Identification of new polymorphic regions and differentiation of cultivated olives (Olea europaea L.) through plastome sequence comparison

<p>Abstract</p> <p>Background</p> <p>The cultivated olive (<it>Olea europaea </it>L.) is the most agriculturally important species of the Oleaceae family. Although many studies have been performed on plastid polymorphisms to evaluate taxonomy, phylogeny and phylogeography of <it>Olea </it>subspecies, only few polymorphic regions discriminating among the agronomically and economically important olive cultivars have been identified. The objective of this study was to sequence the entire plastome of olive and analyze many potential polymorphic regions to develop new inter-cultivar genetic markers.</p> <p>Results</p> <p>The complete plastid genome of the olive cultivar Frantoio was determined by direct sequence analysis using universal and novel PCR primers designed to amplify all overlapping regions. The chloroplast genome of the olive has an organisation and gene order that is conserved among numerous Angiosperm species and do not contain any of the inversions, gene duplications, insertions, inverted repeat expansions and gene/intron losses that have been found in the chloroplast genomes of the genera <it>Jasminum </it>and <it>Menodora</it>, from the same family as <it>Olea</it>.</p> <p>The annotated sequence was used to evaluate the content of coding genes, the extent, and distribution of repeated and long dispersed sequences and the nucleotide composition pattern. These analyses provided essential information for structural, functional and comparative genomic studies in olive plastids. Furthermore, the alignment of the olive plastome sequence to those of other varieties and species identified 30 new organellar polymorphisms within the cultivated olive.</p> <p>Conclusions</p> <p>In addition to identifying mutations that may play a functional role in modifying the metabolism and adaptation of olive cultivars, the new chloroplast markers represent a valuable tool to assess the level of olive intercultivar plastome variation for use in population genetic analysis, phylogenesis, cultivar characterisation and DNA food tracking.</p

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 &lt; 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&nbsp;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

The Sex-Specific Detrimental Effect of Diabetes and Gender-Related Factors on Pre-admission Medication Adherence Among Patients Hospitalized for Ischemic Heart Disease: Insights From EVA Study

Background: Sex and gender-related factors have been under-investigated as relevant determinants of health outcomes across non-communicable chronic diseases. Poor medication adherence results in adverse clinical outcomes and sex differences have been reported among patients at high cardiovascular risk, such as diabetics. The effect of diabetes and gender-related factors on medication adherence among women and men at high risk for ischemic heart disease (IHD) has not yet been fully investigated.Aim: To explore the role of sex, gender-related factors, and diabetes in pre-admission medication adherence among patients hospitalized for IHD.Materials and Methods: Data were obtained from the Endocrine Vascular disease Approach (EVA) (ClinicalTrials.gov Identifier: NCT02737982), a prospective cohort of patients admitted for IHD. We selected patients with baseline information regarding the presence of diabetes, cardiovascular risk factors, and gender-related variables (i.e., gender identity, gender role, gender relations, institutionalized gender). Our primary outcome was the proportion of pre-admission medication adherence defined through a self-reported questionnaire. We performed a sex-stratified analysis of clinical and gender-related factors associated with pre-admission medication adherence.Results: Two-hundred eighty patients admitted for IHD (35% women, mean age 70), were included. Around one-fourth of the patients were low-adherent to therapy before hospitalization, regardless of sex. Low-adherent patients were more likely diabetic (40%) and employed (40%). Sex-stratified analysis showed that low-adherent men were more likely to be employed (58 vs. 33%) and not primary earners (73 vs. 54%), with more masculine traits of personality, as compared with medium-high adherent men. Interestingly, women reporting medication low-adherence were similar for clinical and gender-related factors to those with medium-high adherence, except for diabetes (42 vs. 20%, p = 0.004). In a multivariate adjusted model only employed status was associated with poor medication adherence (OR 0.55, 95%CI 0.31–0.97). However, in the sex-stratified analysis, diabetes was independently associated with medication adherence only in women (OR 0.36; 95%CI 0.13–0.96), whereas a higher masculine BSRI was the only factor associated with medication adherence in men (OR 0.59, 95%CI 0.35–0.99).Conclusion: Pre-admission medication adherence is common in patients hospitalized for IHD, regardless of sex. However, patient-related factors such as diabetes, employment, and personality traits are associated with adherence in a sex-specific manner

Forward rapidity J/ψ production as a function of charged-particle multiplicity in pp collisions at s \sqrt{s} = 5.02 and 13 TeV

International audienceThe production of J/ψ is measured as a function of charged-particle multiplicity at forward rapidity in proton-proton (pp) collisions at center-of-mass energies $\sqrt{s}$ = 5.02 and 13 TeV. The J/ψ mesons are reconstructed via their decay into dimuons in the rapidity interval (2.5 < y < 4.0), whereas the charged-particle multiplicity density (dN$_{ch}$/dη) is measured at midrapidity (|η| < 1). The production rate as a function of multiplicity is reported as the ratio of the yield in a given multiplicity interval to the multiplicity-integrated one. This observable shows a linear increase with charged-particle multiplicity normalized to the corresponding average value for inelastic events (dN$_{ch}$/dη/〈dN$_{ch}$/dη〉), at both the colliding energies. Measurements are compared with available ALICE results at midrapidity and theoretical model calculations. First measurement of the mean transverse momentum (〈p$_{T}$〉) of J/ψ in pp collisions exhibits an increasing trend as a function of dN$_{ch}$/dη/〈dN$_{ch}$/dη〉 showing a saturation towards high charged-particle multiplicities.[graphic not available: see fulltext

Enhanced deuteron coalescence probability in jets

The transverse-momentum (pT) spectra and coalescence parameters B2 of (anti)deuterons are measured in pp collisions at s√=13 TeV for the first time in and out of jets. In this measurement, the direction of the leading particle with the highest pT in the event (pleadT>5 GeV/c) is used as an approximation for the jet axis. The event is consequently divided into three azimuthal regions and the jet signal is obtained as the difference between the Toward region, that contains jet fragmentation products in addition to the underlying event (UE), and the Transverse region, which is dominated by the UE. The coalescence parameter in the jet is found to be approximately a factor of 10 larger than that in the underlying event. This experimental observation is consistent with the coalescence picture and can be attributed to the smaller average phase-space distance between nucleons inside the jet cone as compared to the underlying event. The results presented in this Letter are compared to predictions from a simple nucleon coalescence model, where the phase space distributions of nucleons are generated using PYTHIA 8 with the Monash 2013 tuning, and to predictions from a deuteron production model based on ordinary nuclear reactions with parametrized energy-dependent cross sections tuned on data. The latter model is implemented in PYTHIA 8.3. Both models reproduce the observed large difference between in-jet and out-of-jet coalescence parameters, although the almost flat trend of the BJet2 is not reproduced by the models, which instead give a decreasing trend