coronary artery disease (CAD), and the interplay between clinical, functional, biological and psycho-social features, are still far to be fully elucidated. Objectives: To develop a machine-learning (ML) model for the supervised prediction of obstructive versus non-obstructive CAD. Methods: From the EVA study, we analysed adults hospitalized for IHD undergoing conventional coronary angiography (CCA). Non-obstructive CAD was defined by a stenosis < 50% in one or more vessels. Baseline clinical and psycho-socio-cultural characteristics were used for computing a Rockwood and Mitnitski frailty index, and a gender score according to GENESIS-PRAXY methodology. Serum concentration of inflammatory cytokines was measured with a multiplex flow cytometry assay. Through an XGBoost classifier combined with an explainable artificial intelligence tool (SHAP), we identified the most influential features in discriminating obstructive versus non-obstructive CAD. Results: Among the overall EVA cohort (n = 509), 311 individuals (mean age 67 ± 11 years, 38% females; 67% obstructive CAD) with complete data were analysed. The ML-based model (83% accuracy and 87% precision) showed that while obstructive CAD was associated with higher frailty index, older age and a cytokine signature characterized by IL-1β, IL-12p70 and IL-33, non-obstructive CAD was associated with a higher gender score (i.e., social characteristics traditionally ascribed to women) and with a cytokine signature characterized by IL-18, IL-8, IL-23. Conclusions: Integrating clinical, biological, and psycho-social features, we have optimized a sex- and gender-unbiased model that discriminates obstructive and non-obstructive CAD. Further mechanistic studies will shed light on the biological plausibility of these associations. Clinical trial registration: NCT02737982
An explainable model of host genetic interactions linked to COVID-19 severity
We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients
A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death
: The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10-8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10-8). A total of 113 variants were associated with survival at P-value < 1.0 × 10-5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways
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