Traditional farmers’ varieties: a valuable source of genetic variability for biofortification programs

Several studies underlined the superiority from a nutritional point of view of ancient varieties. In the last years the interest for landraces has been growing, for this reason preservation and valorisation of these genetic sources is very important. In particular these varieties are source of precious genetic variability interesting from a scientific point of view to preserve biodiversity but also for biofortification programs aimed to support small rural communities, where the particular maize germplasm has been developed. In this work we characterized from the nutritional point of view 13 ancient Italian varieties and one coming from Spain (Millo Corvo). In this pre-breeding work we demonstrate the nutritional superiority of ancient varieties if compared with modern hybrids. In particular Spinato di Gandino is the best variety for milling properties and for oil, protein, and total phosphorus content; Storo is the best variety for calorific value and for carotenoids and free phosphorus content. Using these varieties in the next future we will start a bio-fortification program aimed to obtain new populations with improved yields and high nutritional value

3D Microfluidic model for evaluating immunotherapy efficacy by tracking dendritic cell behaviour toward tumor cells

Immunotherapy efficacy relies on the crosstalk within the tumor microenvironment between cancer and dendritic cells (DCs) resulting in the induction of a potent and effective antitumor response. DCs have the specific role of recognizing cancer cells, taking up tumor antigens (Ags) and then migrating to lymph nodes for Ag (cross)-presentation to naïve T cells. Interferon-α-conditioned DCs (IFN-DCs) exhibit marked phagocytic activity and the special ability of inducing Ag-specific T-cell response. Here, we have developed a novel microfluidic platform recreating tightly interconnected cancer and immune systems with specific 3D environmental properties, for tracking human DC behaviour toward tumor cells. By combining our microfluidic platform with advanced microscopy and a revised cell tracking analysis algorithm, it was possible to evaluate the guided efficient motion of IFN-DCs toward drug-treated cancer cells and the succeeding phagocytosis events. Overall, this platform allowed the dissection of IFN-DC-cancer cell interactions within 3D tumor spaces, with the discovery of major underlying factors such as CXCR4 involvement and underscored its potential as an innovative tool to assess the efficacy of immunotherapeutic approaches

Risk factors for gram-negative bacterial infection of cardiovascular implantable electronic devices: Multicentre observational study (CarDINe Study)

Background: Infections of cardiovascular implantable electronic devices (CIED) are mainly due to Gram-positive bacteria (GPB). Data about Gram-negative bacteria CIED (GNB-CIED) infections are limited. This study aimed to investigate risk factors, clinical and diagnostic characteristics, and outcome of patients with GNB-CIED. Methods: A multicentre, international, retrospective, case-control-control study was performed on patients undergoing CIED implantation from 2015 to 2019 in 17 centres across Europe. For each patient diagnosed with GNB-CIED, one matching control with GPB-CIED infection and two matching controls without infection were selected. Results: A total of 236 patients were enrolled: 59 with GNB-CIED infection, 59 with GPB-CIED infection and 118 without infection. No between-group differences were found regarding clinical presentation, diagnostic and therapeutic management. A trend toward a higher rate of fluorodeoxyglucose positron emission computed tomography (FDG PET/CT) positivity was observed among patients with GNB than in those with GPB-CIED infection (85.7% vs. 66.7%; P = 0.208). Risk factors for GNB-CIED infection were Charlson Comorbidity Index Score (relative risk reduction, RRR = 1.211; P = 0.011), obesity (RRR = 5.122; P = 0.008), ventricular-pacing ventricular-sensing inhibited-response pacemaker implantation (RRR = 3.027; P = 0.006) and right subclavian vein site of implantation (RRR = 5.014; P = 0.004). At 180-day survival analysis, GNB-CIED infection was associated with increased mortality risk (HR = 1.842; P = 0.067). Conclusions: Obesity, high number of comorbidities and right subclavian vein implantation site were associated with increased risk of GNB-CIED infection. A prompt therapeutic intervention that may be guided using FDG PET/CT is suggested in patients with GNB-CIED infection, considering the poorer outcome observed in this group

Predictive model for bacterial co-infection in patients hospitalized for COVID-19: a multicenter observational cohort study

Objective: The aim of our study was to build a predictive model able to stratify the risk of bacterial co-infection at hospitalization in patients with COVID-19. Methods: Multicenter observational study of adult patients hospitalized from February to December 2020 with confirmed COVID-19 diagnosis. Endpoint was microbiologically documented bacterial co-infection diagnosed within 72 h from hospitalization. The cohort was randomly split into derivation and validation cohort. To investigate risk factors for co-infection univariable and multivariable logistic regression analyses were performed. Predictive risk score was obtained assigning a point value corresponding to β-coefficients to the variables in the multivariable model. ROC analysis in the validation cohort was used to estimate prediction accuracy. Results: Overall, 1733 patients were analyzed: 61.4% males, median age 69 years (IQR 57-80), median Charlson 3 (IQR 2-6). Co-infection was diagnosed in 110 (6.3%) patients. Empirical antibiotics were started in 64.2 and 59.5% of patients with and without co-infection (p = 0.35). At multivariable analysis in the derivation cohort: WBC ≥ 7.7/mm3, PCT ≥ 0.2 ng/mL, and Charlson index ≥ 5 were risk factors for bacterial co-infection. A point was assigned to each variable obtaining a predictive score ranging from 0 to 5. In the validation cohort, ROC analysis showed AUC of 0.83 (95%CI 0.75-0.90). The optimal cut-point was ≥2 with sensitivity 70.0%, specificity 75.9%, positive predictive value 16.0% and negative predictive value 97.5%. According to individual risk score, patients were classified at low (point 0), intermediate (point 1), and high risk (point ≥ 2). CURB-65 ≥ 2 was further proposed to identify patients at intermediate risk who would benefit from early antibiotic coverage. Conclusions: Our score may be useful in stratifying bacterial co-infection risk in COVID-19 hospitalized patients, optimizing diagnostic testing and antibiotic use

Large-scale evaluation of shotgun triacylglycerol profiling for the fast detection of olive oil adulteration

Fast and effective analytical screening tools providing new suitable authenticity markers and applicable to a large number of samples are required to efficiently control the global olive oil (OO) production, and allow the rapid detection of low levels of adulterants even with fatty acid composition similar to OO. The present study aims to develop authentication models for the comprehensive detection of illegal blends of OO with adulterants including different types of high linoleic (HL) and high oleic (HO) vegetable oils at low concentrations (2-10%) based on shotgun triacylglycerol (TAG) profile obtained by Flow Injection Analysis-Heated Electrospray Ionisation-High Resolution Mass Spectrometry (FIA-HESI-HRMS) at a large-scale experimental design. The sample set covers a large natural variability of both OO and adulterants, resulting in more than one thousand samples analysed. A combined PLS-DA binary modelling based on shotgun TAG profiling proved to be a fit for purpose screening tool in terms of efficiency and applicability. The external validation resulted in the correct classification of the 86.8% of the adulterated samples (diagnostic sensitivity = 0.87), and the 81.1% of the genuine samples (diagnostic specificity = 0.81), with an 85.1% overall correct classification (efficiency = 0.85)

Quantitative dopamine transporter imaging assessment in Parkinson’s disease (PD) patients carrying GBA gene mutations compared with Idiopathic PD patients: A case-control study

Background: Genetic risk factors impact around 15% of Parkinson’s disease (PD) patients and at least 23 variants have been identified including Glucocerebrosidase (GBA) gene variants. Using different clinical and instrumental qualitative-based data, various studies have been published on GBA-PD cohorts which suggested possible differences in dopaminergic nigrostriatal denervation pattern, particularly in caudate and putamen nuclei. Methods: This retrospective study included two consecutive homogenous cohorts of GBA-PD and idiopathic (I-PD) patients. Each consecutive GBA-PD patient has been matched with a 1:1 pairing method with a consecutive I-PD subject according to age, age at disease onset, sex, Hoehn & Yahr (H&Y) staging scale and comorbidity level (CCI). Semiquantitative volumetric data by the DaTQUANTTM software integrated in the DaTSCAN exam performed at time of the diagnosis (SPECT imaging performed according to current guidelines of I-123 FPCIT SPECT imaging) were extrapolated. Bilateral specific binding ratios (SBR) at putamen and caudate levels were calculated, using the occipital lobes uptake. The Mann–Whitney test was performed to compare the two cohorts while the Spearman’s test was used to find correlations between motor and volumetric data in each group. Bonferroni correction was used to account for multiple comparisons. Results: Two cohorts of 25 patients each (GBA-PD and I-PD), were included. By comparing GBA-PD and I-PD patients, lower SBR values were found in the most affected anterior putamen and left caudate of the GBA-PD cohort. Furthermore, in the GBA-PD cohort the SBR of the most affected posterior putamen negatively correlated with the H&Y scale. However, none of these differences or correlations remained significant after Bonferroni correction for multiple comparisons. Conclusions: We observed differences in SBR values in GBA-PD patients compared with I-PD. However, these differences were no longer significant after Bonferroni multiple comparisons correction highlighting the need for larger, longitudinal studies

Large-scale evaluation of shotgun triacylglycerol profiling for the fast detection of olive oil adulteration

Final version is available in open access in publisher’s site.-- This abstract is based on the published article: Beatriz Quintanilla-Casas, Giulia Strocchi, Julen Bustamante, Berta Torres-Cobos, Francesc Guardiola, Wenceslao Moreda, José Manuel Martínez-Rivas, Enrico Valli, Alessandra Bendini, Tullia Gallina Toschi, Alba Tres, Stefania Vichi. Large-scale evaluation of shotgun triacylglycerol profiling for the fast detection of olive oil adulteration. Food Control, Volume 123, 2021, 107851, https://doi.org/10.1016/j.foodcont.2020.107851.-- http://hdl.handle.net/10261/229187Peer reviewe

Cardiac autonomic control in Rett syndrome: Insights from heart rate variability analysis

Rett syndrome (RTT) is a rare and severe neurological disorder mainly affecting females, usually linked to methyl-CpG-binding protein 2 (MECP2) gene mutations. Manifestations of RTT typically include loss of purposeful hand skills, gait and motor abnormalities, loss of spoken language, stereotypic hand movements, epilepsy, and autonomic dysfunction. Patients with RTT have a higher incidence of sudden death than the general population. Literature data indicate an uncoupling between measures of breathing and heart rate control that could offer insight into the mechanisms that lead to greater vulnerability to sudden death. Understanding the neural mechanisms of autonomic dysfunction and its correlation with sudden death is essential for patient care. Experimental evidence for increased sympathetic or reduced vagal modulation to the heart has spurred efforts to develop quantitative markers of cardiac autonomic profile. Heart rate variability (HRV) has emerged as a valuable non-invasive test to estimate the modulation of sympathetic and parasympathetic branches of the autonomic nervous system (ANS) to the heart. This review aims to provide an overview of the current knowledge on autonomic dysfunction and, in particular, to assess whether HRV parameters can help unravel patterns of cardiac autonomic dysregulation in patients with RTT. Literature data show reduced global HRV (total spectral power and R-R mean) and a shifted sympatho-vagal balance toward sympathetic predominance and vagal withdrawal in patients with RTT compared to controls. In addition, correlations between HRV and genotype and phenotype features or neurochemical changes were investigated. The data reported in this review suggest an important impairment in sympatho-vagal balance, supporting possible future research scenarios, targeting ANS

APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research

Introduction: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several studies have been aimed at identifying biomarkers able to predict benefit from these therapies and create a prediction model of response, despite this there is a lack of information to help clinicians in the choice of therapy for lung cancer patients with advanced disease. This is primarily due to the complexity of lung cancer biology, where a single or few biomarkers are not sufficient to provide enough predictive capability to explain biologic differences; other reasons include the paucity of data collected by single studies performed in heterogeneous unmatched cohorts and the methodology of analysis. In fact, classical statistical methods are unable to analyze and integrate the magnitude of information from multiple biological and clinical sources (eg, genomics, transcriptomics, and radiomics). Methods and objectives: APOLLO11 is an Italian multicentre, observational study involving patients with a diagnosis of advanced lung cancer (NSCLC and SCLC) treated with innovative therapies. Retrospective and prospective collection of multiomic data, such as tissue- (eg, for genomic, transcriptomic analysis) and blood-based biologic material (eg, ctDNA, PBMC), in addition to clinical and radiological data (eg, for radiomic analysis) will be collected. The overall aim of the project is to build a consortium integrating different datasets and a virtual biobank from participating Italian lung cancer centers. To face with the large amount of data provided, AI and ML techniques will be applied will be applied to manage this large dataset in an effort to build an R-Model, integrating retrospective and prospective population-based data. The ultimate goal is to create a tool able to help physicians and patients to make treatment decisions. Conclusion: APOLLO11 aims to propose a breakthrough approach in lung cancer research, replacing the old, monocentric viewpoint towards a multicomprehensive, multiomic, multicenter model. Multicenter cancer datasets incorporating common virtual biobank and new methodologic approaches including artificial intelligence, machine learning up to deep learning is the road to the future in oncology launched by this project