Oxidative Stress Is Increased in Combined Oral Contraceptives Users and Is Positively Associated with High-Sensitivity C-Reactive Protein

Information concerning the mechanisms underlying oxidative stress and low-grade inflammation in young healthy women predisposing eventually to future diseases is scarce. We investigated the relationship of oxidative stress and high-sensitivity C-reactive protein (hsCRP) in fertile-age women by oral combined contraceptive (OC) use. Caucasian Italian healthy non-obese women (n = 290; 100 OC-users; 190 non-OC-users; mean age 23.2 ± 4.7 years) were analyzed. Blood hydroperoxides, as oxidative stress biomarkers, were assessed by Free Oxygen Radical Test (FORT). Serum hsCRP was determined by an ultra-sensitive method (hsCRP). Markedly elevated oxidative stress (≥400 FORT Units) was found in 77.0% of OC-users and 1.6% of non-OC-users, odds ratio (OR) = 209, 95% CI = 60.9–715.4, p < 0.001. Elevated hsCRP levels ≥ 2.0 mg/L, considered risky for cardiovascular diseases (CVDs), were found in 41.0% of OC-users and 9.5% of non-OC-users, OR = 6.6, 95%CI 3.5–12.4, p < 0.001. Hydroperoxides were strongly positively correlated to hsCRP in all women (r_s = 0.622, p < 0.001), in OC-users (r_s = 0.442, p < 0.001), and in non-OC-users (r_s = 0.426, p < 0.001). Women with hydroperoxides ≥ 400 FORT Units were eight times as likely to have hsCRP ≥ 2 mg/L. In non-OC-users only, hydroperoxides values were positively correlated with weight and body mass index, but negatively correlated with red meat, fish and chocolate consumption. Our research is the first finding a strong positive correlation of serum hydroperoxides with hsCRP, a marker of low-grade chronic inflammation, in young healthy women. Further research is needed to elucidate the potential role of these two biomarkers in OC-use associated side-effects, like thromboembolism and other CVDs.     

A Multimethodological Characterization of Cannabis sativa L. Inflorescences from Seven Dioecious Cultivars Grown in Italy: The Effect of Different Harvesting Stages

The chemical profile of the female inflorescence extracts from seven Cannabis sativa L. dioecious cultivars (Carmagnola, Fibranova, Eletta Campana, Antal, Tiborszallasi, Kompolti, and Tisza) was monitored at three harvesting stages (4, 14, and 30 September), reaching from the beginning of flowering to end of flowering/beginning of seed formation, using untargeted nuclear magnetic resonance (NMR) and targeted (ultra-high-performance liquid chromatography (UHPLC) and spectrophotometry) analyses. The tetrahydrocannabinol content was always below the legal limits (<0.6%) in all the analyzed samples. The NMR metabolite profile (sugars, organic acids, amino acids, and minor compounds) subjected to principal components analysis (PCA) showed a strong variability according to the harvesting stages: samples harvested in stage I were characterized by a high content of sucrose and myo-inositol, whereas the ones harvested in stage II showed high levels of succinic acid, alanine, valine, isoleucine, phenylalanine, and threonine. Samples harvested in stage III were characterized by high levels of glucose, fructose, choline, trigonelline, malic acid, formic acid, and some amino acids. The ratio between chlorophylls and carotenoids content indicated that all plants grew up exposed to the sun, the Eletta Campana cultivar having the highest pigment amount. Tiborszallasi cultivar showed the highest polyphenol content. The highest antioxidant activity was generally observed in stage II. All these results suggested that the Cannabis sativa L. inflorescences of each analyzed dioecious hemp cultivar presented a peculiar chemical profile affected by the harvesting stage. This information could be useful for producers and industries to harvest inflorescences in the appropriate stage to obtain samples with a peculiar chemical profile suitable for proper applications.     

Mean-Field Pontryagin Maximum Principle

This paper provides a characterization of the optimal average cost function, when the long-run (risk-sensitive) average cost criterion is used. The Markov control model has a denumerable state space with finite set of actions, and the characterization presented is given in terms of a system of local Poisson equations, which gives as a by-product the existence of an optimal stationary policy.     

Experimental synchronization of single-transistor-based chaotic circuits

This work deals with nonautonomous chaotic circuits and, in particular, with the experimental characterization of the synchronization properties of two simple nonautonomous circuits. Two single-transistor chaotic circuits, which are among the simplest chaotic oscillators, are investigated. We studied synchronization of these circuits and found that the most appropriate technique to synchronize two single-transistor chaotic circuits is that based on the design of an inverse circuit.     

Sequential multiphoton absorption enhancement induced by zinc complexation in functionalized distyrylbenzene analogs

Functionalized distyrylbenzene analogs and , bearing a tris-(2-pyridylmethyl)amine-based receptor for Zn(2+), were synthesized by a Horner-Emmons-Wittig coupling reaction. It has been found that Zn(2+) complexation induces changes in the linear absorption spectrum that enhance a nonlinear sequential two-photon absorption of nanosecond pulses at 532 nm. This absorption was also found to depend on the nature of the substituent at the side benzene ring of the styrylbenzene structure.     

Berberine Derivatives as Pseudomonas aeruginosa MexXY-OprM Inhibitors: Activity and In Silico Insights

The natural alkaloid berberine has been demonstrated to inhibit the Pseudomonas aeruginosa multidrug efflux system MexXY-OprM, which is responsible for tobramycin extrusion by binding the inner membrane transporter MexY. To find a structure with improved inhibitory activity, we compared by molecular dynamics investigations the binding affinity of berberine and three aromatic substituents towards the three polymorphic sequences of MexY found in P. aeruginosa (PAO1, PA7, and PA14). The synergy of the combinations of berberine or berberine derivatives/tobramycin against the same strains was then evaluated by checkerboard and time-kill assays. The in silico analysis evidenced different binding modes depending on both the structure of the berberine derivative and the specific MexY polymorphism. In vitro assays showed an evident MIC reduction (32-fold and 16-fold, respectively) and a 2–3 log greater killing effect after 2 h of exposure to the combinations of 13-(2-methylbenzyl)- and 13-(4-methylbenzyl)-berberine with tobramycin against the tobramycin-resistant strain PA7, a milder synergy (a 4-fold MIC reduction) against PAO1 and PA14, and no synergy against the ΔmexXY strain K1525, confirming the MexY-specific binding and the computational results. These berberine derivatives could thus be considered new hit compounds to select more effective berberine substitutions and their common path of interaction with MexY as the starting point for the rational design of novel MexXY-OprM inhibitors.     

Fast data-driven model reduction for nonlinear dynamical systems

We present a fast method for nonlinear data-driven model reduction of dynamical systems onto their slowest nonresonant spectral submanifolds (SSMs). While the recently proposed reduced-order modeling method SSMLearn uses implicit optimization to fit a spectral submanifold to data and reduce the dynamics to a normal form, here, we reformulate these tasks as explicit problems under certain simplifying assumptions. In addition, we provide a novel method for timelag selection when delay-embedding signals from multimodal systems. We show that our alternative approach to data-driven SSM construction yields accurate and sparse rigorous models for essentially nonlinear (or non-linearizable) dynamics on both numerical and experimental datasets. Aside from a major reduction in complexity, our new method allows an increase in the training data dimensionality by several orders of magnitude. This promises to extend data-driven, SSM-based modeling to problems with hundreds of thousands of degrees of freedom.

     

Ab Initio Study of Fine and Hyperfine Interactions in Triplet POH

Phosphorous-containing molecules have a great relevance in prebiotic chemistry in view of the fact that phosphorous is a fundamental constituent of biomolecules, such as RNA, DNA, and ATP. Its biogenic importance has led astrochemists to investigate the possibility that P-bearing species could have formed in the interstellar medium (ISM) and subsequently been delivered to early Earth by rocky bodies. However, only two P-bearing molecules have been detected so far in the ISM, with the chemistry of interstellar phosphorous remaining poorly understood. Here, in order to shed further light on P-carriers in space, we report a theoretical spectroscopic characterisation of the rotational spectrum of POH in its 3A″ ground electronic state. State-of-the-art coupled-cluster schemes have been employed to derive rotational constants, centrifugal distortion terms, and most of the fine and hyperfine interaction parameters, while the electron spin–spin dipolar coupling has been investigated using the multi-configuration self-consistent-field method. The computed spectroscopic parameters have been used to simulate the appearance of triplet POH rotational and ro-vibrational spectra in different conditions, from cold to warm environments, either in gas-phase experiments or in molecular clouds. Finally, we point out that the predicted hyperfine structures represent a key pattern for the recognition of POH in laboratory and interstellar spectra.     

Effects of Vaccination Efficacy on Wealth Distribution in Kinetic Epidemic Models

The spread of the COVID-19 pandemic has highlighted the close link between economics and health in the context of emergency management. A widespread vaccination campaign is considered the main tool to contain the economic consequences. This paper will focus, at the level of wealth distribution modeling, on the economic improvements induced by the vaccination campaign in terms of its effectiveness rate. The economic trend during the pandemic is evaluated, resorting to a mathematical model joining a classical compartmental model including vaccinated individuals with a kinetic model of wealth distribution based on binary wealth exchanges. The interplay between wealth exchanges and the progress of the infectious disease is realized by assuming, on the one hand, that individuals in different compartments act differently in the economic process and, on the other hand, that the epidemic affects risk in economic transactions. Using the mathematical tools of kinetic theory, it is possible to identify the equilibrium states of the system and the formation of inequalities due to the pandemic in the wealth distribution of the population. Numerical experiments highlight the importance of the vaccination campaign and its positive effects in reducing economic inequalities in the multi-agent society.