Electrochemical phosphate detection in oligotrophic seawater with a stand-alone plastic electrode

The northern Adriatic Sea is a particular water system, in which the levels of nutrients are commonly low or unbalanced. In general, phosphate detection can be done with the classical molybdenum-blue method. However, the method cannot be used in oligotrophic seawater samples due to its low sensitivity and high interference problems. In this study, we present a new electrochemical method, based on the application of a plastic conductive electrode containing a molybdenum reagent embedded. The sensitivity for phosphate was high enough to detect this nutrient in oligotrophic seawater

Chapter Electrochemical phosphate detection in oligotrophic seawater with a stand-alone plastic electrode

The northern Adriatic Sea is a particular water system, in which the levels of nutrients are commonly low or unbalanced. In general, phosphate detection can be done with the classical molybdenum-blue method. However, the method cannot be used in oligotrophic seawater samples due to its low sensitivity and high interference problems. In this study, we present a new electrochemical method, based on the application of a plastic conductive electrode containing a molybdenum reagent embedded. The sensitivity for phosphate was high enough to detect this nutrient in oligotrophic seawater

New eco-sustainable feed in aquaculture: influence of insect-based diets on the content of potentially toxic elements in the experimental model zebrafish (Danio rerio).

According to the concept of circular economy, insects represent good candidates as aquafeed ingredients. Nevertheless, there are some potential chemical risks linked with insect consumption. In this study, we reared the teleost Danio rerio, used as an experimental model, with five experimental diets characterized by increasing levels (0%, 25%, 50%, 75%, and 100%) of full-fat Hermetia illucens (Hi) prepupae, substituting for fish meal (FM) and fish oil (FO). We investigated the presence of potentially toxic elements (PTEs) Cd, Pb, Ni, As, and Hg in larval (20 days), juvenile (2 months), and adult (6 months) fish. Quantitative determinations of Cd, Pb, Ni, and As were made with an atomic absorption spectrometer; the total mercury content was determined by a direct mercury analyzer. The substitution of FM and FO with Hermetia illucens meal led to a reduction in the content of some PTEs, such as Pb, As, and Ni, in fishfeed, leading to concentrations below the legal limit of undesirable substances in animal feed. By increasing the Hi meal dietary content, we observed in the Danio rerio specimens an increase in Cd, Pb, and Ni content and a reduction in As content for all life stages. Moreover, a general increase in the content of Cd, Pb, Hg, and Ni from larvae to juvenile was measured, while the shift of Danio rerio from the juvenile to the adult stage involved a significant increase in the content of Pb, Hg, and Ni. Larvae had a reduced ability to bioaccumulate metal(loid)s compared to juveniles and adults. In conclusion, the content of PTEs in Danio rerio is influenced both by the type of diet administered and by the life stage of the animal itself. This research demonstrates the possibility of using Hi prepupae as an aquafeed ingredient without exposing fish to a chemical risk and, in perspective, allows applying these eco-sustainable diets for the breeding of edible fish species, without endangering human healt

Synthesis and NLRP3-Inflammasome Inhibitory Activity of the Naturally Occurring Velutone F and of Its Non-Natural Regioisomeric Chalconoids

Plant-derived remedies rich in chalcone-based compounds have been known for centuries in the treatment of specific diseases, and nowadays, the fascinating chalcone framework is considered a useful and, above all, abundant natural chemotype. Velutone F, a new chalconoid from Millettia velutina, exhibits a potent effect as an NLRP3-inflammasome inhibitor; the search for new natural/non-natural lead compounds as NLRP3 inhibitors is a current topical subject in medicinal chemistry. The details of our work toward the synthesis of velutone F and the unknown non-natural regioisomers are herein reported. We used different synthetic strategies both for the construction of the distinctive benzofuran nucleus (BF) and for the key phenylpropenone system (PhP). Importantly, we have disclosed a facile entry to the velutone F via synthetic routes that can also be useful for preparing non-natural analogs, a prerequisite for extensive SAR studies on the new flavonoid class of NLRP3-inhibitors

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

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

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

Fistulae aquariae dal territorio di Lanuvio : note e aggiunte

Illuminati Anna. Fistulae aquariae dal territorio di Lanuvio : note e aggiunte. In: Epigrafia della produzione e della distribuzione. Actes de la VIIe Rencontre franco-italienne sur l'épigraphie du monde romain (Rome, 5-6 juin 1992) Rome : École Française de Rome, 1994. pp. 661-673. (Publications de l'École française de Rome, 193