Exploring Gunnera tinctoria: From Nutritional and Anti-Tumoral Properties to Phytosome Development Following Structural Arrangement Based on Molecular Docking

Gunnera tinctoria, an underexplored invasive plant found in Azores, Portugal, was studied regarding its nutritional, antioxidant, and antitumoral properties. Higher antioxidant activity was found in baby leaves, followed by adult leaves and inflorescences. A phenolic fraction of the plant was enriched using adsorbent resin column chromatography (Diaion^TM HP20LX, and Relite EXA90). Antitumoral effects were observed with the enriched fractions in breast (MCF-7) and pancreatic (AsPC-1) cancer cell lines, being more pronounced in the latter. To improve protection and membrane absorption rates of phenolic compounds, nano-phytosomes and cholesterol-conjugated phytosomes coated with natural polymers were loaded with the enriched fraction. The particles were characterized, and their physiochemical properties were evaluated and compared. All samples presented anionic charge and nanometer size in relation to the inner layer and micrometer size regarding the external layers. In addition, the molecular arrangement of phenolics within both types of phytosomes were studied for the first time by molecular docking. Polarity and molecular size were key factors on the molecular arrangement of the lipid bilayer. In conclusion, G. tinctoria showed to be an interesting source of nutrients and phenolic compounds with anti-tumoral potential. Moreover, phytosome loading with these compounds can increase their stability and bioavailability having in view future applications.     

Synthesis of a Novel Class of Carbohydrate‐Containing Calix[4]resorcinarene Adopting an Asymmetrical Diamond Structure

A novel type of calixsugars, containing sugar moieties at the methine bridges of the calixarene is introduced. These calixsugars were prepared via a nonconvergent stepwise fragment condensation. Four new stereogenic centers were formed simultaneously, and only one diastereoisomer 5 was isolated. The condensation procedure is remarkably mild allowing for a large diversity of labile groups to be used. The solution structure of calixarene 5 with two D ‐glucose and two hexyl moieties was determined by NMR spectroscopy by means of NOEs and coupling constants for molecular dynamics (MD). Chemical shifts were used to validate the conformation with the least NOE and J violations. The structure of calixsugar 5 has the configuration rctc referring to one sugar residue (r=reference, c=cis, t=trans) and adopts a diamond conformation for the macrocyclic backbone with the two sugar moieties axial on opposite sides of the macrocyclic ring and the two hexyl groups on the same side.     

Electrochemical Real‐Time Mass Spectrometry (EC‐RTMS): Monitoring Electrochemical Reaction Products in Real Time

Methods that provide real‐time information are essential to resolve transients occurring at dynamic interfaces. Now a powerful method is presented that enables the time‐ and potential‐resolved characterization of liquid and gaseous products of electrochemical reactions shortly after their formation. To demonstrate its extraordinary potential, the electrochemical real time mass spectrometry (EC‐RTMS) approach is used to determine the products of the CO₂ reduction reaction (CO₂RR) during potential step or sweep experiments on pristine and in situ anodized copper. The enhanced formation of several C₂₊ products over C₁ products is tracked directly after copper anodization, with unprecedented temporal resolution. This new technique creates exciting new opportunities for resolving processes that occur at short timescales and eventually for guiding the design of new, robust catalysts for selective electrosynthesis under dynamic operation.     

Data-driven inverse optimization with imperfect information

In data-driven inverse optimization an observer aims to learn the preferences of an agent who solves a parametric optimization problem depending on an exogenous signal. Thus, the observer seeks the agent’s objective function that best explains a historical sequence of signals and corresponding optimal actions. We focus here on situations where the observer has imperfect information, that is, where the agent’s true objective function is not contained in the search space of candidate objectives, where the agent suffers from bounded rationality or implementation errors, or where the observed signal-response pairs are corrupted by measurement noise. We formalize this inverse optimization problem as a distributionally robust program minimizing the worst-case risk that the predicted decision (i.e., the decision implied by a particular candidate objective) differs from the agent’s actual response to a random signal. We show that our framework offers rigorous out-of-sample guarantees for different loss functions used to measure prediction errors and that the emerging inverse optimization problems can be exactly reformulated as (or safely approximated by) tractable convex programs when a new suboptimality loss function is used. We show through extensive numerical tests that the proposed distributionally robust approach to inverse optimization attains often better out-of-sample performance than the state-of-the-art approaches.     

Finitely additive,modular, and probability functions on pre-Semirings

In this paper, we define finitely additive, probability and modular functions over semiring-like structures. We investigate finitely additive functions with the help of complemented elements of a semiring. We also generalize some classical results in probability theory such as the law of total probability, Bayes’ theorem, the equality of parallel systems, and Poincaré’s inclusion-exclusion theorem. While we prove that modular functions over a couple of known semirings are almost constant, we show it is possible to define many different modular functions over some semirings such as bottleneck algebras and the semiring (Id(D),+,?), where D is a Dedekind domain.